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There is accumulating evidence that prior knowledge about expectations plays an important role in perception . The Bayesian framework is the standard computational approach to explain how prior knowledge about the distribution of expected stimuli is incorporated with noisy observations in order to improve performance . However , it is unclear what information about the prior distribution is acquired by the perceptual system over short periods of time and how this information is utilized in the process of perceptual decision making . Here we address this question using a simple two-tone discrimination task . We find that the “contraction bias” , in which small magnitudes are overestimated and large magnitudes are underestimated , dominates the pattern of responses of human participants . This contraction bias is consistent with the Bayesian hypothesis in which the true prior information is available to the decision-maker . However , a trial-by-trial analysis of the pattern of responses reveals that the contribution of most recent trials to performance is overweighted compared with the predictions of a standard Bayesian model . Moreover , we study participants' performance in a-typical distributions of stimuli and demonstrate substantial deviations from the ideal Bayesian detector , suggesting that the brain utilizes a heuristic approximation of the Bayesian inference . We propose a biologically plausible model , in which decision in the two-tone discrimination task is based on a comparison between the second tone and an exponentially-decaying average of the first tone and past tones . We show that this model accounts for both the contraction bias and the deviations from the ideal Bayesian detector hypothesis . These findings demonstrate the power of Bayesian-like heuristics in the brain , as well as their limitations in their failure to fully adapt to novel environments .
Perception is a complex cognitive process , in which noisy signals are extracted from the environment and interpreted . It is generally believed that perceptual resolution is limited by internal noise that constrains our ability to differentiate physically similar stimuli . The magnitude of this internal noise is typically estimated using the 2-alternative forced choice ( 2AFC ) paradigm , which was introduced to eliminate participants' perceptual and response biases [1] , [2] . In this paradigm , a participant is presented with two temporally-separated stimuli that differ along a physical dimension and is instructed to compare them . The common assumption is that the probability of a correct response is determined by the physical difference between the two stimuli , relative to the level of internal noise . Performance is typically characterized by the threshold of discrimination , referred to as the Just Noticeable Difference ( JND ) . Thus , the JND is a measure of the level of internal noise such that the higher the JND , the higher the inferred internal noise . However , the idea that there is a one-to-one correspondence between the JND and the internal noise is inconsistent with theoretical considerations which postulate that participants' performance can be improved by taking into account expectations about the stimuli in the process of perception or decision-making . If the internal representation of a stimulus was uncertain , the prior expectations should bias the participant against unlikely stimuli . The larger the uncertainty , the larger the contribution of these prior expectations should be . The Bayesian theory of inference describes how expectations regarding the probability distribution of stimuli should be combined with the noisy representations of these stimuli in order to optimize performance [3] . In fact , expectations , formalized as prior distribution of stimuli used in the experiment , have been shown to bias participants' responses in a way that is consistent with the Bayesian framework ( reviewed in [4] ) . In particular , responses in the 2AFC paradigm have been shown to be biased by prior expectations: when the magnitudes of the two stimuli are small relative to the distribution of stimuli used in the experiment , participants tend to respond that the 1st stimulus was larger , whereas they tend to respond that the 2nd stimulus was larger when the magnitudes of the two stimuli are relatively large [5]–[7] . In a previous study we have shown that this bias , known as the “contraction bias” , can be understood in the Bayesian framework: following the presentation of the two stimuli , the participant combines her noisy representations of the two stimuli with the prior distribution of the stimuli to form two posterior distributions . Rather than comparing the two noisy representations of the stimuli , the participant is assumed to compare the two posteriors in order to maximize the probability of a correct response . The contribution of the prior distribution to the two posteriors is not equal . The larger the level of noise in the representation of the stimulus , the larger is the contribution of the prior distribution to the posterior . The level of noise in the representation of the magnitude of the 1st stimulus is larger than the level of noise in the representation of the magnitude of the 2nd stimulus because of the noise associated with the encoding and maintenance of the 1st stimulus in memory [8] , [9] . As a result , the posterior distribution of the 1st stimulus is biased more by the prior distribution than the posterior distribution of the 2nd stimulus . If the prior distribution is unimodal , both posteriors are contracted towards the median of the prior distribution . Because the posterior of the 1st stimulus is contracted more than the posterior of the 2nd stimulus , participants' responses are biased towards overestimating the 1st stimulus when it is relatively small and underestimating it when it is relatively large [7] . One limitation of the Bayesian model is that it relies heavily on the assumption that the prior distribution of stimuli is known to the observer . While this assumption may be plausible in very long experiments comprising a large number of trials ( e . g . thousands in [10] ) or in experiments utilizing natural tasks ( e . g . , reading , [11] ) , it is unclear how Bayesian inference can take place if participants have less experience in the task . In this paper we study participants' pattern of responses in a 2AFC tone discrimination task in relatively short experiments consisting of tens of trials . We report a substantial contraction bias that persists even when it hampers performance due to a-typical statistics . We show that participants' pattern of behavior is consistent with an “implicit memory” model , in which the representation of previous stimuli is a single scalar that continuously updates with examples . Thus , this model can be viewed as a simple implementation of the Bayesian model that provides a better account of participants' perceptual decision making .
We measured the performance of our participants in the random 2AFC paradigm ( Materials and Methods , Fig . 1 ) , in which subjects compared the frequencies of two sequentially presented tones drawn from a broad frequency range . Averaged across the population of participants , the JND was 13 . 6%±0 . 7% ( SEM ) , which is higher than typically reported in the literature ( [12] , [13] ) . The relatively high value of the JND , which is likely to result from the lack of experience of the participants and the fact that no reference was used , is comparable with previous studies using the random frequency paradigm , with short stimuli and untrained participants [14] , [15] . As predicted by the contraction bias , the JND did not capture the full pattern of participants' responses . This is depicted in Fig . 2A . The coordinates of each dot in Fig . 2A correspond to the frequencies of the 1st and 2nd tones in a trial , referred to as and . Blue and red dots denote trials , in which the participant's response was correct and incorrect , respectively . The closer the dots are to the diagonal , the smaller is the difference in the frequencies of the two tones . Therefore naively , one would expect that the probability of a trial to be incorrect ( red dot ) would be highest near the diagonal . Moreover , if the probability of a correct response as a function of is symmetrical around 0 , as implicitly assumed when measuring the JND , then the pattern of red and blue dots is expected to be symmetrical around the diagonal . In contrast , we found that the pattern of incorrect responses is highly non-symmetrical . Participants tended to err more when both frequencies were high and and when both frequencies were low and . To quantify this asymmetry , we considered separately two regions: the Bias+ region corresponds to trials in two sections of this plane ( yellow in Fig . 2A ) : in the first section are trials in which the frequencies of both stimuli are above the median ( 1000 Hz ) and the frequency of the 1st tone is lower than that of the 2nd tone . In the second section are trials in which the frequencies of both stimuli are below the median frequency and the frequency of the 1st tone is higher than that of the 2nd tone . Similarly , The Bias− region ( gray in Fig . 2A ) corresponded to trials in which the frequencies of both stimuli are above the median ( 1000 Hz ) and the frequency of the 1st tone is higher than that of the 2nd tone and trials in which the frequencies of both stimuli are below the median frequency and the frequency of the 1st tone is lower than that of the 2nd tone . Participants' rate of success differed greatly between the Bias+ and Bias− regions . Participants were typically successful when either the two tones were low ( <1000 Hz ) and the 2nd tone was lower ( lower left yellow region , 88 . 2%±0 . 5% correct responses , mean ± SEM ) or when the two tones were high ( >1000 Hz ) and the 2nd tone was higher ( upper yellow region , 88 . 4%±0 . 6% correct responses ) . On the other hand , performance was relatively poor either when the two tones were low and the 1st tone was lower ( lower left gray region , 63 . 2%±0 . 8% correct responses ) or when the two tones were high and the 1st tone was higher ( upper gray region , 61 . 8%±0 . 8% correct responses ) . These effects were highly significant in each of the two quadrants ( p<10−6 , Monte Carlo Permutation test ) . The differential level of proficiency in the yellow and gray regions indicates a substantial contraction bias , in line with that bias described in previous studies [6] , [7]: when the frequency of the 1st tone was relatively low , participants tended to overestimate it ( leading to successful performance when the 1st tone was higher ) . The opposite was true when the frequency of the 1st tone was relatively high ( leading to successful performance when the 1st tone was lower ) . The differential level of proficiency in the yellow and gray regions is evident not only in the response pattern of the population of participants but also in the response pattern in individual blocks ( Fig . S1A–C ) . Moreover , it was evident for all levels of proficiency in the task ( Fig . S1D ) . To further illustrate the contraction bias , we constructed a two-dimensional histogram of participants' performance by binning the space of Fig . 2A and computing the fraction of correct responses in each bin ( Fig . 2B , grayscale ) . The non-symmetrical distribution of the shades of gray of the squares around the diagonal reflects the contraction bias . Note in particular the two squares denoted by arrows . Despite the fact that they were of equal ‘objective’ difficulty ( the absolute difference in frequencies was the same ) , the performance in the bottom right square region was almost perfect ( 92 . 2% correct responses; n = 324 ) , whereas it was almost at chance level in the top left square region ( 50 . 8% correct responses; n = 323; p<10−33 , Fisher's exact test ) . It should be noted that the bias in participants' response cannot be accounted for by a general preference in favor of one of the alternative answers , because the bias is opposite in the low and high frequencies . The non-symmetrical performance around the diagonal ( Fig . 2 ) is not captured by a single performance measure , the JND . This has motivated us to consider a measure of performance that captures some of this asymmetry . To that goal , we computed two separate JNDs for each participant ( see Materials and Methods ) : one for the trials in the regions in which the contraction bias augments behavior ( Bias+ , yellow ) and the other for the regions in which the contraction bias impairs behavior ( Bias− , gray ) . These JNDs differed by more than 6 fold ( the medians of JNDs across the population were 4 . 1% , and 27 . 0% for the Bias+ and Bias− regions , respectively; p<10−5 , Monte Carlo Permutation test ) . In fact , as depicted in Fig . S2 in the Supporting Information section , a participant's proficiency on a trial depended more on the contraction bias ( i . e . Bias+ versus Bias− regions ) than on the participant's overall proficiency ( overall low versus high JND ) . These results demonstrate the substantial contribution of this bias to behavior . In a previous study we have shown that the contraction bias in a visual discrimination task is consistent with a model of an ideal detector that utilizes Bayes' rule to incorporate the prior distribution with the sensed stimuli in order to optimize performance [7] . In agreement with that study , such a Bayesian model , with 2 free parameters that correspond to the noise in the internal representation of each of the two stimuli , can qualitatively account for the observed contraction in the two-tone discrimination task ( see Fig . S3 in the Supporting Information section ) . However , it should be noted that the Bayesian model relies on the assumption that the prior distribution of stimuli is known to the observer , which seems unreasonable in our experiment , which consisted of merely tens of trials . Therefore , it is not clear how the history of trials experienced by the participants in the experiment contributes to the bias . To address this question , we considered the contribution of individual trials to the bias . Because the statistics of stimuli in our experiment are stationary , all past trials are equally informative about the prior distribution . Therefore , normative considerations that incorporate an assumption of stationarity imply that the effect of past trials on participants' choices will be independent of the number of trials elapsed between these trials and the choice . By contrast , previous studies have reported that participants' responses are influenced to a greater degree by recent stimuli , which is known as the recency effect [16]–[21] . In addition , the activity of neurons in the primary auditory cortex has been shown to contain information about both current and previous stimuli [22] . To test for recency in our dataset , we fitted a linear non-linear model that relates the response in each trial to a linear combination of present and past stimuli according to the following equation: ( 1 ) where is the probability that the model would report that the frequency of the 1st tone was higher than that of the 2nd tone in trial ; is the normal cumulative distribution function such that ; and are parameters , and are the frequencies of the 1st and 2nd tone , respectively , in trial and is the geometric mean of the frequencies of all stimuli in the experiment until trial . To gain insights into the behavior of the model ( Eq . ( 1 ) ) we consider the simple case in which and . In this case , Eq . ( 1 ) becomes , which corresponds to a model participant that is indifferent to the history of the experiment and its choices depend solely on the ratio of the frequencies of the two tones and the internal noise . The value of denotes the level of internal noise of the model participant . If is very small , then independently of the frequencies of the stimuli , and , , and the model participant responds at random . In contrast , if is very large , then where is the Heaviside step function such that for and for . In other words , if is very large the model participant always answers correctly . The larger the value of , the smaller the JND of the model participant . The values of the parameters determine the contribution of past stimuli to perception , where the value of determines the contribution of the stimulus presented trials ago and the value of determines the contribution of the average frequency of past stimuli to perception . If all past stimuli contribute equally to perception , as expected from normative participants who assume that the distribution of stimuli is stationary then we expect and . In contrast , if the participant assumes that the statistics of the experiment is non-stationary then we expect the most recent trials to have a stronger effect on behavior , resulting in whose magnitude decreases as the value of increases . Assuming that , we analyzed the sequence of frequencies and decisions of our participants . We found the values of the parameters ( Fig . 3 , green ) , ( dark blue ) and ( black ) that minimize the mean square error ( MSE ) , the mean square distance of the vector of probabilities , from the vector of choices , such that if the participant responded that the frequency of the 1st tone was higher than the frequency of the 2nd tone in trial and otherwise . Note that the values of and in Fig . 3 are larger than the values of all other coefficients , . This result reflects the simple fact that the tones presented in a trial influence the decision in that trial more than tones presented in previous trials . The recency effect is manifested in the non-zero coefficients of ( see Materials and Methods ) . As depicted in Fig . 3 , the contribution of past trials to choice diminishes within several trials . This result is consistent with other findings of rapid perceptual learning [23] , [24] ( but see also [25] ) and demonstrates that at least some aspects of the prior distribution are estimated using a small number of the most recent trials . It should also be noted that the contribution of past stimuli to decision is dominated by past values of and not past values of ( Fig . 3 . See also Materials and Methods ) . The recency effect described in the previous section is difficult to reconcile with a Bayesian inference model that takes into account the stationary statistics of the experiment . This finding has motivated us to consider the possibility that the contraction bias described in Fig . 2 emerges from simpler cognitive processes that do not require an explicit representation of the prior distribution . In this section we present a simple model that accounts for the contraction bias and the recency effect , which does not explicitly keep track of the prior distribution of stimuli presented in the experiment . In our model , the memory trace of past stimuli is a single scalar ( rather than the full prior distribution ) . In response to the presentation of , the participant updates the value of such that is a linear combination of the past value of with the present stimulus , corrupted by sensory and encoding noise . Formally , the value of in trial , is given by ( 2 ) where is the weight given to the memory and is the noise associated with the encoding of . We assume that this noise is Gaussian with variance and is uncorrelated across trials: , where is the Kronecker delta function , if and if . A decision in a trial in this model depends on the relative values of and . If , the model responds that “” . Otherwise it responds that “” . In this model we assume that the noise is restricted to the representation of . The reason for ignoring noise in the representation of is that noise in is mathematically equivalent to a larger magnitude noise in when considering decision in a given trial . It is easy to show that in this model , is an exponentially weighted sum of the current and past stimuli and their respective encoding noises: ( 3 ) Note that in this model past values of do not contribute to behavior . This reflects the dominance of past values of in Fig . 3 ( see also Materials and Methods ) . It should also be noted that in this model , the contribution of past stimuli to decision ( which plays the role of the prior distribution in the Bayesian model ) is encoded using the same variable as the encoding of . Therefore , the model does not require any form of separate representation of the long term memory of past trials . The implicit-memory model is characterized by two parameters that denote the level of noise , and the extent to which the history of the experiment affects perception , . Fig . 4 depicts the results of a simulation of a population of implicit memory models , each with the parameters and best fitting a single block in our dataset ( see Materials and Methods ) . As shown in Figs . 4A and 4B , the model results in a contraction bias , which is comparable to the experimentally observed ( compare Figs . 4A and 4B to Figs 2A and 2B , respectively ) . A quantitative analysis reveals that the goodness-of-fit of the Implicit memory model is comparable to that of the Bayesian model ( Fig . S4 ) . However , in contrast to be Bayesian model that assumes a constant prior , the contribution of very recent trials to performance ( Eq . ( 1 ) ) in the Implicit memory model is similar to that of our participants ( compare Fig . 4C to Fig . 3 ) . The contraction bias in Fig . 2 can be justified using optimality considerations , in which prior knowledge is incorporated with the observations in order to maximize performance ( Fig . S3 ) . Would contraction bias persist in an experiment in which it impairs performance due to the dependencies between the frequency distribution of the two tones ? In order to address this question , we conducted a second experiment ( Experiment 2 in the Materials and Methods ) , in which we manipulated the correlations between the frequencies of the two tones such that in some blocks the contraction bias is beneficial to performance whereas in others it is detrimental . Contraction bias is beneficial in the Bias+ region ( yellow in Figs . 2A and 4A ) and is detrimental in the Bias− region ( gray in Figs . 2A and 4A ) . Therefore , in this experiment we manipulated the fraction of trials in the Bias+ and Bias− regions in different blocks . In one condition , the two tones were chosen such that the 2nd tone was typically higher than the 1st when the two frequencies were relatively high , and the 2nd tone was typically lower than the 1st when the two frequencies were relatively low . We refer to this condition as the ‘Bias+ condition’ , because there were many more trials in the Bias+ region than in the Bias− region ( 11 , 233 vs . 1172 ) . In the other condition , the two tones were chosen such that the 1st tone was typically higher than the 2nd when the frequencies of the two tones were relatively high and the 1st tone was typically lower than the 2nd when the frequencies of the two tones were relatively low . This ‘Bias− condition‘ was comprised of substantially more trials in the Bias− region than in the Bias+ region ( 8111 vs . 952 ) . Figs . 5A and 5B depict the distribution of trials and correct and incorrect responses in the Bias+ and Bias− conditions , respectively . Similar to the pattern of responses in the first experiment ( Fig . 2A ) , participants were more likely to be correct in the Bias+ regions , compared to the Bias− regions . This was true both for the Bias+ condition ( 82 . 0%±0 . 4% correct responses vs . 44 . 5%±1 . 6% correct responses , p<10−126 Fisher exact test ) and the Bias− condition ( 88 . 0%±1 . 2% correct responses vs . 72 . 6%±0 . 6% correct responses , p<10−21 Fisher exact test ) . The JNDs were significantly different in the two conditions: the mean JND in the Bias+ condition was only 4 . 3%±0 . 6% , compared to 14 . 1%±1 . 1% in Bias− condition ( Fig . 5C , black , p<10−25 , Wilcoxon rank sum test ) . In the framework of the Bayesian model , the difference in proficiency between the two conditions is surprising because given the joint distribution , the detection problem in the two conditions is symmetric . However , our results indicate that our participants did not utilize these probabilities when making a decision about the relative frequencies in this task . To test the ability of the implicit-memory model to account for the results of the second experiment , we fitted the parameters of the model ( and ) to the experimental data of the Bias+ condition . We then simulated each of the model participants in both the Bias+ and Bias− conditions . The resulting JNDs ( mean ± SEM 3 . 7%±0 . 5% and 13 . 3%±0 . 9% for the Bias+ and Bias− conditions , respectively , purple in Fig . 5C ) are not statistically different from to the experimentally measured JNDs ( 4 . 3%±0 . 6% and 14 . 1%±1 . 6%; p = 0 . 78 and p = 0 . 85 , respectively , Wilcoxon rank sum test ) , suggesting that the participants did not utilize the differential statistics of the two tones in the two conditions . For example , they did not decrease the weights of recent trials even when their performance was consequently hampered . In fact , adapting to the Bias− condition simply by setting the weight of the history-dependence parameter to 0 ( effectively eliminating the contribution of past stimuli to decision in the model ) would have improved their performance . To demonstrate this , we simulated the model participants in the Bias− condition while assuming that . The resultant JND was only 9 . 1%±0 . 7% , lower than the JND of the model participants when assuming the history-dependence parameter measured in the Bias+ condition .
In this work we showed that the contraction bias is a dominant determinant of participants' behavior in a 2AFC tone frequency discrimination task . Some aspects of this bias are consistent with the behavior of an ideal detector that utilizes the prior distribution to maximize performance . However , a substantial recency effect combined with a failure of the participants to utilize the joint distribution of the stimuli implies that this Bayesian-like computation is approximated using a much simpler algorithm , in which the prior distribution is not fully represented . What information does the cognitive system store about the prior distribution ? The full Bayesian model represents one extreme approach , in which it is assumed that the participant has full information about the joint distribution of the two stimuli . The standard way in which signal detection theory is applied to psychophysics represents the other extreme , in which the participant does not have ( or does not utilize ) any prior information about the identity of the stimuli ( but only about the probability of each response being correct [1] ) . The contraction bias in Fig . 2 demonstrates that participants have some information about the marginal probabilities . However , the strong recency effect ( Fig . 3 ) indicates that this marginal probability is constantly updated using a small number of most recent observations , even in stationary environments . In a normative framework , the recency effect , observed previously in various tasks [26] , [27] , implies that participants believe that the environment is highly volatile and as a result only the very recent history is informative about future stimuli . The results of experiment 2 ( Fig . 5 ) indicate that participants are either unable to compute the joint distribution or unable to utilize it , at least within a single experimental block of 80 trials . The implicit memory model can be viewed as a minimal modification of the standard approach of applying signal detection theory to perception in the direction of the full Bayesian model . Here , participants represent the prior distribution of the stimuli with a single scalar , which is an estimate of the mean of the marginal of the prior distribution . Nevertheless this implicit model captures many aspects of the behavioral results . Further studies are needed to determine whether , and to what extent other moments of the prior distributions are learned and utilized in the 2AFC discrimination task , especially under longer exposure to distribution statistics . Several studies have shown that the magnitude of the contribution of the prior distribution to perception on a given trial depends on the level of internal noise [10] , [28] . In particular in the framework of the 2AFC task , increasing the delay between the 1st and 2nd stimuli [29] , [30] or introducing a distracting task between them [7] enhances the contraction bias . These results are consistent with the Bayesian approach . How can these results be accounted for in the framework of the implicit memory model ? One possibility is to assume that the relative contribution of the prior in the simplified online rule of Eq . ( 2 ) is affected by perceptual noise . However , it should be noted that at least in one case , the level of noise was determined after the encoding of the 1st stimulus [7] . The dependence of on the level of noise can be accounted for in the framework of the implicit memory model if we assume that the computation of , which incorporates the prior knowledge with the response to the 1st stimulus , is carried out simultaneously by several neurons , or populations of neurons , which are characterized by different values of [22] , [31] , [32] . At the time of the decision , the magnitude of the noise determines which populations of neurons will be the most informative with respect to the 1st stimulus . If the level of noise is high , the populations of neurons that are more affected by past trials ( for whom the value of is large ) will dominate perception , resulting in a substantial contraction bias . Otherwise the populations that are less affected by past trials will dominate perception , resulting in a small contraction bias . Almost 40 years ago , Tversky and Kahneman characterized irrational decision making and reasoning and concluded that “people rely on a limited number of heuristic principles which reduce the complex tasks … to simpler judgmental operations . In general , these heuristics are quite useful , but sometimes they lead to severe and systematic errors” [33] . Our study extends these results to the domain of implicit perceptual judgments .
The research was approved by the department ethics committee , and all participants signed consent forms . 150 participants ( mean age 24±3 . 1 years ) engaged in a 2AFC high/low pure tone frequency discrimination task , after signing consent forms . 18 participants were excluded due to poor performance on a hearing test or because they did not complete the full schedule . Each participant performed 2 blocks of 80 trials . Each trial consisted of two 50 ms pure tones , with 10 ms linear rise time , and 10 ms linear fall time , separated by 950 ms . Immediately after the 2nd stimulus was played , the text ‘Which tone was higher ? ’ appeared on screen , and the participant responded by clicking one of two on-screen buttons using a computer mouse , with no time constraint . Visual feedback of a smiling face or a sad face was presented for 300 ms after correct and incorrect responses , respectively . After a pause of 700 ms the next trial began ( Fig . 1 ) . All stimuli were presented binaurally through Sennheiser HD-265 linear headphones using a TDT System III signal generator ( Tucker Davis Technologies ) controlled by in-house software in a sound attenuated room in the laboratory . Tone intensity was 65 dB SPL . Both the 1st and the 2nd frequencies in each trial were drawn from a wide distribution according to the following procedure: a frequency was drawn from a uniform distribution between 800 Hz and 1200 Hz . Another frequency , either or was drawn with a probability 0 . 5 , where was controlled by an adaptive 3-down 1-up staircase , in which the initial difference between the stimuli in each block was 20% and was bounded from below by 0 . 1% . The step size decreased every four reversals , from 4 . 5% to 2% to 1% to 0 . 5% to 0 . 1% . One of the two frequencies was randomly selected as and the other frequency was selected as . This schedule is expected to converge to a for which the participant answers correctly in 79 . 4% of the trials ( [34]; Fig . 2A , dots ) . Blocks that did not converge to at least 65% correct responses in the last 40 trials were excluded from the analysis ( 12 of 264 blocks ) . The JND was calculated as the average difference between the stimuli frequencies in the last 6 reversals . As a result of the adaptive staircase schedule , the ratios between the frequencies of the two stimuli tended to decrease in the first trials of the block . On average , after 15 trials this ratio stabilized and therefore the first 15 trials of each block were excluded from the analysis . To estimate the JND in a Bias+ or Bias− region of a block , we fitted a cumulative normal distribution function psychometric curve that relates the response in each trial to the difference in the logarithm of the 1st and 2nd frequencies: where is the normal cumulative distribution function , such that . The value of the parameter was chosen as to minimize the square difference between the vector predictions and the vector of choices such that on trials in which the participant responded “” and otherwise . Assuming that the cumulative normal distribution function reflects the probability of responding “” , the corresponding value of the JND is the difference in the natural logarithms of and such that the probability of a correct response is the asymptotic performance level in our staircase paradigm , 0 . 794 . Therefore , . To test for differences in performance between different regions , we used a Monte Carlo permutation test in which the identities of and in a trial were randomly shuffled . We used 106 permutations , and in all cases the experimentally observed differences were larger than the differences observed in all permutations , resulting in p<10−6 . To test for differences in the JNDs between different regions , we used a Monte Carlo permutation test in which the identities of and in a trial were randomly shuffled . We estimated the JND of these simulated results using the same process as described for the data , and estimated the median JND+ and median JND- for the whole population . We used 105 permutations and the experimentally observed difference was larger than the difference observed in all permutations , resulting in p<10−5 . In order to verify the contribution of the parameters for to the linear-non-linear model ( Eq . 1 ) , we compared several models using a cross validation test: the parameters of the different models were estimated using all blocks but one , and these parameters were used in order to compute the MSE for that block . The MSE of the model was computed by repeating this procedure for all blocks in the experiment and averaging the resultant MSE . We considered three models: ( 1 ) a naïve model with no history dependence: ; ( 2 ) a model with a global history term , ; ( 3 ) the full model with an explicit history dependence of three previous trials , and a global term , . The resultant MSEs are ; ; . We found that is significantly smaller than and ( and respectively , Wilcoxon signed rank test ) . In order to verify that the contribution of past trials is dominated by values of , we compared two additional models , using the same analysis as above: ( 4 ) a model in which the recent history is represented by only: ; ( 5 ) a model in which the recent history is represented by only: . The resultant MSEs are and . While is not statistically different from ( ) , is significantly higher ( ) indicating that the model with only coefficients corresponding to the contribution of is as predictive as the full model . Experiment 2 was similar to experiment 1 , except for the joint distribution of and : in each trial , a frequency was chosen such that the natural logarithm of , measured in Hz , was drawn from a normal distribution with mean 6 . 908 ( corresponding to 1000 Hz ) , and standard deviation 0 . 115 . In all trials , the mean of and ( in the logarithmic domain ) was . Another frequency , either or ( in the logarithmic domain ) was drawn with a probability 0 . 5 , where was controlled by an adaptive 3-down 1-up staircase schedule . In contrast to Experiment 1 , the order of frequencies was biased and depended on . In trials in which , was chosen to be larger than with a probability . In contrast , in trials in which , was chosen to be larger than with a probability . We studied two conditions: in one condition , which we refer to as “Bias+” , . In the second condition , referred to as “Bias−” , . 60 participants ( mean age 23 . 8±3 . 3 years ) that did not participate in experiment 1 performed 6 interleaved blocks of Bias+ and Bias− conditions , with the order counterbalanced across participants . Similar to experiment 1 , each block consisted of 80 trials . Rewriting Eq . ( 3 ) , where is a “signal” term that depends on previous trials and is a “noise” term . The probability of responding “” response is thus given by , where is the normal cumulative distribution function , and is the standard deviation of . Because we excluded the first 15 trials from our analysis , we assumed that . We fitted the pair to the remaining 65 trials of each block to minimize the square error between the predictions of the model and the actual responses , . | In this paper we study how history affects perception using an auditory delayed comparison task , in which human participants repeatedly compare the frequencies of two , temporally-separated pure tones . We demonstrate that the history of the experiment has a substantial effect on participants' performance: when both tones are high relative to past stimuli , people tend to report that the 2nd tone was higher , and when they are relatively low , they tend to report that the 1st tone was higher . Interestingly , only the most recent trials bias performance , which can be interpreted as if the participants assume that the statistics of stimuli in the experiment is highly volatile . Moreover , this bias persists even in settings , in which it is detrimental to performance . These results demonstrate the abilities , as well as limitations , of the cognitive system when incorporating expectations in perception . | [
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"perception"
] | 2012 | How Recent History Affects Perception: The Normative Approach and Its Heuristic Approximation |
Protection against virulent pathogens that cause acute , fatal disease is often hampered by development of microbial resistance to traditional chemotherapeutics . Further , most successful pathogens possess an array of immune evasion strategies to avoid detection and elimination by the host . Development of novel , immunomodulatory prophylaxes that target the host immune system , rather than the invading microbe , could serve as effective alternatives to traditional chemotherapies . Here we describe the development and mechanism of a novel pan-anti-bacterial prophylaxis . Using cationic liposome non-coding DNA complexes ( CLDC ) mixed with crude F . tularensis membrane protein fractions ( MPF ) , we demonstrate control of virulent F . tularensis infection in vitro and in vivo . CLDC+MPF inhibited bacterial replication in primary human and murine macrophages in vitro . Control of infection in macrophages was mediated by both reactive nitrogen species ( RNS ) and reactive oxygen species ( ROS ) in mouse cells , and ROS in human cells . Importantly , mice treated with CLDC+MPF 3 days prior to challenge survived lethal intranasal infection with virulent F . tularensis . Similarly to in vitro observations , in vivo protection was dependent on the presence of RNS and ROS . Lastly , CLDC+MPF was also effective at controlling infections with Yersinia pestis , Burkholderia pseudomallei and Brucella abortus . Thus , CLDC+MPF represents a novel prophylaxis to protect against multiple , highly virulent pathogens .
Historically , control of bacterial infections has been dependent on administration of antibiotics . However , with many acute , lethal , bacterial infections , e . g . those mediated by Francisella tularensis , Yersinia pestis and Staphylococcus aureus , diagnosis and timely administration of appropriate antibiotics represents a significant hurdle in successful treatment of disease mediated by these pathogens . Further , mass administration of prophylactic antibiotics in an outbreak situation may result in the generation of antibiotic resistant strains , rendering this treatment ineffective for both ongoing infections and future outbreaks . Thus , there is a need for novel , broad spectrum , prophylaxis against highly pathogenic bacterial infections . F . tularensis is a Gram negative , facultative intracellular bacterium and the causative agent of Tularemia . F . tularensis is extremely infectious , capable of causing acute , lethal , disease following inhalation of as few as 10–15 bacteria [1] , [2] . Currently , there is no vaccine approved for use against F . tularensis . Although antibiotic therapy can successfully treat pneumonic Tularemia , therapy must be initiated within the first few days following the onset of symptoms when individuals are often unaware of the severity of their infection [3] . Furthermore , treatment with antibiotics can fail to adequately clear F . tularensis , resulting in recrudescence of infection once antibiotic therapy ends [4] , [5] , [6] . A number of studies have described development of novel anti-microbials that target the host immune response rather than the invading pathogen [7] , [8] , [9] . These immunotherapeutics target host pathways which either directly activate effector cells or relieve pathogen induced suppression of host killing mechanisms , resulting in control and elimination of a wide variety of microorganisms . In the case of intracellular pathogens such as F . tularensis , targeting host effector mechanisms is appealing since some antibiotics preferred for treatment of Tularemia , e . g . gentamicin , poorly permeate the host cell and therefore fail to reach the targeted organism . Activation of host effector cells capable of killing intracellular pathogens with novel immunotherapeutics or prophylaxes represents a viable alternative , or supplement , to exiting chemotherapy . In this report we describe a novel anti-microbial comprised of cationic liposome DNA complexes ( CLDC ) and crude membrane protein fraction ( MPF ) derived from attenuated F . tularensis strain LVS . CLDC+MPF effectively controlled in vivo and in vitro infections of virulent F . tularensis strain SchuS4 in mouse and human cells , respectively . The combined delivery of CLDC and MPF was critical for mediating this protection , since treatment with CLDC or MPF alone failed to attenuate F . tularensis replication and pathogenicity . The dramatic control of F . tularensis infection mediated by CLDC+MPF was dependent on stimulation of both reactive oxygen and nitrogen species ( ROS and RNS , respectively ) in vivo and in vitro . Finally , we demonstrate that CLDC+MPF was also an effective antimicrobial against three other important bacteria , Burkholderia pseudomallei , Yersinia pestis and Brucella abortus . Thus , data presented herein represents an important step toward development of novel , efficacious , broad spectrum , antimicrobial therapy directed against highly pathogenic microbes .
To establish the anti-microbial potential of CLDC+MPF we first examined the effect of this compound on the infection and replication of SchuS4 in mouse and human macrophages . Cells were treated with either 5% dextrose water ( D5W;untreated ) , CLDC , MPF or CLDC+MPF approximately 18 h prior to SchuS4 infection . At the indicated time points , viable intracellular bacteria were enumerated . Macrophages treated with MPF or CLDC alone failed to control SchuS4 replication ( Table 1 and 2 ) . Additionally , treatment of mouse macrophages with MPF or CLDC alone exacerbated SchuS4 replication in these cells ( Table 1 ) . In contrast to cells treated with the individual components or untreated controls , cells pre-treated with CLDC+MPF had significantly fewer intracellular bacteria ( Table 1 and 2 ) . It was possible that treatment with CLDC+MPF induced cell death which in turn resulted in smaller numbers of intracellular SchuS4 . However , staining by trypan blue revealed that , similar to untreated controls , greater than 90% of CLDC+MPF treated macrophages were viable at the time of infection ( Figure S1 ) . Thus , generalized cell death could not account for the reduction in bacterial loads following CLDC+MPF treatment . Together this data shows that while CLDC+MPF did not limit uptake of SchuS4 , it did control replication of the intracellular bacterium . Intracellular replication of SchuS4 in macrophages is dependent on their ability to escape the phagolysosome within the first hour of infection [10] . Thus , although CLDC+MPF did not appear to alter the initial uptake of SchuS4 by macrophages , it was possible that this mixture inhibited the ability of SchuS4 to escape the phagolysosome subsequently resulting in killing of the bacterium . Phagosomal escape by SchuS4 can be measured by microscopy by the loss of LAMP-1 colocalization with the bacterium following macrophage phagocytosis [10] . To assess the effect CLDC , MPF and CLDC+MPF had on SchuS4 phagosomal escape we next examined co-localization of SchuS4 with LAMP-1 in treated mouse and human macrophages 24 h after infection by microscopy . As described above , CLDC+MPF did not significantly alter the number of bacteria phagocytosed by either mouse or human macrophages compared to untreated controls ( Figure 1B and 2B , respectively ) . Further , CLDC+MPF treatment did not inhibit the ability of SchuS4 to escape into the cytosol of infected cells as evident by the absence of SchuS4 co-localization with LAMP-1 4 hours after infection in all treatment groups ( Figure 1A and 2A ) . In contrast , CLDC+MPF significantly reduced the number of infected human and mouse macrophages 24 h after infection ( Figures 1A , C and 2A , C , respectively ) . We also examined if CLDC+MPF mediated killing of SchuS4 by electron microscopy . As expected , in untreated cells SchuS4 was present as intact bacteria in the cytosol ( Figure S2 ) . In contrast , bacteria present in CLDC+MPF treated macrophages were largely degraded with few to no intact bacteria present in the cytosol ( Figure S2 ) . Following entry and escape into the host cytosol , SchuS4 undergoes a lag period of approximately 4 hours prior to initiation of replication . Replication in the primary infected cell then commences and continues over a 12–18 hour time period [11] . Thus , we next determined at what point after infection CLDC+MPF could restrict intracellular SchuS4 growth in macrophages , Cultures treated with CLDC+MPF 4 hours after infection had significantly fewer infected cells compared to untreated controls ( p<0 . 05 ) ( Figure S3 ) . In contrast , macrophages treated with CLDC+MPF 12 hours after SchuS4 infection failed to control bacterial replication compared to untreated controls ( Figure S3 ) . Together , these data suggested that in order for CLDC+MPF to exert its protective effects macrophages must be stimulated at time points prior to intracellular replication of SchuS4 . Stimulation of ROS and RNS in mammalian cells represents an important mechanism by which the host controls and eliminates bacterial growth , especially in the intracellular environment ( as reviewed , [12] ) . Furthermore , ROS and RNS have been implicated as important mediators for control of attenuated strains of F . tularensis [13] , [14] , [15] , [16] . Thus , we hypothesized that CLDC+MPF may be mediating control of SchuS4 infection in macrophages via induction of ROS and/or RNS . We first determined if MPF , CLDC , or CLDC+MPF induced expression of genes associated with oxidative stress . Mouse macrophages treated with CLDC+MPF had higher expression levels of genes associated with RNS ( nitric oxide synthetase 2 ) and ROS ( superoxide dismutase 2 , NADPH oxidase 1 ) compared to untreated controls ( Figure 3 ) . Induction of RNS and ROS related genes was highest when cells were treated with CLDC+MPF rather than CLDC or MPF alone ( Figure 3 ) . Similarly , treatment of human cells with CLDC+MPF resulted in increased expression of genes associated with generation of ROS , e . g . phox p47 , superoxide dismutase 2 , NADPH oxidase , and GTP cyclohydrolase , as well as RNS , e . g . and nitric oxide synthase 2A compared to untreated cells and cells treated with MPF alone ( Figure 3 ) . Interestingly , although CLDC alone failed to control SchuS4 infection in human macrophages , cells treated with this compound in the absence of MPF had greater gene transcription for three genes involved in generation of ROS , i . e . superoxide dismutase 2 , phox47 and GTP cyclohydrolase compared to cells treated with CLDC+MPF ( Figure 3 ) . We also compared induction of ROS and RNS related genes in cells treated with a known inducer of RNS , IFN-γ to CLDC+MPF . CLDC+MPF elicited higher gene transcription of nitric oxide synthetase ( nos2 ) , NADPH oxidase and superoxide dismutase ( sod2 ) in mouse cells and GTP cyclohydrolase , nitric oxide synthetase 3 ( nos3 ) , NADPH oxidase , phox 47 and sod2 in human cells than IFN-γ ( Figure S4 ) . Induction of both RNS and ROS is often dependent on the presence of IFN-γ , TNF-α , IFN-β and other pro-inflammatory cytokines . In correlation with the expression levels of RNS and ROS associated genes , mouse macrophages treated with CLDC+MPF secreted significantly higher concentrations of TNF-α compared to cells treated with CLDC or MPF alone ( Figure 4 ) . Addition of MPF to CLDC also increased secretion of IL-6 and IFN-β from mouse cells compared to cells treated with CLDC alone , however these differences were not significant ( Figure 4 ) . We also monitored production of cytokines from human cells treated with MPF , CLDC or CLDC+MPF . Although no IL-12p40 or IFN-β was detected in any cell culture supernatant , CLDC+MPF induced secretion of significantly higher concentrations of IL-6 from human macrophages compared to cells treated with CLDC alone ( Figure 4 ) . Human macrophages also produced significantly higher concentrations of TNF-α in response to CLDC and CLDC+MPF compared to cells treated with D5W or MPF ( Figure 4 ) . Thus , both CLDC and CLDC+MPF elicited production of cytokines associated with induction of RNS and ROS , and in some cases , the combination of CLDC+MPF resulted in higher concentrations of these cytokines . To determine if the induction ROS , RNS or both ROS and RNS by treatment of cells with CLDC+MPF contributed to control of SchuS4 infection , we first examined the ability of CLDC+MPF to limit SchuS4 replication 24 h after infection in macrophages obtained from mice deficient for both RNS and ROS . There was not a difference in the percentage of infected cells among untreated wild type and nos2/gp91−/− macrophages , suggesting that nos2/gp91−/− cells were not more susceptible to SchuS4 infection compared to wild type cells ( Figure 5A ) . As previously observed , wild type macrophages treated with CLDC+MPF had significantly fewer infected macrophages compared to untreated cells ( p<0 . 01 ) ( Figure 5A ) . In contrast , CLDC+MPF failed to control SchuS4 infection in macrophages from nos2/gp91−/− mice ( Figure 5A ) . Furthermore , pre-treatment of nos2/gp91−/− macrophages with CLDC+MPF resulted in significantly more infected macrophages 24 h after the onset of the experiment ( p<0 . 01 ) ( Figure 5A ) . Thus , CLDC+MPF mediated control of SchuS4 infection was at least partially dependent on ROS and RNS in mouse macrophages . To determine the contribution of RNS and ROS in CLDC+MPF mediated control of SchuS4 infection in wild type mouse macrophages , we conducted additional experiments using compounds that specifically interfere with either the generation of RNS ( L-NMMA ) or ROS ( NAC ) . IFN-γ has been shown to mediate killing of intracellular bacteria , including Francisella , following stimulation of both ROS and RNS ( 23 ) . Thus , macrophages pretreated with IFN-γ followed by exposure to L-NMMA or NAC served as positive controls for inhibition of ROS and RNS species . As expected , pretreatment of mouse and human macrophages with IFN-γ significantly reduced the number of cells infected with SchuS4 compared to untreated controls ( p<0 . 01 ) ( Figure 5B–E ) . The role of both RNS and ROS in IFN-γ mediated control of SchuS4 in mouse macrophages was confirmed by significant increases in SchuS4 infected cells following addition of either L-NMMA or NAC to IFN-γ treated cells ( p<0 . 05 ) ( Figure 5B–C ) . Similarly , addition of L-NMMA or NAC to CLDC+MPF pretreated mouse macrophages reversed the protective effect observed with this prophylaxis ( Figure 5B–C ) . Furthermore , addition of either L-NMMA or NAC to CLDC+MPF treated cells also appeared to increase the number of infected cells over untreated controls ( Figure 5B–C ) . Thus , in mouse macrophages CLDC+MPF mediated killing of SchuS4 was dependent on the generation of both RNS and ROS . In contrast to mouse cells , inhibition of RNS had little effect on the ability of CLDC+MPF to control SchuS4 infection in primary human macrophages ( Figure 5D ) . Rather , inhibition of ROS following addition of NAC significantly increased the number of infected cells among CLDC+MPF treated samples ( p<0 . 05 ) ( Figure 5E ) . This suggested that in human macrophages generation of ROS , rather than RNS , following treatment with CLDC+MPF was the primary mechanism for control of SchuS4 in human macrophages . Macrophages are one of the primary cells targeted by SchuS4 for replication in vivo [17] . The dramatic effect CLDC+MPF had on control of intracellular growth of SchuS4 in macrophages in vitro ( Figures 1–5 ) suggested that this compound may be an effective anti-microbial in vivo . Thus , we next assessed the ability of CLDC , MPF and CLDC+MPF to protect mice from pulmonary challenge with SchuS4 . Pretreatment of mice with CLDC alone failed to protect animals from SchuS4 related mortality , regardless of the route of time at which the CLDC was administered . In fact , administration of CLDC within 48 hours prior to infection by any route exacerbated disease , as indicated by an increase in the mean time to death of treated animals compared to untreated controls ( Table 3 ) . In contrast , administration of CLDC intravenously , intranasally or intraperitoneally 72 hours prior to infection modestly increased the mean time to death ( ∼0 . 2 days ) ( Table 3 ) . Thus , as observed among in vitro stimulated macrophages , CLDC did alone did not protect animals for death following SchuS4 infection . Administration of CLDC three days prior to challenge resulted in a minor increase in mean time to death . Furthermore , treatment of animals prior to that time point resulted in exacerbated disease . Thus , we chose to examine the protective efficacy of CLDC+MPF in animals treated three days prior to infection . The results of these studies are depicted in Table 4 . Administration of CLDC+MPF intranasally failed to protect or improve survival of SchuS4 infections . Twenty percent of animals treated with CLDC+MPF subcutaneously or intraperitoneally survived SchuS4 infection . Additionally , animals treated via these routes that succumbed to infection survived longer than untreated controls . Animals treated with CLDC+MPF intravenously had the greatest survival rate , with approximately 50% of these animals surviving SchuS4 infection ( Table 4 and Figure 6A ) . Intravenous injection of either CLDC or MPF failed to protect animals from succumbing to infection ( Table 4 ) . Furthermore , intravenous injection of CLDC+MPF 1 , 2 or 7 days prior to infection failed to protect animals against SchuS4 ( data not shown ) . Thus , in vivo protection against SchuS4 required CLDC and MPF delivered three days prior to infection . Previous studies have shown that LVS LPS can protect mice from lethal LVS infections [18] , [19] , [20] , [21] , [22] . MPF contains LVS LPS . Thus , we postulated that LVS LPS present in MPF may represent an important immunogen for conferring the protection observed in CLDC+MPF treated mice . To test this hypothesis , mice were injected intravenously with LPS purified from LVS alone or in combination with CLDC . Surprisingly , neither LVS LPS alone nor LVS LPS in CLDC protected mice from lethal SchuS4 infection ( Table 4 ) . However , LVS LPS in CLDC did increase the mean time to death by approximately 2 days compared to untreated controls ( Table 4 ) . This suggested that LVS LPS combined with CLDC was able to stimulate the host immune response for minimal control of SchuS4 infection . Although LPS from LVS and SchuS4 do not elicit strong production of pro-inflammatory cytokines , it was possible that there might be other differences in the immunostimulating potential of these two LPS molecules that would only be revealed in vivo [23] , [24] , [25] . Thus , we also compared protective efficacy of SchuS4 LPS to protect against SchuS4 infection . Similar to LVS LPS , mice treated with SchuS4 LPS were not protected from death ( Table 4 ) . However , inclusion of CLDC did modestly increase the mean time to death in SchuS4+CLDC treated animals ( Table 4 ) . Together , these data suggest that Francisella LPS was not the major component of MPF mediating protection against SchuS4 infection in CLDC+MPF treated animals . Given the importance of both ROS and RNS in CLDC+MPF mediated control of SchuS4 infection in mouse macrophages in vitro , we also assessed the role of these antimicrobial host components in vivo . Pretreatment of mice with CLDC+MPF protected significantly more wild type animals from SchuS4 compared to untreated controls ( p = 0 . 0027 ) ( Figure 6B ) . In contrast to the protection observed in wild type animals , CLDC+MPF did not significantly increase the number of surviving nos2/gp91−/− compared to untreated controls ( p = 0 . 3173 ) ( Figure 6B ) . Furthermore , untreated nos2/gp91−/− mice were not more susceptible to SchuS4 infection compared to untreated wild type mice . This suggested that the lack of protection observed in CLDC+MPF treated nos2/gp91−/− was not due to inherent lack of resistance to F . tularensis in these animals . Rather , our data suggests that in the absence of intact pathways for generation of ROS and RNS CLDC+MPF activates cells that render them more susceptible to infection . These results further underscore the importance of induction of ROS and RNS in F . tularensis infections . Together this data confirmed that protection mediated by CLDC+MPF was dependent on stimulation of pathways associated with oxidative stress in vivo . Previous experiments have shown that CLDC alone is an effective prophylaxis against B . pseudomallei and attenuated strains of Francisella [26] , [27] . However , CLDC alone failed to protect against virulent Francisella and Y . pestis ( [27] and CM Bosio , unpublished data ) . As shown above , compared to CLDC alone , CLDC+MPF provided superior protection against virulent Francisella ( Table 1 and 2; Figures 1 and 2 ) . Thus , it was possible that the combination of CLDC and antigen may also effectively control infections mediated by other , unrelated pathogens . Furthermore , the ability of CLDC or CLDC+MPF to control bacterial infections in human cells has not been examined . To assess the anti-bacterial capabilities of CLDC+MPF , we pretreated human macrophages with CLDC+MPF , infected them with B . pseudomallei , Y . pestis or B . abortus , and evaluated bacterial replication over time . As previously observed with CLDC alone in mouse cells , CLDC+MPF controlled both the number of B . pseudomallei infected human macrophages and replication of intracellular bacteria within 6 h of infection ( Figure 7 ) . Surprisingly , CLDC+MPF also reduced the number of cells infected with Y . pestis at 2 and 6 h after infection and B . abortus 24 h after infection ( Figure 7 ) . Furthermore , treatment of cells with CLDC+MPF inhibited the intracellular replication of both Y . pestis and B . abortus ( Figure 7 ) . Together this data suggests that , unlike CLDC alone , stimulation of cells with CLDC+MPF can aid in the control of several different , unrelated , virulent bacteria .
The discovery of antibiotics as broad spectrum chemotherapeutics for bacteria greatly enhanced our ability to fight off and control bacterial diseases . However , commiserate with the general use of antibiotics , bacteria have responded by developing resistance to these important and ubiquitous compounds . One strategy employed to enhance resistance against microbial pathogens is to directly stimulate the host immune response and allow natural , host mediated , killing mechanisms to control microbial infections . These novel immunotherapeutics could be used independently or in context of antibiotic therapy to aid in clearance of bacteria . In turn this would allow for a decrease the amount of time antibiotics should be administered , an increase in the time before antibiotics must be administered , and/or lower dosages of antibiotics required for complete clearance of the bacterium . Here we describe a novel , broad spectrum antimicrobial immunoprophylaxis consisting of cationic DNA liposome complexes ( CLDC ) and crude membrane preparations ( MPF ) derived from F . tularensis that effectively limited replication of virulent F . tularensis , B . pseudomallei , Y . pestis and B . abortus in human and mouse macrophages in vitro . Importantly , administration of CLDC+MPF prior to pulmonary infection with F . tularensis also contributed to survival in mice . The mechanism of protection mediated by CLDC+MPF was , in part , dependent on the induction of reactive oxygen and nitrogen species in vivo and in vitro . Previous reports have shown that either CpG oligodeoxynucleotides ( ODN ) or CLDC alone can protect against lethal infections with attenuated strains of F . tularensis , e . g . LVS [27] , [28] , [29] . However , neither of these therapeutics have been able to protect animals from death following SchuS4 infection [27] , [29] . We confirmed and extended these results by demonstrating that regardless of the route of time CLDC was administered prior to challenge , this reagent could not decrease the number of mortalities among SchuS4 infected mice . In fact , in our hands injection of CLDC 1 or 2 days prior to SchuS4 challenge exacerbated disease as indicated as a decrease in the mean time to death ( Table 3 ) . Our results do slightly differ from those reported by Troyer et al , but are closer in agreement with the report by Rozak et al in which administration of CpG ODN less than 24 hours prior to infection exacerbated disease [27] , [29] . In the experiments reported by Troyer et al . , addition of DNA to cationic liposomes was performed under standard laboratory conditions with no obvious means to monitor quality control . Further , there was no indication of endotoxin levels present in the preparations of DNA . Addition of other TLR agonists to cationic liposomes enhances their immunogenicity [30] . Thus , contaminating endotoxin could have increased and/or changed the inflammatory response in the Troyer study resulting in a different mean time to death . The CLDC used in the study presented herein were produced under strict GMP laboratory conditions and underwent a battery of quality control assays prior to use to insure consistency from lot to lot . Thus , it is possible that minor variations in CLDC preparations used in the Troyer study could account for the 1 . 4 day extension in mean time to death among SchuS4 infected mice . It is not clear why CLDC exacerbated infection in vitro and in vivo . One possibility is that activation of macrophages with CLDC increases their phagocytic capability without eliciting effective killing mechanisms . Indeed , immediately after infection CLDC treated cells had significantly more intracellular bacteria compared to untreated cells ( p<0 . 05 ) ( Table 2 ) . MPF alone also activates macrophages and increased uptake of SchuS4 . Thus , it is possible that the exacerbation of infection observed in macrophages treated with either CLDC or MPF alone may be a direct result of increased phagocytosis in the absence of effective killing . In contrast to exacerbation of infection in mice treated with CLDC alone , we observed a small increase in the mean time to death among animals treated with CLDC alone 3 days prior to infection ( Table 3 ) . Similarly , CpG has been noted to increase the mean time to death of SchuS4 infected mice by 1 day if delivered 2 days prior to infection [29] . This suggested CLDC and CpG alone could contribute toward controlling SchuS4 infection when delivered at the appropriate time before infection . CLDC does contain CpG ODN sequences . However , these sequences are not required for CLDC to exert protective effects against infections in vivo [7] . The induction of inflammatory responses by CLDC which do not contain CpG motifs may be attributed to cellular recognition of bacterial DNA . Although TLR9 represents an important receptor for recognition of CpG motifs present in bacterial DNA , it is not the only host receptor capable of detecting prokaryotic DNA . For example , DAI is a cytosolic receptor capable of detecting bacterial DNA that does not contain CpG motifs and can trigger immune responses in mammalian cells in a TLR9 independent manner [31] . Thus , the immunogenicity of CLDC cannot be completely attributed to the presence of CpG . One of the major components of MPF is LPS . LPS from LVS lacks properties typically associated with endotoxin , e . g . stimulation of pro-inflammatory cytokines ( 25 ) . However , injection of LVS LPS can protect animals from lethal LVS infections . Thus , we tested LPS from both LVS and SchuS4 for protective efficacy against pulmonary tularemia . Surprisingly , neither LPS preparation was able to protect animals from death following intranasal SchuS4 infection ( Table 4 ) . Administration of Francisella LPS in CLDC did modestly increase the mean time to death in SchuS4 infected animals , but these animals eventually succumbed to infection ( Table 4 ) . This suggested that Francisella LPS alone is not the bacterial antigen contributing to the protective effects of CLDC+MPF . Another bacterial ligand that may contribute to the protective efficacy of CLDC+MPF is peptidoglycan or one of its precursors , i . e . muramyl dipeptide ( MDP ) or tracheal cytotoxin ( TCT ) . Both MDP and TCT can contribute toward the induction of nitric oxide [32] , [33] , [34] , [35] , [36] . Interestingly , MDP typically requires cells to be primed with IFN-γ or other immunostimulants in order to induce nitric oxide [35] , [36] . We have not quantitated MDP or TCT present in our MPF preparations . However , it is tempting to speculate that either or both of these compounds may contribute to the protective efficacy of CLDC+MPF . In both the in vitro and in vivo models pre-stimulation of macrophages before replication of SchuS4 began was required for killing of bacteria . In vitro , cells stimulated with CLDC+MPF 12 h after infection failed to significantly control Francisella replication ( Figure S3 ) . Similarly , administration of CLDC+MPF less than three days prior to pulmonary challenge failed to protect animals from lethal disease ( CM Bosio , unpublished data ) . There are several explanations for this pre-stimulation requirement . First , the kinetics of SchuS4 intracellular replication on the level of individual cells following in vivo infection has not been defined . It is possible that following infection of macrophages in vivo SchuS4 does not undergo a lag phase prior to replication such as that observed among in vitro infected macrophages . Second , SchuS4 targets multiple cell types in vivo . In addition to macrophages , this bacterium also infects dendritic cells and epithelial cells at the outset of infection [37] , [38] . It is not known if CLDC+MPF activates dendritic cells and epithelial cells in the same manner we have observed in macrophages . Longer stimulation of these cells may be required for adequate priming of killing mechanisms in these and/or neighboring cells . The third possibility may be a requirement for activation of other host effector cells or molecules . It has been suggested that NK cells contribute to eradication of F . tularensis following pulmonary infections [39] . Interestingly , intravenous injection of CLDC results in accumulation of NK cells in the lungs which peaks three days after injection [40] . Data from our laboratory suggests that SchuS4 specific NK cells present in lungs of vaccinated mice are capable of controlling SchuS4 replication in this tissue ( CM Bosio and RV Anderson , unpublished data ) . Thus , injection of CLDC+MPF three days prior to infection may allow the accumulation of SchuS4 specific NK cells capable of restricting bacterial replication in the lungs . The requirement for pre-stimulation may also lie in the amount of time necessary for ROS and RNS to be activated . F . tularensis encodes genes that specifically interfere with production of reactive oxygen and nitrogen species [41] . In the absence of pre-activation , RNS and ROS generation in host macrophages is efficiently impeded by virulent F . tularensis [41] . Similarly , interference with induction of RNS and ROS as a mechanism to evade killing has also been reported for Y . pestis and B . pseudomallei [42] , [43] . Thus , generation of adequate RNS and ROS by hosts cells prior to infection or replication of bacteria if host cells would be required for optimal control of infections with these virulent bacteria . An additional explanation for the necessity of pre-stimulation of host cells lies in the mechanism by which RNS and ROS are generated . Reactive oxygen and nitrogen species are most effectively produced in response to several pro-inflammatory cytokines . For example , although neither TNF-α nor IFN-β can act alone to induce release of nitric oxide or hydrogen peroxide , these cytokines act synergistically with bacterial antigens to augment production of these two antimicrobial compounds [44] . Our data demonstrate that CLDC , and in some cases CLDC+MPF , induced significantly more TNF-α and IFN-β compared to untreated cells or cells exposed to MPF alone ( Figure 4 ) . Thus , it is possible that optimal stimulation of RNS and ROS was dependent on the generation of these , and perhaps other , proinflammatory cytokines which would require additional time for generation of ROS and RNS prior to infection . Another important observation made in the studies presented herein was that the putative roles for ROS and RNS for control of F . tularensis were dramatically different in mouse and human macrophages . As described above , CLDC+MPF mediated killing in mouse macrophages was dependent on the generation of ROS and RNS ( Figure 5A–C ) . This is in agreement with previous reports describing the contribution of these species for control of more attenuated strains of F . tularensis [15] , [41] , [45] . However , in human macrophages inhibition of RNS had no effect on the antibacterial activity mediated by CLDC+MPF on F . tularensis ( Figure 5D and E ) . Rather , generation of ROS was essential for CLDC+MPF mediated killing of F . tularensis . In the past it was commonly believed that human cells could not produce RNS . Thus , one might assume that the dependency on ROS for CLDC+MPF mediated killing in human cells was due to an inherent inability of these macrophages to generate RNS . Indeed , soon after the description of cytokine induced nitric oxide in mouse cells , investigators attempted to reproduce the phenomenon in human macrophages . However , early studies in human cells did not recapitulate the potent nitric oxide response observed in mouse macrophages [46] . This led to the hypothesis that human cells did not express the product responsible for cytokine induced nitric oxide , iNOS . Since those early studies there have been a number of reports demonstrating the presence and function of iNOS in human cells [47] . We now understand that the inability of human macrophages to produce nitric oxide in response to cytokines alone was due to the nature of the cell type ( as reviewed , [48] ) . For example , macrophages differentiated in vitro from resting peripheral blood monocytes of normal donors generally do not express iNOS . In contrast , macrophages differentiated from monocytes obtained from donors with chronic inflammatory disorders or currently battling infection readily express iNOS [49] , [50] . Thus , under the appropriate conditions human macrophages , like mouse macrophages can induce RNS . As shown in the present manuscript , IFN-γ induced RNS is capable of controlling SchuS4 replication in human macrophages , thus confirming the ability of human cells to generate effective RNS responses . Therefore , the role for ROS in CLDC+MPF mediated killing of SchuS4 in human macrophages is not due to the inability of the cells to generate RNS , but is a unique feature of CLDC+MPF stimulation of this cell type . Understanding and identifying the different requirements and redundancy for RNS and ROS in mouse and human cells is important for several reasons . First , identification of the mechanisms by which human and mouse cells control infections with virulent bacteria is essential for monitoring the potential effectiveness of novel drugs . Second , identification of the specific killing pathways will also aid in development of other novel therapeutics . Lastly , understanding the different requirements for bacterial killing in human and mouse macrophages may reveal new pathways used by host cells to effectively combat invading pathogens . As described above , unlike stimulation with IFN-γ , CLDC+MPF revealed a difference in the mechanism by which human and mouse macrophages control virulent F . tularensis . Thus , this reagent may also serve as a useful tool to dissect the relative roles of these pathways in the effective control of infections with virulent bacteria . This in turn may result in superior immunoprophylaxis and therapeutics for infections mediated by diverse groups of bacteria .
Human blood cells were collected from anonymous volunteers under a protocol reviewed and approved by the NIH Clinical Center Institutional Review Board . Signed , informed consent was obtained from each donor acknowledging that their donation would be used for research purposes by intramural investigators throughout NIH . Francisella tularensis strain SchuS4 was kindly provided by Jeannine Peterson , Ph . D . ( Centers for Disease Control , Fort Collins , Colorado ) , F . tularensis strain LVS was provided by Jean Celli , Ph . D . ( Rocky Mountain Laboratories , Hamilton , Montana ) . SchuS4 and LVS were cultured in modified Mueller-Hinton ( MMH ) broth at 37°C with constant shaking overnight , aliquoted into 1 ml samples , frozen at −80°C and thawed just prior to use as previously described [37] . Frozen stocks were titered by enumerating viable bacteria from serial dilutions plated on modified Mueller-Hinton agar as previously described [51] , [52] . The number of viable bacteria in frozen stock vials varied less than 5% over a 10 month period . Yersinia pestis strain 195/P expressing GFP was provided by B . Joseph Hinnebusch , Ph . D . ( Rocky Mountain Laboratories , Hamilton , Montana ) . 195/P-GFP was cultured overnight at 21°C in BHI broth followed by subculture at 37°C as previously described [43] . Bacterial titer was estimated by optical density of the culture at 600nm . Inoculum titers were confirmed following enumeration of viable bacteria from serial dilutions plated on blood agar plates as previously described [43] . Burkholderia pseudomallei strain DD503 expressing GFP was provided by David DeShazer , Ph . D . and Mary Burtnick , Ph . D . ( USAMRIID , Fort Detrick , MD and University of South Alabama , Mobile AL , respectively ) . DD503-GFP was cultured in LB broth overnight at 37°C . Three hours before use , DD503-GFP was diluted 1∶25 in TSBDC culture medium [53] and incubated at 37°C . Bacterial titer was estimated by optical density of the culture at 600nm . Immediately prior to use bacteria were diluted in tissue culture medium and added to cells as described below . Inoculum titers were confirmed following enumeration of viable bacteria from serial dilutions plated on LB agar as previously described [54] . Brucella abortus strain 2308 expressing GFP was kindly supplied by Jean Celli , Ph . D . ( Rocky Mountain Laboratories , Hamilton , MT ) . GFP-B . abortus was cultured on Tryptic Soy agar ( TSA ) plates for 48 h at 37°C . Individual colonies were then transferred to Tryptic Soy Broth ( TSB ) and bacteria were cultured overnight at 37°C with constant shaking . The number of bacteria present on broth cultures was determined by OD 600nm . Actual numbers of viable bacteria were confirmed by plating an inoculum on TSA plates as previously described [55] . LVS was grown in MMH broth as described above . Following overnight culture , LVS was centrifuged for 15 minutes at 8000×g . The resulting pellet was resuspended in breaking buffer ( 50 mM Tris/HCl , 0 . 6 µg/ml DNase , 0 . 6 µg/ml RNase , 1 mM EDTA [all from Sigma] and 1 Complete EDTA free tablet [Roche] ) and the bacteria were centrifuged again for 15 minutes at 8000×g . Pelleted bacteria were then resuspended in breaking buffer . To break open LVS , the bacteria were added to Fast Prep Lysing Matrix B tubes and processed in a FastPrep24 ( MPBio ) for 10 cycles of 45 seconds with 2 minute rest periods on ice in between each cycle . The resulting slurry was then centrifuged at 10 , 000 rpm for 10 minutes . The supernatant was collected and centrifuged twice at 100 , 000×g for 4 h . The pellet was resuspended in buffer containing 50 mM Tris/HCl , 1 mM EDTA and dialyzed against PBS using 3000 MW cutoff Slide-A-Lyzer cassettes ( Pierce ) . Protein concentration of LVS membrane protein fraction ( MPF ) was determined using a BCA Protein Assay Reagent Kit according to the manufacturer's instructions . Endotoxin levels were determined using Limulus Amebocyte Lysate ( LAL ) assay . Endotoxin levels were <0 . 1 EU/µg of protein . MPF was then aliquoted , irradiated to render it sterile , and stored at -80°C . SchuS4 LPS was generated as previously described [23] . LVS LPS was obtained from the BEI Resources ( Manassas , VA ) . CLDC was provided by Juvaris Biotherapeutics . Formulation of CLDC has been previously described [56] . CLDC was prepared by Juvaris Therapeutics under good manufacturing conditions ( GMP ) . Briefly , DOTIM∶cholesterol liposomes were combined to form a liposome intermediate . pMB75 . 6 plasmids were generated from the non-pathogenic strain of E . coli DH5α . The plasmid contains the following elements: ( i ) the cytomegalovirus immediate early ( CMV-IE ) promoter/enhancer , ( ii ) a polyadenylation signal derived from simian virus 40 ( SV40 ) , ( iii ) a kanamycin-resistance gene , and ( iv ) an origin of replication ( pUCori/f1ori ) . There are no genes expressed by the plasmid . pMB75 . 6 plasmids were added to liposomes at a ratio of 9 . 8∶1 ( lipid∶DNA ) . CLDC were aliquoted , lyophilized , and stored at 4°C . Endotoxin levels were determined using Limulus Amebocyte Lysate ( LAL ) assay . Endotoxin levels of CLDC were <0 . 1 EU/mg DNA . Immediately prior to use , CLDC was hydrated using 500 µl endotoxin free , water ( Cape Cod Associates Incorporated , E . Falmouth , MA ) . CLDC were allowed to rehydrate for approximately 5 minutes at room temperature . CLDC were then diluted 1∶3 in 5% dextrose water ( D5W; Baxter Healthcare , Deerfield , IL ) . For in vitro experiments , MPF was thawed , vortexed and added to CLDC at a final concentration of 3 . 52 µg/ml . As indicated , MPF and CLDC were also tested individually . In these experiments MPF was diluted in 5% dextrose water to 3 . 52 µg/ml . All CLDC , MPF and CLDC+MPF mixtures were added to cells in a volume of 50 µl/well and were used immediately following preparation . For in vivo experiments , MPF or LPS was thawed , vortexed , and diluted in 5% dextrose water . In experiments testing MPF or LPS alone , MPF and LPS were diluted to 50 µg/ml . In experiments testing combination of CLDC and MPF or LPS , the reagents were added to CLDC at a final concentration of 50 µg/ml . In these experiments MPF was diluted in 5% dextrose water to 50 µg/ml . All CLDC , MPF and CLDC+MPF mixtures were used immediately following preparation . Mice were injected with 200 µl of prepared CLDC+MPF . Bone marrow derived macrophages were generated as previously described [51] with the exception that cells were differentiated into macrophages in tissue culture plates with or without glass coverslips in the presence of 10 ng/ml recombinant murine M-CSF ( Peprotech , Rocky Hill , NJ ) . All cells were used on day 6 of culture . Human monocyte derived macrophages were differentiated from apheresed peripheral blood monocytes as previously described [57] . Briefly , apheresed monocytes were enriched using Ficoll-paque ( GE Healthcare ) . CD14+ progenitor cells were enriched via negative selection using Dynabeads MyPure Monocytes Kit for untouched human cells per manufacturer's instructions ( Invitrogen ) . Cells were resuspended at 3×105/ml in cRPMI supplemented with 10 ng/ml M-CSF ( Peprotech ) plated at 1 ml/well in 24-well plates with or without glass coverslips and incubated at 37°C/5%CO2 . On day 2 and 5 of culture medium was replaced with cRPMI supplemented with 10 ng/ml M-CSF . All cells were used on day 6 of culture . Human blood cells were collected from anonymous volunteers under a protocol reviewed and approved by the NIH Clinical Center Institutional Review Board . Signed , informed consent was obtained from each donor acknowledging that their donation would be used for research purposes by intramural investigators throughout NIH . Macrophages were treated with CLDC , MPF or CLDC+MPF , prepared as described above , 18 h prior to infection with bacteria . As indicated , 1 or 6 hr prior to addition of CLDC+MPF human and mouse macrophages were pretreated with 10 mM ( human ) or 3 mM ( mouse ) N-acetyl-L-cysteine ( NAC ) ( Sigma ) , 3 mM ( human ) or 1 mM ( mouse ) L5-[imino ( methylamino ) methyl]-L-ornithinemonoacetate ( L-NMMA ) , ( Caymen Chemicals ) , respectively . Following treatments described above , macrophages were infected with either F . tularensis SchuS4 ( MOI = 50 ) , B . abortus ( MOI = 50 ) , B . pseudomallei ( MOI = 1 ) , or Y . pestis ( MOI = 2 ) . Briefly , medium was removed and reserved , and then F . tularensis was co-incubated with macrophages at 37°C in 7% CO2 for 1 . 5 h followed by treatment with gentamicin ( Invitrogen ) at 500 µg/ml for 1 h . Then , cultures were washed extensively and reserved medium was replaced . The infection inoculum was confirmed by plating serial dilutions of stock F . tularensis on MMH agar plates immediately prior to addition to cell cultures . B . pseudomallei was co-incubated with macrophages at 37°C in 5% CO2 for 1 h followed by addition of kanamycin ( Invitrogen ) at 250 µg/ml for the remainder of the experiment . Y . pestis was co-incubated with macrophages at 21°C in 5% CO2 for 1 h followed by treated with gentamicin at 80 µg/ml for 1 h . Then , cultures were washed extensively and reserved medium supplemented with 8 µg/ml gentamicin was replaced . Macrophages were infected with B . abortus as previously described [55] . At the indicated time points , cells were either lysed for enumeration of intracellular bacteria or isolation of RNA , or were fixed with 3% paraformaldehyde in PBS for 20 min at 37°C/5%CO2 prior to analysis for bacteria as described below . At the indicated time points , medium was removed and cells were washed extensively . Then , cells were lysed following incubation in sterile water . Cell lysates were immediately serially diluted and plated on either MMH , LB , blood , or TSA agar plates . Agar plates were incubated at 37°C/7% CO2 for 48–72 h for enumeration of bacterial colonies . Macrophages were grown on coverslips , treated , and infected with SchuS4 , GFP-B . pseudomallei , GFP-Y . pestis or GFP-B . abortus as described above . Cells were fixed in 3% paraformaldehyde for 20 minutes at 37°C/5%CO2 . Cells were washed with PBS and stained for LAMP-1 as previously described [10] , [57] . SchuS4 was detected using Alexa Fluor488 goat conjugated anti-F . tularensis ( US Biological , Swampscot , MA ) as previously described [57] . Samples were observed on a Carl Zeiss ( Thornwood , NY ) Axio Imager . M1 epifluoresence microscope for quantitative analysis . Approximately 75–100 cells/field and a minimum of three fields per coverslip were analyzed for presence of intracellular bacteria . Percent of infected cells was calculated as follows: ( number infected cells/total number of cells ) ×100 . Confocal images of 1 , 024×1 , 024 pixels were acquired and assembled using Adobe Photoshop CS2 software ( Adobe Systems , San Jose , CA ) . RNA was isolated and converted to cDNA using RT2 qPCR Grade RNA Isolation Kit and RT2 First Strand Kit ( both from SA Biosciences , Frederick , MD ) according to manufacturer's instructions . Samples were assessed for ROS and RNS associated genes expression using nitric oxide RT2 Profiler PCR Arrays for mouse and human per manufacturer's instructions ( SA Biosciences ) . Gene expression was quantitated using RT2 Profiler PCR Array Data Analysis Software ( SA Biosciences ) . Accession numbers for genes in which expression was increased or decreased compared to untreated controls are listed in Table S1 . Specific-pathogen-free , 6–8 week old male C57Bl/6 mice ( wild type ) ( n = 10/group ) were purchased from Jackson Laboratories ( Bar Harbor , MI ) . nos2/phox gp91 deficient mice ( nos2/gp91−/− ) mice were bred at the NIAID/Rocky Mountain Laboratories . All research involving animals was conducted in accordance with Animal Care and Use guidelines and animal protocols were approved by the Animal Care and Use Committee at RML . CLDC , MPF and CLDC+MPF were prepared as described above . At the time points indicated , mice were injected intravenously ( i . v . ) , intraperitoneally ( i . p . ) or subcutaneously ( s . c . ) with 200 µl of each preparation prior to challenge . For intranasal ( i . n . ) administration mice were anesthetized via intraperitoneal injection with 100 µl of ketamine ( 12 . 5 mg/ml ) + xylazine ( 3 . 8 mg/ml ) solution and the reagents were delivered in a total volume of 25 µl evenly distributed between the nares at the indicated time points prior to challenge . Then , mice were anesthetized via intraperitoneal injection with 100 µl of ketamine ( 12 . 5 mg/ml ) + xylazine ( 3 . 8 mg/ml ) solution and intranasally infected with 25 CFU SchuS4 diluted in a final volume of 25 µl of PBS . Inoculating doses were confirmed by plating inoculum on MMH agar . This inoculum routinely results in 100% mortality and a mean time to death of 5 days following infection in naive animals . For in vitro studies , statistical differences between two groups were determined using an unpaired student t test with the significance set at p<0 . 05 . For comparison between three or more groups , analysis was done by one-way ANOVA followed by Tukey's multiple comparisons test with significance determined at p<0 . 05 . For in vivo studies , significance in survival was assessed using log-rank ( Mantel Cox ) test with significance set at p<0 . 05 . | Conventional treatment of bacterial infections typically includes administration of antibiotics . However , many pathogens have developed spontaneous resistance to commonly used antibiotics . Development of new compounds that stimulate the host immune system to directly kill bacteria by mechanisms different from those utilized by antibiotics may serve as effective alternatives to antibiotic therapy . In this report , we describe a novel compound capable of controlling infections mediated by different , unrelated bacteria via the induction of host derived reactive oxygen and reactive nitrogen species . This compound is comprised of cationic liposome DNA complexes ( CLDC ) and crude membrane preparations ( MPF ) obtained from attenuated Francisella tularensis Live Vaccine Strain ( LVS ) . Pretreatment of primary mouse or human cells limited replication of virulent F . tularensis , Burkholderia pseudomallei , Yersinia pestis and Brucella abortus in vitro . CLDC+MPF was also effective for controlling lethal pulmonary infections with virulent F . tularensis . Thus , CLDC+MPF represents a novel antimicrobial for treatment of lethal , acute , bacterial infections . | [
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"Methods"
] | [
"immunology/immunity",
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] | 2010 | Effective, Broad Spectrum Control of Virulent Bacterial Infections Using Cationic DNA Liposome Complexes Combined with Bacterial Antigens |
Methylation is a post-translational modification that can affect numerous features of proteins , notably cellular localization , turnover , activity , and molecular interactions . Recent genome-wide analyses have considerably extended the list of human genes encoding putative methyltransferases . Studies on protein methyltransferases have revealed that the regulatory function of methylation is not limited to epigenetics , with many non-histone substrates now being discovered . We present here our findings on a novel family of distantly related putative methyltransferases . Affinity purification coupled to mass spectrometry shows a marked preference for these proteins to associate with various chaperones . Based on the spectral data , we were able to identify methylation sites in substrates , notably trimethylation of K135 of KIN/Kin17 , K561 of HSPA8/Hsc70 as well as corresponding lysine residues in other Hsp70 isoforms , and K315 of VCP/p97 . All modification sites were subsequently confirmed in vitro . In the case of VCP , methylation by METTL21D was stimulated by the addition of the UBX cofactor ASPSCR1 , which we show directly interacts with the methyltransferase . This stimulatory effect was lost when we used VCP mutants ( R155H , R159G , and R191Q ) known to cause Inclusion Body Myopathy with Paget's disease of bone and Fronto-temporal Dementia ( IBMPFD ) and/or familial Amyotrophic Lateral Sclerosis ( ALS ) . Lysine 315 falls in proximity to the Walker B motif of VCP's first ATPase/D1 domain . Our results indicate that methylation of this site negatively impacts its ATPase activity . Overall , this report uncovers a new role for protein methylation as a regulatory pathway for molecular chaperones and defines a novel regulatory mechanism for the chaperone VCP , whose deregulation is causative of degenerative neuromuscular diseases .
Methyltransferases catalyze the transfer of a methyl group ( CH3 ) from a donor , generally S-adenosyl-L-methionine ( AdoMet ) , to various acceptor molecules such as proteins , DNA , RNA , lipids , and small metabolites [1]–[3] . Protein N-methylation predominantly targets the side chains of two amino acids , lysine and arginine , whereas the side chains of other residues , including histidine , glutamine , and asparagine represent minor targets for methylation [4]–[6] . Dicarboxylic amino acids ( glutamate , aspartate ) and cysteine are also known to be respectively O- and S-methylated on occasion [7] , [8] . In addition , some proteins were shown to be methylated on their N-terminal and C-terminal ends [9]–[11] . The vast majority of methyltransferases are grouped into three large families based on their structure , namely seven-β-strand , SET and SPOUT domain-containing methyltransferases [2] . All protein R methyltransferases ( PRMT ) are part of the seven-β-strand superfamily , while protein K methyltransferases ( PKMT ) fall almost exclusively within the SET domain-containing group . Until recently , the only known seven-β-strand PKMT was Dot1 [12] . Efforts to characterize substrates of PKMT have mostly focused on nucleosome components . Methylation of histone H3 residues K4 , K36 , and K79 are associated with transcriptionally active euchromatin , whereas methylation of H3K9 , H3K27 and H4K20 coincides with heterochromatin and transcriptional repression [13] , [14] . Recent reports have furthermore shown that the type of lysine methylation ( i . e . , mono- , di- or trimethylation ) should also be taken into consideration when assessing chromatin state [15]–[17] . Epigenetics has been paramount in demonstrating that a modification as seemingly insignificant as the addition of a methyl group can have a considerable impact on a biological process as crucial as gene expression . Evidence of lysine methylation-driven regulation has been documented for an ever-increasing number of non-histone proteins , including calmodulin , cytochrome C , Rubisco , ribosomal proteins , p53 , and NF-κB [18]–[27] . As part of an effort to systematically map protein-protein interactions , we came across a previously uncharacterized protein sharing distant homology with PRMTs nestled within a network of molecular chaperones involved in protein complex assembly . Subsequent local alignement searches using that protein as seed uncovered a group of 10 distantly related putative methyltransferases . Characterization of the interaction network of this novel subgroup of methyltransferases was undertaken by Affinity Purification coupled to Mass Spectrometry ( AP-MS ) and then computationally assessed . Our results revealed that enzymes of this subgroup preferentially interact with molecular chaperones . Validation experiments using three of the identified interactors , Kin17 , Hsc70 , and VCP/p97 , indicated that they represent bona fide substrates . In each case , trimethylated lysine residues were identified in vivo and confirmed in vitro using recombinant methyltransferase-substrate pairs . In addition , we have shown that methylation of one of these substrates , VCP/p97 , by METTL21D can be modulated by ASPSCR1/UBXD9 and that this modification regulates ATPase activity of the VCP chaperone . The results presented here bring to light an entirely new cast of PKMTs of the seven-β-strand variety and expands our knowledge of non-histones substrates , most notably molecular chaperones . This finding points to a new role for protein methylation in regulating protein folding , quality control , and turnover .
The study of this group of previously uncharacterized methyltransferases was initiated when METTL22 was identified in the soluble fraction of a protein affinity purification that targeted the DNA/RNA binding protein Kin17/KIN . Local alignment searches were performed to ascertain the function of this protein ( data not shown ) . It was discovered that METTL22 was part of a larger group of 10 proteins ( if the diversity of FAM86 closely-related isoforms are considered as a single member ) that shared distant homology with PRMTs . Phylogenetic analysis of the most conserved region of these two protein groups ( Figure S1 ) confirmed this observation , suggesting that this family of uncharacterized methyltransferases is related to , but distinct from , PRMTs ( Figure 1A; Figure S2 ) . Computational structure prediction further demonstrated the similarity between the members of this family of putative methyltransferases and PRMTs ( Figure 1B , 1C ) . The subsequent publication of the human “methyltransferasome” by Clarke and colleagues confirmed that these proteins are putative methyltransferases and that they form a distinct family [2] . Indeed , most of the methyltransferases described here fall within the so-called “Group J . ” Based on the observed homology with PRMTs , we hypothesized that these proteins were likely protein methyltransferases themselves . To identify possible substrates and cofactors , we elected to map the protein interaction network for each member of this novel family by AP-MS ( main interactors are marked in Figure 2 , additional targets are listed in Table S1 ) [28]–[35] . The main METTL22 interactor identified in the soluble fraction was KIN , which confirmed our initial observation and further strengthened the notion that these two factors interact . A common theme for most of these putative methyltransferases' interactors was chaperones , be they of the Hsp70 or Hsp90 variety ( see METTL18 , CAMKMT , METTL21C , METTL22 , METTL23 , METTL21A , and METTL21B ) , chaperonins HSPD1 and CCT ( see METTL18 , CAMKMT , METTL20 , and METTL21B ) , and even the AAA ATPase VCP ( see METTL21D ) that is believed to act as a chaperone in various processes , most notably Endoplasmic Reticulum-Associated Protein Degradation ( ERAD ) [36]– . Recent publications have substantiated the accuracy of this interactome . Firstly , it was demonstrated in another report by Steven Clarke on the yeast homolog of METTL18 , YIL110W , that this protein methylates the ribosomal protein RPL3 [6] . Our own purification of METTL18 identified RPL3 and its associated ribosome biogenesis factor GRWD1 [41] as the two main interactors . Secondly , CAMKMT has been shown to methylate calmodulin on a lysine residue [42] . We were likewise able to co-purify calmodulin protein CALM2 in our CAMKMT affinity purification . However , it should be noted that since our AP-MS protocol includes beads bearing the calmodulin-binding peptide ( CBP ) , calmodulin often appears as a non-specific target , although usually with a weaker signal . Computational assessment showed that CALM2 was a high confidence interactor of CAMKMT ( FDR<10% ) . Protein database searches were repeated allowing for mono- , di- , and trimethylation of lysine residues ( as a variable modification ) . Of note , lysine trimethylation and acetylation are sometimes mis-annotated due to the closeness in mass of these modifications ( +42 . 0468 Dalton and +42 . 0105 Dalton , respectively ) [43] . Fortunately , the high mass accuracy obtained with the LTQ Orbitrap mass spectrometer was sufficient to distinguish between these PTMs . The most promising hits were a trimethylated lysine on KIN at position 135 in the METTL22 purification , another trimethylated lysine at position 315 on VCP in the METTL21D purification , and a number of trimethylated lysines on multiple Hsp70 isoforms , which correspond to a homologous site , in the METTL21A purification ( Figure 3A; see corresponding mass spectra in Figure S3 ) . These methylation sites were highly conserved through evolution ( Figure 3B ) . Conservation of the VCP methylation site K315 is not surprising considering the relative immutability of the overall protein ( roughly 70% sequence identity from Homo sapiens to Saccharomyces cerevisiae ) . The target lysine 561 in HSPA8/Hsc70 was likewise conserved through evolution and orthologs are found in species as distant as S . cerevisiae . Moreover , and as mentioned previously , this site is also retained in a number human Hsp70 paralogs ( HSPA1 , HSPA1L , HSPA2 , HSPA5 , and HSPA6 ) . In fact the only conserved residue in this region of loose homology is the target lysine , pointing to a possible important regulatory role for this modification . The target lysine in KIN , K135 , is present in a number of species , including Arabidopsis thaliana and Drosophila melanogaster , but is absent in Saccharomyces cerevisiae and Plasmodium falciparum . Interestingly , METTL22 orthologs are concurrently absent in species where the corresponding lysine in KIN is not conserved , which further suggests a strong link between the two . We then proceeded with in vitro methylation assays to confirm the identity of these methylation targets ( Figure 3C–3E ) . A positive signal was observed for each reaction , confirming that these are in fact protein methyltransferases . Moreover , substitution of each identified lysine to an arginine , a relatively conserved substitution , led to the abrogation of the methylation signal . In the case of KIN , the K135R substitution greatly diminished the methylation signal , but did not completely abolish it as with other mutants tested . This could mean that there might be a second methylation site on KIN , but given that no other methylated peptide was ever observed by mass spectrometry , either in the original purification of METTL22 or in the in vitro methylation reaction itself ( see corresponding mass spectra in Figure S4 ) , we believe that the residual methylation is more likely to occur on a cryptic site , i . e . , one that is not normally methylated in wild-type KIN . Of note , methylation by METTL21A was assayed on three Hsp70 homologs ( HSPA1 , HSPA5 , and HSPA8 ) , but it stands to reason that the modification would also apply to other isoforms where the lysine residue is conserved . To further characterize the function of the methyltransferases , intracellular localization was determined by immunofluorescence . To this end , recombinant FLAG-tagged proteins were expressed in HeLa cells ( Figure 4 ) . For most methyltransferases , a marked preference for the cytoplasm was observed , although this trend is reversed in METTL21C and METT22 , where the localization is predominantly nuclear . This nuclear distribution could hint at a nucleosomal methylation activity , since it is frequent with most other protein methyltransferases , but none of the four major histones appear to be methylated in vitro by the members of this family ( see Figure S5 ) . Localization of METTL18 was never determined , since no significant expression of the recombinant methyltransferase has ever been observed . It is tempting to speculate that this effect could be the result of impaired translation , since METTL18 interacts with , and probably methylates , ribosomal subunit RPL3 . Whereas most methyltransferases display a diffuse distribution , METTL20 is concentrated in cytoplasmic granular foci and METTL23 displays internal membrane-like structures . In the three instances where a methylation target has been identified , the substrate proteins ( or associated protein ASPSCR1 , in the case of METTL21D ) bearing a GFP marker were co-expressed with the corresponding methyltransferase ( Figure 4B ) . All methyltransferases and methyl acceptors more or less colocalize within the same cell compartments . In the case of METTL21A with HSPA8 and METTL21D with VCP or ASPSCR1 , the colocalization is nearly perfect . METTL22 and KIN are both present in the nucleus , although METTL22 is clearly more concentrated in the periphery than KIN . Methyltransferases often require cofactors to aid in the modification of their substrates . A good example of this is methylation of spliceosomal Sm proteins by the PRMT5/WD45 complex with the help of pICIn [44] . In the purification of METTL21D , we were able to identify two poorly documented VCP binding proteins , UBXN6/UBXD1 and ASPSCR1/UBXD9 . This came as a surprise since VCP was shown to interact with an impressive number of cofactors including the entirety of the UBX ( ubiquitin regulatory X ) family [45] . Given this apparent specificity , we tested whether these proteins could act as cofactors in the methylation of VCP . As shown in Figure 5A , methylation experiments revealed that neither ASPSRC1 nor UBXN6 could be methylated directly by METTL21D but that only the addition of ASPSCR1 , not UBXN6 , could enhance methylation of VCP . N- and C-terminal fragments of ASPSCR1 were generated in an effort to determine which domain of the cofactor is responsible for this effect ( Figure 5B ) . To our surprise , we observed that only the C-terminal fragment ( residues 280–553 ) , which was previously shown to interact weakly with VCP [46] , could enhance VCP methylation in a similar manner as full-length ASPSCR1 . An in vitro GST pull-down experiment ( Figure 5C ) confirms direct binding of the methyltransferase METTL21D to its substrate VCP , but also shows interaction with ASPSCR1 , more specifically , to its C-terminal fragment . Furthermore , addition of VCP and ASPSCR1 or VCP and the C-terminal fragment of ASPSCR1 together appear to have a synergetic effect on binding to METTL21D , which could account for the concomitant increase in methylation signal . Numerous mutations in the VCP gene have been linked with genetic disorders such as Inclusion Body Myopathy with Paget's disease of bone and Fronto-temporal Dementia ( IBMPFD ) and familial Amyotrophic Lateral Sclerosis ( ALS ) [47] , [48] . Substitutions R155H and R191Q have been implicated in both IBMPFD and ALS . Furthermore , R159G was observed in patient with ALS , although other substitutions targeting arginine 159 were found in patients with IBMPFD ( Figure 5D ) . In vitro methylation assay using recombinant VCP bearing these substitutions was done in order to test whether disease-causing mutations can also impact VCP methylation ( Figure 5E ) . Although all mutant proteins appears to be methylated to a similar degree as wild-type VCP in vitro , the addition of the UBX protein no longer seems to enhance the methylation signal . These results can be explained by the notion the mutants used in this assay , as with most described VCP mutations , reside within the N-terminal domain believed to be involved in cofactor association [49]–[51] . In vitro GST pull-down experiment ( Figure 5F ) confirms that mutation of VCP has no impact on affinity of METTL21D for its substrate . However , when ASPSCR1 is added to the mix , the synergetic increase in binding is only observed with wild-type VCP . Given VCP's involvement in disease , we decided to further scrutinize the functional implications of its methylation . This member of the AAA ( ATPases Associated with various cellular Activities ) family of ATPases contains dual ATPase domains . The methylation site falls in close proximity to the Walker B motif of VCP's first ATPase domain ( Figure 6A ) . Knowing that Walker B motifs are usually involved in ATP hydrolysis , we hypothesized that trimethylation of lysine 315 might affect the ATPase activity of this domain . To test this idea , in vitro ATPase assays were performed with a fragment of VCP spanning its N-terminal and first ATPase domain . The reasoning behind this was that since most of VCP's ATPase activity stems from its second ATPase domain [52] , if methylation of K315 only affects the activity of the first ATPase domain , we might not have detected a change in the overall activity of the full-length protein . Before going forward with in vitro ATPase assays , we first verified that the fragment could still be methylated and that methylation could be inhibited by S-adenosylhomocysteine ( AdoHcy ) , a byproduct of methylation that also acts as a methylation inhibitor for most methyltransferases . A catalytically inactive mutated form of the methyltransferase was also created that targets the conserved acidic residue in METTL21D's AdoMet-binding motif ( E73Q , see Figure 1C ) . The results show that the fragment is methylated as efficiently as full-length VCP ( Figure 6B ) . Furthermore , substitution of the VCP fragment by an unmethylatable mutant ( K315R ) , substitution of the methyltransferase by the catalytically inactive mutant ( E73Q ) , or even addition of AdoHcy all resulted in nearly complete inhibition of methylation . We then performed the in vitro ATPase assay and found that when a wild-type VCP fragment is pre-incubated with wild type METTL21D and the methyl donor , AdoMet , a significant decrease in ATPase activity was detected as compared to three separate control reactions where either the methyltransferase is replaced by its E73Q mutant; VCP is replaced with its unmethylatable mutant ( K315R ) ; or the methyl donor is replaced with AdoHcy ( Figure 6C and 6D ) . A possible interpretation of this finding is that methylation of VCP does not inhibit the ATPase activity per se , but that binding of the methyltransferase itself hinders the ATPase function . To eliminate this possibility , in vitro GST pulldowns were carried out ( Figure 6E ) . Although we did observe a decreased binding between methyltransferase and substrate when METTL21D is replaced by the E73Q mutant , addition of AdoHcy and mutation of VCP lysine 315 do not appear to affect the interaction when compared to wild-type METTL21D and wild-type VCP in presence of AdoMet . This result confirms the conclusion that methylation of VCP directly modulates the ATPase activity of its first ATPase domain . Additionally , these experiments were repeated with a full-length form of VCP whose second ATPase domain has been inactivated by a mutation targeting a critical residue within the Walker B motif ( E578Q; Figure S6 ) [53] . Again , a decrease in ATPase activity is observed when VCP_E578Q is preincubated with METTL21D and AdoMet .
The data presented here bring an entirely new group of protein methyltransferases into light and suggest a role for this post-translational modification in modulating chaperone function . Hsp70 isoforms have been known to be methylated both on arginine and lysine residues for quite some time [54] , [55] , but up until now the exact sites of these modifications and the enzymes responsible for them had remained elusive . The role of these modifications is also uncertain , but we speculate that they may help direct specificity of these chaperones towards substrates and cofactors . Evidence for this could be derived from the AP-MS data presented here . Indeed , METTL21A , the only known Hsp70 methyltransferase identified so far , copurified with a number of Hsp70 isoforms but few cofactors aside from Hsp110s . The closely related METTL21B also copurified with significant amounts of Hsp70 but this time appeared to be complexed with STIP1/Hsp90 or CCT chaperonin . That differential methylation by these enzymes drives Hsp70 specificity is a hypothesis that remains to be tested . What is certain based on the results presented in this article is that the ATPase activity of another seemingly unrelated chaperone , VCP , can be modulated by METTL21D-dependent lysine trimethylation . As with Hsp70s , VCP has also been shown to be extensively modified , mostly by phosphorylation and acetylation [56]–[60] . In this report , we demonstrate that methylation of the VCP requires a novel , specific methyltransferase , which in turn seems to be highly conserved throughout evolution . Indeed , tandem-affinity purification of a yeast homolog of METTL21D , Nnt1p , led to the identification of the yeast homolog of VCP , Cdc48p ( Figure S7 and Table S2 ) , hinting at the importance of this interaction . Strickingly , methylation of VCP is further enhanced by direct interaction of the methyltransferase with ASPSCR1 , a poorly characterized VCP cofactor , and this effect appears to require the C-terminal half of ASPSCR1 . Mutations in the VCP gene have been linked to autosomal dominant disorders Inclusion Body Myopathy with Paget's disease of bone and Fronto-temporal Dementia ( IBMPFD ) and familial Amyotrophic Lateral Sclerosis ( ALS ) [47] , [48] . Most VCP mutations reside within the N-terminal domain , which has been proposed to be involved in cofactor association [49]–[51] . Substitutions R155H , R159G and R191Q have no impact on the in vitro methylation of the protein . However , addition of ASPSCR1 no longer appears to increase the methylation of mutant VCP as compared to the wild-type protein . This observation opens up a whole new area of investigation in understanding the molecular physiopathology of IBMPFD and familial ALS . It may therefore be of interest to assess the relative methylation of VCP in affected patients as compared to healthy individuals . Many studies were performed to define how these disease mutations affect the function of VCP . From a biochemical point of view , the most promising alteration concerned the increased ATPase activity that may reflect structural changes induced by ATP binding [61] , [62] . Methylation of VCP by METTL21D is shown here to significantly decrease activity of the first ATPase domain of this chaperone . This modification could eventually help modulate enzymatic activity of VCP that has gone haywire due to mutation . Our work on the KIN protein , which eventually led to the discovery of its associated methyltransferase METTL22 , began when it was detected in the interactome of a number of prefoldins ( see supporting data in [32] ) . Thus , even though KIN is not known to have chaperone activity , it still appears to interact with chaperones and potentially affect their activity . The exact function of KIN is still a matter of debate . This DNA and RNA binding protein has been assigned a role in DNA repair and/or replication [63]–[66] and possibly mRNA processing as suggested by its identification in a number of proteomic analyses of the spliceosome [67] , [68] . The role of the herein identified methylation will likely go hand in hand with the function of the winged helix domain in which it resides . Interestingly , yet another winged helix-containing protein was detected in the METTL22 purification , FOXK1 . In this case , the function of the winged helix is known since it is required for DNA binding of this transcription factor . If METTL22 is shown to methylate FOXK1 as it did with KIN , this may in turn point to a more complex regulation of winged helix factors . Advances in proteomics have helped to catalog various post-translational modifications of the proteome , and it now seems evident that chaperones contain several occurrences of such modifications . Recent identification of Hsp90 methylation by lysine methyltransferase SMYD2 is further evidence of the significance of this modification in regulating chaperone function [69] . Just like post-translational modifications of histone tails were shown to modulate binding to multiple chromatin remodeling , transcription , and mRNA processing factors , we believe that chaperone modifications may compose a similar code to help define specificity of discrete subsets to their seemingly innumerable effectors . Further decrypting this “chaperone code” is now required to understand how the functional organization of the proteome is orchestrated .
Coding sequences for methyltransferases discussed in this article were obtained from the I . M . A . G . E . consortium clone library ( Thermo Scientific ) . The corresponding cDNAs were cloned into the mammalian expression vector pMZI [70] carrying a TAP tag at its C-terminus [71] , [72] . Stable human embryonic kidney cell lines ( EcR-293; derived from HEK293 ) carrying these constructs were produced as described previously [28] , [33] . Induction for 48 hours with 3 µM ponasterone A ( Life Technologies ) was used to express the TAP-tagged proteins . Whole cell extracts prepared from induced and non-induced stable EcR-293 cell lines were subjected to purification by the TAP procedure as described previously [28] , [33] . TAP eluates were desalted and concentrated on Amicon Ultra 10K centrifugal filter units ( Millipore ) and resolved on NuPAGE 4–12% Bis-Tris Gel ( Life Technologies ) . The gels were silver-stained , and the entirety of the tracks where the eluates had migrated were cut in about 20 slices that were subsequently digested with trypsin as described previously [28] , [33] . The resulting tryptic peptides were purified and identified by LC-tandem mass spectrometry ( MS/MS ) using a microcapillary reversed-phase high pressure liquid chromatography coupled to a LTQ Orbitrap ( ThermoElectron ) mass spectrometer with a nanospray interface . The peak list files were generated with extract_msn . exe ( version February 15 , 2005 ) using the following parameters: minimum mass set to 600 Da , maximum mass set to 6000 Da , no grouping of MS/MS spectra , precursor charge set to auto , and minimum number of fragment ions set to 10 . Protein database searching was performed with Mascot 2 . 3 ( Matrix Science ) against the human NCBInr protein database ( version April 2 , 2009 ) . There are 10 , 427 , 007 sequences in this database . The mass tolerances for precursor and fragment ions were set to 10 ppm and 0 . 6 Da , respectively . Trypsin was used as the enzyme allowing for up to two missed cleavages . Carbamidomethyl , oxidation of methionine , mono- , di- , and trimethylation of lysine were allowed as variable modifications . In cases where multiple gene products were identified from the same peptide set , all were unambiguously removed from the data set . In the case of multiple isoforms stemming from a unique gene , the isoform with the best sequence coverage was reported . Proteins identified on the basis of a single peptide were also discarded . Reliability assessment of protein-protein interactions was performed by our previously published software Decontaminator [73] . A set of 17 pairs of matched non-induced bait expression ( control ) and induced bait expression vectors was used for the algorithm training . Those were chosen on the basis of the absence of leaky expression of the tagged protein in the non-induced experiments . Decontaminator builds Bayesian probabilistic models of the Mascot scores [74] for each protein observed in the training set . It then assigns a p-value to each bait-prey interaction by computing the significance of the observed prey Mascot score compared to its corresponding control Mascot score model . A False Discovery Rate ( FDR ) is then calculated for each protein-protein interactions in the dataset using a leave-one-out scheme . All interactions with a FDR below 10% were reported as bait-specific , resulting in a dataset of 234 interactions . In other words , less than 24 interactions are expected to be the consequence of contamination . The protocol was slightly modified from Inamitsu et al . [75] . Coding sequences of methyltransferases were cloned into pGEX-4-T1 vector ( GE Healthcare ) . Coding sequences of putative methylation substrates were cloned into pET-23a ( + ) vector ( EMD Chemicals ) . All vectors were transformed in One Shot BL21 Star ( DE3 ) ( Life Technologies ) , and protein synthesis was induced with IPTG . Bacteria were harvested by centrifugation , and pellets were lysed with the use of an IEC French Press ( Thermo Scientific ) . The resulting GST- and 6xHis-fusion proteins were purified using Glutathione Sepharose 4B ( GE Healthcare ) and Ni-NTA Agarose ( QIAGEN ) beads , respectively , according to the manufacturers' specifications . In each reaction described in this article , 1 µg of GST-tagged methyltransferase was incubated with 2 . 5 µg His-tagged substrate and 5 µCi of S-[methyl-3H]-Adenosyl-L-methionine ( 81 . 7 Ci/mmol; PerkinElmer ) in 50 µl of PBS for 90 min at 37°C . The samples were resolved on 10% acrylamide gels that were stained with Coomassie to show total amounts of proteins . Gels were then treated with EN3HANCE ( PerkinElmer ) according to the manufacturer's specifications . Tritium-based methylation signals were detected by autoradiography with four hours of exposure on Amersham Hyperfilm MP ( GE Healthcare ) at −80°C . Alternatively , an assay was produced with unlabeled S-adenosyl-L-methionine that was resolved on NuPAGE 4–12% Bis-Tris Gel ( Life Technologies ) and Coomassie stained . The bands corresponding to the His-tagged substrates were excised , trypsin digested , and analyzed as described above . HeLa S3 ( CCL-2 . 2 ATCC ) cells were grown on Lab-Tek II chamber slides ( Nalge Nunc ) and co-transfected with FLAG and GFP expressing vectors ( p3XFLAG-CMV-14 and pGFP2-N1; Sigma-Aldrich & PerkinElmer Life Sciences , respectively ) using Lipofectamine 2000 according to the manufacturer's specifications ( Life Technologies ) . Twenty-four hours following transfection , cells were fixed with 3 . 7% formaldehyde in Phosphate-Buffered Saline ( PBS ) and permeabilized with 0 . 3% Triton X-100 PBS . Slides were then fixed in 5% donkey serum PBS for 1 hour , incubated with 1∶200 monoclonal FLAG antibody ( M2; Sigma-Aldrich ) in 5% donkey serum PBS for 90 min , and then incubated for an additional hour with 1∶50 Cy3-conjugated donkey anti-mouse IgG secondary antibody ( Jackson ImmunoResearch ) in 5% donkey serum PBS . Slides were washed three times with PBS for 5 min after each step . DNA was stained with TO-PRO-3 ( Molecular Probes ) . Slides were mounted using ProLong Gold antifade reagent ( Life Technologies ) . Images were acquired with an LSM 700 confocal laser scanning microscope at 63× magnification and analyzed using ZEN 2010 software ( Zeiss , Toronto , Canada ) . The assay was based on the protocol described in Zwijsen et al . [76] . Briefly , 500 ng of GST-tagged METTL21D was incubated for 1 hour at 4°C with 100 ng of His-tagged VCP , ASPSCR1 or UBXN6 , and 25 µl Glutathione Sepharose 4B beads ( GE Healthcare ) in 1 ml of binding buffer ( 50 mM NaCl , 50 mM HEPES-KOH pH 7 . 6 , 0 . 1% NP-40 , 0 . 5% charcoal-stripped FBS ) complemented with complete EDTA-free protease inhibitor cocktail ( Roche ) . The beads were washed three times by centrifugation with the same buffer and the bound proteins were eluted by boiling for 5 min in sample buffer , and separated on NuPAGE 4–12% Bis-Tris Gel ( Life Technologies ) . Binding of His-tagged proteins was detected by Western blot analysis using mouse monoclonal anti-6X His tag-antibody ( abcam ) . A second blot was made with rabbit polyclonal anti-GST antibody ( abcam ) to ensure that comparable amounts of GST-tagged baits were purified by the pull-down . PiColorLock Gold Phosphate Detection System ( Innova Biosciences ) was used to quantify ATPase activity in vitro . Three micrograms of a His-tagged fragment corresponding to the first 481 residues of VCP were incubated beforehand with 2 µg of GST-METTL21D and 0 . 5 mM S-adenosyl-L-methionine for 30 min at 37°C in 100 µl of 0 . 1 M Tris pH 7 . 5 . All assays were performed in triplicate . Independent experiments were carried out where the VCP fragment was replaced by an unmethylatable mutant ( K315R ) ; the methyltransferase was replaced by a catalytically inactive mutant ( E73Q ) ; or the methyl donor , S-adenosyl-L-methionine , was replaced by a methylation inhibitor , S-adenosyl-L-homocysteine . The rest of the protocol followed the guidelines provided by the manufacturer . All available ortholog sequences of PRMTs and of the family of 10 putative methyltransferases in the UniProt database [77] were aligned using the ClustalW2 multiple sequence alignment software ( version 2 . 0 . 12 ) [78] . The most conserved region of the alignment was then selected to build an unrooted phylogenetic tree through the Jalview software [79] using the neighbor-joining algorithm [80] with the BLOSUM62 substitution matrix [81] . Orthologs forming monophyletic groups with their respective human sequences were collapsed to a single node in the phylogenetic tree shown in Figure 1A . | Methylation , or transfer of a single or multiple methyl groups ( CH3 ) , is one of many post-translational modifications that occur on proteins . Such modifications can , in turn , affect numerous aspects of a protein , notably cellular localization , turnover , activity , and molecular interactions . In addition to post-translational modifications , the structural organization of a protein or protein complex can also have a significant impact on its function and stability . A group of factors known as “molecular chaperones” aid newly synthesized proteins in reaching their native conformation or alternating between physiologically relevant states . We present here a new family of factors that promote methylation of chaperones and show that , at least in one case , this modification translates into a modulation in the activity of the substrate chaperone . Our results not only characterize the function of previously unknown gene products , uncover a new role for protein methylation as a regulatory pathway for chaperones , and define a novel regulatory mechanism for the chaperone VCP , whose deregulation is causative of neuromuscular diseases , but also suggest the existence of a post-translational modification code that regulates molecular chaperones . Further decrypting this “chaperone code” will help understanding how the functional organization of the proteome is orchestrated . | [
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] | 2013 | A Newly Uncovered Group of Distantly Related Lysine Methyltransferases Preferentially Interact with Molecular Chaperones to Regulate Their Activity |
Malaria parasites dramatically alter the rheological properties of infected red blood cells . In the case of Plasmodium vivax , the parasite rapidly decreases the shear elastic modulus of the invaded RBC , enabling it to avoid splenic clearance . This study highlights correlation between rosette formation and altered membrane deformability of P . vivax-infected erythrocytes , where the rosette-forming infected erythrocytes are significantly more rigid than their non-rosetting counterparts . The adhesion of normocytes to the PvIRBC is strong ( mean binding force of 440pN ) resulting in stable rosette formation even under high physiological shear flow stress . Rosetting may contribute to the sequestration of PvIRBC schizonts in the host microvasculature or spleen .
Plasmodium spp . derived changes to the rheology of infected red blood cells ( IRBCs ) play a central role in the pathogenesis of human malaria . Malaria parasite remodelling of IRBCs dramatically alter their deformability and cytoadhesive properties [1] . Interestingly , for all four non-zoonotic causes of human malaria ( P . falciparum , P . vivax , P . ovale and P . malariae ) IRBCs cytoadhere to uninfected RBCs forming distinctive ‘rosettes’ [2–4] . While the precise role of rosetting in malaria pathogenesis remains contentious , many believe that this adaptation may play important roles in the survival of parasites within the circulation [5] . Rheological studies on P . falciparum rosettes show them to be stable and the binding force between the IRBC and the uninfected RBCs tends to be very strong ( >300pn ) [6] . Indeed , most studies on rosetting have focused on P . falciparum , leading to the discovery of rosetting ligands such as PfEMP1 [7] , STEVOR [8] , and RIFINs [9] . Although rosette formation has been reported to be a common phenomenon in P . vivax [2 , 10 , 11] , the rosetting ligand of this species has yet to be discovered . Despite recent evidence showing cytoadhesive potential for P . vivax-infected RBCs [12] , most consider this species to be much less adhesive than P . falciparum , as it lacks any orthologue to the PfEMP1 protein ( the key cytoadhesive ligand in P . falciparum ) and the knobby IRBC ultrastructure ( which concentrate and display PfEMP-1 ) that facilitate binding of IRBCs to the vascular endothelium under physiological shear flow [13] . Therefore , although P . vivax rosettes are relatively commonly observed , it is not known whether they are stable structures or ephemeral ex-vivo formations that break apart in the haemodynamic environment of the circulation in vivo . The objective of this study was to examine the rheological consequences of rosetting on PvIRBCs and specifically quantify the binding strength of normocytes to PvIRBCs .
Blood samples of vivax malaria patients from the Northwestern Thailand were collected under the following ethical guidelines and approved protocols: OXTREC 027–025 ( University of Oxford , Centre for Clinical Vaccinology and Tropical Medicine , UK ) and MUTM 2008–215 from the Ethics Committee of Faculty of Tropical Medicine , Mahidol University , Thailand . Experiments were conducted in Singapore Immunology Network ( SIgN ) and National University of Singapore ( NUS ) , Singapore . All adult subjects provided informed written consent , and a parent or guardian of any child participant provided informed written consent on their behalf . Ten clinical samples were collected from malaria patients of SMRU clinics in Northwestern Thailand using BD Vacutainer with lithium heparin anticoagulant . Thick and thin blood smears were prepared for each sample to determine the species of malaria parasite , the parasitemia , and the predominating developmental stage of the parasite . White blood cells were depleted with cellulose ( Sigma-Aldrich ) packed columns . Blood samples containing predominantly ring-stage parasites ( ≥ 70% ) were cryopreserved with Glycerolyte 57 ( Fenwal ) . For experiments , cryopreserved isolates were thawed and the parasites matured in vitro [14] . When the parasite population reached late erythrocytic stages ( late trophozoite and schizont ) , 50 μl of the culture suspension was taken for rosetting assay using a wet mount method as described elsewhere[11] . Rosetting rate ( percentage of rosette-forming IRBCs ) was determined by examining the number of of rosettes per 200 IRBCs observed . Subsequently , 1 μl packed RBCs were suspended in 1 ml of 1X PBS supplemented with 1% BSA for micropipette aspiration and microfluidic assays . Micropipette aspiration was modified from Hochmuth et al [15] . Briefly , aspiration was performed at 32°C to 37°Cand observed using an oil immersion objective ( 1000 x magnification ) with an Olympus research inverted microscope IX73 . Borosilicate glass micropipettes ( diameter 1 . 5±0 . 2 μm ) were used to hold or aspirate RBCs . Rosetting and non-rosetting IRBCs were individually selected for measurements . Individual RBCs were aspirated at a pressure drop rate of 0 . 5 Pa/s for 100s . The corresponding cell membrane deformation was recorded using the Dual CCD Digital Camera DP80 ( Olympus ) at an image taking rate of one frame/s . Images were processed by cellSens Dimension ( Olympus ) . Hemispherical cap model was used to calculate the membrane shear elastic modulus , as a quantitative surrogate measure of the rigidity of RBC membrane skeleton [15] . To quantify the binding force between RBCs and an IRBC in a P . vivax rosette , a double pipette aspiration method was used as described previously [6] . A rosette was held by a micropipette ( diameter = 2 . 0±0 . 2μm ) . A second micropipette was used to aspirate the uninfected RBCs of the rosette at a gradually increased aspirating pressure . The force ( F ) to detach an RBC from an IRBC was calculated as F = πr2 × P; where r is the inner diameter of the second micropipette , and P is the pressure required to detach two cells . The aspiration pressure was measured by a pressure transducer ( P61 model , Validyne Engineering ) and recorded by USB-COM Data logger ( Validyne Engineering ) . The process was recorded using a Dual CCD Digital Camera DP80 ( Olympus ) at one frame/s . Recorded images were analyzed with cellSens Dimension ( Olympus ) . To characterize the ability of PvIRBCs to move through narrow channels , polydimethylsiloxane ( PDMS ) microfluidic chips with 4μm slits were used . To avoid RBCs from interacting with ( or adhering to ) the walls of the microfluidic chip , channels were pre-filled and incubated with 1X PBS supplemented with 1% BSA for one hour prior to the experiment being performed . Subsequently , 1μl of RBC suspension was injected into the microfluidic channel . Cells were forced through the channel at a constant pressure gradient of 0 . 1 Pa/μm . Numbers of RBCs that blocked at the openings of the microfluidic channels in each experiment were recorded . Videos of the microfluidic assay were recorded using a Dual CCD Digital Camera DP80 ( Olympus ) . Data were subsequently analyzed using the cellSens Dimensions software ( Olympus ) . GraphPad Prism 5 was used for statistical analysis of all experimental data . The one-way ANOVA test was used to compare differences between different experimental groups .
In keeping with previous report [11] , cryopreserved P . vivax isolates showed rosetting , albeit with lower frequency than the fresh isolates . The rosettes found in these cryopreserved isolates were generally small . A mode of three uninfected normocytes were involved in rosettes ( Fig 1 ) . Similar to the previous study [11] , rosetting in this study was only observed with RBCs infected with the late erythrocytic stages ( predominantly schizonts ) . Membrane shear elastic modulus measurements were used to quantify IRBC membrane deformability ( Fig 1A ) . Uninfected reticulocytes showed significantly higher membrane shear moduli than uninfected normocytes ( 11 . 40±1 . 85 pN/μm vs . 4 . 55±2 . 58 pN/μm; P < 0 . 001 ) . Interestingly , the membrane shear elastic moduli of P . vivax ring-infected reticulocytes were reduced to values similar to uninfected normocytes ( 6 . 09±6 . 45 pN/μm ) . The membrane shear elastic moduli of IRBCs remained virtually unchanged at the trophozoite stage ( 6 . 45±4 . 31 pN/μm ) . The membrane shear elastic modulus of non-rosetting schizonts were significantly higher than measurements recorded by trophozoites ( 8 . 84±6 . 88 pN/μm; P < 0 . 05 ) . Measurements performed on rosetting schizonts ( 12 . 1±11 . 36 pN/μm ) were significantly higher than those of non-rosetting schizonts ( P < 0 . 01 ) . All RBCs showed an increased elongation length ( i . e . increased deformability ) with increasing aspiration pressure ( Fig 1B ) . The attachment of a single uninfected RBC caused a significant reduction in deformability of the IRBC ( P < 0 . 05 ) . However , a Spearman’s rank correlation analysis showed that the attachment of additional RBCs did not result in further decreases to IRBC deformability , regardless of the size of the rosettes formed ( Fig 1B ) . From dual micropipette aspiration assays ( Fig 2A ) ( S1 Video ) , the shear force to separate uninfected RBCs from a rosetting complex was 440±197 . 4pN , which was similar to that reported previously for P . falciparum [6] ( Fig 2B ) . In microfluidic experiments ( Fig 2C ) , RBCs infected with either P . vivax ring , trophozoite or schizonts ( early schizont and mature segmenting schizont ) stages ( Three clinical isolates in total were used ) were injected into microfluidic channels as previously shown ( S2–S5 Videos ) [16] . The only cells observed blocking the microfluidic restrictions were rosetting and very mature segmenting schizonts . Rosettes blocking the microfluidic restrictions did not lose cells under pulsed shear flow pressure up to of 1 . 0 Pa/μm . To better determine if the act of rosetting directly causes changes to the IRBC shear modulus ( as opposed to IRBCs with a higher shear modulus are more likely to form rosettes ) we measured the shear modulus of rosetting IRBCs , then using the dual micropipette we carefully peeled off the uninfected normocytes and repeated the measurement on the denuded IRBC . As the rosetting cells strongly bind to the IRBC , the separation process usually resulted the destruction of the IRBC . We were able to conduct 5 successful paired rosette separations , showing a significant reduction in the mean geometric shear modulus of the IRBC from 13 . 3pN ( Rosetting ) to 9 . 5pN ( Non-Rosetting ) ( P<0 . 05 , t = 2 . 8 , df = 4 ( Paired t-test ) ) .
Plasmodium vivax , the most globally-widespread cause of human malaria , has a specific tropism for the rigid CD71+ve reticulocytes generally found in the bone marrow [14 , 17] . Within six hours post invasion , P . vivax remodels the IRBC membrane and cytoskeleton , causing it to become as deformable as an uninfected normocyte [14 , 18] . In contrast to P . falciparum , RBCs infected with trophozoite and early schizont stages of P . vivax retain a relatively low shear modulus ( compared to reticulocytes and P . falciparum IRBCs ) , and are able to deform and pass through micro-capillaries and 2μm sinusoidal slits [16] . It is thought that P . vivax increases the deformability of the host cell to avoid splenic clearance [18] . Our results show that rosetting with at least one uninfected RBC is closely associated with a a significant increase in the rigidity of the P . vivax IRBCs . While it is difficult to demonstrate direct causality , we were able to demonstrate that the removal of rosetting RBCs , restores the deformability of the IRBC to the levels usually seen in non rosetting IRBCs . It is Important to understand that these rosettes are stable even under shear stress , and on encountering microfluidic constrictions they not only block the restriction , but also retain their full complement of attached uninfected red cells . The only other P . vivax IRBCs that tend to block the microfluidic restrictions are very mature schizonts . Traditionally these very late stage schizonts are referred to as ‘segmenters’ , because the merozoites are fully mature and clearly defined within the schizont complex . In P . falciparum , late stage asexual parasites become rigid due to a range of proteins such as RESA , KHARP , MESA , PfEMP3 and STEVOR interacting with the IRBC cytoskeleton and membrane[1 , 19–23] . In P . vivax we do not understand the molecular basis driving the switch from a relatively deformable early schizonts , to a rigid segmenter . However , as this change occurs an hour or so before schizonts rupture; we speculate the rigidity in P . vivax segmenters is due to osmotic deregulation ( as opposed to the incorporation of crosslinking proteins into the cytoskeleton ) as the IRBC membrane degenerates prior to merozoite release . In any case , our study clearly demonstrates that segmenting schizonts and rosetting are the only events responsible for significant rigidity of the P . vivax IRBCs . Recent studies in Brazilian individuals infected with P . vivax reveal a disparate and unexpected disappearance of schizonts from the circulation [24] . Although this may be partially due to cytoadherence to endothelial receptors expressed on the surface of the vascular endothelium [12] , we suggest that the increased rigidity of segmenters and rosetting IRBCs is a major factor behind the paucity of P . vivax schizonts in the circulation . The ligands responsible for P . vivax rosetting remain unknown . The vir proteins of P . vivax have been associated with endothelial cytoadhesion [12] . While we still expect to see spontaneous rosette formation occurring in the circulation , our study suggests that a large proportion P . vivax rosettes will be sequestered . Although the incidence and rate of P . vivax rosetting is high , we are still unsure how this phenomenon contributes to the pathology of vivax malaria[25] . It is important to understand that while rosetting has been observed in most forms of human malaria[2–4 , 26] , we only have a a clear understanding of this process in P . falciparum . Future studies should strive to understand the pathobiological process behind non-falciparum and possible develop therapeutics that disrupt their formation[27 , 28] . | While Plasmodium vivax is generally not as virulent as P . falciparum; severe manifestations of vivax malaria do occur . While little is known about the mechanisms underlying the pathobiology of P . vivax , most agree its ability to increase the deformability of stiff host reticulocytes is key adaptation to avoid splenic clearance . We show that P . vivax-infected red blood cells ( PvIRBCs ) rosette irreversibly with normocytes and are significantly more stiff than non-rosetting PvIRBCs . We discuss how these stiff PvIRBC rosettes are removed from the peripheral circulation and its rheopathological consequences . | [
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"marrow"... | 2016 | Rheopathologic Consequence of Plasmodium vivax Rosette Formation |
Meiotic crossovers are produced when programmed double-strand breaks ( DSBs ) are repaired by recombination from homologous chromosomes ( homologues ) . In a wide variety of organisms , meiotic HORMA-domain proteins are required to direct DSB repair towards homologues . This inter-homologue bias is required for efficient homology search , homologue alignment , and crossover formation . HORMA-domain proteins are also implicated in other processes related to crossover formation , including DSB formation , inhibition of promiscuous formation of the synaptonemal complex ( SC ) , and the meiotic prophase checkpoint that monitors both DSB processing and SCs . We examined the behavior of two previously uncharacterized meiosis-specific mouse HORMA-domain proteins—HORMAD1 and HORMAD2—in wild-type mice and in mutants defective in DSB processing or SC formation . HORMADs are preferentially associated with unsynapsed chromosome axes throughout meiotic prophase . We observe a strong negative correlation between SC formation and presence of HORMADs on axes , and a positive correlation between the presumptive sites of high checkpoint-kinase ATR activity and hyper-accumulation of HORMADs on axes . HORMADs are not depleted from chromosomes in mutants that lack SCs . In contrast , DSB formation and DSB repair are not absolutely required for depletion of HORMADs from synapsed axes . A simple interpretation of these findings is that SC formation directly or indirectly promotes depletion of HORMADs from chromosome axes . We also find that TRIP13 protein is required for reciprocal distribution of HORMADs and the SYCP1/SC-component along chromosome axes . Similarities in mouse and budding yeast meiosis suggest that TRIP13/Pch2 proteins have a conserved role in establishing mutually exclusive HORMAD-rich and synapsed chromatin domains in both mouse and yeast . Taken together , our observations raise the possibility that involvement of meiotic HORMA-domain proteins in the regulation of homologue interactions is conserved in mammals .
Faithful segregation of chromosomes during the first meiotic division requires that parental homologous kinetochores are physically connected until all pairs of homologous kinetochores attach to microtubules and orient toward opposite spindle poles during metaphase I [1] . Crossovers ( COs ) in collaboration with sister chromatid cohesion provide these physical connections between maternal and paternal homologues in most organisms , including mammals [1] . Each pair of homologues must have at least one ( “obligate” ) CO to ensure correct segregation during the first meiotic division . COs are produced during the first meiotic prophase via recombination . A conserved enzyme , SPO11 , introduces double strand breaks ( DSBs ) into the genome [2]–[4] . DSBs can be repaired using either homologues ( inter-homologue repair ) or sister chromatids ( inter-sister repair ) as a recombination/repair template . To ensure CO formation , DSBs are preferentially repaired through the inter-homologue pathway , a phenomenon called the inter-homologue bias ( IH bias ) [5] . This process also requires that homologous sequences recognise each other . The search for homology is aided by 3′ single-stranded overhangs of resected DSBs , which are produced at the beginning of the repair process [6] . Two RecA homologs , RAD51 and DMC1 , assist homology search by promoting strand invasion of resected DNA ends into homologous DNA sequences [7] . The DSB repair process is also coordinated and tightly coupled with dynamic changes in chromatin architecture that facilitate the homology search and stabilise interactions between homologous DNA sequences [1] , [8] . One of the key events of meiotic chromosome dynamics is the formation of synaptonemal complexes ( SCs ) between pre-aligned homologues . SCs play an important role in DSB repair and CO formation [1] , [8]–[10] . These proteinaceous structures consist of three parallel elongated elements , two axial elements ( AEs ) and a central element , which are linked by transverse filaments . The axial element comprises the shared axes of a sister chromatid pair . During SC formation , AEs of homologous chromosomes become connected via the central element/transverse filaments along their entire lengths . AEs begin to form during leptotene prior to the formation of SCs , which starts in zygotene . SCs are fully assembled during pachytene and disassemble as cells progress through diplotene . SC dynamics and the DSB repair process are coordinated with progression in meiosis . In mammals , spermatocytes with defects in SC formation or DSB repair are eliminated at mid pachytene [11]–[15] . Meiotic silencing of unsynapsed chromosomes ( MSUC ) , in particular the silencing of sex chromosomes , is crucial for normal progression past this arrest point in males [16]–[19] . Due to their restricted homology , X and Y chromosomes are only partially synapsed , and their unsynapsed regions are remodelled into a transcriptionally silenced , phospho-histone H2AX ( γH2AX ) rich chromatin domain , termed the sex body [16] , [20] , [21] . Completion of SC formation on autosomes restricts MSUC to sex chromosomes , and is thus essential for full silencing of the X and Y [17] , [19] . Spermatocytes with defective SCs exhibit increased expression from sex chromosomes , which is believed to trigger robust elimination by programmed cell death at mid pachytene [19] . In budding yeast , where meiosis is most extensively explored , SC formation and DSB repair are also monitored by a meiotic prophase checkpoint [22] , [23] . A conserved feature of the mouse and budding yeast meiotic prophase checkpoints , is the involvement of ATM/ATR-like kinases [22] . In mice , ATR is restricted to unsynapsed chromosome regions during zygotene and pachytene [17]–[19] . Hence , ATR is assumed to phosphorylate H2AX in these regions , resulting in MSUC [17]–[19] , [22] . In budding yeast , the ATR and ATM homologs , Mec1 and Tel1 , respectively , are required for the prophase checkpoint in collaboration with Hop1 , a meiosis-specific HORMA-domain protein ( Hop1 , Rev7 and MAD2 homology domain ) [24] , [25] . Hop1 is required for efficient DSB formation , SC formation and the prophase checkpoint [5] , [25]–[28] . It also promotes IH bias by inhibiting DSB repair from sister chromatids . [5] , [25]–[27] , [29] . In particular , phosphorylation of Hop1 by Tel1 and Mec1 is essential for the meiotic prophase checkpoint and for IH bias [25] . Meiotic HORMA-domain proteins are evolutionarily conserved molecules , and they play crucial roles in chromosome behaviour ( e . g . , SC formation and DSB repair ) in other organisms as well , including plants and nematodes [30]–[37] . However , no prior studies have documented involvement of mammalian HORMA-domain proteins in any of the functions known for this important class of proteins . In an effort to find genes that are specifically involved in meiotic chromosome behaviour in mice , we carried out a screen based on expression profiling of murine meiotic cells . This approach identified Hormad1 and Hormad2 , two HORMA-domain encoding genes . HORMAD1 and HORMAD2 proteins are specifically expressed during meiosis in both sexes . We took advantage of characteristic features of mammalian meiosis and powerful cytological methods in mouse in order to better understand the relationships between mouse HORMADs , SC formation , DSB repair , and MSUC .
From expression profiling of reproductive tissues , we found Hormad1 and Hormad2 as genes that are up-regulated in female and male gonads when germ cells enter meiosis and progress to the first meiotic prophase ( our unpublished results ) . RT-PCR analysis shows that Hormad1 and -2 are not expressed in 17 different somatic tissues , and that both Hormads are specifically expressed in the female and male gonads that contain meiotic germ cells ( Figure S1A , S1C and S1D ) . Expression of both genes is restricted to meiotic germ cells in the female gonad at 16 . 5 days post coitum ( dpc ) ( Figure S1B ) . Therefore , we conclude that both Hormad genes are specifically expressed during meiosis . An earlier study also identified Hormad1 as a meiosis-specific gene based on in silico screening of expressed sequence tags [38] . HORMAD1 and HORMAD2 sequences are similar to the sequences of meiosis-specific HORMA-domain proteins in other organisms ( Figure S2 ) . HORMAD1 and -2 are closely related to one another ( Figure S2B ) , and both of them have human homologs ( Figure S2A ) [39] . To gain insight into the likely meiotic functions of HORMAD1 and -2 , antisera were raised against their poorly conserved C-terminal domains ( three for HORMAD1 and three for HORMAD2 ) . Antibodies were affinity purified from these antisera ( see Materials and Methods ) . In immunoblot analysis of testis extracts , the anti-HORMAD1 and anti-HORMAD2 antibodies recognised different proteins that have electrophoretic mobilities consistent with the different molecular weights of HORMAD1 and -2 , respectively ( Figure S3 and Materials and Methods ) . This suggests that our anti-HORMAD1 and anti-HORMAD2 antibodies recognise HORMAD1 and -2 , respectively , and that the antibodies can be used to distinguish between the two HORMADs . To determine the precise timing of HORMAD1/2 expression during spermatogenesis , we detected HORMADs and the AE component SYCP3 on testis cryo-sections by immunofluorescence ( IF ) ( Figure 1 ) . HORMADs are abundant in the nucleus of spermatocytes throughout the first meiotic prophase , reaching their highest levels during early pachytene . In addition to the general nuclear staining , we observed wide-spread axis-like staining with both anti-HORMAD1 and -2 antibodies during meiotic prophase . No specific staining above background was observed in somatic testicular cells . To determine the precise dynamics of chromosome association of HORMADs during meiosis , we immunostained surface-spread chromosomes from adult and juvenile ( 21 dpp ) testes for HORMADs and the AE component SYCP3 , as well as the transverse filament component SYCP1 , γH2AX , RAD51 or centromeres ( Figures 2–6 ) . The pattern of SYCP3 staining was used to identify spread spermatocytes at different stages of meiosis . To test if the correlation between HORMAD1/2 depletion and SC formation also exists in cells that fail to form proper SC on all homologue pairs , we examined the behaviour of HORMADs in Smc1β−/− spermatocytes , which are partially defective in SC formation [48] . SMC1β is a meiosis-specific mammalian cohesin subunit [49] . In the absence of SMC1β , chromosome axes are shorter than in WT and chromosomes frequently fail to form normal SCs , as evidenced by a lack of SYCP1 along AEs of a subset of condensed chromosomes . Consequently , spermatocytes are eliminated by the mid pachytene checkpoint [48] . In nuclear spreads of Smc1β −/− spermatocytes that are at a meiotic stage equivalent to pachytene as judged by their shortened chromosome axes , HORMADs are depleted from synapsed chromosome axes but remain at high levels on abnormally unsynapsed autosomal axes in all mutant “pachytene-like” cells examined ( n = 100 cells ) ( Figure 10A ) . Thus , we observe a tight correlation between SC formation and local depletion of HORMADs from axes both in WT and in Smc1β−/− mutants . To further assess the negative correlation between SC formation and axial enrichment of HORMADs , we tested whether HORMAD depletion also occurs in cases where SC forms between illegitimate partners , i . e . , between sister chromatids or between non-homologous chromosomes . REC8 is a meiosis-specific cohesin subunit that is required for normal SC formation between homologues [51] , [52] . In the absence of REC8 , sister chromatids remain close together during meiotic prophase , suggesting that some form of cohesion still exists [50] , [51] , but frequently , pairs of sister chromatids form paired AEs , between which SC can form abnormally [51] . Interestingly , we observed high levels of HORMADs only on unsynapsed chromosome axes , whereas HORMADs were depleted from synapsed chromosome axes in all Rec8−/− spermatocytes analyzed ( n = 100 cells ) ( Figure 10B ) . Thus , SC formation between sister chromatids correlates with local depletion of HORMADs from the synapsed chromosome axes . To address if SC formation between non-homologous chromosomes also correlates with depletion of HORMADs , we examined HORMAD1/2 behaviour in Dmc1−/− mutant cells ( Figure 11 ) . DMC1 is a meiosis-specific RecA homolog . In Dmc1−/− mutants , DSBs are produced but can not be repaired efficiently , probably due to a failure in homology search and homologue alignment [52] , [53] . Consequently , only short stretches of SCs form , and these tend to connect non-homologous chromosomes [52] , [53] . We find that SYCP1 levels on synapsed axes in the Dmc1−/− mutant are much lower than in WT pachytene cells ( Mann-Whitney U test , p<0 . 0001; Figures 11A , C , and D ) . SYCP1 levels in the mutant are comparable to , or slightly lower than , the levels seen in WT cells at zygotene ( p = 0 . 2838 and p = 0 . 0007 in the HORMAD2 and -1 experiments; Figures 11A , C , and D ) . These data indicate that Dmc1−/− mutant cells do not form fully matured “pachytene”-type SCs . Nevertheless , we found that SC formation in this mutant correlates with a clear reduction in the amount of axis-associated HORMADs , with both HORMAD1 and -2 showing significantly lower signals on synapsed axes than on unsynapsed ones ( p<0 . 0001; Figures 11C , D ) . Interestingly , staining intensities for HORMAD2 are similar between Dmc1−/− mutant and WT zygotene cells for axes with similar synaptic configurations ( Figure 11D ) . In contrast , median HORMAD1 levels are higher in the mutant than in WT zygotene cells ( p<0 . 0001 , for both synapsed and unsynapsed axes , Figure 11C ) . Taken together , these results reveal that DMC1-dependent progression of homologous recombination is not essential for depletion of HORMADs from axes , and we can conclude that both homologous and non-homologous synapsis correlate with local depletion of HORMADs . To test if SC formation is required for depletion of HORMADs from chromosome axes , we examined mutants lacking SYCE1 and SYCE2 , two essential components of the SC central element [11] , [14] , [54] . Neither Syce1−/− nor Syce2−/− mutant spermatocytes are able to form stable SCs , and mutant spermatocytes undergo apoptosis at a stage equivalent to mid pachytene [11] , [14] . Despite the lack of SC formation , fully formed AEs for each homologue pair appear to align in the mutants [11] , [14] . Both HORMAD1 and HORMAD2 are highly enriched on the aligned but unsynapsed axes in all mutant spermatocytes examined ( n = 100 cells for each mutant from 6 weeks old animals ) ( Figure 12 , and data not shown for Syce2−/− ) . When chromosome spreads were prepared from mixed populations of WT and mutant cells , direct comparison between cells on the same slides showed that the signal intensity of HORMAD1/2 staining is at least as high on unsynapsed axes of mutant spermatocytes as on unsynapsed axes in WT zygotene cells ( n = 100 cells were compared ) ( Figure 12 ) . In fact , HORMAD1 signal appears to be comparable between unsynapsed axes in the mutant and unsynapsed regions of sex chromosomes in WT during pachytene ( data not shown ) . Thus , there is no depletion of HORMAD1 or HORMAD2 from chromosome axes in mutants lacking SC central element components . These observations are inconsistent with the idea that SC formation and depletion of HORMADs from synapsed axes are simultaneous , but independently regulated processes in WT . To the contrary , these results suggest that there is a causal relationship between the two events , in which SC formation may directly or indirectly promote local depletion of HORMADs from the axes . Nevertheless , we can not fully exclude the possibility that previously unrecognised SC-independent functions of SYCE1 and SYCE2 are responsible for the depletion of HORMADs concomitant with synapsis . We observed a strong correlation between the accumulation of HORMADs on chromosome axes and the accumulation of γH2AX on neighbouring chromatin in WT cells ( Figure 2A and 3A ) and in all the previously discussed mutants during pre-diplotene stages ( data not shown ) . In WT mice , ATM promotes formation of γH2AX in response to SPO11-induced DSBs during leptotene and early zygotene ( Figure S5 ) [15] , [55] . ATM is not required during late zygotene and pachytene , when ATR instead is thought to be responsible for formation of γH2AX on unsynapsed chromosomal regions and for meiotic silencing of unsynapsed chromosomes ( MSUC ) [15] , [17] , [18] , [55] . The correlation between presence of γH2AX and the initial accumulation of HORMADs on axes may reflect a causal relationship between HORMAD localization and DSB formation and/or ATM/ATR activity . To test this possibility , we examined Spo11−/− and Atm−/− mutant spermatocytes [2] , [3] , [56] ( Figure S5 , 13 ) . In Spo11−/− mutants , DSBs do not form and , as a consequence , ATM does not phosphorylate H2AX during early meiotic prophase [15] , [20] , [55] . HORMADs associate normally with the developing chromosome axes in leptotene and early zygotene spermatocytes in both Spo11−/− and Atm−/− mutants ( Figure S5 ) . Hence , neither DSBs nor ATM activity is required for accumulation of HORMADs on chromosome axes in early prophase . Despite extensive asynapsis and elimination of spermatocytes by the mid pachytene checkpoint , incomplete SCs can form in the Spo11−/− mutant [2] , [3] , [15] . In the absence of DSBs , homologues do not pair and align with one another and SCs frequently form between non-homologous chromosome axes [2] , [3] . Similar to Dmc1−/− mutants , the intensity of SYCP1 staining in Spo11−/− cells is comparable to staining in WT zygotene cells , and is much lower than in WT pachytene cells , indicating that mature “pachytene-type” SCs do not form in Spo11−/− mutants ( Figure S6 ) . Nevertheless , combined immunostaining of HORMADs , SYCP3 and SYCP1 shows that both HORMADs are depleted from synapsed chromosome axes in mutant cells ( n = 100 cells ) ( Figure 13A and S6 ) . Similar to Dmc1−/− mutants , HORMAD1 levels on both synapsed and unsynapsed chromosomes appear higher in the Spo11−/− mutant than in WT zygotene cells ( Figure S6 ) . We conclude that neither DSB formation nor ongoing recombination is essential for reciprocal distribution of SYCP1 and HORMADs along chromosome axes . ATR , TOPBP1 ( an activator of ATR ) and γH2AX frequently accumulate in a restricted chromatin domain in Spo11−/− spermatocytes at a stage that is believed to be equivalent to pachytene ( i . e . , in which a significant amount of SC formation is evident ) [15] , [19] , [20] , [55] . This γH2AX-rich domain was termed the pseudo-sex body because it resembles the transcriptionally silenced sex body in WT spermatocytes but rarely overlaps with the sex chromosomes [15] , [19] , [55] . The pseudo-sex body overlaps with a subset of unsynapsed chromosome axes and effective MSUC is observed in these regions [19] . It is believed that spatially restricted ATR activity is responsible for the formation of pseudo-sex body [15] , [19] , [55] . Importantly , many unsynapsed chromosome axes do not overlap with the pseudo-sex body in Spo11−/− spermatocytes [19] . This situation permitted us to test if ATR activity , marked by accumulation of γH2AX , is needed for preferential accumulation of HORMADs on unsynapsed chromosomes . Combined IF of HORMADs , SYCP1 and γH2AX in Spo11−/− spermatocytes shows that levels of HORMADs are higher on unsynapsed axes than on synapsed axes both inside and outside of pseudo-sex bodies in all observed cells ( Figure 13B , 13C ) . This result suggests that ATR activity and MSUC are not a prerequisite for HORMAD1/2 accumulation on unsynapsed chromosomes . Such a conclusion is also consistent with the published localization pattern of ATR and TOPBP1 in WT spermatocytes . These two proteins co-localize during meiosis [57] . During zygotene , they appear as dot-like foci on unsynapsed axes , whereas during pachytene , they continuously coat the unsynapsed sex chromosome axes and spread to the surrounding silenced sex chromatin [18] , [45] , [57] . Overall , this localization patter is similar to that of HORMADs in that all of these proteins are restricted to unsynapsed AEs during zygotene and pachytene [18] , [57] . Importantly , however , HORMAD1/2 staining coats unsynapsed axes more continuously than TOPBP1 during zygotene ( Figure S7A ) . This difference further supports the idea that axis association of HORMADs is not dependent on ATR activity and MSUC . Although HORMAD levels are always higher on unsynapsed than synapsed axes in Spo11−/− cells that formed full-length AEs , HORMADs accumulate to especially high levels on a localized subset of unsynapsed axes within a significant fraction of the mutant cells ( bottom rows of Figures 13B and 13C ) . This phenomenon is more frequently observed for HORMAD2 . Importantly , the chromosome axes that have very high HORMAD staining are nearly always located within the pseudo-sex bodies of such cells ( 99/102 cells for HORMAD1 and 41/42 cells for HORMAD2 ) ( Figures 13B and 13C ) . When we examined mutant cells with pseudo-sex bodies more closely , we found three predominant patterns of HORMAD1/2 staining relating to SC formation and developmental stage . In a minority of cells , little SC formation is observed ( 34% , n = 397 ) , suggesting that these cells are equivalent to late zygotene/early pachytene in WT [15] . In these cells , all unsynapsed axes display comparable HORMAD levels ( n = 72 and n = 64 for HORMAD1 and -2 , respectively ) ( data not shown ) . The remainder of cells have more extensive ( non-homologous ) SC formation , from which we infer that these cells represent a more advanced developmental stage . These cells can be subdivided into two groups , depending on whether HORMAD levels on unsynapsed axes are comparable inside vs . outside pseudo-sex bodies ( top rows in Figures 13B and 13C ) , or HORMAD levels are substantially elevated within pseudo-sex bodies as compared to axes that lie outside ( bottom rows in Figure 13B and 13C ) . A similar pattern is observed if pseudo-sex bodies are detected by accumulation of TOPBP1 instead of γH2AX ( Figures S7B and S7C ) . Because pseudo-sex bodies are readily detected in cells without hyper-accumulation of HORMADs , we can conclude that pseudo-sex body formation and the restriction of ATR activity to a subset of unsynapsed chromosomes in Spo11−/− mutants is unlikely to be a downstream consequence of additional accumulation of HORMADs . The fact that HORMAD hyper-accumulation ( when it is seen ) is nearly always associated with pseudo-sex bodies raises the possibility that the presence of high ATR activity and/or other MSUC components supports the accumulation of increased amounts of HORMADs on unsynapsed chromosome axes at more advanced stages of meiosis . We speculate that this pattern in Spo11−/− cells might be related to the hyper-accumulation of HORMADs on unsynapsed portions of the X and Y within the sex body in normal cells ( e . g . , Figures 2 and 3 ) . Localization of budding yeast Hop1/HORMA-domain protein is regulated by the pachytene checkpoint 2 protein ( Pch2 ) [58] , [59] . Specifically , Pch2 is required for the depletion of Hop1 from chromosomal regions where Zip1 , the yeast transverse filament protein , is abundant [58] . Pch2 is also required for one branch of the meiotic prophase checkpoint and for timely repair of DSBs [58]–[60] . The mouse Pch2 homolog is TRIP13 . Analysis of animals homozygous for a hypomorphic mutation ( Trip13RRB047/RRB047; abbreviated Trip13hypo for simplicity ) indicates that TRIP13 is required for timely and efficient repair of meiotic DSBs , but appears to have no meiotic checkpoint function [61] ( unpublished data of I . Roig , M . Jasin and S . Keeney ) . In spite of defective DSB repair , Trip13hypo spermatocytes form apparently normal looking SCs [61] . To test if PCH2/TRIP13 has a conserved role in the regulation of HORMA-domain proteins , we examined HORMAD localization in the Trip13hypo mutant . Remarkably , both HORMADs remain detectable at high levels on synapsed axes in all examined mutant spermatocytes during zygotene ( n = 100 ) and in the vast majority of mutant spermatocytes during pachytene ( HORMAD1 100% , n = 300; HORMAD2 99 , 2% , n = 500 cells ) ( Figure 14 ) . HORMADs persist on desynapsing axes during diplotene but do not accumulate further . The persistently high level of HORMAD1/2 staining in areas where SC has formed in this mutant is unlike any of the patterns observed in WT or any of the other mutants examined . Therefore , we conclude that TRIP13 is required for the normal depletion of HORMADs from synapsed chromosome axes . Furthermore , the ability to readily detect HORMADs in synapsed regions in the Trip13hypo mutant further reinforces the conclusion that the normal pattern of HORMAD depletion observed in WT and many mutants is not a trivial consequence of epitope masking by the SC ( see above ) . Interestingly , although there is a clear defect in depletion of HORMAD2 from synapsed axes in the Trip13hypo mutant , HORMAD2 levels nevertheless do appear higher on the unsynapsed sex chromosomes than on synapsed autosomes in cells where autosomal SC formation is complete ( Figure 14B , second row ) . Similar enrichment on the sex chromosomes is not apparent for HORMAD1 ( Figure 14A , second row ) . Most Trip13hypo spermatocytes undergo apoptosis during pachytene , but because the mutation reduces but does not fully eliminate Trip13 gene expression , a small subset of cells are able to progress further , to diplotene and beyond ( [61] , and unpublished data of I . R . , M . J . , and S . K . ) . Hence , it is possible that the slight enrichment of HORMAD2 on sex chromosomes is a consequence of residual TRIP13 activity in a subset of Trip13hypo spermatocytes that are able to advance the furthest in meiosis . Alternatively , it may be that restriction of high ATR activity to the sex chromosomes during sex body formation , which occurs apparently normally in the majority of pachytene Trip13hypo spermatocytes , promotes additional accumulation of HORMAD2 on sex chromosome axes in spite of a general defect in depletion of HORMAD2 from synapsed regions . The latter interpretation is consistent with the frequent hyper-accumulation of HORMAD2 observed on unsynapsed axes within pseudo-sex bodies of Spo11−/− spermatocytes ( see above ) .
One of the most striking findings from this study is the pronounced depletion of HORMADs from chromosome axes that have undergone SC formation , both in WT and in mutants where SCs form inefficiently and/or form between illegitimate partners ( non-homologous chromosomes or sister chromatids ) . Several mechanisms , not mutually exclusive , could underlie this inverse correlation between HORMAD localization and the SC . First , SC formation and HORMAD1/2 depletion could be promoted concurrently and independently by another process , such as progression through meiosis , homologue alignment , and/or early DSB repair steps . Alternatively , there may be a causal relationship between SC formation and localized HORMAD1/2 depletion . In this case , either SC formation promotes HORMAD1/2 depletion ( directly or indirectly ) , or axis-associated HORMADs antagonize SC formation . In C . elegans , the HORMA-domain protein HTP-1 and the SC component SYP-1 acquire an almost mutually exclusive , reciprocal localization pattern at the end of pachytene [37] , and HTP-1 is also required to prevent premature SC formation between non-homologous chromosomes , which suggests that HTP-1 may inhibit SC formation under some conditions [32] , [33] . A similar relationship might exist between SCs and axis-associated HORMADs in mice , but such putative inhibition of SC formation does not provide a straightforward explanation for HORMAD1/2 behaviour in the mutants examined in this study . For example , HORMADs are not depleted from axes in the absence of SC central element components SYCE1 and -2 ( Figure 12 ) . If HORMAD depletion is a necessary upstream precondition for SC formation , it is not obvious why HORMAD depletion would be blocked by the absence of central element components , which presumably would cause a relatively late block in SC formation . Moreover , the robust formation of SC in the Trip13hypo mutant [61] , despite persistent axial HORMAD localization ( Figure 14 ) , argues against HORMAD depletion being a strict prerequisite for synapsis . The Syce1 and Syce2 mutant phenotypes also argue against the possibility that HORMAD depletion and SC formation are independently induced by another process . For example , extensive AE development , pairing and alignment of homologues , and early steps in DSB repair upstream of SC formation all appear to occur in a timely fashion in these mutants [11] , [14] , implying that these events are not sufficient to trigger HORMAD depletion . Moreover , it seems unlikely that the spermatogenic arrest in Syce1 and Syce2 mutants can account for the defect in HORMAD depletion , because Dmc1 , Spo11 , Smc1 , and Rec8 mutants also undergo spermatogenic arrest [13] , [15] , [48] , [50] , [51] , yet these mutants successfully achieve HORMAD depletion in regions where SC has formed . In summary , although we cannot exclude alternative explanations for the inverse correlation between SC formation and HORMAD localization , we favour the interpretation that SC formation itself , directly or indirectly , promotes localized depletion of HORMADs from synapsed axes . If SC formation does promote depletion of HORMADs from AEs , this could occur through various mechanisms . One possibility could be that SC formation is needed indirectly for meiotic “cell cycle” progression to a zygotene/pachytene-like stage that is permissive for HORMAD1/2 depletion . This possibility seems unlikely , however . WT cells complete full-length AE assembly only in late zygotene , after SCs have already formed along a large fraction of chromosomes . In Syce1 and Syce2 mutants , full-length AEs assemble and align in a large fraction of spermatocytes , which indicates that these cells reach a stage that is equivalent to late zygotene/early pachytene [11] , [14] . Since WT cells at this stage would have commenced depletion of HORMADs , we infer that meiotic progression defects in Syce1 and Syce2 mutants are unlikely to account for lack of HORMAD1/2 depletion from axes . Moreover , as noted above , HORMAD1/2 depletion still occurs in mutants that are competent to assemble at least some SC , but that have similar spermatogenic blocks as Syce1−/− and Syce2−/− [13] , [15] , [48] , [50] , [51] . Based on these considerations , and taking into account the observation that HORMAD depletion is highly specific for axes that have engaged in SC assembly , we suggest that the simplest interpretation of our findings is that the accumulation of SC components on AEs , on their own or in combination with other proteins , induces localized HORMAD depletion . How might this work ? SC formation is required for crossing over and efficient DSB repair in mice [11] , [12] , [14] , [62] , [63] . Hence , one could argue that SC formation promotes HORMAD1/2 depletion solely via promoting DSB repair . However , HORMADs are depleted from illegitimately synapsed axes in Spo11−/− and Dmc1−/− mutants ( Figure 11 , 13 , S6 and S7 ) , in which DSBs either do not form or are not repaired [2] , [3] , [52] , [53] . Thus , progression of homologous recombination is not strictly required for HORMAD depletion from synapsed axes . Nevertheless , we note that more HORMAD1 remains on synapsed axes in Spo11−/− and Dmc1−/− mutants than in WT , and HORMAD1 levels on unsynapsed axes also appear higher in these mutants ( Figure 11 , 13 , S6 and S7 ) . One possibility is that HORMAD1 somehow distinguishes aligned homologues from interactions between non-homologous chromosomes . Alternatively , it is possible that efficient HORMAD1 depletion may be partially dependent on normal execution of DSB repair . Precedent for such a dependency is found in C . elegans , where the timing and spatial organization of HORMA-domain protein depletion from chromosomes is intimately tied to recombination [37] . In mice , early steps in recombination are required for the robust formation of homologous SCs , so it is possible that the DSB repair process could support HORMAD1 depletion indirectly via promoting normal SC formation . Indeed , SYCP1 staining is relatively weak in Dmc1−/− and Spo11−/− mutants , most similar to the SYCP1 staining of freshly formed SCs in WT zygotene cells ( Figure 11 and S6 ) . Thus , non-homologous SCs might be qualitatively different from normal pachytene SCs ( e . g . , immature , or unstable ) . Moreover , we find a negative correlation between SYCP1 levels and residual HORMAD1/2 levels on synapsed axes in WT , which indicates that SC maturation might influence the efficiency of HORMAD1/2 depletion ( Figure 5 ) . Finally , an alternative way to account for the correlation between recombination progression and the efficiency of HORMAD1 depletion is to propose that both SC formation and the production of late recombination intermediates promote HORMAD1 dissociation independently from each other . Although we can not exclude this possibility , behaviour of HORMADs on sex chromosomes argues against this idea . Even though DSBs are repaired on unsynapsed regions of sex chromosomes during late pachytene in WT cells ( as judged by the disappearance of axis associated foci of RAD51 and RPA ) [41] , [45] , [46] , HORMAD1/2 levels nonetheless remain high on these unsynapsed axes during pachytene and diplotene ( Figures 2 , 3 , 4 ) . Hence , we infer that progression of DSB repair is not sufficient to trigger robust depletion of HORMADs from sex chromosomes . In summary , we suggest that a simple interpretation of our data is that SC formation is required for depletion of HORMADs from axes , and that SC assembly can promote HORMAD1/2 depletion in the absence of the DSB repair process . Thus , we propose that the reciprocal distribution of SYCP1 and HORMADs on axes in normal meiosis is a consequence of HORMAD1/2 depletion from chromosome axes in response to SC formation . In contrast , DSB formation and repair are not absolutely required for depletion of HORMADs , although DSB repair steps downstream of SC formation may increase the efficiency of SC-promoted HORMAD1 depletion . We show here that TRIP13 is required for depletion of HORMADs from synapsed axes ( Figure 14 ) . Because HORMAD1/2 depletion from SCs can occur in the presence of unrepaired DSBs in a Dmc1−/− mutant , we infer that the persistence of HORMADs on synapsed axes in Trip13hypo spermatocytes is unlikely to be a consequence of the delayed DSB repair in this mutant . Instead , it is more likely that TRIP13 promotes depletion of HORMADs from synapsed axes independently from DSB repair . TRIP13 activity could mediate depletion of HORMADs from axes in response to SC formation or , alternatively , TRIP13 could modify properties of SCs in a manner that promotes HORMAD1/2 depletion from axes . It is also possible that TRIP13 and SC act independently from each other such that neither is sufficient alone , but in combination they promote HORMAD1/2 depletion from axes ( Figure S8 ) . Budding yeast Hop1 and the SC transverse filament protein , Zip1 , exhibit reciprocal localization patterns along chromosome axes , and Pch2 is required for the depletion of Hop1 from Zip1-rich regions , which most likely represent fully synapsed axes [58] . It is not known whether Hop1 is depleted from chromosome axes in response to progression in DSB repair or synapsis formation per se . Nevertheless , the apparent similarity between the behaviour of HORMA-domain proteins in yeast and mouse suggests that Pch2/TRIP13 supports depletion of Hop1/HORMADs from synapsed chromosome axes in both organisms . The regulated depletion of HORMA-domain proteins from synapsed chromosomes is a striking feature of meiosis shared by budding yeast , rice , C . elegans and mouse [37] , [58] , [64] , [65] . The conservation of this phenomenon suggests that removal of HORMA-domain proteins from synapsed axes may play an important role during meiosis . The cytological studies presented here do not allow us to definitively determine the functions of mammalian HORMADs . Nevertheless , our results in combination with published analyses of HORMA-domain proteins in other organisms allow us to speculate about the possible roles of HORMADs ( Figure S8 ) . We discuss here four possible functions that might no longer be needed , or that might need to be actively down-regulated , after SC formation . The continued presence of HORMADs on chromosomes after diplotene suggests the possibility of a role in meiosis after the completion of recombination . C . elegans HTP-1 is required for maintenance of centromeric sister chromatid cohesion during the first meiotic division [37] . We found that HORMADs localize near centromeres in metaphase I spermatocytes ( Figure 6 . ) , suggesting that HORMADs may also be involved in this essential characteristic of meiosis-specific chromosome behaviour in mice . The behaviours of the two HORMADs are similar , but not identical , so it is not yet possible to determine if they are involved in identical or only partially overlapping processes . For example , HORMAD2 is more likely than HORMAD1 to show preferential accumulation within pseudo-sex bodies ( Figure 13 and S7 ) . We also saw differences in localization during WT diplotene in males , with HORMAD2 more highly enriched on the sex chromosomes than on the desynapsing autosomes , as compared with HORMAD1 ( Figure 2 , 3 and 4 ) . These differences may be a reflection of different abundance of the two proteins ( their relative amounts are not yet known ) , or may reflect a genuine difference in the relationship between MSUC pathway components and the two HORMADs . There are also differences in the extent of overlap between forming SCs and the two HORMADs during zygotene , with HORMAD2 tending to spread more into synapsed regions than HORMAD1 ( Figure 4 and 5 ) . This difference may indicate that the two proteins are depleted from synapsed axes with different kinetics , and/or that they respond to different SC-associated processes . The resolution of these questions will require the generation of HORMAD mutant mice , which is the next logical step to precisely determine the meiotic functions of HORMADs in mammals .
Female NZW rabbits and female Hartley guinea pigs were used for immunization experiments . For expression analysis , immunofluorescence and immunoblot wild type ( WT ) testis tissue was isolated from C57BL/6JOlaHsd mice and WT embryonic ovaries were obtained from NMRI mice . For staging embryonic development the day of detection of a vaginal plug was marked as 0 . 5 days post coitum ( dpc ) . Analysed null mutant mice strains ( Smc1β−/− , Syce1−/− , Syce2−/− , Rec8−/− , Dmc1−/− , Spo11−/− , Atm−/− ) have been described previously [3] , [11] , [14] , [48] , [51] , [53] , [56] . The commercially available ES clone with the gene trap-disrupted allele of Trip13 was described previously [61] . The Trip13RRB047/RRB047 strain we studied was generated by I . Roig , M . Jasin and S . Keeney ( unpublished ) . This mouse line carries the same mutation as the previously described Trip13 mutant line but the line was generated independently from the previous study [61] . Experimental animals were compared with controls from the same litter ( when possible ) or from other litters from the same mating . All animals were used and maintained according to regulations provided by the animal ethical committee of the Technische Universität Dresden . Total RNA was isolated from fresh adult mouse testis tissue and frozen embryonic gonads using the RNeasy Mini Kit ( Qiagen ) . Mouse total RNA samples from different mouse somatic tissues were purchased via Ambion ( liver , brain , thymus , heart , lung , spleen and kidney , Cat#7800 ) and Zyagen ( mammary gland , pancreas , placenta , salivary gland , skeletal muscle , skin , small intestine , spinal cord , tongue and uterus , Cat#MR-010 ) . One or half micrograms of total RNAs were reverse transcribed using Superscript III ( Cat#18080-044 , Invitrogen ) and oligo dT ( 20 ) primers . In no-RT controls the reaction mixture contained water instead of reverse transcriptase . RT-PCR was performed with gene specific primers: 5′- TGTTTGTCACCTACACTCAGG-3′ and 5′-GTAAGGAAGAAGAAACTATGC-3′ for Hormad1 , 5′- CCTGCAAGTTACAGACAGATA-3′ and 5′-AACCTGTGAGTTGGAATCCT-3′ for Hormad2 . The primes for amplifying Sycp3 , Mvh , Xist , S9 and S12 as controls were described previously [80] . The cycling conditions were: 94°C 3 min; 94°C 30 s , 54°C 30 s , and 72°C 25 s for 30 cycles; and 72°C 7 min . RNA-Isolation from FACS sorted ovarian cells and RT-PCR on these templates were performed as described previously [80] . HORMAD1 and -2 are most similar in their HORMA-domain containing N-terminal region ( Figure S2B ) . Their C-terminus differs considerably . To avoid cross-reactivity , we raised antibodies against the less conserved C-terminal domain of HORMADs . The cDNA fragments encoding for the C-terminal 142 amino-acids of Hormad1 ( H1C ) and the C-terminal 72 amino-acids of Hormad2 ( H2C ) were sub cloned into the Escherichia coli expression vectors pDEST17 ( Cat#11803012 , Invitrogen ) and pDEST15 ( Cat#11802014 , Invitrogen ) , respectively . H1C was expressed in fusion with N-terminal 6xHis-tag and purified on Ni Sepharose ( Cat#17-5318-01 , Amersham , GE Healthcare ) . H2C was expressed in fusion with an N-terminal GST-tag and purified on Glutathione Sepharose ( Cat# 17-5132-01 , Amersham , GE Healthcare ) . One guinea pig and two rabbits were immunized with each of the two recombinant proteins ( H1C and H2C ) [81] . Polyclonal antibodies were affinity purified on antigen coupled Sepharose Beads ( Cat# 17-0906-01 , Amersham , GE Healthcare ) . Specificity of affinity purified anti-Hormad1 ( rabbit polyclonal AB209 and AB153 and guinea pig polyclonal AB146 ) and anti-Hormad2 ( rabbit polyclonal AB205 and AB211 and guinea pig polyclonal AB104 ) antibodies were tested by immunoblot analysis of testis extracts . Anti-HORMAD1 and anti-HORMAD2 antibodies recognise different proteins in testis extracts ( Figure S3 ) . All of our affinity purified anti-HORMAD1 antibodies recognise a protein , which is approximately 50 kDa based on its electrophoretic mobility . The anti-HORMAD2 antibodies recognise a protein that migrates as a 40 kDa protein during SDS poly-acryl amide electrophoresis . The estimated masses of the recognised proteins are consistent with the calculated molecular mass of HORMAD1 ( 43 kDa ) and HORMAD2 ( 35 kDa ) . AB205 , 209 and 211 recognize additional proteins other than HORMAD1 and 2 in immunoblots ( Figure S3 ) . These cross-reactive proteins are enriched in the detergent soluble fraction of testicular cells as opposed to HORMAD proteins that are enriched in the detergent insoluble ( crude chromatin ) fractions of testis extracts . Testis tissue from 20 days old C57BL/6 mice were minced with a surgical blade and homogenized by a loose-Dounce homogenizer with about 30 strokes in ten times volume ( w/v ) of PBS pH 7 . 4 containing 1 mM EDTA ( Cat#E5134 , Sigma ) , 1× Complete EDTA free protease inhibitor cocktail ( Cat#11873580001 , Roche ) , 25 mM b-Glycerophosphate ( Cat#35675 , Merck ) , 10 mM Na4P2O7 ( Cat#71515 , Sigma ) , 50 mM NaF ( Cat#P0759S , NEB ) , 2 mM Na3VO4 ( Cat#P0758L , NEB , ) and 1 mM PMSF ( Cat#10236608001 , Roche ) . The cell suspension was filtered through a 40 µm sieve ( BD BioScience , San Jose , CA ) and centrifuged for one minute at 960 rcf . The pellet was resuspended in 1 ml of RSB-G with 0 . 25% NP-40 ( Cat#74385 , Sigma , ) , 1 mM DTT ( Cat#D9779 , Sigma , ) containing protease and phosphatase inhibitors listed above and then centrifuged at 10 , 000 rcf for one minute [82] . The supernatant was collected and used for western blot analysis ( NP-40 soluble testis fraction ) . The pellet was washed once with RSB-G ( without NP-40 ) and once with RIPA buffer containing protease and phosphatase inhibitors listed above . Following one minute centrifugation with 10000 rcf a pellet was obtained , which was dissolved by five minutes of boiling in SDS loading buffer and used for immunoblot analysis of HORMAD antibodies ( detergent insoluble testis fraction ) . Proteins from testis extracts were separated on 13% SDS poly-acryl amide gels and blotted onto PVDF membrane ( Cat#P2938 , Sigma ) . The membranes were incubated with antibodies at 1∶500 ( AB209 ) , 1∶1000 ( AB153 ) , 1∶500 ( AB146 ) , 1∶200 ( AB205 ) , 1∶2000 ( AB211 ) and at 1∶500 ( AB104 ) dilutions in Western-incubation buffer ( 5% milk , Tris-buffered saline plus 0 . 05% Tween 20 ) . Membrane bound primary antibodies were detected by 1∶10000 diluted HRP-coupled Goat Anti-Rabbit IgG or Goat Anti-Guinea Pig ( Cat#111-035-144 and Cat#106-035-003 , Jackson ImmunoResearch ) antibodies using the Immobilon Western Chemiluminescent HRP Substrate ( Cat# WBKLS0100 , Millipore ) . “Standard” nuclear surface spreads of spermatocytes and oocytes were prepared either as described previously or according to a modified protocol [83] . Briefly , cell suspensions were prepared in PBS by vigorous pipetting of the gonads . In the modified protocol , slides were covered with a thin layer of 0 . 25% NP-40 ( Sigma ) . Cell suspensions of fresh or frozen testis or ovaries in PBS pH 7 . 2 ( one third volume of NP-40 ) were pipetted onto the NP-40 surface and incubated for no longer than 2 min before adding drop by drop three times the NP-40 volume of S-fix fixative ( 1% paraformaldehyde , 10 mM sodium borate buffer pH 9 . 2 ) . Samples were incubated for two hours at room temperature in a humid chamber . Following fast drying under a hood , the slides were washed two times for one minute with 0 . 4% Agepon ( AgfaPhoto ) and another three times for one minute with water . Slides were used immediately or kept at 4°C in PBS pH 7 . 4 until IF staining . The “disrupted” nuclear spreads were prepared by extending incubation time of cells in 0 . 25% NP-40 up to 20 min before addition of S-fix . For cryo-sections , adult testes were fixed in 2% formaldehyde in PBS pH 7 . 4 , 0 . 1% Triton X-100 at room temperature for 20 min . Following fixation , testis was placed into 30% sucrose overnight at 4°C and then frozen on dry ice in “O . C . T . ” ( Sakura Finetek Europe ) . 8 µm thick sections were cut and dried onto slides followed by five minute fixation by 2% formaldehyde in PBS pH 7 . 4 , 0 . 1% Triton X-100 . The sections were washed in PBS pH7 . 4 and immediately used for IF staining . Before immunostaining surface spreads or cryo-sections , samples were blocked with blocking buffer [2% BSA ( Cat# A2153 , Sigma ) , 10% goat serum ( Cat# ab7481 , Abcam ) , 0 . 1% Triton X-100 in PBS pH 7 . 4] for 30 min . Primary antibodies diluted in blocking buffer were applied to samples for three hours or overnight at 37°C in a humid chamber . Slides were washed three times with PBS and incubated with secondary antibodies for 1 h , and finally mounted in Vectashield mounting medium with DAPI ( Cat#H-1200 , Linaris ) . Primary antibodies used in this study were as follows: rabbit anti-HORMAD1 AB209 ( 1∶2000 ) and AB153 ( 1∶1000 ) , guinea pig anti-HORMAD1 AB146 ( 1∶500 ) , rabbit anti-HORMAD2 AB205 ( 1∶2000 ) and AB 211 ( 1∶3000 ) , guinea pig anti-HORMAD2 AB104 ( 1∶500 ) , monoclonal mouse anti-SYCP3 II52F10 ( 1∶100 , a gift from R . Jessberger ) [84] , rabbit anti-SYCP3 ( 1∶1000 , Cat#ab15092 , Abcam , Cambridge , MA ) , mouse anti γ-H2AX ( 1∶3000 , Cat#05-636 , Upstate/Millipore ) , rabbit anti-SYCP1 ( 1∶1000 , Cat#ab 15090 , Abcam ) , rabbit anti-hRPA70 ( 1∶500 , a gift from E . Marcon ) [46] , rabbit anti-hH1t ( 1∶1000 , a gift from E . Marcon ) [85] , guinea pig anti H1t ( 1∶5000 , a gift from M . A . Handel ) [86] , rabbit anti-TOPBP1 ( 1∶1000 , a gift from J . Chen ) [87] , rabbit anti-TRF1 #644 ( 1∶2000 , a gift from T . de Lange ) , human anti-Centromere protein ( 1∶1000 , Cat#15-235 , Antibodies Inc . ) . Goat secondary antibodies conjugated with either Alexa Fluor 488 , 568 or 647 ( Cat# A11034 , A11036 , A21245 , A11073 , A11075 , A21450 , A21090 , A11031 , A11029 , A21236 , Molecular Probes/Invitrogen ) were used at a dilution of 1∶600 . Donkey secondary antibodies conjugated with DyLight488 , 594 or 649 ( Jackson ImmunoResearch Europe Ltd . ) were used at 1∶300 dilutions . Fluorescence was visualized with Zeiss Axiophot fluorescence microscope . To stain HORMADs on cryo-sections we only used AB153 and AB104 , two antibodies that are highly specific to HORMAD1 and -2 , respectively . In nuclear surface spreads of spermatocytes , where most of the detergent soluble cell material is removed , all antibodies raised against the same antigen ( H1C or H2C ) showed similar staining patterns . To conclude on the pattern of fluorescence staining for various proteins , staining patterns were assessed by eye under the microscope in at least 100 spread nuclei . As a second step , at least 30 nuclei of particular meiotic stages were first identified based on the localization pattern of SYCP3 AE component , then imaged at appropriate wavelengths to determine the pattern of co-stained proteins such as HORMADs , TOPBP1 or SYCP1 , etc . At least two independent sets of nuclear spreads were examined from each mutant . Apart from the Rec8−/− mutant , we examined nuclear spreads from at least two different animals . Unless indicated differently , the panels shown in the figures were the exclusive or predominant patterns seen . To assess changes in chromosome associated staining of HORMAD1 , HORMAD2 and SYCP1 we quantified IF signals specific to these proteins along synapsed and unsynapsed chromosome axes in at least 15 randomly picked nuclei of WT and Dmc1−/− mutants . To compare IF signal levels in WT and Dmc1−/− mutant we prepared nuclear spreads parallel from mutant and control animals . Spread nuclei were co-stained with antibodies recognising SYCP3 , SYCP1 and either one of the HORMADs . Mutant and WT spreads were stained at the same time with the same mixes of antibodies . Imaging of the cells in each experiment were carried out in the same day with the same microscope and camera settings and TetraSpeck Fluorescent Microspheres Size Kit , T14792 Molecular Probes , Invitrogen were used to control for possible changes in illumination during the course of imaging . Measurement of IF signal was carried out with the help of Adobe Photoshop CS4 Extended version . SYCP3/axis staining was used to select synapsed and unsynapsed chromosome axes that belong to a single chromosome . In the second step , we measured total IF signal intensity of HORMADs and/or SYCP1 in identical-sized rectangles that were placed over straight stretches of the selected synapsed and unsynapsed chromosome axes . Signal intensities were also measured in four regions around examined chromosomes in each nucleus in order to estimate the background . Signal intensity values shown in Figure 5 and 11 are background corrected . Whenever it was possible we measured signal intensities on at least two chromosomes in each nucleus . Statistical analysis was performed with GraphPad Prism 5 . For statistical analysis Wilcoxon signed-rank test was used when paired signal intensities on unsynapsed and synapsed axes of WT zygotene chromosomes were compared . For the comparison of independent samples two-tailed non-parametric Wilcoxon–Mann–Whitney two-sample rank-sum test was used . We acknowledge that there are clear limitations to quantification of IF signal on nuclear spreads . Due to the nature of the spreading methodology variable amounts of soluble and axis associated proteins are removed from each spread nucleus . Therefore , there is considerable variation in IF signal intensities and background levels within the same sample preparation and in between sample preparations . Hence , we do not think that these measurements can be used to accurately determine fold changes in protein levels on chromosome axes . Nevertheless , we think that the presented quantifications are suitable to illustrate tendencies in the data . They also reconfirm conclusions we drew from the observation of larger number of cells in larger number of experiments . HORMAD1 and HORMAD2 orthologs were identified by blastp alignments of HORMAD1 and HORMAD2 sequences of Genbank protein database . Accession numbers of used sequences are shown in supplementary table S1 . Protein sequence alignments were prepared with ClustalW software using the entire amino-acid sequences . The tree was constructed in MEGA4 software [88] . The neighbour-joining method with Poisson correction was used . The reliability of internal branches was assessed by using 500 bootstrap replicates , and sites with gaps were ignored in this analysis . | Generation of haploid gametes in most organisms requires that homologues become connected via crossovers during meiosis . Efficient formation of crossovers depends on HORMA-domain proteins in diverse taxa . These proteins ensure that programmed meiotic DSBs are preferentially repaired from homologues , rather than from sister chromatids . This inter-homologue bias is crucial for homology search and crossovers formation . HORMA-domain proteins have been also implicated in DSB formation , in suppression of synaptonemal complex formation between non-homologous chromosomes , and in the meiotic prophase checkpoint that monitors DSB repair . Despite the importance of HORMA-domain proteins in various organisms , a role for these proteins in mammalian meiosis hasn't been reported . We examined the behaviour of meiotic mouse HORMA-domain proteins—HORMAD1 and HORMAD2—in wild-type and meiotic mutants . HORMAD1/2 preferentially accumulate on unsynapsed chromosome axes . Our data suggest that HORMAD1/2 depletion from chromosomes is a response to synaptonemal complex formation and it that is a conserved process supported by TRIP13/Pch2 AAA-ATPase . Assuming that HORMA-domain functions are conserved in mammals , we speculate that depletion of HORMADs from axes might contribute to the down-regulation of inter-homologue bias and the prophase checkpoint once homology search is completed and synaptonemal complexes form between aligned homologues . | [
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"bio... | 2009 | Mouse HORMAD1 and HORMAD2, Two Conserved Meiotic Chromosomal Proteins, Are Depleted from Synapsed Chromosome Axes with the Help of TRIP13 AAA-ATPase |
Little is known about the repertoire of cellular factors involved in the replication of pathogenic alphaviruses . To uncover molecular regulators of alphavirus infection , and to identify candidate drug targets , we performed a high-content imaging-based siRNA screen . We revealed an actin-remodeling pathway involving Rac1 , PIP5K1- α , and Arp3 , as essential for infection by pathogenic alphaviruses . Infection causes cellular actin rearrangements into large bundles of actin filaments termed actin foci . Actin foci are generated late in infection concomitantly with alphavirus envelope ( E2 ) expression and are dependent on the activities of Rac1 and Arp3 . E2 associates with actin in alphavirus-infected cells and co-localizes with Rac1–PIP5K1-α along actin filaments in the context of actin foci . Finally , Rac1 , Arp3 , and actin polymerization inhibitors interfere with E2 trafficking from the trans-Golgi network to the cell surface , suggesting a plausible model in which transport of E2 to the cell surface is mediated via Rac1- and Arp3-dependent actin remodeling .
Viral infection requires extensive subcellular trafficking , including cell entry , delivery of the genome to replication sites , and transport of viral proteins to and assembly of viral particles at the plasma membrane for egress . To this end , viruses make use of different cellular cues and signals to hijack existing endocytic and secretory pathways , cellular motor proteins , and cytoskeletal filaments . Here we examine cellular trafficking machineries utilized by alphaviruses . Alphaviruses ( family Togaviridae ) are single-stranded , positive-sense RNA viruses that produce enveloped virions . Chikungunya virus ( CHIKV ) , eastern equine encephalitis virus ( EEEV ) , Venezuelan equine encephalitis virus ( VEEV ) , and western equine encephalitis virus ( WEEV ) are the most medically important human alphaviruses that cause debilitating arthritides ( CHIKV ) or encephalitides ( EEEV , VEEV , and WEEV ) [1–3] . For instance , since December 2013 , spread of CHIKV in the Caribbean has caused tens of thousands of human infections [4] . The alphavirus genome consists of two open reading frames encoding nonstructural and structural polyproteins . Four nonstructural proteins ( nsP1-4 ) are required for transcription and replication of viral RNA , and three main structural proteins ( i . e . , capsid protein C , envelope glycoproteins E2 and E1 ) are the main constituents of virions . Alphavirus replication occurs initially at the plasma membrane [5 , 6] . Replication complexes are subsequently internalized via an endocytic process that requires a functional actin-myosin network . Following endocytosis , replication complex-containing vesicles migrate via a microtubule-dependent mechanism to the perinuclear area where they form stable , large and acidic compartments termed cytopathic vacuoles ( CPV ) -I . CPV-I structures are derived from modified endosomes and lysosomes and are associated with the alphaviral nonstructural proteins and viral RNA [7–9] . In the late stage of alphavirus infection , trans Golgi network ( TGN ) -derived vacuoles marked with the E1/E2 glycoproteins become predominant [10 , 11] . In these membrane vacuoles ( termed CPV-II ) , the viral glycoproteins are arranged in a tubular structure . CPV-II vacuoles are implicated in intracellular transport of alphavirus glycoproteins from the TGN to the site of budding on the plasma membrane prior to virus egress [8 , 12] . Results from small interfering RNA ( siRNA ) screens identified a number of host factors that possibly promote or restrict nonpathogenic alphavirus infection [13–15] . However , detailed mechanistic studies regarding the role of host factors in alphavirus trafficking have not been performed . In this study , we used an RNAi-based screen to identify and validate trafficking host factors required for infection by the pathogenic VEEV and other pathogenic alphavirus relatives . Mutagenesis- , chemical inhibitor- and imaging-based approaches were further used to validate and decipher the role of these factors in alphavirus infection .
siRNA pools targeting each of 140 human trafficking genes were transfected into HeLa cells . A non-targeting siRNA was used as a control . Cells were subsequently infected with VEEV ( chosen as a prototype alphavirus for the screen ) for 20 h and then fixed and stained with a VEEV E2 glycoprotein-specific antibody ( Fig 1A ) . Staining was performed without permeabilization to detect only E2 present on the cell surface . Cell number and infection rate were determined using quantitative high-content image-based analysis ( see Materials and Methods ) . The infection rate of control siRNA-transfected cells was optimized to yield , on average , 70–80% . Analysis of the results revealed that siRNAs against 51 host trafficking factors decreased VEEV infection rate by >30% ( Z-score <-2 ) ( S1 Table ) . To confirm results of the primary screen and to rule out potential off-target effects of individual siRNAs , we performed a secondary screen of deconvoluted siRNA pools . A hit was considered validated if at least 2 siRNAs from the set of 4 individual siRNAs targeting the gene product reduced the VEEV infection rate by ≥30% and had a p-value of <0 . 05 versus control siRNA-transfected wells . Wells that had low normalized cell numbers ( final cell number <70% of the control siRNA-transfected well ) due to combined effects of siRNA toxicity and VEEV cytopathic effects were excluded from further analyses . Analysis of the results led to validation of 19 ( 61% ) out of the 31 primary hits ( S2 Table ) . Importantly , the list of validated hits was enriched for crucial regulators of the actin cytoskeleton . In particular , knockdown of four subunits of the heptameric Arp2/3 complex , ARPC4 , ARPC5 , ARPC1B ( S2 Table ) , and ACTR3 ( actin-related protein 3; Arp3 ) ( Fig 1B ) , significantly inhibited VEEV infection . In addition , Ras-related C3 botulinum substrate 1 ( Rac1 ) , and phosphatidylinositol 4-phosphate 5-kinase type 1-alpha ( PIP5K1-α or PIP5K1A ) were also identified as hits ( Fig 1B ) . The Arp2/3 complex plays a central role in actin dynamics by controlling filament nucleation [16 , 17] . Rac1 is a member of the Rho GTPase family and among its many functions modulates actin cytoskeleton organization [18] . PIP5K1-α is a lipid kinase involved in the synthesis of the signaling molecule phosphatidylinositol-4 , 5-bisphosphate ( PI4 , 5P2 ) , which is a central regulator of the actin cytoskeleton in response to multiple signals [19] . Our siRNA results were further confirmed using single siRNAs against Rac1 , Arp3 , and PIP5K1-α from another source ( Fig 1B , siRNAs 5–7 ) . We also observed a ≈10 to >30 fold reduction in VEEV titer following knockdown of these host factors ( Fig 1C ) . Finally , siRNA-mediated knockdown of Rac1 , Arp3 , or PIP5K1-α inhibited infection of CHIKV ( S1A and S1B Fig ) . These results indicate that Rac1 , Arp3 , and PIP5K1-α play an important role in alphavirus infections . To validate the role of Rac1 and Arp3 in VEEV infection , we tested whether the Rac1 inhibitors EHT1864 and NSC23766 [20 , 21] and the Arp3 inhibitors CK548 and CK869 [22] could block VEEV infection . Upon treatment of HeLa cells with either of these types of inhibitors , VEEV infection rates were reduced in a dose-dependent manner ( Fig 2A and 2B ) . Similar results were observed when the Rac1 inhibitors EHT1864 or NSC23766 or the Arp3 inhibitor CK548 , were tested in primary human astrocytes ( Fig 2C and 2D ) . These inhibitors were also effective in reducing infection rates of other alphaviruses . EHT1864 inhibited infections by CHIKV and the closely related Sindbis virus ( SINV ) , and CK548 decreased CHIKV , SINV , EEEV , and WEEV infection rates ( S2A and S2B Fig ) . None of the treatment conditions in either assays resulted in cytotoxicity . Overall , our results further confirm the importance of host factors Rac1 and Arp3 in alphavirus infection . To determine if the function of Rac1 in alphavirus infection required Rac1’s GTPase activity , we established tetracycline-inducible 293 Flp-In T-REx cell lines that express chloramphenicol acetyltransferase ( CAT , used as a control ) , wild-type Rac1 , constitutively active Rac1 ( G12V ) , or dominant-negative Rac1 ( T17N ) ( Fig 2E ) [23 , 24] . Rac1 expression in these cells was induced with tetracycline for 24 h , followed by infection with VEEV , or a non-alphavirus control ( Rift Valley fever virus; RVFV strain ZH501 , hereafter , RVFV ) . Expression of both Rac1 mutant variants ( G12V , T17N ) reduced VEEV but not RVFV infection rates , whereas expression of wild-type Rac1 had no effect ( Fig 2F , S2C Fig ) . Both Rac1 mutants also reduced VEEV titer in the media ( S2D Fig ) . We also confirmed the importance of Rac1 GTPase activity during WEEV and CHIKV infection ( S2F and S2G Fig ) . The inhibitory effects of both Rac1 mutant variants on alphavirus infection likely indicate that the role of Rac1 during infection requires completion of the GTP-GDP-exchange/GTP-hydrolysis cycle . Cycling between GTP- and GDP-bound states may be required for productive infection , and shifting the level of activity predominantly to either side may block signaling pathways that emanate from the turnover . Rac1 also forms a complex with PIP5K1 kinases that are necessary for stimulation of PI4 , 5P2 synthesis and actin assembly [25] . PIP5K1-α directly binds Rac1 via the polybasic tail of Rac1 . Specific mutations within this region , such as K186E , abrogate Rac1:PIP5K1-α binding in vitro [26] . To examine whether Rac1:PIP5K1-α complex formation is important for VEEV infection , we used the tetracycline-inducible 293 Flp-In T-REx cell line to expresses Rac1 variant K186E ( Fig 2G ) . Once induced , these cells and control cells expressing CAT or wild-type Rac1 were infected with VEEV or RVFV . Expression of Rac1 K186E reduced VEEV but not RVFV infection rates ( Fig 2H , S2E Fig ) . VEEV titer in the media was also reduced ( S2D Fig ) . Finally , we confirmed the importance of Rac1:PIP5K1-α complex formation to infection with CHIKV ( S2H and S2I Fig ) . These results suggest that binding of Rac1 to PIP5K1-α plays a role in alphavirus infections . We used a multi-cycle VEEV in our screen . Consequently , Rac 1 and Arp3 could have acted at a number of stages of the VEEV lifecycle . To determine when Rac1 and Arp3 act , we first determined the time necessary for a single lifecycle ( round ) of VEEV TC-83 ( live-attenuated vaccine strain ) infection . We measured virus particle release from HeLa cells to the media at different time points post virus inoculation using qRT-PCR analysis . Virus particle release into the media was observed at 9 h post inoculation of HeLa cells ( Fig 3A and S3A Fig , left panel ) , suggesting an approximately 9-h replication cycle for VEEV under these conditions . Expression kinetics of the late alphaviral gene product , E2 , was also analyzed . E2 expression was detected as early as 7 h post virus inoculation ( Fig 3B and S3A Fig , right panel ) . Experiments performed with virulent VEEV IC-SH3 yielded similar results on expression of E2 and C proteins at these time points ( Fig 3C ) . We confirmed our results with a one step-like growth curve analysis using a high MOI ( MOI = 10 ) and also measured intracellular viral RNA ( vRNA ) levels as a function of time . Significant increase in intracellular vRNA levels was found at 5 h post virus inoculation , suggesting that virus replication/transcription is initiated prior to this time point ( Fig 3D ) . To narrow down the lifecycle stage targeted by Rac1 and Arp3 , we performed time-of-addition experiments using inhibitors of these host factors . This time-based approach determines how long the addition of a compound can be postponed before losing its antiviral activity in cell culture . For example , if an inhibitor that targets viral fusion is present at the time when virus entry and fusion occurs within the viral lifecycle , productive infection will be inhibited . In contrast , if this inhibitor is added after the entry/fusion process is completed , the inhibitor will no longer be effective in blocking infection . As a positive control for infection inhibition , HeLa cells were pretreated with increasing concentrations of Rac1 or Arp3 inhibitors 1 h before addition of virus . Alternatively , inhibitors were added to the cells at different time points after virus inoculation ( 1 , 3 , 5 , or 7 h , Fig 3E ) but prior to virus release ( 9 h post inoculation ) . When the Rac1 inhibitor EHT1864 or the Arp3 inhibitor CK548 were added 1 , 3 , or 5 h after VEEV exposure , VEEV infection rates were reduced to that detected with the positive control condition ( pretreatment ) . However , addition of inhibitors 7 h after virus inoculation had significantly less effect on infection , suggesting that the inhibitors lose their antiviral activity at this time . Similar results were obtained with VEEV TC-83 in the context of a single replication cycle ( S3B Fig ) ; both EHT1864 and CK548 inhibitors reduced VEEV TC-83 infection when they were added up to 7 h post inoculation . Furthermore , when the inhibitors were added to HeLa cells 5 h following VEEV inoculation , VEEV titer in the media was significantly reduced ( approximately 80- to >7 , 000-fold reduction , S3C Fig ) . Since the inhibitors exhibited antiviral activity when they were added 5 h post virus inoculation but significantly lost their antiviral affect when they were added 7 h post virus inoculation , these results indicate that Rac1 and Arp3 most likely play a role in the VEEV life cycle sometime between 5 h and 7 h post virus inoculation . Since one lifecycle of the virus takes at least 9 h to complete , and since transcription/replication is initiated prior to 5 h post virus inoculation , these results indicate that these inhibitors act at a late stage of virus infection . To further confirm that Rac1 and Arp3 do not act at earlier stages ( entry and replication ) , we first utilized a VEEV cell entry surrogate system composed of retroviral pseudotypes ( Moloney murine leukemia virus; MoMLV ) encoding eGFP and carrying the viral envelope proteins [27 , 28] . HeLa cells pretreated with control siRNA or with siRNAs targeting Rac1 or Arp3 were transduced with MoMLV-VEEV or MoMLV-EBOV ( non-alphavirus control ) . As previously reported , MoMLV-EBOV entry into HeLa cells was reduced following knockdown of Rac1 or Arp3 [29 , 30] ( Fig 3F ) . However , Rac1 or Arp3 knockdown had no or minimal effect on MoMLV-VEEV transduction rates , indicating that envelope-mediated entry of VEEV is independent of these two proteins . Next , we examined the effect of the various inhibitors on total E2 protein levels in the context of virus infection . None of the inhibitors had an effect on E2 protein levels as determined by western blot analysis ( Fig 3G ) . Finally , we tested the effect of Rac1 and Arp3 on alphavirus replication in infected cells by treating cells with siRNAs as described above or with inhibitors against Rac1 or Arp3 . Intracellular vRNA copy numbers were determined by qRT-PCR . The siRNAs as well as the inhibitors had no significant effect on intracellular vRNA copy numbers ( Fig 3H and 3I ) . Similar results were obtained when the inhibitors were tested for their effect on CHIKV replication using a previously published replicon system ( S3D Fig [31] ) . Overall , these results indicate that Rac1 and Arp3 function after virus entry and replication , but prior to budding and release . As mentioned above , Rac1 , Arp3 , and PIP5K1A all affect cellular actin dynamics [16–19] . Previous studies have demonstrated a role for actin in alphavirus infection [32 , 33] . For example , in the early stages of infection of another alphavirus , Semliki Forest virus , replication complexes are internalized via an endocytic process that requires a functional actin-myosin network [7] . However , our time-of-addition experiments suggest that Rac1 and Arp3 play a role later in infection . We therefore investigated whether actin dynamics might play an additional role at later stages of infection . To this end , we performed time-of-addition experiments ( similar to the ones described above ) with actin polymerization inhibitors . Cells were either pretreated with increasing concentrations of inhibitors before addition of virus ( positive control ) or preincubated with virus and subsequently treated with inhibitors at different time points after infection ( Fig 4A and 4B ) . Compared to the positive control condition ( pretreatment ) , the actin polymerization inhibitors , latrunculin A and cytochalasin D , were less effective in inhibiting VEEV infection when they were added 1 h after virus inoculation ( Fig 4A and 4B ) . This loss of antiviral activity is possibly due to the previously described role of actin in internalization of alphavirus replication complexes [7] . Inhibition of VEEV infection rates remained similar if actin polymerization inhibitors were added up to 5 h after virus inoculation . However , additional loss of antiviral activity was observed when the inhibitors were added at 7 h post virus inoculation . These results suggest that actin polymerization inhibitors target two separate steps in VEEV’s life cycle , one early in infection and one late in infection . To further validate our results that actin might play a role in the later stages of the alphavirus lifecycle , we tested the effect of various doses of actin polymerization inhibitors ( latrunculin A , cytochalasin B and D ) or a microtubule-depolymerizing agent ( nocodazole ) on VEEV infection rate when added at various time points post virus inoculation . HeLa cells and primary human astrocytes were inoculated with VEEV first , and inhibitors were added 3 ( HeLa ) or 5 ( astrocytes ) h later . Disruption of actin dynamics by the actin polymerization inhibitors reduced VEEV infection rates and VEEV titer in a dose-dependent manner without cytotoxicity ( Fig 4C–4E ) . Although some nocodazole-mediated inhibition of viral infection was observed , inhibition was not as marked as that observed with actin polymerization inhibitors and was accompanied by increased cytotoxicity ( Fig 4C and S4A Fig ) . Phalloidin and tubulin staining demonstrated that the actin and microtubule cytoskeleton morphology was indeed disrupted upon treatment with these inhibitors ( S4B and S4C Fig ) . These results further imply that actin polymerization might have an essential role in later stages of VEEV infection . To determine if the actin polymerization inhibitors ( latrunculin A and cytochalasin D ) might block viral replication or E2 expression at later stages of infection , we inoculated cells with VEEV TC83 and treated them 5 h later with the inhibitors . Intracellular vRNA copy numbers were determined by qRT-PCR 11 h after virus inoculation . Alternatively , cells were lysed and analyzed for E2 expression by immunoblotting . Both inhibitors had no significant effect on vRNA copy numbers and E2 expression levels ( Fig 4F and 4G ) . Finally , no effect on virus replication was observed when the actin polymerization inhibitors were tested for their effect on a CHIKV replicon system ( S4D Fig ) [31] . Together , the data suggests that the role of actin in the later stages of infection does not involve viral replication or late gene expression . To assess the possible role of actin in the later stages of alphavirus infection , we assessed temporal changes of actin rearrangements during the course of viral infection . HeLa cells were infected with VEEV , CHIKV , or RVFV ( used as a control ) and co-stained at the indicated time points with antibodies against viral proteins and phalloidin . Confocal microscopy revealed major changes in the actin-staining pattern within alphavirus-infected cells ( VEEV , CHIKV ) , as indicated by the accumulation of actin in large structures in the cytoplasm ( i . e . , actin foci , indicated by asterisks in Fig 5A ) . These foci co-localized with the alphavirus envelope protein E2 ( Fig 5A ) . In contrast , such actin rearrangements were not observed in RVFV- or mock-infected cells ( Fig 5A ) . Actin foci were further quantified ( measured as the number of foci per cell ) in mock- , VEEV- , CHIKV- , and RVFV-infected cells ( Fig 5B ) . These foci were detected as early as 7 h after VEEV inoculation ( Fig 5C ) and could also be detected upon infection with other alphaviruses ( EEEV , WEEV , and SINV , S5A Fig ) . We also tested whether alphavirus nsP1 , which was previously shown to mediate disruption of actin stress fibers and induction of filopodia-like extensions [34] , could induce generation of actin foci . Expression of VEEV TC83 nsP1 in HeLa cells did induce filopodia-like extensions . However , no actin foci were observed ( S5B Fig ) . Overall , our results demonstrate that , as early as 7 h post inoculation with alphaviruses , infection causes major cellular actin rearrangements leading to the formation of actin foci that are not nsP1-dependent and that co-localize with the alphavirus envelope protein E2 . Because our data suggested that the timing of the effects of Rac1 and Arp3 and the formation of actin foci take place late in infection ( Figs 3 and 5 ) , we speculated that Rac1 and Arp3 proteins might play a role in this alphavirus-induced actin remodeling . To test this hypothesis , HeLa cells were treated with increasing concentrations of Rac1 or Arp3 inhibitors , infected with VEEV , and subsequently stained with fluorescent phalloidin and antibodies against E2 . Treatment with either the Rac1 ( EHT1864 ) or Arp3 ( CK548 ) inhibitor significantly reduced the number of actin foci and the percentage of infected cells in a dose-dependent manner ( Fig 5D and 5E ) . In fact , under these conditions actin foci were rarely observed in confocal images even in E2-positive cells . These observations clarify that Rac1 and Arp3 function upstream of the major actin rearrangements detected in VEEV-infected cells . Since Rac1-PIP5K1-α complex formation plays a role in alphavirus infection ( Fig 2 ) and because Rac1 inhibitor reduced actin foci formation in alphavirus-infected cells ( Fig 5 ) , we next examined whether both host factors could be observed on actin foci and/or filaments within alphavirus-infected cells . Basal-to-apical confocal section series of VEEV-infected HeLa cells are shown in Fig 5F . PIP5K1-α and Rac1 show increased co-localization with actin foci and E2 towards the apical area ( S5C and S5D Fig ) . Both host factors are also detected along actin filaments , where they co-localize with E2 ( Fig 5F , insets ) . To better characterize the nature of the observed actin foci within infected cells , we performed sequential scanning of cells stained for actin and alphavirus E2 in both stimulated emission depletion ( STED ) microscopy and confocal microscopy imaging modes ( for comparison , see S6A Fig ) . With improved resolution of STED microscopy , actin foci within infected cells were found to be clusters of filamentous actin with a diameter range of 5–11 μm ( Fig 6A ) . Actin filaments within the clusters are seen with VEEV E2 puncta at their ends or along them ( Fig 6A ) . On the cell periphery , E2 puncta are localized in proximity to actin filaments ( Fig 6A ) . E2 puncta are also observed at the ends of actin filaments in primary human astrocytes , and in CHIKV-infected HeLa cells ( Fig 6B ) . In a series of basal- ( Section 7 ) to-apical ( Section 25 ) confocal sections , a single VEEV-infected cell can be seen with an actin cluster ( S6B Fig ) . E2 co-localizes with the actin cluster , and cytoplasm/nucleus staining demonstrates that the generated actin cluster is localized within the cell ( S6C Fig ) . In contrast , co-localization of E2 and microtubules was not significant ( S6B Fig ) . We also performed electron microscopic studies to examine the localization of cytoskeletal elements relative to alphaviral CPV-II structures . These structures compartmentalize the viral glycoproteins E1 and E2 and serve as transport vehicles for the glycoproteins from the TGN to the viral budding sites on the plasma membrane . Electron-microscopic studies of VEEV-infected cells ( Fig 6C ) show CPV-II structures alongside or at the end of thin filaments , which , based on size and morphology , most likely correspond to actin filaments [12] . CPV-I replication compartments are also present within these cells ( Fig 6C , bottom right panel ) [9] . Because alphavirus E2 co-localized with actin filaments in infected cells , we next tested whether VEEV E2 associates with actin . HeLa cells were infected with VEEV or RVFV ( control ) or left uninfected ( mock ) . Virus envelope protein-binding factors were subsequently immunoprecipitated from cell lysates with antibodies to surface glycoproteins E2 ( VEEV ) or Gn ( RVFV ) . Western blot analysis of the immunoprecipitated fraction ( IP ) showed enrichment of actin in E2 immunoprecipitates from VEEV-infected cells relative to mock-infected control ( more than 4-fold increase by densitometry analysis , Fig 6D , left panel ) . Such an increase in immunoprecipitated actin was not observed or was minimal in Gn immunoprecipitates from RVFV-infected cells ( 1 . 5-fold or less increase by densitometry analysis , Fig 6D , middle panel ) . To confirm the E2-actin association , we repeated these immunoprecipitation assays using more stringent lysis and washing conditions and performed the reverse experiment using an antibody against actin to examine its ability to immunoprecipitate E2 from VEEV-infected cells . Our results show that antibodies against E2 immunoprecipitated actin ( more than 8-fold increase by densitometry analysis ) and antibodies against actin immunoprecipitated E2 ( more than 4-fold increase by densitometry analysis ) from VEEV-infected , but not from mock-infected cells ( Fig 6D right panel ) . These results indicate that VEEV E2 either directly or indirectly associates with actin in lysates from infected cells . However , since our lysis buffer included detergent ( NP-40 ) , the observed association between E2 and actin was most likely not in the context of CPV-II structures . E2 was mainly localized in perinuclear puncta in cells treated with the Rac1 and Arp3 inhibitors , whereas in DMSO-treated cells E2 was found throughout the cytoplasm and at the plasma membrane ( Fig 5D ) . Previous studies have demonstrated that the alphavirus glycoproteins E1/E2 are transported from the TGN to the cell surface via TGN-derived vacuoles [12 , 35] , suggesting that the observed puncta might represent TGN or TGN-derived vacuoles . We therefore hypothesized that Rac1- and Arp3-dependent actin remodeling in alphavirus-infected cells might be important for trafficking of E1/E2 . To test this hypothesis , primary human astrocytes were treated with DMSO , EHT1864 , or CK548 and then infected with VEEV . Cells were stained with antibodies against VEEV E2 glycoprotein and the TGN marker TGN46 . VEEV E2 was primarily located at the cell surface in control DMSO-treated cells ( Fig 7A , zoom 1 ) . In some of the cells , E2 puncta co-localized with TGN46 . However , upon treatment with the Rac1 or Arp3 inhibitors , E2 localization in TGN46-positive puncta was significantly enhanced ( Fig 7A , zoom 2 and 3 ) and less E2 glycoprotein was observed at the cell surface . Quantification of TGN46-to-cell-surface ratio of E2 staining intensity in control- or compound-treated VEEV-infected astrocytes is shown in S7A Fig . Similar experiments performed in HeLa cells using the inhibitors and the TGN marker Golgi-localized , gamma ear-containing , ARF-binding protein 3 ( GGA3 ) yielded comparable results ( S7B Fig ) . In addition , we developed a flow cytometry-based assay for detection of VEEV E2 on the plasma membrane . We examined cell-surface expression of E2 following treatment with actin polymerization , microtubules depolymerization , Rac1 , or Arp3 inhibitors . HeLa cells were infected with VEEV and treated 5 h later with increasing concentrations of EHT1864 , CK548 , latrunculin A , cytochalasin D , or nocodazole . Cells were subsequently stained for surface expression of E2 and with the 7-amino-actinomycin D viability dye . Concomitantly , an aliquot of the cells of each treatment group was lysed and analyzed for total E2 expression in whole-cell lysates . None of the inhibitors significantly affected total protein levels of E2 . However , the actin , Rac1 , and Arp3 inhibitors decreased geometric mean fluorescence intensity of E2 on the cell surface in a dose-dependent manner ( Fig 7B and 7C ) . In contrast , the microtubule inhibitor , nocodazole , had no effect on cell surface E2 expression . The effect of the actin , Rac1 , and Arp3 inhibitors on E2 surface expression was specific as no or minimal effect was observed on surface expression of cellular CD44 ( S7C Fig ) . Overall , our data suggest that actin , Rac1 , and Arp3 , but not microtubule , inhibitors might interfere with trafficking of E2 from the TGN or TGN-derived vacuoles to the cell surface . To examine if the actin remodeling observed in alphavirus-infected cells is associated with any TGN membrane structures , we stained VEEV-infected cells with the TGN marker TGN46 . Actin clusters were observed near TGN46 ( S8A Fig ) and VEEV E2 was detected on these actin clusters and co-localized with the TGN marker . Rac1 was also found to co-localize with the TGN marker and E2 , whereas PIP5K1-α co-localized with E2 but not with TGN46 ( S8B and S8C Fig ) .
Reorganization of the host cytoskeleton varies among infections with different viruses and can play a role in every stage of the viral life cycle . Examples include virion movement ( surfing ) towards entry sites , actin-enhanced endocytic entry pathways , and actin-based , filopodial extensions ( termed tunnelling nanotubes ) that act as bridges to facilitate virus spread ( reviewed in [36–39] ) . Here , using an siRNA screen , we identified trafficking host factors that are important for alphavirus infection and are crucial regulators of the actin cytoskeleton . To date , Rac1- and Arp2/3-mediated actin rearrangements have mainly been associated with virus uptake and entry [30 , 40–44] . Rac1 is predominantly known as a key regulator of the actin cytoskeleton at the plasma membrane [45] . There , Abelson interactor 1 ( Abi1 ) and Wiskott-Aldrich syndrome protein ( WASP ) family verprolin-homologous protein ( WAVE ) , but not neural ( N ) -WASP , are essential for Rac1-dependent membrane protrusion and macropinocytosis [46] . Recently , however , Rac1 , the Arp2/3 complex , and actin have emerged as major factors in the secretory pathway in processes such as biogenesis and motion of Golgi-derived transport carriers to the plasma membrane [47–50] . During formation of TGN carriers , Rac1 functions downstream of ADP-ribosylation factor 1 ( Arf1 ) . Arf1 recruits clathrin/adaptor protein 1 ( AP-1 ) -coated carriers and a complex composed of cytoplasmic fragile X mental retardation 1 ( FMR1 ) -interacting protein ( CYFIP ) , nucleosome assembly protein 1 ( NAP1 ) , and Abi1 to the TGN . Rac1 and its exchange factor Rho guanine nucleotide exchange factor 7 ( ARHGEF7 ) bind CYFIP and trigger N-WASP- and Arp2/3-mediated actin polymerization necessary to tubulate clathrin-AP-1-coated carriers [51] . Therefore , during alphavirus infection , Rac1 could potentially be recruited to the TGN to mediate biogenesis of E2-containing vesicles and/or their transport from the TGN to the cell surface via actin ( see model , Fig 7D ) . In support of this hypothesis , some of the host factors mentioned above , such as clathrin heavy chain 1 ( CLTC ) , AP-1 subunits ( AP1M1 ) , and Arf1 were identified as hits in our primary and validation siRNA knockdown screens ( S1 and S2 Tables ) . Furthermore , siRNAs targeting N-WASP reduced the infection rate of both VEEV and CHIKV ( S1B Fig ) . Finally , during VEEV infection Rac1 was found to co-localize with E2 at the TGN ( S8 Fig ) . Hence , Arf1 may function upstream of Rac1 to facilitate biogenesis and/or motion of E2 transport carriers from the TGN to the plasma membrane and that this transport is mediated by N-WASP . Viruses have evolved specific egress pathways for transporting viral components to the plasma membrane , often using the cell’s secretory pathway via the endoplasmic reticulum , the Golgi , and even transport vesicles . Most exocytic transport of cellular secretory cargo to the plasma membrane relies on microtubules for long-range translocations [52 , 53] . The microtubule network is also emerging as the preferred cytoskeletal element recruited for transportation of components of certain viruses to the cell surface [54–57] . Examples are microtubule delivery of influenza A virus HA membrane glycoprotein to the apical surface of MDCK cells [58] and vesicular stomatitis Indiana virus glycoprotein G trafficking from the TGN-to-plasma membrane [59] . In contrast , our results demonstrate that transport of the alphavirus membrane glycoprotein E2 is at least in part dependent on actin and actin regulators ( Rac1 and Arp3 ) . We hypothesize that the coordinated activities of PIP5K1-α , Rac1 , and the Arp2/3 complex might mediate alphavirus envelope E2 trafficking from the TGN to the cell surface via actin . Several results support this actin-dependent transport model ( Fig 7D ) . First , time-of-addition experiments with Rac1 and Arp3 inhibitors demonstrated that both factors function at a late stage of virus infection ( Fig 3 ) . Second , within a similar time frame ( concomitantly with E2 expression in infected cells ) major actin rearrangements into clusters occur in alphavirus-infected cells ( Figs 3 and 5 ) . Super high-resolution fluorescence microscopy and electron microscopy show that CPV-II structures containing E1 or E1/E2 , respectively , are localized along or at the end of actin filaments . Rac1 and PIP5K1-α also co-localize with E2 on actin foci ( Fig 5 ) . In infected cell lysates , E2 envelope protein was found to associate ( either directly or indirectly ) with actin ( Fig 6 ) . Third , Rac1 and Arp3 inhibitors blocked formation of virus-induced actin clusters ( Fig 5 ) . In cells treated with actin , Rac1 , or Arp3 inhibitors , most of the E2 staining was found to localize with TGN markers , and E2 levels at the cell surface were reduced ( Fig 7 ) . We have not yet examined the role of actin , PIP5K1-α , Rac1 , and the Arp2/3 complex in E1 trafficking . However , since E1 and E2 are oligomerized into trimeric complexes during transit to the plasma membrane in CPV-II structures [60] , we speculate that these host factors will have a similar function in trafficking of both viral proteins . Actin dynamics are involved in numerous aspects of intracellular transport . However , little is known regarding manipulation of these host machineries by pathogenic alphaviruses . Viruses can serve as unique tools to decipher how a particular cargo recruits actin filament tracks and the host factors and motors associated with these movements . Our results suggest a previously unidentified role of host factors Rac1 , Arp3 and PIP5K1-α late in alphavirus infection via actin remodeling that possibly mediates transport of alphavirus envelope glycoproteins from the TGN to the cell surface . It is important to note that although our data indicate that actin plays a major role in alphavirus glycoprotein transport , our experiments do not exclude the existence of other , parallel , transport mechanisms mediated by intermediate filaments or microtubules . Recombinant alphaviruses expressing tagged E2 could be useful to further substantiate our findings . However , until now , we have not succeeded in rescuing such viruses . Finally , our high-content siRNA screen reveals novel host regulators of alphavirus infection and potential therapy targets .
An arrayed library targeting 140 trafficking genes ( Dharmacon Human ON-TARGETplus siRNA Library—Membrane Trafficking—SMARTpool , G-105500-05 , Thermo Scientific , ) was used to transiently reverse-transfected HeLa cells ( 10 , 000 cells per well , 96-well format ) in triplicate at a 30-nM final concentration , using HiPerfect ( Qiagen ) . Cells were washed on the following day and infected 24 h later with VEEV ICS-SH3 at an MOI of 0 . 5 for 20 h . Cells were fixed with 10% formalin ( Val Tech Diagnostics ) and stained for high-content quantitative image-based analysis . The screen was repeated three times . In 6 wells on each plate , cells were transfected with a negative control siRNA ( NT , siCONTROL Non-Targeting siRNA #2 , Dharmacon D-001210-02 ) . The infection rate of control siRNA-transfected cells was optimized to yield , on average , 70–80% , following multiple virus replication cycles . For the primary screen , siRNA pools were classified as hits if the average of triplicate wells showed that the percentage of VEEV-positive cells decreased by more than 30% compared to that observed with the control siRNA wells on the plate ( Z-score <-2 SD ) . In the validation screen , the individual oligomers comprising each pool were placed into separate wells , and the screen was repeated . siRNA targets were considered validated if two or more of the individual oligomers were classified as hits compared to the control wells on the plate ( similar parameters as above ) and if the cell number was not less than 30% of the average of the negative control wells on the plate . Catalog numbers and sequences of siRNAs are provided in Table 1 . The percent of infected cells relative to controls , as well as the normalized cell numbers ( normalized to control siRNA ) is provided in S1 Table . HeLa ( ATCC , #CCL-2 ) , BHK-21 ( ATCC , #CCL-10 ) , and Vero cells ( ATCC , #CCL-81 ) were maintained in Eagle’s minimum essential medium supplemented with 10% fetal calf serum . T-REx-HeLa cells expressing human wild type Rac1 fused to eGFP , and Flp-In 293 T-REx cells expressing human wild type Rac1 , Rac1 G12V , Rac1 T17N , Rac1 K186E or CAT upon tetracycline induction were generated by using the T-REx System or the Flp-In T-REx system , respectively , according to the manufacturer's instructions ( Life Technologies ) . Cells were induced to express wild-type human Rac1 , variants thereof , or CAT in 96-well plates by adding tetracycline ( 1 μg/ml ) to the growth medium . Normal human astrocytes were obtained from Lonza and maintained according to the provider's instructions . Plasmids encoding Rac1 variants ( wild-type Rac1 , Rac1 T17N or Rac1 G12V ) fused to an avian myelocytomatosis ( myc ) protein tag were purchased from the Missouri S&T cDNA Resource Center ( www . cdna . org ) . A plasmid encoding Rac1 K186E was generated by using the QuikChange Lightning Site-Directed Mutagenesis Kit ( Agilent Technologies ) . Sequences of the primers are provided in Table 1 . A plasmid encoding pcDNA3-EGFP-Rac1-wt was obtained from Addgene . Mouse monoclonal antibodies against CHIKV ( 2D21-1 ) , EEEV ( 1C2 ) , VEEV ( 1A4A-1 ) , WEEV ( 9F12 ) , and RVFV envelope glycoprotein Gn ( 4D4 ) and nucleoprotein ( R3-ID8-1-1 ) were obtained from US Army research Institute of Infectious Diseases ( USAMRIID ) archives [61] . Goat antibody against VEEV capsid ( C ) or envelope protein was generously provided by AlphaVax ( via Kurt Kamrud ) . Rabbit antibodies against Arp3 , actin , N-WASP , GAPDH , FLAG , and HA were obtained from Sigma-Aldrich . Mouse monoclonal antibodies against actin , CD44 , GGA3 , and Rac1 were purchased from BD Transduction Laboratories . Rabbit antibody against α/β-tubulin was obtained from Cell Signaling Technology . Sheep anti-human TGN46 antibody was from AbD Serotec . Alexa Fluor-conjugated antibodies and phalloidin , Hoechst 33342 , and HCS CellMask Red were obtained from Life Technologies . All chemical inhibitors were purchased from Sigma-Aldrich , with the exception of EHT1864 ( Tocris Bioscience ) . Cells were incubated with inhibitors for 1 h before addition of viruses unless otherwise indicated in the figure legends . Infections with VEEV IC-SH3 , EEEV FL91-4679 , WEEV CBA87 , RVFV ZH501 , and CHIKV AF15561 were conducted under Biosafety Laboratory 3 conditions . All alphaviruses were propagated in BHK-21 cells and purified via sucrose gradients . RVFV was propagated in Vero cells . Viral infectivity was titrated by plaque assays as previously described [62] . MoMLV-eGFP pseudotypes carrying the VEEV envelope proteins E1/E2 or Ebola virus envelope GP1 , 2 ( control ) were produced as previously described [27 , 28 , 63] . MoMLV-eGFP pseudotypes were added to siRNA-treated HeLa cells for 6 h . Cells were then washed and supplemented with growth medium . Cell transduction efficiency was determined 2 days later by measuring eGFP expression using an Opera confocal reader ( PerkinElmer ) . For CHIKV replicon assays , we used the previously described BHK-CHIKV-NCT cells , which contain the CHIKV replicon with two reporter genes , Renilla luciferase ( Rluc ) and EGFP [31] . BHK-CHIKV-NCT cells were seeded onto 96-well plates at densities of 2 × 104 cells/well , incubated overnight , and treated with the indicated compounds at various concentrations . After exposure for 48 h , the Rluc activity resulting from the translation of CHIKV-Rluc genomic RNA was determined from the lysates using a Rluc assay kit ( Promega ) with a Tecan microplate reader . HeLa cells in 6-well plates were infected with VEEV TC-83 or RVFV MP12 ( MOI = 1 ) for 8 h . Cells were lysed in a mild lysis buffer ( 50 mM Tris pH 7 . 4 , 50 mM NaCl , 0 . 2 mM ethylenediaminetetraacetic acid ( EDTA ) , and 1% Triton X-100 ) or a lysis buffer ( 25 mM Tris pH 7 . 4 , 150 mM NaCl , 1 mM EDTA , 5% glycerol , and 1% NP-40 ) from Pierce Crosslink Immunoprecipitation supplemented with Complete protease inhibitor cocktail ( Thermo Scientific Pierce ) . Cleared lysates were incubated overnight at 4°C with protein A/G beads ( Thermo Scientific Pierce ) and VEEV E2- or RVFV Gn-specific antibodies or with beads cross-linked to antibodies against VEEV E2 or actin . Cell lysate immunoprecipitates were analyzed by SDS-PAGE and immunoblotting using the indicated antibodies . For western blot analyses , cells were lysed with RIPA lysis and extraction buffer supplemented with complete protease inhibitor cocktail ( Thermo Scientific Pierce ) . Cleared lysates were analyzed by SDS-PAGE and immunoblotting using WesternBreeze chromogenic or chemiluminescent kits ( Life Technologies ) and the indicated antibodies . Densitometric analysis of western blots was performed with ImageJ [64] . Cells were grown on glass cover slips and inoculated with VEEV or CHIKV for 1 h . Cells were fixed 20 h ( VEEV ) or 48 h ( CHIKV ) later , permeabilized with 0 . 5% Triton X-100 ( Sigma-Aldrich ) in phosphate-buffered saline ( PBS ) , blocked with 3% bovine serum albumin in PBS for 1 h . and stained using mouse anti-E2 antibodies ( 1:1 , 000 dilution ) , followed by ATTO 647N Goat Anti-Mouse IgG ( Active Motif ) ( 1:2 , 000 dilution ) . Actin was stained with Phalloidin ATTO 565 ( Sigma-Aldrich ) ( 1:80 dilution ) . Slides were mounted in ProLong Gold Antifade Reagent ( Life Technologies ) and dried overnight at room temperature before imaging . All confocal images were acquired on the Leica SP5 TCS 2C STED confocal system ( Leica Microsystems ) equipped with Leica’s inverted DMI 6000 microscope and STED 100x oil objective . Images were acquired at an imaging speed of 400 Hz , pin hole set to Airy1 , line average of 6 , and 1024 X 1024 formats . For STED of ATTO dyes , the pulsed Ti:SA infra red laser ( Mai Tai , model # MAI TAI BB990 , Spectra-Physics ) was tuned to 740 nm . HeLa cells grown on a MatTek dish ( MatTek corporation , MA ) were infected with VEEV TC83 ( MOI = 5 ) for 20 h . Cells were fixed for 1 h in primary fixative ( 2 . 5% formaldehyde , 2 . 5% glutaraldehyde , 0 . 1 M sodium cacodylate , pH 7 . 4 ) , washed three times in ice-cold 0 . 1 M sodium cacodylate buffer , and incubated with 1% osmium tetroxide in 0 . 1 M of sodium cacodylate for 1 h , washed three times with distilled water , stained and stabilized on ice with 2% uranyl acetate for 1 h and successively dehydrated on ice through a series of 22% , 50% , 75% , and 95% ethanols . The cells were then dehydrated three times at room temperature in 100% ethanol and infiltrated in well-mixed 50% ethanol and 50% Durcupan ACM resin ( Fluka , Sigma-Aldrich ) for 1 h with agitation . Cells were infiltrated twice by 100% Durcupan ACM for 3 h with agitation , after which the samples were placed in an oven and polymerized at 60°C for at least 48 h . The glass coverslip was peeled away from the bottom using a razor blade , and the selected area was cut out and glued to a block for sectioning . Thin sections ( approximately 80 nm ) were collected and pre-stained with 1% uranyl acetate and Sato lead before examination on a JEOL 1011 transmission electron microscope at 80 kV . Digital images were acquired using an AMT camera system . Plasmid encoding HA-tagged PIP5K1α was generously provided by Dr . Richard Anderson ( University of Wisconsin ) . Plasmid encoding FLAG-tagged nsP1 was generated in-house by PCR . Plasmids were transiently reverse-transfected into HeLa cells on glass coverslips ( Fisher Scientific ) using Lipofectamine LTX Reagent ( Life Technologies ) . T-REx HeLa cells on glass coverslips were induced with tetracycline for 24 h to express Rac1-eGFP . VEEV-infected cells were fixed , permeabilized , and blocked as described for STED . After incubation with primary antibodies and fluorescent secondary antibodies , slides were mounted as described for STED and air-dried before imaging with a TCS-SP5 confocal/multiphoton microscope ( Leica Microsystems ) . All confocal images represent a single plane acquired with a 100× oil objective . Similar experimental conditions were used for imaging studies of actin , tubulin , TGN46 , and VEEV E2 in HeLa cells . Co-localization analysis of tubulin or actin with VEEV E2 was performed with the ImageJ program using the Interactive 3D Surface Plot plugin [64] . For analysis of the siRNA screen , cells were stained without prior permeabilization . Cells inoculated with CHIKV , EEEV , RVFV , WEEV or SINV or cells designated for phalloidin or TGN staining were permeabilized prior to blocking as described above . Cells were then stained with murine monoclonal antibodies against the indicated viral proteins ( 1:1 , 000 dilution ) and , where indicated , against TGN46 or GGA3 ( 1:250 dilution ) . Subsequently , cells were stained with appropriate Alexa Fluor-conjugated antibodies ( 1:1 , 000 dilution ) , and Alexa Fluor 568 Phalloidin ( 1:100 dilution ) where indicated . All infected cells were also stained with Hoechst 33342 and HCS CellMask DeepRed for nuclei and cytoplasm detection , respectively . High-content quantitative imaging data were acquired and analyzed on an Opera quadruple excitation high sensitivity confocal reader ( model 3842 and 5025; Perkin-Elmer ) , at two exposures using a ×10 air , ×20 water , or ×40 water objective lenses as described in [65] . Images were analyzed using Acapella 2 . 0 , 2 . 6 , 2 . 7 ( Perkin-Elmer ) scripts in Evoshell or the building-blocks interface in the Columbus image analysis server ( PerkinElmer ) . Nuclei and cytoplasm staining were used to determine total cell number and cell borders , respectively . Mock-infected cells were used to establish a fluorescence intensity threshold for virus-specific staining . Quantification of virus-positive cells was subsequently performed based on mean fluorescent intensities in the virus-specific staining channel . Infection rates were then determined by dividing the number of virus-positive cells by the total number of cells measured . Detailed pipelines for image-based quantification of alphavirus-induced actin foci and TGN46-to-plasma membrane E2 staining intensity ratio are available upon request . At least 5 , 000 cells and up to 15 , 000 cells were analyzed per replicate in drug- or siRNA-treated cells . For actin foci analysis , 1 , 000–1 , 500 cells were used per replicate . For analysis of TGN46-to-plasma membrane E2 staining intensity ratio , 700 cells were used per replicate . HeLa cells in 12-well plates were inoculated with VEEV TC-83 ( MOI = 10 ) for 5 h . DMSO , EHT1864 , CK548 , nocodazole , latrunculin A , or cytochalasin D were subsequently added at the indicated concentrations . Five or 6 h later , cells were detached with Cell Dissociation Buffer ( Life Technologies ) and washed with flow buffer ( PBS/0 . 5% bovine serum albumin/2mM EDTA ) . Cells were incubated with mouse anti-VEEV E2 or CD44 primary antibody ( 1:1 , 000 dilution in flow buffer ) for 30 min on ice and then washed twice with ice-cold flow buffer . Cells were incubated for 20 min in the dark with Alexa Fluor 488 Goat Anti-Mouse IgG secondary antibody ( Life Technologies ) ( 1:5 , 000 dilution in ice-cold flow buffer ) and with 7-amino-actinomycin D to exclude dead cells from analysis ( 1:500 dilution ) . Following two more washes with ice-cold flow buffer , cells were fixed in 1% paraformaldehyde . Cytometric collection was performed using a FACS Canto II ( BD Biosciences ) , and data were analyzed using Flowjo v7 . 6 . 5 ( TreeStar ) . VEEV TC-83 RNA yields from the media and the cells and relative expression levels of PIP5K1-α in siRNA-treated HeLa cells were determined by qRT-PCR as previously described [65] . Serial 10-fold dilutions of the assayed ( 102 to 107 copies ) virus were used as standards . Relative expression levels were determined by using the comparative cycle threshold method . Sequences of qRT-PCR probes/primers are provided in Table 1 . Data are representative of at least three independent experiments , and values are given as mean of triplicates ± standard deviation ( SD ) unless otherwise indicated . Statistical significance was determined by the paired Student’s t test . | Alphaviruses , such as Chikungunya or Venezuelan equine encephalitis viruses , are significant human pathogens that cause arthritis or fatal encephalitis in humans . For productive infection of cells , alphaviruses rely on a repertoire of cellular host proteins , including trafficking factors that mediate transport of viral components across the cell . We have performed a functional screen to identify cellular factors that are crucial for this transport process . We show that Rac1 , PIP5K1-alpha , and the Arp2/3 complex are cellular regulators of alphavirus infection . These factors are important for major cellular actin rearrangements that occur at a late stage of virus infection and are virus-induced . Concomitantly , these factors might be essential for trafficking of the viral E2 surface glycoprotein from the trans-Golgi network ( TGN ) to the cell surface . E2 was found to associate with actin , as well as to co-localize with Rac1 , PIP5K1-α , and actin filaments . Late E2-containing vesicles , termed cytopathic vacuoles II ( CPV-II ) , were also imaged along and at the end of actin filaments in alphavirus-infected cells . | [
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"cul... | 2016 | siRNA Screen Identifies Trafficking Host Factors that Modulate Alphavirus Infection |
The suprachiasmatic nuclei ( SCN ) host a robust , self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment . Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity . Coherent circadian output of the SCN tissue is established by intercellular signaling factors , such as vasointestinal polypeptide . It was recently shown that besides coordinating cells , the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity . Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons . Based on these observations , the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level . The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained . The authors simulated different experimental conditions and found that: ( 1 ) in normal , constant conditions , coupled circadian oscillators quickly synchronize and produce a coherent output; ( 2 ) in large populations , such oscillators either synchronize or gradually lose rhythmicity , but do not run out of phase , demonstrating that rhythmicity and synchrony are codependent; ( 3 ) the number of oscillators and connectivity are important for these synchronization properties; ( 4 ) slow oscillators have a higher impact on the period in mixed populations; and ( 5 ) coupled circadian oscillators can be efficiently entrained by light–dark cycles . Based on these results , it is predicted that: ( 1 ) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; ( 2 ) a small number of neurons or a low connectivity results in desynchrony; and ( 3 ) amplitudes and phases of neurons are negatively correlated . The authors conclude that to understand the orchestration of timekeeping in the SCN , intracellular circadian clocks cannot be isolated from their intercellular communication components .
In most mammalian cells , a set of “clock” genes and proteins forms a regulatory network that produces oscillations with a circadian period ( ≈24 h ) [1] . Molecular and physiological rhythms are coordinated with the daily changes in the environment by a dominant circadian pacemaker , the suprachiasmatic nuclei ( SCN ) of the hypothalamus . The SCN neurons endogenously generate circadian rhythm and adapt that rhythm according to light–dark ( LD ) cycles of the environment ( entrainment ) . The approximately 20 , 000 neurons in the SCN [2 , 3] vary ( 1 ) in their ability to sense the environmental timing cues , ( 2 ) in the neurotransmitters they express or respond to , and ( 3 ) in their connectivity properties . A desire to understand how such a heterogeneous network produces a coherent and synchronous circadian output has motivated extensive experimental and theoretical work . Organotypic SCN slices or SCN neurons in high-density dispersal cultures express a coordinated rhythmic activity for as long as they are viable ( a few weeks up to several months ) [2] . SCN neurons in low-density dispersal cultures , however , do not show a coordinated activity but express a large variation in their free-running periods [4 , 5] . This has led to the conclusion that SCN neurons are self-sustained circadian oscillators that need a synchronization signal to produce a coherent output . Even before this experimental evidence , it had been hypothesized that the coupling of “sloppy” clocks improves the reliability of the output [6] . So far , all published mathematical models of the synchronization of the SCN rest on the coupling of self-sustained circadian oscillators . Among candidate synchronization factors are the neuropeptides vasoactive intestinal polypeptide ( VIP ) , gastrin-releasing peptide ( GRP ) , [7] and prokineticin 2 [8] , and the neurotransmitter GABA [9] . In addition , signals using the G-protein subunit Gi/o [10] as well as gap junctions [11] have been implicated in the intra-SCN synchronization mechanism . The concept of mutual coupling , in which the neurotransmitter is released in a circadian fashion and feeds back on the clock , has been put forward by different authors [9 , 12–18] . Two recent studies analyzed the consequences of targeted disruption of genes coding for VIP or its receptor , VPAC2 [18 , 19] . In both cases , not only the synchrony between SCN neurons was lost , but , surprisingly , a majority of neurons also became arrhythmic . Similarly , inhibition of sodium channels by tetrodotoxin ( TTX ) desynchronizes and suppresses oscillatory activity in clock neurons [20] . In Drosophila also , electric disturbance of clock neurons can stop their free-running activity [21] . Activity at the neuronal membrane thus seems to play a role in maintenance of intracellular rhythms and coordination of neuronal clocks [22] . Here , we show that these results can be reproduced by a mathematical model of synchronization of coupled oscillators that are damped rather than self-sustained . Our model reproduces a number of experimental results well: ( 1 ) quick and robust synchronization under normal conditions; ( 2 ) loss of synchrony and rhythmicity in SCN slices after application of TTX , or in the absence of VIP signaling; and ( 3 ) entrainment by LD cycles . In addition , we show that if the number of oscillators is large enough and/or the connectivity between SCN neurons sufficiently strong , synchrony becomes a condition sine qua non for rhythmicity ( i . e . , the loss of coherent activity results in damped oscillations of individual neurons ) . Far from being coincidental , we suggest that synchrony-dependent rhythmicity in individual cells is a defining property of robustly synchronized systems like the SCN . Synchronization factors thus have a dual role in maintaining rhythmicity and synchronizing circadian oscillators .
To simulate synchronization within the SCN , we constructed a network of coupled but damped molecular circadian oscillators . The model is built in two levels . First , on a single-cell level , we used a detailed molecular model to describe ( 1 ) the intracellular dynamics of clock genes and proteins , ( 2 ) the circadian neurotransmitter release by clock proteins , and ( 3 ) a simplified two-step signaling cascade leading to gene activation in response to neurotransmitter release ( Figure 1 ) . Second , on the “tissue” level , we placed the cells on a grid with the topology of a 2-D or 3-D SCN , and coupled them . We considered several coupling schemes mimicking different experimental conditions: ( 1 ) random sparse coupling ( type 1 , Figure 2A ) , ( 2 ) nearest-neighbor coupling ( type 2 , Figure 2B ) , and ( 3 ) SCN-like coupling combining nearest-neighbor and sparse coupling ( type 3 , Figure 2C ) . We studied the synchronization dynamics of coupled SCN neurons under four different conditions: high-density culture , low-density culture , presence of TTX , and loss of VIP/VPAC2 receptor . First , we wanted to test how well coupled oscillators can synchronize under normal conditions that mimic wild-type SCN slices or neuronal cultures ( high-density , no mutation ) . We simulated this by a nearest-neighbor coupling ( type 2; Figure 3A , 3B , and Video S1 ) in a 2-D SCN slice geometry . In these simulations , we ignored spatial heterogeneity of the SCN except that we set the periods of the DM cells to be slightly shorter ( 4% ) than those of the VL cells , consistent with experimental findings [24] , and we distributed the periods around 24 h with a standard deviation of 5% [4 , 5] . As a readout for synchrony , we defined an order parameter R ( Equation 18 in Materials and Methods ) . R is a normalized variance of the average Per/Cry mRNA concentrations in all cells , and varies between 0 ( no oscillator synchronized ) and 1 ( all oscillators synchronized in phase ) . To describe the strength of the synchronization signal , we introduced a parameter K ≥ 0 that controls the overall coupling strength , and represents the sensitivity of cell to the neurotransmitter ( for details , see Materials and Methods ) . With the coupling strength set to K = 0 . 9 , the slice is well synchronized ( R = 0 . 83 ) , and the overall period is 24 . 4 h . The whole slice reached a stationary synchronized state less than 72 h after starting the oscillators from random initial conditions ( Figure 3A and 3B; the first 72 h transients are not shown ) . Thus , the model reproduces well the high degree of synchrony seen in SCN slices . The connectivity , defined as the average of the ratio between the number of connections and the maximal number of connections , is higher in 3-D ( 0 . 16 ) than in 2-D ( 0 . 10 ) , as more neighbors are present within a given radius . Therefore , a complete SCN should synchronize even better than a 2-D slice . Indeed , simulations in a 3-D SCN geometry showed extremely well-synchronized cells ( R = 0 . 97 ) with only a 2 . 5-h spread from the most advanced to the most delayed cells , compared with more than 4 h for a 2-D slice ( Figure S2 and Video S2 ) . Second , having established that the model is well-synchronized under normal conditions , we wanted to know whether it could reproduce an SCN neuron culture dispersed at low density . To test this , we simulated a population of oscillators in which the neurotransmitter is only perceived by the cell that releases it ( autocrine activation ) . Although individual oscillators are not self-sustained , simulations showed that isolated cells with autocrine activation become self-sustained oscillators , and oscillate with their intrinsic periods ( Figure 3C and 3D ) . Thus , autocrine neurotransmitter activation seems to be sufficient to sustain oscillations in a dispersed cell culture . In addition , individual oscillators have an average intrinsic period of 24 . 3 ± 1 . 2 h that is very close to the period of the synchronized cells . Third , we wanted to reproduce the loss of synchrony and rhythmicity in SCN slices after application of TTX . TTX blocks voltage-gated sodium channels and desynchronizes and suppresses oscillatory activity in clock neurons [20] . After removing TTX , the clock neurons resumed their oscillation and reestablished the same phase relationship as before TTX application . We simulated TTX experiments by using a weak coupling ( K small ) in a 2-D network with a nearest-neighbor coupling . We transiently decreased K from 0 . 9 , as in normal conditions , to 0 . 3 , and observed that all oscillators damped out . They quickly resumed their high-amplitude oscillations after restoration of full coupling ( Figure 3E ) . Thus , the model reproduces the TTX experiments well . Fourth , we simulated an SCN neuron culture in the absence of VIP signaling . Experimentally , in the absence of VPAC2 , neurons show desynchronized and low-amplitude oscillations , or no oscillations [18] . In some cases , low-amplitude behavioral rhythmicity is retained [10 , 18 , 19 , 25] , so we assumed that weak cell-to-cell interaction subsists [7 , 10] and decreases with the distance between cells . With such a severely impaired coupling , most of the oscillators rapidly damped out , while a few remained irregularly rhythmic for a longer time ( Figure 3F ) . Simulations over a longer time of multiple slices confirmed that these are not self-sustained oscillations ( i . e . , single cells eventually become arrhythmic ) . The rhythmic average output is preserved in the first 144 h , with R = 0 . 78 . Later , from 144 h to 288 h , R is considerably reduced ( to 0 . 20 ) , indicating a severe disruption of the synchrony after a few days . After having established that oscillators can be efficiently synchronized , and that weak coupling leads to loss of synchrony and rhythmicity in individual oscillators , we wanted to investigate whether coupled damped oscillators indeed only have two dynamic states: rhythmic and synchronized , or arrhythmic and desynchronized . To do this , we first recapitulated the simulations made in the previous subsection with only two coupled oscillators to explore all the dynamic states they can take . We then confirmed that in a large population , individual oscillators could not be rhythmic if their neighbors are not synchronized . We simulated possible dynamic outcomes of the coupling of two damped oscillators with random periods . We varied the coupling strength and the ability of the oscillators to sense autocrine or paracrine synchronization signals . First , if the oscillators sense strong autocrine and paracrine signals ( K high enough , intercellular coupling ) , they synchronize ( Figure 4A ) . Second , if the oscillators sense only autocrine signals ( K high enough , no intercellular coupling ) , they oscillate , but do not synchronize ( Figure 4B ) . Third , if the oscillators sense weak autocrine and paracrine signals ( K small , intercellular coupling ) , their oscillations die out ( Figure 4C ) . Despite many numeric simulations , we never encountered two normally coupled oscillators that are rhythmic but desynchronized . This indicates that in our model , rhythmicity is sufficient to induce synchronization , and vice versa . A single oscillator in a large enough neighborhood of rhythmic but totally desynchronized cells would sense a constant average synchronization signal . In our model , the neurotransmitter activates the CREB protein in the signaling cascade . In simulations with constantly activated CREB protein ( X2 , Equation 9 ) , oscillations stopped and a stable steady state was reached ( Figure 4D ) . Any transient oscillatory activity damped out to that state ( Figure 4E ) . Hence , a variable input is required for sustained rhythmicity of individual oscillators . In a large population of well-coupled cells , the variable input can only come , by definition , from synchronized neighbors . Noise is another source of variability that might affect synchrony . Two kinds of noise can be distinguished and can have different effects on the synchronization of oscillators . First , the noise can affect individual properties of oscillators ( e . g . , the successive periods of a given oscillator ) or their coupling ( e . g . , the neurotransmitter released by each cell ) . Such a local noise impairs the synchrony as the strength of noise increases ( Figure S3A–S3D ) . Alternatively , a spatially uniform extracellular noise could contribute to synchronize the cells ( Figure S3E and S3F ) , even in the absence of synchronization signals , in much the same way that was described by Zhou and coworkers [26] . This result shows that synchrony is necessary for rhythmicity of single oscillators ( i . e . , single-cell oscillator rhythmicity and synchrony are codependent ) . So far , we have looked at a large number of oscillators and found that robust synchronization is achieved when oscillators are appropriately coupled . To analyze the influence of the number of oscillators as well as the connectivity on synchronization dynamics , we used a uniform , random coupling ( type 1 ) , and we varied either the number of oscillators or the nominal connectivity ( Figure 5 ) and measured the R values . First , we considered the synchronization of ensembles consisting of six to 63 oscillators , with a nominal connectivity c0 = 0 . 1 . For the larger ensembles , strong synchronization was consistently achieved ( R > 0 . 8 for n > 40 ) . For smaller ensembles , the order parameter R shows a high variance , ranging from 0 . 15 to almost 1 for n = 27 . High variability of R values denotes poor , nonrobust , network-dependent synchronization ( Figure 5A ) . Representative average outputs for small cell numbers are damped or irregular compared with larger networks ( Figure 5B , two top panels versus bottom panel ) . Second , we tested the influence of the connectivity on synchronization properties ( c0 ranging from 0 . 005 to 1 with a fixed number of cells n = 12 ) . For dense networks ( c0 ≥ 0 . 5 ) , synchronization was consistently excellent ( R > 0 . 9 ) . Sparsely connected networks ( c0 < 0 . 5 ) result in highly variable R values , as for small numbers of oscillators . For small c0 values ( <0 . 1 ) , we observed better synchronization , perhaps because usually only one synchronized cluster forms ( Figure 5C ) . Sparsely coupled networks show dynamics similar to small population networks , as the connectivity is varied ( Figure 5D ) . These results show that in random networks , both a sufficient number of oscillators and connectivity contribute to strong and robust synchronization . In weakly coupled networks , in addition to a loss of rhythmicity , Per/Cry mRNA concentration decreases exponentially ( Figure 5B and 5D , top panels ) , consistent with the relative “dark” cells observed in VPAC2 receptor–deficient luciferase reporter mice [18] . For large numbers of SCN neurons , as in vivo ( hundreds to thousands ) , we found that synchrony is achieved even for very small connectivity values . Therefore , a larger number of neurons in the network ensures that even a great reduction in connectivity will not impair synchrony . Mutations in clock genes that modify the free-running period of the SCN provide a way to test the synchronization properties of neurons with different periods . Hamsters homozygous for the tau mutation have free-running periods of about 20 h compared with 24 h in wild-type hamsters [27] . The free-running periods in mutant and wild-type animals are determined by the average of periods of dispersed individual clock cells [28 , 29] . In a recent experiment by the Herzog lab , when dispersed SCN neurons of tau mutants and wild-type hamsters were mixed in cell cultures , the resulting period of the total population turned out to be longer than the average period of the two unmixed populations , which would have been the naive prediction ( S . Aton and E . Herzog , personal communication ) . With this experimental observation in mind , we tested whether our model might be able to explain this nonintuitive result . We randomly mixed and connected a 24 h–period population with a 20 h–period population ( total , n = 100; standard deviations of the periods , 0 . 1 h ) in various ratios . The resulting period of the synchronized population was compared with the period that would have been expected from averaging the individual oscillator periods . For ratios between 0 . 2 and 0 . 8 ( i . e . , 20% and 80% wild-type cells ) , the resulting population period was systematically longer than expected ( five runs per ratio , R > 0 . 8; Figure 6A and 6B ) . Thus , in mixed population , slow oscillators seem to have a higher impact on the period than the faster ones . In a synchronized SCN neuron slice culture or a high-density SCN neuron dispersal culture , the intrinsic periods of the neurons ( i . e . , of the noncoupled neurons ) cannot be determined experimentally , only the phases and amplitudes . Thus , we used our model to relate these two measures to the intrinsic periods of the neurons . To this end , we extracted the intrinsic periods of the neurons by uncoupling them and calculating their free-running periods . We saw that , when coupled , oscillators with short periods are phase-advanced , and oscillators with long periods are phase-delayed compared with the phase of the average output of the population ( Figure 6C and 6D ) , consistent with the observation that the DM region is advanced with respect to the VL region [20] . We also saw that the amplitudes of oscillators are higher when their periods are longer ( Figure 6E ) . Consequently , oscillators with high amplitudes are phase-delayed , and oscillators with low amplitudes are phase-advanced ( Figure 6F ) . These findings explain why synchronized oscillators have a period longer than expected ( i . e . , because high-amplitude oscillators contribute more to the population than those with small amplitude ) . An important property of the circadian clock is its capability to be entrained by daily LD cycles . The light signal is conveyed from the retina to the SCN via the retino-hypothalamic tract [30] . Retino-hypothalamic cells release glutamate and PACAP , which activate Per gene expression in the target VL cells [31] , which then relay the light signal to the DM cells [17] . After a phase-shift in the LD cycle , the light-responsive VL neurons re-entrain rapidly ( ∼2 d ) to the new schedule , while the DM neurons take much longer to readjust—up to 13 d after a 6-h advance in the LD cycle [32] . To test whether our model is able to entrain to LD cycles and to analyze entrainment dynamics , we simulated a 12 h–12 h LD cycle in a 2-D SCN with a type 3 coupling by imposing a periodic forcing on the expression of Per/Cry gene in the VL cells . Through neuronal projections , VL cells entrained the DM cells ( Figure 7A and 7B , and Video S3 ) . Starting from completely desynchronized cells , high synchrony ( R = 0 . 92 ) and phase-locking to the LD cycle ( with a 24-h period ) are reached very fast , within 72 h . The phases of DM cells were slightly more advanced than those of the light-inducible VL cells ( unpublished data ) , as observed experimentally [20] . After a 12-h phase-shift in the LD cycle , VL cells resumed their phase quickly ( after 2 d ) , while DM cells took more than 10 d to resynchronize to the LD cycle ( Figure 7C ) . These results are in agreement with experimental findings [32] , and show that entrainment by a LD cycle is efficient even if only a fraction of the cells can respond to the light signal ( 102 out of 309 ) , but also that the light-insensitive cells take a longer time to adjust their phase .
Recent technological advances made it possible to measure the oscillation dynamics of single neurons within a SCN tissue at a high resolution , thus providing experimental data to construct and support more realistic SCN models [3 , 19] . Several papers proposed models for the molecular mechanism underlying circadian oscillations at the single-cell level [23 , 33–35] , but without considering intercellular communication . Other studies considered intercellular coupling mechanisms between generic oscillators without taking into account the influence of the rhythmicity of the intercellular coupling on the oscillators themselves . In two models , the intracellular oscillator is a van der Pol oscillator , which is a generic two-variable system displaying strong self-sustained oscillations . The models differ in the way cells are coupled: Kunz and Achermann [36] showed how uniformly locally coupled networks can robustly synchronize , while Antle and coworkers [37 , 38] proposed that a subset of gate cells provide daily inputs to rhythmic oscillators . Rougemont and Naef [39] used more abstract Kuramoto oscillators , in which only the phase ( not amplitude ) is described , with periods and phases randomly varying in time to characterize the source of phase dispersion . The first attempt to describe synchronization of circadian oscillators that are based on realistic genetic network was by Ueda et al . [40] , who showed that synchronization factors confer noise resistance to circadian rhythms in populations of oscillators . Roenneberg and Merrow [41] proposed the concept of zeitnehmer , where the cellular circadian oscillator feeds back on the input pathways of the zeitgebers , blurring the distinction between intra- and extracellular components . Here , we present a molecular model for the SCN circadian system that combines intracellular and extracellular dynamics at the single-cell level . So far , all published models assumed that individual oscillators are self-sustained . Recent experimental observations challenge that assumption . SCN slices treated with TTX , an inhibitor of sodium channels , lose both synchronization and rhythmicity [20] . In VIP and VPAC2 receptor–deficient high-density neuron dispersals , about 70% of the neurons are no longer rhythmic [19] . Similarly , in the slices from mice lacking the VPAC2 receptor , only a minority of neurons from the dorsal shell is rhythmic , and shows poorly organized and low-amplitude circadian gene expression [18] . These results suggest that synchronization factors are not only required for synchrony , but also for rhythmicity of individual cells . Therefore , in the present model , we considered a population of oscillators that are damped in the absence of synchronization signals . We built a heterogeneous network of coupled damped circadian oscillators . On a single-cell level , we used a molecular model of the circadian clock [23] , neurotransmitter release by clock proteins , and signaling cascade that leads to clock gene activation . We obtained a damped intracellular oscillator by reducing the steepness of the Per/Cry promoter feedback loop ( Hill coefficient ) . The Hill coefficient represents the cooperative character of the transcriptional inhibition process . A lower Hill coefficient leads to a more gradual inhibition of the promoter , whereas a high Hill coefficient results more in a switch-like process . On a population level , we placed the cells on a grid with a flexible topology of a 2-D or 3-D SCN , and coupled them . The phenotypes of the neurons ( period , amplitude , sustained or damped activity , neuropeptide release and receptor expression , connectivity , etc . ) were specified according to their position in the grid . We verified that our model reproduces well-known behaviors of SCN . In high-density networks , the modeled coupled oscillators are rhythmic and well synchronized in absence of external cues ( Figure 3A and 3B ) . We simulated TTX treatment of neurons [20] by lowering the coupling strength and showed that rhythmic activity in single oscillators disappeared and resumed quickly after the full coupling was restored ( Figure 3E ) . Then , we simulated loss of VIP and VPAC2 receptor [13 , 18 , 19] by lowering the coupling strength and reducing the range of connectivity , and showed that oscillators were slowly desynchronized and damped ( Figure 3F ) . We assumed the presence of a short-range coupling because in the absence of the VPAC2 receptor , mice express multiple circadian periods over more than 80 d when kept in constant darkness [19] , suggesting the existence of isolated islands of synchronized , locally coupled SCN neurons . We also verified that a periodically entrained subset of neurons ( the VL core ) could entrain the rest of the neurons ( the DM shell ) to a 24-h period ( Figure 7A and 7B ) . After simulating a 12-h phase-shift in the LD cycle , the light-inducible VL region reset its phase much faster than the DM region ( 2 d versus 10 d; Figure 7C ) . Damped oscillators in a large coupled population can adopt two and only two dynamic behaviors , depending on the coupling: ( 1 ) damping if uncoupled or weakly coupled , or ( 2 ) synchrony if normally coupled ( Figure 4 ) . A direct consequence is that coupled cells cannot run out of phase and still oscillate ( individual cells dispersed at low density are viewed as many independent synchronized systems ) . The coupling of damped oscillators produces a circadian pacemaker that is robustly synchronized: provided they are rhythmic , neurons will synchronize . If some neurons lose synchrony , they will damp out , leaving the rest of the SCN unperturbed . We showed that to achieve robust synchronization , the number of neurons and the connectivity matter ( Figure 5 ) . In neuron dispersals , coherent rhythmic output is density-dependent [4 , 5 , 19] . In addition , Yamaguchi et al . [20] reported that the upper dorsal region of a SCN slice lost its rhythmicity when cut out from the ventral region , perhaps because of the small size of the separated region—25 neurons were measured in the cut piece . In VPAC2 receptor–deficient or VIP-deficient mice , simultaneous multiple free-running periods in behavior could result from parallel , synchronized clusters in loosely connected networks . Ohta et al . [42] reported that after 3–5 mo , 10% of the mice kept in constant light showed arrhythmicity . They showed that the arrhythmicity is due to desynchronization between rhythmic SCN neurons . The only way our model could reproduce these results is by decreasing paracrine coupling without interfering with autocrine coupling . But at present , there is no evidence that constant light could induce such a selective disruption . In a driven harmonic oscillator like a pendulum , the highest amplitude is achieved when the driving period and the intrinsic period coincide [43] . Unexpectedly , in our model , we obtained a monotonic curve in which the amplitudes increase with the periods , possibly because of the interaction between Per/Cry gene activation by the synchronization signal and BMAL1 protein ( Figure 6E ) . As a result , slow oscillators have a higher impact on the period in a mixed population , qualitatively reproducing the results from a mixed-genotype experiment ( E . Herzog and S . Aton , personal communication ) . This contrasts with mutually coupled threshold-activated oscillators , where the fastest elements set the period [6] . In homogenous cell cultures , the difference between the free-running period and the average period of individual neurons is smaller than what is statistically detectable [29] . Our simulations also showed no statistical difference between average and synchronized periods ( simulations from Figure 3A–3D , two-sided t-test , p = 0 . 20 ) . Based on our results , we propose three experimentally testable predictions . ( 1 ) Oscillations in a majority of VPAC2 receptor–negative neurons dispersed at low density should rapidly damp out after induction by serum shock . If validated , this would confirm that loss of rhythmicity in a VPAC2 receptor–negative SCN slice is not due to unexpected cell–cell interaction . To test that neurons need periodic synchronization signals to be rhythmic , one could treat VIP-deficient neurons with constant high levels of VPAC2 agonist . We predict that arrhythmic neurons will stay arrhythmic . ( 2 ) A low number of neurons or a low connectivity should result in desynchrony . Medium-density neuron cultures with a small number of neurons should display variability in their synchrony levels ( including nonoscillatory neurons as defined by the order parameter R ) . Increasing the density or the number of neurons would reduce the variability of synchronization levels and increase the average synchrony . Knife cuts in SCN slices to isolate different numbers of neurons could be a way to test size dependency . We predict that pieces that contain fewer than 40 neurons will display large variations in synchronization levels . In mice heterozygous in the gene coding for the VPAC2 receptor , SCN neurons seem to have synchronization properties similar to those in wild-type mice [18] . However , if connectivity is subtly altered in heterozygous mice , a prediction is that asynchrony will occur in larger-cut SCN pieces than for wild-type mice . ( 3 ) In high-density dispersal cultures , normalized amplitudes [44] of oscillations should be negatively correlated with the phases as in Figure 6F , provided there is a small variation in the natural amplitudes of isolated neurons . This would be a way to estimate the free-running periods of individual neurons without the need to disperse them . The synchronization of damped oscillators is independent from the particular intracellular model used . Systems with a Goodwin-type model as used in [45] , the Leloup-Goldbeter model [33] , and other simple negative feedback oscillators have similar synchronization properties ( Figure S4–S6 ) . Numeric exploration of such models suggests that positive feedback loops facilitate , but are not necessary for , efficient synchronization ( unpublished data ) . The variability of behavioral periods in Rev-Erbα knockout mice , in which the positive loop is dysfunctional , could reflect that feature [46] . One could test whether synchronization properties of SCN neurons are altered in these mice by analyzing SCN neurons from Rev-Erbα−/−Per2:luc double-transgenic mice . We predict that Rev-Erbα knockout mice will have lower amplitude and more spread-out synchronized SCN neurons . Li and coworkers [47] introduced “transient resetting” as a possible synchronization mechanism , in which uncoupled oscillators are synchronized by a force ( which may be noise ) that transiently moves them to a region where they have a stable steady state . In our model , the driving force was generated autonomously by the coupled oscillators . To our knowledge , it is the first time that synchronization-induced rhythmicity is described in a biological system . Damped but uncoupled oscillators have been considered before in a model of interaction between a clock and a zeitgeber input pathway [41] . Temporal and spatial rhythms can occur when identical stable systems are diffusively coupled together , giving rise to well-studied Turing instabilities [48 , 49] . Oscillations can also emerge from electrical coupling between nonoscillating cells [50 , 51] . Nonetheless , two features distinguish our work from that mentioned above . ( 1 ) In our system , temporal instabilities do not arise from spatial heterogeneity or local coupling because synchrony also holds in case of all-to-all coupling of identical oscillators . ( 2 ) Oscillators are directly coupled , instead of being diffusively coupled [52] . Direct coupling means that even under perfect synchrony , the coupling term is nonzero , unlike in the diffusive coupling case . The question of how a coherent and robust circadian output is generated from a heterogeneous network of 20 , 000 oscillators in the SCN has led to many surprising results [2 , 3 , 18–20] , bringing a better understanding of the interaction between the single-cell clock and its organization . To understand the orchestration of timekeeping in the SCN , intracellular circadian modules cannot be isolated from their intercellular communication components .
The intracellular oscillator is a seven-variable model representing clock genes' mRNA and proteins [23] . It consists of interlocked transcriptional/translational feedback loops and reflects the essential features of the mammalian circadian oscillator ( Figure 1 ) . The circadian release of a neuropeptide mediates intercellular coupling of circadian cells in the SCN [9 , 12–18] . Here , we assumed that the release of the neuropeptide is induced by the cytosolic PER/CRY protein complex . The neuropeptide activates a two-step cascade in connected cells that leads to Per/Cry mRNA transcription . The assumption that the PER/CRY complex induces neuropeptide release was made to ensure that the transmitter is released quickly after Per/Cry gene activation . The cascade is schematized by PKA and CREB activation . With the neurotransmitter and the two-step cascade , the complete single-cell system has ten variables . The nonlinear transcription functions are The coupling term Q induces a signaling cascade leading to activation of Per/Cry promoter , and is proportional to the local mean field F . The variables represent the following species: Y1 , Per/Cry mRNA; Y2 , PER/CRY cytosolic complex; Y3 , nuclear PER/CRY complex; Y4 , Bmal1 mRNA; Y5 , cytosolic BMAL1; Y6 , nuclear BMAL1; Y7 , transcriptionally active BMAL1*; V , neurotransmitter; X1 , PKA; and X2 , CREB . F is the local mean field as defined in Equation 17 , and K is a scalar determining the coupling strength . Equations for X and Y are replicated n times , where n is the number of cellular oscillators ( we omitted the indices i for readability ) . The entry Qi corresponds to the coupling term in cell i , i = 1 , . . . , n . Furthermore , each system is scaled by a factor ei to generate a distribution of periods . For ei , we generated a sample gi drawn from a Gaussian distribution centered at 1 with a standard deviation of 0 . 05 . Additional heterogeneity was added in the form of a vector ui that defines a linear or radial gradient of periods according to the position of the cells in the SCN . The scaling factor ei is defined as This produces a distribution of periods between 20 and 28 h . The parameter values for the model are v1b = 9 . 0 , k1b = 1 . 0 , k1i = 0 . 56 , p = 3 , h = 2 , k1d = 0 . 18 , k2b = 0 . 3 , q = 2 , k2d = 0 . 1 , k2t = 0 . 36 , k3t = 0 . 02 , k3d = 0 . 18 , v4b = 1 . 0 , k4b = 2 . 16 , r = 3 , k4d = 1 . 1 , k5b = 0 . 24 , k5d = 0 . 09 , k5t = 0 . 45 , k6t = 0 . 06 , k6d = 0 . 18 , k6a = 0 . 09 , k7a = 0 . 003 , k7d = 0 . 13 , k8 = 1 . 0 , k8d = 4 . 0 , K = 1 . 0 , kx1 = 3 . 0 , X1T = 15 . 0 , kdx1 = 4 . 0 , kx2 = 0 . 25 , X2T = 15 . 0 , kdx2 = 10 . 0 , and L0 = 0 . 22 . Rates k are in h−1 except k2b ( h−1nM− ( q−1 ) ) , k1b ( nM ) , k1i ( nM ) , and v4b ( nM ) , kx1 and kx2 ( h−1nM−1 ) , v and L0 ( nM h−1 ) , and XT ( nM ) . Parameters were minimally adapted from the original model [23] to satisfy the following conditions: individual oscillators must be damped , and the coupled system must synchronize with a circadian period . Specifically , we reduced the Hill coefficient p from 8 to 3 . A small Hill coefficient makes the periods longer , so we compensated the periods by increasing the degradation rates . Neuropeptide release and action in the intercellular medium are fast compared with the 24-h period of the neurons , allowing diffusion and transport delays between connected cells to be neglected . For a given neuron , we defined a local mean field as the average concentration of neurotransmitter released by the neighboring ( connected ) cells . This type of coupling is termed direct , as opposed to a diffusive coupling [52] . We considered two different shapes for the SCN . ( 1 ) The whole SCN is defined on a 3-D discrete cubic grid G , of size s , where each nonempty node represents a neuron ( Figure 2D ) . Each neuron ( node ) is assigned a number from 1 to n , and empty nodes have a value 0 . Functional or physical regions of the SCN are defined by subgrid E of G by retaining as nonempty only the nodes belonging to the desired region . This way , various overlapping regions can be defined . ( 2 ) An SCN slice is defined on a 2-D square grid in a manner analog to the whole SCN ( Figure 2C ) . Regions of the slice are constructed the same way as in 3-D . We used a Euclidian distance d ( i , j ) to measure the distance between neurons i and j , with d = 1 for adjacent neurons ( Figure 2B ) . A coupling matrix M , which depends on the geometry of the SCN and a connectivity map C , describes the connections between cells . A neuron i , belonging to a population of size n , receives an input from neuron j if Ci , j is 1 . We considered three different types of coupling for C ( Figure 2A–2C and Figure S1 ) . Random coupling ( type 1 ) : Ci , j = 1 with probability c0 ( the nominal connectivity ) ( Figures 2A and S1A ) . All-to-all coupling is a particular case of sparse coupling when c0 = 1 . Nearest-neighbor coupling ( type 2 ) : Ci , j = 1 if di , j < dmax and neuron i is downstream of neuron j ( Figures 2B and S1B ) . SCN-like coupling ( type 3 ) : we divided the SCN into four regions: left and right VL , and left and right DM regions . The VL part ( the ventral core ) corresponds to the light-inducible cells and has many projections into the DM region [3 , 53] . Neurons within the VL part are not coupled and are not spontaneously rhythmic [3 , 18] . The DM region ( the dorsal shell ) receives the input from the VL neuronal projections . We used a uniform type 2 coupling ( nearest-neighbor ) to couple DM cells ( Figures 2C and S1C ) . We used this coupling type in conjunction with an LD cycle . In addition to the connectivity , a function f ( d ) determines the relative coupling strength between neurons separated by a distance d . Because of the mean field assumption , the effect of all neurons upstream of neuron i is averaged , so the coupling matrix M ∈ Rn×n is where the dot ( · ) denotes the element-wise matrix product and C~ is normalized so that the sum of each line is 1 , The matrix C is normalized as a result of the local mean field assumption: the input to one cell is the average of the signal coming from upstream neurons . The fraction of nonzero entry of C is the connectivity , a scalar denoted by c . The input at each neuron in the SCN is described by the mean field vector F ∈ Rn , where V is the transmitter concentration ( Equation 8 ) . To measure synchrony , we used an order parameter R [54] defined as where 〈 . . . 〉 denotes the average over time , and is the average of the variable of interest among oscillators . For comparison with bioluminescence recordings , we chose the variable of interest to be Per/Cry mRNA concentration , Y1 in Equation 1 ( half-lives of the reporters are short enough for the reporter itself to be neglected [20] ) . We simulated light entrainment by a clipped sine wave , ( 0 < L ( t ) ≤ L0 and L ( t ) = 0 alternating every tlight and tdark h ) . Unless specified , initial conditions for each simulation were randomly chosen , with each variable taking a value between 0 and 2 times the average value of the variable when the system is synchronized . Simulations and analysis were performed in the Matlab 6 . 5 environment ( The MathWorks , http://www . mathworks . com ) . The ordinary differential equations were simulated with the medium-order adaptive step solver ode45 . The codes are available on request . | Circadian rhythms , characterized by a period close to 24 h , are observed in nearly all living organisms , from cyanobacteria to plants , insects , and mammals . In mammals , the central circadian clock is located in the suprachiasmatic nucleus ( SCN ) of the hypothalamus , where it receives light signals from the retina . In turn , the SCN controls circadian rhythms in peripheral tissues and behavioral activity . The SCN is composed of about 20 , 000 neurons characterized by a small size and a high density . Within each individual neuron , clock genes and proteins compose interlocked regulatory feedback loops that generate circadian oscillations on the molecular level . SCN neurons dispersed in cell cultures display cell-autonomous oscillations , with periods ranging from 20 h to 28 h . The ventrolateral part of the SCN receives light input from the retina , serving as a relay for the dorsomedial part . Coupling and synchronization among SCN neurons are ensured by neurotransmitters . A desire to understand how such a network of heterogeneous circadian oscillators achieves a synchronous and coherent output rhythm has motivated extensive experimental and theoretical work . In this paper , we present a molecular model combining intracellular and extracellular dynamics for the SCN circadian system , and propose a novel synchronization mechanism . Our results predict a dual role for the coupling factors within the SCN , both in maintaining the rhythmicity and in promoting the synchronization between the circadian oscillators . | [
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] | 2007 | Synchronization-Induced Rhythmicity of Circadian Oscillators in the Suprachiasmatic Nucleus |
The tick-borne flavivirus , Powassan virus ( POWV ) causes life-threatening encephalitis in humans in North America and Europe . POWV is transmitted by ixodid tick vectors that feed on small to medium-sized mammals , such as Peromyscus leucopus mice , which may serve as either reservoir , bridge or amplification hosts . Intraperitoneal and intracranial inoculation of 4-week old Peromyscus leucopus mice with 103 PFU of POWV did not result in overt clinical signs of disease . However , following intracranial inoculation , infected mice seroconverted to POWV and histopathological examinations revealed that the mice uniformly developed mild lymphocytic perivascular cuffing and microgliosis in the brain and spinal cord from 5 to 15 days post infection ( dpi ) , suggesting an early inflammatory response . In contrast , intracranial inoculation of 4-week old C57BL/6 and BALB/c mice was lethal by 5 dpi . Intraperitoneal inoculation was lethal in BALB/c mice , but 40% ( 2/5 ) of C57BL/6 mice survived . We concluded that Peromyscus leucopus mice infected i . c . with a lethal dose of POWV support a limited infection , restricted to the central nervous system and mount an antibody response to the virus . However , they fail to develop clinical signs of disease and are able to control the infection . These results suggest the involvement of restriction factors , and the mechanism by which Peromyscus leucopus mice restrict POWV infection remains under study .
Powassan virus ( POWV ) is a tick-borne flavivirus ( TBFV ) belonging to the tick-borne encephalitis virus ( TBEV ) serogroup . POWV is closely related to the deer tick virus ( DTV ) , also known as POWV lineage II , and the two are the only TBFVs in the TBEV serogroup known to circulate in North America . Current information suggests that the incidence of POWV , particularly lineage II , is increasing in the USA [1] . Despite the availability of a highly effective vaccine , the TBEV serogroup of viruses is responsible for up to 15 000 infections annually in Europe , leading to life-threatening encephalitis and death in close to 40% of infected cases depending on the TBEV strain [2–4] . POWV was first described in 1958 in a fatal case of encephalitis in a 5 year old boy in the small town of Powassan , Ontario , Canada [5] . Since then , POWV has continued to cause sporadic infections in the USA , with cases reported in several states , such as New York State , New Hampshire and Massachusetts [1 , 6–11] . POWV is also known to cause human disease in eastern regions of Russia [9] . Transmission of TBFVs to humans is mainly through tick bites , but alimentary infection through the consumption of unpasteurized milk and/or milk products obtained from infected domestic animals in endemic regions is also well documented [12–14] . Although POWV has been isolated from Dermacentor andersoni ticks , the blacklegged hard-bodied ticks , Ixodes scapularis and Ixodes cookei , are the principal vectors responsible for transmitting POWV in North America , and Hemaphysalis longicornis is known to transmit the virus in East Asia [1 , 15–17] . Field studies have shown that the prevalence of TBFVs in ticks from different geographic locations is variable . For example , the prevalence of Powassan virus in Ixodes scapularis in the same area in the state of Connecticut rose from 0% in 2008 to 3 . 9% in 2010 [18] . A study conducted in Switzerland showed that 0 . 16–11 . 11% of Ixodes ricinus ticks were positive for TBEV by RT-PCR [19] . Once infected , ticks harbor the virus at each developmental stage for the duration of their lives , which may span several years , and they can also transmit the TBFV transovarially [20–22] . Through a process known as “co-feeding” , infected ticks feeding in close proximity on the same host can rapidly transmit TBFVs to each other via migratory cells in the skin [21 , 23–25] . Thus , the ticks play a critical role in the maintenance of TBFVs in nature by direct horizontal tick-to-tick transmission . The wild animal species responsible for much of TBFV transmission are the same species from which the vectors naturally obtain blood meals , i . e . , small to medium-sized mammals , such as white-footed mice ( Peromyscus leucopus ) , striped field mice ( Apodemus agrarius ) , skunks ( Mephitis mephitis ) and woodchucks ( Marmota momax ) [1 , 26–30] . The detection of viral RNA or isolation of TBFVs from wild rodents is substantive evidence implicating these mammals as reservoirs or amplification hosts . For example , the TBEV strain A104 was isolated from the brain of a wild-caught yellow-necked mouse , Apodemus flavicolis , in Austria [31] . In Hokkaido , Japan , the TBEV strains Oshima 08-As and Oshima-A-1 were isolated from spleens of Apodemus speciosus , and Oshima-C-1 from the gray-backed vole Clethrionomys rufocanus [32 , 33] . Researchers in South Korea also reported PCR detection as well as isolation of TBEV from lung and spleen tissue dissected from wild Apodemus agrarius mice [30] . A group in Finland detected TBEV RNA in mouse brains , but some mice that had viral RNA were seronegative [34] . Additional and surrogate evidence suggesting exposure to TBFVs in wild rodents includes the detection of anti-POWV antibodies in wild-caught Peromyscus truei and Peromyscus maniculatus in New Mexico; Myodes rutilus in Siberia and Alaska; and Myodes gapperi in Southern Alaska [9] . Bank voles , Myodes glareolus , wild-caught in a small TBEV focus area in Hungary had higher seropositivity rates of 20 . 5% , than a combined Apodemus flavicolis ( 3 . 7% ) and Apodemus agrarius ( 4 . 6% ) [35] . The difference could be the behavioral result of less mobility of lactating bank voles , which become easy targets for questing TBEV-infected ticks [35] . In spite of this unequivocal evidence that wild small-medium sized mammals play a crucial role in the biology and ecology of the TBFVs , very little is known about how these animals actually respond when exposed to the viruses . The inbred laboratory mouse strain BALB/c is a well-characterized model for studying Powassan virus infection and has been shown to suffer severe neurological disease [36] . Using this model , it has been established that death may occur via respiratory insufficiency , and that yet-undefined component ( s ) of tick salivary gland extract affects the course of POWV infection [37 , 38] . Peromyscus leucopus and the congeneric deer mice ( Peromyscus maniculatus ) are the most abundant mixed-forest rodents in eastern USA [39] , where most of POWV infections have been reported . After observing that inoculation of POWV ( lineage II ) caused no overt disease in adult Peromyscus leucopus ( P . leucopus ) mice , Telford et al . suggested these mice could be reservoirs of POWV [40] . However , limited conclusions regarding pathogenesis in these mice could be drawn from these studies . A recent review also cites resistance or tolerance to POWV in Peromyscus mice , suggesting that the species may act as natural reservoirs [41] . Therefore , we decided to rigorously model POWV infection in this natural host . Intraperitoneal ( i . p . ) and intracranial ( i . c . ) inoculation of these mice resulted in no overt clinical signs of disease . However , lesions suggestive of mild inflammation were observed in the brains and spinal cords of i . c . -inoculated mice that were accompanied by limited virus replication in the olfactory lobe of the brain . In contrast to the 2 strains of laboratory mice , the P . leucopus mice were able to limit the infection and did not suffer clinical disease .
POWV ( a kind gift from Dr . Robert Tesh , World Reference Center for Emerging Viruses and Arboviruses , University of Texas Medical Branch ) was triple-plaque purified from a primary stock that had been passaged 6 times in Vero cells ( ATCC ) . The virus was semi-purified by ultracentrifugation in a SW28 rotor ( Beckman-Coulter ) at 131 000 x g over a 20% sucrose cushion at 4°C and resuspended in serum-free Dulbecco’s Modified Eagle Medium ( sfDMEM; Life Technologies ) . Sanger sequencing indicated that the nucleotide sequence of the POWV genome was 99 . 99% identical to the LB strain . Only 10 nucleotide sequence differences were observed between our POWV strain and that of the LB strain in GenBank ( Accession number L06436 ) , leading to 5 amino acid sequence differences in NS1 ( L838F ) , NS3 ( N2078T ) , NS4B ( A2444S and A2457V ) , and NS5 ( G2670E ) . The Rocky Mountain Laboratories ( National Institute of Allergy and Infectious Diseases , National Institutes of Health ) Animal Care Use Committee reviewed and approved the animal study protocol ( ASP ) , number 2014-012-E . The ASP adhered to the National Institutes of Health Guidelines , the Public Health Service Policy on Humane Care and Use of Laboratory Animals , the United States Department of Agriculture’s Animal Welfare Act , and the Guide for the Care and Use of Laboratory Animals . All the mice used in this study were 4 weeks old , and all animal experiments were performed in animal biosafety level-3 ( ABSL3 ) facilities . P . leucopus mice were bred from a colony at the Rocky Mountain Laboratories’ animal facility . The colony was established from P . leucopus mice , which were wild-caught in North-Western USA more than 13 years ago . Sentinel monitoring of the colony is performed quarterly and the colony is negative for all tested murine pathogens . BALB/cAnNHSd mice were purchased from Harlan Laboratories and C57BL/6J mice were supplied by Jackson Laboratories . All mice were housed in individually ventilated cage systems with a 12:12 light-dark cycle with water and food provided ad libitum . Intraperitoneal inoculations were performed with POWV doses between 102 and 108 PFU in 100 μl sfDMEM using a 25 gauge x ½" needle . Intracranial infections were done with 103 PFU of POWV in 50 μl sfDMEM . Control mice for the different routes were inoculated with equivalent volumes of serum-free DMEM . Experimental end points were set at 28 days post infection . The mouse organs that were harvested at necropsy for total RNA extraction were blood , brain , kidney , liver , cervical lymph nodes and spleen . Blood was centrifuged to remove serum and the cell pellet was used for total RNA extraction . Harvested mouse organs were homogenized in 1 mL of TRIzol ( Invitrogen ) by vigorous beating with steel or ceramic beads . Total RNA extraction was performed using an RNeasy kit ( Qiagen ) according to the RNeasy manufacturer’s protocol . A microgram of total RNA extracted from each organ was used to synthesize cDNA using a SuperScript VILO cDNA synthesis kit ( Invitrogen , Life Technologies ) according to the manufacturer’s instructions . The qPCR reaction was made up of 1X POWV-specific forward ( GCACGGACCTCTATGTGTATTC ) and reverse ( AACTGGTCCTCTCACTGTAGTA ) primers , probe ( TAGTGCAGTGGAAAGAAGCGCAGA ) , 1X Platinum qPCR SuperMix-UDG with ROX buffer ( Invitrogen ) , H2O and 2 μl cDNA . The qPCR was analyzed on a 7900HT Fast Real Time PCR machine ( Applied Biosystems ) . A plasmid containing an insert with the target POWV sequence was serially diluted and used for the standard curve from which the genome copy numbers in various mouse organs were extrapolated . An in-house IgG ELISA was used to detect anti-POWV antibodies in the serum of infected and control mice under BSL3 conditions . The antigen was generated by infecting 2 x 106 Vero cells ( ATCC ) in a 75 cm2 flask ( Nunc ) with POWV at a multiplicity of infection of 1 . At the onset of the cytopathic effect , the monolayer was washed 3 times with cold phosphate-buffered saline ( PBS ) followed by the addition of 10 ml of PBS containing 10% borate and 1% Triton X-100 . Cell lysis was enhanced by 3 freeze-thaw cycles . The lysate was clarified by centrifugation at 3000 rpm for 20 min . 100 μl of a 1:1000 dilution of the lysate was used to coat wells of a 96-well plate ( Nunc ) overnight at 37°C in a humidified chamber . Unbound antigen was removed followed by washing the wells twice with PBS containing 0 . 025% Tween 20 ( wash buffer ) . Blocking was performed with a blocking solution of 0 . 05% skimmed milk in PBS with 0 . 05% Tween 20 for 2 h at 37°C . The blocking solution was aspirated followed by washing 4 times with the wash buffer . 8 , 5-fold serial dilutions of each mouse serum sample were prepared and 100μl of each dilution was added to appropriate wells and incubated at 37°C for 2 h . A positive anti-POWV antibody was hyper-immune serum of POWV-infected C57BL/6 mice , and ascites fluid from uninfected mice was used as negative antibody control . The diluted serum samples were aspirated after the incubation , followed by washing the wells 6 times with the wash buffer and 100 μl of horseradish peroxidase-labeled anti-P . leucopus IgG antibody ( KPL ) was added at 1:1000 dilution and incubated at 37°C for 30 min . For the positive control , an anti-mouse IgG antibody ( Dako ) was used , diluted to 1:1000 and also incubated at 37°C for 30 min . The secondary antibodies were aspirated and the wells were washed 6 times with the wash buffer , and 100 μl of a 3 , 3' , 5 , 5'-tetramethylbenzidine ( TMB ) substrate ( Sigma-Aldrich ) was added and incubated at room temperature for 1 h . The reaction was stopped with 2 M H2SO4 and color reactions were used to qualitatively call positive or negative results by visual examination . To perform a focus reduction test ( FRNT ) , sera from i . c . -inoculated P . leucopus mice were serially diluted 5-fold , starting at 1:10 . Serum from uninfected P . leucopus mice was used as negative controls . The diluted serum samples were incubated with 103 PFU of POWV at room temperature for 30 minutes , followed by infecting confluent Vero cells in 12-well plates and incubating at 37°C with rocking for 1 h . The infecting preparations were aspirated and the wells were washed 3 times with PBS . The cells were overlaid with complete DMEM containing 0 . 8% methylcellulose ( Sigma-Aldrich ) and incubated for 3 days . POWV foci were developed and counted using an immunofocus assay as described before [42] . Necropsies of mock- and POWV-infected mice were performed under ABSL3 conditions . Harvested tissues were fixed in 10% neutral-buffered formalin for 7 days . Tissues were placed in cassettes and processed with a Sakura VIP-5 Tissue Tek on a 12 h automated schedule using a graded series of ethanol , xylene and ParaPlast Extra . Embedded tissues are sectioned at 5 μm and dried overnight at 42°C prior to staining . Hematoxylin and eosin ( H&E ) staining was performed using standard procedures . In situ hybridization ( ISH ) was performed on 5 μm tissue sections . Probes hybridizing to the positive-sense genomic ( + ) and minus-sense complementary ( - ) RNA strands were designed and synthesized at Advanced Cell Diagnostics ( Hayward , California ) to target the region spanning nucleotides 246–1687 and 7894–9335 , respectively . The probe for the ( - ) sense strand was specific for the replicating RNA . Detection of POWV RNA was performed using the RNAscope FFPE assay ( Advanced Cell Diagnostics ) as previously described [43] and in accordance with the manufacturer’s instructions . Briefly , tissue sections were deparaffinized and pretreated with heat and protease before hybridization with target-specific probes for Powassan virus RNA . Ubiquitin C and the bacterial gene , dapB , were used as positive and negative controls , respectively . Whole-tissue sections from selected representative cases were stained for Powassan viral RNA , UBC and dapB by the RNAscope VS FFPE assay ( RNAscopeVS ) using the Ventana Discovery ULTRA slide auto staining system ( Ventana Medical Systems Inc . ) .
Our first goal was to confirm neurotropism and neurovirulence in 2 laboratory strains of mice , BALB/c and C57BL/6 and then to assess the neurovirulence of POWV in age-matched P . leucopus mice . Thus , 4-week old BALB/c and C57BL/6 were challenged intracranially ( i . c . ) with 103 PFU of virus . All 20 BALB/c mice succumbed to disease at 4 dpi , whereas 45% ( 9/20 ) of C57BL/6 succumbed at 4 dpi and the rest at 5 dpi ( Fig 1A ) . In both mouse species , the experimental endpoint was preceded by rapid and severe disease , characterized by hunched posture , ruffled fur , hind limb paralysis and severe weight loss . In addition to hind limb paralysis , some C57BL/6 mice also presented fore-limb paralysis . We determined the level of POWV in the brain of these mice by qPCR analysis , and extremely high copy numbers of POWV RNA genomes were detected in the brains of BALB/c and C57BL/6 mice ( Fig 1B ) . The average genome copy number in the brain homogenates of i . c . -inoculated BALB/c mice was 7 x 108 copies/μg of total RNA , whereas the average genome copy numbers in brain homogenates of i . c . -inoculated C57BL/6 mice was 1 x 108 copies/μg of total RNA ( Fig 1B ) . Interestingly , qPCR analyses showed that POWV infection of the brain , spread to other organs such as spleens and kidneys after i . c . inoculation . For example , average POWV RNA copy numbers in the C57BL/6 spleens was 3 . 6 x 106 copies/μg of total RNA ( range: 2 . 3 x104–5 . 7 x 107 copies/μg of total RNA ) , and the average in the kidneys was 1 . 2 x 106 copies/μg of total RNA ( range: 6 . 8 x 103–7 . 0 x 106 copies/μg of total RNA ) . The BALB/c spleens contained an average of 7 . 6 x 106 POWV RNA copies/μg of total RNA ( range: 4 . 4 x 104–9 . 1 x 107 copies/μg of total RNA ) and the kidneys had an average of 1 . 4 x 107 copies/μg of total RNA ( range: 2 . 0 x 105–9 . 1 x 107 copies/μg of total RNA ) . An average of 8 . 6 x 104 POWV RNA copies/μg of total RNA ( range 8 . 6 x 104–2 . 5 x 105 copies/μg of total RNA ) was detected in the blood of BALB/c mice , whereas an average of 3 . 3 x 106 copies/μg of total RNA ( range: 6 . 5 x104–2 . 8 x 107copies/μg of total RNA ) was detected in C57BL/6 mouse blood . In summary , i . c . infection of the laboratory strains of mice led to a systemic fatal infection of the nervous system accompanied by widespread permissive viral replication . We next assessed neurovirulence of POWV for P . leucopus mice . A total of 20 4-week old P . leucopus mice were inoculated i . c . with 103 PFU of POWV and observed over a 28 day period . In marked contrast to the BALB/c and C57BL/6 mice , all of the inoculated P . leucopus mice survived to 28 days ( Fig 1A ) , without showing any clinical signs of disease . These findings indicated that the P . leucopus mice were resistant to neurological disease induction by i . c . inoculation of a dose of POWV that was lethal for all of the BALB/c and C57BL/6 mice . Although P . leucopus mice challenged with POWV via i . c . inoculation did not show any clinical signs of disease , viral RNA was detected by qPCR in their brain homogenates at the experimental end point of 28 dpi ( Fig 1B ) . The average POWV RNA genome copy number in P . leucopus mouse brains was 778 copies/μg of total RNA . Thus , limited POWV replication took place in the brains of i . c . -inoculated P . leucopus mice , but this did not lead to obvious clinical disease . To gain additional insight into the POWV replication kinetics in P . leucopus mice , we i . c . inoculated 4-week old mice in 8 groups of 5 and euthanized them daily from 1 dpi through to 7 dpi , as well at 15 dpi . We could isolate infectious POWV from the brain homogenates from 1 dpi through to 7 dpi although the virus titer did not increase in a dramatic fashion ( Fig 2A ) . Using qPCR , we determined that the average POWV RNA copy number at 1 dpi was 4 . 7 x 104 copies/μg of total RNA ( Fig 2B ) . This average steadily peaked to 3 . 8 x 105 copies/μg of total RNA at 7 dpi , but declined to 1 x 104 copies/μg of total RNA at 15 dpi ( Fig 2B ) . The presence of POWV RNA in the brain was also associated with viral RNA in the blood for the first 4 days post infection ( Fig 2C ) , suggesting short-lived early viremia . These results indicated that POWV was able to initiate a productive , infection in P . leucopus mice following i . c . challenge , but that the mice were able to limit the infection and remained completely asymptomatic . Our next aim was to define the neuroinvasiveness of POWV in laboratory mouse strains as well as in age-matched P . leucopus . Therefore , we inoculated 5 4-week old BALB/c mice intraperitoneally with 103 PFU of virus . BALB/c mice have been previously reported to succumb to POWV encephalitis within 9 days [36] , and the mice in our experiments started to show clinical signs of disease i . e . , ruffled fur and weight loss at 6 dpi . All of the BALB/c mice progressed to show signs of severe neurological disease , characterized by hind limb paralysis and >15% weight loss and were euthanized by 8 dpi ( Fig 3A & 3B ) . These results confirmed the previous reports that POWV infection in BALB/c mice is neuroinvasive . We also challenged 5 4-week old C57BL/6 mice i . p . with the same dose of POWV . One mouse was euthanized at 8 dpi due to severe hind limb paralysis , ruffled fur , emaciation and >15% weight loss ( Fig 3A & 3C ) . The other 4 POWV-infected C57BL/6 mice also showed signs of disease at 8 dpi , but the weight loss was variable <15% ( Fig 3C ) . An additional 2 mice developed severe progressive disease and were euthanized at 11 dpi . The 2 surviving C57BL/6 mice recovered and lived without obvious signs of disease until they were euthanized at the experimental end point of 28 dpi ( Fig 3A ) . In order to quantify the level and extent of infection in BALB/c and C57BL/6 mice , we were able to detect POWV RNA by qPCR in the brain , but not in the spleen , liver , kidney or cervical lymph node LN . The average POWV RNA genome copy number in the BALB/c brains was 1 . 5 x 106 copies/μg of total RNA . The POWV RNA genome copy numbers in the brains of C57BL/6 mice were more varied , depending on severity and outcome of disease . The highest POWV RNA genome copy number was 3 . 3 x 107 , which was detected in the animal which was euthanized at 8 dpi ( Fig 3D ) . The 2 animals that survived to the experimental end point of 28 dpi had lower viral genome copy numbers of 440 and 2175 copies/μg of total brain RNA , respectively ( Fig 3D ) . In marked contrast , i . p . inoculation of 4-week old P . leucopus mice with 103 PFU of POWV resulted in no overt signs of clinical disease and all inoculated mice survived to the experimental end point of 28 days ( Fig 3A ) . Furthermore , no evidence of illness was evident over the 28 day period of observation after i . p . inoculation of 102 , 105 or 108 PFU of POWV . In addition , no POWV RNA was detected by qPCR in the brain , spleen , liver or cervical LN samples harvested from i . p-inoculated P . leucopus mice at 28 days post challenge . Thus , these results suggested that POWV was not neuroinvasive in P . leucopus mice . To probe for subtle P . leucopus mouse responses to POWV , we examined sections of brain and spinal cord for any histological changes at various time points after i . c . inoculation with POWV . The histopathology revealed changes consistent with mild inflammatory responses in the brains and spinal cords of i . c . -inoculated P . leucopus mice from 5 to 15 dpi . The specific lesions were nodular microgliosis and lymphocytic perivascular cuffing ( Fig 4 ) , and these were uniform and more extensive at 15 dpi . However , no lesions were present at 28 dpi , suggesting that inflammation had resolved . Examination of brain and spinal cord sections obtained from i . c . -inoculated BALB/c and C57BL/6 mice revealed the presence of lesions consistent with encephalitis and meningitis . In addition to nodular microgliosis and lymphocytic perivascular cuffing observed in P . leucopus mice , BALB/c and C57BL/6 mice also presented lymphocytic infiltrations in the meninges ( Fig 4 ) . Taken together , these results suggested that POWV induced low-grade encephalitis in i . c . -inoculated P . leucopus mice . However , the inflammatory response was not associated with meningitis and seemed unaccompanied by observable clinical signs of illness . In contrast , BALB/c and C57BL/6 mice suffered severe , usually fatal , encephalitis , coupled with meningitis . We used in situ hybridization ( ISH ) to analyze the distribution of POWV plus-sense genomic RNA in the CNS of P . leucopus mice over time , after i . c . inoculation , and small amounts of viral RNA were detectable at 1 dpi only in the subventricular white matter . From 2 dpi through to 7 dpi , POWV RNA was more abundant , but localized mainly to the olfactory bulb and ventricle ( Fig 5A ) . Lesser amounts could be detected in the cerebral cortex , granular layer of the cerebellum and spinal cord ( Fig 5A ) . However , the viral RNA was undetectable in P . leucopus CNS by ISH at 28 dpi ( Fig 6 ) . Calculations based on the qPCR results enabled us to estimate that the average POWV RNA copy numbers in the P . leucopus brains at 28 dpi ( Fig 1 ) translated to ~0 . 004 genome copies per cell , suggesting that the viral load was too low for detection with ISH . Next , we performed ISH analyses with a probe targeting the minus-sense strand of POWV RNA to determine if POWV was actually replicating in the brain of i . c-inoculated P . leucopus mice . POWV ( - ) RNA was detected and also localized mainly to the olfactory bulb and the ventricle ( Fig 5Bii ) . Thus we confirmed that P . leucopus mice supported limited POWV replication . In contrast , POWV plus-sense genomic RNA was widely distributed in most parts of the brain and the spinal cord in BALB/c and C57BL/6 mice ( Fig 6 ) . Minus-sense RNA was also distributed extensively in the brain ( Fig 5Biii & 5Biv ) , indicating widespread permissive viral replication in these 2 mouse species . To determine if P . leucopus mice challenged with POWV mounted an antibody response , we screened sera from i . c . and i . p . inoculated mice with an ELISA assay . The analysis showed that i . c . -inoculated P . leucopus mice generated anti-POWV antibodies in the titer range 250–1250 . Further analysis indicated that these antibodies had a FRNT60 titer of 250 . Thus , P . leucopus mice generated neutralizing antibodies when inoculated i . c . However , anti-POWV antibodies were undetectable in mice that had been i . p . inoculated , except those that got 108 PFU of POWV ( titer 250 ) .
Powassan virus ( POWV ) causes severe encephalitis and death in humans in North America and some parts of Russia [1 , 5 , 6 , 8 , 9 , 44 , 45] . The virus persists in a cycle involving infected ixodid tick vectors , and small to medium-sized mammals , which play important roles as reservoirs , amplification or bridge hosts [1 , 26–28] . In this study , we have examined POWV infection in 2 strains of laboratory mice ( BALB/c and C57BL/6 ) , and a strain of wild mice ( P . leucopus ) , which might be a natural host for this virus . POWV was neurovirulent and neuroinvasive in both strains of laboratory mice , causing a severe neurological disease that was uniformly fatal in BALB/c mice , but killed only 60% of C57BL/6 mice . Thus , these 2 strains of mice were suitable models for the human disease [36 , 37 , 46] . In marked contrast , the Peromyscus showed no evidence of virus replication or disease after peripheral inoculation , although mice inoculated with 108 PFU developed a modest antiviral antibody response . Notably , although i . c . inoculation of POWV into the Peromyscus mice did not result in observable disease , there was clear evidence of low level viremia and limited viral replication in the olfactory bulb that was cleared by 28 dpi . Thus , the biology of this virus in the natural host is very different from that in laboratory mice , and our findings may have implications for the role of the natural host in the ecology of POWV and other pathogens that are found in these mice [38 , 40] . Low-level viremia was observed only at early time points of experimental infection in P . leucopus mice . This may be the critical time period during which the ticks could acquire virus from feeding on a host under these experimental conditions . Natural infection of mammals occurs via tick-bites , and the tick saliva has been shown to enhance transmission of POWV and affects the course disease [37] . However , co-feeding is probably the major mechanism by which TBFVs are transmitted between ticks during feeding [20 , 21 , 23 , 24] . Intraperitoneal inoculation of 4-week old BALB/c mice was uniformly lethal in our laboratory . Interestingly , C57BL/6 mice were partially resistant to i . p challenge with POWV and the surviving mice still had viral RNA in the brain tissue , suggesting viral persistence . This result was similar to the effect of the mosquito-borne West Nile virus ( WNV ) in C57BL/6 mice inoculated subcutaneously in which the virus caused 20% mortality [47] . We and others previously showed that C57BL/6 mice are partially resistant to the attenuated TBFV Langat virus when inoculated i . p . [48 , 49] , suggesting that a similar mechanism of resistance may be involved . However , one report recently described 100% mortality in C57BL/6 mice inoculated with 5 x 103 or 5 x 106 PFU of POWV via footpad injection [46] . It is unclear if these differences result from the route of infection , source of mice , differences in the POWV , or some other undefined variable . Nevertheless , C57BL/6 may be useful as a model to study flavivirus persistence [47] . P . leucopus mice were completely refractory to POWV infection following i . p . inoculation although mice injected with extremely high doses developed POWV specific antibodies . And even then , there was no sign of disease or viral replication in the organs that we surveyed . We note that our experimental infection differs completely from natural infection through tick bites and this could be the reason why we do not observe seroconversion in i . p . inoculated P . leucopus mice . The differences include the fact that the ixodid ticks feed slowly for 3–5 days while inoculating immunomodulating salivary components , and each mouse may be infested with several ticks at the same time . As a result , the continued exposure to virus in the presence of tick salivary components over time is likely to lead to a robust seroconversion in nature . Thus , we hypothesize that the P . leucopus mice may be quickly and efficiently restricting i . p . inoculated POWV before a humoral immune response . In pursuit of this hypothesis , we are currently studying potential restriction factors that could be involved in restriction of POWV . We also did not observe obvious signs of disease following i . c . inoculation of P . leucopus mice with POWV , but mild encephalitis developed as indicated by the presence of minimal to moderate lymphocytic perivascular cuffing and nodular microgliosis in the CNS . The encephalitis had resolved by 28 dpi although viral RNA was still detectable at this time point . Our results were similar to observations by Telford et al [40] , who reported that adult P . leucopus mice challenged subcutaneously with the DTV , a close relative of POWV , survived with no apparent illness . Similar observations were also made in the bank vole ( Myodes glareolus ) , a natural host of tick-borne TBEV in Europe [50] , but some bank voles developed acute generalized symptoms at 8 dpi [50] , an observation not seen in P . leucopus mice . In contrast , 67% ( 2/3 ) of bank voles infected with TBEV exhibited inflammatory changes in the brain at 25 dpi [50] , suggesting that resolution of encephalitis caused by TBEV may take longer in the bank vole . Taken together , the emerging picture is that natural rodent hosts do not suffer the uniformly severe disease characteristic of human infection or that in laboratory mice . The accumulation of POWV ( + ) RNA and ( - ) RNA was limited to the olfactory bulb and ventricle of i . c . inoculated P . leucopus mice brains with minimal amounts in other regions ( Fig 5 ) . In Swiss albino , C3H and C57BL/6 mice , the initial detection of viral antigen reportedly is in the olfactory bulb following intranasal , subcutaneous or i . p . inoculation of neurotropic flaviviruses [51 , 52] . It has been proposed that the olfactory bulb may be more permissive for viral replication in these mouse species , and that viremia may contribute towards increased virus replication across the whole brain [51 , 53] . Our results showed that POWV rapidly replicated and spread across the brains of i . c . inoculated BALB/c and C57BL/6 mice by 4 dpi . However , this was never the case for P . leucopus mice ( Figs 5 & 6 ) even though viremia was evident in the first 4 dpi . Thus , when compared to BALB/c and C57BL/6 mice , P . leucopus mice are clearly capable of limiting virus replication and spread in the brain . The limited extent of infection in P . leucopus mice suggests that these mice are able to restrict replication and spread of POWV . Some restriction factors operative against various vector-borne flaviviruses have been described [54–56] . A report by Kurhade et al [49] suggests that IPS-1 signaling is important for controlling LGTV replication in the brains of C57BL/6 mice [49] , and this has also been shown to be true for Japanese encephalitis virus and WNV replication in BALB/c mouse brains [57 , 58] . The Peromyscus genus is divergent from the Mus genus [59] , and it remains to be determined if IPS-1 signaling and restrictions factors , such as TRIM79α [54] are important in the P . leucopus mouse . Therefore , additional research aimed at understanding the molecular mechanisms of peripheral and CNS restriction of POWV in P . leucopus is warranted . Experiments designed to model POWV restriction in cell cultures systems may prove informative . In conclusion , P . leucopus mice do not show clinical signs of disease after i . c . or i . p . inoculation with POWV . However , POWV induces minimal to mild encephalitis without meningitis at early time-points and inflammation resolves by 28 dpi following i . c . inoculation . P . leucopus mice restrict POWV replication mainly to the olfactory bulb and ventricle without extensive spread to the whole brain , suggesting that these mice have restriction factors , which need to be further characterized . The P . leucopus mouse is a novel model , which will be useful for studying efficient host responses and molecular mechanisms of effective restriction of POWV and other viruses in the TBEV serogroup . | Powassan virus ( POWV ) is a neuroinvasive tick-borne flavivirus ( TBFV ) , which causes life-threatening encephalitis in humans in North America and Europe . The virus is persistently maintained in a natural cycle involving infected ixodid ticks and small-to-medium sized mammals , such as mice , woodchucks and skunks . Despite conclusive evidence showing that wild rodents play an important role in the maintenance of TBFVs in nature , very little is known regarding the relationship between POWV and its natural mammalian hosts . We selected Peromyscus leucopus , one of the most abundant mixed forest rodent in the USA , as a natural host model for studying POWV infection . Challenging this mouse species with POWV via different routes of inoculation did not result in obvious clinical signs of disease , suggesting resistance , which may be associated with virus restriction factors . The model will be useful for studies aimed at understanding how the animals restrict POWV without clinical signs of disease . | [
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"biolo... | 2017 | Modeling Powassan virus infection in Peromyscus leucopus, a natural host |
Beginning January 2014 , Psychological Science gave authors the opportunity to signal open data and materials if they qualified for badges that accompanied published articles . Before badges , less than 3% of Psychological Science articles reported open data . After badges , 23% reported open data , with an accelerating trend; 39% reported open data in the first half of 2015 , an increase of more than an order of magnitude from baseline . There was no change over time in the low rates of data sharing among comparison journals . Moreover , reporting openness does not guarantee openness . When badges were earned , reportedly available data were more likely to be actually available , correct , usable , and complete than when badges were not earned . Open materials also increased to a weaker degree , and there was more variability among comparison journals . Badges are simple , effective signals to promote open practices and improve preservation of data and materials by using independent repositories .
Signals rapidly communicate information such as values , beliefs , and identities to others [17–19] . Male peacocks signal fitness with elaborate feather displays , automobile drivers signal political identities with bumper stickers , and Chicagoans signal acceptance of yearly disappointment by wearing Cubs apparel . Badges are an easy means of signaling and incentivizing desirable behaviors . Journals can offer badges acknowledging open practices to authors who are willing and able to meet criteria to earn the badge ( https://osf . io/tvyxz/ ) . Badges acknowledging open practices signal that the journal values transparency , lets authors signal that they have met transparency standards for their research , and provides an immediate signal of accessible data , materials , or preregistration to readers . Badges allow adopting journals to take a low-risk policy change toward increased transparency . Compared , for example , to measures that require data deposition as a condition of publication , badge implementation is relatively resource-lite , badges are an incremental change in journal policy , and if badges are not valued by authors , they are ignored and business continues as usual . In January 2014 , Psychological Science ( PSCI ) adopted badges to acknowledge open data , open materials , and preregistration of research if published . Following the specifications maintained by the Center for Open Science ( http://cos . io/ ) Badges Committee for what it means to be “open data” or “open materials , ” the PSCI editorial team awarded one or more badges to authors who applied for them upon article acceptance and provided evidence to the editors that they met the specified criteria . To meet the criteria to earn an open data badge , authors must make all digitally shareable data relevant to the publication available on an open access repository . Similarly , to earn an open materials badge , authors must make all digitally shareable materials , such as survey items , stimulus materials , and experiment programs , available on an open access repository . Materials that cannot be shared digitally must be described in sufficient detail for an informed reader to know how to reproduce the protocol . Those who apply for a badge and meet open data or open materials specifications receive the corresponding badge symbol at the top of their paper and provide an explicit statement in the paper including a URL to the data or materials at an open repository . We did not include preregistration , the act of confirming an unalterable version of one’s research plan prior to collecting data , in this analysis . Preregistration requires initiating behaviors prior to starting the research and thus will require more time to see any impact in the published literature than in our assessment of impact within the first 1 . 5 years . We examined the impact of adopting badges by comparing data and material sharing rates before ( 2012–2013; PSCI before badges ) and after adoption ( 2014–May 2015; PSCI with badges ) in Psychological Science , and across the same time period in comparison journals from the same discipline ( journals without badges ) . Articles already in the publication process on January 1 , 2014 may not have had an opportunity to apply for badges even though their article appeared in 2014 . This suggests that the results reported in this article underestimate the overall impact of badges . The design and analysis of this study was preregistered at https://osf . io/ipkea/ , and all data and materials are available at https://osf . io/rfgdw/ . We preregistered an additional investigation involving reaching out to authors to evaluate accessibility of data or materials that were not shared upon publication . However , we postponed that part of data collection due to feasibility constraints .
We used the population of empirical articles with studies based on experiment or observation ( N = 2 , 478 ) published in 2012 , 2013 , 2014 , and January through May 2015 issues of one journal that started awarding badges , Psychological Science ( PSCI; N = 838 ) , and four journals in the same discipline that did not: Journal of Personality and Social Psychology ( JPSP; N = 419 ) , Journal of Experimental Psychology: Learning , Memory , and Cognition ( JEPLMC; N = 483 ) , Developmental Psychology ( DP; N = 634 ) , and Clinical Psychological Science ( CPS; N = 104 ) . Psychological Science ( 2014 impact factor [IF] = 4 . 94 ) is a respected journal that publishes empirical research from any area of psychology . The four comparison journals ( 2014 IF’s 2 . 86 to 5 . 03 ) are respected journals that publish empirical research from a particular area of psychology represented by their titles . Clinical Psychological Science , which has only been publishing since January 2013 , does not yet have an estimate of impact . It was selected to represent clinical psychology and as the other empirical journal published by the Association for Psychological Science . A total of 220 additional articles published in these journals between 2012 and May 2015 are not part of this corpus because they were not reports of empirical research ( i . e . , editorials , theoretical reviews , commentaries ) . Coders were trained to reliably apply the coding scheme for assessing accessibility of data and research materials ( https://osf . io/4rf3v/ ) . Five trial articles from four journals included in this study , with content representative of a range of possible outcomes , were given to each coder . The first author’s coded responses to these articles were defined as the gold standard . Coders had to achieve 95% reliability with the gold standard before actual coding began . All questions , including free text answers , were included in this evaluation of reliability . If any response did not provide the same conclusion as the gold standard , it was marked incorrect . If 95% reliability was not met with the initial five , coders received three new trial articles and repeated the process . Once their responses were reliable , coders received additional coding instructions ( https://osf . io/er9xk/ ) and access to the population of articles . All articles had a unique , standardized identification number based on their order , month , year , and journal of publication . Coders selected articles solely by this identification number . Individual articles can be matched to their corresponding bibliographic metadata , available at https://osf . io/rmune/ . Availability of data and materials were coded using an identical coding structure . The full coding scheme illustrated in Fig 1 is available at https://osf . io/4rf3v/ . All of the variables used in analysis for this article are as follows: Badge awarded . Whether or not the article was awarded a badge for open data or open materials . Availability statement . Whether or not the article makes a statement regarding the location , available or unavailable , of its data or materials . Reported available . Whether or not the article specifically states the data or materials were available for use , including noting that the data or materials are not available . Reported location . If data or materials were available , what means were provided for accessing them: an independent archive/repository , personal website , independent website , journal supplement , appendix or table , or an indication that data or materials were available upon request . Actually available . Whether the data or materials reported available at a publicly accessible location were found at the expected location , excluding articles with data or materials in the article text , appendix , or journal-hosted supplement . Correct data/materials . If the data or materials could be retrieved , whether the data or materials corresponded to what was reported as being available . To determine correctness of open data , coders evaluated whether the type of data , the variables in the dataset , the number of participants , and the data contents matched the description provided in the manuscript . To determine correctness of open materials , coders evaluated whether the contents of the materials , such as survey items and stimuli , matched the description provided . Usable data/materials . If data or materials could be retrieved , whether the data or materials were understandable and usable after brief review . To determine the usability of data/materials , coders evaluated whether they felt the format of and the context provided with the data/materials would allow them to easily be used for their own purposes . Complete data/materials . If data or materials could be retrieved , whether all of the data or materials for reproducing the reported findings appeared to be available . To determine the completeness of the data/materials , coders evaluated whether all data/materials described for all studies in the article were accessible .
We first examined whether articles’ reporting availability of data and materials increased over time , particularly in Psychological Science ( PSCI ) after badges were introduced on January 1 , 2014 . We examined the entire population of empirical articles from the target and comparison journals ( N = 2 , 478 ) ; as such , we used descriptive statistics to evaluate our research questions . In PSCI , for the half years prior to 2014 , an average of 2 . 5% of articles reported open data ( range = 1 . 5% to 4 . 0% per half year ) , and after January 1 , 2014 , increased monotonically with an average of 22 . 8% of articles reporting open data ( range = 12 . 8% to 39 . 4%; Fig 2 ) . Across the four comparison journals , for the half years prior to 2014 , an average of 3 . 3% of articles reported open data ( range = 1 . 6% to 4 . 9% ) , and after January 1 , 2014 , the average was 2 . 1% ( range = 1 . 8% to 2 . 3% ) . All four comparison journals had very low rates of articles reporting data availability ( JPSP = 4 . 5% , JEPLMC = 2 . 3% , DP = 2 . 4% , CPS = 1 . 0% ) . In PSCI , for the half years prior to 2014 , an average of 12 . 7% of articles reported open materials ( range = 6 . 1% to 17 . 7% ) , and after January 1 , 2014 , increased monotonically with an average of 30 . 3% reporting open materials ( range = 27 . 5% to 41 . 0%; Fig 3 ) . Across the four comparison journals , for the half years prior to 2014 , an average of 19 . 3% of articles reported open materials ( range = 16 . 2% to 23 . 4% ) , and after January 1 , 2014 , 20 . 6% ( range = 17 . 4% to 26 . 1% ) . The four comparison journals varied widely in rates of reporting materials availability ( JPSP = 32 . 2% , JEPLMC = 28 . 8% , DP = 6 . 6% , CPS = 9 . 6% ) . The social- and cognitive-psychology-oriented journals tended to report sharing materials more frequently . Usually , those were descriptions of surveys or stimulus items in an appendix for the article , rather than a complete description of the protocol . In summary , reported sharing of materials and especially data increased dramatically in Psychological Science after introducing badges , but did not change systematically in the comparison journals over the same time period . We next examined whether the introduction of badges was associated with an increase in the rate of using independent repositories . Repositories may provide greater quality assurance and guarantees of preservation than other storage locations such as personal web pages . For this analysis , we considered only those articles that reported sharing . Among PSCI articles reporting available data , 7 . 7% ( N = 1 ) before January 1 , 2014 , and 71 . 2% ( N = 52 ) after , reported that the data were available in an independent repository . Among comparison journal articles reporting available data , 9 . 7% ( N = 3 ) before January 1 , 2014 , and 26 . 7% ( N = 4 ) after , reported that the data were available in an independent repository . This suggests that , when data is shared , it is increasingly likely over time to be shared in an independent repository , and that availability of badges dramatically accelerates this trend . In fact , 46 of the 73 PSCI articles reporting data availability in 2014 and 2015 also earned a badge , and 100% of those 46 reported being in an independent repository . Similarly , among PSCI articles reporting available materials , 0% ( N = 0 ) before January 1 , 2014 , and 45 . 4% ( N = 44 ) after reported that the materials were available in an independent repository . Among comparison journal articles reporting available materials , 0% ( N = 0 ) of materials before January 1 , 2014 , and 2 . 0% ( N = 3 ) after reported that the materials were available in an independent repository . Again , 38 of the 97 PSCI articles reporting materials availability in 2014 and 2015 also earned a badge , and 100% of those 38 reported being in an independent repository . The first results showed nearly a 10-fold increase in reported availability of data for PSCI with badges ( 22 . 8% ) , compared with PSCI before badges ( 2 . 5% ) and the four journals without badges combined ( 2 . 8% ) . Effects were similar but weaker for materials ( 30 . 3% , 12 . 7% , and 19 . 9% , respectively ) . However , reporting availability of data and materials does not guarantee that they are available , or that they are correct , usable , and complete . Do badges increase the likelihood that reported available data and materials are actually available , correct , usable , and complete ? It is possible that badging is sufficient to increase motivation to claim the behavior , but not sufficient to increase performing the behavior . However , the specified criteria for earning the badge , the simple editorial checks on meeting those criteria , and the visibility of the badge may all stimulate sharing behavior .
The present investigation leverages a naturalistic intervention that occurred at Psychological Science and not at similar journals in the same discipline . However , opportunities to earn badges were not randomly assigned to journals or authors . This necessarily weakens the certainty of causal inference . Nonetheless , we assert a causal interpretation that badges promote data sharing because of the implausibility of alternative explanations . The most obvious alternative explanation is that the adoption of badges changed the population of authors submitting or earning acceptance at Psychological Science dramatically toward that very small minority ( <3% ) that shares data and materials even when badges are not offered . Given that Psychological Science has extremely high rejection rates ( ~93% ) , such a scenario would require a rapid and sizable shift in population submitting to the journal [21] . In comparison , rejection rates at Clinical Psychological Science , Developmental Psychology , Journal of Experimental Psychology: Learning , Memory , and Cognition , and Journal of Personality and Social Psychology are ~77% , 80% , 78% , and 89% , respectively ( personal communication , [22] ) . Also , given Psychological Science’s status , concerns about optional sharing would need to exceed the perceived value of publishing in the field’s premiere empirical outlet . Moreover , many of the manuscript submissions of articles published in 2014 would have occurred in 2013—prior to the announcement of the new policy . Another weakness in the present research is that the evaluations of data and material accessibility , correctness , usability , and completeness were the result of coder assessments and did not include reanalysis of the data or reuse of the materials . Such an effort would provide complementary insight on the extent to which this increase in transparency translates to an increase in reproducibility . Another research opportunity with the existing data is to code the research domains of the PSCI articles with badges to see if data and materials sharing rates accelerated more quickly in some subfields compared to others . All data reported in this paper are available at https://osf . io/u6g7t/ to facilitate follow-up investigation . Finally , badges are not a panacea . Sharing rates increased dramatically , but not all data or materials that could be shared were shared . Moreover , even with badges , the accessibility , correctness , usability , and completeness of the shared data and materials was not 100% . Some incompleteness could be attributable to gaps in the specifications for earning badges . For example , in late 2015 , the Center for Open Science Badges Committee ( http://osf . io/tvyxz ) considered provisions for situations in which the data or materials for which a badge was issued somehow disappear from public view . Adherence to badge specifications can also be improved by providing easy procedures for editors or journal staff to validate data and material availability before issuing a badge , and by providing community guidelines for validation and enforcement . Broader adoption of badges across journals will accelerate the accumulation of evidence about their effectiveness and will facilitate the refinement of specifications for badge awards and the process of badge administration . For example , the Center for Open Science is collaborating with publishers and others to create a badge “bakery” that inserts metadata about the issuer , recipient , and location of resources into the badge itself . As digital objects , the badges could then be searched , indexed , and maintained programmatically , which would increase their value for monitoring transparent practices . Badges will not be sufficient to make transparent all data and materials that could be made publicly accessible . Additional interventions will include government , funder , or publisher mandates , such as some of the more stringent standards offered in the Transparency and Openness Promotion ( TOP ) Guidelines ( http://cos . io/top/ ) [14] . Evaluation of different mechanisms for promoting or requiring transparency will help reveal the most efficient and effective methods . And , of course , 100% availability is unlikely because of ethics , privacy , and intellectual property exceptions . However , badges and additional interventions can shift the culture to make sharing the default .
Badges may seem more appropriate for scouts than scientists , and some have suggested that badges are not needed [23] . However , actual evidence suggests that this very simple intervention is sufficient to overcome some barriers to sharing data and materials . Badges signal a valued behavior , and the specifications for earning the badges offer simple guides for enacting that behavior . Moreover , the mere fact that the journal engages authors with the possibility of promoting transparency by earning a badge may spur authors to act on their scientific values . Whatever the mechanism , the present results suggest that offering badges can increase sharing by up to an order of magnitude or more . With high return coupled with comparatively little cost , risk , or bureaucratic requirements , what’s not to like ? | Openness is a core value of scientific practice . The sharing of research materials and data facilitates critique , extension , and application within the scientific community , yet current norms provide few incentives for researchers to share evidence underlying scientific claims . In January 2014 , the journal Psychological Science adopted such an incentive by offering “badges” to acknowledge and signal open practices in publications . In this study , we evaluated the effect that two types of badges—Open Data badges and Open Materials badges—have had on reported data and material sharing , as well as on the actual availability , correctness , usability , and completeness of those data and materials both in Psychological Science and in four comparison journals . We report an increase in reported data sharing of more than an order of magnitude from baseline in Psychological Science , as well as an increase in reported materials sharing , although to a weaker degree . Moreover , we show that reportedly available data and materials were more accessible , correct , usable , and complete when badges were earned . We demonstrate that badges are effective incentives that improve the openness , accessibility , and persistence of data and materials that underlie scientific research . | [
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"... | 2016 | Badges to Acknowledge Open Practices: A Simple, Low-Cost, Effective Method for Increasing Transparency |
Malaysia experienced an unprecedented dengue outbreak from the year 2014 to 2016 that resulted in an enormous increase in the number of cases and mortality as compared to previous years . The causes that attribute to a dengue outbreak can be multifactorial . Viral factors , such as dengue serotype and genotype , are the components of interest in this study . Although only a small number of studies investigated the association between the serotype of dengue virus and clinical manifestations , none of these studies included analyses on dengue genotypes . The present study aims to investigate dengue serotype and genotype-specific clinical characteristics among dengue fever and severe dengue cases from two Malaysian tertiary hospitals between 2014 and mid-2017 . A total of 120 retrospective dengue serum specimens were subjected to serotyping and genotyping by Taqman Real-Time RT-PCR , sequencing and phylogenetic analysis . Subsequently , the dengue serotype and genotype data were statistically analyzed for 101 of 120 corresponding patients’ clinical manifestations to generate a descriptive relation between the genetic components and clinical outcomes of dengue infected patients . During the study period , predominant dengue serotype and genotype were found to be DENV 1 genotype I . Additionally , non-severe clinical manifestations were commonly observed in patients infected with DENV 1 and DENV 3 . Meanwhile , patients with DENV 2 infection showed significant warning signs and developed severe dengue ( p = 0 . 007 ) . Cases infected with DENV 2 were also commonly presented with persistent vomiting ( p = 0 . 010 ) , epigastric pain ( p = 0 . 018 ) , plasma leakage ( p = 0 . 004 ) and shock ( p = 0 . 038 ) . Moreover , myalgia and arthralgia were highly prevalent among DENV 3 infection ( p = 0 . 015; p = 0 . 014 ) . The comparison of genotype-specific clinical manifestations showed that DENV 2 Cosmopolitan was significantly common among severe dengue patients . An association was also found between genotype I of DENV 3 and myalgia . In a similar vein , genotype III of DENV 3 was significantly common among patients with arthralgia . The current data contended that different dengue serotype and genotype had caused distinct clinical characteristics in infected patients .
Since the 1950’s , dengue has become a serious health problem in the South-East Asia region . In 1902 , Malaysia experienced its first case of dengue [1] . Since then , Malaysia has increasingly become popular for perpetual dengue endemic issues , resulting from the continuous rise in reported dengue infection cases . The country experienced major outbreaks in 1974 , 1978 , 1982 , 1990 . Notably , Malaysia recorded the highest number of dengue cases between 2014 and 2017 . In 2014 , a total of 108 , 698 cases were reported in Malaysia which was equivalent to an incidence rate ( IR ) of 361 . 1 cases in 100 , 000 populations with 215 mortalities . This alarming figure had outnumbered the previous recorded dengue cases in 2013 by 150 . 8% . Meanwhile , there was a noticeable increase in 2015 with 120 , 836 cases ( IR = 396 . 4 ) , along with 336 mortalities . In 2016 , the total number of dengue cases declined to around 101 , 357 , although , the mortality rate was 10% higher as compared to that in 2014 . [2 , 3] . Finally in 2017 , the dengue situation in Malaysia came under control as the total number of cases continued to drop . However , the number was still higher as compared to that in 2013 . Subsequently , this prompted the Malaysian government to implement a program to eradicate Aedes aegypti mosquito breeding sites . Recently , a National Dengue Plan ( 2015–2020 ) was implemented by the Malaysian government to intensify the readiness and response capacity in detecting dengue cases and outbreaks , requiring immediate action and attention . Several risk factors at various intensities have contributed towards the severity of dengue infection during the course of an outbreak . Viral factors are often considered as one of the risk factors and components of interest in many studies in this field . A shift in the distribution of dengue serotypes and genotypes may contribute to the accelerating number of dengue cases due to an antibody-dependent enhancement ( ADE ) effect [4] . Interestingly , new genotype clades were discovered in some countries such as India and Sri Lanka during dengue outbreaks [5 , 6] . While many studies investigated the association between certain serotype of dengue virus and disease severity , only a few studies provided comparative details of the clinical manifestations among dengue serotypes and genotypes [7 , 8 , 9] . This comparison is particularly important to further aid in the early prediction of a patient’s condition based on the clinical characteristics and information on the serotype and genotype of the dengue virus infecting the patient . With advanced laboratory tests , the serotyping of the dengue virus from an infected patient can be performed even on the first day of fever . Most clinical symptoms of severe dengue infection only manifest at a later stage of dengue infection . Therefore , information on serotype or genotype-specific dengue manifestations may serve as early surrogate markers to predict disease progression . Furthermore , specific clinical manifestations may be over-represented in patients infected with certain DENV serotype and genotype . In consideration of the above discussion , this study aims to investigate the clinical manifestations of dengue patients in relation to dengue serotype and genotype during a dengue outbreak period in Malaysia .
This study has obtained an ethical approval from the Medical Research & Ethics Committee , Ministry of Health Malaysia ( Reference number: NMRR-15-923-25233 ) . All patients’ data were totally anonymous and requested from clinicians involved in this study . This is a retrospective observational study performed with a total of 120 dengue serum specimens obtained from two tertiary hospitals and a research institute in Malaysia . The serum specimens were acquired from patients who were primarily admitted for dengue fever and confirmed for dengue infection at Hospital Serdang ( n = 94 ) and Hospital Ampang ( n = 24 ) from October 2014—May 2017 . Two more sera from DENV 4-infected patients were obtained from the Virology Unit , at the Institute for Medical Research ( IMR ) , in Kuala Lumpur . The inclusion criteria at the time of sample collection included samples that were positive for dengue NS1 antigen whereas exclusion criteria included suspicion for dengue but were negative for NS1 and identified as other febrile illnesses . The dengue confirmation criteria incorporated the results from the NS1 antigen rapid test , with or without Dengue IgM/IgG rapid combo tests performed by the hospitals . These tests were typically performed as soon as dengue infection was suspected in a patient . If dengue IgM was negative before day seven of the onset of fever , a repeat sample was taken at the recovery phase . The IgM and IgG rapid tests results were used to classify the cases as primary and secondary infection . Dengue cases that were positive for IgM but negative for IgG were regarded as primary infection whereas cases that were positive for either IgG only or both IgM and IgG were classified as secondary infection . The commercially available diagnostic kits incorporate an immunochromatography-based technique manufactured by Pan Bio ( Brisbane , Australia ) . The NS1 antigen rapid test was interpreted by a single band targeting the dengue NS1 antigen . The IgM/IgG Dengue Duo Cassette highlights the presence of anti-dengue IgM and IgG antibodies in their specific bands . The results of the tests were displayed as reactive or non-reactive without titration . The reactive IgG result was semi-quantitative , showing the presence of antibodies in the serum which was equivalent to HAI titer of 1:2 , 560 , indicating a secondary dengue infection . Dengue fever was diagnosed and defined according to the World Health Organization ( WHO ) 2009 dengue classification and severity level . The classification was used to indicate dengue , dengue with warning sign and severe dengue . Severe dengue includes severe plasma leakage , severe haemorrhage and severe organ dysfunction . To make the clinical diagnosis and determine the severity of the dengue infection , a medical officer performed physical examination on the patient , after which the findings were keyed in the e-file and request was made for necessary laboratory tests to be performed . Following this , a team of experienced clinicians including consultants or specialists further verified the accuracy of the clinical diagnosis during daily clinical ward round based on patients’ progress in their symptoms , clinical findings as well as the latest laboratory test report . The implication of the observation was to determine whether the patient requires intensive unit ( ICU ) care or normal ward management . Dengue serotyping and phylogenetic analysis were performed for all 120 specimens . Socio-demographic , clinical profiles and laboratory data were obtained from the patient's record from the respective hospitals . The information was later analyzed with the dengue serotyping and genotyping results performed in this study . Notably , in the sta-tistical analysis , some samples were excluded due to incomplete clinical information , the presence of co-infection with leptospirosis and small sample size for a particular serotype . The rationale for excluding the samples of patients co-infected with leptospirosis was due to the overlapping clinical features of the patients infected with leptospirosis and dengue . These samples , however , were not tested for other closely related co-infections such as Zika or Chikungunya due to budgetary constraints . Moreover , the information on the history and clinical presentation of the patients were unlikely to be of these diseases . QIAamp Viral RNA Mini Kit ( Qiagen ) was used to perform the extraction of dengue viral ribonucleic acid ( RNA ) from the serum specimens according to the manufacturer’s instructions . The eluted 50 μl viral RNA was used as a template in the PCR assays . Dengue virus serotyping was carried out in a fourplex Taqman Real-Time RT-PCR detection platform as described by Johnson et al . ( 2005 ) [10] . PCR reactions were prepared in a cocktail of 12 . 5 μl of 2X RT ( reverse transcriptase ) -PCR Mix ( i-Script One Step RT-PCR kit , Biorad , USA ) , 0 . 5 μl of each primers ( DENV 1 and DENV 3 primers: 50 μM; DENV 2 and DENV 4 primers: 25 μM ) , 0 . 45 μl of each probes ( 10μM ) , 0 . 5 μl of RT Enzyme Mix , and 1 . 2 μl of nuclease-free water . Positive controls for each serotype comprised of RNA from previously confirmed dengue patients , and obtained from the Virology Unit , IMR . The negative control consisted of reactions without an RNA template , which was substituted with 5μl of nuclease-free water . Taqman Real-Time RT-PCR amplification was performed on the CFX 96 ( Biorad , USA ) platform at 50°C for 10min , 95°C for 5min , followed by 45 cycles of 95°C for 15 sec and 60°C for 30 sec . The aforementioned PCR mix and cycling conditions were optimized by the Virology Unit . io: dx . doi . org/10 . 17504/protocols . io . rabd2an . [PROTOCOL DOI] The partial E gene of dengue virus was amplified before sequencing by using four sets of serotype-specific oligonucleotides [11] . All amplification reactions were carried out in a 96-well conventional Thermal Cycler ( Bio Rad , USA ) . The PCR was undertaken at 50°C for 30 min , 94°C for 2 min and 45 cycles of ( 94°C for 15 sec , 50°C for 30 sec and 68°C for 1 min ) followed by an extension reaction at 68°C for 5 min . A 25 μl aliquot of each PCR reaction was analyzed on 1 . 5% pre-stained agarose by gel electrophoresis and viewed under UV illumination . The corresponding amplicons were extracted from the agarose gel and purified by a Gel Extraction Kit ( Qiagen , USA ) according to the manufacturer’s instruction . The final elution contained 30 μl of purified PCR amplicons whereby 5 μl of these were reanalyzed on 1 . 5% agarose gel to substantiate the accuracy of purification step . The purified PCR amplicons were outsourced for Sanger Sequencing ( 1st Base , IDT , Singapore ) . io:dx . doi . org/10 . 17504/protocols . io . racd2aw . [PROTOCOL DOI] The sense and antisense sequences obtained by sequencing were aligned to produce a consensus partial E gene sequence by using CLUSTAL Omega software ( https://www . ebi . ac . uk/Tools/msa/clustalo/ ) . Reference sequences of E gene for each serotype were extracted from the GenBank database from various geographical regions . Phylogenetic trees were constructed with Mega 7 software adopting neighbor-joining method ( bootstrap replication 1000x ) for all four serotypes to determine the genotypes of dengue virus isolates . Statistical package for the social sciences ( SPSS ) version 21 . 0 was adopted to analyze data collected from the dengue patients . Categorical variables were expressed as frequencies ( percentages ) . Chi-square or Fisher’s Exact test was performed to analyze the significance of the categorical variables . Continuous variables were tested for normality with the Komolgorov-Smirnov test . Non-parametric analysis by Kruskal-Wallis was employed for data with non-normal distribution and presented in median and interquartile range ( IQR ) . The normally distributed data were analyzed by One-Way ANOVA and expressed as mean and standard deviation ( SD ) . The patients’ data were tabulated according to categorical variables including gender , serotypes , genotypes and a spectrum of clinical manifestations . Meanwhile , continuous variables refer to parameters such as age , day of fever and laboratory test results . These data were utilized to determine the distribution of dengue serotype and genotype in the study population and describe the relation with demography , clinical manifestations and laboratory parameters . The analyses were performed at 95% confidence with level of significance of p<0 . 05 .
Serotyping results ( Fig 1 ) from 120 study subjects revealed that more than half of the study population were infected with DENV 1 ( 64/120; 53 . 0% ) followed by DENV 2 ( 31/120; 26 . 0% ) , DENV 3 ( 20/120; 17 . 0% ) , DENV 4 ( 4/120; 3 . 0% ) and mixed serotype DENV 1/ DENV 2 ( 1/120; 1 . 0% ) . The distribution of these serotypes by year of infection is shown in Fig 2 . Among our study subjects , a domination of DENV 1 was seen from the year 2014–2016 with prevalence of 35 . 3% ( 6/17 ) , 63 . 2% ( 36/57 ) and 58 . 6% ( 17/29 ) each year , respectively . In 2017 , DENV 2 was more frequently observed than other serotypes ( 7/17; 41 . 2% ) among the study subjects . The number of DENV 3-infected cases from 2014–2017 were less than DENV 1 and DENV 2 except in the year 2014 with prevalence of 29 . 4% ( 5/17 ) , 19 . 4% ( 7/57 ) , 13 . 8% ( 4/9 ) and 23 . 5% ( 4/17 ) , respectively . DENV 4-infected cases were observed more in 2014 ( 3/17; 17 . 6% ) and one case in 2017 ( 1/17; 5 . 9% ) while one DENV 1/ DENV 2 mix serotype case was found in 2015 ( 1/17; 5 . 9% ) . Further , phylogenetic analysis classified these dengue strains into genotypes ( Figs 3–6 ) . All DENV 1 and DENV 2 strains were classified under genotype I and cosmopolitan genotype , respectively . DENV 3 strains clustered into two distinct genotypes . Genotype III comprised most of the DENV 3 strains as compared to genotype I . The DENV 4 strains from the study belong to genotype I and genotype II . In addition , one dengue strain with mixed serotypes of DENV 1/DENV 2 were identified . However , only DENV 2 from the mixed strain could be amplified by PCR and sequenced . All 120 sequences were deposited in NCBI with accession numbers MG450795 –MG450914 . The 2014–2017 DENV 1 strains ( Fig 2 ) displayed a monophyletic relationship being clustered in the genotype I group . These strains showed a distant connection with strains from Vietnam , Cambodia , China and Taiwan-imported case from the same genotype . D1/Malaysia/330877/04 and D1/Malaysia/36139/05 , which were two strains from the former 2004–2005 outbreaks formed their own clade , quite distinctively from the recent outbreak strains . One recent outbreak strain ( D1/Malaysia/PUR/765027/15 ) , isolated in December 2015 was noticeably set apart from other DENV 1 genotype I strains . There was no obvious clustering within the 2014–2017 DENV 1 strains as all of them were randomly dispersed within the clades . The DENV 2 phylogeny ( Fig 3 ) displayed a well-defined clade formation within the Cosmopolitan genotype . The Cosmopolitan genotype of Malaysian strains formed two main clades , which are referred to as Clade 1 and Clade 2 . Clade 2 was further divided into sub-clade 2a and sub-clade 2b . There were two strains within Clade 1 , namely D2/Malaysia/BAG/ 680429/14 and D2/Malaysia/WCK/738138/15 , which were isolated in December 2014 and August 2015 , respectively . Clade 2 comprised of strains isolated during the 2014–2017 outbreak . Domination of dengue strains by year of outbreak within sub-clade 2a and sub-clade 2b was observed . Early outbreak strains from the year 2014–2015 clustered in sub-clade 2b whereas late outbreak strains from the year 2015–2017 dominated sub-clade 2a . The DENV 3 phylogeny ( Fig 4 ) classified the current outbreak strains into genotype I and genotype III . The 2014–2015 DENV 3 strains were commonly noticed among genotype III clade , whereas the 2016–2017 strains appeared more in genotype I clades . The dengue strains from genotype III branched into two clades whereas genotype I strains were clustered together . The DENV 4 strains in this study belonged to genotype I and genotype II ( Fig 5 ) . Of the total 120 cases investigated , 101 cases were included in the statistical analysis while the remaining 19 were omitted . As mentioned earlier , the excluded cases were those with incomplete clinical information , co-infection with leptospirosis and small sample size for particular serotype ( DENV 4 and mixed serotype ) . The demographic details of the 101 study subjects are shown in Table 1 . Age of the patients was significantly related to dengue serotypes . The median age group for DENV 1 , DENV 2 and DENV 3-infected patients was 14 , 27 and 23 respectively . A significant relationship was detected between dengue serotypes and disease classification ( p = 0 . 007 ) ( Table 2 ) . Dengue infections without warning signs were observed more frequently in patients who were infected with DENV 1 ( 29/58; 50 . 0% ) and DENV 3 ( 8/16; 50 . 0% ) . Notably , DENV 2-infected patients more frequently developed severe dengue ( 9/27; 33 . 3% ) . In the present study , a total of 17 severe dengue cases were identified of which two were noted as fatal cases . Apart from this , dengue with warning signs were frequently displayed by patients infected with DENV 2 ( 13/27; 48 . 1% ) . The investigation of dengue serotype-specific clinical manifestations demonstrated that DENV 2-infected patients were more frequently present with persistent vomiting ( p = 0 . 010 ) , epigastric pain ( p = 0 . 018 ) , severe plasma leakage ( p = 0 . 004 ) and shock ( p = 0 . 038 ) . Additionally , myalgia and arthralgia were the two major musculoskeletal symptoms observed in DENV 3 infection ( p = 0 . 015 , p = 0 . 014 ) . Although statistically insignificant , relatively high proportion of DENV 1-infected patients suffered from lethargy ( 9/58; 15 . 5% ) and diarrhea ( 12/58; 20 . 7% ) . Furthermore , genotype I of DENV 3 was frequently found in patients with myalgia ( p = 0 . 036 ) . Likewise , genotype III of DENV 3 and arthralgia were found to be associated with one another ( p = 0 . 035 ) . Investigation of laboratory parameters in relation to dengue serotype and genotype is shown in Table 3 . None of the laboratory parameters were significant among dengue serotypes and genotypes . A majority of the study subjects that were infected with DENV 1 ( 57/68; 98 . 3% ) and DENV 2 ( 26/27; 96 . 3% ) had primary infection . The percentage of secondary infection was greater in the DENV 3 ( 2/16; 12 . 5% ) infected group than other serotypes . The mean platelet count was the lowest among DENV 2-infected patients as indicated by mean ( ±SD ) of 106 x 109 ( ±71 . 5 ) whereas the hematocrit level was the highest among DENV 3 patients ( 43 . 0 ( ±5 . 9 ) ) . Serotype association with disease severity in regards to primary and secondary infection was elucidated in Table 4 . In the primary infection group , the percentage of severe and non-severe dengue cases was 16 . 5% ( 16/97 ) and 83 . 5% ( 81/97 ) , respectively . Also , within the primary infection group , disease severity was significantly associated with dengue serotype ( p = 0 . 014 ) . Among the severe dengue cases within the primary infection group , a great proportion were infected with DENV 2 ( 9/16; 56 . 3% ) followed by DENV 1 ( 6/16; 37 . 5% ) and DENV 3 ( 1/16; 6 . 3% ) whereas among the non-severe dengue cases , 63 . 0% ( 51/81 ) were infected with DENV 1 , followed by DENV 2 ( 17/81; 21 . 0% ) and DENV 3 ( 13/81; 16 . 0% ) . In addition , within the secondary infection group , the percentage of severe cases was 25 . 0% ( 1/4 ) while 75 . 0% ( 3/4 ) were non-severe cases . The only severe dengue case in the secondary infection group was infected with DENV 3 while the three non-severe cases were each infected with DENV 1 , DENV 2 , and DENV 3 .
The present study focused on identifying the pattern of dengue serotype and genotype distribution from the year 2014–2017 in Malaysia and attempted to investigate the clinical spectrum of patients in relation to this distribution pattern . It was found that DENV 1 genotype I was the predominant serotype and genotype in the recent dengue outbreak in Malaysia . This reflected a serotype shift replacing the formerly predominant DENV 2 prior to the outbreak . Comparison of dengue serotype and genotype with disease spectrum contended that these clinical characteristics are serotype and genotype-specific . As most clinical symptoms of severe dengue infection only manifest at a much later stage of dengue infection , therefore , information on serotype or genotype-specific dengue manifestations may serve as early surrogate markers to predict disease progression . In Malaysia , the serotype distribution of dengue virus has been inconsistent . However , there was a seemingly interesting pattern of circulation during outbreak period whereby major outbreaks were likely to follow the switching of DENV serotypes [12] . A predominantly circulating dengue serotype before an outbreak is replaced by another serotype which persists towards the end of the outbreak . Once the number of cases decline , the persistent serotype is again replaced by another serotype . For instance , during the 1996–1998 dengue outbreaks in Malaysia , both DENV 1 and DENV 2 dominated other serotypes . Prior to 1996 , DENV 3 was consistently circulating . After the outbreak subsided , DENV 2 began to surge from the year 1999 onwards . Similarly , when there was a sharp increase in the number of dengue cases in 2001 and 2002 , DENV 2 in the prior years was replaced by DENV 3 . Then , DENV 3 was overtaken by DENV 1 from year 2003 onwards as the number of cases declined [2 , 13 , 14] . In the present study , DENV 1 was primarily present at the study area from 2014–2017 . This indicated that DENV 1 had replaced a formerly predominant DENV 2 . The existing trend contended that serotype replacement , most probably with DENV 3 is predicted to take place once the current outbreak subsides . In contrast to our prediction , Tan et al ( 2017 ) reported the unlikeliness for DENV 3 to surge as serotype cyclical outbreak cycle in Malaysia has recently been disrupted with DENV 3 remained in the background of DENV 1 and DENV 2 from 2003 until now [15] . Apart from serotype replacement , emergence of new genotypes or genotypic clade replacements have been reported during dengue outbreak [16 , 17 , 18] . This is often attributed to positive pressure selection and viral fitness for survival . In the current study , all DENV 1 strains were classified into genotype I , which subsequently formed minute branches within the same genotype but well conserved . The monophyletic pattern indicated high genetic similarity among the DENV 1 Malaysian strains . As for DENV 2 Cosmopolitan genotype , the current outbreak strains diverged into clades , indicating minor evolution . The DENV 3 strains in our study were divided into genotype I and genotype III . Genotype III was constantly documented in Malaysia from 2007–2013 [15 , 19] . Interestingly , genotype I of DENV 3 was last documented in 2011 and also circulated in this country during dengue epidemics in 1974 and 2007–2008 [15] . Hence , the appearance of genotype I that was equal to genotype III among DENV 3 strains in our study raised the possibility of re-emergence of genotype I especially during outbreaks . DENV 4 is a rare dengue serotype in Malaysia . Three strains from genotype I and a strain from genotype II were detected in the present study . One of the DENV 4 strains clustered together with the dengue strains from Myanmar , reflecting the likelihood of an imported case . A handful of studies have shown the differences in dengue symptoms are serotype specific , but majority of these studies are conducted outside outbreak periods . A study among adult dengue patients in Singapore from 2005–2011 found that cases infected with DENV 1 were more likely to be presented with red eyes and had higher risk of developing severe dengue . In contrast , those DENV 2-infected patients were found to have frequent joint pains and significantly low platelet count [9] . Another study was conducted among dengue patients in Peru , Bolivia , Ecuador and Paraguay from 2005–2010 . The findings showed that DENV 3 had a higher prevalence of musculoskeletal and gastrointestinal manifestations while DENV 4 had a higher prevalence of respiratory and cutaneous manifestations [7] . On the other hand , a group of Indian researchers who undertook a study from 2002–2006 in New Delhi reported a significant result of hepatomegaly and abdominal pain in DENV 2-infected patients . The results of their study also noted that DENV 4 patients suffered from severe hemorrhagic manifestations [20] . All the aforementioned results showed that there were differences in clinical manifestations of dengue patients relating to the serotype owing to the differences in terms of year of study and level of endemicity in particular regions . In response to this , the present study investigated the relationship between dengue serotype and genotype , and the disease spectrum in Malaysia , a dengue hyper endemic country , during a recent outbreak period . The present study showed a significant number of DENV 2-infected patients developed severe dengue more frequently as compared to other serotypes . These patients were also frequently presented with clinical manifestations such as persistent vomiting , epigastric pain , plasma leakage and shock . Many studies have proven that severity and DENV 2 are common especially in relation to shock manifestation [21 , 22 , 23] . Similarly in a retrospective study of dengue cases in Thailand , it was also found that DENV 2 was the most frequent serotype isolated from dengue hemorrhagic ( DHF ) and dengue shock syndrome ( DSS ) cases followed by DENV 3 , DENV 1 and DENV 4 [24] . Although substantial evidence confirmed that DENV 2 caused severe dengue infection , one study found no differences between any DENV serotypes and severity of the disease [25] . Our data suggested that both DENV 1 and DENV 3-infected patients displayed the mildest clinical presentation . The data also signified that DENV 3-infected patients suffered from myalgia and arthralgia . When compared across the genotypes , DENV 2 cosmopolitan was highly prevalent among patients with epigastric pain and shock . Besides that , DENV 3 genotype III was significantly observed among patients with arthralgia whereas DENV 3 genotype I was common among patients with myalgia . Several studies also reported an association between DENV 3 and musculoskeletal manifestations . According to Chan et al . ( 2009 ) , the findings showed a significant relationship between DENV 3 and myalgia , but the genotype information was unknown [26] . Similarly , Hasley et al ( 2012 ) also found that DENV 3-infected patients had frequent myalgia and arthralgia symptoms [7] . Therefore , we hypothesized that DENV 3 has a high preference and binding affinity to the receptors in the musculoskeletal system , narrowing down further that genotype I targets muscles whereas genotype III targets the joints . The comparison between genotypes also exhibited that genotype III of DENV 3 may appear to be more virulent than genotype I . This is supported by the presence of two severe cases among DENV 3 genotype III-infected patients . These two cases were presented with severe organ impairment and shock ( dengue shock syndrome ) , respectively . This finding may warrant further interest to investigate severity associated with DENV genotype III with inclusion of larger sample size . It can be postulated that since genotype III has been circulating dominantly among DENV 3 genotypes in Malaysia for extended period from its introduction in 2007 till 2013 , thus it acquired sufficient survival fitness to become virulent over time as compared to genotype I which was dormant from 2012–2013 and had re-emerged during the outbreak in 2014 . However re-emergence of DENV 3 genotype I has to be cautiously monitored as it could undergo adaptation to become more infectious to replace and diminish the existence of DENV 3 genotype III . This highlights the importance of studying serotype and genotype specific clinical manifestations during dengue outbreak to allow prediction of an outbreak outcome . Previous research had claimed that DENV 1 and DENV 2 are often associated with primary infections and secondary infections , respectively [26] . Contrary to these findings , our investigation revealed insignificant differences between dengue serotypes and infection type as in primary and secondary infection . Indeed , this could be mainly due to low number of secondary infected cases in the present study . In our study , primary dengue infections were found to be more frequent than secondary infections . This finding contradicted with reports of high seroprevalence rate of secondary infection in Malaysia [27] . The seroprevalence rates in Malaysia were shown to be age dependent , whereby as the age increases the seroprevalence also increases and by 70 years old almost 80% of the Malaysian population were already infected with dengue . Our findings on secondary infection rate was different from the above study based on two aspects . Firstly , the distribution of subjects by age group in our study indicate that more than half of the study subjects belonged to younger age group ( ≤ 20 ) ; hence , less likely to have past exposures ( S1 Table ) . Past studies also supported this in which a shift of the dengue infection from affecting primarily children to adults more than age 20 years old , was demonstrated [28 , 29] . Secondly , in our study , exclusion of samples with incomplete information , unable to be serotyped or genotyped and the coverage of only two locations contributed to small sample size , thus , we are unable to provide a detailed description of the seroprevalence rate . However , our study findings on high primary infection rate could pose a serious implication if the next outbreak is predominantly caused by DENV 2 . It is known that severe dengue is associated with secondary infection and infection with DENV 2 superimposed on previous DENV 1 infection carries the highest risk for development of severe dengue [30] . Even though the DENV 3 upsurge after the current outbreak is predicted , however as mentioned earlier , one study [15] has cautioned that this cycle was recently disrupted , raising the possibility for DENV 2 dominance . Therefore , our study findings on the high prevalence of primary infection is very crucial in the conveyance of early warning for a severe outbreak in the future . Comparison of serotype severity after stratifying by infection types demonstrated that among primary dengue infection cases , there is a significant association between DENV 2 and the disease severity . This indicates that primary infections caused by DENV 2 may lead to more severe presentations than DENV 1 . Interestingly , only one severe case was found in the secondary infection group and no significance was observed among the serotypes and severity in this group . One possible explanation , in this case , could be that the patients in the secondary infection group could have been previously infected by the same serotype ( homotypic infection ) . Recent studies have reported the evidence of homotypic dengue re-infection [31 , 32] . The findings for these studies demonstrate that , in some cases , serotype-specific immunity to DENV may be short-lived . Such cases challenge the paradigm of lifelong , serotype-specific DENV immunity following a natural infection . A greater risk to develop severe dengue is caused by heterotypic secondary DENV infection with a dengue serotype distinct from the primary infecting type [33] . Having said that , prior to the onset of the recent outbreak , DENV 1 were equally circulating with other serotypes ( DENV 2 and DENV 3 ) from the year 2010–2012 . It was only in the year 2013 , there was an upsurge of DENV 2 . Since the information is not available on the serotype that previously infected the patients in the secondary infection group , therefore our findings raised the possibility that these patients had been previously infected by DENV 1 also . Hence , increased disease severity was not observed . The theory of peak enhancement titer provides a second possible explanation . The enhancement of severe dengue is dependent on the pre-existing antibody titer , resulting from a different serotype infection . The pre-existing dengue antibody titer of 1: 21 to 1:80 induced high risk to develop severe dengue , whereas , a titer above 1: 320 triggered a protective effect [33] . It is more likely that the pre-existing dengue antibody titers in the secondary infection group in our study did not fall into the peak enhancement zone , thus causing less risk for severity . The IgM and IgG rapid test results were utilized to discriminate between primary and secondary infection . Several studies have evaluated the accuracy of infection status assignment using this method . One such study demonstrated a 100% sensitivity of an IgM/IgG rapid test in an attempt to distinguish between primary and secondary dengue virus infections [34] . Another study evaluated the similar rapid test kit ( Dengue Duo Cassette; Panbio , Brisbane , Australia ) which was also used in the present study and found that the test has good reproducibility , with the inconsistency of only 5% [35] . These findings collectively showed that the IgM/IgG rapid tests are reliable diagnostic tools for the indication of primary or secondary dengue infection . Several strengths are inherent in this study . To the best of the researcher’s knowledge , this is the first observational study to investigate the relationship between dengue serotype and genotype with patients’ clinical manifestation during the recent outbreak peri-od among Malaysians . Additionally , our study findings may warrant further research to elucidate the strong association of dengue serotype and genotypes focusing on a larger population and localities . However , the study has limitations as well . Firstly , all retrospective studies depend on the completeness of medical data , and missing data is therefore unavoidable . In the present study , a number of subjects had to be excluded from the original count due to incompleteness of clinical data , thus resulted in a smaller sample size . Secondly , in Malaysia , many dengue specimens from hospitals were sent to the national reference laboratories for molecular diagnosis and surveillance purpose . Therefore , our collaborators from the hospitals were only able to provide those specimens that were not required for national surveillance . We need to acknowledge that there is a possibility of selection bias but , the findings in our study of resurgent DENV 1 infection during the recent outbreak period is consistent with the national surveillance of the dengue infection . In view of this , the selection bias was not substantial . Not only that , there was underrepresentation of certain serotypes in this study due to the small numbers such as DENV 4 causing it to be omitted from the statistical analysis . Lastly , the proportion of dengue subjects obtained in the year 2014 was low despite a spike in the dengue cases because the sample collection was initiated towards the end of the particular year . Our study findings demonstrated that symptoms of dengue infected patients in Malaysia were indeed serotype and genotype-specific . DENV 1 was found to cause dengue without warning signs and mild symptoms . DENV 2 patients were more likely to present with severe dengue as compared to other serotypes . In addition , DENV 3-infected patients frequently had musculoskeletal symptoms . These findings suggested that different dengue serotypes targeted different receptors or organs to establish infection . Following our findings and to benefit from further research , we recommend continuous monitoring of dengue clinical manifestations in relation to serotype and genotype and investigate the link between DENV 3 genotype III and disease severity with larger sample size . We also propose to look into the recent prevalence of primary and secondary dengue infection among Malaysian population as this has an implication on dengue vaccine . | The study highlights interesting relationship between viral factors and clinical manifestation of dengue disease during an outbreak . The viral factors which include serotype and genotype of dengue virus were studied to discover if the clinical manifestation in patients were serotype and genotype-specific . As most clinical symptoms of severe dengue infection only manifest at a much later stage of dengue infection , therefore , information on serotype or genotype-specific dengue manifestations may serve as early surrogate markers to predict disease progression . We found that specific clinical manifestations were over-represented by a specific DENV serotype and genotype . Severe dengue was significantly present in DENV 2 Cosmopolitan-infected group while non-severe dengue was prominent among DENV 1 genotype I-infected patients . DENV 3-infected patients commonly manifested musculoskeletal symptoms . This study was undertaken between 2014 and mid-2017 , which was considered to be crucial , given that Malaysia experienced an unprecedented outbreak of dengue during this period . Consequently , the occurrence of serotype shift and possible re-emergence of DENV 3 genotype I were reported . | [
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Based on metabolic and morphological similarities between infective third-stage larvae of parasitic nematodes and dauer larvae of Caenorhabditis elegans , it is hypothesized that similar genetic mechanisms control the development of these forms . In the parasite Strongyloides stercoralis , FKTF-1 is an ortholog of DAF-16 , a forkhead transcription factor that regulates dauer larval development in C . elegans . Using transgenesis , we investigated the role of FKTF-1 in S . stercoralis' infective larval development . In first-stage larvae , GFP-tagged recombinant FKTF-1b localizes to the pharynx and hypodermis , tissues remodeled in infective larvae . Activating and inactivating mutations at predicted AKT phosphorylation sites on FKTF-1b give constitutive cytoplasmic and nuclear localization of the protein , respectively , indicating that its post-translational regulation is similar to other FOXO-class transcription factors . Mutant constructs designed to interfere with endogenous FKTF-1b function altered the intestinal and pharyngeal development of the larvae and resulted in some transgenic larvae failing to arrest in the infective stage . Our findings indicate that FKTF-1b is required for proper morphogenesis of S . stercoralis infective larvae and support the overall hypothesis of similar regulation of dauer development in C . elegans and the formation of infective larvae in parasitic nematodes .
Parasitism among nematodes appears to have arisen multiple times throughout evolution [1] . However , the exact mechanism by which nematodes developed parasitic life histories is unknown . Altering gene regulation through variation in conserved signaling systems , is a potential mechanism by which a free-living species might develop characteristics required for parasitism [2] . Insulin-like signaling regulates metabolism and lifespan in a variety of organisms including nematodes , insects and mammals [3] , [4] . In Caenorhabditis elegans , this signaling pathway mediates entry into the dauer larvae diapause by negatively regulating DAF-16 , a forkhead transcription factor type O ( FOXO ) [5] . Biological requirements of C . elegans dauer larvae include increased resistance to stress and a metabolism altered to allow the animal to persist , potentially for months , in unfavorable environments [6] . Infective larvae of parasitic nematodes , such as S . stercoralis , have similar requirements for survival prior to host finding . The ‘dauer hypothesis’ recognizes the common physiological characteristics of dauer larvae and parasitic infective larvae , and proposes that the same molecular genetic mechanisms control the morphogenesis of both forms [7] . The life cycles of Strongyloides and Parastrongyloides spp . , unusual among the parasitic nematodes , alternate between free-living and parasitic generations [8] , [9] . First-stage larval progeny of parasitic S . stercoralis females typically develop into free-living adults unless triggered by genetic , environmental or host-associated conditions to develop directly into infective third-stage larvae ( L3i ) [10] . Progeny of the free-living generation of S . stercoralis are uniformly fated to become L3i that invade the host and develop into parasitic females . Previous work identified the FOXO encoding gene fktf-1 ( forkhead transcription factor-1 ) as the ortholog of C . elegans daf-16 in S . stercoralis [11] . In heterologous rescue experiments , a transgene construct designed to express FKTF-1b ( isoform b ) partially restored DAF-16 function to C . elegans daf-2;daf-16 double mutants [12] rescuing the dauer development phenotype . These data indicate that fktf-1b encodes a working forkhead transcription factor that can function in insulin-like signaling to regulate L3 development in C . elegans . The more relevant question of whether FKTF-1b regulates infective larval development in S . stercoralis itself can now be addressed using new methods for transgenesis in this parasite [13] , [14] . In the present study , we transformed free-living adult female S . stercoralis with constructs encoding a 2 . 6 kb fktf-1β promoter controlling expression of GFP::FKTF-1b fusion proteins . We then examined first-stage larval progeny of these female worms for anatomical and intra-cellular localization of GFP-linked proteins and for phenotypes associated with expression of transgenes encoding mutant forms of FKTF-1b .
First , we asked whether the localization of fktf-1β expression in S . stercoralis mimics that of C . elegans daf-16β , which is expressed primarily in the pharynx and body neurons [5] . First-stage S . stercoralis larvae expressed fktf-1β::gfp::fktf-1b ( Figure S1 ) predominantly in the procorpus of the pharynx ( Figure 1A , and Figure 1B , arrow ) and the hypodermis ( Figure 1C and 1D ) . These expression patterns continued into the L3i ( Figure 1E and 1F ) . In S . stercoralis , remodeling of the short , trilobed rhabditiform pharynx of the L1 into the long , cylindrical filariform pharynx of the L3i is a hallmark of the transition to infectivity [15] . The rhabditiform pharynx , found in all free-living stages , has three main components: the procorpus , the isthmus and the terminal bulb . The procorpus of the pharynx is the muscular region anterior to the narrow isthmus and is primarily responsible for food intake [15] . The pharynx of the non-feeding L3i , is not contractile and has no readily identifiable lobes [15] . Interestingly , expression of the fktf-1β reporter construct in the filariform pharynx was restricted to a band ( Figure 1F arrow ) analogous to the procorpus of a rhabditiform pharynx . The hypodermal cell layer is responsible for secretion of the cuticle in a stage specific manner [16] . The infective larval cuticle must not only protect the L3i , it must also allow the L3i to sense the presence of a host and secrete molecules facilitating invasion . Although the expression patterns of the fusion protein in L1 varied somewhat ( Figure 1G ) , the fact that the predominant sites of expression were the pharyngeal procorpus and the hypodermis bolsters confidence that the endogenous fktf-1β promoter is active in these tissues in wild-type larvae . This pattern of expression is consistent with a role for FKTF-1b in the development of structures characteristic of infective larvae . Insulin-like signaling negatively regulates the function of forkhead transcription factors , including DAF-16 , via phosphorylation of serines or threonines at specific sites by Akt/PKB kinases [17] . To ascertain similar post-translational regulation of FKTF-1b , we transformed S . stercoralis with vectors encoding mutant versions of GFP::FKTF-1b that were predicted to behave as either constitutively phosphorylated or non-phosphorylated forms of the protein . Substitution of charged residues , either aspartic or glutamic acids , for serines at Akt/PKB phosphorylation sites in the forkhead domain of human FOXOs is sufficient for disruption of DNA binding by these proteins and for their export from the nucleus [18] , [19] . Homologous ‘phospho-mimetic’ mutations in predicted Akt/PKB sites of FKTF-1b also resulted in constitutive export of the fusion protein GFP::FKTF-1b ( S238E/T240E ) ( encoded by pPV244 , Figure S1 ) from nuclei of hypodermal cells in transgenic S . stercoralis L1 ( Figure 2A and 2B and 2G ) . Likewise , disruption of all four predicted Akt/PKB sites in FKTF-1b by substitution of the neutral amino acid alanine for critical serine or threonine residues ( see pPV243 , Figure S1 ) resulted in strongly enhanced nuclear localization of the ‘phospho-null’ fusion protein GFP::FKTF-1b ( 4A ) ( Figure 2E–2G ) . These data indicate that FKTF-1b's intra-cellular localization , and thereby its access to genomic response elements , is regulated by phosphorylation in a similar manner to DAF-16 and other FOXO-class transcription factors . Its anatomical localization and intra-cellular trafficking support the hypothesis that FKTF-1b is an ortholog of DAF-16 and that through it , insulin-like signaling regulates S . stercoralis' larval development . More conclusive testing of this hypothesis requires experimental manipulation of gene function and evaluation of phenotypic outcomes . Thus far , S . stercoralis , like many other parasitic nematodes , has proven insensitive to targeted gene silencing via RNAi [20] . Therefore , we opted for an approach based on transgenesis in which we express altered forms of FKTF-1b designed to interfere with the function of the endogenous transcription factor . Two such mutant proteins , encoded by plasmids pPV251 and pPV298 , respectively ( Figure S1 ) , are tagged with GFP and carry the four ‘phospho-null’ mutations described above , causing them to be sequestered in the nucleus where they presumably out-compete native FKTF-1b for response elements in the genome . In addition , both mutant proteins are truncated within the C-terminal domain immediately downstream of the fourth regulatory phosphorylation site , ablating key transactivator binding motifs . In one of the dominant interfering proteins , encoded by pPV251 and dubbed GFP::FKTF-1b ( dominant-repressor ) , the truncated C-terminal domain is fused to the repressor domain of Ce-PIE-1 , a protein responsible for the transcriptional repression characterizing the germline precursor of C . elegans [21] . In the other mutant protein , encoded by pPV298 and dubbed GFP::FKTF-1b ( dominant-negative ) , the truncated C-terminal domain is not linked to Ce-PIE-1 . Upon hatching , larvae expressing either of the dominant interfering constructs were shorter but virtually identical in form to larvae expressing GFP-tagged wild-type FKTF-1b at similar levels ( Figure S2 ) , indicating that the S . stercoralis transcription factor , like DAF-16 in C . elegans [22] , does not play a significant role in embryonic development . By contrast , at 24 hours , S . stercoralis L1 expressing either of the dominant interfering mutants of FKTF-1b exhibited phenotypic changes in the form and apparent function of their intestinal cells , with these being most evident in larvae expressing the dominant-repressor construct . These phenotypes ranged from flattening of the normally apically rounded intestinal cells and a decrease in the number of cytoplasmic storage granules in the presence of GFP::FKTF-1b ( dominant-negative ) ( compare Figure 3J to Figure 3H and Figure 3I ) to an almost complete loss of intestinal cell architecture and of cytoplasmic storage granules in the presence of the GFP::FKTF-1b ( dominant-repressor ) . Perhaps due to compromised intestinal cell function , S . stercoralis L1 expressing GFP::FKTF-1b ( dominant-repressor ) exhibited significant ( P<0 . 01 ) growth retardation at 24 hours ( Figure 3N ) . Owing to the severity of the associated phenotypes , none of the larvae expressing GFP::FKTF-1b ( dominant-repressor ) survived beyond the L1 . The fact that S . stercoralis L1 expressing comparable levels of wild-type FKTF-1 tagged with GFP ( Figure 3B , 3E , and 3I ) were morphologically similar to untransformed larvae ( Figure 3A and 3H ) argues against the observed phenotypes being due to non-specific effects of recombinant protein expression . Therefore , it is clear from these findings that FKTF-1 is necessary for normal development of intestinal cells in pre-infective larvae of S . stercoralis and specifically for accumulation of storage granules , which may contain reserves necessary for survival of the L3i . With regard to the dauer hypothesis and the role of insulin signaling in infective larval development , the most significant results in the present study were the morphogenetic changes seen in L3 expressing the GFP::FKTF-1b ( dominant-negative ) transgene . Under the null hypothesis , all of our transgenic larvae should develop to L3i . While L3i expressing the wild-type GFP::FKTF-1b fusion protein were morphologically identical to their non-transgenic counterparts ( Figure 4A and 4B , compare to Figure S3A ) , L3 expressing the dominant-negative transgene ( Figure 4C and 4D ) exhibited some indications of bypassing developmental arrest and failing to undergo the pharyngeal and intestinal remodeling characteristic of L3i . Three of the 11 transgenic L3 appeared to initiate an aberrant molt to the fourth stage as evidenced by the existence of a pointed tail inside a notched L3i cuticle cast ( Figure 4E and 4F compared to wild-type Figure 4G ) . The notched tail is characteristic of infective larvae and is created by pairs of ‘L3i-specific’ alae [15] . Another L3 expressing the dominant-negative construct exhibited an elongated rhabditiform pharynx complete with a grinder-like structure ( Figure 4H and 4I ) instead of the expected filariform pharynx ( Figure S3B and Figure S3C ) . Incomplete remodeling of the rhabditiform pharynx and initiation of a supernumerary molt in culture are consistent with expression of the interfering FKTF-1b transgenes in the pharyngeal procorpus and the hypodermis . Initiation of ecdysis by L3 in combination with retention of some rhabditiform pharyngeal characteristics as we observed suggests that worms expressing GFP::FKTF-1b ( dominant-negative ) were developing in the direction of a second-generation free-living L4 . While such a form occurs in some strongyloidoid species ( e . g . Strongyloides planiceps , Parastrongyloides trichosuri ) , it does not exist in the natural life cycle of S . stercoralis [8] , [23] . Five of the 11 transgenic L3 expressing the dominant-negative construct exhibited changes consistent with a failure to remodel the free-living intestine into the darkened , radially constricted intestine of the L3i . In some cases , the L3 intestine retained bacteria ( Figure 4E ) and in others , it failed to constrict and close ( Figure 4I to the left of the black triangle ) . The incompletely remodeled intestine seen in the transgenic L3 is consistent with the defects in intestinal structure seen in the L1 . Together , these data indicate that FKTF-1b is required for the proper remodeling of the pharynx and the intestine of a free-living larva into structures characteristic of the infective larva . Our findings support the ‘dauer hypothesis’ [7] by showing that the forkhead transcription factor FKTF-1b , presumably under the control of insulin-like signaling , regulates infective larval development in Strongyloides stercoralis in a manner similar to the dauer regulatory functions of DAF-16 in Caenorhabditis elegans . Furthermore , in this study , we have demonstrated the utility of transgenesis in S . stercoralis for investigation not only of temporal and spatial patterns of gene expression , but also of endogenous gene function . This work opens new avenues of inquiry into the genes involved in the shift between free-living and parasitic states in Strongyloides stercoralis and ultimately into the evolution of parasitism in nematodes generally .
The UPD strain of Strongyloides stercoralis was maintained in immuno-suppressed dogs and cultured as described [24] . Free-living adult S . stercoralis were isolated from two-day-old coprocultures via Baermann funnels . The worms were washed twice with sterile deionized water to reduce carryover of fecal bacteria and plated on Nematode Growth Medium ( NGM agar ) plates seeded with Escherichia coli OP50 . All cultures of S . stercoralis were incubated at 22°C unless otherwise noted . Adult female S . stercoralis were transformed with transgene encoding plasmids via intra-gonadal microinjection using standard protocols [24] , [26] . Coding plasmids were injected at a concentration of 10–100 ng/ml with non-coding plasmids being used as necessary to make up the total DNA concentration to 100 ng/ml . Following injection , worms were transferred to clean NGM OP50 plates with an excess of males and incubated at 22°C . For general expression patterns , plates were scored at 24 hour intervals for adult survival and frequency of transgene expression among F1 progeny . For specific time points , adults were transferred to clean NGM OP50 plates at three to five hour intervals to obtain egg cohorts . All plates with eggs were checked at hourly intervals for the presence of transgenic progeny . When the time of hatch was known , transgenic larvae were transferred to clean plates marked with the time point and examined after the appropriate interval . Transgenic progeny for which the time of hatch was not known were used for analysis of L3i development . The low transformation rate , <5% , of S . stercoralis larvae made it impractical to accumulate sufficient numbers of individuals for both phenotypic study ( Table S2 for phenotype counts ) and confirmation of a full-length gfp::fktf-1b transcript . However , we have confirmed that C . elegans transformed with the same gfp::fktf-1b coding sequence under the control of the daf-16 promoter exhibit GFP fluorescence and express a full length transcript encoding the fusion protein ( data not shown ) . Current methods only allow us to observe transgene expression in F1 generation following transformation . Transgenic larvae were identified based on GFP fluorescence using an Olympus SZX12 stereomicroscope with coaxial epifluorescence . For more detailed examination of particular tissues and individual cells , larvae were immobilized on 4% Agar Noble ( Sigma , St . Louis , Missouri , USA ) pads in 10 mM ( L1 ) or 20 mM ( L3i ) levamisole and observed using an Olympus BX60 compound microscope equipped with Nomarski Differential Interference Contrast ( DIC ) optics and epifluorescence ( Olympus America Inc . , Center Valley , Pennsylvania , USA ) . Specimens were imaged with a Spot RT Color digital camera and images were processed using either the Spot Advanced image analysis software package ( Diagnostic Instruments , Inc . , Sterling Heights , Michigan , USA ) or Adobe Photoshop 7 . 0 . All image-processing algorithms ( e . g . brightness and contrast adjustments ) were applied in a linear fashion to the entire image . Worm lengths were measured using the ImageJ program available from the National Institutes of Health ( http://rsb . info . nih . gov/ij/ ) [27] . Calibrations were done by determining the distance of 10 µm on a micrometer in pixels and then setting the scale in the program . All measurements were done in duplicate using the freehand line option , taking the average of the results for analysis . As categorical data , expression patterns , localization and phenotypes , were analyzed using χ2 tests . Analysis of the expression patterns of the fktf-1β promoter constructs was based on the null hypothesis that the expression patterns were not specific to the hypodermis and the pharynx . Categories of intra-cellular GFP localization were analyzed based on the null hypothesis that the phosphorylation status of the FKTF-1b protein had no effect on its localization . In order to compare the mean lengths of wild-type and transgenic larvae , we used the Mann-Whitney test , which makes no assumptions as to the population distribution of the observations . | Parasitic nematodes are an important threat to public health in much of the world . Understanding how these worms find and invade their hosts may lead to improved therapies . The infectious forms of many parasitic nematodes developmentally arrest as infective third-stage larvae that require hosts to reactivate . Development of these larvae has been compared to that of the diapausing dauer larvae of Caenorhabditis elegans . Our lab studies the development of the human nematode parasite Strongyloides stercoralis . We identified S . stercoralis' FKTF-1 as an ortholog of DAF-16 , a forkhead transcription factor controlling dauer larval development in C . elegans . Transgenes were introduced into S . stercoralis to investigate the possibility that FKTF-1 regulates development of its infective larvae . We discovered that recombinant FKTF-1b tagged with GFP localizes to specific tissues remodeled in infective larvae . Furthermore , mutant forms of FKTF-1b designed to interfere with endogenous FKTF-1b function resulted in incomplete development of the infective larval structures and prevented some transgenic larvae from arresting in the infective stage . Indicating that FKTF-1b is required for the proper development of Strongyloides stercoralis infective larvae , our findings support the hypothesis of similar controls over parasitic and free-living nematode development and pave the way for further comparative studies . | [
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Escher is a web application for visualizing data on biological pathways . Three key features make Escher a uniquely effective tool for pathway visualization . First , users can rapidly design new pathway maps . Escher provides pathway suggestions based on user data and genome-scale models , so users can draw pathways in a semi-automated way . Second , users can visualize data related to genes or proteins on the associated reactions and pathways , using rules that define which enzymes catalyze each reaction . Thus , users can identify trends in common genomic data types ( e . g . RNA-Seq , proteomics , ChIP ) —in conjunction with metabolite- and reaction-oriented data types ( e . g . metabolomics , fluxomics ) . Third , Escher harnesses the strengths of web technologies ( SVG , D3 , developer tools ) so that visualizations can be rapidly adapted , extended , shared , and embedded . This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools .
The behavior of an organism emerges from the complex interactions between genes , proteins , reactions , and metabolites . With next-generation sequencing and various “omics” technologies , it is now possible to rapidly and comprehensively measure these components and interactions . These technologies have transformed the scientific process over the past decade . Data acquisition is substantially easier , but data analysis is increasingly becoming the primary bottleneck to discovery . To address the analysis bottleneck , there has been a demand for data visualization tools to complement statistical and modeling methods . Biological visualizations often fall into categories characterized by biological scale , and the style of a visualization reflects the type of information at that scale . Three-dimensional objects are often used for representing protein structures [1 , 2] , one-dimensional tracks for genome sequences [3 , 4] , force-directed graphs for interaction networks [5] , trees for phylogenetic relationships [6 , 7] . And , finally , two-dimensional pathway maps have long been a popular visual representation of metabolic pathways and other biological pathways . For each type of visualization , data can be associated with the biological components in the visualization . Visualizing data in this way contextualizes and enriches the dataset for scientists . Data-rich visualizations have been extremely valuable for viewing , interpreting , and communicating data . A tool for visualizing pathway maps must satisfy a set of core features . The tool must ( 1 ) visually represent reactions and pathways clearly and in a way that is biochemically correct , ( 2 ) allow users to navigate and search through the visualization , ( 3 ) allow users to design and customize pathway maps , ( 4 ) allow users to represent diverse data types within the map using visual cues like size and color , ( 5 ) provide import and export features so that maps can be stored , shared , and exported to other tools , and ( 6 ) provide an application program interface ( API ) so the tool can be used within data analysis pipelines . The existing tools that satisfy these core features are all desktop applications . Briefly , these tools include Omix [8] , Cytoscape [5] , CellDesigner [9] , Vanted [10] with the SBGN-ED add-on [11] , VisAnt [12] and PathVisio [13] . Desktop applications have many advantages over web applications , including speed , stability , and integration with the operating system , and these merits have made desktop applications more popular . The advantages of web applications include rapid deployment ( no need to download an application or browser plug-in ) , greater cross-platform compatibility ( e . g . mobile devices ) , flexible sharing , collaborating , and embedding features , as well as easy application development . Recently , a critical mass of performance enhancements and new libraries has made web tools comparable to desktop tools for many applications . A number of web-based tools exist for visualizing pathway maps: ArrayXPath [14] , Pathway Projector [15] , iPath2 . 0 [16] , WikiPathways [17] , Biographer [18] , and the BioCyc pathway viewer [19] . However , none of these satisfy all the core features for a pathway map visualization tool . One of the key differentiating features of a web application is that modern web browsers come with a built-in software development platform ( often called the Developer Tools ) . This development platform includes a JavaScript shell for directly interacting with the web page runtime and a tool for inspecting and modifying every element in the web page document object model ( DOM ) . Thus , any user can locally modify any element on the page at any time . If a web application is built on the DOM , then users can rapidly prototype new features and build extensions to the application while it is running . ( A comparable feature is the extensibility of the EMACS editor , which can be extended while the editor is running [20] . On the strength of this feature , EMACS has remained popular for 30 years . ) To utilize this powerful feature , one must use a visualization library that is based on the DOM , the most popular of which is Data-Driven Documents ( D3 ) [21] . Escher is a web application for visualizing pathway maps , and it is designed to be a fully featured pathway visualization tool that also harnesses all the advantages of the web . Escher has three key features that distinguish it from all existing pathway visualization tools , including the popular desktop applications . First , Escher makes building pathway maps fast and easy , using the information in datasets and genome-scale models to suggest pathways to the user—with this , pathway map design can be semi-automated . Second , Escher connects genes and enzymes to the reactions they catalyze , so that genomic data can be visualized in the context of the reaction network . We show how Escher can be used to visualize reaction data ( metabolic fluxes ) , metabolite data ( metabolomics ) , and genomic data ( transcriptomic data ) , bridging the gap between these data types . Third , Escher uses the advantages of web technologies so that pathway maps can be adapted , extended , shared , and embedded . We illustrate the export and development features of Escher , including native support for scalable vector graphics ( SVG ) export , a downloadable tool for converting Escher maps to common standards for representing layouts , and application program interfaces ( APIs ) for developing new applications that extend the functionality of Escher .
To build a pathway map , one first needs a source for the names , stoichiometries , and associated genes for each biochemical reaction in an organism . This information is provided by a constraint-based reconstruction and analysis ( COBRA ) model , a collection of all the reactions , metabolites , and genes known to exist in an organism ( also called a genome-scale model ( GEM ) or constraint-based model ( CBM ) ) [22] . While COBRA models have generally focused on metabolism , the COBRA modeling approach can be applied to any biochemical reaction network [22] , so Escher could be used to visualize pathways like gene expression and membrane translocation , which are now being incorporated into COBRA models [23–25] . The Escher interface is centered around a canvas for the pathway map ( Fig 1A ) . In the Escher Builder , a number of editing modes are available in the Edit menu; these include tools for navigating the map ( Pan mode ) , selecting and modifying elements ( Select mode ) , adding reactions ( Add reaction mode ) , rotating the current selection ( Rotate mode ) , and adding and editing text annotations ( Text mode ) . In Add reaction mode , a new pathway can be added to the canvas . Clicking on the canvas or an existing metabolite opens the new reaction search box . The search box can find reactions with a number of queries: reaction identifiers ( IDs ) and display names , metabolite IDs and display names , and gene IDs and names ( Fig 1B ) . ( IDs and names are based on those in the COBRA model . ) If a reaction or gene dataset is loaded , then Escher provides suggestions of the next reaction to build , sorted by the data value for that reaction ( Fig 1B ) . With this set of suggestions , a user can quickly build an Escher map based on previous knowledge of the organism or using the suggestion of a dataset . Data-driven map layout is also extremely useful for understanding an organism at the genome-scale—guided by the data , it is possible to find all the elements of a network that are , for example , highly upregulated without any bias toward well known pathways . To add the top suggested reaction , a user can simply press the Enter key . Thus , if a pathway is linear or has high values in a given dataset , then pressing Enter repeatedly will draw a linear pathway that is based entirely on the information in the data and the COBRA model . This process can be repeated to build perpendicular branches from metabolites in the pathway . The Escher interface includes a general menu , a menu bar for accessing common functions , a tool for switching between maps , and a canvas containing the interactive pathway map ( Fig 1A ) . The Map and Model menus contain import and export functions for maps and COBRA models . The Data menu contains the data loading functions , and the View menu contains zoom options and access to the Settings page . Three types of data can be visualized on an Escher map: reaction data , metabolite data , and gene data . And Escher supports visualizing a single dataset , or visualizing the comparison of two datasets using a number of comparison functions ( log , log2 , and difference ) . The Settings page includes a detailed set of options for coloring and sizing elements based on statistical features of a dataset ( min , max , quartiles , mean ) . Here , examples are provided for each data type , and the files required for recreating the visualizations are in the supplementary data .
Escher is a web application written primarily in JavaScript , using the libraries D3 [21] , and , optionally , JQuery ( http://jquery . com ) and Bootstrap ( http://getbootstrap . com ) . The Escher JavaScript code can be compiled into a single JavaScript file , and a JavaScript API is available for interacting with and extending an Escher visualization ( Fig 3A ) . All layout , editing , import , and export features of Escher are included in the JavaScript library , and the default visual styles are defined in two cascading style sheets ( CSS ) files . The Escher website is built using the JavaScript API , and other web applications can be built on top of this library . A Python package for Escher is also available ( Fig 3A ) , and this package includes a number of extra features: access to Escher maps from Python terminals and IPython Notebooks , offline access to Escher , a local server with map and model caching , and a Python API for developing applications with these additional features . Accessing maps from Python and IPython Notebook allows Escher to be integrated directly with data analysis and modeling workflows . For example , within an IPython Notebook , the results of an in silico flux simulation can be applied to an Escher map , and the map will be embedded and shared with the notebook . Escher even supports NBViewer for sharing static IPython Notebooks as websites ( http://nbviewer . ipython . org ) . Escher includes a database of pathway maps and genome-scale models . Pathway maps are currently available for a number of organisms , and new pathway maps will be continually added to the database from our group . The maps in the BiGG database are being converted to the new Escher format [33] . We also accept contributions from the community , and the method for submitting pathway maps is described in the documentation ( S2 File ) . Both Escher maps and COBRA models are stored as JavaScript Object Notation ( JSON ) files . JSON is a useful , plain-text format for storing nested data structures . For Escher maps , a JSON Schema has been defined ( S1 File , see the schema file escher/jsonschema/1-0-0 ) , and the schema can be enforced using the JSON Schema validators available in a number of languages ( http://json-schema . org ) . Thus , Escher maps conform to a well-defined specification that can be generated by other tools and scripts . Escher represents biochemical reactions as transformations from a set of reactants to a set of products , and each reaction can be assigned enzymes using a Boolean gene reaction rule . Thus , Escher uses a well-defined representation of the biochemical network , but the scope of the Escher notation is much more specific than community standards such as Systems Biology Graphical Notation ( SBGN ) [34] and Systems Biology Markup Language ( SBML ) with the layout extension [35–37] . Escher can be exported to both formats using the EscherConverter application ( Fig 4 ) . EscherConverter is written in Java™ , and it is available as a standalone executable file ( S3 File ) that includes a graphical user interface with graph drawing capabilities and a command-line interface . Files can be opened through drag and drop or the file menu , and a history of up to 10 recent files is stored . Several user preferences allow flexible customization of the file conversion . The conversion to SBML and SBGN-ML ( the XML implementation of SBGN ) relies heavily on JSBML [38] and libSBGN [39] . Escher is hosted on GitHub , with a public bug tracker and tools for community contribution to the codebase ( https://github . com/zakandrewking/escher ) . Documentation for Escher is available and was generated using Sphinx and ReadTheDocs ( https://escher . readthedocs . org ) . This documentation includes a description of the Escher features and detailed information on the JavaScript and Python APIs . The Escher Python package , which is available from the Python Package Index ( PyPI , https://pypi . python . org ) , can be used to integrate Escher maps with data analysis and simulation workflows . Using the available functions , datasets can be applied to Escher maps , and the resulting maps can be saved as standalone web pages , saved as JSON or SVG , or exported using the EscherConverter as a command line utility . The Python package works directly with COBRA models using COBRApy [40] . It also includes functions for modifying all of the Escher map settings , including the color and size scales for all elements . The Python package also includes a simple web server to run Escher locally . The web server caches maps and models for offline use , and users can also add maps to the cache directory so that they appear in the local web application . The following commands will install the package , print the location of the local cache directory , and run the Escher server: # install escher pip install escher # print the cache directory python -c “import escher; print escher . get_cache_dir ( ) ” # run the local server ( available at http://localhost:7778 ) python -m escher . server Application programming interfaces ( APIs ) are available for both JavaScript and Python to enable users to build , modify , and export maps programmatically . The specific functions in the APIs are defined in the Escher Documentation . New web applications can be built on top of the basic Escher functions by developing with the Escher JavaScript API . The Documentation provides details on implementing a very simple web page with an embedded Escher map .
A major focus during development of future Escher versions will be to generalize and improve the approach to web visualization . As discussed in the Introduction , there are many types of biological visualizations that contribute to our interpretation of “omics” datasets . Successful user interface designs should be applicable to all of these visualization types , with modifications for the specific needs of a tool . As web platforms become ubiquitous for application development , it is important to consider what elements might be shared across a suite of visualization tools . This would make development of new tools easier , and improve interoperability between tools . For example , a genetic dataset in Escher could link directly to a visualization of the dataset on a genome browser . Escher will be included in the next release of the BiGG database [33] . The BiGG database is a repository for COBRA models developed in the Systems Biology Research Group at the University of California , San Diego . BiGG already includes static pathway maps for many models in the database . Escher maps will be embedded in the web pages for models , reactions , and metabolites so that users can quickly see the network context of a biological component , and the maps will be available on both the BiGG and Escher websites . The Escher framework is highly amenable to improvements , such as new visual features . Example improvements include compartment membranes , representations of regulation and signaling such as those in the SBGN specification , better statistical tools for analyzing and comparing various data types , more import and export options , and direct integration of other visualizations ( such as protein and metabolite structures ) . Because Escher is an open-source project , contributions from the community—bug fixes , use cases , code contributions , etc . —will be encouraged and will be an important factor in making Escher a sustainable , long-term solution to the challenges of visualizing biological pathways . | We are now in the age of big data . More than ever before , biological discoveries require powerful and flexible tools for managing large datasets , including both visual and statistical tools . Pathway-based visualization is particularly powerful since it enables one to analyze complex datasets within the context of actual biological processes and to elucidate how each change in a cell effects related processes . To facilitate such approaches , we present Escher , a web application that can be used to rapidly build pathway maps . On Escher maps , diverse datasets related to genes , reactions , and metabolites can be quickly contextualized within metabolism and , increasingly , beyond metabolism . Escher is available now for free use ( under the MIT license ) at https://escher . github . io . | [
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] | [] | 2015 | Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways |
A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 ( Chr 1 ) that corresponds to human Chr 1q21–q23 . This region is highly enriched in quantitative trait loci ( QTLs ) that control neural and behavioral phenotypes , including motor behavior , escape latency , emotionality , seizure susceptibility ( Szs1 ) , and responses to ethanol , caffeine , pentobarbital , and haloperidol . This region also controls the expression of a remarkably large number of genes , including genes that are associated with some of the classical traits that map to distal Chr 1 ( e . g . , seizure susceptibility ) . Here , we ask whether this QTL-rich region on Chr 1 ( Qrr1 ) consists of a single master locus or a mixture of linked , but functionally unrelated , QTLs . To answer this question and to evaluate candidate genes , we generated and analyzed several gene expression , haplotype , and sequence datasets . We exploited six complementary mouse crosses , and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1 . Qrr1 can be broadly divided into a proximal part ( Qrr1p ) and a distal part ( Qrr1d ) , each associated with the expression of distinct subsets of genes . Qrr1d controls RNA metabolism and protein synthesis , including the expression of ∼20 aminoacyl-tRNA synthetases . Qrr1d contains a tRNA cluster , and this is a functionally pertinent candidate for the tRNA synthetases . Rgs7 and Fmn2 are other strong candidates in Qrr1d . FMN2 protein has pronounced expression in neurons , including in the dendrites , and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d . Our analysis revealed a highly complex gene expression regulatory interval in Qrr1 , composed of multiple loci modulating the expression of functionally cognate sets of genes .
The distal part of mouse Chr 1 harbors a large number of QTLs that generate differences in behavior . Open field activity [1] , fear conditioning [2] , rearing behavior [3] , and several other measures of emotionality [4] , [5] have been repeatedly mapped to distal Chr 1 . This region is also notable because it appears to influence responses to a wide range of drugs including ethanol [6] , caffeine [7] , pentobarbital [8] , and haloperidol [9] . In addition to the behavioral traits , a number of metabolic , physiological and immunological phenotypes have been mapped to this region ( table 1 ) [10]–[36] . This QTL rich region on mouse distal Chr 1 exhibits reasonably compelling functional and genetic concordance with the orthologous region on human Chr 1q21–q23 . Prime examples of genes in this region that have been associated with similar traits in mouse and human are Rgs2 ( anxiety in both species ) , Apoa2 ( atherosclerosis ) , and Kcnj10 ( seizure susceptibility ) [37]–[42] . Studies of gene expression in the central nervous system ( CNS ) of mice have revealed major strain differences in the expression level of numerous genes located on distal Chr 1 , e . g . , Copa , Atp1a2 , and Kcnj9 [26] , [43]–[45] . These differentially expressed genes are strong candidates for the behavioral and neuropharmacological traits that map to this region . We have recently shown that sequence variants near each of these candidate genes are often responsible for the prominent differences in expression [26] , [46] , [47] . In other words , sequence differences near genes such as Kcnj9 cause expression to differ , and variation in transcript level maps back to the location of the source gene itself . Transcripts of this type are associated with cis-QTLs . These expression genetic studies have also uncovered another unusual characteristic of mouse distal Chr 1 . In addition to the extensive cis-effects , a large number of transcripts of genes located on other chromosomes map into this same short interval on distal Chr 1 [47] , [48] . These types of QTLs are often referred to as trans-QTLs . The clustering of trans-QTLs to distal Chr 1 has been replicated in multiple crosses and CNS microarray datasets [47] . We refer to this region of Chr 1 , extending from Fcgr3 ( 172 . 5 Mb ) to Rgs7 ( 177 . 5 Mb ) as the QTL-rich region on Chr 1 , or Qrr1 . It is possible that these modulatory effects on expression are the first steps in a cascade of events that are ultimately responsible for many of the prominent differences in behavior and neuropharmacology . For example , Qrr1 modulates the expression of several genes that have been implicated in seizure ( e . g . , Scn1b , Pnpo , Cacna1g ) , and this may be a basis for the strong influence Qrr1 has on seizure susceptibility [41] . In this study , we exploited 18 diverse array datasets derived from different mouse crosses to systematically dissect the expression QTLs in Qrr1 . The strong trans effects are consistently detected in CNS tissues of C57BL/6J ( B6 ) ×DBA/2J ( D2 ) and B6×C3H/HeJ ( C3H ) crosses , but are largely absent in ILS/Ibg ( ILS ) ×ISS/Ibg ( ISS ) and C57BL/6By ( B6y ) ×BALB/cBy ( BALB ) , and in all non-neural tissues we have examined . We applied high-resolution mapping and haplotype analysis of Qrr1 using a large panel of BXD recombinant inbred ( RI ) strains that included highly recombinant advanced intercross RI lines . Our analyses revealed multiple distinct loci in Qrr1 that regulate gene expression specifically in the CNS . The distal part of Qrr1 ( Qrr1d ) has a strong effect on the expression of numerous genes involved in RNA metabolism and protein synthesis , including more than half of all aminoacyl-tRNA synthetases . Fmn2 and Rgs7 , and a cluster of tRNAs are the strongest candidates in Qrr1d .
The Chr 1 interval , from 172–178 Mb , harbors 32 relatively precisely mapped QTLs for classical traits such as alcohol dependency , escape latency , and emotionality ( Mouse Genome Informatics at www . informatics . jax . org , Table 1 ) . To compare the enrichment of QTLs in Qrr1 with that in other regions , we counted classical QTLs in 100 non-overlapping intervals covering almost the entire autosomal genome ( table S1 ) . These intervals were selected to contain the same number of genes as Qrr1 . Numbers of QTLs ranged from 0 to 23 , and averaged at 9 . 16±5 . 37 ( SD ) . Compared to these regions , Qrr1 had the highest QTL number , over 4 SD above the mean , and over three times higher than average . In this section , we summarize the number of expression phenotypes that map to Qrr1 in different tissues and mouse crosses . The results are based on the analysis of 18 array datasets that provide estimates of global mRNA abundance in neural and non-neural tissues from six different crosses . These crosses are— ( i ) BXD RI and advanced intercross RI strains derived from B6 and D2 , ( ii ) CXB RI strains derived from B6y×BALB , ( iii ) LXS RI strains derived from ILS and ISS , ( iv ) B6×C3H F2 intercrosses , and ( v & vi ) two separate B6×D2 F2 intercrosses . These datasets were generated by collaborative efforts over the last few years [46] , [47] , [49]–[52] and some were generated more recently ( e . g . , the Illumina datasets for BXD striatum and LXS hippocampus , and BXD Hippocampus UMUTAffy Exon Array dataset ) . All datasets can be accessed from GeneNetwork ( www . genenetwork . org ) . We mapped loci that modulate transcript levels and selected only those transcripts that have peak QTLs in Qrr1 with a minimum LOD score of 3 . This corresponds to a generally lenient threshold with genome-wide p-value of 0 . 1 to 0 . 05 , but corresponds to a highly significant pointwise p-value . Because we are mainly interested in testing a short segment on Chr 1 , a pointwise ( region-wise ) threshold is more appropriate to select those transcripts that are likely to be modulated by Qrr1 . Qrr1 covers approximately 0 . 2% of the genome and extends from Fcgr3 ( more precisely , SNP rs8242852 at 172 . 887364 Mb using Mouse Genome Assembly NCBI m36 , UCSC Genome Browser mm8 ) through to Rgs7 ( SNP rs4136041 at 177 . 273526 Mb ) . We defined this region on the basis of the large number of transcripts that have maximal LOD scores associated with markers between these SNPs . Hundreds of transcripts map to Qrr1 with LOD scores ≥3 in neural tissue datasets of BXD RI strains , B6D2F2 intercrosses , and B6C3HF2 intercrosses ( table 2 ) . The QTL counts in Qrr1 are far higher than the average of 15 to 35 expression QTLs in a typical 6 Mb interval . The fraction of QTLs in Qrr1 is as high as 14% of all trans-QTLs , and 5% of all cis-QTLs in the whole genome ( table 2 ) . The enrichment in trans-QTLs in Qrr1 is even more pronounced when the QTL selection stringency is increased to a LOD threshold of 4 ( genome-wide p-value of approximately 0 . 01 ) . For example , 27% of all highly significant trans-QTLs in the BXD cerebellum dataset are in Qrr1 ( table 2 ) . The BXD hippocampus dataset that was assayed on the Affymetrix Exon ST array is an exception—there are over a million probe sets in this array , and the percent enrichment of QTLs in Qrr1 appears to be relatively low . Nevertheless , about 1000 transcripts map to Qrr1 in this exon dataset . In contrast to the CNS datasets , relatively few transcripts map to Qrr1 in non-neural tissues of the BXD strains and B6C3HF2 intercrosses . While the number of cis-QTLs is still relatively high ( 1–3% ) , Qrr1 has limited or no trans-effect in these datasets ( table 2 ) . Qrr1 does not have a strong trans-effect in the LXS and CXB hippocampus datasets ( table 2 ) . This indicates that the sequence variants underlying the trans-QTLs do not segregate to nearly the same extent in the LXS and CXB RI panels as they do in B6×D2 and B6×C3H crosses . This contrast among crosses can be exploited to parse Qrr1 into sub-regions and identify stronger candidate genes . The trans-QTLs in Qrr1 are highly replicable . A large fraction of the transcripts , in some cases represented by multiple probes or probe sets , map to Qrr1 in multiple CNS datasets . For example , there are 747 unique trans-QTLs with LOD scores greater than 4 ( genome-wide p-value≤0 . 01 ) in the BXD hippocampus dataset ( assayed on Affymetrix M430v2 arrays ) . Out of these highly significant trans-QTLs , 155 are in Qrr1 and the remaining 592 are distributed across the rest of the genome ( figure 1 ) . We compared the trans-QTLs in the hippocampus dataset with a similar collection of trans-QTLs ( LOD≥4 ) in the cerebellum dataset ( assayed on Affymetrix M430 arrays ) . Only 101 trans-QTLs in the hippocampus are replicated in the cerebellum ( for trans-QTLs that were declared as common , the average distance between peak QTL markers in the two datasets is 1 . 6 Mb ) . But it is remarkable that of the subset of common trans-QTLs , 64 are in Qrr1 ( figure 1 ) . The replication rate of trans-QTLs in Qrr1 is therefore about 6-fold higher relative to the rest of the genome . When we compared the BXD hippocampus dataset with the B6C3HF2 brain dataset ( assayed on Agilent arrays ) , we found 54 trans-QTLs common to both datasets ( for the common trans-QTLs , the average distance between peak markers in the two datasets is 2 . 7 Mb ) . Strikingly , out of the 54 trans-QTLs common to both crosses , 52 are in Qrr1 ( figure 1 ) . Among the transcripts with the most consistent trans-QTLs are glycyl-tRNA synthetase ( Gars ) , cysteinyl-tRNA synthetase ( Cars ) , asparaginyl-tRNA synthetase ( Nars ) , isoleucyl tRNA synthetase ( Iars ) , asparagine synthetase ( Asns ) , and activating transcription factor 4 ( Atf4 ) . These transcripts map to Qrr1 in almost all datasets in which the strong trans-effect is detected . Gars , Cars , and Nars are aminoacyl-tRNA synthetases ( ARS ) that charge tRNAs with amino acids during translation . Asns and Atf4 are also involved in amino acid metabolism—Asns is required for asparagine synthesis and is under the regulation of Atf4 , which in turn is sensitive to cellular amino acid levels [53] . Other transcripts that consistently map as trans-QTLs to Qrr1 include brain expressed X-linked 2 ( Bex2 ) , splicing factor Sfrs3 , ribonucleoproteins Snrpc and Snrpd1 , ring finger protein 6 ( Rnf6 ) , and RAS oncogene family member Rab2 . Qrr1 contains 164 known genes . The proximal part of Qrr1 is gene-rich and has several genes with high expression in the CNS ( e . g . Pea15 , Kcnj9 , Kcnj10 , Atp1a2 ) . The middle to distal part of Qrr1 is relatively gene sparse and consists mostly of clusters of olfactory receptors and members of the interferon activated Ifi200 gene family . Though comparatively gene sparse , the middle to distal part of Qrr1 contains a small number of genes that have high expression in the CNS—Igsf4b , Dfy , Fmn2 , and Rgs7 . A subset of 35 genes were initially selected as high priority candidates based on the number of known and inferred sequence differences between the B6 allele ( B ) and D2 allele ( D ) and based on expression levels in multiple CNS datasets ( table 3 ) . Eleven of these candidates contain missense SNPs segregating in B6×D2 crosses . We also scanned Qrr1 for variation in copy number [54] , [55] . Graubert et al . [55] reported segmental duplication in Qrr1 with a copy number gain in D2 compared to B6 near the intelectin 1 ( Itlna ) gene at 173 . 352 Mb . We failed to detect any expression signatures of a copy number variation around Itlna in any of the GeneNetwork datasets . However , we did identify an apparent 150 kb deletion across the Ifi200 gene cluster ( 175 . 584–175 . 733 Mb ) . Affymetrix probe sets 1426906_at , 1452231_x_at , and 1452349_x_at detect Ifi204 and Mnda transcripts in B6 but not in D2 . The expression difference is robust enough to generate cis-QTLs with very high LOD scores ( >40 ) . This gene cluster has low expression in the CNS ( Affymetrix declares this probe sets to be “not present” ) , but high expression in tissues such as hematopoietic stem cells and kidney , in which the trans-effect of Qrr1 is not detected . The Ifi200 gene cluster was therefore excluded as a high priority candidate . Transcripts of 26 of the 35 selected candidate genes map as cis-QTLs ( LOD≥3 ) in the BXD CNS datasets ( table 3 ) . These putatively cis-regulated genes are among the strongest candidates in the QTL interval . The D allele in Qrr1 has the positive effect on the expression of Sdhc , Ndufs2 , Adamts4 , Dedd , Pfdn2 , Ltap , Pea15 , Atp1a2 , Kcnj9 , Kcnj10 , Igsf4b , and Grem2 . Increase in expression caused by the D allele ranges from about 10% for Adamts4 to over 2-fold for Atp1a2 . In contrast , the B allele has the positive effect on the expression of Pcp4l1 , Fcer1g , B4galt3 , Ppox , Ufc1 , Nit1 , Usf1 , Copa , Pex19 , Wdr42a , Igsf8 , Dfy , Fmn2 , and Rgs7 . Increase in expression caused by the B allele ranges from about 7% for Usf1 to 40% for Pex19 . Individual probes were screened to assess if the strong cis-effects are due to hybridization artifacts caused by SNPs in probe targets . Thirteen candidate genes with cis-QTLs were then selected for further analysis and validation of cis-regulation by measuring allele specific expression ( ASE ) difference [56] . This method exploits transcribed SNPs , and uses single base extension to assess expression difference in F1 hybrids . By means of ASE , we validated the cis-regulation of 10 candidate genes—Ndufs2 , Nit1 , Pfdn2 , Usf1 , Copa , Atp1a2 , Kcnj9 , Kcnj10 , Dfy , and Fmn2 ( table 4 ) . Adamts4 and Igsf4b failed to show significant allelic expression difference . In the case of Ufc1 , the polarity of the allele effect failed to agree with the ASE result ( D positive at p-value = 0 . 02 ) . The BXD CNS datasets were generated from a combined panel of conventional RI strains and advanced RI strains that were derived by inbreeding advanced intercross progeny . The advanced RIs have approximately twice as many recombinations compared to standard RIs and the merged panel offers over a 3-fold increase in mapping resolution [57] . This expanded RI set combined with the relatively high intrinsic recombination rate within Qrr1 [58] provides comparatively high mapping resolution . Mapping precision can be empirically determined by analyzing cis-QTLs in multiple large datasets , particularly the BXD Hippocampus Consortium , UMUTAffy Hippocampus , and Hamilton Eye datasets . These three datasets were selected because they have expression measurements from six BXD strains with recombinations in Qrr1 . These strains—BXD8 , BXD29 , BXD62 , BXD64 , BXD68 , and BXD84—collectively provide six sets of informative markers and divide Qrr1 into six non-recombinant segments , labeled as segments 1–6 ( haplotype structures shown in figure 2 ) . As cis-acting regulatory elements are usually located within a few kilobases of a gene's coding sequence [59] , we used the cis-QTLs as an internal metric of mapping precision by measuring the offset distance between a cis-QTL ( position of peak QTL marker ) and the parent gene ( figure 3 ) . For cis-QTLs with LOD scores between 3–4 ( genome-wide p-value of 0 . 1–0 . 01 ) the mean gene-to-QTL peak distance is 900 kb . The offset decreases to a mean of 640 kb for cis-QTLs with LOD scores greater than 4 ( p-value<0 . 001 ) . Very strong cis-QTLs with LOD scores greater than 11 ( p-value<10−6 ) have a mean gene-to-QTL peak distance of only 450 kb . In all , 60% of cis-QTLs we examined have peak linkage on markers located precisely in the same non-recombinant segment as the parent gene , and 30% have peak linkage on markers in a segment adjacent to the parent gene ( dataset S1 ) . These cis-QTLs provide an empirical metric of mapping precision within Qrr1 . Mapping precision of cis-QTLs is comparatively higher in the BXD hippocampus dataset ( average offset of only 410 kb ) , and we used this set to examine the trans-QTLs ( LOD≥3 ) at higher resolution . The trans-QTLs in Qrr1 were parsed into subgroups based on the location of peak LOD score markers ( figure 4 ) . This method of resolving trans-QTLs effectively grouped subsets of transcripts into functionally related cohorts . For instance , all the QTLs for the aminoacyl-tRNA synthetases ( ARS ) have peak LOD scores only within the distal three segments of Qrr1 ( figure 5 ) . This consistency in QTL peaks for transcripts of the same gene family is itself a good indicator of mapping precision . In addition to the ARS , numerous other genes involved in amino acid metabolism and translation map to the distal part of Qrr1 ( e . g . , Atf4 , Asns , Eif4g2 , and Pum2 ) . We divided the trans-QTLs into two broad subgroups—those with peak QTLs on markers in the proximal part of Qrr1 ( Qrr1p; 172–174 . 5 Mb or segments 1 , 2 , 3 in figure 2 ) , and those with peak QTLs on markers in the distal part of Qrr1 ( Qrr1d; 174 . 5–177 . 5 Mb or segments 4 , 5 , and 6 in figure 2 ) . While Qrr1p is relatively gene-rich , only 35% of the trans-QTLs ( 129 out of 365 probe sets ) have peak LOD scores in this region . The majority of trans-QTLs—about 65% ( 236 out of 365 probe sets ) —have peak QTLs in the relatively gene-sparse Qrr1d . The two subsets of transcripts—those with trans-QTLs in Qrr1p and those with trans-QTLs in Qrr1d—were analyzed for overrepresented gene functions using the DAVID functional annotation tool ( http://david . abcc . ncifcrf . gov/ ) . This revealed distinct gene ontology ( GO ) categories enriched in the two subsets ( dataset S2 ) . Enriched GOs among the transcripts modulated by Qrr1p include GTPase-mediate signal transduction ( modified Fisher's exact test p = 0 . 001 ) , and structural constituents of ribosomes ( p = 0 . 003 ) . Transcripts modulated by Qrr1d are highly enriched in genes involved in RNA metabolism ( p = 4×10−7 ) , tRNA aminoacylation ( p = 1×10−5 ) and translation ( p = 2×10−5 ) , RNA transport ( p = 0 . 003 ) , cell cycle ( p = 0 . 004 ) , and ubiquitin mediated protein catabolism ( p = 0 . 006 ) . Other GO categories show enrichment in both Qrr1p and Qrr1d . For example , genes involved in RNA metabolism and ubiquitin-mediated protein catabolism are also overrepresented among the transcripts modulated by Qrr1p ( p = 0 . 002 for RNA metabolism and p = 0 . 005 for ubiquitin-protein ligases ) . This may either be due to limitations in QTL resolution , or due to multiple loci in Qrr1p and Qrr1d controlling these subsets of transcripts . A remarkable number of transcripts of the ARS gene family map to Qrr1 . A total of 16 ARS transcripts have trans-QTLs at a minimum LOD score of 3 in one or multiple BXD , B6D2F2 , and B6C3H CNS datasets ( table 5 ) . In almost all cases , QTLs peak on markers on the distal part of Qrr1 . Except for Hars , the B allele in Qrr1 consistently increases expression by 10% to 30% . In the case of Hars , the D allele has the positive additive effect and increases expression by about 10% . We examined all probes or probe sets that target ARS and ARS-like genes in the B6×D2 CNS datasets . The Affymetrix platform measures the expression of 34 ARS and ARS-like genes; 24 of these map to Qrr1 at LOD scores ranging from a low of 2 to a high of 12 . Even in the case of the suggestive trans-QTLs ( i . e . , LOD values between 2 and 3 ) , the B allele in Qrr1 has the positive effect on expression . The ARS family is also highly represented among trans-QTLs in the B6C3HF2 brain dataset . Thirty-seven probes in this dataset target the tRNA synthetases , eleven of these have trans-QTLs in Qrr1d ( LOD scores ranging from 2 to 20 ) , and almost all have a B positive additive effect ( exceptions are Hars and Qars ) . The co-localization of trans-QTLs to Qrr1d , the general consensus in parental allele effect , and their common biological function indicate that there is a single QTL in the distal part of Qrr1 modulating the expression of the ARS . It is crucial to note that this genetic modulation is only detected in CNS tissues . In the LXS hippocampus dataset , Qrr1 has only a limited trans-effect on gene expression . Despite the weak effect , expression of Dars2 ( probe ID ILM580427 ) maps to the distal part of Qrr1 at a LOD of 3 . Although this is only a weak detection of the ARS QTL in the LXS dataset , it nonetheless demonstrates the strong regulatory effect of Qrr1 on the expression of this gene family . In the case of the CXB hippocampus dataset , not a single trans-QTL for the ARS is detected in Qrr1 . In addition to the high overrepresentation of transcripts involved in translation and RNA metabolism , several transcripts known to be transported to neuronal processes or involved in RNA transport also map to Qrr1d , including Camk2a , Bdnf , Cdc42 , Eif4e , Eif4g2 , Hnrpab , Ppp1cc , Pabpc1 , Eif5 , Kpnb1 , Rhoip3 , Stau2 , and Pum2 [60]–[63] . An interesting example is provided by the brain derived neurotrophic factor ( Bdnf ) . Two alternative forms of Bdnf mRNA are known—one isoform has a long 3′ UTR and is specifically transported into the dendrites; the other isoform has a short 3′ UTR and remains primarily in the somatic cytosol [64] . The Affymetrix M430 arrays contain two different probe sets that target these Bdnf isoforms . Probe set 1422169_a_at targets the distal 3′ UTR and is essentially specific for the dendritic isoform , and probe set 1422168_a_at targets a coding sequence common to both isoforms . Although both probe sets detect high expression signal in the hippocampus , only the dendritic isoform maps as a trans-QTL to Qrr1d . This enrichment in transcripts that are transported to neuronal processes raises the possibility that this CNS specific trans-effect may be related to local protein synthesis . Prompted by the many ARS transcripts that consistently map to Qrr1d , we searched the genomic tRNA database [65] for tRNAs in this region . Interestingly , distal Chr 1 is one of many tRNA hotspots in the mouse genome and several predicted tRNAs are clustered in the non-coding regions of Qrr1 ( figure 2 ) . The majority of these tRNA sequences are in the proximal end of Qrr1 , over 2 Mb away from Qrr1d . We scanned the intergenic non-coding regions in Qrr1d for tRNAs using the tRNAscan-SE software [65] and uncovered tRNAs for arginine and serine , and three pseudo-tRNA sequences between genes Igsf4b and Aim2 ( 175 . 204–175 . 257 Mb ) in Qrr1d ( dataset S3 ) . Transfer RNAs are involved in regulating transcription of the ARS in response to cellular amino acid levels [66] and are functionally highly relevant candidates in Qrr1d . Polymorphism in the tRNA clusters ( e . g . , possible copy number variants , differences in tRNA species ) may have significant impact on the expression of the ARS . Trans-regulation of large number of transcripts by Qrr1 is a strong feature of crosses between B6 and D2—both the BXD RI set and B6D2F2 intercrosses—and in the B6 and C3H intercrosses . The feature is much weaker in the large LXS RI set and in the small CXB panel . The effect specificity demonstrates that a major source of the Qrr1 signal is generated by variations between B and D , and B and C3H alleles ( H ) but not by variations between the ILS and ISS alleles ( L and S , respectively ) , and B and BALB alleles ( C ) . This contrast can be exploited to identify sub-regions that underlie the trans-QTLs [67] . SNPs were counted for all four pairs of parental haplotypes—B vs D , B vs H , B vs C , and L vs S—and SNP profiles for the four crosses were compared ( figure 6 ) . Qrr1 is a highly polymorphic interval in the B6×D2 crosses . The flanking regions , however , have few SNPs ( 170–172 . 25 Mb proximally , and 177 . 5–179 . 5 Mb distally ) and are almost identical-by-descent between B6 and D2 . The B6×BALB crosses , despite being negative for the trans-effect , have moderate to high SNP counts in Qrr1 and share a SNP profile somewhat similar to B6×D2 crosses . The B6×C3H crosses also have moderate to high SNP counts in Qrr1 , with a relatively higher SNP count in Qrr1d compared to Qrr1p . In contrast , in the LXS , Qrr1p is more SNP-rich than Qrr1d . Most notably , the segments that harbor the tRNAs and candidates Fmn2 , Grem2 , and Rgs7 are almost identical by descent between ILS and ISS . This SNP comparison indicates that the strongest trans-effect is from Qrr1d . A possible reason why the trans-effect is not detected in the CXB RI strains , despite being SNP rich in Qrr1 , is that the crucial SNPs underlying the trans-QTLs may not be segregating in this cross or that undetected copy number variants make important contributions to the Qrr1 effects . A final explanation may be that the small CXB dataset ( 13 strains ) is simply underpowered . We used the specificity of cis-QTLs in the multiple crosses to identify higher priority candidates in Qrr1 . The assumption is that candidate genes whose transcripts have cis-QTLs ( LOD score above 3 ) in the B6×D2 and B6×C3H crosses but not in the LXS and CXB RI strains are stronger candidates for trans-QTLs that are detected in the former two crosses but not in the latter two crosses . In contrast , cis-QTLs with the inverse cross specificity are less likely to underlie these trans-QTLs . Based on this criterion , there are four high-ranking candidates in Qrr1p—Purkinje cell protein 4-like 1 ( Pcp4l1 ) , prefoldin ( Pfdn2 ) , WD repeat domain 42 a ( Wdr42a ) , and Kcnj10 ( table 3 ) . There are only two high-ranking candidates in Qrr1d—formin 2 ( Fmn2 ) , an actin binding protein involved in cytoskeletal organization , and regulator of G-protein signaling 7 ( Rgs7 ) ( table 3 ) . Both Fmn2 and Rgs7 are almost exclusively expressed in the CNS and are high priority candidates for the CNS specific trans-QTLs . A point of distinction between the two candidates is that while expression of Rgs7 maps as a cis-QTL only in the B6×D2 and B6×C3H crosses , expression of Fmn2 maps as a cis-QTL in B6×D2 and B6×C3H crosses , and in the CXB RI strains in which the trans-effect is not detected ( table 3 ) . Based on the pattern of specificity of cis-QTLs in multiple crosses , Rgs7 is a more appealing candidate . However , Fmn2 has known missense SNPs that segregate in the B6×D2 ( Glu610Asp , Pro1077Leu , Asp1431Glu ) and B6×C3H crosses ( Val372Ala ) . There are no known missense mutations in Fmn2 in the CXB and LXS RI strains , and no known missense mutation in Rgs7 in any of the four crosses . Linkage disequilibrium ( LD ) is a major confounding factor that limits fine-scale discrimination among physically linked candidates in a QTL . To further evaluate the two high-priority candidates in Qrr1d—Fmn2 and Rgs7—we implemented a partial correlation analysis [68] in which the effect of genotype at Qrr1d was controlled . For this analysis , we computed the partial correlation coefficient between cis-regulated transcripts and each trans-regulated transcript after regression against the Qrr1d genotype . This partial correlation reveals residual variance that links cis candidates with trans targets , independent of genetic variance at Qrr1d . We computed the partial correlation between Rgs7 and Fmn2 , and 14 transcripts representative of the different GOs that map to Qrr1d ( dataset S4 ) . The highest partial correlations are between Fmn2 and Rnf6 ( r = 0 . 68 , p-value<10−13 ) , Atf4 ( r = 0 . 6 , p-value<10−9 ) , Asns ( r = 0 . 55 , p-value<10−7 ) , Ube2d3 ( r = 0 . 5 , p-value<10−6 ) , Hnrpk ( r = 0 . 5 , p-value = 10−5 ) , Rab2 ( r = −0 . 5 , p-value = 10−5 ) , and Gars ( r = 0 . 5 , p-value = 10−5 ) . The strongest correlate of Fmn2 is Rnf6 , a gene involved in regulating actin dynamics in axonal growth cones [69] . Although not unequivocal , this analysis provides stronger support for Fmn2 than for Rgs7 . Fmn2 is almost exclusively expressed in the nervous system [70] and is a strong candidate for a trans-effect specific to neural tissues . However , its precise function in the brain has not been established . Fmn2-null mice do not have notable CNS abnormalities [71] , but to evaluate a possible role of Fmn2 on expression of genes that map to Qrr1d , we generated array data from brains of Fmn2-null ( Fmn2−/− ) and coisogenic ( Fmn2+/+ ) 129/SvEv controls . At a stringent statistical threshold ( Bonferroni corrected p<0 . 05 ) , only eight genes have significant expression differences between Fmn2−/− and Fmn2+/+ genotypes ( table 6 ) . Five out of the eight genes , including Pou6f1 , Usp53 , and Slc11a , have trans-QTLs in Qrr1d . Deletion of Fmn2 had the most drastic effect on the expression of the transcription factor gene Pou6f1 , a gene implicated in CNS development and regulation of brain-specific gene expression [72] , [73] . Expression of Pou6f1 maps as a trans-QTL ( at LOD score of 3 ) to Qrr1d in the hippocampus dataset , and its expression was down-regulated more than 44-fold in the Fmn2−/− line . While the expression analysis of Fmn2-null mice does not definitively link all the trans-QTLs to Fmn2 , variation in this gene is likely to underlie some of the trans-QTLs in Qrr1d . The possible compensatory mechanism in the Fmn2-null CNS , and the different genetic background of the mice ( 129/SvEv ) are factors that may have contributed to the weak detection of trans-effects in the knockout line . We examined the intracellular distribution of FMN2 protein in neurons using immunocytochemical techniques . All hippocampal pyramidal neurons on a culture dish exhibited distinct and fine granular immunoreactivity for FMN2 . The cell body itself had the strongest signal ( figure 7A ) . This fine punctate labeling extended into proximal dendrites and could be followed into distal dendrites . In some instances very thin processes , possibly the axons , were also labeled . The strong trans-effect that Qrr1 has on gene expression is a likely basis for the classical QTLs that map to this region . For example , the major seizure susceptibility QTL ( Szs1 ) has been precisely narrowed to Qrr1p [74] . We found that 10 genes already known to be associated with seizure or epilepsy have trans-QTLs with peak LOD scores near Szs1 and in Qrr1p . These include Scn1b , Cacna1g , Pnpo , and Dapk1 ( Table S2 ) [75]–[84] . In every case , the D allele has the positive additive effect on the expression of these seizure related transcripts , increasing expression 5% to 20% . The two potassium channel genes , Kcnj9 and Kcnj10 , are the primary candidates [74] . Both are strongly cis-regulated . The tight linkage between these genes ( within 100 kb ) limits further genetic dissection , but in situ expression data from the Allen Brain Atlas ( ABA , www . brain-map . org ) provides us with a powerful complementary approach to evaluate these candidates [85] . Kcnj9 ( figure 8A ) is expressed most heavily in neurons within the dentate gyrus , whereas Kcnj10 ( figure 8B ) is expressed diffusely in glial cells in all parts of the CNS . The seizure-related transcripts with trans-QTLs near Szs1 are most highly expressed in neurons , and all have comparatively high expression in the hippocampus . Furthermore , expression patterns of six of the seizure transcripts that map to Qrr1p show spatial correlations with Kcnj9 . Dapk1 and Cacna1g ( figure 8C ) have expression pattern that match Kcnj9 with strong labeling in the dentate gyrus and CA1 , and weaker labeling in CA2 and CA3 . In contrast , Socs2 ( figure 8D ) , Adora1 , Pnpo , and Kcnma1 complement the expression of Kcnj9 with comparatively strong expression in CA2 and CA3 , and weak expression in CA1 and dentate gyrus .
The two inwardly rectifying potassium channel genes—Kcnj9 and Kcnj10—are strong candidates for the seizure susceptibility QTL in Qrr1p that has been unambiguously narrowed to the short interval from Atp1a2 to Kcnj10 [74] . In BXD CNS datasets , Qrr1 also modulates the expression of a set of genes implicated in the etiology of seizure and epilepsy , including Pnpo , Scn1b , Kcnma1 , Socs2 , and Cacna1g . Polymorphisms in the Kcnj9/Kcnj10 interval that influence expression of these genes are excellent candidates for the Szs1 locus . The in situ expression data in the ABA shows a striking spatial correlation between expression of Kcnj9 and other seizure-related transcripts that have trans-QTLs in Qrr1p . The complementary expression of Kcnj9 and the seizure-related transcripts ( figure 8 ) make Kcnj9 a stronger candidate than Kcnj10 . Kcnj9 has over a 2-fold higher expression in D2 [our data] , [and cf . 26 , 86] , a seizure prone strain , compared to B6 , a relatively seizure resistant strain , suggesting that the proximal cause of Szs1 may be high expression of this gene , perhaps due to the promoter polymorphism discovered by Hitzemann and colleagues [26] . Fine mapping of complex traits have often yielded multiple constituent loci within a QTL interval [87] , [88] . Our mapping analyses of expression traits also show that multiple gene variants , rather than one master regulatory gene , cause the aggregation of expression QTLs in Qrr1 . Subgroups of genes with tight coexpression can be dissected from the dense cluster of QTLs . Most notable is the strong trans-regulatory effect of Qrr1d on genes involved in amino acid metabolism and translation , including a host of ARS transcripts . However , there are limits to our ability to dissect Qrr1 , and genes associated with protein degradation and RNA metabolism map throughout the region . In part this may be due to inadequate mapping resolution , but it may also reflect clusters of functionally related loci and genes [89] . At this stage we are also unable to discern whether there is a single or multiple QTLs within Qrr1d . While it is likely that a single QTL modulates the expression of the ARS , there may be additional gene variants in Qrr1d that modulate other transcripts involved in translation and RNA metabolism . With increased resolving power it may be possible to further subdivide transcripts that map to Qrr1p and Qrr1d into smaller functional modules . There may be multiple loci in Qrr1 that modulate different stages of protein metabolism in the CNS . Maintenance of cellular protein homeostasis requires finely tuned cross talk between transcription and RNA processing , the translation machinery , and protein degradation [90]–[92] , gene functions highly overrepresented among the transcripts that map to Qrr1 . While these are generic cellular processes , there are unique demands on protein metabolism in the nervous system . Neurons are highly polarized cells and specialized mechanisms are in place to manage local protein synthesis and degradation in dendrites and axons [93] . The nervous system is also particularly sensitive to imbalances in protein homeostasis [94] , [95] , a possible reason why the trans-effects of Qrr1 are detected only in neural tissues . Transfer RNAs are direct biological partners of the ARS , and the cluster of tRNAs in the highly polymorphic intergenic region of Qrr1d ( figure 6 ) is an enticing candidate . In addition to their role in shuttling amino acids , tRNAs also act as sensors of cellular amino acid levels and regulate transcription of genes involved in amino acid metabolism and the ARS [66] . There is tissue specificity in the expression of different tRNA isoforms [96] , and we speculate that the tRNA cluster in Qrr1d is specifically functional in neural tissues . Rgs7 , a member of the RGS ( regulator of G-protein signaling ) family , is another high-ranking candidate in Qrr1d . RGS proteins are important regulators of G-protein mediated signal transduction . Rgs7 is predominantly expressed in the brain and has been implicated in regulation of neuronal excitability and synaptic transmission [97] , [98] . Although RGS proteins are usually localized in the plasma membrane , RGS7 has been found to shuttle between the membrane and the nucleus [99] . This implies a role for RGS7 in gene expression regulation in response to external stimuli . Our final high-ranking candidate in Qrr1d is Fmn2 . It codes for an actin binding protein exclusively expressed in the CNS and oocytes , and is involved in the establishment of cell polarity [70] , [71] . In Drosophila , the formin homolog , cappuccino , has a role in RNA transport and in localizing the staufen protein to oocyte poles [100]–[102] . It is possible that FMN2 has parallel functions in mammalian neurons . Interestingly , Staufen 2 ( Stau2 ) , a gene involved in RNA transport to dendrites [62] , maps to Qrr1d in BXD CNS datasets . Furthermore , deletion of formin homologs in yeast results in inhibition of protein translation [103] , compelling evidence for an interaction between the protein translation system and formins . Evidence for a role for Fmn2 in dendrites also comes from our immunocytochemical analysis that clearly demonstrates the expression of FMN2 protein in dendrites . Taken together , Fmn2 is a functionally relevant candidate gene in Qrr1d and may be related to RNA transport and protein synthesis in the CNS .
The microarray datasets used in this study ( table 2 ) were generated by collaborative efforts [46] , [47] , [49]–[52] . All datasets can be accessed from www . genenetwork . org . They provide estimates of global mRNA abundance in neural and non-neural tissues in the BXD , LXS , and CXB RI strains , B6D2F2 intercrosses , and B6C3HF2 intercrosses . Detailed description of each set , tissue acquisition , RNA extraction and array hybridization methods , and data processing and normalization methods are provided in the “Info” page linked to each dataset . In brief , the datasets are: The conventional BXD RI strains were derived from the B6 and D2 inbred mice [104] , [105] . The newer sets of advanced RI strains were derived by inbreeding intercrosses of the RI strains [57] . The parental B6 and D2 strains differ significantly in sequence and have approximately 2 million informative SNP . A subset of 14 , 000 SNPs and microsatellite markers have been used to genotype the BXD strains [106] , [107] . We used 3 , 795 informative markers for QTL mapping . Thirty such informative markers are in Qrr1 and we queried these markers to identify strains with recombinations in Qrr1; genes with strong cis-QTLs ( Sdhc , Atp1a2 , Dfy , and Fmn2 ) were used as additional markers . Smaller sub-sets of markers were used to genotype the two F2 panels ( total of 306 markers for the whole brain , and 75 markers for the striatum F2 datasets ) . The LXS RI strains were derived from the ILS and ISS inbred strains . They have been genotyped using 13 , 377 SNPs , and some microsatellite markers [108] . 2 , 659 informative SNPs and microsatellite markers were used for QTL mapping . The CXB panel consists of 13 RI strains derived from C57BL/6By and BALB/cBy inbred strains . A total of 1384 informative markers were used for QTL mapping . The B6×C3H/HeJ F2 intercrosses have been genotyped using 13 , 377 SNPs and microsatellite markers , and 8 , 311 informative markers were used for QTL mapping . Majority of the BXD and LXS tissues ( cerebellum , eye , forebrain , hippocampus , kidney , liver , and striatum for the HQF Illumina dataset ) were dissected at the University of Tennessee Health Science Center ( UTHSC ) . Mice were housed at the UTHSC in pathogen-free colonies , at an average of three mice per cage . All animal procedures were approved by the Animal Care and Use Committee . Mice were killed by cervical dislocation , and tissues were rapidly dissected and placed in RNAlater ( Ambion , www . ambion . com ) and kept overnight at 4° C , and subsequently stored at −80 degree C . Tissue were then processed at UTHSC or shipped to other locations for processing . For the tissues that were processed at UTHSC ( all BXD and LXS CNS tissues except HBP Affymetrix striatum ) , RNA was isolated using RNA STAT-60 ( Tel-Test Inc . , www . tel-test . com ) as per manufacturer's instructions . Samples were then purified using standard sodium acetate methods prior to microarray hybridization . The eye samples required additional purification steps to remove eye pigment; this was done using the RNeasy MinElute Cleanup Kit ( Qiagen , www . qiagen . com ) . RNA purity and concentration was evaluated with a spectrophotometer using 260/280 nm absorbance ratio , and RNA quality was checked using Agilent Bioanalyzer 2100 prior to hybridization . Array hybridizations were then done according to standard protocols . We have re-annotated a majority of Affymetrix probe sets to ensure more accurate description of probe targets . Each probe set represents a concatenations of eleven 25-mer probes , and these have been aligned to the NCBI built 36 version of the mouse genome ( mm8 in UCSC Genome Browser ) by BLAT analysis . We have also re-annotated the Illumina probes and incorporated these annotations into GeneNetwork . Each probe in the Illumina Mouse–6 and Mouse–6 . 1 arrays is 50 nucleotides in length , and these have been aligned to NCBI built 36 . We used the strain average expression signal detected by a probe or probe set . QTL mapping was done for all transcripts using QTL Reaper [47] . The mapping algorithm combines simple regression mapping , linear interpolation , and standard Haley-Knott interval mapping [109] . QTL Reaper performs up to a million permutations of an expression trait to calculate the genome-wide empirical p-value and the LOD score associated with a marker . We selected only those transcripts that have highest LOD scores , i . e . , genome-wide adjusted best p-values , on markers located on Chr 1 from 172 to 178 Mb . This selected transcripts that are primarily modulated by Qrr1 but excluded transcripts that have QTLs in Qrr1 but have higher LOD scores on markers located on other chromosomal regions . Cis- and trans-QTLs were distinguished based on criteria described by Peirce et al . [47] . To identify trans-QTLs common to multiple datasets , we selected probes/probe sets that target the same genes and have peak LOD scores within 10 Mb in the different datasets . We screened all Affymetrix probe sets with cis-QTLs in Qrr1 for SNPs in target sequences . This step was taken to identity false cis-QTLs caused by differences in hybridization . As probe design is based on the B6 sequence , such spurious cis-QTLs show high expression for the B allele , and low expression for the D allele . Our screening identified only two probe sets in which SNPs result in spurious local QTLs—1429382_at ( Tomm40l ) , and 1452308_a_at ( Atp1a2 ) . The majority of cis-QTLs in Qrr1 are likely to be due to actual differences in mRNA abundance . We did not detect a bias in favor of the B allele on cis-regulated expression and the ratio of transcripts with B- and D- positive additive effects is close to 1∶1 . To measure expression difference between the B and D alleles , we exploited transcribed SNPs to capture allelic expression difference in F1 hybrids [56] using a combination of RT-PCR and a single base extension technology ( SNaPshot , Applied Biosystems , www . appliedbiosystems . com ) . For each transcript we analyzed , Primer 3 [110] was used to design a pair of PCR primers that target sequences on the same exon and flanking an informative SNP . We prepared four pools of RNA from the hippocampus , and four pools of genomic DNA from the spleen of F1 hybrids ( male and female B6×D2 and D2×B6 F1 hybrids ) . To avoid contamination by genomic DNA , the four RNA pools were treated with Turbo DNase ( Ambion , www . ambion . com ) , and then first strand cDNA was synthesized ( GE Healthcare , www . gehealthcare . com ) . The genomic DNA samples were used as controls , and both cDNA and genomic DNA samples were tested concurrently using the same assay to compare expression levels of B and D transcripts . We amplified the cDNA and genomic DNA samples using GoTaq Flexi DNA polymerase ( Promega Corporation , www . promega . com ) . PCR products were purified using ExoSap-IT ( USB Corporation , www . usbweb . com ) followed by SNaPshot to extend primer by a single fluorescently labeled ddNTPs . Fluorescently labeled products were purified using calf intestinal phosphatase ( CIP , New England BioLabs , www . neb . com ) and separated by capillary electrophoresis on ABI3130 ( Applied Biosystems ) . Quantification was done using GeneMapper v4 . 0 software ( Applied Biosystems ) , and transcript abundance was measured by peak intensities associated with each allele . Ratio of B and D allele in both cDNA and gDNA pools was computed , and t-test ( one tail , unequal variance ) was done to validate expression difference and polarity of parental alleles . GeneNetwork has compiled SNP data from different sources—Celera ( http://www . celera . com ) , Perlegen/NIEHS ( http://mouse . perlegen . com/mouse/download . html ) , BROAD institute ( http://www . broad . mit . edu/snp/mouse ) , Wellcome–CTC [107] , dbSNP , and Mouse Phenome Database ( http://www . jax . org/phenome/SNP ) . SNP counts were done on the GeneNetwork SNP browser . A partial correlation is the correlation between X and Y conditioned on one or more control variables . In this study , first order partial correlation was used to detect the interaction between trans-regulated transcripts and cis-regulated candidate genes conditioned on the genotype ( marker rs8242481 at 175 . 058 Mb ) . If x , y and z are trans-regulated transcripts , cis-regulated transcript , and genotype in the QTL , respectively , then the first order partial correlation coefficient is calculated as—where rxy can be either Pearson correlation or Spearman's rank correlation between x and y . We employed the Spearman's rank correlation because the expression levels of many transcripts do not follow a normal distribution . The significance of a partial correlation with n data points was assessed with a two-tailed t test on where r is the first order correlation coefficient , and k is the number of variables on which we are conditioning . Cultured hippocampal neurons from male B6 mice , prepared as described in Schikorski et al . [111] and cultured for 23 days , were fixed with 4% paraformaldehyde and 0 . 1% glutaraldehyde in HEPES buffered saline ( pH 7 . 2 ) for 15 min . Cell membranes were permeabilized with 0 . 1% triton X-100 and unspecific binding sites were quenched with 10% BSA for 20 min at room temperature ( RT ) . Neurons were incubated with a polyclonal anti-FMN2 antibody ( Protein Tech Group , www . ptglab . com ) diluted to 0 . 3 µg/ml at RT overnight . An anti-rabbit antibody raised in donkey ( 1∶500 , Invitrogen; http://www . invitrogen . com ) conjugated with the fluorescent dye Alexa488 was used for the detection of the first antibody . All regions of interest were photographed with identical illumination and camera settings to allow for a direct comparison of the staining in labeled and control neurons . The Fmn2−/− mice were generated using 129/SvEv ( now strain 129S6/SvEvTac ) derived TC-1 embryonic stem cells . Chimeric mice were backcrossed to 129/SvEv [70] . The Fmn2-null and littermate controls are therefore coisogenic . To validate the isogenicity of regions surrounding the targeted locus [112] , we genotyped the Fmn2+/+ , Fmn2+/− , and Fmn2−/− mice using ten microsatellite markers located on , and flanking Fmn2 ( markers distributed from 172 Mb to 182 Mb ) . These markers are D1Mit455 , D1Mit113 , D1Mit456 , D1Mit356 , D1Mit206 , D1Mit355 , D1Mit150 , D1Mit403 , D1Mit315 , and D1Mit426 . With the exception of a marker at Fmn2 ( D1Mit150 ) , all alleles in null , heterozygote , and wildtype animals were identical . RNA was isolated from whole brain samples of Fmn2+/+ and Fmn2−/− mice , and assayed on Illumina Mouse-6 array slides ( six samples per slide ) . We compared five samples from Fmn2−/− nulls , and five samples from Fmn2+/+ wildtype . Equal numbers of each genotypes were placed on each slide to avoid batch confounds . Microarray data were processed using both raw and rank invariant protocols provided by Illumina as part of the BeadStation software suite ( www . illumina . com ) . We subsequently log-transformed expression values and stabilized the variance of each array . To identify genes with significant expression difference between the Fmn2−/− and Fmn2+/+ cases , we carried out two-tailed t-tests and applied a Bonferroni correction for multiple testing , and selected probes with a minimum adjusted p-value<0 . 05 . Classical QTLs counts are based on the April 2008 version of Mouse Genome Informatics ( MGI: www . informatics . jax . org ) [113] . Search for tRNAs was done using tRNAscan-SE 1 . 21 ( http://lowelab . ucsc . edu/tRNAscan-SE/ ) [65] . GO analysis was done using the analytical tool DAVID 2007 ( http://david . abcc . ncifcrf . gov/ ) [114] . Overrepresented GO terms were identified and statistical significance of enrichment was calculated using a modified Fisher's Exact Test or EASE score [115] . We used the Allen Brain Atlas to analyze expression pattern in the brain of young C57BL/6J male mice ( www . brain-map . org ) [85] , [116] . In RI strains , non-syntenic associations can lead to LD between distant loci [89] , [106] . In the BXDs , we detected such non-syntenic associations between markers in Qrr1 and markers on distal Chr 2 and proximal Chr 15 . As a result of these associations , some transcripts that have strong cis- or trans-QTLs in Qrr1 tend to have weak LOD peaks , usually below the suggestive threshold , on distal Chr 2 and proximal Ch15 . However , there is no bias for genes located in these intervals in LD with Qrr1 to have trans-QTLs in Qrr1 . The Qrr1 segment has been reported to have paralogues on mouse Chrs 1 ( proximal region ) , 2 , 3 , 6 , 7 , 9 , and 17 [117] , [118] . We examined if the trans-QTLs in Qrr1 are of genes located in these paralogous regions . However , genes located in the paralogous regions are not overrepresented among the trans-QTL . | A major goal of genetics is to understand how variation in DNA sequence gives rise to differences among individuals that influence traits such as disease risk . This is challenging . Most traits are the result of a complex interplay of genetic and environmental factors . One of the first steps in the path from DNA to these complex traits is the production of mRNA molecules . Understanding how sequence differences modulate expression of different RNAs is fundamental to understanding the molecular origins of complex traits . Here , we combine classic gene mapping methods with microarray technology to characterize and quantify RNA levels in different crosses of mice . We focused on a hotspot on chromosome 1 that controls the expression of a large number of different types of RNAs in the brain . This hotspot also controls many disease traits , including anxiety levels , and vulnerability to seizure in mice and humans . We show that this hotspot is made up of several distinct functional regions , one of which has an unusually strong and selective effect on aminoacyl-tRNA synthetases and other genes involved in protein translation . | [
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... | 2008 | Dissection of a QTL Hotspot on Mouse Distal Chromosome 1 that Modulates Neurobehavioral Phenotypes and Gene Expression |
Bourbon virus ( BRBV ) is an emerging tick-borne RNA virus in the orthomyxoviridae family that was discovered in 2014 . Although fatal human cases of BRBV have been described , little is known about its pathogenesis , and no antiviral therapies or vaccines exist . We obtained serum from a fatal case in 2017 and successfully recovered the second human infectious isolate of BRBV . Next-generation sequencing of the St . Louis isolate of BRBV ( BRBV-STL ) showed >99% nucleotide identity to the original reference isolate . Using BRBV-STL , we developed a small animal model to study BRBV-STL tropism in vivo and evaluated the prophylactic and therapeutic efficacy of the experimental antiviral drug favipiravir against BRBV-induced disease . Infection of Ifnar1-/- mice lacking the type I interferon receptor , but not congenic wild-type animals , resulted in uniformly fatal disease 6 to 10 days after infection . RNA in situ hybridization and viral yield assays demonstrated a broad tropism of BRBV-STL with highest levels detected in liver and spleen . In vitro replication and polymerase activity of BRBV-STL were inhibited by favipiravir . Moreover , administration of favipiravir as a prophylaxis or as post-exposure therapy three days after infection prevented BRBV-STL-induced mortality in immunocompromised Ifnar1-/- mice . These results suggest that favipiravir may be a candidate treatment for humans who become infected with BRBV .
Bourbon virus ( BRBV ) is an emerging tick-borne RNA virus and a member of the genus Thogotovirus in the family orthomyxoviridae . It was first discovered in 2014 in a clinical specimen obtained from a severely ill patient from Bourbon County , Kansas . This individual died two days later from complications of renal failure , acute respiratory distress syndrome , and ventricular tachycardia [1] . The genome of BRBV is composed of six gene-segments that are predicted to encode for PB2 , PB1 , and PA polymerase proteins , a nucleoprotein ( NP ) , a surface glycoprotein ( GP ) , and a matrix ( M ) protein . Following the initial discovery of this virus , one additional case of human BRBV infection was identified [2] . BRBV replicates in tick cell lines [3] , and surveillance studies have identified BRBV-positive ticks near the border of Missouri and Kansas [2 , 4] . All positive ticks reported to date belong to the species Amblyomma americanum , also known as the Lone-Star tick . A . americanum is an aggressive tick that feeds on many species including humans . The host range and natural reservoir of BRBV are not known , and antiviral therapies and vaccines against BRBV have not been developed . Here , we report on the isolation and characterization of the second human isolate of BRBV ( BRBV-STL ) . BRBV-STL was cultured from a clinical specimen obtained from a fatal BRBV case . BRBV-STL replication was inhibited in vitro by the RNA polymerase inhibitor favipiravir . In vivo administration of favipiravir prior to or following BRBV infection protects against fatal disease in immunocompromised Ifnar1-/- mice . These data support the evaluation of favipiravir as antiviral drug in future human cases of BRBV .
In June of 2017 , a 58-year old Caucasian woman undergoing treatment for relapsed follicular lymphoma with rituximab and bendamustine presented with a two-week history of generalized weakness , myalgia , nausea , and rash , all of which occurred approximately one week after she noted exposure to ticks . She subsequently developed diarrhea and a fever of 39°C , prompting her admission to a hospital . Initial diagnostic laboratory workup was notable for marked thrombocytopenia ( 18 , 000 per mm3 ) , leukopenia ( 2 , 400 per mm3 ) , lymphopenia ( 500 per mm3 ) , and mild elevation of aspartate transaminase ( AST; 74 U/L ) ; these abnormalities were not noted after previous cycles of her chemotherapy . Serological testing for Rocky Mountain spotted fever ( RMSF ) and HIV , as well as PCR testing for Ehrlichia and Anaplasma spp . from serum , were negative . The patient was started on empiric doxycycline and broad-spectrum antibiotics without clinical improvement . The patient continued to experience debilitating fatigue , progressive rash , and wheezing with mild hypoxia , although chest radiograph and chest computed tomography scan did not initially demonstrate pulmonary infiltrates . Her ferritin levels were high at 4 , 785 ng/mL , and systemic steroids were initiated due to concern for hemophagocytic lymphohistiocytosis ( HLH ) . Bone marrow biopsy on hospital day 5 did not find evidence of lymphoma , but did show scattered hemophagocytic histiocytes . The patient’s rash progressed to include marked involvement of the palms and soles , with skin biopsy on hospital days 5 and 9 demonstrating interface dermatitis inconsistent with Rickettsial disease . Repeat RMSF serologies on hospital day 14 again were negative . In the setting of ongoing diarrhea , an ELISA for Clostridium difficile toxin was positive , and the patient was started on oral vancomycin . Notwithstanding these interventions , her diarrhea persisted , and she developed oral mucositis with ulcerations that were negative for herpes simplex virus by PCR . A serum sample sent to the Center for Disease Control , Division of Vector-Borne Diseases , on hospital day 3 , was found to be positive for BRBV RNA on hospital day 10 . The patient’s wheezing and dyspnea worsened , and on hospital day 17 , chest radiograph demonstrated new , diffuse , bilateral , upper lobe-predominant interstitial infiltrates with a small left-sided pleural effusion . She developed fluctuating cognitive impairment with disorientation and somnolence , and a brain MRI on hospital day 21 demonstrated mild white matter fluid-attenuated inversion recovery hyperintensity . Elevations in aspartate aminotransferase and alanine transaminase ( 482 and 110 U/L respectively on hospital day 21 ) and ferritin ( 11348 ng/mL ) worsened , prompting the initiation of etoposide to treat HLH . The patient’s mental status and hypoxic respiratory failure continued to worsen , and she was transferred to the intensive care unit . A transthoracic echocardiogram showed left ventricular systolic dysfunction and a hemorrhagic pericardial effusion . She died on hospital day 23 . Serum collected from the patient was used to inoculate Vero cells . Three days later , cytopathic effect ( CPE ) was observed in the cells inoculated with a 1:5 dilution of the serum . CPE was observed 4 and 5 days post infection ( dpi ) in the cells inoculated with 1:50 and 1:500 dilution of serum . RNA was extracted from the supernatant of these infected cells and used for next generation sequencing; the resulting sequence identified BRBV . The average sequence coverage was 10 , 000x with lower coverage near the 3’ and 5’ untranslated regions of each gene-segment . Compared to the original isolate of BRBV from Kansas ( BRBV-KS ) [1 , 3] , BRBV-STL is 99 . 3% identical at the nucleotide level ( Fig 1 ) . A total of 21 amino acid differences were identified in five of the six predicted viral proteins ( Table 1 ) . Of note , one region in the PB1 protein ( 573–577 ) and another in the NP ( 67–71 ) protein were variable between the two BRBV isolates . Favipiravir is a drug with efficacy against influenza A virus ( a distantly related orthomyxoviridae family member ) that acts by inhibiting its RNA dependent RNA polymerase [5–7] . Since BRBV is a member of the orthomyxoviridae , we hypothesized that favipiravir might have antiviral activity against BRBV . To test this , we performed a virus growth assay in the presence or absence of 100 μg/mL of favipiravir and measured viral titers in the culture supernatant every 24 hours ( h ) for 4 days by a virus titration assay ( TCID50/mL ) . Without favipiravir , BRBV-STL grew to ~108 TCID50/mL in 4 days . In contrast , addition of the drug immediately after infection inhibited virus production in the culture supernatant nearly a million-fold ( Fig 2a ) . At this dose of favipiravir , the viability of the Vero cells was minimally affected ( Fig 2b ) . Next , we determined the minimal effective concentration ( EC50 ) of favipiravir against BRBV-STL . Vero cells were infected with BRBV-STL in the presence of different concentrations of favipiravir . Culture supernatant was collected at 72 hours post infection ( hpi ) and the virus titer was quantified by plaque assay ( pfu/mL ) . No replicating virus was detected by plaque assay at 100 and 300 μg/mL ( 0 . 64 and 1 . 9 mM ) concentrations of favipiravir ( Fig 2c ) ; concentrations that did not affect the viability of Vero cells ( Fig 2b ) . No inhibitory effect of favipiravir on BRBV-STL virus titers was observed at 30 μg/mL or lower concentrations ( Fig 2c ) . Based on this data , the EC50 of favipiravir against BRBV was calculated as ~48 μg/mL ( 0 . 31 mM ) . To confirm that favipiravir targets the polymerase complex of BRBV-STL , we developed a mini-genome reporter assay for BRBV-STL . Transfection of 293T cells with expression plasmids encoding for the PB2 , PB1 , PA and NP proteins , plus the firefly-luciferase reporter gene , resulted in robust firefly-luciferase activity ( Fig 2d ) . This activity was specific for the polymerase complex of BRBV , as removal of the essential polymerase gene PB1 resulted in no reporter activity . This assay was used to quantify the inhibitory effects of favipiravir on BRBV replication . The polymerase activity of BRBV-STL was significantly reduced at 100 , 30 , 10 , 3 and 1 μg/mL ( 640–6 . 4 μM ) concentrations of favipiravir compared to the mock-treated control ( P < 0 . 001 , Fig 2d ) ; the EC50 value was calculated as 1 μg/mL ( 6 . 4 μM ) . Subcutaneous inoculation of wild-type WT mice with 4 x 104 plaque forming units ( pfu ) of BRBV-STL in the footpad resulted in no weight loss or mortality after infection ( Fig 3a and 3b ) . As replication of human viruses in mice often is inhibited by type I interferon ( IFN ) signaling and induction of antiviral gene expression due to a species-specific failure to antagonize this key host antiviral pathway [8] , we repeated experiments in Ifnar1-/- mice lacking the type I IFN receptor . Footpad inoculation of Ifnar1-/- mice with 4 x 104 pfu of BRBV-STL resulted in significant weight loss ( P < 0 . 0001 ) , starting at 4 dpi and 100% mortality by 10 dpi ( P < 0 . 0001 , Fig 3a and 3b ) . A similar result was observed after inoculation of 4 x 104 pfu of BRBV-STL via the intraperitoneal route ( Fig 3c and 3d ) . All Ifnar1-/- mice started losing weight at 2 dpi and succumbed to infection at 8 dpi . Intraperitoneal ( IP ) inoculation with 4 x 102 pfu of BRBV-STL also resulted in substantial weight loss ( P < 0 . 0001 ) and 100% mortality after infection ( P < 0 . 0001 , Fig 3c and 3d ) . To characterize the tissue tropism of BRBV-STL , we collected serum , liver , spleen , kidney , and lung tissues at 3 and 6 dpi from WT and Ifnar1-/- mice inoculated with 4 x 104 pfu of BRBV-STL via intraperitoneal route . The tissues were homogenized and the viral load was quantified by plaque assay on Vero cells . At 3 dpi , we observed high virus titers ( 105–107 pfu/mL ) in the liver and spleen of Ifnar1-/- mice , whereas the serum , kidneys , and lungs of Ifnar1-/- mice had lower virus titers ( 103–105 pfu/mL ) ( Fig 4a ) . In contrast , WT mice had no detectable virus in all of the organs tested . At 6 dpi , the liver and spleen of BRBV-STL inoculated Ifnar1-/- mice still contained high levels of virus , although the titer in the spleen had dropped by ~100-fold ( Fig 4b ) . No replicating virus was detected in WT mice at this time point . To further define the tropism of BRBV-STL in Ifnar1-/- mice , we performed RNA in situ hybridization ( RNA-ISH ) and histological analysis on tissue sections of BRBV-STL infected wild type and Ifnar1-/- mice ( Fig 4c , S1 and S2 Figs ) . At 3 dpi , viral RNA was detected in the liver and spleen of all three Ifnar1-/- mice . In the liver , the staining corresponded to sinusoidal cells , whereas in the spleen viral RNA was primarily detected in macrophages of the white pulp with fewer positive cells in the red pulp . One animal showed minimal staining in the lungs that corresponded to alveolar macrophages . No viral RNA was detected in the brain , heart , and kidney at 3 dpi . At 6 dpi , viral RNA was detected in liver , spleen , lung , heart and kidney of all three Ifnar1-/- mice ( Fig 4c , and S2 Fig ) . Only one of the mice was positive for viral RNA in the brain . Staining of these same tissues with hematoxylin and eosin ( H & E ) revealed minimal multifocal hepatitis with signs of inflammation at 3 dpi , and moderate diffuse hepatitis with coagulative necrosis and extra medullary granulopoiesis in the liver of Ifnar1-/- mice ( S1 Fig ) . In the white pulp of the spleen there was mild to moderate lymphoid necrosis and inflammation at 3 dpi . At 6 dpi , there was marked diffuse lymphocyte necrosis and inflammation in the white pulp and an increase in extramedullary granulopoiesis in the red pulp . Finally , in the heart and lungs there was evidence of neutrophil and mononuclear cell infiltration at 6 dpi . No significant lesions were found in the kidneys and brains of Ifnar1-/- mice at 6 dpi . In contrast , no BRBV RNA positive cells were detected in any of the tissue sections from WT mice ( S2 Fig ) . To test whether favipiravir had efficacy against BRBV-STL in vivo , we inoculated Ifnar1-/- mice via IP route with 4 x 102 pfu of BRBV-STL and treated the mice twice daily with 150 mg/kg of favipiravir in 0 . 5% methylcellulose via oral gavage for 8 days beginning immediately after infection . Compared to mock-treated animals , favipiravir treated animals did not show evidence of weight loss ( P < 0 . 0001 ) after infection , and none of the treated animals succumbed to infection ( P < 0 . 0001 , Fig 5a and 5b ) . We next evaluated the therapeutic effect of favipiravir . Animals treated twice daily with 150 mg/kg of favipiravir for 8 days starting 1 dpi did not lose weight , and all animals survived infection ( Fig 5c and 5d ) . Analysis of the virus burden in different organs revealed low to undetectable BRBV replication 3 days after initiation of treatment ( Fig 5e ) in liver and lungs of the treated mice . In comparison , mock-treated mice had demonstrable virus titers in these organs ( Fig 5e ) . No effect of favipiravir on spleen virus load was detected . To determine if favipiravir was effective after the onset of symptoms , we initiated treatment at 3 dpi with BRBV-STL . At this time point , the animals were starting to lose weight and replicating BRBV-STL was detected throughout the body ( Fig 4a ) . One-day after favipiravir treatment initiation ( 4 dpi ) , the mice stopped losing weight and gradually recovered from the infection ( Fig 5c ) . Remarkably , all of the animals survived the infection , whereas the mock-treated animals all succumbed ( P < 0 . 001 , Fig 5d ) . Collectively , these data show that favipiravir treatment has therapeutic efficacy against BRBV-STL in this pre-clinical mouse model .
BRBV is a recently discovered tick-borne orthomyxovirus that was first identified in 2014 in a human patient who died due to complications from the disease . Currently , there is no approved therapy or vaccine against BRBV . Here we report the isolation and characterization of the second human isolate of BRBV ( BRBV-STL ) from a fatal case and demonstrate that BRBV replication is inhibited by the broad-spectrum antiviral drug favipiravir . Using a novel mouse model of BRBV pathogenesis , we also show that favipiravir has prophylactic and therapeutic activity against fatal BRBV disease . These findings support the possible evaluation of favipiravir as a therapeutic for future human BRBV cases . This study describes a lethal mouse model for BRBV . A previous study showed that immunocompetent mice inoculated via IP or intracranial routes with BRBV sustained no signs of morbidity or mortality [3] . We confirmed this finding , as we observed no signs of weight loss or death after inoculation with high doses of BRBV-STL ( 4 x 104 pfu ) . Partial neutralization of the type I IFN response , using a blocking monoclonal antibody against the type I IFN receptor ( MAR1-5A3 ) did not result in fatal BRBV disease ( S3 Fig ) . However , some replicating virus was detected 3 dpi in the spleen of mice suggesting that inhibition of the innate antiviral immune response increased the susceptibility to BRBV infection . Indeed , inoculation of Ifnar1-/- mice with low doses of BRBV-STL resulted in high viral titers in liver and spleen , weight loss , and uniform death 7–10 days after infection . Ifnar1-/- mice have been used previously for other viral animal models , including Ebola , Zika , West Nile ( WNV ) and severe fever with thrombocytopenia syndrome ( SFTSV ) viruses [9 , 10] . Viral pathogenesis in Ifnar1-/- mice has been associated with higher viral burden and increased inflammation caused by the dysregulation of type I IFN inducible negative regulation of inflammation [11 , 12] . In the WNV and SFTSV models in Ifnar1-/- mice , the inflammatory dysregulation results in uniform death of the mice at 3 and 4–5 dpi , respectively . It is not known if BRBV-STL induces a similar dysfunctional inflammatory response , and if this results in demise of the mice . A comparison between the pathophysiology of BRBV disease in mice and humans is difficult to make given the small number of human cases reported to date . BRBV-STL demonstrated broad tissue tropism in immunocompromised Ifnar1-/- mice; particularly high levels of viral replication were noted in the liver and spleen , but substantial quantities of BRBV RNA were also detected in lung , serum and kidney . In both cases of human BRBV disease reported to date , a systemic illness progressing to multiple organ dysfunction was noted , and viremia was present . Which of these multisystem manifestations of BRBV disease is directly attributable to viral replication in the relevant end organs is unclear , as systemic inflammation could accompany BRBV infection and also cause disease . Indeed , the presence of hemophagocytic histiocytes in the bone marrow biopsy is suggestive of a systemic inflammatory response to viral infection . However , the elevations in serum ALT , AST , and ferritin levels in both human cases reported to date are also consistent with cytopathic BRBV replication in the liver , as was seen in Ifnar1-/- mice . Favipiravir is broad-spectrum antiviral compound that inhibits the RNA dependent RNA polymerase of RNA viruses [13 , 14] . It was originally discovered as an antiviral compound against influenza A viruses ( IAV ) , but subsequent studies showed a broad-spectrum activity against other RNA viruses . Since BRBV is a member of the family of orthomyxoviridae , like IAV , we hypothesized that favipiravir might have antiviral activity against BRBV . Our in vitro studies show that favipiravir inhibits BRBV replication; however , the EC50 is significantly higher compared to IAV ( 0 . 03–1 . 6 μg/mL ) [15 , 16] . The basis for this difference is not known , but it is possible that the amino acid differences between the viruses affect the shape or size of the binding pocket in the PB1 protein and therefore reduces the EC50 . Structural studies and comparisons between various PB1 proteins may identify the reason for this reduced sensitivity . Multiple antiviral compounds against influenza virus are in clinical trials , and many of these compounds target components of the polymerase complex ( PB2 , PB1 and PA proteins ) of Influenza A virus . It will be important to test these anti-influenza virus drugs against BRBV to identify additional inhibitors of virus replication and perhaps develop a combinatorial therapy to increase effectiveness and avoid resistance [17] . The EC50 value of favipiravir against BRBV-STL in Vero cells was relatively high and comparable to that of Ebola and yellow fever viruses [14] . Despite this , administration of 150 mg/kg favipiravir twice daily three days after BRBV-STL infection , when virus infection was established in many different organs , was 100% effective , and all of the animals survived infection . The serum concentration of favipiravir following 150 mg/kg twice daily administration reaches 200 μg/mL concentration [16] , which is well above the EC50 value measured in Vero cells , and 100-fold higher than the EC50 value in the mini-genome reporter assay . Future titration studies will identify the minimal effective dose of favipiravir in this model and evaluate if combinations of antiviral drugs , such as a polymerase inhibitor and an endonuclease inhibitor can increase the efficacy of either compound alone . The effective concentration ( EC50 ) of favipiravir in the mini-genome assay is nearly 100-fold lower than the virus replication assay . This difference is not caused by a change in cell type , since the EC50 for virus replication on 293T cells was similar than that of Vero cells ( S4 Fig ) . It is possible that the mini-genome assay is more sensitive to perturbation of PB1 activity , the target of favipiravir , or the assay conditions increase intracellular drug concentrations . Alternatively , the expression of the other BRBV proteins inhibit the activity , transport , or activation of the drug . The genome of BRBV-STL is highly similar to that of the original isolate , BRBV-KS , with the exception of two regions that distinguish the viruses . These two regions are in the PB1 and NP protein , and the significance of these changes is not known . The amino acid differences in the PB1 and NP protein between BRBV-KS and BRBV-STL also were found in RNA directly obtained from the clinical specimen excluding the possibility of tissue culture adaptations . Since BRBV-STL and BRBV-KS were isolated from geographically distinct areas , it is possible that the differences in genome sequence are caused by the differences in host or tick species between these two geographic areas . In summary , our study has shown that the pan antiviral compound favipiravir can treat an ongoing BRBV infection in a pre-clinical animal model , suggesting that favipiravir may be a candidate drug for the treatment of BRBV in humans .
This study was approved by the Human Research Protection Office of Washington University School of Medicine in St . Louis . Informed consent was obtained . Four to eight-week-old male and female C57BL/6J ( WT ) and Ifnar1-/- mice were bred in a barrier facility at Washington University School of Medicine . All animal studies were approved and performed in accordance with the Washington University School of Medicine Institutional Animal Care and Use Committees . Vero cells ( ATCC ) were grown in Dulbecco’s Modified Eagle Medium ( DMEM ) media ( Corning Cellgro ) supplemented with 10% Fetal Bovine Serum ( FBS , Biowest ) , 100 U/mL Penicillin ( Life Technologies ) , 100 μg/mL streptomycin ( Life Technologies ) , and 2 mM L-Glutamine ( Corning ) . 293T cells ( gift from Dr . Webby at St . Jude Children’s Research Hospital ) were maintained in Opti-MEM ( Life Technologies ) with 10% Hyclone FBS ( Thermo Fisher Scientific ) , 2 mM L-glutamine , 100 U/ml of Penicillin and 10 μg/mL of Streptomycin . Bourbon virus ( BRBV ) was isolated from a serum sample obtained from a 58-year old female who was admitted to Barnes Jewish Hospital in St . Louis in June of 2017 . This isolate , BRBV-STL , grew to high titers in Vero cells , similar to that reported for the reference isolate [3] . A passage 2 ( P2 ) stock of BRBV-STL was aliquoted , stored at -80°C , and used for all subsequent studies . The virus titer of the P2 stock was 2 x 108 TCID50/mL or 4 x 107 pfu/mL . RNA was isolated from the supernatant of Vero cells inoculated with the serum of the patient using the E . Z . N . A . Total RNA kit ( Omega Bio-tek ) . The RNA was used to identify the genome sequence and clone segments 3–6 into expression vectors . For next-generation sequencing ( NGS ) , the sample was amplified using a random RT-PCR protocol , and the resulting amplicons were used to generate a library using the NEBNext ( NEB ) kit as described [18] . The library was sequenced on the 2x250 base pair Illumina MiSeq platform . We used BWA to align the reads and LoFreq version 2 to identify SNPs relative to the published sequence of the original isolate of BRBV ( BRBV-KS ) [19 , 20] . A phylogenetic tree of segment 2 ( PB1 gene ) of different orthomyxoviruses was constructed using ClustalW in the DNASTAR Lasergene 15 software package . Bourbon virus strain St . Louis ( BRBV-STL , MK453528 ) ; Bourbon virus strain original ( BRBV-KS , KU708254 . 1 ) ; Dhori virus ( NC_034263 . 1 ) ; Oz virus ( LC320124 . 1 ) ; Jos virus ( HM627170 . 1 ) ; Aransas virus ( KC506163 . 1 ) ; Thogoto virus ( AF004985 . 1 ) ; Influenza A virus ( CY009450 ) ; Influenza B virus ( AY582058 . 1 ) ; Influenza C virus ( NC_006308 . 2 ) ; Influenza D virus ( LN559121 . 1 ) ; Quaranfil virus ( FJ861695 . 1 ) . The virus titer in stocks , supernatants and organs was quantified by plaque assay ( pfu/mL ) or virus titration assay ( TCID50/mL ) . For the plaque assay , confluent monolayers of Vero cells were grown in 24-well plates overnight . The next day , the cells were washed with serum free DMEM medium and inoculated with 250 μL of medium containing 10-fold serially diluted virus , culture supernatant , or organ homogenate , starting at a 1:10 dilution . After 1 h at 37°C , the inoculum was aspirated and 1 mL of 2% methylcellulose in DMEM supplemented with 2% FBS , 100 U/mL Penicillin , 100 μg/mL streptomycin , and 2 mM L-Glutamine was added to each well . The plate was incubated for 6 days at 37°C/5% CO2 before the monolayer was fixed with 250 μL of 4% paraformaldehyde ( PFA , in PBS ) for 1 h and stained with 0 . 5% crystal violet for 1 h at 20°C . The number of plaques per dilution were enumerated and used to calculate the pfu/mL . For the TCID50 virus titration assays , confluent monolayers of Vero cells were grown in 96-well plates overnight . The next day , the cells were washed with serum-free DMEM medium and inoculated with 100 μL of DMEM medium containing 10-fold serially diluted virus , culture supernatant , or organ homogenate , starting at a 1:10 dilution . After 1 h at 37°C/5% CO2 , the inoculum was aspirated and 200 μL of fresh DMEM supplemented with 2% FBS , 100 U/mL Penicillin , 100 μg/mL streptomycin , and 2 mM L-Glutamine ( D2F media ) was added to each well , and the plate was incubated for 6 days at 37°C . Next , the cells were fixed with 4% PFA for 1 h and stained with 0 . 5% crystal violet at 20°C . The cytopathic effect from BRBV destroys the monolayer and this can be used to quantify virus load according to the Reed & Munch method . Confluent monolayers of Vero cells in 24-well plates were inoculated with 20 pfu ( Multiplicity of infection ( MOI ) = 0 . 001 ) for 1 h at 37°C/5% CO2 . Next , the inoculum was aspirated and the cells were washed with medium before 1 . 0 mL of fresh D2F was added to each well . To test the effects of favipiravir , different concentrations ( 300 μg/mL to 1 μg/mL ) of the compound , diluted in DMSO , were added to the wells . Each concentration of favipiravir was tested in duplicate per experiment and the experiment was repeated three times . Control wells were treated with the same concentration of DMSO . The 300 μg/mL and 100 μg/mL concentration of favipiravir have the same DMSO control ( 1% final concentration ) . Culture supernatant was collected at different time points and used to quantify the amount of infectious virus produced by virus titration assay . The cytotoxicity of favipiravir on 293T and Vero cells was evaluated by 2 , 3-Bis ( 2-methoxy-4-nitro-5-sulfophenyl ) -2H-tetrazolium-5-carboxanilide ( XTT ) assay . Cells were seeded at 4 x 104 cells per well in a 96-well plate . After overnight incubation , different concentrations of favipiravir diluted in RPMI 1640 media ( Gibco ) were added to each well . Cells treated with 1% Triton X-100 were used as the positive control for cell death . After 3 days , cells were treated with 0 . 2 mg/mL XTT and 0 . 1 mM phenazine methosulfate for 2 h at 37°C . XTT reduction to formazan was measured at 450 nm wavelength and background ( 630 nm ) corrected absorbance values were used to calculate cell viability . The PB2 , PB1 , PA , and NP genes of BRBV-STL were cloned into pcDNA3 . 1+ expression vectors . The PA and NP genes were derived from cDNA generated from BRBV-STL RNA extracted from Vero cell culture supernatant inoculated with a 1:5 dilution of the patient serum . The PB2 and PB1 genes of BRBV-STL were synthesized by GENEWIZ . The firefly luciferase gene was cloned into the pLuci vector flanked by the 3' and 5' untranslated region of segment 6 of the original BRBV isolate ( BRBV-KS ) . A total of 500 ng of DNA split evenly between the 4 BRBV genes , the firefly reporter construct and the Renilla luciferase internal control was transfected into 293T cells in 24-well plates using TransIT LT1 ( Mirus Bio ) . Two days later , the amount of firefly and Renilla luciferase activity were quantified with the Dual luciferase assay reporter system ( Promega ) . To test the effects of favipiravir , different concentrations of the compound dissolved in DMSO were added to the well along with the transfection mixture . The polymerase activity for each condition was normalized to that of the mock-treated ( DMSO only ) control cells . WT and Ifnar1-/- mice were inoculated subcutaneously with 4 x 104 pfu of BRBV-STL via footpad injection , or with 4 x 102 or 4 x 104 pfu via intraperitoneal injection . Weight change and survival were monitored for 14 days . To identify tissue tropism , organs from BRBV-STL infected animals were harvested 3 and 6 dpi , and viral load was determined by plaque assay on Vero cells after homogenization in 1 . 0 mL of DMEM media . For RNA in situ hybridization , organs from BRBV-STL infected or mock-infected animals were harvested 3 and 6 dpi and fixed in 10% formalin for 7 days prior to paraffin embedding and sectioning . To evaluate the prophylactic and therapeutic activity of favipiravir ( BOC Sciences , 259793-96-9 ) against BRBV-STL , mice were inoculated via the intraperitoneal route with 4 x 102 pfu and treated either immediately or 1 or 3 dpi with 150 mg/kg of favipiravir in 0 . 5% methylcellulose twice daily . Control animals received the same amount of 0 . 5% methylcellulose without the drug . Weight change and survival were monitored for 14 days after BRBV-STL infection . A type I IFN receptor blocking antibody , MAR1-5A3 ( Leinco Technologies , Inc . ) or isotype control ( 2 μg per mouse ) were administered to mice via intraperitoneal route prior to inoculation with BRBV-STL . RNA in situ hybridization for BRBV was applied to different organs of BRBV-STL infected WT and Ifnar1-/- mice . Three and six days after subcutaneous infection with 4 x 104 pfu of BRBV-STL , the liver , spleen , heart , brain , lung , and kidney were collected and fixed in 10% formalin for 7 days . Sections of each of these tissues were used for RNA-ISH ( ACDBio ) . Probes against segment 5 of BRBV-STL ( NP ) were developed by ACDBio and used according to the manufacturers’ recommendations . BRBV-STL positive cells were visualized with 3 , 3'-diaminobenzidine ( dark brown stain ) . Statistical analyses were performed using GraphPad Prism 8 . 0 software . Differences in mortality were determined using the log-rank ( Mantel-Cox ) test . Independent t-test with a Holm-Sidak correction for multiple comparisons was used determine statistical significance in weight loss 8 days after BRBV infection . A one-way ANOVA with a Dunnett correction for multiple comparisons was used to determine statistical significance of the effects of favipiravir on polymerase gene activity and cytotoxicity assay . The study was approved by the institutional review board of Washington University School of Medicine in St Louis . Written consent was obtained from the guardian of the patient . Animal experiments were approved and performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . The protocols were approved by the Institutional Animal Care and Use Committee at the Washington University School of Medicine ( Assurance number A3381-01 ) . | Bourbon virus ( BRBV ) is a novel tick-borne RNA virus that can cause fatal disease in humans . No approved antiviral treatment is available . We have cultured the second human isolate of BRBV and with it developed a small animal disease model . In this mouse model , BRBV causes severe disease as measured by weight loss after infection and uniform death 6 to 10 days after infection . Virus replication occurred predominantly in the spleen and the liver of the infected animals , with additional organs infected at later time points after infection . This disease model was used to test the efficacy of favipiravir , a viral RNA polymerase inhibitor that was developed for the related Influenza A virus . Prophylactic and therapeutic treatment with favipiravir resulted in complete protection from a lethal BRBV infection . These data suggest that favipiravir and perhaps other RNA polymerase inhibitors could be used to treat BRBV infections in humans . | [
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"model",... | 2019 | Therapeutic efficacy of favipiravir against Bourbon virus in mice |
A thermodynamic model of thermoregulatory huddling interactions between endotherms is developed . The model is presented as a Monte Carlo algorithm in which animals are iteratively exchanged between groups , with a probability of exchanging groups defined in terms of the temperature of the environment and the body temperatures of the animals . The temperature-dependent exchange of animals between groups is shown to reproduce a second-order critical phase transition , i . e . , a smooth switch to huddling when the environment gets colder , as measured in recent experiments . A peak in the rate at which group sizes change , referred to as pup flow , is predicted at the critical temperature of the phase transition , consistent with a thermodynamic description of huddling , and with a description of the huddle as a self-organising system . The model was subjected to a simple evolutionary procedure , by iteratively substituting the physiologies of individuals that fail to balance the costs of thermoregulation ( by huddling in groups ) with the costs of thermogenesis ( by contributing heat ) . The resulting tension between cooperative and competitive interactions was found to generate a phenomenon called self-organised criticality , as evidenced by the emergence of avalanches in fitness that propagate across many generations . The emergence of avalanches reveals how huddling can introduce correlations in fitness between individuals and thereby constrain evolutionary dynamics . Finally , a full agent-based model of huddling interactions is also shown to generate criticality when subjected to the same evolutionary pressures . The agent-based model is related to the Monte Carlo model in the way that a Vicsek model is related to an Ising model in statistical physics . Huddling therefore presents an opportunity to use thermodynamic theory to study an emergent adaptive animal behaviour . In more general terms , huddling is proposed as an ideal system for investigating the interaction between self-organisation and natural selection empirically .
In cold environments , huddling together is a ‘good trick’ that is exploited by many endothermic species in order to keep warm . Huddling in many species of mammals and birds has been described as a self-organising system [1–4] , whereby simple local interactions between individual animals collectively give rise to a complex group-level behaviour . The huddle constitutes an adaptive thermoregulatory system in which the interaction between self-organisation and natural selection , two forces that shape all biological systems , may be expressed in terms of a common ( metabolic ) currency . Here we investigate the interaction between self-organisation and selection by first developing a thermodynamic model of huddling , and then evolving the thermal physiologies of individuals in the model under pressure to thermoregulate at low individual metabolic cost . The model reveals how a balance between cooperative and competitive interactions between animals may constrain the dynamics of natural selection . Converging evidence suggests that thermogenesis plays a central role in balancing competition and cooperation in rodent litters . Non-shivering thermogenesis via brown adipose fat tissue ( BAT ) is functional in juvenile rats , and in the cold they huddle together . Rats seek cold when BAT is pharmaceutically increased [5] , and huddling ceases when BAT is pharmaceutically blocked [6] . Hamsters , who develop functional BAT later and do not normally huddle start to huddle when fostered into litters of rats . Thus heat generated by some individuals can trigger huddling in others [7] . Huddling patterns in rat litters can be understood by considering females ( who have more BAT ) as heat sources and males as heat sinks [8] . Computational modelling suggests that BAT-thermogenesis breaks symmetries between body temperatures in the group , which is necessary for the emergence of realistic huddling patterns [9] . The metabolic costs of BAT-thermogenesis to the individual may be offset by the thermoregulatory benefits of huddling to the group . In cold environments individuals must cooperate by contributing heat in order for the huddle to self-organise , but generating too much heat is energetically costly . The price for burning oxygen must ultimately be paid in the consumption of food , e . g . , the milk of the dam , and pressure to thermoregulate thus puts individuals in competition for food when energy resources are limited . Understanding the thermodynamics of huddling may shed light on how biological systems are shaped by the tension between cooperation and competition , and thus by the interaction between self-organisation and selection in more general terms . Thermoregulatory huddling behaviours displayed by litters of juvenile rodents give rise to what has been described as a second-order critical phase transition , i . e . , a continuous but abrupt decrease in the degree of aggregation as the temperature of the environment is increased [2] . In the language of thermodynamics ( i . e . , statistical physics [10] ) , a second-order critical phase transition ( henceforth simply a phase transition ) occurs only in systems whose component interactions express long-range correlations . In such terms the phase transition describes the change in the macrostate of a system of particles , for example the change that occurs when ice turns into water when it is heated . Analogously , the phase transition in rodent behaviours describes a change in state from a stable aggregation at low ambient temperatures ( huddling ) , to a dispersion of animals at higher temperatures . The classic system for investigating phase transitions is the Ising spin-glass model [10 , 11] , according to which magnetic spins arranged on a lattice dynamically re-orient , directed by the orientation of neighbouring spins . Differences in the relative orientations of neighbouring spins yield differences in ‘energy’ across the lattice , leading to dynamics that may either settle into a stable configuration in which spins remain continually aligned , or the states of the system may cycle a dynamic attractor . The attractor into which a particular system will settle is governed by the temperature of the system , which in theoretical formulations translates to the probability that the orientation of a given spin will be perturbed from its current alignment . At extreme temperatures , dynamics tend to stabilise , whereas at intermediate temperatures complex dynamics may persist . In spin-glass models , a phase transition reveals itself as a peak in the fluctuations of the total energy ( the heat capacity ) of the system , around what is described as its critical temperature . The peak in heat capacity is a defining feature of a phase transition . Rodent huddles display a group-level behaviour known as ‘pup flow’ , whereby individuals continually cycle between the cool periphery of the huddle and its warm core [12] . Huddling can be quantified in terms of the exposed surface area of the group , and pup flow can be quantified in terms of the rate of change of huddling . By these metrics , a recent self-organising model of rodent huddling predicts a peak in pup flow around the critical temperature of the phase transition [9] . If we assume that huddling corresponds to the energy in an Ising model , then pup flow reflects the heat capacity of the system , and hence a peak in pup flow is consistent with the predictions from classical thermodynamics . A thermodynamic description of a complex adaptive animal group behaviour in which metabolic cost can be defined explicitly , could open the door for a thermodynamic theory of the interaction between self-organisation and selection . To this end , in the following section we derive a description of self-organising thermoregulatory huddling in thermodynamic terms . Thermal physiologies in the model are then evolved under pressure to reduce metabolic cost , and the model is shown to display a phenomenon called self-organised criticality [13] . The emergence of criticality in the model suggests that a tension between competition and co-operation creates complex evolutionary dynamics that are stable across a wide range of thermal environments . Finally , application of the same evolutionary pressure to a full agent-based simulation of huddling [9] demonstrates that the evolutionary dynamics are maintained when physical interactions between animals in a closed arena are simulated explicitly , validating the thermodynamic description of huddling , and suggesting that criticality may be a more general property of evolving self-organising systems .
The approach here is to construct the simplest possible description of the huddle as a self-organising thermoregulatory system . The main criteria for a successful description of self-organising huddling are i ) that across a range of intermediate ambient temperatures , the average body temperature , computed over all individuals , should remain approximately constant at a preferred body temperature of 37°C , ii ) that a metric of huddling should display a second-order critical phase transition as the ambient temperature is manipulated , and iii ) that an appropriate metric of ‘pup flow’ should display a peak at the critical ambient temperature of the phase transition . The simplest model that can generate a second-order phase transition is known to be the Ising spin-glass model , and the dynamics of an Ising model can be simulated using a Monte Carlo algorithm ( see e . g . , [11] ) . Our aim here is therefore to develop a Monte Carlo algorithm whose behaviour satisfies the criteria for a successful huddling model , which is defined in terms that are directly interpretable as factors affecting rodent huddling interactions . The Monte Carlo algorithm presented here uses the standard method of Gibbs sampling , which is described next in terms of huddling interactions . The description of huddling is based only on a description of the litter in terms of the sizes of its component groups ( or ‘aggregons’ [4 , 14 , 15] ) , and abstracts the dynamics of real huddling , however it captures the idea that when two pups come into contact they will either stay in contact ( if doing so is energetically favourable ) , or one will avoid the other and so be displaced from its group . Central to the Gibbs sampling method is to determine the probability of making a decision between two outcomes . Consider the situation where two independent groups of aggregated individuals collide . As a result of a contact between two individuals ( from different groups ) , two outcomes are possible . Outcome 1 is that the individuals may remain in contact , and thus the two groups to which they belong will have merged together into one larger group . Outcome 2 is that an individual may become displaced from its group to form a new group of size 1 . Note that all other possibilities that might be observed , for example the possibility of both individuals becoming simultaneously displaced from their groups , of both individuals returning to their original pre-contact groups , or of one individual leaving its group and joining the other , are all possible as consequences of further iterations of the decision between outcomes 1 and 2 . Hence , our algorithm is based on iteratively deciding between outcomes 1 and 2 , and updating the sizes of the groups after each iteration accordingly . On each iteration , the probability of outcome 1 , p1 , is p 1 = 1 + e - T - 1 , ( 1 ) where T is referred to as the ‘temperature parameter’ . Outcome 1 is more likely to occur when the temperature parameter is higher . Gibbs sampling involves generating a random number from a uniform distribution r ∈ [0 , 1] , and on each iteration selecting outcome 1 if r < p1 and selecting outcome 2 otherwise . The probability of outcome 2 is therefore p2 = 1 − p1 . The algorithm of the huddling model proceeds as follows . Each of N individuals are assigned to a group . The number of individuals in a particular group is n . For individuals indexed by i ∈ [1 , N] , the number of individuals in the group to which individual i belongs is defined to be ni . On each iteration , two individuals , labelled a and b , are selected at random from two different groups . Accordingly , the probability that individual i is selected to be individual a is pa = ni/N , and for the remaining N − 1 individuals the probability of being selected as individual b is therefore pb = ni/ ( N − na ) . Note that individuals from larger groups are more likely to be selected . If r < p1 , then the groups to which a and b belong are joined together to create a single group of size na + nb ( outcome 1 ) , otherwise a is removed from its group to form a new group of size 1 ( outcome 2 ) . The temperature parameter T is defined in terms of the body temperature , TB , of individuals a and b , T = 2 T P - T B a - T B b , ( 2 ) where TP = 37°C is the preferred ( or target ) body temperature , and the factor 2 accounts for the combination of temperatures measured from two individuals . According to Eq 2 , the further the body temperatures in a group drop below the preferred body temperature , the more likely it is that the group will merge with another , which is consistent with our intuitions about the consequence of individual thermoregulatory huddling behaviours . The body temperature of each individual is computed using a well-established model of endothermy derived from Newton’s law of cooling [16–18]; T B i = T A + G i A i k 1 , ( 3 ) where TA is the ambient temperature , G is the rate of heat production by thermogenesis , A ∈ [0 , 1] is the proportion of the surface area that is exposed to the ambient temperature , and k1 is the area-specific wet thermal conductance . Note that the area-specific wet thermal conductance is dependent on many factors intrinsic and extrinsic to the body , including emittance , thermal conductivity , thickness of the fur , speed of the wind , viscosity and density of the air , and the geometry of the body [18 , 19] . This model captures the intuition that a highly exposed body that conducts heat more rapidly to a cold environment must generate more heat to maintain a high body temperature . Geometrical considerations and controlled experiments with small rodents [2 , 20 , 21] show that the average exposed surface area that can be achieved by individuals in a group decays exponentially with the size of the group n , according to A i = n i - 1 / 4 . ( 4 ) Note that the behaviour of the model developed here is not sensitive to other sensible choices of the exponent , e . g . , −1/3 . By combining Eqs 1–4 the Monte Carlo model can be summarised as follows . At each iteration of the algorithm the groups to which randomly chosen individuals a and b belong are joined together if r < 1 + e ( G a n a 1 / 4 + G b n b 1 / 4 ) / k 1 - 2 ( T P - T A ) - 1 , ( 5 ) else individual a is isolated to form a new group of size 1 . In the special case where the number of groups is 1 , p1 = 0 , and in the special case where the number of groups is N , p2 = 0 . Note that by this description of huddling , smaller groups are less likely to be selected to potentially join with other groups , but when selected they are ( in cold environments ) more likely to join with other groups . This tension underlies the dynamics of the model that are revealed in Fig 1 to satisfy our criteria for a successful description of self-organising thermoregulatory huddling interactions . All figures in this paper can be recreated using the source code available in the supplementary materials as S1 Code .
The Monte Carlo huddling algorithm was initialized with a single group of size n = N = 12 , and iterated for t = 5000 iterations . In independent simulations , the model was simulated through a range of ambient temperatures ( TA ∈ [0°C , 50°C] ) . For correspondence with later sections , individual rates of thermogenesis , G , were drawn at random from a uniform distribution , G ∈ [0 , 5] . For Fig 1 the parameter k1 was chosen to be k1 = 0 . 3 , which effectively sets the slope of the phase transition , and was found by experiment to provide a qualitative match to similar results derived from a related model [9] . The metric of huddling is defined to be h = 1 - 1 N ∑ i A i , which is shown in Fig 1 as an average over iterations , and the metric of pup flow was defined as the standard deviation of h over iterations . By this metric , pup flow approximates the heat capacity of the system . The model displays a second-order critical phase transition as the ( ambient ) temperature is manipulated , which is revealed in terms of both the average group size ( Fig 1A ) and the average exposed surface area ( Fig 1B ) , as well as a peak in heat capacity ( Fig 1C ) , which is a hallmark of a true phase transition . These are general thermodynamic properties that are inhereted from the Ising spin model from which the huddling model is derived . Confidence that the particular form of the model is a valid description of rodent huddling interactions , and thus confidence in the analogy between huddling pups and magnetic spins , comes from two observations . First , the temperature parameter T is represented here in terms of temperatures that describe factors that influence huddling , i . e . , a combination of body , ambient , and preferred temperatures . Second , Fig 1D shows that the average body temperature remains approximately constant around TP = 37°C over a range of intermediate ambient temperatures , i . e . , huddling aids thermoregulation . The huddling model is particularly interesting from a theoretical perspective because unlike in a particle system in which temperature is a parameter under influence only by factors external to the system ( e . g . , the temperature of a heat bath in which the system is assumed to be situated ) , temperatures in the huddling model are a property that is internal to the components of the system , i . e . , a property that may be influenced by the rate of thermogenesis of the individuals . Moreover , the system is interesting from a biological perspective if we assume that optimisation of the rate of thermogenesis , G , a key determinant of the body temperature , is under the influence of natural selection . The rate of heat production of an animal is directly related to its metabolic rate . Hence optimisation of G can be thought of as optimisation of the metabolic costs of thermoregulation . To investigate how huddling might interact with natural selection we may borrow from another influential model with origins in statistical physics , which has important implications for evolutionary theory , and allows us to capture the intuition that selection within the huddle constitutes a tension between co-operation and competition . The original model of sandpile formation by Bak and colleagues [22] explains self-organised criticality in the distribution of avalanche events that emerges when grains of sand are iteratively added to a pile . A hallmark of such critical systems is that they exhibit scale-invariance , as evidenced in the sandpile model by a power-law distribution in the sizes of avalanches . Bak and Sneppen later proposed a simpler model that exhibits criticality [23 , 24]; iteratively randomizing the fitness ( a number between zero and one ) of the least fit in a population , and simultaneously randomizing the fitnesses of two neighbours , generates avalanches in fitness whose distribution conforms to a power law . Power-law distributions found in complex systems varying from earthquakes to economics have been described in terms of such underlying dynamics [13] . Bak suggests that the underlying long-range correlations ( i . e . , as introduced by mutating also the neighbours of the least fit species ) may account also for punctuated equilibria; step-wise changes in complexity evidenced by fossil records . The implication of this idea is that fitness ( adaptation to the environment ) evolves by a natural selection driven primarily by mutation of the weakest , rather than by selection of the fittest per se . Simply put , if fitnesses are correlated , then a domino effect can emerge , such that removing the weakest individual has a knock-on effect for other inividuals whose fitnesses are higher due to interactions with the weakest . If co-operative huddling behaviours introduce long-range correlations in fitness between interacting rodents that depend on the exchange of thermal energy ( Fig 1 ) , and competition amongst rodents to metabolise at minimal energetic cost ( and thus contribute less heat ) is enforced by selection pressure operating on the weakest huddler , might the resulting tension between competition and competition also lead to self-organised criticality ? If so , huddling would represent an ideal biological system in which laws governing the interaction between self-organisation ( group-level huddling behaviours ) and natural selection ( for individually efficient metabolism ) might reveal themselves . The aim here is therefore to determine whether self-organised criticality might emerge from selection based on huddling efficiency . By direct analogy with the model of Bak and Sneppen [23] , our approach is to iteratively substitute the weakest individual in the simulation for another with a random thermal physiology . Crucially , we will substitute only one individual per generation , such that any evidence that long-range correlations in the huddling model influence the evolution of the group must be attributable to couplings in thermal physiology that are expressed through self-organising huddling interactions . To this end , we next subject the model to a simple evolutionary procedure , starting with the following definition of fitness; F i = - T B ¯ i - T P + α G i , ( 6 ) where T B ¯ i is the average body temperature over time . According to the first term in the brackets of Eq 6 , an individual is considered to be better adapted to its thermal environment if it maintains an average body temperature that is closer to the preferred temperature . This term corresponds to the cost of poor thermoregulation , and is influenced by huddling interactions . According to the second term , an individual is considered to be fitter if it has a lower metabolic rate . This term corresponds to the cost of thermogenesis , and is not influenced by huddling interactions . The constant α is a free parameter that is introduced to allow the relative costs of thermoregulation and thermogenesis to be balanced . Thus α can be tuned to place the evolving system in a regime where the costs of thermoregulation and thermogenesis are comparable . By experimentation , a value α = 6 . 06 was chosen as the smallest value that stops metabolic rates evolving immediately towards G = 0 . Note that the appropriate value of α depends on the choice of the thermal conductance k1 and the size of the group N , but importantly once k1 , N , and α are set , the resulting evolutionary dynamics are robust to variations in the control parameter of interest , TA , as explained shortly . On each of 10 , 000 generations of the evolutionary algorithm , the thermodynamic huddling model was simulated through t = 1000 iterations , the average fitness F was computed for each individual at each generation , and the individual with the lowest fitness was replaced in the next generation by an individual with a metabolic rate drawn randomly from a uniform dstribution G ∈ [0 , 5] . The validity of this evolutionary procedure is considered in full in Discussion . However , note that this algorithm effectively poses the following question of the system; what configuration of metabolic rates in the group is optimal when selection pressure on individual physiological thermoregulation ( pressure to reduce G ) is balanced with pressure on behavioural thermoregulation ( pressure to reduce |TB − TP| ) ? Evolution of the distribution of thermal physiologies in the group resulted in extended periods of stasis , sometimes lasting for hundreds of generations , in which the metabolic rates of all in the group remained at constant low values . However , these periods of stasis were interrupted by prolonged bursts in which the fitnesses of several in the group suddenly reached significantly lower values before returning to stasis . In deference to descriptions of self-organised criticality in models of sandpile formation [13] , these sudden transitions are referred to as the onsets of new avalanches . To understand this observation , it is useful to inspect the interaction between the weakest group member , i . e . , the individual that will be replaced in the next generation , and the individual from the remainder of the group that has the highest metabolism , i . e . , that which we might expect to be the second-weakest individual . The emergence and evolution of a representative avalanche is shown in Fig 2 , in terms of the interaction between the metabolic rates of these two individuals at each generation . Fig 2 reveals that the onset of an avalanche occurs when the least fit is substituted for another with a random metabolic rate whose extra heat renders it an attractive target for huddling to the rest of the group . During the period of stasis prior to an avalanche , the metabolic rates of the group are maintained at low values because the fitness function penalises high values of G . The individual with the highest metabolic rate is likely to consistently be the least fit , and hence during periods of stasis the metabolic rate of the least fit varies randomly because it is randomly substituted . However in the generation at which an avalanche is triggered , the random metabolic rate of the individual that has been substituted into the group was observed to be higher than that of the individual subsequently evaluated to be the least fit . This means that the new individual is fitter not because it has a lower metabolic rate , but because it benefits more than the least fit from compensatory savings in thermoregulation . The high metabolic rate G of the new individual is compensated for a small |TB − TP| , which must occur due to effective huddling interactions with the rest of the group . At the onset of an avalanche , the individual that will be replaced in the next generation is therefore not the individual that is contributing the most heat to the group by thermogenesis , hence the total heat available to the group in the next generation increases . In general , the fitness function penalises high metabolic rates and thus the heat from individual thermogenesis tends to reduce as the system evolves , but at the onset of an avalanche the total heat is instead transiently increased . Thus the evolving configuration of the group becomes critically stable , such that the total heat in the group gradually reduces until the overall reduction of heat triggers the next avalanche . To reveal how the critically stable dynamics revealed by inspection of a single avalanche unfold over the full evolutionary history , Fig 3 shows the distribution of avalanche events across all 10000 generations . Fig 3A shows the full distribution of fitnesses , F , at each generation for all individuals except for the least fit , which as we have seen in Fig 2 has an essentially random distribution that would otherwise mask the interesting group dynamics . Fig 3A confirms that long periods of stasis in fitness are punctuated by avalanches that persist for several generations and involve multiple group members . This example simulation was run at an ambient temperature of TA = 10°C , hence we expect pressure to reduce G towards 0 to maintain fitnesses at around |TA − TP| = −27 ( by assuming TB = TA ) . Values of F that exceed this baseline indicate where huddling interactions have increased the body temperature and values below the baseline indicate where additional costs of sustaining a high metabolic rate have been incurred . Fig 3B shows the metabolic rate of the second-least fit individual at each generation , which is referred to as Gmin , and the close temporal correspondence between Fig 3A and 3B confirms that the avalanches in fitness are caused by transient increases in Gmin , by the mechanism explained in relation to Fig 2 . A number of avalanches are shown in greater detail in Fig 3C . A histogram of the distribution of metabolic rates in the second least fit , H ( Gmin ) , reveals a fall-off in frequency indicative of a power-law distribution . A fitted curve obtained by linear regression of the histogram after a log-log transformation , i . e . , a fit to the model log H ( Gmin ) = m log Gmin + c , is shown in Fig 3D , which reveals a good fit to a negative power-law relationship . Hence the distribution conforms to H ( G min ) = e m G min + c . A power-law relationship is a strong indicator of self-organised criticality , ( see e . g . , [13] ) . A second hallmark of self-organised criticality is that the emergence of the power law distribution is robust to manipulation of the external influences on the system . The external thermal environment of the huddling model is represented by the ambient temperature TA , hence obtaining a power law fit to the distribution of metabolic rates from simulations conducted through a range of ambient temperatures would be stronger evidence of self-organised criticality . Twenty-four evolutionary simulations were run , each at a constant ambient temperature Ta ∈ [0°C , 50°C] . For all simulations at TA < TP , where huddling is expected to improve fitness , the distribution conformed well to a power-law model . The exponent m of the power-law fit obtained at each ambient temperature is shown in Fig 4 . This plot confirms that m remains approximately constant over a wide range of lower ambient temperatures , and the steepness of the curve increases as the ambient temperature approaches 37°C . The emergence of self-organised criticality in the thermodynamic huddling model reveals how the tension between cooperative and competitive interactions in animal groups may constrain evolutionary dynamics . Next we ask whether the effects are a specific feature of the abstract thermodynamic description of huddling developed here , or whether self-organised criticality might also emerge in the evolution of a physically realisable model of self-organising huddling behaviours , i . e . , one that describes also the movements of the individuals . The thermodynamic model of huddling was developed on the basis of an analogy between interacting rodents and the magnetic spins of an Ising model . In an Ising model , spins are fixed in position on a lattice . However , the characteristic thermodynamics of Ising models are preserved in what is known as a Vicsek model [25] . A Vicsek model is a system of continually moving particles whose directions of travel are affected by the directions of proximal particles [25–27] . The Vicsek model provides a theoretical bridge between the thermodynamics of stationary spins and of moving particles , and has successfully been applied to explain the emergent properties of self-organising flocking behaviours of animals interacting in large groups , where the trajectories of individuals ( e . g . , flocking birds or shoaling fish ) are influenced by the trajectories of nearby animals [28 , 29] ( see [30] for a review ) . A Vicsek model is formulated as an agent-based simulation in which each individual particle moves according to d x i d t = v 1 cos θ i ( t ) sin θ i ( t ) , ( 7 ) where x is the 2D position of the individual , v1 is its velocity , and θ ( t ) is its direction of travel at time t . The change in the direction of travel is a function of its interactions with proximal particles . A recent agent-based model of rodent thermoregulatory huddling describes the huddle as a self-organising system , generating a second-order phase transition in huddling and a peak in pup flow at the critical temperature [9] . Interestingly , this model can be formulated as a Vicsek model , where dθ/dt is a function of the difference between the body temperature and the preferred temperature . According to the model of [9] , rat pups are simulated as circles that move continually forwards in a two-dimensional arena with a circular boundary . The orientations and body temperatures of the simulated pups are continually updated so that they move to minimise the discrepancy between the current body temperature and a preferred temperature , and when they make contact they exchange body heat . According to the agent-based huddling model , pups turn using a strategy of ‘homeothermotaxis’ , defined as follows . The temperature on the left and right of the body , TLi and TRi , are computed by averaging over many thermal sensors around its circumference , each registering either the ambient temperature or the body temperature of another pup where a contact occurs . The resulting temperatures are mapped to two ‘sensor’ values that incorporate the difference between the preferred temperature and the body temperature , sLi = ( 1 + exp ( −σ ( TP − TBi ) TLi ) ) −1 and sRi = ( 1 + exp ( −σ ( TP − TBi ) TRi ) ) −1 , which are combined so as to turn the body in the direction that will reduce this difference , d θ i d t = arctan v 2 ( s L i - s R i ) / ( s L i + s R i ) , ( 8 ) where v2 sets the turning rate . The body temperature of pup i changes according to d T B i d t = G i - k 1 A i ( T A - T B i ) - k 2 ( 1 - A i ) ( T B i - T C i ) , ( 9 ) where TCi is the average temperature of the thermal sensors of pup i that are in contact with other pups ( who are thus reducing its exposed area ) . The parameter k2 is another thermal conductance constant , which determines the rate at which heat is exchanged between pups that are in contact . The three terms on the right of Eq 9 correspond to i ) thermogenesis , ii ) heat exchange with the environment , and iii ) heat exchange between contacting individuals , respectively . It is important to note that when A = 1 , i . e . , when an individual is isolated and therefore fully exposed , the solution of Eq 9 corresponds exactly to the earlier Eq 3 , hence the underlying physiological assumptions of the thermodynamic model and the agent-based model are consistent . Fig 5 shows that as the ambient temperature varies the metrics of huddling obtained from simulation of the full agent-based model vary in the same way as the corresponding metrics derived from the thermodynamic model ( c . f . , Figs 5 and 1 ) . Given the relationship between the Ising and Vicsek models of particle interactions , and the assumption that our model of rodent huddling is correspondingly related to the model of [9] , we ask here whether the full agent-based huddling model of [9] will also display criticality when subjected to the same evolutionary pressure . The results presented in Fig 5 were obtained by setting the values of G , k1 , and k2 to values in the range investigated originally by [9] . However , the purpose of evolving the agent-based model here is to establish whether self-organised criticality is a robust phenomenon in simulations of a more plausible huddling model , in which the full range of interactions between thermal physiologies in the group are under the influence of self-organisation and selection . Therefore to allow the evolutionary algorithm to freely explore the space in which self-organisation and selection might interact , the agent-based model was evolved by substituting the least fit individual for another with a random metabolic rate and a random thermal conductivity . The overall thermal conductivity is determined by the ratio between k1 and k2 , hence we chose to fix k1 = 1 and allow the evolutionary algorithm to additionally explore k2 ∈ [0 , 5] . The dynamics of the agent-based huddling model were simulated for t = 1000 timesteps , and the fitness of each pup was again computed using Eq 6 . The thermal physiology of the least fit was substituted at each of 10 , 000 generations , for an individual with a random metabolic rate G ∈ [0 , 5] and a random thermal conductivity determined by k2 ∈ [0 , 5] . Results are shown in Fig 6 , for TA = 10°C and α = 3 . 0 . Evolution of the full agent-based huddling model again generated avalanches in fitness ( Fig 6A ) , whose onset corresponded to peaks in the metabolic rate of the second-weakest individual ( Fig 6B and 6C ) , with a distribution that conformed to a power-law model ( Fig 6D ) . The dynamic exchange of heat via huddling interactions manifests as greater variability in the distribution of heat amongst the group in the full agent-based model compared with the thermodynamic model . Moreover , as rapid exchange of heat can occur between individuals with a high conductivity k2 , the group are collectively able to generate higher body temperatures during huddling interactions . As a result , when substitution of a random thermal physiology into the group triggers an avalanche , the fitnesses of those who benefit from huddling with it can be seen to spread out above the baseline fitness in Fig 6A . Although the consequences of an avalanche for the fittest are more pronounced in the agent-based model , close inspection of the interactions between the least fit and the second-least fit revealed that the mechanism by which an avalanche is triggered and propagates through the group is the same as for the thermodynamic model , i . e . , individuals generating more heat become increasingly attractive targets for huddling as metabolic rates in the rest of the group are reduced under selection pressure . Fig 7 confirms that the power law is a good model for the evolutionary dynamics at ambient temperatures TA < TP , and that the exponent of the fitted curve is stable across a wide range of lower ambient temperatures .
A thermodynamic description of rodent huddling behaviours was developed here , according to which the thermoregulatory properties of the huddle can be understood in terms of a second-order phase transition , as it is defined and studied in statistical physics . In particular , the model equates the phenomenon of pup flow observed in rodent huddles with fluctuations in the heat capacity of a particle system , and as such predicts that a peak in pup flow should occur at the critical temperature of the phase transition between huddling at low temperatures and non-huddling at higher temperatures . If this prediction cannot be confirmed in future experiments , then the thermodynamic model developed here is wrong , and the onset of self-organising huddling behaviours at low ambient temperatures is not evidence of a true second-order phase transition . To investigate how tensions between co-operation and competition within animal groups may influence natural selection , the thermodynamic huddling model was subjected to a simple evolutionary procedure . Simulations revealed that individual thermal physiologies interacting via huddling may together be maintained in a regime of self-organised criticality . In simulation , optimisation of metabolic rates to exploit the metabolic savings of huddling leads to an ultimately unstable set of thermal couplings within the group . Evolved over a wide range of low environment temperatures , these instabilities manifest as a distribution of low metabolic rates that remain stable for long evolutionary periods , but which are periodically interrupted by abrupt decreases in fitness that affect all group members . When huddling interactions were instead represented with a full agent-based simulation of huddling interactions , essentially the same evolutionary dynamics were found to emerge , suggesting that criticality is a robust feature of the evolutionary algorithm , when either model of huddling is used to introduce long-range correlations in fittness between individuals . The present results indicate that under pressure to reduce individual metabolic costs , exploiting interactions with the group causes individuals to become critically dependent upon the group . We often think of evolution as a gradual ascent of a genome towards peak fitness , but the present simulations show how long-range correlations in phenotypic fitness due to interactions within animal groups can carve deep cliffs into a fitness landscape ( see also [31] ) . It is important to acknowledge that the evolutionary procedure implemented here was not expressed in terms of a genetic algorithm , and as such it is abstract with respect to a full population-based account of the exchange of genetic information between generations . By simply replacing the weakest thermal physiology for a random physiology , many generations of agent-based huddling interactions could be simulated efficiently . More importantly , this abstraction expresses in its simplest form how the tension between co-operation and competition in the huddle might impact on natural selection . Substituting one random thermal physiology into the huddle at a time enables the emergence of criticality to be attributed here directly to huddling interactions , rather than to additional correlations introduced if deriving physiologies genetically , i . e . , by recombination . This procedure also allows the emergence of criticality in the model to be understood in terms of explanations for criticality in similarly formulated models of complexity ( e . g . , [23] ) . With these considerations in mind , the following discussion identifies some mechanisms by which social and physiological thermoregulation may allow self-organisation and natural selection to interact in endothermic species that huddle . For endotherms , the benefits of huddling are afforded only by groups in which individuals contribute heat , i . e . , by thermogenesis . For example juvenile hamsters , who develop non-shivering thermogenesis late relative to rats and do not huddle [32] , will actively huddle when fostered into litters of rat pups , causing a reduction in metabolic expenditure that benefits all [7] . However , individual differences in rates of thermogenesis lead to differences in themoregulatory efficiency , and the huddle is therefore also a competition . For example male rats , who contribute less heat to the group than females , expend more energy during huddling behaviours to retain the extra heat generated by females [8] . Thermoregulatory huddling is thus a combination of selfless and selfish interactions , with differences in individual thermal physiology underpinning differences in the genetic investment of the individual in the success of the group [33 , 34] . Contributing too little heat does not yield the benefits of huddling , but contributing too much heat incurrs the costs of sustaining a high metabolism . The reward for getting it ‘just right’ is increased weight gain . Efficient thermoregulation is important for growth and ultimately for survival . For example , growth rates in developing mice vary markedly with manipulations of the environment temperature [35] , and differences in growth rates due to manipulation of body temperature are correlated with survival rates [36] . In cold environments , increases in group size lead to reductions in oxygen consumption [21 , 37] , and survival times double when mice are housed in pairs [38] . Huddling in groups effectively insulates the pups , promoting survival into adulthood by allowing the energy that would otherwise be lost to non-shivering thermogenesis to be allocated instead to growth [39] . Heavier pups outcompete lighter littermates in the ‘scramble’ for the milk of the mother [40 , 41] . Under cold challenge , heavier pups , which tend to occupy the thermally advantageous center of the huddle , in turn sustain lower metabolic rates , obtain more milk from the mother , and are more efficient at converting the extra calories into body mass [42 , 43] . The net effect for heavier pups is short-term gains in terms of survival rate , and long-term gains in terms of reproductive fitness [44] . The evolutionary algorithm used in the present simulations ( substituting the ‘runt’ of the litter ) similarly captures the competition within a co-operating group for shared energy resources , i . e . , food , against which metabolic efficiency is ultimately measured . Evolutionary dynamics are doubtless strongly governed by absolute fitness; if an animal is too cold it will die before it reproduces . However , within a group , the animal needing the most energy to stay warm relative to the others will lose out in the competition for shared energy resources . The critical challenge within a litter may therefore be simply to ‘out-thermoregulate’ the runt of the litter . For rats and mice , a direct selection pressure acting on the runt of the litter may derive from the tendency of the dam to eat the runt , particularly in cold environments ( e . g . , [35] ) . Cohabitation of successive litters , which occurs commonly in the wild due to mating at postpartum estrus , may also introduce direct competition between generations via huddling interactions [45] . These considerations suggest that applying selection pressure directly to the weakest group member , which is the key to self-organised criticality in theoretical formulations [23] , captures an important component of natural selection in groups of endotherms . In more abstract terms , the model developed here is similar in spirit to the seminal model of self-organised criticality presented by Bak and colleagues [23 , 24] , which shows that even iterative random mutation of the lowest fitness value and its immediate ‘neighbours’ on a circular vector gives rise to self-organised criticality . On one hand , the present model behaves as an elaborate version of this model . As such , the weakest interpretation of the present result is that social thermoregulation , as described by either the thermodynamic model or the agent-based huddling model of [9] , is sufficient to establish long-range correlations in metabolic efficiency between littermates with ‘neighbouring’ ( i . e . , coupled ) thermal physiologies , comparable with those underpinning criticality in the model of [23] . This conclusion does not depend on the ecological validity of the simulated evolutionary process . On the other hand , a stronger interpretation is that in addition to its immediate influence on individual fitness , thermoregulatory huddling may serve to constrain the dynamics of natural selection , to help maintain the thermal physiologies of animals that interact in groups in a self-organised critical attractor . The modelling approach here is necessarily limited to consideration of only the immediate metabolic costs and benefits of huddling in terms of thermoregulation , but secondary benefits of social thermoregulation may exert a strong influence on natural selection too . For example , pups reared in groups develop improved motor co-ordination [46] , and score higher as adults on indices of emotionality [45 , 47] and personality [48 , 49] compared to pups reared in isolation . Interestingly , lighter pups that tend to occupy the periphery of the huddle have been shown to develop increased pro-social behaviours as adults [50] . Hence at the level of the social group it may be considered favourable to maintain litters as a heterogeneous mixture of heat sources and heat sinks , to establish in the early physiological differences in the litter , a template for the emergence of complementary differences in adult social behaviour [12] . Along similar lines , if sustaining pup flow dynamics provides all littermates with comparable developmental experiences , such that peripheral versus central huddling experiences are shared equally amongst the group , then a selection pressure to match the critical temperature of the huddling phase transition to the typical environment temperature encountered by the species could conceivably emerge . Under such pressure we might observe an auto-tuning of the critical temperature ( by redistributing thermal physiologies amongst the group ) . Auto-tuning of the critical temperature at which dynamic group interactions persist would constitute an ‘evolution towards the edge of chaos’ , of the kind pursued by the theoretical biologist Stuart Kauffman through his study of random boolean networks [51] . Further study of the interaction between self-organisation and selection , using the language of statistical physics and through the empirical lens of thermoregulatory huddling behaviour , might allow abstract theoretical models of this nature to be investigated empirically . | Huddling is an adaptive behavior that emerges from simple interactions between animals . Huddling is a particularly important self-organising system because the behavior that emerges at the level of the group directly impacts the fitness of the individual . The huddle insulates the group , allowing pups to thermoregulate at a reduced metabolic cost , however a huddle can only self-organise if pups in turn contribute heat . Contributing too much heat is costly but contributing too little compromises the ability of the huddle to self-organise . To investigate how the resulting tension between co-operation and competition in the huddle might affect natural selection , litters of simulated rodents were subjected to a simple evolutionary process . After interacting with its littermates , the individual that incurred the greatest metabolic cost for thermoregulation was iteratively replaced by another with random thermal properties . Simulations resulted in the emergence of a phenomenon called self-organised criticality . Criticality is a hallmark of complex systems , and is evidenced here by the emergence of a power-law distribution of thermal properties in the evolving composition of the group . The model therefore reveals how complexity can emerge in a well-defined biological system ( thermoregulation ) , where experiments can be designed to investigate the interaction between self-organisation and natural selection . | [
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"thermodynamics... | 2017 | Self-organised criticality in the evolution of a thermodynamic model of rodent thermoregulatory huddling |
The host factor and interferon ( IFN ) -stimulated gene ( ISG ) product , zinc-finger antiviral protein ( ZAP ) , inhibits a number of diverse viruses by usurping and intersecting with multiple cellular pathways . To elucidate its antiviral mechanism , we perform a loss-of-function genome-wide RNAi screen to identify cellular cofactors required for ZAP antiviral activity against the prototype alphavirus , Sindbis virus ( SINV ) . In order to exclude off-target effects , we carry out stringent confirmatory assays to verify the top hits . Important ZAP-liaising partners identified include proteins involved in membrane ion permeability , type I IFN signaling , and post-translational protein modification . The factor contributing most to the antiviral function of ZAP is TRIM25 , an E3 ubiquitin and ISG15 ligase . We demonstrate here that TRIM25 interacts with ZAP through the SPRY domain , and TRIM25 mutants lacking the RING or coiled coil domain fail to stimulate ZAP’s antiviral activity , suggesting that both TRIM25 ligase activity and its ability to form oligomers are critical for its cofactor function . TRIM25 increases the modification of both the short and long ZAP isoforms by K48- and K63-linked polyubiquitin , although ubiquitination of ZAP does not directly affect its antiviral activity . However , TRIM25 is critical for ZAP’s ability to inhibit translation of the incoming SINV genome . Taken together , these data uncover TRIM25 as a bona fide ZAP cofactor that leads to increased ZAP modification enhancing its translational inhibition activity .
The recent re-emergence and spread of viruses beyond their normal geographic distribution have affected countries worldwide . Understanding the biology of host factors with broad antiviral activity is crucial to vaccine and drug development efforts to counteract existing and emerging viral infections . As a first line of defense against viruses , the host produces type I interferons ( IFNs ) , which signal through the JAK/STAT pathway to induce hundreds of IFN-stimulated genes ( ISGs ) that block various steps of the viral life cycle ( reviewed in [1] ) . Among the ISGs , zinc finger antiviral protein ( ZAP ) , encoded by the ZC3HAV1 gene , inhibits alphaviruses , filoviruses , hepatitis B virus , retroviruses , and the LINE-1 and Alu retroelements [2–8] . However , ZAP does not inhibit yellow fever virus , vesicular stomatitis virus , and herpes simplex virus 1 ( HSV-1 ) [3] . It is not well understood what determines the broad yet specific antiviral activity of ZAP . ZAP , also called PARP13 , is a member of the poly ( ADP-ribose ) polymerase ( PARP ) family and is alternatively spliced . The long isoform of ZAP ( ZAPL ) contains a PARP-like domain on the C-terminus that is missing in the short isoform ( ZAPS ) . This PARP-like domain is not enzymatically active [9] , although exchange of the inactive catalytic triad in ZAPL to that of the active PARPs completely abolishes its antiviral activity [10] , suggesting an important yet unknown role of the PARP-like domain in the antiviral function of ZAP . Several studies have demonstrated distinct activities for the two isoforms . ZAPL is more active against alphaviruses , such as SINV and Semliki Forest virus , than ZAPS , and carries signatures of positive selection [11 , 12] . While both isoforms are induced by IFN , ZAPS is upregulated more than ZAPL by virus infection and type I IFN [5 , 13 , 14] . Diverse cellular pathways have been implicated in ZAP’s function ( reviewed in [15] ) , but its precise mechanism is unknown . It is possible that ZAP interacts with multiple host factors , and the involvement of those factors in the viral life cycle is what provides the specificity . For example , ZAP binds RNA and recruits the exosome complex to target viral RNAs for degradation [5–7 , 16–18] . ZAP also directly inhibits translation of the incoming alphaviral genome [3] , with interference in the interaction between eIF4A and eIF4G [19] implicated as one mechanism . In addition , ZAP synergizes with other ISGs for its maximal activity and upregulates RIG-I-mediated IFN-β production [14 , 20] . These studies support a model in which ZAP interacts with various host factors and cellular complexes to achieve an optimal antiviral state against diverse viruses . In an attempt to unify the divergent pathways in which ZAP is involved and to uncover novel cofactors that are important for ZAP’s inhibitory activity , we performed a genome-wide siRNA screen in a cell line inducible for ZAP expression . Large-scale RNAi screens allow us to take an unbiased approach to interrogate every gene in the genome . However , off-target effects lead to false positive hits and severely limit the value of genome-wide screens [21 , 22] . To address this we performed a rigorous set of confirmatory assays to verify the top hits and exclude off-target effects . We identified several genes that synergize with ZAP to target SINV or inhibit SINV independently of ZAP . Among the hits , TRIM25 was validated to be a cofactor of ZAP . TRIM25 is an E3 ubiquitin and ISG15 ligase , and is responsible for the polyubiquitination and activation of RIG-I [23–25] . We generated CRISPR clones in ZC3HAV1-knockout 293T cells where TRIM25 expression is significantly reduced and further confirmed that TRIM25 synergizes with both ZAPS and ZAPL to block SINV replication . Our data demonstrates that TRIM25 triggers ubiquitination of ZAP and enhances its antiviral activity through inhibition of viral translation , highlighting the importance of cofactors in the mechanisms of broadly antiviral proteins .
We performed a genome-wide screen with pooled siRNAs from Dharmacon to identify genes that are required for ZAP’s antiviral activity ( see Fig 1A for screen workflow ) . Viral replication is low in T-REx-hZAP cells when ZAP expression is induced , and silencing of ZC3HAV1 increases replication of a luciferase-encoding SINV , Toto1101/Luc , by 2 logs . The premise of the screen is as follows: should knockdown of an essential cofactor render ZAP nonfunctional , viral replication will be restored , resulting in increased luciferase activity ( refer to “ZAP cofactor siRNA” column in Fig 1A ) . The screen was performed in triplicate to improve robustness , and we identified 480 genes , whose silencing significantly elevated SINV Toto1101/Luc replication with an average robust Z score of >3 ( Fig 1B ) . As expected , ZC3HAV1 was the top hit with an average robust Z score of 582 . 65; this was followed by BAI3 ( 165 . 56 ) , TRIM25 ( 116 . 52 ) and RICS ( 100 . 42 ) ( see S1 Table for the entire results ) . Normalized percent activation ( NPA ) and robust Z score were utilized for hit selection [26] . The genes with the highest NPA and robust Z score >3 in all three replicate wells were chosen for validation in a secondary screen ( 91 genes ) . Since siRNAs can act as microRNAs and target genes non-specifically through their seed sequences [27] , we included 4 genes that were potential off-target candidates from Haystack analysis ( PDIK1L , SNAP25 , FOXK1 , DGAT2L3 ) . In addition , we included 1 gene based on overlap with ISGs that we previously found as synergistic with ZAP in an overexpression screen ( MAP3K14; [20] ) , and 6 genes from pathways that were significantly enriched but were not on the top 91 list ( APC , FZD2 , GFRA1 , JAK1 , SP1 , and WNT8B ) . We re-screened the candidate genes with a library of single siRNAs obtained from a different company ( Ambion ) to exclude hits that are mediated by off-target effects from further characterization . Knockdown of 5 genes by 6 . 25 nM siRNA ( Fig 2A ) and knockdown of 13 genes by 25 nM siRNA ( Fig 2B ) significantly increased SINV Toto1101/Luc replication ( see S2 Table for the entire results ) . Among them , ZC3HAV1 was identified as the top hit . TRIM25 , KCNH5 , GCS1 and JAK1 were also hits at both siRNA concentrations . In addition to the T-REx-hZAP cells used for the primary screen , a 293 clone that is inducible for the expression of rat ZAP C88R mutant , a dominant negative inhibitor of ZAP function [28] , was also tested in parallel . Since endogenously expressed ZAP is antiviral , this cell line inhibited for ZAP function allowed us to identify hits with a ZAP-independent antiviral role . Silencing of GCS1 and GPRC5D by 6 . 25 nM ( Fig 2C ) and 25 nM ( Fig 2D ) siRNAs significantly increased SINV Toto1101/Luc replication in these cells where ZAP is not functional ( see S2 Table for the entire results ) , suggesting that they might inhibit SINV in a ZAP-independent manner . Next , we validated the candidate ZAP cofactors in a lower throughput assay . Silencing of TRIM25 , KCNH5 , JAK1 , and ZC3HAV1 led to increased virus replication for at least 2 of the 3 siRNAs ( Fig 3A ) , which was consistent with reduced protein levels of TRIM25 ( S1A Fig ) and ZAP ( S1B Fig ) , and reduced mRNA levels of KCNH5 and JAK1 ( S1C Fig ) . Among the candidates , 3 independent siRNAs targeting TRIM25 significantly increased SINV Toto1101/Luc replication by 10- to 26-fold compared to the NT control ( Fig 3A ) . Since TRIM25-targeting siRNA #3 was most efficient at rescuing SINV Toto1101/Luc replication , we designed and tested an additional C911 control . The 9th to 11th nucleotides of the siRNA were mutated to their complementary sequence , hence the designation C911 , to rule out the possibility that the knockdown phenotype was due to the off-target effects of the siRNA [29 , 30] . The C911 control should lose its siRNA activity but still maintain its off-target effects as a microRNA . While TRIM25-targeting siRNA #3 rescued SINV Toto1101/Luc replication by about 1 log compared to the NT control , #3-C911 did not lead to increased viral replication and did not reduce the protein level of TRIM25 ( Fig 3B ) , suggesting that the phenotype of siRNA #3 is due to specific silencing of TRIM25 and not inhibition of an off-target gene . Furthermore , TRIM25 was silenced in ZC3HAV1-knockout 293T cells [14] , which were then infected by SINV Toto1101/Luc to determine whether endogenously expressed TRIM25 has a ZAP-independent antiviral role . As controls , ZC3HAV1 and TRIM25 were silenced in 293T cells . While ZC3HAV1 ( Fig 3C; left ) and TRIM25 ( Fig 3C; middle ) silencing in 293T cells restored SINV Toto1101/Luc replication by 1–3 logs by 40 h p . i . , silencing of TRIM25 in ZC3HAV1-knockout cells did not further increase SINV Toto1101/Luc replication compared to the NT control ( Fig 3C; right ) . These data suggest that TRIM25 requires ZAP for its anti-SINV activity . Next , we asked whether TRIM25 physically interacts with ZAP . We infected 293T with endogenous TRIM25 and ZAP expression with SINV , and immunoprecipitated TRIM25 to look for ZAP association at various time points following infection . We found that endogenous ZAP co-immunoprecipitated with endogenous TRIM25 over the course of SINV infection ( Fig 4A ) . There were less TRIM25 and ZAP proteins present at 24 h p . i . , which is consistent with the cytopathic effects observed at that time point , leading to less TRIM25 and ZAP pulldown . Previously , TRIM25 was found to interact with ZAP in the presence of RNA although only ZAPL was investigated [8] . To determine the interaction of TRIM25 and different ZAP isoforms , ZAPS or ZAPL , and/or TRIM25 were co-expressed in ZC3HAV1-knockout 293T cells , which were harvested for co-immunoprecipitation . Immunoprecipitation of both ZAPS and ZAPL by a monoclonal antibody recognizing the N-terminal portion of human ZAP ( NZAP ) pulled down TRIM25 , although more TRIM25 is associated with ZAPL ( Fig 4B ) . TRIM25 was dramatically modified in the presence of ZAPS , evident by the presence in the whole cell lysates ( WCL ) of a ladder of bands larger than the molecular weight of TRIM25 ( Fig 4B; WCL ) . TRIM25 consists of a RING domain , two B box domains , a coiled coil ( CCD ) domain , and a SPRY domain . The RING domain encodes the ubiquitin ligase activity while the CCD domain is required for oligomerization of TRIM proteins and the SPRY domain is important for mediating protein interactions and substrate specificity [31] . Next , we asked which domain in TRIM25 was responsible for interaction with ZAP . Since more ZAPL associates with TRIM25 , we co-expressed similar levels of individual TRIM25 domains with ZAPL and immunoprecipitated ZAPL . We found that the SPRY domain of TRIM25 but not its RING and B box/CCD domains co-immunoprecipitated with ZAPL ( Fig 4C ) . These data suggest that both ZAP isoforms form a complex with TRIM25 , likely through interaction with the SPRY domain of TRIM25 . Since TRIM25 is an E3 ubiquitin ligase and has been shown to be important for ubiquitinating RIG-I and upregulating RIG-I-mediated IFN-β production , we hypothesized that TRIM25 also ubiquitinates ZAP and/or other proteins that complex with ZAP in order to stimulate ZAP’s antiviral activity . To test this , we targeted TRIM25 by CRISPR in ZC3HAV1-knockout 293T cells to interrogate the functional interaction between ZAP isoforms and TRIM25 . CRISPR targeting led to either in-frame deletions in all three chromosomal copies of TRIM25 ( clone D ) or frameshift insertions in two chromosomal copies and an in-frame deletion in one ( clone F ) , consistent with the almost undetectable protein expression of TRIM25 ( S2 Fig ) . Clones D and F are designated TRIM25lo . Clone E is wild type and has similar TRIM25 protein expression as the parental ZC3HAV1-knockout 293T cells ( S2 Fig ) . Both TRIM25lo clones ( D and F ) were tested in the subsequent experiments and showed similar results . We transfected TRIM25lo cells with ZAP-expressing constructs and infected them with SINV Toto1101/Luc . TRIM25 knockdown significantly enhanced SINV Toto1101/Luc replication in the presence of ZAPS and ZAPL overexpression ( Fig 5A ) . Furthermore , we co-transfected TRIM25lo cells with TRIM25- and ZAP-expressing constructs to determine the antiviral effect of the different TRIM25 and ZAP combinations . FL TRIM25 alone inhibited SINV replication , likely due to overexpression ( Fig 5B ) . We found that FL TRIM25 enhanced the activity of ZAPS more than the RING- and CCD-deficient TRIM25 mutants at both high MOI ( Fig 5B ) and low MOI ( S3A Fig ) , in the context of similar expression levels of FL and mutant TRIM25 proteins ( S3B Fig ) . This data suggests that both the E3 ligase activity and oligomerization of TRIM25 are important for the activation of ZAP . However , FL TRIM25 does not significantly enhance SINV inhibition by ZAPL ( Fig 5B and S3A Fig ) , which hints at potential isoform-specific differences in the ZAP-TRIM25 synergy . Since the E3 ligase-defective TRIM25 ( ΔRING ) failed to stimulate the activity of ZAPS ( Fig 5B ) , we hypothesized that TRIM25 might act by ubiquitinating ZAP and/or other host proteins . First , we asked whether ZAP is ubiquitinated . 293T cells transfected with a construct expressing HA-tagged ubiquitin were lysed under denaturing conditions to disrupt protein-protein interactions , and endogenous ZAP was immunoprecipitated with an anti-ZAP polyclonal antibody and probed with an anti-HA antibody . A control anti-GFP antibody of the same species as the anti-ZAP antibody was used to check for non-specific pulldown . We found that ZAP was modified by ubiquitination at baseline and upon SINV infection ( Fig 6A ) . When ZAPS and ZAPL were overexpressed in the ZC3HAV1-knockout 293T cells in the presence of HA-tagged ubiquitin and subject to immunoprecipitation , both ZAP isoforms were found to be modified by ubiquitin , suggesting that the modified lysine ( s ) are likely shared by both isoforms and located in ZAPS ( Fig 6B ) . However , ZAPL is more polyubiquitinated than ZAPS , which hints to additional ubiquitination sites in the PARP-like domain . In addition , we asked whether TRIM25 is implicated in the ubiquitination of ZAP and determined the effect of both endogenous and overexpressed TRIM25 on ZAP ubiquitination level . Both ZAPS and ZAPL ubiquitination in the TRIM25lo cells was reduced compared to that in the parental TRIM25 sufficient ZC3HAV1-knockout cells ( Fig 6C ) . Consistent with that , overexpressed TRIM25 dramatically increased the level of modification of ZAP isoforms by both endogenous ( Fig 6D ) and overexpressed ubiquitin ( Fig 6E ) . Furthermore , we determined which linkage type of polyubiquitin TRIM25 induces on ZAP by overexpressing ubiquitin mutants , in which all the lysine residues are mutated except for K48 or K63 . We immunoprecipitated ZAP isoforms that were co-expressed with TRIM25 , and HA-tagged wild type or mutant ( K48 , K63 ) ubiquitin , and found that both ZAPS and ZAPL were ubiquitinated by both K48- and K63-linked polyubiquitin ( Fig 6F ) . Together , these data suggest that TRIM25 is responsible for ZAP modification . Next , the lysine residues in ZAPS that were predicted to be ubiquitinated with medium to high confidence by UbPred and CKSAAP_UbSite were changed to arginine residues individually ( K226R , K296R , K314R , K401R , K416R , K448R , and K629R ) or in combination ( K296R/K448R , 7UbΔ ) to determine whether potential ubiquitination at any of these sites affects ZAP’s antiviral activity . Moreover , a previous study , in which a global approach was taken to identify all the ubiquitinated proteins in the cell , reported a tryptic peptide with a ubiquitinated lysine in ZAPL ( EEGK783 ( glygly ) LLFYATSR ) [32] . We confirmed that this residue is ubiquitinated using a targeted mass spectrometry approach and the lysine was mutated to arginine in ZAPL ( K783R ) . When we co-expressed the panel of ZAP ubiquitination site mutants with TRIM25 and immunoprecipitated ZAP to determine the level of modification , we found that the mutations diminished the level of ZAP ubiquitination to various degrees ( S4A Fig ) . Most importantly , introduction of all 7 mutations at the same time almost completely abrogated ZAP ubiquitination ( refer to “S 7UbΔ” in S4A Fig ) . However , the ZAPS 7UbΔ mutant was still capable of inhibiting SINV replication ( S4B Fig ) . Our data suggests that TRIM25 upregulates ZAP’s antiviral function not by modifying ZAP , but potentially other host factors . It is possible that ZAP changes the interactome of TRIM25 , which ubiquitinates and functionally modulates these interacting partners resulting in an antiviral state . To test this hypothesis , we co-immunoprecipitated TRIM25 in the absence or presence of ZAPS , of which the antiviral activity was more affected by the E3 ligase function of TRIM25 ( Fig 5B ) , and identified by mass spectrometry proteins that interacted significantly more or less with TRIM25 upon ZAPS expression ( S5 Fig ) . We found that most of these ZAP-mediated TRIM25 interacting partners are involved in mRNA metabolism and translation ( S3 Table ) , which are cellular processes known to be affected by ZAP . However , the change in abundance of most of these proteins is not dramatic ( S5 Fig ) , suggesting that the ZAP-mediated effects on TRIM25 targets might lie in their ubiquitination status . Taken together , we have shown that TRIM25 ubiquitinates ZAP , and that ZAP changes the interactions of TRIM25 with other host proteins that might contribute to the antiviral effects of the ZAP-TRIM25 synergy . Further work is required to determine whether these TRIM25 interacting partners are ubiquitinated and the functional consequences of their modification by TRIM25 . In order to further elucidate the mechanism by which TRIM25 synergizes with ZAP , we investigated the effects of TRIM25 on different ZAP activities that were previously reported ( reviewed in [15] ) . We knocked down TRIM25 in T-REx-hZAP cells and infected them with a temperature sensitive SINV that is unable to replicate at the non-permissive temperature . Since the antiviral mechanisms of ZAP include targeting of viral RNAs for degradation by the exosome complex and translational inhibition , we measured the level of SINV RNA and translation of the incoming viral genome over the course of infection . We found that the kinetics of viral RNA degradation was similar in the presence or absence of TRIM25 ( Fig 7A ) . However , ZAP’s ability to block SINV translation was significantly reduced by about 1 log in the absence of TRIM25 ( Fig 7B; two-way ANOVA: p<0 . 0001 ) , mirroring the magnitude of SINV inhibition upon TRIM25 knockdown in the same cells ( Fig 3A ) . This data suggests that the mechanism by which TRIM25 enhances ZAP activity is through viral translational inhibition .
We reported in this study that ZAP requires multiple host factors for its maximal antiviral activity . We identified novel partners of ZAP that are normally important for a range of cellular processes , such as membrane ion permeability , innate immune signaling , and post-translational protein modification . Among the hits , JAK1 is a kinase important for signaling of the type I IFN receptor and can potentially act by augmenting the stimulatory effects of ZAP on the RIG-I pathway . On the other hand , KCNH5 is an outward rectifying potassium channel and it is not clear how it can stimulate ZAP’s function . It has been shown that reduction of the intracellular K+ concentration can activate the NLRP3 inflammasome , linking ion efflux to innate immunity [33] . It is interesting to note that known interacting partners of ZAP , such as RIG-I or components of the exosome complex , were not hits in the screen , although that is likely largely dependent on the type of assay used and the basal expression levels of genes that are knocked down . Moreover , although MAP3K14 was previously found to be synergistic with ZAP in an ISG overexpression screen [20] , it was not a hit in our confirmatory screen . It is likely that synergistic effects are less pronounced in our screen where endogenous levels of proteins are being interrogated and the effect from silencing of one gene might be compensated by a homologous gene or another ZAP partner . Our study shows for the first time that both ZAP isoforms are ubiquitinated , adding to the existing body of work on post-translational modifications of ZAP . Previous studies have shown that in addition to being post-translationally modified itself , ZAP is implicated in the modifications of other cellular and viral proteins . In some of these cases the modification regulates the function of ZAP or other proteins . For example , the C-terminal end of ZAPL is prenylated , and mutation of this prenylation site reduces the anti-SINV activity of ZAPL to a level similar to that of ZAPS , which is normally not prenylated [12] . It is possible that prenylation positions ZAPL in membrane compartments , allowing it to target viruses with an endocytic life cycle step . In addition , phosphorylation of ZAP by glycogen synthase kinase 3β positively modulates ZAP activity potentially by enhancing its ability to inhibit mRNA translation [34] . Moreover , when cells are stressed , ZAP localizes to cytoplasmic stress granules and is modified by poly-ADP-ribosylation [35] . Modified ZAP is implicated in the poly-ADP-ribosylation of Ago2 , which correlates with derepression of miRNA-mediated translational silencing of cellular transcripts [13 , 35] . In particular , derepression of ISG transcripts results in viral inhibition , as demonstrated for HSV-1 and influenza A virus [13] . ZAP , specifically the long isoform , is also implicated in the poly-ADP-ribosylation and ubiquitination of influenza viral PB2 and PA polymerase proteins and their subsequent degradation [36] . Interestingly , another study reports that ZAPS inhibits influenza protein expression and is antagonized by the viral NS1 protein [37] . A NS1 mutant that lacks the ability to suppress the E3 ligase activity of TRIM25 [38] also loses the ability to antagonize ZAPS [37] , suggesting that ZAPS could inhibit influenza virus through a mechanism that requires TRIM25-mediated ubiquitination , which is antagonized by NS1 . Although we clearly demonstrate here that TRIM25 is implicated in ZAP modification ( Fig 6C–6F ) , mutagenesis of ZAP ubiquitination sites does not impact its antiviral function ( S4 Fig ) . One plausible explanation is that the E3 ligase activity of TRIM25 enhances ZAP function ( Fig 5B ) by ubiquitinating other host factors . It is likely that ZAP affects the interactions of TRIM25 with other proteins , resulting in changes of their modification and function and hence remodeling of the antiviral proteome in the cell . Since ZAP and TRIM25 synergize to block viral translation ( Fig 7B ) , it is intriguing yet not unexpected to find that most of the TRIM25 interacting partners affected by ZAP are involved in mRNA metabolism and translation ( S3 Table ) . Future work determining the ubiquitination status of these proteins will shed light on the impact of TRIM25 E3 ligase activity on the antiviral effects of ZAP . Alternatively , TRIM25 and ZAPS can synergize to positively modulate the activity of RIG-I , leading to heightened innate immune signaling . About half of the TRIM family members have been shown to enhance innate immune responses and both ZAPS and TRIM25 physically interact with RIG-I to stimulate type I IFN response [14 , 23 , 39] . However , whether there is a requirement for RIG-I in ZAP function and vice versa are not settled . Inhibition of the RIG-I pathway and knockdown of RIG-I fail to abrogate ZAP-mediated HBV and XMRV inhibition , respectively [5 , 7] . Furthermore , RIG-I-dependent production of type I IFN and cytokines are not reduced in ZAP-deficient primary mouse cells [40] . Hence , the contribution of TRIM25 and ZAP synergy to innate immunity warrants further investigation . Our data also suggest differences in the interaction between TRIM25 and ZAPS and ZAPL , consistent with previous studies demonstrating distinct activities for the ZAP isoforms . TRIM25 was dramatically modified in the presence of ZAPS , although these modified forms were not associated with ZAPS ( Fig 4B ) . On the other hand , ZAPL expression did not result in extensive modification of TRIM25 and more TRIM25 was found to associate with ZAPL ( Fig 4B ) . This suggests that in addition to the shared domains in ZAPS and ZAPL , ZAPL might interact with TRIM25 through its PARP-like domain . These observations argue that ZAP interacts primarily with unmodified TRIM25 , although the expression of the ZAP isoforms differentially regulates TRIM25 post-translational modification . Based on these observations , we postulate that ZAP might affect the ubiquitination status of TRIM25 and as a result modulate the innate immune response . It has been shown that ubiquitin-specific peptidase 15 deubiquitinates TRIM25 , leading to its stabilization and sustained RIG-I signaling [41] . However , when we performed mass spectrometry on the immunoprecipitates of TRIM25 , we did not see a significant increase in ubiquitinated TRIM25 peptides in the presence of overexpressed ZAPS . It is possible that the increased modification of TRIM25 is due to something other than ubiquitin . Future studies are needed to determine the impact of ZAP isoforms on post-translational modification of TRIM25 . In addition , even though endogenous TRIM25 is required for the function of both ZAPS and ZAPL ( Fig 5A ) , overexpressed TRIM25 stimulates the antiviral activity of ZAPS to a greater extent than that of ZAPL ( Fig 5B ) , which is likely due to ZAPL’s greater baseline inhibitory effect compared to ZAPS in the absence of TRIM25 . In conclusion , our study has uncovered a novel requirement for TRIM25 in ZAP function and elucidated the mechanism of this synergy . Recent outbreaks , such as chikungunya virus ( Alphavirus ) in the Caribbean and U . S . , Ebola virus ( Filovirus ) in West Africa , and Zika virus ( Flavivirus ) in South and Central America , prompts the development of therapeutic strategies for disruption of crucial virus-host interactions . Given that the replication of these viruses greatly depend on the host factor repertoire of the target cells , our study is highly relevant and advances our understanding of host factor contributions to innate immune responses .
T-REx-rZAPC88R cells with tetracycline-inducible protein expression of the rat ZAP C88R mutant were previously described [18 , 28] . To generate the T-REx-hZAP cell line , the short isoform of human ZC3HAV1 was amplified from the ATCC clone 7521231 ( deposited by The I . M . A . G . E . Consortium ) and restriction sites HindIII and SacII were added using primers ( 5’-GGGAAGCTTGCCACCATGGCGGACCCGGAGGTGTGCTGCTTC-3’ and 5’-GCGGATCCGCGGCTCTGGCCCTCTCTTCATCTGCTGCAC-3’ ) . The HindIII/SacII digested PCR product was then cloned into pcDNA4/TO/myc-hisB to generate pcDNA4/TO/hZAP-myc-hisB . We stably transfected T-REx-293 cells ( Thermo Fisher Scientific ) with pcDNA4/TO/hZAP-myc-hisB and selected for Zeocin resistance . A single clone with good induction of hZAP expression ( 6C5 ) was selected and expanded . T-REx-rZAPC88R and T-REx-hZAP were cultured in Dulbecco's Modified Eagle Medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) , 5 μg/ml blasticidin , and 200 μg/ml Zeocin . ZC3HAV1-knockout 293T ( clone 89 ) was obtained from Dr . Akinori Takaoka at Hokkaido University [14] . Wild type and TRIM25lo ZC3HAV1-knockout clones ( see below for details ) , ZC3HAV1-knockout clone , and 293T cells were cultured in DMEM supplemented with 10% FBS . Total RNA was isolated from 293T cells by RNeasy Mini Kit ( Qiagen ) , and reverse transcribed using SuperScript III First-Strand Synthesis System for RT-PCR ( Invitrogen ) and specific primers targeting the 3’UTR regions of the short and long isoforms of human ZAP ( ZAPS 3’UTR: 5’-ACTTGATGAGCCCAGGGCATG-3’; ZAPL 3’UTR: 5’-GTCTGCGGCAATTTAGTTCTG-3’ ) . ZAPS and ZAPL were amplified from 293T cDNA using primers ( ZAPS: 5’-GTTTTGTACAGCCACCATGGCGGACCCGGAGGTG-3’ and 5’-GGTAGCGGCCGCTTACTCTGGCCCTCTCTTCATC-3’; ZAPL: 5’-GTTTTGTACAGCCACCATGGCGGACCCGGAGGTG-3’ and 5’-GGTA GCGGCCGCCTAACTAATCACGCAGGCTTTG-3’ ) and cloned into the BsrGI and NotI sites of a modified pTRIPZ construct ( Open Biosystems ) under the control of the CMV promoter . The 3’ ends of ZAPS and ZAPL were swapped into SmaI and XhoI sites of pTRIP-RFP-NZAP [42] to generate pTRIP constructs expressing N-terminally RFP-fused ZAPS and ZAPL . V5-tagged FL TRIM25 and derivatives ( domains alone: RING , B box/CCD and SPRY; domain deletion mutants: ΔRING and ΔCCD ) were expressed from a modified pIRES-puro vector encoding a C-terminal V5 tag as previously described and were gifts from Jae U . Jung [23 , 38] . pcDNA3 . 1 ( HA-Ub ) 6 was previously described [43] . pRK5-HA-Ubiquitin-K48 ( all the lysines in ubiquitin are mutated except K48 ) , pRK5-HA-Ubiquitin-K63 ( all the lysines in ubiquitin are mutated except K63 ) and pRK5-HA-Ubiquitin-WT were gifts from Ted Dawson ( Addgene plasmid #17605 , 17606 and 17608 ) [44] . pSpCas9 ( BB ) -2A-Puro ( PX459 ) was a gift from Feng Zhang ( Addgene plasmid # 48139 ) [31] . SINV ( Toto1101 ) , and SINV expressing firefly luciferase ( Toto1101/Luc and Toto1101/Luc:ts6 ) or EGFP ( TE/5’2J/GFP ) have been previously described [3 , 45 , 46] . Stocks were generated in baby hamster kidney 21 ( BHK-21; ATCC ) cells as previously described [3] . The Toto1101/Luc stock used for the screen was concentrated using polyethylene glycol with an average molecular weight of 6 , 000 ( Fluka ) as described [47] . Viral titers for multiplicity of infection ( MOI ) calculations were determined in BHK-21 cells . Viral infections were performed as previously described [3] . For the primary ZAP cofactor screen , siRNAs from the siGENOME library targeting the whole human genome ( Dharmacon; pools of 4 siRNAs per gene ) were pre-arrayed in fifty-eight 384-well plates , mixed with DharmaFECT 1 Transfection Reagent ( diluted 1:100 ) , and transferred to 384-well assay plates ( 5 μl/well; 25 nM final ) with a Janus automated workstation ( PerkinElmer ) . The entire screen was carried out in triplicate by reverse transfection . siGENOME NT and ZC3HAV1-targeting siRNA smartpools were used as negative and positive controls ( 5 wells per control per plate; see the position of the controls in S1 Table ) . A total of 7500 T-REx-hZAP cells were seeded in DMEM with 3% FBS , 5 μg/ml blasticidin , and 200 μg/ml Zeocin ( 25 μl/well ) with a MultiDrop Combi liquid dispenser ( Thermo Fisher Scientific ) . One day post-plating , ZAP expression was induced by addition of 1 μg/ml doxycycline ( 5 μl/well ) . Since removing the media from 384-well plates and adding virus inoculum in a minimal volume to allow adsorption was not feasible , cells were infected with a highly concentrated PEG-precipitated SINV stock at a MOI of ~200 ( 5 μl/well ) two days following siRNA treatment . The MOI was calculated based on titration of the viral stock under standard infection conditions , and due to dilution was likely much lower under the conditions used in the screen . Twenty-four hours p . i . , cells were lysed with Steady-Glo Luciferase Assay Substrate ( Promega; 20 μl/well ) and luminescence measured on an EnVision plate reader ( PerkinElmer ) . For each well , the raw luciferase value reflects the level of SINV infection . The raw luciferase values and the plate median from each of the 384-well plates were used to calculate the median absolute deviation ( MAD ) : 1 . 4826 x MEDIAN ( each raw value − plate median ) . The robust Z score was then calculated by dividing the difference between each raw luciferase value and the plate median by MAD [26] . Normalized percent activation ( NPA ) was also calculated for each well as follows: 100* ( Xi−μc- ) / ( μc+−μc- ) , where Xi = raw luciferase value , μc+ = mean positive controls and μc- = mean negative controls . The entire screen was performed in triplicate and the Z' and strictly standardized mean difference ( SSMD ) were calculated for every plate [26] . A Z' factor of >0 . 5 and a SSMD of >3 were used as cutoffs for assay validation [26 , 48 , 49] . Those wells with the highest NPA and robust Z score >3 in all three replicates were considered ‘hits’ . For the secondary screen , Silencer siRNAs ( Ambion; 3 individual siRNAs per gene ) were tested in 384-well plates in triplicate at two different concentrations: 6 . 25 nM ( the concentration of each single siRNAs in the original Dharmacon pools ) and 25 nM ( the concentration of the original Dharmacon pools used in the primary screen ) . In order to rule out ZAP-independent effects of the top hits , the secondary screen was carried out in two different cells lines: T-REx-hZAP and T-REx-rZAPC88R . Genes with an average Z score of >3 for at least two out of the three siRNA sequences were considered ‘hits’ . Pathway analysis was performed using Enrichr [50] . All genes with an average robust Z score >3 were normalized using -5 as the minimum ( essentially the value of the negative controls ) and the mean value for ZC3HAV1 as the maximum , scaled between 0 and 1 , and exported as a comma-separated table with the normalized score and gene symbol , a format recognized by Enrichr . Genes belonging to pathways that were significantly enriched and overlapping with the list of genes with the highest NPA and robust Z score >3 in at least 1 out of 3 replicates were validated in the secondary screen . Haystack analysis was performed to identify the most statistically significant genes whose predicted knockdown via off-target effects was correlated with the phenotypes observed in the primary screen [27] . Differences between experimental conditions during the course of infection were determined using two-way ANOVA . Differences between experimental conditions at a single time point were determined using an unpaired , two-tailed Student’s t-test with a 95% confidence interval . For our validation studies , mammalian cells ( T-REx-hZAP , 293T and ZC3HAV1-knockout 293T cells ) were reverse transfected with 25 nM Silencer siRNAs targeting TRIM25 , KCNH5 , JAK1 , ZC3HAV1 ( Ambion ) that were used in the secondary screen or a C911 control for TRIM25 ( Ambion ) using DharmaFECT 1 Transfection Reagent ( diluted 1:100 ) . siGENOME NT and ZC3HAV1-targeting siRNA smartpools ( Dharmacon ) were used as negative and positive controls . Sequences for TRIM25-targeting Ambion Silencer and the corresponding C911 control siRNAs were as follows: TRIM25 siRNA #3 ( 5’-CCCUGAGGCACAAACUAACtt-3’ and 5’-GUUAGUUUGUGCCUCAGGGtg-3’ ) ; and TRIM25 #3-C911 ( 5’-CCCUGAGGGUGAAACUAACtt-3’ and 5’-GUUAGUUUCACCCUCAGGGtg-3’ ) . One day post-transfection , ZAP expression was induced in T-REx-hZAP cells by 1 μg/ml doxycycline . Two days post-transfection , the media was removed and T-REx293-hZAP , 293T and ZC3HAV1-knockout 293T cells were infected with SINV Toto1101/Luc at a MOI of 0 . 01 or 10 in a minimal inoculum volume . 24 hours p . i . , cells were lysed with 1x Cell Culture Lysis Reagent ( Promega ) and luminescence measured on a Synergy Neo plate reader . For time course experiments , cells were lysed at 6 , 12 , 24 , and 40 hours p . i . and luciferase activity measured . Cells were transfected in different combinations with constructs expressing V5-tagged TRIM25 ( FL ) or derivatives ( RING , B box/CCD , SPRY , ΔRING , and ΔCCD ) , ZAPS or ZAPL , and HA-tagged wild type ubiquitin or mutants with X-tremeGENE 9 DNA Transfection Reagent ( Roche Life Science ) at a ratio of 3 μl reagent to 1 μg DNA . Total plasmid amount in co-transfections was kept constant by transfecting cells with empty vectors ( pIRES-puro , pTRIPZ and pcDNA3 . 1 ) . Guide RNAs ( gRNAs ) targeting exon 1 of the human TRIM25 gene were designed by the MIT Optimized CRISPR Design portal ( http://crispr . mit . edu/ ) , and two with the least predicted off-target effects ( gRNA #1: GTCGCGCCTGGTAGACGGCG; gRNA #3: GAGCCGGTCACCACTCCGTG ) were selected for cloning into the Cas9-expressing PX459 vector . Oligos containing the gRNA sequences ( gRNA #1: 5’-CACCGGTCGCGCCTGGTAGACGGCG-3’ and 5’-AAACCGCCGTCTACCAGGCGCGACC-3’; gRNA #3: 5’-CACCGGAGCCGGTCACCACTCCGTG-3’ and 5’-AAACCACGGAGTGGTGACCGGCTCC-3’ ) were ligated and cloned into PX459 linearized with BbsI . ZC3HAV1-knockout 293T cells were transiently transfected with PX459 expressing gRNA #1 or 3 , and one day after transfection selected under 1 μg/ml puromycin for 2 days to eliminate cells that were not transfected . Surviving cells were then counted , diluted to 0 . 5 cell/well in a 96-well plate and seeded in 10% FBS DMEM . Single cell clones were marked and allowed to expand . Several clones per gRNA #1 were treated with or without puromycin and the ones that were sensitive to puromycin , suggesting that the clones had not integrated the gRNA-expressing vector , were harvested for immunoblot analysis to evaluate TRIM25 expression . Two knockdown clones ( D and F ) and one wild type clone ( E ) were selected ( see S2 Fig ) . Genomic DNA was isolated from these clones , and a 600bp sequence flanking the gRNA targeting site was amplified by PCR and cloned into TOPO vector ( Thermo Fisher Scientific ) . Sequencing of TOPO clones confirmed that all three chromosomes were targeted in clones D and F resulting in insertions and/or deletions in exon 1 of TRIM25 , while clone E is wild type . Transfected or untransfected cells in 6-well plates were collected and then lysed in 0 . 5% NP40 buffer ( for co-IP; 10 mM HEPES , pH 7 . 5 , 150 mM KCl , 3 mM MgCl2 , 0 . 5% NP-40 ) or 0 . 5% SDS buffer ( for denaturing ZAP IP; 0 . 5% SDS , 50 mM Tris-HCl , pH 7 . 5 , 200 mM NaCl , 1 mM EDTA ) supplemented with a complete protease inhibitor cocktail ( Roche ) and 0 . 1 mM PMSF ( Sigma ) . For co-IP of endogenous TRIM25 and ZAP , 300 μl of WCL were incubated with 1 μg of anti-TRIM25 antibody overnight at 4 °C , and then with 40 μl Protein A Dynabeads ( Invitrogen ) for 2 h at 4°C . For co-IP of overexpressed TRIM25 and ZAP , 5 . 25 μg of anti-NZAP antibody was covalently crosslinked to 70 ul Protein A Dynabeads by BS3 ( Thermo Fisher Scientific ) and incubated with 300 μl of cell lysate at 4 °C for 4h . Immunoprecipitates were washed 3 times with 0 . 5% NP40 buffer , followed by two washes with 0 . 05% NP40 buffer . For denaturing IP , 300 μl WCL were diluted into 1X TNA buffer ( 0 . 25% Triton , 50 mM Tris-HCl , pH 7 . 5 , 200 mM NaCl , 1 mM EDTA ) + 2 mg/ml BSA , incubated with 1 μg anti-ZAP , or anti-GFP antibody overnight at 4°C , and then with 40 μl Protein A Dynabeads ( Invitrogen ) for 2 h at 4°C . Immunoprecipitates were washed 3 times with 1X TNA buffer + 2 mg/ml BSA . Bound proteins were eluted with SDS loading buffer and boiled for 5 min . Polypeptides were resolved by SDS–polyacrylamide gel electrophoresis ( SDS–PAGE ) and transferred to a nitrocellulose membrane ( GE Healthcare ) . Immunodetection was achieved with 1:5000 anti-ZAP ( ab154680; Abcam ) , 1:5000 anti-NZAP ( mouse monoclonal 23D1 . 1; see below ) , 1:5000 anti-V5 ( MA5-15253; Thermo Fisher Scientific ) , 1:5000 anti-TRIM25 ( 610570; BD Biosciences ) , 1:1000 anti-HA ( clone 3F10; Roche ) , 1:500 anti-ubiquitin ( P4D1; Santa Cruz Biotechnology ) , or 1:50 , 000 anti-actin-HRP ( A3854; Sigma ) antibodies . The primary antibodies were detected with 1:20 , 000 goat anti-mouse HRP ( 115-035-146; Jackson ImmunoResearch ) , 1:20 , 000 goat anti-rabbit HRP ( 31462; Thermo Fisher Scientific ) , or 1:20 , 000 donkey anti-rat HRP ( 712-035-153; Jackson ImmunoResearch ) . Mouse monoclonal antibodies to rat NZAP previously generated [51] were screened for cross-reactivity to human NZAP . The clone 23D1 . 1 was submitted for production and purification by Cell Essentials . Anti-GFP antibody ( rabbit polyclonal ) was generated previously [52] . The proteins were visualized by ECL Prime Western Blotting Detection Reagent ( GE Healthcare ) or SuperSignal West Pico Chemiluminescent Substrate ( Thermo Fisher Scientific ) . Total RNA was isolated from siRNA-treated cells using the RNeasy mini kit ( Qiagen ) . 1 μg of input RNA was used as a template for reverse transcription using SuperScript III ( Invitrogen , Carlsbad , CA ) and random hexamers . RT-qPCR was performed using 5 μl of 10-fold-diluted cDNA and primers targeting JAK1 ( 5’-CCACTACCGGATGAGGTTCTA-3’ and 5’-GGGTCTCGAATAGGAGCCAG-3’ ) , KCNH5 ( 5’-CCGTGTGGCTAGGAAACTGG-3’ and 5’-CAATGACCTCGTAGTCTCCGA-3’ ) , and RPS11 ( 5’-GCCGAGACTATCTGCACTAC-3’ and 5’-ATGTCCAGCCTCAGAACTTC-3’ [53] ) in a SYBR Green qPCR assay on the LightCycler 480 Real-Time PCR System ( Roche Applied Sciences , Indianapolis , IN ) . qPCR conditions were as follows; initial denaturation step at 50°C for 2 min and 95°C for 10 min , then 45 cycles of 95°C for 15 sec , 56°C for 15 sec , and 72°C for 20 sec , and followed by a melting step of 95°C for 10s , 65°C for 10s and a 0 . 07°C/s decrease from 95°C , and a cooling step of 50°C for 5s . Transcript levels of JAK1 and KCNH5 were determined by normalizing the target transcript CT value to the CT value of the endogenous housekeeping RPS11 transcript . This normalized value was used to calculate the fold change relative to the average of cells treated with the NT siRNA control ( CT method ) . To determine SINV RNA levels in TRIM25-targeting or NT siRNA treated T-REx-hZAP cells over the course of infection with Toto1101/Luc:ts6 , 1 μg of total cellular RNA was used in a one-step quantitative real-time PCR assay using primers and a Taqman probe targeting the nsP2 region of SINV . Primer pairs for SINV Taqman RT-qPCR are as follows: SINV nsP2 ( forward ) : 5’-GGTAGCTCATTGGGACAACA-3’; SINV nsP2 ( reverse ) : 5’-GCTGGAACACCGGAAATCTA-3’; SINV nsP2 Taqman probe ( reverse ) : 5’-TGGCGTGATCGTACCCATACTTGC-3’ . RNA was amplified using Lightcycler 480 RNA Master Hydrolysis Probes ( Roche ) under the following thermal conditions: RT at 63°C for 3 min; denaturation at 95°C for 30 s; 45 cycles of amplification at 95°C for 15 s , 60°C for 30 s , and 72°C for 1 s; and a final cooling step at 40°C for 10 s . Viral RNA copy number at each time point p . i . was then determined by comparing the threshold cycle ( CT ) value to a standard curve of serial 10-fold dilutions of purified in vitro transcribed SINV RNA . Viral RNA levels were normalized to that at 0 h p . i . ZAPS ubiquitination site mutants ( K226R , K296R , K314R , K401R , K416R , K448R , K629R , and K296R/K448R ) were generated by mutagenesis of pTRIP-RFP-ZAPS using the QuikChange II XL Site-Directed Mutagenesis Kit ( Agilent Technologies ) . Primers for site-directed mutagenesis of ZAP were as follows: ZAPS K226R ( 5’-GCAAGCACATGCAGAGGAATCCCCCAGGGCC-3’ and 5’-GGCCCTGGGGGATTCCTCTGCATGTGCTTGC-3’ ) ; ZAPS K296R ( 5’-ACGATCTCACCCGCAGGTTCACGTATCTGGG-3’ and 5’-CCCAGATACGTGAACCTGCGGGTGAGATCGT-3’ ) ; ZAPS K314R ( 5’-CCTCAGGCTCGTCCAGGGCTACTGATCTTGG-3’ and 5’-CCAAGATCAGTAGCCCTGGACGAGCCTGAGG-3’ ) ; ZAPS K401R ( 5’-CTGTGACCACCAGAAGGGGCACAGGCTTGC-3’ and 5’-GCAAGCCTGTGCCCCTTCTGGTGGTCACAG-3’ ) ; ZAPS K416R ( 5’-GGATCATCAATGGCAGAAGTGGAACTCAGGACATCC-3’ and 5’-GGATGTCCTGAGTTCCACTTCTGCCATTGATGATCC-3’ ) ; ZAPS K448R ( 5’-CCAGATCCTTAAATTACAGAAGCACTAGCAGCGGTCACAG-3’ and 5’-CTGTGACCGCTGCTAGTGCTTCTGTAATTTAAGGATCTGG-3’ ) ; ZAP K629R ( 5’-GAGAAAGACAAACGGAGAAATTCAAACGTCGACTCTTC-3’ and 5’-GAAGAGTCGACGTTTGAATTTCTCCGTTTGTCTTTCTC-3’ ) . ZAPS 7UbΔ was generated by cloning a 1 . 9 kb synthesized DNA fragment ( IDT ) containing all the lysine-to-arginine mutations into pTRIP-RFP-ZAPS . The ZAPL K783R mutant was generated by cloning an overlapping PCR fragment into the SalI and XhoI sites of ZAPL ( PCR #1: 5’-GTTTGTCGACTCTTCATACCTGGAG-3’ and 5’-GGAGTCTTCCTTCTTCCTTCATCTG-3’; PCR #2: 5’-GAAGGAAGACTCCTATTTTATGCGAC-3’ and 5’-GGTACTCGAGCTAACTAATCACGCAGGCTTTG-3’ ) . Clones were sequence verified and packaged into lentiviruses by co-transfection with Gag-Pol and VSV-G-expressing plasmids into 293T cells [20] . ZC3HAV1-knockout 293T were transduced with lentiviruses carrying RFP alone , ZAPS , ZAPL , and various ubiquitination site mutants , and 2 days later infected with TE/5’2J/GFP at a MOI of 10 . Cells were harvested at 6–8 h p . i . and fixed in 1% paraformaldehyde for flow cytometry analysis . Data was acquired using a BD LSRII and FACS Diva software ( version 8 . 0 ) and analyzed using FlowJo 8 . 8 . 7 ( TreeStar Inc . ) . Percent infected ( GFP+ ) cells in the transduced ( RFP+ or RFP-tagged ZAP+ ) population was calculated for ZAPS , ZAPL and their mutants . For the ZAP ubiquitination experiment , based on alignment of the ZAP IP Western Blot , SDS-PAGE gel bands corresponding to ZAP were excised and trypsinized as described previously [54] . For the co-immunoprecipitation experiment , TRIM25 and associated proteins were co-immunoprecipitated and eluted from anti-V5 antibody-crosslinked M-270 Epoxy Dynabeads ( Thermo Fisher Scientific ) using 8M Urea ( GE Healthcare Life Sciences ) , reduced , alkylated and digested with Endopeptidase Lys-C ( >4M Urea ) for 6 hours followed by overnight trypsinization ( >2M Urea ) . Peptides were analyzed by reversed phase nano LC-MS/MS ( Ultimate 3000 nano-HPLC system coupled to a Q-Exactive Plusor a Fusion Lumos mass spectrometer , operated in high/low mode , Thermo Fisher Scientific ) . Known ( EEGK783 ( glygly ) LLFYATSR [32] ) and predicted ubiquitinated ZAP peptides were analyzed by parallel reaction monitoring ( PRM ) [55] while data dependent acquisition ( DDA ) was used for unknown ZAP ubiquitination sites . Peptides generated from the co-immunoprecipitation experiment were analyzed in DDA mode . All peptides were separated on a C18 column ( 12 cm / 75 μm , 3 μm beads , Nikkyo Tecnologies ) at 300 nl/min with a gradient increasing from 2% Buffer B/98% buffer A to 40% buffer B/60% Buffer A in 37 min or 80 min ( buffer A: 0 . 1% formic acid , buffer B: 0 . 1% formic acid in acetonitrile ) . For data analysis , ubiquitination focused DDA data was extracted and queried against UniProts complete human proteome database ( March 2016 ) concatenated with common contaminants [56] using Proteome Discoverer 1 . 4 ( Thermo Fisher Scientific ) /MASCOT 2 . 5 . 1 ( Matrix Science ) . Protein N-terminal acetylation , oxidation of methionine , and di-glycine modification of lysine were allowed as variable modifications . In cases where proteins were reduced ( DTT ) and alkylated ( iodoacetaminde ) , carbamidomethylation was included as a variable modification of cysteines and lysines . 10 ppm and 20 mDa were used as mass accuracy for precursors and fragment ions , respectively . Matched peptides were filtered using 1% False Discovery Rate calculated by Percolator [57] and in addition requiring that a peptide was matched as rank 1 and that precursor mass accuracy was better than 5 ppm . Data from the co-immunoprecipitation experiment , in biological triplicates , was analyzed by MaxQuant v . 1 . 5 . 3 . 28 using match between runs . Search criteria similar to above were used . Fold differences were calculated based on label-free quantification ( LFQ ) values ( http://www . ncbi . nlm . nih . gov/pubmed/24942700 ) while intensity-based absolute quantitation ( iBAQ ) values ( https://www . ncbi . nlm . nih . gov/pubmed/21593866 ) were used to estimate abundance of different proteins . The statistical packet Perseus ( https://www . ncbi . nlm . nih . gov/pubmed/27348712 ) was used for data analysis . | Organisms have evolved various innate strategies to defend against pathogens . During virus infection , the cell senses the viral nucleic acid and produces type I interferon , which alerts the neighboring cells . Signaling of type I interferon triggers expression of a wide array of genes , some of which encode proteins that inhibit the replication of diverse virus families . It is not clear what determines the broad yet specific activity of these interferon-induced gene products . Identification of cellular cofactors and pathways required for the function of these broadly antiviral proteins would help elucidate their mechanisms . Here , we perform a genome wide knockdown screen to identify host factors important for the antiviral action of zinc finger antiviral protein ( ZAP ) , a broad-spectrum inhibitory protein induced by interferon . We find that ZAP synergizes with host proteins with divergent functions and identify TRIM25 as a bona fide ZAP cofactor . TRIM25 binds to both splice isoforms of ZAP , and stimulates their ubiquitination and function by facilitating the ability of ZAP to block viral translation . Our data sheds light on the antiviral mechanism of ZAP and advances our understanding of host factor contributions to innate immune responses against viral infections . | [
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"prote... | 2017 | TRIM25 Enhances the Antiviral Action of Zinc-Finger Antiviral Protein (ZAP) |
Evolutionary innovation relies partially on changes in gene regulation . While a growing body of evidence demonstrates that such innovation is generated by functional changes or translocation of regulatory elements via mobile genetic elements , the de novo generation of enhancers from non-regulatory/non-mobile sequences has , to our knowledge , not previously been demonstrated . Here we show evidence for the de novo genesis of enhancers in vertebrates . For this , we took advantage of the massive gene loss following the last whole genome duplication in teleosts to systematically identify regions that have lost their coding capacity but retain sequence conservation with mammals . We found that these regions show enhancer activity while the orthologous coding regions have no regulatory activity . These results demonstrate that these enhancers have been de novo generated in fish . By revealing that minor changes in non-regulatory sequences are sufficient to generate new enhancers , our study highlights an important playground for creating new regulatory variability and evolutionary innovation .
The question of the evolutionary origin and modification of enhancer elements is central for understanding the dynamics of gene expression [1]–[3] . A growing body of evidence points out that new enhancers evolve from existing ones via duplication . According to the classic model of evolution by duplication as put forward by Ohno [4] , the duplicated copies are used as starting material for variation in the binding site composition , which modifies the respective enhancer's activity [5]–[10] . Mobile genetic elements have also been shown to have regulatory activity [11] , [12] or bear transcription factor binding sites ( TFBSs ) [13] , and thus , their translocation can be associated with changes in gene expression . While the modification/translocation of those pre-existing elements has been shown to play an important functional role , they may only contribute to a fraction of the regulatory innovation . Indeed , recent findings using large-scale comparative analysis of regulatory features have shown that single binding sites can vary extensively between closely related species [14] or even between individuals of the same species [15] . Further supporting the flexibility of regulatory elements , tissue-specific enhancers such as heart enhancers have been shown to be poorly conserved [16] and examples of lineage/specie-specific enhancers have been described [17] , [18] . Recently it has been reported that the genomic positions of tissue-specific enhancers of the yellow gene differ between Drosophila species [19] . Taken together , these results are suggesting that complete autonomous enhancer elements containing all the necessary binding sites in the correct arrangement can be lineage specific . Nevertheless it is currently unclear whether these apparent lineage-specific enhancers appear de novo or are derived from pre-existing enhancers whose sequences have diverged too much to be identifiable . In order to show the de novo nature of these lineage-specific enhancers , a strategy to identify the orthologous regions and test them for enhancer activity is needed . In this report we identify de novo enhancers by searching for special cases that we refer to as “Recycled Regions” ( RRs ) . An RR is a region with enhancer function in one lineage that remains identifiable in another lineage due to sequence constraints imposed by a different kind of function . These scenarios are likely to be very rare in stable genomes . Thus , we took advantage of the most recent Whole Genome Duplication ( WGD ) in teleosts [20] followed by a massive loss of the duplicated coding genes . It is estimated that 75% of the duplicated genes lost one copy [20] . Initially , while one of the duplicated copies remained a coding gene , the other copy lost its coding function and accumulated nucleotide changes . In rare cases , the sequence from the non-coding copy became constrained if a regulatory function arose de novo . Those regulatory sequences are alignable to their coding orthologs if the selection for the new function took place soon enough . Hence we used the ancestral coding function as an evolutionary trap to identify orthologous sequences of the enhancer across lineages ( mammalian , cartilaginous fish , and teleost ) and assessed whether these enhancers are generated de novo in the teleost lineage ( Figure 1A ) .
We developed an algorithm to systematically search for the RRs in teleost fish genomes that satisfy the corresponding criteria ( Figure 1B ) : ( 1 ) are located in the locus corresponding to the lost copy of a duplicated gene; ( 2 ) despite no evidence for the coding function , are conserved with part of the human coding ortholog; and ( 3 ) as experimental validation is performed during embryogenesis , we selected those RRs flanked by at least one gene annotated to be involved in development ( Figure S1 and Materials and Methods , Computational Pipeline ) . The algorithm was first run on the stickleback ( Gasterosteus aculeatus ) genome because of the high quality of the gene annotation and assembly , and later the results were transferred to the Oryzias latipes ( medaka ) genome . Our analysis identified four RRs ( Figure 1C , Table S1 , and Table S2 ) as putative de novo regulatory regions satisfying the above criteria . Those RRs are conserved across teleosts including Danio rerio ( zebrafish ) , suggesting that they appear after the WGD but before the Cypriniformes-Euteleostei split . We investigated the enhancer activity of the four medaka RRs ( Figure 1C and Table S1 ) using an in vivo reporter assay in medaka that we previously developed [21] . We cloned the four RRs extended with a maximum of 200 bp flanking sequences upstream of an hsp70 minimal promoter and a reporter gene ( gfp ) . The basal expression of the hsp70 minimal promoter in the lens [22] was used as injection control . We found that all four regions tested drive reporter gene expression in specific structures in the medaka embryo ( Figure 2A–D ) . The assay is highly reproducible , resulting in a consistent expression pattern in a large fraction of embryos ( Table S3 ) . The onset of reporter gene expression depends on the nature of the RR and varies from developmental stage 20 ( fam44bRR ) to stage 32 ( dock9RR ) and is in all cases maintained in juvenile ( Figure S2 ) and adult fish ( unpublished data ) . Moreover , the specific expression pattern observed in injected embryos ( Table S3 ) is retained in stable lines . In line with our hypothesis , these results show enhancer activity for all four RR reporter constructs . We further addressed the contribution of the four RRs to the observed enhancer activity by deleting the orthologous regions corresponding to the exon , leaving only the flanking regions from the reporter constructs ( Figure S3A–D ) . In two cases , the deletion constructs completely abolished reporter gene expression ( Figure S3E–F ) . For ccdc46RR , the deletion altered and massively reduced the reporter gene expression to a few cells in the hindbrain ( Figure S3G ) . Only for fam44bRR did the deletion construct not abolish the original enhancer activity of the full construct ( Figure S3H ) and therefore fam44bRR was excluded from further analysis . These results demonstrate that three out of four RRs are necessary for enhancer activity . We next investigated whether the enhancer activity of the remaining three RRs recapitulates aspects of the expression pattern of flanking genes . For this , we analysed the in situ expression pattern of those genes . We found that in all cases RR-driven reporter gene expression temporally and spatially resembles the expression of at least one of the respective flanking genes ( Figure S4 ) . To further confirm this , we performed double fluorescent whole mount in situ hybridisation on stable transgenic lines by combining probes for the reporter and the flanking genes . In all cases , we identified at least one flanking gene that recapitulates key aspects of the expression pattern of the RR-driven reporter gene ( Figure 3 ) . In particular , both ttc29RR-driven GFP ( Figure 3B ) and the flanking gene pou4f2 ( Figure 3A ) are expressed in the optic tectum and retina ( Figure 3C ) . dock9RR shows very specific enhancer activity in the cerebellum ( Figure 3E , H ) as do the neighbouring genes zic5 and zic2 ( Figure 3D , G ) , which exhibit an expression pattern that includes the cerebellum ( Figure 3F , I ) . Finally , ccdc46RR shows activity in the forebrain ( Figure 3K ) , recapitulating part of the expression pattern of its flanking gene axin2 ( 1 of 2 ) ( Figure 3J , L ) . All putative target genes have been reported to play important roles in developmental processes: Zic2 and 5 are zinc finger proteins of the cerebellum , and mutations in the zic2 gene have been reported to cause holoprosencephaly [23] . Axin2 , an Axin-related protein , has been shown to play an important role in the regulation of β-catenin stability in the Wnt signalling pathway [24] , and Pou4f2 , better known as Brn3b , is a member of the POU-domain family of transcription factors and is a key regulator for axon outgrowth and pathfinding in projection neurons [25] . Our results demonstrate that the RRs exhibit enhancer activity that recapitulates multiple aspects of the expression of neighbouring genes . Our results further suggest that the identified RRs contribute to the transcriptional regulation of genes that are key players in embryonic development . Two possible evolutionary scenarios may account for our results obtained so far: ( 1 ) the ancestral function was both regulatory and coding or ( 2 ) the ancestral vertebrate sequence was coding but the teleosts have lost that function in one of the duplicated copies and acquired regulatory function instead ( which supports the de novo enhancer hypothesis ) . For the former scenario , dual functions on the same region have been hypothesised [26] and shown for several cases [27]–[32] while the latter scenario has not been shown so far . To shed light on the ancestral state of the RRs , we investigated the RRs in lineages that diverged prior to the last WGD in teleosts . In species that have diverged prior to the teleost-tetrapod split ( e . g . , elephant shark ( Callorhinchus milii ) or ciona ( Ciona savignyi ) ) the sequences corresponding to the three RRs showed an open reading frame ( ORF ) spanning the coding exon that is in frame with the human ORF ( Figure S5 ) . For both TTC29 and CCDC46 we also found EST evidence in the ciona lineage ( Table S2 ) . These results show that the RRs ancestral sequences were very likely to have been coding at the split of the teleost-tetrapod lineages . We next investigated the evolutionary dynamics of these regions by analysing the similarity between the human coding exon and the orthologous regions in various lineages at both the amino-acid ( AA ) and nucleotide level . We found that the percentage identity at the nucleotide level is higher for the fish RRs , while the similarity at the AA level is higher for all other lineages , including the fish coding paralog ( Figure S6 ) . Consistent with the alignment similarities , the ratio of non-synonymous compared to synonymous base pair changes ( Ka/Ks ) [33] is increased for the RRs compared to the coding homologs ( see Materials and Methods and Figure S6 ) . In accordance with the results obtained so far , these data further support the hypothesis that ( 1 ) the RRs were ancestrally coding and ( 2 ) the fish RRs are under a selection acting at the nucleotide rather than at the AA level . These data suggest that the RRs were ancestrally not regulatory since the Ka/Ks ratio between human and shark or ciona would favour a selection acting at the AA level only . To test the nature ( regulatory or non-regulatory ) of the ancestral state at the tetrapod-teleost split , we further explored the enhancer activity of the exons homologous to the RRs in two independent lineages ( mouse and elephant shark ) as well as the coding paralog in fish ( Figure 4 ) . In none of the cases tested was an enhancer activity detectable ( Figure 4 and Table S3 ) . As the exon orthologous to the RRs was tested in the Medaka embryo , the absence of activity could be due to trans-regulatory changes [34] . To rule out this hypothesis , the mouse exons orthologous to the RRs were tested directly in mouse . Again , in none of the cases tested was an enhancer activity detectable ( Figure 4 and Material and Methods ) , confirming that the mouse exons orthologous to the RRs have no enhancer activity ( at the time point assayed ) . The results obtained so far provide convincing evidence that the enhancer function in teleosts was de novo acquired in this lineage . As most of the de novo genesis of enhancers is expected to occur in “neutrally” evolving sequences , these cases of de novo enhancers deriving from cooption may constitute a very small subset of all possible de novo enhancers . We roughly estimate at several thousands the number of de novo enhancers under positive selection since the tetrapod-teleost split ( 450 mya [35] , see Text S1 and Figure S7 for a more detailed analysis of the estimation of the number of de novo enhancers ) . Considering that those de novo elements under purifying selection may constitute only a tiny fraction of all possible regulatory elements generated , the rate of genesis of new enhancers ( regardless of their evolutionary fate ) may be very high in vertebrate genomes . While this estimation of the number of de novo enhancers is only tentative and based on a number of assumptions ( see Text S1 ) , a more accurate prediction of the de novo enhancers across various phylogenetic branches of vertebrates will require further studies . Nonetheless , these results highlight the importance of the genesis of enhancers and provide one possible explanation amongst others of the widespread observation that a large fraction of TFBSs appears non-conserved [36] . Nonetheless , those TFBSs forming de novo enhancers may represent only a fraction of all the apparent lineage-specific binding sites found by genome-wide chromatin immunoprecipitation experiments . In an attempt to predict what the possible TFBS involved in the generation of the de novo enhancers are , we further investigated at the sequence level the difference in terms of putative TFBSs between the RRs and the exons ( Materials and Methods ) . We found from five to seven binding sites in the medaka RRs that are specific to teleosts and are not present in other vertebrate species nor in the predicted ancestral reconstruction ( Figure S8 ) . Interestingly , dock9RR in medaka ( with enhancer activity in the cerebellum ) has a new binding site for Pax2 , a transcription factor known to be involved in cerebellum development [37] . These de novo enhancers may either confer additional domains of expression to their target genes or rather act as redundant enhancers . To tackle the functional consequences of the de novo enhancers , we took advantage of a conserved block flanking the ccdc46RR homologous exon previously shown to be bound by p300 in mouse forebrain ( Figure S9 , orange bar , upper panel ) [38] . We tested the mouse extended region containing both the p300 pulldown region and the extended exonic sequence ( Figure S9 , light green bar , upper panel ) and detected enhancer activity in the medaka forebrain ( Figure S9A ) . This activity was not altered when deleting the exonic sequence ( Figure S9 , blue bar , upper panel and Figure S9B ) , demonstrating that the exon itself is not required for enhancer function ( see also Figure 4 ) . Similarly , the shark and medaka sequences ( Figure S9 , orange bar , lower panel ) orthologous to the mouse p300-bound enhancer also show forebrain activity ( Figure S9C–D ) . These results demonstrate that the p300-bound enhancer element is an ancestral feature and suggest that the nearby ccdc46RR de novo enhancer in fish has complementary function to reinforce the forebrain expression rather than creating a new expression domain . Similarly dock9RR is active in the medaka cerebellum , while the mouse zic2 and 5 genes are also expressed in this structure [39] . While those de novo enhancers may still quantitatively modify the transcript level within the cell or activate transcription in related cell types within the same domains , these results favour the hypothesis of redundant enhancer . This hypothesis is supported by the recent finding that redundant enhancers confer phenotypic robustness [40] , [41] and thus are likely to be selected for . Similar to TFBS turnover by the de novo emergence of new binding sites [42] , complete enhancers may also be turned over , leading to the disappearance of the ancestral element .
It has long been thought that new functions emerge primarily by duplication and/or modification of existing functional elements [43] . On the gene level , this view has begun to change with the recent publication of several studies reporting the de novo origin of genes in yeast [44] , drosophila [45] , and human [46] . In this study we show that not only genes but also enhancers can be de novo generated . De novo genesis of enhancers raises the question of how evolution can produce such complex functional elements . Indeed , enhancers were generally believed to have a stringent regulatory code , and thus the odds for generating a de novo enhancer were believed to be low . Recent studies have already started challenging that view by pointing either to the flexibility of this code [18] , [47] or the rapid turnover of binding sites [14] , [15] , [42] . It is possible that the appearance of new binding sites can not only modify pre-existing enhancer but also lead to the creation of completely new autonomous enhancers . This work further shows the relative “facility” of conferring regulatory activities to non-regulatory sequences . Consequently , the birth of regulatory elements is a highly dynamic property of vertebrate genomes and should also be considered as an evolutionary toolkit for innovation . The results of this study have significant implications , notably in the gene regulation and medical genetic fields by pointing out that genomic variation could lead to the generation of enhancers in regions with no apparent regulatory function . As such variation may also lead to altered gene expression , more attention should be devoted to variation in so-called “neutral” DNA . | The genome of each living organism contains thousands of genes , and the precise control of the timing and location of expression of these genes is key for normal development and homeostasis of each individual . Despite the oftentimes high genetic similarity between organisms , the source of phenotypic differences , for example between human and mouse , is thought to originate mainly from changes in how and when genes are expressed . This is partially determined by enhancers , that contribute to the control of gene expression . For decades , duplication of existing genomic enhancers , mobile elements , and changes in the sequence of existing enhancers were believed to be the major ways of increasing the number and modifying the activity of enhancers . In this study , we show that enhancers don't have to be derived from pre-existing ones but can also appear de novo in regions of the genome that were previously not regulating gene expression . We analyzed teleost fish genomes and found three regions for which a limited number of changes in the DNA sequence was sufficient to generate new enhancers . We predict that such a process is frequent in vertebrate genomes , making de novo generation of enhancers an important mechanism for creating variation in gene expression . | [
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"b... | 2011 | De Novo Genesis of Enhancers in Vertebrates |
Different functional constraints contribute to different evolutionary rates across genomes . To understand why some sequences evolve faster than others in a single cis-regulatory locus , we investigated function and evolutionary dynamics of the promoter of the Caenorhabditis elegans unc-47 gene . We found that this promoter consists of two distinct domains . The proximal promoter is conserved and is largely sufficient to direct appropriate spatial expression . The distal promoter displays little if any conservation between several closely related nematodes . Despite this divergence , sequences from all species confer robustness of expression , arguing that this function does not require substantial sequence conservation . We showed that even unrelated sequences have the ability to promote robust expression . A prominent feature shared by all of these robustness-promoting sequences is an AT-enriched nucleotide composition consistent with nucleosome depletion . Because general sequence composition can be maintained despite sequence turnover , our results explain how different functional constraints can lead to vastly disparate rates of sequence divergence within a promoter .
The advent of genome sequencing introduced the practice of searching for regulatory elements in evolutionarily conserved regions [1]–[5] . However , functional elements are by no means strictly confined to regions of high primary sequence conservation [6]–[9] . In fact , cis-regulatory elements can retain functionality over great evolutionary distances despite sharing little or no identifiable sequence similarity , and can correctly drive reporter gene expression when placed in a distantly related species [10]–[12] . Two questions arise from these observations . First , how do different functional constraints account for different degrees of sequence conservation ? Whereas the relationship between function and sequence conservation in not well understood in general , this problem is particularly acute for cis-elements [13] . A major obstacle is that we do not have a cis-regulatory code akin to that for protein-coding sequences . For example , even within conserved cis-regulatory elements there are interspersed nonconserved sequences that seem to be important for their function [12] , [14]–[18] . In other cases , cis-regulatory architecture can be cryptically conserved despite sequence divergence [19]–[21] . In yet other promoters , not even the architecture appears to be conserved [22] , [23] . Second , since gene expression is increasingly considered to be a quantitative trait for which populations vary [24] , [25] , functional comparisons of regulatory elements ought to be made with quantitative measurements across populations of individuals [26] or cells [27] . Only then can expression patterns be compared in terms of how much they differ , and how intrinsically variable they are . Variation of gene expression can take many forms , for instance the number of cells expressing a gene or the amount of transcript made in individual cells . Despite variation , gene expression , like many other biological processes , exhibits substantial robustness , that is , resilience to perturbations by genetic and environmental challenges [28]–[31] . Robustness of expression , much like pattern of expression , is encoded in regulatory elements [32] , [33] . One way of encoding robustness in cis is with redundant or “shadow” enhancers [34] . The loss of one “shadow” enhancer does not substantially perturb gene expression , unless the organism is challenged by genetic or environmental stresses [35] , [36] . Another documented mechanism that confers robustness in cis is the presence of miRNA target sites in 3′ UTR [37] , [38] . Our goal is to understand the relationship between function and sequence evolution in a single cis-element . We studied a promoter of the Caenorhabditis elegans unc-47 gene , which drives a simple , easily quantifiable expression pattern . This promoter contains regions of high and low sequence conservation when compared to orthologs from four closely related [39] Caenorhabditis nematodes . We quantified functional similarities and differences of these promoters to infer the constraints that gave rise to the observed patterns of sequence evolution .
We first tested the hypothesis that an evolutionarily conserved expression pattern results from evolutionarily conserved regulatory sequences alone . In C . elegans , the unc-47 gene is expressed in all 26 GABAergic neurons , including 19 D-type neurons of the ventral nerve cord and the postanal cell DVB ( Figure 1A ) [40] . We selected these cells because they are easy to recognize due to a characteristic morphology , and they reside close to the body surface , thus easing the quantification of expression . The endogenous pattern of unc-47 is recapitulated when a reporter construct containing a 1 . 2 kb sequence immediately 5′ of the gene ( we refer to it as a full-length promoter as it extends to the locus of the upstream gene ) is used to drive green fluorescent protein ( GFP ) in C . elegans ( Figure 1B ) . A construct containing a promoter of the same length of the C . briggsae unc-47 ortholog is expressed in a qualitatively indistinguishable pattern in C . briggsae ( Figure 1C ) . Indeed the C . briggsae promoter drives expression in the same neurons even in C . elegans ( see below ) . These results suggest that expression patterns of unc-47 orthologs have been conserved since their common ancestor and that the information required for driving proper expression is contained within ∼1 . 2 kb promoters upstream of the genes . Because expression patterns of nematode unc-47 orthologs are conserved , we investigated whether expression is mediated solely by conserved cis-regulatory elements . We aligned the C . briggsae sequence along with those of two other close relatives C . brenneri and C . remanei , to the C . elegans unc-47 promoter . As reported previously [41] , sequence conservation in this promoter is heavily biased to the most proximal ∼250 bp ( Figure 1D , Figure S1 , Table S1 ) . We carried out extensive analyses which showed that little sequence conservation can be found distal to the ∼250 bp boundary ( Figure S2 , Table S1 ) . This does not exclude the possibility that there exist short and conserved motifs in the distal promoter; they are simply below our level of detection . Some may exist and even be functional; nonetheless , the rates of sequence divergence are profoundly different between the proximal and the distal portions of this promoter . If the conserved expression patterns result from solely the conserved portions of the cis-regulatory elements , then the proximal promoters of both C . elegans and C . briggsae should be sufficient to recapitulate the entire pattern . We therefore compared functions , in C . elegans , of both full-length and proximal promoters ( Figure 1E ) derived from C . elegans and C . briggsae . Strains bearing each of these four constructs exhibited qualitatively similar patterns of expression . However , we noticed that the proximal C . briggsae promoter was not robust – it drove both weak and inconsistent expression . In contrast , a robust promoter would express strongly and consistently , as do the full-length promoters . We next quantified and compared expression patterns driven by these promoters . The expression patterns driven by the proximal and full-length promoters from both species were qualitatively correct , that is , all cells that were expected to show reporter gene expression were GFP-positive in at least some of the examined animals . To obtain a precise measure of variability , we counted the number of D-type neurons that were expressing GFP in 200 individuals bearing each construct . We examined animals from multiple independent strains for each construct and found that overall inter-strain variance was modest for all constructs ( data not shown ) . We conducted the counts in a blinded fashion to exclude the possibility of unconscious experimenter bias ( see Methods ) . The results of these counts address the first aspect of robustness – consistency of expression pattern . We found that the full-length C . elegans promoter drove somewhat more consistent pattern than the proximal promoter ( Figure 1F; Wilcoxon test , p = 3 . 2×10−3 ) , and that the full-length promoters of C . elegans and C . briggsae were indistinguishable ( p = 0 . 7 ) . The C . briggsae proximal promoter was not expressed as consistently in D-type neurons as the full-length promoter ( Figure 1G; Wilcoxon test , p = 3 . 4×10−8 ) . In a parallel approach we quantified the intensity of GFP fluorescence in DVB and D-type neurons . This allowed us to assess the second aspect of robust expression – consistency of relative expression levels from one cell type to another within an individual . Expression levels in D-type neurons and DVB were relatively similar in animals carrying the full-length promoter ( note the mean ratio of one and a tight , normal scatter , Figure 1H ) . In contrast , individuals with the proximal promoter exhibited a significant increase in variance ( Ansari-Bradley test , p = 1 . 6×10−3 ) , despite a lower relative expression in DVB ( Wilcoxon test , p = 1 . 8×10−5 ) . We thus concluded that the C . briggsae proximal promoter directs less robust expression than the full-length promoter . To ensure that the apparent decrease in robustness of the proximal promoter was not an artifact of using extrachromosomal arrays , we generated transgenic strains in which single-copy full-length or proximal promoters were integrated into the same genomic location . Whereas the absolute levels of expression were considerably lower for all integrated strains ( 20–400 fold ) , the shorter promoter was weaker than the full-length ( 4–6 fold ) and significantly less consistent in its expression ( Figure S3; Wilcoxon test , p = 1 . 9×10−10 ) . Thus the shorter promoter was weaker and less consistently expressed regardless of whether it was tested as an integrated or extrachromosomal transgene . This concordance allowed us to utilize extrachromosomal transgenes for the remainder of this study , because integrated strains showed weak expression that was at the limit of detection . It is formally possible that our observation of the decreased robustness of the proximal promoter compared to the full-length version was due to a peculiar nature of the C . briggsae regulatory sequence . We therefore tested orthologous cis-regulatory sequences of two additional species , C . brenneri and C . remanei , in C . elegans . Their full-length promoters drove GFP in a strong and consistent pattern , statistically indistinguishable from those of C . elegans and C . briggsae orthologs ( Figure 2A , 2B ) . Both proximal promoters , truncated at the orthologous position at the boundary of conserved sequences around 250 bp , directed weaker ( Figure 2C , 2D ) and less robust ( Figure 2E , 2F; Wilcoxon test , C . brenneri p = 1 . 2×10−13 and C . remanei p = 1 . 3×10−13 ) expression in D-type neurons . Expression of the proximal promoters was also less consistent in the tail neuron DVB ( Figure 2G , 2H ) . Our results suggest that the cis-regulatory elements of unc-47 from the four examined nematodes have similar architectural properties – the proximal , highly conserved promoter is sufficient to deliver the qualitatively correct expression pattern , whereas the distal , nonconserved portion is required for consistent expression . It is important to note that this distal sequence is not alone sufficient to direct any expression in D-type neurons or DVB [41] . It therefore contributes to robustness via a mechanism different from that of recently described “shadow” enhancers [35] , [36] , each of which is sufficient to drive expression independently . Furthermore “shadow” enhancers are conserved , whereas the distal promoter of unc-47 is not . Distal promoters were required for stronger and more consistent expression , even when worms were reared under constant and nearly optimal growth conditions ( 20°C ) . We tested whether these sequences could also buffer against environmental challenges . We compared GFP expression levels directed by the full-length and proximal promoters in worms reared at a high temperature of 26°C and a low of 15°C . We measured the intensity of GFP-fluorescence in D-type neurons and DVB and observed several trends . First , expression levels driven by the full-length C . elegans promoter ( Figure 3A ) were more consistent than those driven by the proximal promoter ( Figure 3B ) at both the 26°C ( Kolmogorov-Smirnov test , p = 2 . 9×10−5 ) and 15°C ( p = 1 . 2×10−6 ) . Second , the full-length promoter was comparably consistent in its expression at 26°C and 15°C ( Figure 3A , Table S2 ) . In contrast , consistency of expression of the proximal promoter differed dramatically between the two temperatures ( Figure 3B , Table S2 ) . Similar results were observed for the C . briggsae promoters . The full-length promoter ( Figure 3C ) directed more consistent expression than the proximal promoter ( Figure 3D ) at both temperatures ( Kolmogorov-Smirnov test , at 26°C p = 1 . 2×10−2 , at 15°C p = 2 . 2×10−14 ) . Temperature had a minor effect on the consistency of expression of the full-length promoter , but a more substantial effect on the proximal promoter ( Table S2 ) . We repeated measurements for multiple independent strains carrying full-length and proximal promoters from C . elegans and C . briggsae and observed concordant results ( Figure S4 , Table S2 ) . We concluded that full-length promoters are more robust to temperature stress , regardless of their species of origin ( compare Figure 3A and 3C ) . Proximal promoters , primarily composed of conserved sequences , were significantly less robust , particularly after the cold treatment ( Figure 3B and 3D ) . These results indicate that a robustness-conferring function is encoded in distal promoters in both species , and is thus conserved despite the lack of detectable sequence conservation . We dissected the distal promoters to determine which of their components were necessary for robust expression . The proximal promoters contain all of the densely arranged blocks of sequence conservation . Additionally , a pair of short motifs ( 8 and 6 bp ) that is shared by all four examined nematodes is located approximately 50 bp distal to the boundary of greatest conservation ( 1 ) . We considered the distal extent of these motifs to be the absolute boundary of the evolutionarily conserved promoter sequence , because in the remaining distal promoter there were no sequences longer than 10 bp that were shared by all four species . We tested a promoter encompassing all of this “extended conservation” for the ability to drive robust expression . It performed intermediately in terms of consistency of expression between the full-length C . briggsae promoter ( Figure 4A; Wilcoxon test , p = 1 . 4×10−2 ) and the proximal promoter alone ( p = 4 . 0×10−3 ) . We next examined intensity of GFP expression in the D-type neurons and DVB in animals reared under temperature stress . At 15°C , although not at 26°C , this promoter produced more variable expression than the full-length C . briggsae promoter ( compare Figure 4B and Figure 3C; Kolmogorov-Smirnov test , p = 5 . 2×10−4 ) , but significantly less variable expression than the proximal promoter ( compare Figure 4B and Figure 3D; p = 7 . 7×10−5 ) . Therefore the two conserved motifs and the sequences that surround them contribute to , but do not entirely account for the robustness of the longer promoter . Our results suggest that , despite substantial sequence divergence , distal promoters of C . elegans and C . briggsae unc-47 confer robust expression to their respective proximal promoters ( Figure 1F , 1G , Figure 3 ) . To test whether distal promoters confer robustness in a species-specific manner , we asked whether the distal promoter of C . elegans could restore robust expression when fused to the proximal promoter of C . briggsae . We reasoned that if the distal and proximal sequence function as a unit and make up a single cis-regulatory element , the distal part of which has diverged considerably in its sequence , we should expect a chimeric construct not to rescue robustness . If , on the other hand , the proximal , highly conserved promoter and the distal promoter are two distinct functional units , they should be modular . The C . elegans-distal-C . briggsae-proximal chimeric unc-47 promoter drove expression with a consistency intermediate between the full-length and proximal promoters in terms of cell number ( Figure 4C; Wilcoxon test , different from C . briggsae full-length p = 8 . 0×10−3; different from C . briggsae proximal p = 5 . 6×10−3 ) . However , at both 15°C and 26°C this promoter was no more variable than the full-length C . briggsae construct ( Figure 4D; Kolmogorov-Smirnov test , at 26°C p = 0 . 6 , at 15°C p = 0 . 1 ) , constituting a significant rescue of robustness relative to the proximal promoter alone ( Kolmogorov-Smirnov test , at 26°C p = 4 . 6×10−4 , at 15°C p = 1 . 2×10−10 ) . Because much , although perhaps not all , of the robustness of expression can be rescued by this chimeric construct , we conclude that the proximal and distal sequences encode distinct and separable regulatory functions . Multiple chimeric and “extended conservation” constructs were consistent with these results ( Figure S5 , Table S2 ) . The robustness function of the distal element must have much less stringent sequence requirements than the proximal promoter , because distal sequences have diverged considerably but maintain this function . We next tested whether another genomic fragment lacking detectable sequence similarity to the distal unc-47 sequences could confer robustness of expression . We selected an approximately 1 . 3 kb fragment upstream of unc-15 because it does not share significant similarity with the C . briggsae unc-47 distal promoter ( Figure S2 ) . Furthermore , unc-15 encodes a paramyosin ortholog that is expressed in muscles [42] , and thus is not expressed in any of the same cells as unc-47 . The overall length of this sequence is comparable , however , and it is also an intergenic sequence as poorly conserved between C . elegans and C . briggsae as is the distal portion of the unc-47 promoter ( data not shown ) . We were surprised to find that the chimeric promoter containing this distal C . briggsae unc-15 sequence fused to the proximal C . briggsae unc-47 promoter displayed robust expression as consistent as the full-length C . briggsae unc-47 promoter in terms of cell number ( Figure 4E; Wilcoxon test , p = 0 . 37 ) . We observed markedly improved consistency of the expression pattern over the C . briggsae proximal promoter alone ( Figure 4F; difference from proximal promoter , Wilcoxon test , p = 1 . 3×10−5 ) . At 26°C this promoter drove as consistent expression as the full-length C . briggsae promoter ( Kolmogorov-Smirnov test , at 26°C p = 0 . 1; compare Figure 4F , Figure S5 and Figure 3C ) . Whereas at 15°C , it was less consistent than the full-length C . briggsae promoter ( Kolmogorov-Smirnov test , at 15°C p = 2 . 4×10−4 ) , it was significantly more consistent than the proximal promoter at both temperatures ( compare Figure 4F , Figure S5 and Figure 3D; Kolmogorov-Smirnov test , at 15°C p = 4 . 1×10−7 , at 26°C p = 1 . 4×10−5 ) . Next , we tested whether another non-conserved intergenic sequence , from upstream of the C . briggsae promoter of gene unc-25 could rescue robustness of the proximal C . briggsae promoter of unc-47 . Unlike unc-15 , unc-25 is co-expressed with unc-47 [43] , yet it shares no detectable sequence similarity within promoter elements ( data not shown ) . It did indeed show substantially increased robustness of expression , comparable to the full-length promoter ( Figure S6; indistinguishable from C . briggsae full-length Wilcoxon test , p = 0 . 4; different from C . briggsae proximal Wilcoxon test , p = 1 . 3×10−5 ) . These results show that unrelated intergenic sequences are capable of conferring robust expression on a proximal promoter that directs the pattern . To understand why such different sequences were able to restore robustness of expression of the proximal C . briggsae unc-47 promoter , we examined them for general features they might have in common . Specifically , we calculated nucleotide frequencies in the distal unc-47 , unc-15 and unc-25 promoters , and compared them to those of the 1 . 1 kb of vector DNA sequence that lies distal to all of the inserted promoters . Since this vector sequence , when it lies directly upstream of the proximal promoter , is not able to confer robustness , we sought out features that are shared by distal promoters but not the vector sequence . Dinucleotide frequencies differ dramatically between distal unc-47 , unc-15 and unc-25 promoter sequences and the upstream vector sequence . There is systematic enrichment for two dinucleotide classes , relative to the vector sequence , and a depletion of two other dinucleotide classes ( Figure 5A ) . While there are between-sequence enrichment differences , the overall biases towards the AA/TT dinucleotides and away from the GC/CG dinucleotides is consistent among all sequences that confer robustness . This analysis suggests a simple hypothesis , namely that AT-enriched sequences ( more specifically those enriched for AA/TT dinucleotides ) should promote robust expression , whereas sequences depleted for these dinucleotides and enriched for GC/CG pairs ( and to some extent CC/GG pairs ) should not . To test this prediction , we subdivided the genome of C . elegans into 1 kb fragments , matching in size the previously tested distal sequences , and computed the extent of their AT-enrichment . A sequence located downstream of the daf-25 locus is enriched for AA/TT dinucleotides to an extent similar to distal promoters of unc-47 , unc-15 and unc-25 . This 1 kb fragment , when placed upstream of the proximal promoter of C . briggsae unc-47 , was able to confer robustness similarly to the distal unc-47 promoter ( Figure 5B; indistinguishable from C . briggsae full-length Wilcoxon test , p = 0 . 09; different from C . briggsae proximal Wilcoxon test , p = 1 . 9×10−5 ) . In contrast , a 1 kb AT-depleted sequence from the let-2 locus was unable to rescue robustness ( Figure 5C; different from C . briggsae full-length Wilcoxon test , p = 1 . 1×10−5; indistinguishable from C . briggsae proximal Wilcoxon test , p = 0 . 14 ) . Furthermore , the construct containing the daf-25 sequence drove a more consistent expression than the one containing the let-2 sequence ( Wilcoxon test , p = 4×10−3 ) . To ensure that the ability to rescue expression robustness is not restricted to AT-enriched sequences from nematode genomes , we tested whether sequences from distantly related species can perform this function . We segmented the genome of D . melanogaster into 1 kb fragments and selected one AT-enriched and one AT-depleted sequence using the same criteria as were applied to the fragments from the C . elegans genome . As predicted , a construct carrying the AT-enriched sequence drove substantially more robust expression than the proximal promoter alone ( Figure 5D; indistinguishable from C . briggsae full-length Wilcoxon test , p = 0 . 2; different from C . briggsae proximal Wilcoxon test , p = 1 . 5×10−5 ) . A construct carrying the AT-depleted sequence was no more robust than the proximal promoter alone ( Figure 5E; different from C . briggsae full-length Wilcoxon test , p = 3 . 7×10−15; indistinguishable from C . briggsae proximal Wilcoxon test , p = 0 . 04 ) . Together these results suggest three important conclusions . First , AT-enrichment of a sequence can predict its ability to confer robustness of expression . Second , because two different AT-depleted sequences were not able to improve consistency of transgene expression , it is unlikely that robustness results from simply separating the proximal promoter from unknown repressive effects of the vector sequence . Sequence composition must play a critical role . Third , because multiple unrelated nematode sequences and an AT-enriched Drosophila sequence conferred robust expression , it is unlikely that short , gene- or species-specific motifs play a major role in improving consistency of expression . Our data imply that the mechanism responsible for conferring expression robustness relies on the overall nucleotide composition of promoters rather then on specific sequence motifs .
Our results suggest that promoters of Caenorhabditis unc-47 orthologs are organized into two domains that are markedly distinct in functions and evolutionary dynamics . Whereas proximal promoters are highly conserved and are sufficient to direct the appropriate spatial expression pattern , the distal sequences diverge rapidly and their primary function is to confer robustness of expression . The distal sequences within promoters of unc-47 are not capable of directing expression patterns on their own [41] and must therefore confer robustness via a mechanism distinct from redundant and evolutionarily conserved “shadow” enhancers [35] , [36] . The shared nucleotide composition ( Figure 5A ) of the four sequences that promote robust expression – distal promoters of C . elegans and C . briggsae unc-47 as well as upstream regions of two unrelated genes , unc-15 and unc-25 – hints at a potential mechanism of action . Overall sequence composition plays a large role in establishing chromatin states throughout the genome [44] . In particular , AT-rich sequences tend to be associated with nucleosome-poor regions , although multiple factors determine whether DNA is bound to nucleosomes . Recent studies suggest that sequence-composition codes that displace nucleosomes may be common in active metazoan promoters [45] , [46] . Intriguingly , the genomic sequence precisely corresponding to the distal , nonconserved portion of the C . elegans unc-47 promoter is depleted of nucleosomes [47] ( Figure S7 ) . Trinucleotide frequencies are a better predictor of nucleosome positioning than dinucleotides [47] . The robustness-conferring sequences are two-fold enriched for trinucleotides that are preferentially found in nucleosome-depleted regions of the C . elegans genome , far more so than the conserved proximal promoters ( Figure S7 ) . Nucleosome occupancy can differ even in evolutionarily conserved promoters [46] , [48] , [49] , still similar levels of enrichment for nucleosome-depleted trinucleotides were seen in the distal unc-47 promoters of C . brenneri and C . remanei ( Figure S7 ) . All sequences that confer robustness bear a signature consistent with nucleosome depletion , and the C . elegans sequences were shown to be depleted of nucleosomes ( Figure S7 ) . The AT-poor let-2 locus , on the other hand , is enriched for nucleosomes , and other sequences which are unable to improve consistency of expression , show a trinucleotide signature of nucleosome enrichment ( Figure S7 ) . We therefore hypothesize that open chromatin may promote robust expression . We favor the hypothesis that the robustness function is executed by configuring chromatin in an accessible state for other factors to bind the promoter sequence . This hypothesis is consistent with the finding that variability of gene expression may be encoded in nucleosome-positioning sequences [50] , and that chromatin regulators may contribute to environmental canalization [51] . Whether this mechanism of robustness arises as a byproduct of other forces that shape nucleotide composition of intergenic sequences , or whether it is directly selected upon , it has been conserved at the unc-47 locus . We propose a simple scenario to account for the different evolutionary rates between the distal and proximal portions of the unc-47 promoter . The proximal promoter is responsible for directing the expression pattern because it contains numerous transcription factor binding sites . It appears that in the context of the proximal promoter most substitutions are deleterious and thus it evolves relatively slowly . The distal promoter , on the other hand , evolves at a considerably faster rate . Noting that the ability to confer robustness is conserved between distal promoters of unc-47 orthologs , we infer that it is maintained by selection that does not require maintenance of specific sequence identity . Indeed , unrelated sequences from the C . elegans unc-15 , unc-25 , and daf-25 loci and even an AT-rich sequence from D . melanogaster can rescue robustness of expression . Thus the distal promoters appear to be under a simpler constraint – they are only required to maintain a certain nucleotide composition , for instance that which is consistent with nucleosome depletion , to confer robustness of gene expression . Sequences that satisfy this requirement are quite degenerate , so the element tolerates a relatively high rate of sequence turnover , while retaining functional conservation . This hypothesis is consistent with a report of selection on sequence composition that encodes nucleosome organization in yeast [52] . We consider the distal promoter of the unc-47 gene to be an example of a weakly constrained functional sequence [53] . Such low constraint allows developmental systems drift [54] , in which conserved molecular functions are mediated by divergent genetic systems .
To generate reporter constructs , promoter sequences were PCR amplified from genomic DNA and cloned upstream of GFP into pPD95 . 75 . In all cases , reverse primers overlapped the start codon of the unc-47 ortholog . Prior to injections , constructs were sequenced to ensure accuracy . Precise boundaries of full-length , extended conservation and proximal constructs are given in Figure S1 . To generate strains carrying extrachromosomal arrays , we injected a mixture ( 5 ng/µL promoter::GFP plasmid , 5 ng/µL pha-1 rescue construct , 100 ng/µL salmon sperm DNA ) into C . elegans pha-1 ( e2123 ) strain [55] . Transformants were selected at 25°C . The C . briggsae strains carrying Cbr promoter unc-47::GFP were produced by injecting a mixture ( 5 ng/µL promoter::GFP plasmid and 100 ng/µL salmon sperm DNA ) into AF16 strain . Single copy integrated strains were generated following an established protocol [56] . Copy number of inserts was verified through quantitative PCR of GFP ( normalized to genomic unc-47 ) . Mixed-stage populations of C . elegans carrying transgenes were grown at 20°C with abundant food and young adult- or L4-stage worms were selected . These were immobilized on agar slides with 100 mM NaN3 in M9 buffer . The slides were examined on a Leica DM5000B compound microscope under 400× magnification . Each worm was positioned such that the ventral nerve cord with its D-type neurons could be seen clearly , and the number of cell bodies expressing GFP were counted manually . Worms without any visible GFP expression were assumed to have lost the transgene . For each construct studied , multiple independent transgenic lines were generated , and final counts of 100–200 individuals ( see figure legends/text for details ) were derived from a mixture of these lines ( inter-line variance is generally low ) . To mitigate against experimenter bias census counts were taken in a blinded fashion . Individual strains were coded by one investigator to obscure their identity . Another investigator then examined 100 individuals of each of these strains . Once all counting was finished , strain identities were revealed and data were analyzed . Intensity of GFP expression in individual cells was measured on a Leica DM5000B compound scope fitted with a Qimaging Retiga2000 camera . Images of cells were outlined in imageJ , average intensity was measured and the background subtracted . Multiple strains carrying the same transgene were examined throughout and tested for concordance . For integrated strains we used 125 ms exposure , 100% excitation . Pictures of 7 cells ( DD1 , VD1 , VD2 , DD3 , VD6 , VD13 , DVB ) were taken . For each strain and treatment ( 15°C , 20°C , 26°C ) 25 L4-staged worms were measured . For temperature stress experiments ( these were conducted on strains carrying extrachromosomal arrays ) worms were reared at 15°C or 26°C for at least two generations . Then 50 L4 individuals were mounted for each treatment and strain and intensity of GFP was measured ( 125 ms exposure , variable excitation ) for D-type neurons ( average values recorded ) and DVB . All statistical analyses were performed in R . In all cases , the logarithm of measured GFP intensity was used . Wilcoxon test was used to assess consistency of the number of cells expressing different constructs . To assess the amount of scatter in fluorescence measurements ( data reported in Figure 3 , Figure 4 , Figures S4 and S5 , and in Table S2 ) , we computed geometric distances between all data points for a particular strain/treatment and the mean of that strain/treatment . To test whether distributions of distances derived in such a way were significantly different for different strains/treatments , we conducted Kolmogorov-Smirnov tests . We used Ansari-Bradley test to determine whether the relative DVB fluorescence was more variable for proximal compared to full-length promoters . | Comparison between genome sequences of different species is a powerful tool in modern biology because important features are maintained by natural selection and are therefore conserved . However , some important sequences within genomes evolve considerably faster than others . One possible explanation is that they encode little or no function . Alternatively , they may evolve under different constraints that permit sequence turnover while maintaining function . Here we report that the promoter of the unc-47 gene of C . elegans contains two discrete elements . One has a highly conserved sequence that determines the spatial expression pattern . Another shows no sequence conservation , but it makes expression of the gene robust , that is , consistent between individuals and resilient to environmental challenges . Remarkably , multiple unrelated sequences are capable of promoting robust expression . Nucleotide composition of these sequences suggests that open chromatin may play a role in conferring robustness of gene expression . Because general sequence composition and therefore expression robustness can be maintained despite sequence turnover , our results offer an explanation of how rapidly diverging promoter elements can nevertheless remain functionally conserved . | [
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] | 2011 | Distinct Functional Constraints Partition Sequence Conservation in a cis-Regulatory Element |
Genomes must balance active suppression of transposable elements ( TEs ) with the need to maintain gene expression . In Arabidopsis , euchromatic TEs are targeted by RNA-directed DNA methylation ( RdDM ) . Conversely , active DNA demethylation prevents accumulation of methylation at genes proximal to these TEs . It is unknown how a cellular balance between methylation and demethylation activities is achieved . Here we show that both RdDM and DNA demethylation are highly active at a TE proximal to the major DNA demethylase gene ROS1 . Unexpectedly , and in contrast to most other genomic targets , expression of ROS1 is promoted by DNA methylation and antagonized by DNA demethylation . We demonstrate that inducing methylation in the ROS1 proximal region is sufficient to restore ROS1 expression in an RdDM mutant . Additionally , methylation-sensitive expression of ROS1 is conserved in other species , suggesting it is adaptive . We propose that the ROS1 locus functions as an epigenetic rheostat , tuning the level of demethylase activity in response to methylation alterations , thus ensuring epigenomic stability .
In plants , animals , and fungi , DNA methylation is used to repress the transcription of potentially harmful DNA sequences [1] . Targets include long transposable elements ( TEs ) that have intact open reading frames and primarily reside in heterochromatin and shorter TE fragments that are prevalent in euchromatic gene-rich regions . In plants , DNA methylation is dynamically regulated during development and in response to external perturbations . Many of these changes occur at TEs or TE-derived sequences . Examples include modest DNA methylation changes in gene-proximal regions upon exposure to bacteria or bacterial elicitors [2 , 3] and DNA demethylation of TEs in the 5' regions of stress response genes during fungal infection [4] . Dynamic methylation changes have also been implicated in the regulation of genes in response to abiotic signals [5 , 6] . Furthermore , DNA methylation is dynamic during reproductive development . DNA demethylation in the female gametophyte is important for establishing gene imprinting in the endosperm after fertilization [7] . During male gametogenesis , the sperm become hypomethylated in certain sequence contexts [8] . Similar to other dynamic changes , the removal of methylation in gametophytes occurs largely at TE fragments in euchromatin . DNA methylation patterns are a product of methylation and demethylation activities , but how these opposing activities are balanced in the genome is unknown . In plants , DNA methylation is established and maintained in different cytosine sequence contexts by genetically distinct pathways . Euchromatic TEs in Arabidopsis and maize are primarily targeted for cytosine methylation through the process of RNA-directed DNA methylation ( RdDM ) , which results in cytosine methylation in all sequence contexts ( CG , CHG , and CHH , where H represents any base other than G ) [1 , 9] . This process is initiated by transcription of non-coding RNAs by a specialized RNA polymerase unique to plants , RNA Pol IV . These non-coding RNAs are then converted into dsRNAs by the RNA-dependent RNA polymerase RDR2 . Small 24 nt RNAs generated from these transcripts are then loaded into AGO4 . The small RNAs are thought to interact with non-coding transcripts that are generated by a second plant-specific polymerase , RNA Pol V [10] , resulting in the recruitment of the de novo methyltransferase DRM2 and sequence-specific DNA methylation . 21–22 nt small RNAs generated through an RDR6-dependent pathway can also direct de novo methylation independently of RNA Pol IV [11 , 12] . Positive feedback between existing and de novo DNA methylation reinforces silencing [13 , 14] . Maintenance of asymmetric CHH methylation requires continual de novo methylation by RdDM . Other processes maintain DNA methylation in the CG and CHG sequence context . CG DNA methylation is maintained by the maintenance methyltransferase MET1 in conjunction with VIM methyl-binding proteins . CHG methylation is maintained by CMT3 and is positively reinforced by histone H3K9 dimethylation [15] . By contrast , TEs in heterochromatic sequences are methylated by CMT2 with the assistance of the nucleosome remodeler DDM1 [16 , 17] . Because there is positive feedback between methylation and further RdDM activity and because many RdDM targets are near genes , it is important that mechanisms are in place to protect genes from potentially detrimental hypermethylation . In the Arabidopsis genome , 44% of genes have a TE within 2 kb of the transcribed region [18] , potentially creating a conflict between TE suppression by RdDM and gene expression . DNA methylation is opposed by 5-methylcytosine DNA glycosylases that remove methylcytosine from DNA by base excision repair . Plants with mutations in the three DNA glycosylases expressed in somatic tissues , ROS1 , DML2 , and DML3 , gain methylation in all sequence contexts in gene proximal regions , primarily around TEs and TE-derived sequences [19 , 20] . DNA demethylation is therefore important to protect genes from RdDM spreading . This has been demonstrated at several loci . For example , the EPF2 gene , which is associated with a methylated TE approximately 1 . 5 kb 5’ of its transcriptional start site , gains methylation in the region between the TE and 5’ end of the gene in ros1 dml2 dml3 mutants , resulting in transcriptional silencing [21] . Although DNA methylation is primarily thought of as repressive to transcription [20 , 22] , expression of the DNA demethylase gene ROS1 is unexpectedly reduced in some DNA methylation mutants [23–26] . Whether this is a direct or indirect effect has not been demonstrated . These observations on ROS1 expression form the basis of our study . Here we describe the existence of a rheostat for genomic methylation activity . We find that RdDM and DNA demethylation activities converge on TE-derived sequences 5’ of ROS1 . In contrast to other genomic targets of these pathways , expression of ROS1 is promoted by the RdDM pathway and inhibited by demethylation by ROS1 . Thus the ROS1 locus functions as a self-regulating epigenetic rheostat , balancing input from both DNA methylation and demethylation to maintain homeostasis between these opposing systems .
Previous studies have shown that ROS1 expression is reduced in mutants in which DNA methylation is disrupted or altered [23–26] . Additionally , expression of the ROS1 gene is significantly reduced when plants are grown on the methyltransferase inhibitor 5-aza-2-deoxycytidine ( 5-azaC ) [24] ( Fig 1A ) . Here we systematically evaluated which DNA methylation pathways promote ROS1 expression by performing RT-qPCR on multiple Arabidopsis mutants that directly or indirectly alter DNA methylation . met1 plants have pleiotropic methylation phenotypes; methylation in CG , CHG and CHH sequence contexts is reduced genome-wide in combination with local regions of non-CG hypermethylation [20] . We observed extremely low levels of ROS1 transcripts in met1 and vim seedlings ( Fig 1B ) , as has been reported previously [23 , 24] . An approximately ten-fold decrease in ROS1 transcript levels was observed in eleven different RdDM mutants ( Fig 1C ) , consistent with previous findings that ROS1 expression is reduced in rdr2 , nrpd1a , nrpe1 , drd1 , and drm2 mutants [23 , 25] . RdDM is predominantly associated with transcriptional repression; therefore transcriptional activation of ROS1 by RdDM potentially represents an under appreciated function for this pathway . Transcripts from the related 5-methylcytosine DNA glycosylases DML2 and DML3 are present at much lower levels than ROS1 in wild-type tissues ( S1 Fig ) . Mutations in the RdDM pathway do not alter the transcript abundance of DML2 , and result in small reductions in DML3 ( S1 Fig ) . No significant changes to ROS1 transcript abundance were observed in CHG methyltransferase mutants ( Fig 1D ) , in mutants of key regulators of histone H3K9 methylation ( Fig 1D ) , which is tightly associated with CHG methylation [27] , in plants with mutations in genes required to establish non-CG methylation in heterochromatin [16 , 17] ( Fig 1E ) , or in plants with a mutation in the RDR6 gene , which can trigger de novo methylation independently of the canonical RdDM pathway [11 , 12] ( Fig 1E ) . Thus , ROS1 down-regulation in methylation mutants is restricted to mutations in MET1 and its cofactors , and mutations in the RdDM pathway . To test if ROS1 silencing in met1 or RdDM mutants was heritable , we crossed met1 , rdr2 , and drm1; drm2 plants to wild type and evaluated ROS1 expression in heterozygous F1 progeny . ROS1 expression remained reduced in MET1/met1 F1 progeny at levels about half that of wild type plants , regardless of whether the met1 plant served as the male or female parent in the cross ( Fig 2A ) . This suggests that the ROS1 allele inherited from the met1 parent remained silenced through meiosis . However , ROS1 expression was gradually restored as MET1/met1 progeny developed ( Fig 2B ) . Thus , erasure of met1-induced epigenetic changes and restoration of normal regulatory mechanisms at ROS1 likely takes place over multiple cell divisions . By contrast , ROS1 transcripts were restored to wild-type levels in F1 progeny of RdDM mutants crossed to wild type ( Fig 2C ) . Recently it has been shown that reduced expression of the histone demethylase gene IBM1 contributes to reduced ROS1 expression in met1 mutants [26] . However , we found that ROS1 expression is not reduced in ibm1 mutants ( Fig 1D ) , nor is IBM1 expression reduced in the RdDM mutants rdr2 and nrpd1a ( RNA Pol IV ) ( S2 Fig ) , suggesting that the decreased expression of ROS1 expression in RdDM mutants is IBM1-independent . Together these data indicate that the down-regulation of ROS1 observed in met1 and RdDM mutants represents distinct processes , which was further supported by methylation profiling of ROS1 in different mutant backgrounds , described below . To determine if the ROS1 locus is targeted directly by DNA methylation , we performed bisulfite PCR and sequencing of the entire ROS1 gene and 1 kb of 5’ flanking sequences ( Fig 3 , S3 Fig ) . In wild-type plants we identified two small regions where cytosines were methylated in CG , CHG , and CHH sequence contexts ( a hallmark of RdDM ) : a 228 bp region partially overlapping an AtREP5 Helitron TE directly upstream of ROS1 , and in sequences encoding exons 15–18 ( Fig 3 ) . Genome-wide chromatin-IP datasets [10 , 28] showed that peaks of the RdDM proteins NRPE1 ( RNA Pol V ) and AGO4 were present 5' of the ROS1 start codon , overlapping the nearby TE ( Fig 2 ) . This is the same region where an RNA Pol V transcript has been detected [10] . There were high levels of CHH methylation in this region , predominantly on the top strand ( Fig 2 , S3 Fig ) , and we identified multiple 24 nucleotide small RNAs directly matching this sequence from published datasets ( Fig 3 ) [29 , 30] . In addition , we detected multiple small RNAs matching the methylated exons within the ROS1 coding region , but these did not overlap with peaks in the AGO4 or NRPE1 ChIP datasets , consistent with the low levels of CHH methylation in this region ( Fig 3 ) . To determine the proximity of the 5' methylated region to the ROS1 transcriptional start site ( TSS ) , we performed 5' RACE using RNA from wild-type Col-0 seedlings and identified two transcription start sites , 26 and 442 bp 5’ of the ROS1 start codon ( S3 Fig ) , the latter of which is within 100 bp of the methylated region . We also profiled ROS1 methylation in met1 and rdr2 mutants . CG methylation was eliminated in met1 , but the ROS1 coding region was hypermethylated in the CHG context ( Fig 2 ) , as has been previously reported [26] . We did not observe any evidence for coding region hypermethylation in rdr2 mutants . Instead , there was a clear reduction in non-CG methylation 5’ of the ROS1 TSS in rdr2 plants , as typically occurs when RdDM activity is lost ( Fig 3 , S3 Fig ) . Thus the TE at the 5' end of ROS1 is the most likely candidate as the site of RdDM activity that promotes ROS1 expression , despite the fact that methylated TEs 5' of genes are typically associated with transcriptional repression [18 , 20 , 21] . Combined with the distinct behavior of ROS1 alleles inherited from met1 or rdr2 parents ( Fig 2 ) , we propose that the RdDM pathway acts to promote ROS1 expression via a different mechanism than does the MET1 pathway . Although our results suggest that ROS1 expression is positively correlated with DNA methylation at the ROS1 locus , reduced expression of ROS1 in RdDM mutants could be direct or indirect , for example due to altered expression of a ROS1 regulator . To distinguish between these possibilities we sought to restore DNA methylation at the ROS1 5’ region in an rdr2 mutant background and then observe the effect on ROS1 expression . We attempted to bypass the inability of the rdr2 mutant to make a dsRNA that initiates RdDM by expressing an inverted repeat transgene under the control of the constitutive 35S promoter in rdr2 mutants ( Fig 4A ) . Transcription of inverted repeat transgenes creates a double-stranded hairpin RNA that can be processed into small RNAs that direct DNA methylation [31] . We used inverted repeats corresponding precisely to the 228 bp ROS1 5’ region that is methylated in wild type . We screened rdr2 T1 plants for methylation of the ROS1 5’ region and focused on six lines for in-depth analysis of DNA methylation by bisulfite sequencing ( Fig 4B ) . Methylation in each of the six lines was restored to varying degrees , constituting an epiallelic series , with some lines exhibiting a methylation profile strikingly similar to wild type . Methylation occurred in all sequence contexts , indicative of RNA-directed DNA methylation . ROS1 expression was examined in leaves of each independent line by RT-qPCR ( Fig 4C ) . Remarkably , ROS1 expression was restored in rdr2 mutants when methylation of the 5’ region was restored . In a transgenic line with limited restoration of DNA methylation ( line #19 ) , ROS1 expression increased only marginally in rdr2 mutants ( Fig 4C ) . These data demonstrate that methylation of the 5’ sequence is sufficient to promote ROS1 expression , and eliminate the possibility that decreased expression of ROS1 in rdr2 mutants is caused by an indirect mechanism . We noticed that cytosines in the CG context 5’ of ROS1 were intermediately methylated at around 50% in wild-type tissues , with independent variance at every CG position in the sequence ( Fig 3 , S3 Fig ) . CG methylation is faithfully copied by MET1 during DNA replication , and so average methylation at symmetric CG sites is usually close to 0 or 100% [20] . The observed intermediate level of CG methylation and the low frequency of bisulfite clones fully methylated in the CG context ( S3 Fig ) suggested that active DNA demethylation might also be active at the 5’ sequence . We hypothesized that ROS1 might oppose RdDM to remove methylation at its own promoter . We performed bisulfite sequencing of the 5' methylated region in two missense mutants of ROS1 , ros1-2 [32] and ros1-7 , an allele encoding a protein with an E956K substitution in the ROS1 DNA glycosylase domain [33] . Symmetric CG methylation increased to nearly 100% in both mutants compared to their wild-type siblings , along with increases in non-CG methylation ( Fig 5A ) , indicating that ROS1 actively removes methylation from this region in wild-type plants . At other loci , removal of 5' methylation by ROS1 increases transcription [21] . We examined the effect of DNA demethylation by ROS1 on ROS1 transcription by performing RT-qPCR on ros1-2 and ros1-7 mutants . Because these are missense mutations , nonsense-mediated decay should not be a complicating factor in measuring transcript abundance . ROS1 transcripts were 2 to 4-fold more abundant in ros1 mutants ( Fig 5B ) . This suggests that active demethylation by ROS1 represses transcription of ROS1 , counteracting the function of the RdDM pathway , which promotes ROS1 expression . Thus ROS1 regulates the expression of its own gene , forming a negative feedback loop for demethylation activity . To determine if regulation of ROS1 by methylation might be adaptive , we assessed whether methylation-sensitive expression of ROS1 is conserved in other species . Arabidopsis lyrata , which diverged from A . thaliana approximately 10 million years ago , has two highly conserved paralogs of ROS1 in tandem in the genome , which we termed AlROS1a and AlROS1b ( Fig 6A ) . We performed a Bayesian reconstruction of the phylogeny of ROS1 homologs within all sequenced Brassicales ( Fig 6B ) and found that the duplication giving rise to the two ROS1 paralogs in A . lyrata occurred prior to the divergence of A . lyrata from A . thaliana . AtROS1 belongs to the same clade as AlROS1a , and no true homologs to AlROS1b exist in A . thaliana ( Fig 6B ) . The homolog to AlROS1b was likely lost in the lineage that gave rise to A . thaliana . AlROS1a and AlROS1b share a high degree of sequence similarity in their coding region , but no significant similarity in their upstream sequences . Only AlROS1a has an upstream region conserved with AtROS1 ( Fig 6A ) , including the presence of the same 5’ TE . The 5’ sequences are 78% identical over the first 1 . 4 kb . We performed bisulfite sequencing of the AlROS1a 5’ region ( Fig 6C ) and of the exonic sequences in AlROS1a and AlROS1b that match exons 15–18 in ROS1 ( S4 Fig ) . Although CG methylation was present in the 3’ exonic region of both paralogs , non-CG methylation was absent ( S4 Fig ) . Additionally , unlike A . thaliana , we did not find any small RNAs matching these exons for either AlROS1a or AlROS1b in a small RNA dataset from A . lyrata flowers [34] . By contrast , the methylation profile 5’ of AlROS1a was remarkably similar to the methylation profile 5' of AtROS1 ( Fig 6C and 6D and Fig 3 ) . Like AtROS1 , CG methylation in the 5’ region was at an intermediate level between 40–50% , suggesting that RdDM and active DNA demethylation might also simultaneously target AlROS1a . Pair-wise alignment of the sequences from each species showed that the methylation was present at conserved cytosines ( Fig 6D ) . Furthermore , we identified small RNAs from A . lyrata datasets [34] that are almost identical to the small RNAs associated with methylation at the 5' end of AtROS1 ( Fig 6D ) . The methylated sequence matching these RNAs is directly adjacent to a homolog of the AtREP5 TE upstream of AtROS1 ( Fig 6A ) . These data indicate that RdDM targeting to a region 5’ of the ROS1 TSS is evolutionarily conserved . To test whether the expression of either AlROS1 paralog was responsive to methylation alterations , A . lyrata seedlings were grown on varying concentrations of 5-azaC . AlROS1a but not AlROS1b transcripts were significantly decreased in seedlings grown on 5-azaC ( Fig 6E and 6F ) . Thus expression of the true A . lyrata homolog of ROS1 , AlROS1a , which has similar 5’ methylation and conserved small RNAs , is methylation-responsive . Together , these data suggest that the regulation of ROS1 by RdDM and DNA demethylation at 5’ sequences is conserved between A . thaliana and A . lyrata . Interestingly , in transcriptome datasets from shoot apical meristems or immature ears of Z . mays mop1 mutants ( Mop1 is an RDR2 homologue ) , expression of two DNA glycosylase genes with high homology to AtROS1 ( DNG101 and DNG103 ) was reduced 2 to 3 . 3-fold in comparison to wild type [35 , 36] . Reduced expression of ROS1 homologs has also been observed in the transcriptome of Z . mays RNA polymerase IV mutants [37] . We confirmed that DNA glycosylase expression is reduced in mop1 leaves by RT-qPCR ( S5 Fig ) . Both DNG101 and DNG103 have methylated TEs in their 5' region in all sequence contexts , suggesting that both loci could be direct targets of RdDM [38] . These data further suggest that regulation of DNA glycosylases by RdDM might be a general feature of angiosperms , and thus likely adaptive .
Our data demonstrate that ROS1 functions as a self-regulating epigenetic rheostat . RdDM and DNA demethylation activities converge at the ROS1 locus , but each activity has the opposite outcome on ROS1 transcript abundance as compared to typical targets of these processes ( Fig 7 ) . By establishing DNA methylation at the ROS1 locus in rdr2 mutants ( Fig 4 ) , we have conclusively shown that methylation of the 5’ sequence is sufficient to restore ROS1 expression . Thus reduced expression of ROS1 in rdr2 mutants is not caused by an indirect mechanism , such as decreased expression of another gene required for ROS1 expression or increased expression of a negative regulator of ROS1 . While the precise mechanism by which the activity of ROS1 is repressive and RdDM is activating remains unknown , we speculate that a protein that either negatively or positively regulates ROS1 may exhibit differential DNA binding affinity based on methylation of the underlying ROS1 5’ DNA sequence . Alternatively , it is possible that rather than DNA methylation itself , the act of RdDM could play a regulatory role . For example , occupancy , DNA melting or elongation by RNA polymerases IV or V could be required for positive regulatory factors to access ROS1 . Interestingly , RdDM in an intron of the MADS3 gene in Petunia has also been shown to be associated with transcriptional upregulation [39] . In this instance , it is likely that methylation of a short cis-element is necessary to confer increased expression . The reversal of methylation outcomes at ROS1 permits the genome to maintain gene expression ( promoted by DNA demethylation ) and genome defense ( TE silencing by RdDM ) in homeostatic balance . For example , if the genome were under stress from high TE transcriptional activity or invasion , RdDM activity might increase . Under these conditions , RdDM activity would promote the expression of ROS1 , so that the activity of demethylation at target genes would be maintained in equilibrium with the activity of RdDM in the genome ( Fig 7 ) . Conversely , if RdDM were less active , ROS1 expression would be reduced to prevent hypomethylation as a consequence of demethylation activity . The result is that the expression of ROS1 is always maintained in balance by its autoregulation ( Fig 7 ) , which may help underpin the regulation of epigenetic homeostasis within plants and explain why spontaneous changes to methylation are generally very rare [40 , 41] . This homeostatic balance may be dynamically modified in certain conditions , such as fungal or bacterial infections , where active demethylation of defense genes is important for resistance [2–4] . The rheostat may also be important during normal development . In pollen , DRM2 is expressed at a low level in microspores and sperm [8] . In agreement with our findings from drm2 and other RdDM mutants , ROS1 transcripts have not been detected in wild-type sperm [42] . Published methylation profiling data from pollen show that the ROS1 5’ region is hypomethylated in sperm cells , but not in the vegetative nucleus ( S6 Fig ) , where both DRM2 and ROS1 are expressed [42 , 43] . In the future , it will be important to determine whether disrupting the rheostat has consequences for the proper establishment of methylation patterns in sperm or in developing progeny after fertilization . In addition to the methylation-responsive regulation of ROS1 that we have described here , it is possible that additional mechanisms underlie epigenetic homeostasis in Arabidopsis . Targeting of RdDM , H3K9 methylation , and H3K27 methylation are redirected throughout the genome in met1 mutants [20 , 24 , 44] , and it has been hypothesized that this redirection may be the result of compensatory mechanisms necessary to maintain some level of integrity in gene expression [24] . Therefore , other mechanisms may also regulate repressive histone modifications in balance with gene expression . The role of methylation in promoting IBM1 expression [26] may be one such example . Although our experiments have focused on Arabidopsis species , the concept of epigenetic homeostasis might also apply more broadly to other DNA methylation systems , including those in mammals . It is known that the cancer epigenome exhibits global DNA hypomethylation and local hypermethylation [45] , which is broadly similar to the methylation phenotype of a met1 mutant . Interestingly , expression of the three TET enzymes , which are responsible for initiating DNA demethylation in mammals by oxidizing 5-methylcytosine , is reduced in multiple cancers [46] . We conclude that the ROS1 locus serves as a rheostat for methylation levels . We propose that the ROS1 epigenetic rheostat evolved to counter-balance positive feedback between DNA methylation and RdDM activity [13 , 14] to prevent ectopic gain of DNA methylation . The conservation of methylation-sensitive ROS1 expression among divergent angiosperms suggests that this regulation is adaptive and could underpin how plants balance a number extremely effective , potent , and self-reinforcing silencing mechanisms while maintaining gene transcription .
Arabidopsis thaliana , Arabidopsis lyrata , and Zea mays plants were grown in a greenhouse with 16-hour days at 21°C . For experiments performed on whole seedlings , plants were grown on 0 . 5 x MS medium with 5% agar . For treatment with 5-azaC , A . thaliana or A . lyrata seedlings were grown on filter paper moistened with water or 5 , 10 , 15 or 20 μM 5-aza-2-deoxycytidine . Fresh water or 5-azaC was added daily . The accession number for all mutant plants used in this study are in S1 Text . Total RNA was extracted using an RNeasy Plant Mini Kit ( Qiagen ) . RNA was extracted from whole 7-day old Arabidopsis thaliana seedlings for all experiments , except for experiments using 5-azaC , in which case 5-day old A . thaliana or A . lyrata seedlings were used , or experiments with transgenic lines expressing a ROS1 inverted repeat construct , in which case rosette leaves from 21-day old plants were used . RNA was extracted from the tip of the third true leaf of maize plants . For each genotype , 3 biological replicates of at least 5 pooled individual seedlings ( Arabidopsis ) or individual plants ( maize ) were collected . Genomic DNA was removed using amplification-grade DNAseI ( Invitrogen ) . cDNA was synthesized from 500 ng RNA using Superscript II reverse transcriptase ( Invitrogen ) according to manufacturers’ instructions , selecting for polyadenylated transcripts using an oligo-dT primer . For each cDNA synthesis reaction , a control was performed without addition of reverse transcriptase to test the efficacy of the DNAse treatment . Quantitative RT-PCR ( RT-qPCR ) was performed using Fast Sybr-Green mix ( Applied Biosystems ) according to manufacturers’ instructions . All reactions were performed using a StepOne Plus Real-Time PCR system ( Applied Biosystems ) . Primers were designed to have matching melting temperatures between 60–65 °C and to produce amplicons between 80–160 bp in length . All primers were used in a final concentration of 400 nM . The efficiency of all primer pairs was verified using a standard curve dilution of template cDNA prior to their use in quantification of transcripts . Melt curves were analyzed to verify the presence of one amplicon in each reaction , and representative products were also verified by agarose gel electrophoresis . Relative expression was calculated using the ddCt method as described [47] . For Arabidopsis , the reference transcript used for all reactions was AT1G58050 , experimentally verified to be one of the most consistently abundant transcripts in A . thaliana [48] . For maize , the reference transcript was ZmEF1α , defined to be the most consistent reference transcript over the majority of experimental conditions [49] . Primer sequences are available in the S1 Text . 5' RACE of ROS1 was performed using 10 μg Col-0 RNA extracted from 10-day old seedlings . The 5' RACE cDNA library was synthesized using a FIRST-CHOICE RLM-RACE Kit ( Ambion ) according to manufacturers’ instructions , with the exception that a ROS1-specific oligonucleotide was used to prime cDNA synthesis . RACE products were amplified using a nested PCR strategy , purified using a QIAquick gel extraction kit ( Qiagen ) and cloned for sequencing using a TOPO-Blunt PCR cloning kit ( Invitrogen ) . Genomic DNA was isolated from 7-day old seedlings or 21-day old rosette leaves using a CTAB procedure . 2 μg DNA were sheared by sonication and used for bisulfite treatment , which was performed as described [50] . 2 μl bisulfite treated DNA was used in PCR reactions with 2 . 5 U ExTaq DNA polymerase ( Takara ) and 0 . 4 μM primers using the following cycling conditions ( 95 °C 3 minutes , 40 cycles of [95 °C for 15 seconds , 52 °C for 60 seconds , 72 °C for 60 seconds] , 72 °C for 10 minutes ) . PCR products were cloned using TOPO-TA ( Invitrogen ) or CloneJet ( Life Technologies ) PCR cloning kit and individual colonies were sequenced . Sequenced products were aligned using MUSCLE [51] , and methylation of each cytosine residue was calculated using CyMate [52] . The 228 bp sequence 5' of ROS1 that is targeted by RdDM in wild-type plants was amplified and cloned into the directional entry vector pENTR-TOPO-D ( Invitrogen ) . The sequence was then inserted twice in an inverted repeat conformation into the vector pANDA-35HK using a single LR clonase reaction as described by [53] . rdr2 mutant plants were transformed with the inverted repeat transgene by floral dipping [54] , and T1 lines were screened for DNA methylation 5' of ROS1 using a restriction enzyme assay on bisulfite treated DNA . 90% of lines screened exhibited higher DNA methylation than rdr2 and nrpe1 mutants . Six lines covering a range of methylated epigenotypes were selected for bisulfite sequencing and expression analysis . Coding sequences for ROS1 homologs from all fully sequenced genomes within Brassicales were downloaded from Phytozome 9 . 1 . In addition , the coding sequence for Arabidopsis thaliana DME , which belongs to a distinct clade of DNA glycosylases [55] , was included as an out-group . Sequences were aligned using Muscle 3 . 8 [51] , and manually verified using Aliview [56] . The phylogeny was reconstructed from the aligned matrix using MrBayes 3 . 1 . 2 [57] . jModelTest [58] was used to determine the ideal model for analysis , and the general time reversible model with gamma distributed rate variation was chosen . Gaps were treated as missing data . The analysis was run for 2 , 500 , 000 generations sampling every 100 trees . By this time the average standard deviation of split frequencies had reached <0 . 01 and the potential scale reduction factor ( PRSF ) was <1 . 005 for all parameters . The first 25% of trees were discarded as burn-in and the output phylogeny was further analyzed and annotated using FigTree 1 . 4 . | Organisms must adapt to dynamic and variable internal and external environments . Maintaining homeostasis in core biological processes is crucial to minimizing the deleterious consequences of environmental fluctuations . Genomes are also dynamic and variable , and must be robust against stresses , including the invasion of genomic parasites , such as transposable elements ( TEs ) . In this work we present the discovery of an epigenetic rheostat in plants that maintains homeostasis in levels of DNA methylation . DNA methylation typically silences transcription of TEs . Because there is positive feedback between existing and de novo DNA methylation , it is critical that methylation is not allowed to spread and potentially silence transcription of genes . To maintain homeostasis , methylation promotes the production of a demethylase enzyme that removes methylation from gene-proximal regions . The demethylation of genes is therefore always maintained in concert with the levels of methylation suppressing TEs . In addition , this DNA demethylating enzyme also represses its own production in a negative feedback loop . Together , these feedback mechanisms shed new light on how the conflict between gene expression and genome defense is maintained in homeostasis . The presence of this rheostat in multiple species suggests it is an evolutionary conserved adaptation . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Methylation-Sensitive Expression of a DNA Demethylase Gene Serves As an Epigenetic Rheostat |
Polycomb repressive complex 2 ( PRC2 ) is a key regulator of epigenetic states catalyzing histone H3 lysine 27 trimethylation ( H3K27me3 ) , a repressive chromatin mark . PRC2 composition is conserved from humans to plants , but the function of PRC2 during the early stage of plant life is unclear beyond the fact that it is required for the development of endosperm , a nutritive tissue that supports embryo growth . Circumventing the requirement of PRC2 in endosperm allowed us to generate viable homozygous null mutants for FERTILIZATION INDEPENDENT ENDOSPERM ( FIE ) , which is the single Arabidopsis homolog of Extra Sex Combs , an indispensable component of Drosophila and mammalian PRC2 . Here we show that H3K27me3 deposition is abolished genome-wide in fie mutants demonstrating the essential function of PRC2 in placing this mark in plants as in animals . In contrast to animals , we find that PRC2 function is not required for initial body plan formation in Arabidopsis . Rather , our results show that fie mutant seeds exhibit enhanced dormancy and germination defects , indicating a deficiency in terminating the embryonic phase . After germination , fie mutant seedlings switch to generative development that is not sustained , giving rise to neoplastic , callus-like structures . Further genome-wide studies showed that only a fraction of PRC2 targets are transcriptionally activated in fie seedlings and that this activation is accompanied in only a few cases with deposition of H3K4me3 , a mark associated with gene activity and considered to act antagonistically to H3K27me3 . Up-regulated PRC2 target genes were found to act at different hierarchical levels from transcriptional master regulators to a wide range of downstream targets . Collectively , our findings demonstrate that PRC2-mediated regulation represents a robust system controlling developmental phase transitions , not only from vegetative phase to flowering but also especially from embryonic phase to the seedling stage .
One common principle of flowering plants and probably one of the main reasons for their evolutionary success is the alternation of a dormant seed stage with a growing plant that will eventually reproduce and again generate seeds . Seeds harbor not only the plant embryo , i . e . the next plant generation , but typically contain a nourishing tissue , called the endosperm that supports embryo growth and often provides the nutrients for the germinating seedling . Moreover , the embryo and the endosperm are protected by a hard shall , the seed coat , that also facilitates the distribution of seeds . Remarkably , seeds often will stay dormant after ripening and require for germination a defined order of environmental conditions reflecting the progression of the seasons in moderate climates , i . e . they will germinate only after exposure to warmth after a period of cold temperatures . Many factors have been identified to influence this transition from a dormant embryonic phase to a germinating seedling ( for review see [1] ) . However , a unifying molecular framework has not been established so far . For the other major phase transition in plants , e . g . from vegetative growth to flowering , it has been found that Polycomb repressive complex 2 ( PRC2 ) regulation is crucial [2]–[4] . PRC2 activity was also found to be required for repression of flower formation in young seedlings indicating a function in maintaining and/or establishing vegetative growth [5] , [6] . Moreover , severely compromising PRC2 function revealed its function in maintaining overall cell and tissue organization , e . g . the distinction between root and shoot fates [5] , [6] . PRC2 catalyzes the deposition of trimethylation of Lysine 27 on histone H3 ( H3K27me3 ) , a repressive chromatin mark [7] , [8] . The core PRC2 complex is conserved between animals and plants and contains at least four components , which were first identified in Drosophila: the HMTase Enhancer of Zeste ( E ( Z ) ) , the WD40 domain protein Extra sex combs ( ESC ) , the Zn-finger protein Suppressor of zeste-12 ( SU ( Z ) 12 ) and the nucleosome-remodeling factor 55 ( NURF-55 ) [9]–[12] . Arabidopsis contains three presumptive H3K27me3 HMTases , CURLY LEAF ( CLF ) , SWINGER ( SWN ) and MEDEA ( MEA ) that have been found to at least partially compensate for each other . Similarly , Drosophila Su ( Z ) 12 function is represented by three partially redundantly acting genes , EMBRYONIC FLOWER 2 ( EMF2 ) , FERTILIZATION INDEPENDENT SEED DEVELOPMENT 2 ( FIS2 ) , and VERNALIZATION 2 ( VRN2 ) . The homolog of Drosophila ESC , FIE , is the only PRC2 component that is represented by a single member in Arabidopsis . In the past few years , much progress has been made in the understanding of the modus operandi of PRC2 . However , a major obstacle in studying the function of chromatin regulators is their essential role in early development as for instance mutants in ESC in Drosophila and its murine ortholog EED are embryonic lethal [13]–[15] . Similarly , PRC2 function is crucial already for endosperm formation in flowering plants by controlling the parent-of-origin dependent activity of a number of genes in the endosperm ( imprinting ) . PRC2 function is maternal gametophytically required and loss of the maternal PRC2 function releases targets genes from their repression leading to endosperm overproliferation and ultimately to seed abortion [16]–[19] . This requirement for endosperm formation has also precluded so far an analysis of PRC2 action during later stages of seed development and it also remained an open question whether PRC2 function is required for initial body plan formation in flowering plants during which an embryo with shoot , root , and one ( Monocotyledons ) or two ( Dicotyledons ) cotyledons is formed . In contrast to animals , the two stem cell populations established in embryogenesis , i . e . the root and shoot meristem , will produce the body of the adult plant and it has been shown previously that PRC2 is involved in postembryonic shoot meristem function [20] . We and others have previously identified a mutant in the cell cycle regulator CDKA;1 in which the second mitosis during pollen development is missing or substantially delayed [21]–[23] . However , mutant pollen can successfully fertilize the egg cell giving rise to an embryo while triggering the onset of endosperm development without a paternal contribution . This type of fertilization was found to bypass the maternal requirement of PRC2-dependent repression during endosperm development resulting in a mutual rescue of the paternal effect of cdka;1 mutant pollen and the maternal effect caused by mutations in MEA , FIS2 or FIE [24] . Here we have used cdka;1 mutant fertilization to generate homozygous fie mutant plants allowing us to functionally address the requirement of PRC2 action during embryogenesis and subsequent plant growth and development . Our results show that PRC2 is required neither for the generation nor maintenance of embryonic organization in striking contrast to animal PRC2 function . However , PRC2 in plants is vital for the reprogramming of developmental fates mediating the switch from embryonic states to growing seedlings . Furthermore , our genome-wide ChIP- and transcriptional profiling experiments gave insights into the circuitry of PRC2 action indicating that developmental phase transitions are robustly controlled by PRC2 through simultaneously targeting genes at different hierarchical levels and triggering positive feed back loops . This network design allows the transduction of environmental cues into stable and self-maintaining developmental fates likely underlying the enormously adaptable yet enduring growth of plants .
Since the female gametophytic defect of mutants in FIS class genes can be bypassed by fertilization with cdka;1 mutant pollen [24] , we asked whether this would allow the generation of homozygous fie mutant plants in crosses of heterozygous fie mutant mother plants with pollen of cdka;1-fie double heterozygous plants . Indeed , in the progeny of this cross and amid the descendents of a self-pollinated double heterozygous cdka;1-fie mutant a morphologically distinguishable class of plants was identified that was never found among the progeny of heterozygous fie or cdka;1 mutants . Subsequent genotyping confirmed that these plants were homozygous mutant for fie ( Figure 1 ) . Reciprocal crosses corroborated that the appearance of fie resulted solely from fertilization with paternal cdka;1 whereas maternal cdka;1 did not contribute to the generation of viable fie mutants ( Table 1 ) . The fie mutant used as reference allele in this study is a T-DNA insertion line in a central exon and represents a transcriptional null mutant ( Figure S1 ) . In the same way generated homozygous seedlings for three additional fie alleles resulted in the same mutant phenotype ( Figure S1 and data not shown ) . Thus , circumventing the requirement of FIS action in the endosperm is sufficient to generate homozygous null mutants for the PRC2 core gene FIE . Loss of ESC function in flies or mammals causes embryo lethality and is essential for the patterning of the body plan [15] , [25] . In contrast , macro- and microscopical analyses revealed that fie mutant seedlings initially showed a wild-type-like body plan with a root and a shoot , two cotyledons , and newly forming rosette leaves that were at this stage morphologically indistinguishable from wild-type sister plants ( Figure 1A , 1D ) . However , fie mutants grew more slowly than the wild type and around 10 days after stratification ( 10 DAS ) already initiated flower buds ( Figure 1E shows a flower bud at 15 DAS ) whereas the wild type started to flower only after more than 30 DAS . During the next 10 days , homozygous fie mutants developed an increasing number of ectopic cells ( Figure 1K , 1L ) and organs ( Figure 1H , 1I ) , showed signs of organ transformations ( Figure 1G ) and generated somatic embryos ( Figure 1J ) . The loss of spatial and temporal organization continued and homozygous fie seedlings transformed into callus-like structures that could be maintained for several months displaying an increasing number of small cells ( Figure 1F ) . This neoplastic behavior was confirmed by flow cytometrical analyses showing that shortly after germination fie cells started to endoreplicate as a sign of differentiation , a cellular behavior typically found in maturing wild-type plants ( Figure S2A , S2B , S2D ) [26] , whereas at three months after germination the peaks corresponding to 8C and 16C were very much reduced and the remaining cell population gave rise to a DNA profile with cells being mostly in a G1 and a G2 phase , suggesting a massively dividing cell population ( Figure S2C , S2D ) . Thus , PRC2 in plants does not appear to be required for initial body plan organization , indicating a major difference with animal PRC2 function . After germination homozygous fie mutants displayed a progressive loss of cell differentiation states resembling the previously characterized clf-swn double mutant or a special fie mutant allele that results from the incomplete rescue of a fie mutant with a FIE-expressing transgene [5] , [6] . As H3K27me3 is essential in animal embryogenesis we asked if this mark is in fact missing in the viable fie mutants . Therefore we first analyzed by immuno-cytology the distribution of H3K27me3 in the nuclei of wild-type control plants and homozygous fie mutants ( Figure S3 ) . In two-week old wild-type plants , a clear nuclear signal that is widely dispersed along the entire chromatin was found ( Figure S3A–S3C ) consistent with previous studies [27] , [28] . The spotted antibody signal is excluded from compacted heterochromatic regions , as visualized by DAPI staining . In contrast , no signal was observed in nuclei of two-week old fie plants ( Figure S3D–S3F ) . To obtain a high-resolution molecular map of the genome-wide distribution of H3K27me3 in wild type versus fie seedlings , chromatin immunoprecipitation ( ChIP ) was performed , followed by hybridization to a whole genome tiling array . A total of 5634 genes were identified as putative PRC2 targets in wild type seedlings , in good agreement ( 68% overlap ) with a previous analysis ( Table S1 , Figure S4 ) [29] . In fie seedlings , the H3K27me3 signal was absent or extremely reduced throughout the genome ( Figure 2 ) . However , out of 5634 H3K27me3 positive genes in wild type , 1384 ( 24 . 6% ) still passed the detection threshold in fie seedlings ( Figure S4 ) . Furthermore , 2014 genes appeared to be marked de novo by H3K27me3 in fie . Yet , in addition to being much weaker , the H3K27me3 signal in fie showed an atypical distribution pattern over genes and the marked genes were on average larger and slightly closer to transposable elements ( Figure S5 , Table S2 ) . Notably , the most prominent signal in the mutant was found over heterochromatic regions , i . e . repeat-regions and transposable elements although H3K27me3 is typically excluded from these locations ( Figure 2A , Figure S5B ) [29] . Such an apparent re-localization of H3K27me3 signal to heterochromatic regions has also been seen on immuno-localization level in other mutants in PRC2 components [27] . To test the H3K27me3 signal found in wild type and fie tiling arrays , we performed locus-specific qPCR on our ChIP-derived DNA-material . We analyzed seven gene loci and corroborated a H3K27me3 signal in wild type and its absence in fie ( Figure S6A , S6D ) . Moreover , we could detect in qPCR experiments only a slight increase in H3K27me3 over heterochromatic regions in fie in contrast to the array signal ( Figure S6A , S6E , S6F ) . In any case , the signal over heterochromatic regions was much below the level of H3K27me3-positive genic regions in wild type . These findings suggest that the antibody recognizes additional epitopes besides the H3K27me3 mark , preferentially in the absence of the proper antigen . A weak signal may get artificially enhanced in ChIP-on-chip experiments due to the global amplification procedure that is not applied in gene-specific ChIP-qPCR experiments . To investigate the specificity of the antibody , we performed peptide competition assays . Nuclear protein extracts isolated from wild type showed a strong signal in Western blots while no band corresponding to the H3K27me3 mark could be detected in homozygous fie mutants under standard conditions ( Figure 3A ) . However , when over-exposed or under less stringent conditions a faint signal also became visible in fie ( Figure 3A , 3B ) . Using increasing peptide concentrations of up to 10 µg of H3K27me2 and H3K27me1 peptides , a gradual decrease in signal strength was observed in the case of H3K27me2 and H3K27me1 in the fie mutant , with the mono-methylated peptide being the most effective ( Figure 3C ) . As the signal was strongly reduced by the peptides the cross-reactivity of the antibody might account to a large extent for the remaining H3K27me3 signal in our Western and ChIP-experiments . Moreover the H3K27me3-peptide could not deplete the signal further in fie as would be expected when the mutant is already largely devoid of any H3K27me3 ( Figure 3B ) . In contrast , the trimethylated peptide effectively reduced the signal in wild type to a level comparable to the detection level in fie whereas the H3K27me2- and H3K27me1-peptides did not show any obvious effect in wild type samples up to concentrations of 10 µg ( Figure 3B , 3D ) . Thus , we conclude that the remaining signal in fie is not H3K27me3 but to some extent H3K27me2 and more pronounced H3K27me1 demonstrating a slight cross-reactivity of the antibody . Given that H3K27me1 is found mainly over heterochromatic regions in Arabidopsis wild-type plants [30] , we conclude that a cross-reactivity of the H3K27me3 antibody with H3K27me1 accounts for the gain in signal over repeat-regions and transposable elements in the fie mutant . To unravel the transcriptional consequences upon the loss of PRC2 function we compared genome-wide expression levels of homozygous fie mutants with wild type at two different time points . At 7 DAS , no major transformations were observed , yet the plants could be unambiguously and reproducibly identified as homozygous fie mutant plants due to their aberrant root growth and subsequent genotyping ( Figure 1 ) . At the second time point at 20 DAS , substantial morphological transformations were clearly visible . Within our reference set ( Table S3 ) , a total of 1115 genes were significantly up-regulated at 7 DAS and 1735 genes at 20 DAS in fie versus wild-type plants ( Bonferroni P-value ≤0 . 05 , see Material and Methods ) . Conversely , we also found genes to be significantly weaker expressed in fie versus wild type: 1308 and 1843 genes at 7 DAS and 20 DAS , respectively ( Bonferroni P-value ≤0 . 05; Figure S7' ) . Next , we compared the expression data with our PRC2 target gene set . Only a fraction of all identified PRC2 target genes became up-regulated in fie mutants , indicating that PRC2 is not the only repressive system and/or besides the revelation of the repression activators are required for gene expression ( Figure S7 ) . Still , our data are consistent with the concept that H3K27me3 mark is associated with inhibition of gene expression since the overlap of the group of up-regulated genes at 7 DAS and 20 DAS with the group of H3K27me3 marked genes is larger than expected by random ( 7 DAS and 20 DAS: representation factor ( rf ) = 7 . 1 , p<1 . 0e−99 *; 7 DAS and H3K27me3: rf = 1 . 6 , p<1 . 8e−21; 20 DAS and H3K27me3: rf = 1 . 1 , p<0 . 009; Figure S7 ) . Conversely , for down-regulated genes at 7 DAS we see the opposite effect , i . e . the overlap of both gene sets is smaller than expected at random ( 7 DAS and 20 DAS: rf = 7 . 5 , p<1 . 0e−99; 7 DAS and H3K27me3: rf = 0 . 6 , p<1 . 3e−13; 20 DAS and H3K27me3: rf = 0 . 9 , p<0 . 122; Figure S7 ) . To evaluate the PRC2 targets that are up-regulated , potentially in direct response to the loss of H3K27me3 , we examined which gene ontology ( GO ) categories are overrepresented among the up-regulated genes that lost H3K27me3 in fie mutants using the BINGO analysis software [31] . Most overrepresented GO categories in the classification system biological function relate to reproduction with two distinct subcategories: Flower- and seed development ( Figure 4 , Figure S8 ) . Besides reproduction , a few additional small categories were overrepresented such as abscisic acid ( ABA ) signaling and lipid-transport and –sequestering . However , a closer analysis of the corresponding genes revealed that they are also linked with reproduction , in particular seed development ( see below ) . H3K27me3 appears to be a key repressive mechanism for the expression of many genes controlling different aspects of flower development and consistent with this , homozygous fie mutants are very early flowering , i . e . as early as 10 DAS and produce ectopical flowers , e . g . on roots . A similar early flowering phenotype has been found in mutants with compromised PRC2 activity [5] , [6] , [32] , and has been related to the early deregulation of LEAFY ( LFY ) , AGAMOUS ( AG ) and PISTILLATA ( PI ) , which starts as early as the embryonic stage . Our analysis identifies several additional genes controlling flower development as PRC2 targets that are significantly up-regulated in fie mutants , including genes involved in the establishment of a floral meristem ( e . g . FLC , AGL24 , LFY , FUL and CAL ) , genes involved in promoting a determinate floral meristem ( e . g . ULT1 , PAN , LFY ) and genes involved in organ identity specification ( e . g . AP3 , SEP3 , LFY , PI ) ( Figure S9 ) . The results of our microarray experiments could be validated by qRT PCRs confirming the significant up-regulation of 5 genes ( AP3 , CRC , FLC , PI , SEP3 ) . In addition , 2 genes that were only slightly ( but not significantly ) up-regulated in our microarray experiment were also found to have significantly elevated expression levels in the qRT PCR on fie mutant material ( AG , AP1 ) , whereas the flowering regulator FWA shows neither upregulation in the array nor in qRT-PCR experiments ( Table S4 ) . The second principal category of PRC2 target genes that became up-regulated in fie mutants are genes functioning in late seed development ( Figure 4 , Figure S8 , Figure S10 ) . Among the PRC2 targets that are up-regulated in fie we find genes acting at different hierarchical levels in late seed development , from master regulators ( e . g . AGL15 , LEC2 , ABI3 , FUS3 ) and more specific modulators ( e . g . WRI , FLC ) over genes promoting ABA and/or inhibiting GA signaling ( e . g . ABI4 , DOG1 , CHO1 , SOM , SPL8 ) down to target genes such as storage compounds ( e . g . CRU3 , CRA1 , LEAs , oleosins ) ( Figure 5 ) . The up-regulation of many important seed regulatory genes raised the hypothesis that fie seedlings , albeit macroscopically resembling wild type seedlings , display seed phase characteristics . To test this , we first analyzed the lipid content using the dye Fat Red that stains for triacylglycerol-lipids in red color . Whereas wild-type seedlings displayed a sharply decreasing lipid content from 5 to 8 DAS , fie mutants showed an intense red color indicating a high lipid content that is typical for late seed maturation stages in wild type ( Figure 1M , 1N ) . To test whether the failure to repress late seed genes during the seed maturation process interferes with germination , we performed seed germination assays of clf-swn and fie mutants in comparison with wild-type plants . Whereas all wild-type seeds germinated within 2 DAS , both clf-swn and fie mutants show delayed germination ( Figure 6A ) . Eventually , over 90% of clf-swn mutants germinated around 4 DAS . In contrast , approximately 40 percent of the homozygous fie mutants stayed dormant for the course of the entire experiment ( 20 days ) , as revealed by dissecting dormant seeds and genotyping of the embryos . Dissected dormant embryos were then allowed to develop on agar plates . As a reference wild-type embryos were isolated from seeds 24h after imbibition . Initially , dormant fie embryos are indistinguishable from wild type embryos ( Figure 6C , 6F ) and around 1/4 of these fie mutants started to develop in a similar manner as wild type , showing root- and root hair formation , unfolding and greening of the cotyledons and the accumulation of anthocyanin ( Figure 6C–6H ) . However the remaining 3/4 of fie embryos stayed dormant for a period of several days . Some of these finally could break dormancy and started to develop although proliferation was extremely delayed ( Figure 6L–6N ) . Notably , heterozygous cdka;1 mutants behaved like wild type seeds consistent with the previous finding that cdka;1 mutants are sporophytically recessive . Similarly , double heterozygous cdka;1-fie mutants also did not show any germination defects demonstrating that the observed dormancy phenotypes are due to the loss of PRC2 function . Germination is associated with a low ABA to gibberellic acid ( GA ) ratio [1] . Intriguingly , the development of some of the dissected , initially dormant fie seedlings resembled the development of wild–type plants that germinated on high concentration of ABA , lacking proper greening of aerial tissue , root formation and expansion of true leaves ( Figure 7I–7J , 7L–7M ) . However , applying high dosage of GA did not lead to higher germination rates of fie mutants ( Figure 7B ) , suggesting that the primary defect in the class of non-germinating fie seeds is dormancy release and not the germination itself . Among the up-regulated genes in fie controlling seed and flower development certain gene families appeared to be overrepresented , e . g . transcription factors , consistent with previous studies showing that those are in particular marked by H3K27me3 ( Table 2 ) [7] , [29] , [33] . To get a more detailed picture , we tested whether all transcription factor families are equally subject to regulation by PRC2 ( Figure S11A , S11B ) . Approximately 2/3 of all transcription factor families have members that are marked by H3K27me3 at 20 DAS . Notably , one of the largest transcription factor families within our reference set in which none of the member was found to carry H3K27me3 was the group of AUXIN RESPONSIVE FACTORS ( ARFs ) that mediate auxin signaling ( Table S3 ) . However , at a more general level , we found that other genes involved in the auxin signal transduction network are targets of PRC2 regulation , for instance several IAAs and PIN auxin transport facilitators ( Table S1 ) . Among transcription factor families that are marked with H3K27me3 , the fraction of PRC2 targets varies substantially . A particular high proportion of PRC2 targets ( ≥60% ) were found in MIKC subclass of MADS transcription factors , in the WOX-class , the HD-Zip-IV Homeobox class and in the C2C2-Dof and C2C2-YABBY zinc finger classes , for the latter even all 6 members were found to be PRC2 targets . The transcription factor subfamily with the most ( in absolute numbers as well as in percentages ) PRC2 targets that also showed transcriptional up-regulation in fie is the MIKC class , among which we find central regulators of seed and flower development ( Figure S11 , Table S1 , Table S5 ) [34] . In addition to transcription factors , a few other gene families were overrepresented among the PRC2 targets that are up-regulated in fie; the most prominent are oleosins and LATE EMBRYONIC ABUNDANT PROTEIN genes ( LEAs ) . Oleosins are structural components of oil bodies and were found to be expressed preferentially in seeds or the tapetum layer of developing anthers [35] ( Figure 5 , Table S5 ) . 11 of the 17 oleosin genes in our reference set are H3K27me3-marked and 8 are in addition up-regulated in fie ( Table 2 ) , which matches the observation of storage lipid accumulation in fie ( Figure 1M , 1N ) . This is a strong overrepresentation since from all genes in our reference set , we find not more than 21% marked by H3K27me3 and only 2% being up-regulated in fie as well . Another gene family that is highly overrepresented in the class of up-regulated PRC2-targets are LEAs , most of which are expressed in seeds . Of 54 LEAs covered by our reference set , we find 27 ( 50% ) H3K27me3-marked and 16 ( 30% ) being in addition up-regulated in fie . Interestingly , we found 7 ( 13% ) of the LEAs down-regulated in fie and with a single exception these are not H3K27me3 targets and show a non-seed specific expression ( Table S5 , Figure S10 ) [36] , [37] . In Drosophila the function of the Polycomb complex Group ( PcG ) is counteracted by the action of the trithorax Group ( trxG ) [7] . In Arabidopsis , the role of TRX has been assigned to ATX1 , ATXR7/SET DOMAIN GROUP25 ( SDG25 ) , PICKLE ( PKL ) /PICKLE-RELATED 2 ( PKR2 ) and ULTRAPETALA 1 ( ULT1 ) [38]–[42] . Our data showed that ULT1 , ULT2 and PKR2 are PRC2 targets and at least ULT1 and ULT2 were substantially up-regulated at 7 and 20 DAS ( Table S3 ) . ULT1 has been shown to act as an anti-repressor ( i . e . limiting H3K27me3 deposition ) and as an activator of the flower regulator AG by mediating Lysine 4 H3 trimethylation [42] . To test whether the loss of H3K27me3 is accompanied with a gain in H3K4me3 , as suggested by our finding of a possible negative feed-back of PRC2 on ULT1/ULT2 activation , we analyzed the genome-wide distribution of H3K4me3 in wild type and fie . Consistent with previous studies [43] , we found that in wild-type plants a large number of genes ( approximately 1/3 of the genome ) are marked with H3K4me3 at 20 DAS ( Figure 2 , Figure 7 ) . However , the number of genes that are marked by both H3K27me3 and H3K4me3 is significantly smaller than expected for an independent distribution , as was observed previously [43] ( Figure 7 ) . This indicates repulsion of these two marks in accordance with the model that H3K27me3 and H3K4me3 signifies repressed and activated genes , respectively . None-the-less , a small set of 501 genes was identified as marked by both histone modifications . In our ChIP-chip experiments we found only a slight increase in number of genes that carry the H3K4me3 mark in fie in comparison to wild-type plants ( 13945 vs . 13211 genes ) and we do not see an elevated level of H3K4me3 in Western blot analyses ( Figure S6C ) . Thus , genes that loose H3K27me3 do not in general gain H3K4me3 in fie ( Figure 7 , Table S3 ) . On the other hand , gene up-regulation in fie is positively correlated with loss of H3K27me3 and gain in H3K4me3 . The global proportion of genes with elevated expression in fie at 7 DAS is 4 . 5% while the percentage of up-regulated genes reaches 28% amongst those that loose H3K27me3 and concomitantly gain H3K4me3 ( Table 3 ) . In addition , for certain gene families , such as the MIKC group of MADS transcription factors , the WOX group of Homeobox genes and the oleosins , we find those genes that gain H3K4me3 in addition to the loss of H3K27me3 to be among the most highly up-regulated for these specific classes ( Table 3 , Table S5 ) . Thus , our data supports the view that H3K4me3 and H3K27me3 are mutually exclusive marks though in general a loss in H3K27me3 is not sufficient to gain H3K4me3 . However , a tightly linked interdependency between both antagonistic marks is operating for a relatively small group of genes including members of the MIKC class of major developmental regulators [42] , [44] , [45] . Our finding that the PRC2-antagonizing TRX-function genes ULT1/ULT2 are themselves targets of PRC2 and consequently up-regulated in fie , provides a possibility for the molecular implementation of such an interconnected control mechanism .
Several lines of evidence indicate that PRC2 in plants is indeed essential for depositing H3K27me3 marks similar to its function in animals . First , our ChIP-on-chip experiments showed that there is no or only a very weak H3K27me3 signal in fie and that the remaining signal shows properties that differ from the typical H3K27me3 mark . Second , at least 3 heterochromatic regions that showed H3K27me3 signal in fie in ChIP-on-chip experiments did not show a substantial level of enrichment in gene specific ChIP-qPCR assays . Third , the little residual signal of H3K27me3 in fie mutants can be further reduced in peptide competition assays with peptides that harbor H3K27me2 or H3K27me1 epitopes . Finally , H3K27me3 peptide is not effective in reducing the signal in fie further , as would be expected when the remaining signal were H3K27me3 . Conversely , the H3K27me3 peptide could reduce the antibody signal in wild type to the signal strength found in fie . Based on the by large mutually exclusive distribution of H3K27me3 and H3K4me3 , we asked if genes which lost H3K27me3 in fie would in turn acquire H3K4me3 . Such a reciprocal regulation has been found for AG and FLC in Arabidopsis [42] , [44] , [45] . Indeed , we could confirm that AG and FLC , both members of the MIKC transcription factor class , gain H3K4me3 in the absence of FIE . Moreover , 7 other MIKC transcription factors that represent important regulators during development showed a similar response . It was recently shown that the SAND domain protein ULTRAPETALA1 ( ULT1 ) mediates the switch from H3K27me3 to H3K4me3 at the AG locus [42] . Interestingly , we found that ULT1 itself is under the control of PRC2 , as it is marked by H3K27me3 in wild type and shows strong up-regulation in fie . This might explain the switch from H3K27me3 to H3K4me3 as seen for a remarkable number of the MIKC transcription factors . In animals the maintenance of trimethylated H3K4 was shown to require permanent TRX activity to counteract PRC2 , as the repressive H3K27me3 state seems to be the default state for genes that are regulated by both antagonizing HMTase machineries [9] . However , global changes in H3K4me3 levels were not observed in fie , and the change from H3K27me3 to H3K4me3 was restricted to about 5 . 5% of the genes marked by H3K27me3 . We also identified a small group of potentially bivalently labeled genes ( 1 . 8% of reference set ) , i . e . harboring the activating H3K4me3 and the repressive H3K27me3 mark . The concomitance of both tags is found in more than 10% of all genes in human and mouse embryonic stem cells and Xenopus tropicalis embryos , and is thought to maintain the target genes in a “poised state” , resulting in transcriptional silencing but allowing for fast reactivation upon commitment to differentiation [46]–[50] . Bivalency has to our knowledge only been found for the AG and FT loci in Arabidopsis and its existence is also unclear for Drosophila [44] , [51] , [52] . However , we showed here that in contrast to Drosophila and mouse , Arabidopsis does not require the PRC2 to establish a normal body organization ( see below ) . This renders it unlikely that animals and plants are using the same epigenetic mechanisms to set up the body plan , at least during embryogenesis . The observation that the plant body plan can be established without PRC2 function is an unexpected result not only because PRC2 function is essential in animal embryogenesis but also regarding the strong postembryonic phenotype of clf-swn double mutants or fie mutants with a partially complementing FIE transgene [5] , [6] . The overall correct body plan of fie embryos and early seedlings suggests that there is a tight network of intercellular communication presumably maintaining positional cues in the plant embryo . Indeed , research in the last decade has unraveled several patterning mechanisms in the plant embryo , for instance polar auxin distribution and non-cell-autonomously acting transcription factors [53] , [54] . However , after body-plan formation , PRC2 function is key for the correct phase transition from embryonic to vegetative growth . Much progress has been made in the understanding of chromatin regulation and in particular the function of PRC2 during the phase transition from vegetative growth to flowering ( for review see [55]–[57] ) . In contrast , the view that chromatin regulation is important for controlling the switch from mature seed to seedling is only now emerging ( for review see [58] , [59] ) , and the involvement of PRC2 in late seed development has been unclear beyond the finding that many genes implicated in seed maturation are labeled by H3K27me3 ( for review see [58] , [60] , [61] ) . Defining the role of PRC2 during seed maturation has been obscured due to a prominent function of PRC2 earlier in seed development , i . e . for endosperm growth and differentiation . The combination of our genetics and genomics studies demonstrate that PRC2 is one of the major control systems of this phase change by shutting down the entire cascade of maturation genes from master regulators to a wide range of downstream targets before or at germination ( see Figure 5 ) . Moreover , our data suggest that the PRC2 mediated phase transition from seed- to seedling stage takes place primarily at the level of the embryo , as seeds with homozygous fie mutant endosperm but heterozygous mutant embryo germinate like wild type . A wealth of genetic and physiological experiments has demonstrated that seed development is under the tight control of plant hormones and that GA triggers while ABA inhibits seed germination ( for review see [1] ) . High ABA and low GA levels are characteristic for maturing seeds allowing the establishment of seed dormancy , while this relationship is inverted at germination . PRC2 action in the maturing seed seems to sustain the antagonistic action of the two plant hormones ABA and GA by inhibiting positive regulators in ABA and negative players in GA signaling . For example , the PRC2 target SOMNUS ( SOM ) , a CCCH-type zinc finger protein , down-regulates GA and up-regulates ABA levels . SOM expression is seed specific and our finding that it is a PRC2 target and up-regulated in fie suggests that in wild type down-regulation of SOM is maintained by H3K27me3 to allow for high GA and low ABA levels in the germinating seed . Besides the regulation of the ABA-GA signaling pathway , we also found that DELAY OF GERMINATION 1 ( DOG1 ) , a major regulator of seed dormancy [62] , is a H3K27me3 target and significantly up-regulated in fie seedlings . Interestingly , it was recently shown that DOG1 is also regulated by HISTONE MONOUBIQUITINATION1 ( HUB1 ) , a C3HC4 RING finger protein required for histone H2B monoubiquitination [63] . In this context it will be interesting to examine if dormancy control is generally regulated at the level of chromatin , as for example different Arabidopsis accessions from diverse environmental origins show dramatic differences in seed dormancy [64] . Since PRC2 function in the perception of cold via the repression of the flowering inhibitor FLC is well established for the transition to the generative phase [57] , it is tempting to speculate that a similar mechanism functions to perceive this environmental stimulus in the seed . The need of cold stratification in order to break seed dormancy in many plant species [65] and the observation that FLC plays a role in this process as well [66] , might reveal a common regulatory mechanism operating in the transition from vegetative to generative phase as well as from embryonic to vegetative phase . Interestingly another phase transition , the switch from gametophytic to sporophytic development was recently shown to be regulated by PRC2 in moss , where PRC2 represses the differentiation of the sporophyte [67] , [68] . The authors correlate their observations with the transition from gametophytic to sporophytic development in flowering plants that is as well controlled by PRC2 , as Arabidopsis fie mutants for example show untimely development of the gametophytic endosperm without fertilization [22] , [67] , [69] , [70] . The reprogramming of gene activity is a mandatory step to allow for cellular differentiation processes and the stable inheritance of these differentiation states needs to be maintained for the integrity of the organism . Plants in particular have to adapt to environmental conditions and therefore need to change their developmental phase accordingly , and the phase transition from embryo to seedling stage can be considered as the earliest adaptive phase in plants . The origin of seed dormancy in land plant evolution is regarded as a major step in the successful establishment of flowering plants to sustain in non-favorable conditions and its control by PRC2 is an exciting example for the recruitment of an evolutionary conserved molecular machinery to fulfill new functions .
Unless indicated otherwise , Col-0 was used as wild type for all experiments . The cdka;1-1 ( AT3G48750 ) allele has been previously described ( SALK_106809 [22] ) . The SALK_042962 line was used as the standard allele for fie . As additional fie alleles the T-DNA lines GK-362D08-016994 and GK-534F01-020364 were used that both displayed the previously described typical fie mutant phenotype . One previously described fie allele in WS-0 [71] was sequenced and shown to carry a base-pair exchange mutation 5′ of the fourth splice acceptor site . The curly leaf ( clf-28 , SALK_139371 , At2g23380 ) and swinger ( swn-4 , SALK_109121 , At4g02020 ) alleles have been previously described [72] , [73] . All seeds were sterilized using chloride gas and sown on 0 . 8% Phyto agar plates ( ½ Murashige & Skoog ( MS ) salts and 1% sucrose ) and grown under day neutral conditions ( 12h light 21°C , 12 h dark 17°C ) . After germination , plants were transferred to either new plates for long-term observation or to soil and grown in long day conditions ( 16 h , 22°C light; 8 h , 18 C°dark ) . To examine germination , seeds from plants that were grown under the same growth conditions and stored for at least 3 months were sterilized with Chloride-gas and stratified for at least 4 days at 4°C . Upon germination induction ( light , 21°C ) , germination rate was monitored for the following 6 days . After approximately 14 days the plants were analyzed with respect to their phenotype to distinguish between mutants and phenotypically wild-type plants and correlated with the day of germination . Dormant seeds were dissected under a stereomicroscope using a fine needle and fine forceps and subsequently genotyped by PCR . Gibberellic acid ( GA , gibberellin A3 , Sigma ) was dissolved in Ethanol ( 10 mM stock solution ) and applied to the MS-plates in concentrations from 0 . 01 µM to 10 µM . The germination rate of fie mutants on GA-plates was analyzed 10–14 days after stratification ( DAS ) . Abscisic acid ( ABA , Sigma ) was dissolved in Methanol ( stock concentration 10 mM ) and used in final concentration of 1 µM . Wild type germination on ABA-plates was monitored over time . Plants were first partially dehydrated in three steps ( 20% , 40% , 60% isopropanole solution ) , then incubated for 1 hour with Fat Red solution ( filtered 0 . 5% Sudan III in 60% isopropanole ) and re-hydrated again using the same dilution series in reversed direction . Subsequently samples were additionally washed twice with water and analyzed under a dissecting microscope . RNA extraction was performed using Qiagen-RNAesy mini-kit , following the manufacturers instruction . RNA-concentration and purity was tested using nanodrop-photometric quantification ( Thermo Scientific ) . RNA-integrity was verified by running 1 ug of total RNA on 1 . 5% agarose TBE-gels to detect the 28S and 16S rRNA bands . 2 µg RNA was treated with DNAseI ( MBI Fermentas ) according to the manual to avoid contamination of genomic DNA and subsequently processed to obtain cDNA using polyT-primer and reverse transcriptase ( Superscript III , Invitrogen ) following the manufacturers instruction . After reverse transcription RNA was removed by RNAseH digest . For negative control , all steps were followed in the same manner , except for adding the reverse transcriptase . The resulting cDNA was used for Reverse Transcription ( RT ) -PCR or quantitative Real Time-PCR ( qRT-PCR ) using the Roche LightCycler 480 system . Oligonucleotides were designed using either Primer3Plus-design tool ( http://www . bioinformatics . nl/cgi-bin/primer3plus/primer3plus . cgi ) or QuantPrime ( qPCR primer design tool: http://www . quantprime . de/main , [74] and used in final concentration of 0 . 25 µM each . Primers for qPCR have been tested for efficiency of >90% and are listed in Table S6 . For qPCR at least two biological and three technical replicates were processed and expression was calculated relative to ACT7 ( AT5G09810 ) . Several reference genes were tested in comparison between mutant and wild type samples to confirm equal loading ( see Table S6 ) . Microarray analysis was carried out at the Unité de Recherche en Génomique Végétale ( Evry , France ) , using the CATMA arrays [75] , [76] . Two independent biological replicates were produced . For each biological repetition and each time point , RNA samples were obtained by pooling RNA from 100 wild-type and 100 fie seedlings at stage 7 DAS and 10 wild type and 50 fie plants at 20 DAS , respectively . 7 DAS stage plants were cultivated on plates , 20 DAS material was grown on plates for 10 days , then transferred to liquid media for another 10 days in day neutral conditions ( 12 h light , 21°C; 12 h dark . 17°C ) . Total RNA was extracted using Qiagen RNeasy plant mini kit according to the supplier's instructions . The hybridization to the slides , and the scanning were performed as described in Lurin et al . ( 2004 ) [77] . Normalization and statistical analysis were based on two dye swaps ( i . e . four arrays , each containing 24 , 576 GSTs and 384 controls ) as described in Gagnot et al . ( 2007 ) [78] . The raw P-values were adjusted by the Bonferroni method , which controls the Family Wise Error Rate , ( with a type I error equal to 5% ) in order to keep a strong control of the false positives in a multiple-comparison context [79] . We considered as being differentially expressed the genes with a Bonferroni P-value ≤0 . 05 , as described in Gagnot et al ( 2007 ) [78] . Microarray data from this article were deposited at Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) , accession no . GSE19851 , direct link: http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? token=djcjpeggkgsuirw&acc=GSE19851 ) and at CATdb ( http://urgv . evry . inra . fr/CATdb/; Project: RS08-09_FIE ) according to the “Minimum Information About a Microarray Experiment” standards . Nuclear enriched protein extracts were prepared after thoroughly grinding in liquid nitrogen of around 1 g of plant material . All subsequent steps are carried out in the cold . The powder was dissolved in 10 ml of Lysis buffer ( 45 ml Low Salt Wash buffer [see below] + 0 . 5 ml TritonX-100 + 5 ml glycerol + 50 µl 100 mM PMSF + 20 µl β-mercaptoethanol freshly prepared on ice ) , vortexed and placed on a rotation wheel for 20 min at 4C . The solution was filtered using 100 µm nylon mesh and centrifuged for 20 min at 4000 rpm at 4°C , following resuspension of the pellet in 2 ml lysis buffer . The solution was transferred to a new 2 ml tube and centrifuged for 20 min , 4000 rpm , 4°C . The resulting pellet was resuspended in 200 µl 1XSDS loading buffer . Low Salt Wash buffer: 20 ml 0 . 5 M HEPES pH 7 . 5 + 6 ml 5 M NaCl + 400 µl 500 mM EDTA + H2O up to 200 ml . 15% SDS-gel page was performed according to standard protocols . After SDS page proteins were blotted on Hybond-P PVDF membrane ( Amersham Biosciences ) for 75 min , 140 mA in temperature controlled condition . All membrane manipulation experiments where carried out at room temperature ( RT ) when not stated otherwise . Membrane was blocked using incubation with 4XBlockAce ( ABD Serotec ) for 3 h . Throughout all experiments we used Anti-H3 1∶20 , 000 ( Millipore , reference nr: 06-755 ) as loading control , Anti-trimethyl-Histone H3 ( Lys27 ) antibody ( Millipore , reference-nr: 07-449 ) in final concentration between 1∶10 , 000 and 1∶50 , 000 , dissolved in 5%BSA in 1xTBST ( 1x TBS with 0 . 1% TritonX-100 ) and Anti-trimethyl-Histone H3 ( Lys4 ) antibody ( Millipore , reference nr: 07-473 ) at 1∶5 , 000–1∶10 , 000 . The primary antibody was incubated at 4°C over night . After washing 3 times 15 min with 1xTBST the secondary antibody ( Anti-Rabbit antibody , GE-Healthcare , reference-nr: NA934-100UL ) was applied at 1∶50 , 000 in 5%BSA-1xTBST solution for 2 h . Washing was either performed stringently with 3x 30 min or less stringently 3x10 min . For detection the two-component reagent Immobilion Western Chemiluminiscent HRP substrate ( Millipore ) was used . For peptide competition , first the sub-saturating antibody concentration was determined . For anti-H3K27me3 this was at a concentration of 1∶50 , 000 . Then increasing concentrations from 0 . 1–10 ug of H3K27me3 , H3K27me2 and H3K27me1 peptide ( Millipore 12-565 , 12-566 , 12-567 ) were added to a 10 ml antibody-solution and incubated under slight agitation for 4 h at RT and an additional 1 h at 4°C before hybridizing on the membrane . Subsequent hybridization and detection were performed as described above . Chromatin immunoprecipitation ( ChIP ) experiments were done as described previously [74] , in two biological replicates , using the following antibodies: H3K4me3 , Millipore 07-473; H3K27me3 , Millipore 07-449 . DNA recovered after ChIP and directly from input chromatin was amplified using the Sigma GenomePlex Complete Whole Genome Amplification ( WGA ) Kit as directed , differentially labeled and hybridized in dye-swap experiments to a custom-made Roche-NimbleGen whole-genome tiling microarray . This microarray covers the entire forward strand of the Arabidopsis genome sequence ( TAIR8 ) at 175 nt resolution with approx . 720K isothermal tiles ( 50–75 oligonucleotides ) . Following ANOVA normalization , raw data were analyzed using a linear regression mixture model ( ChIPmix , [80] ) , which was adapted to handle multiple replicates simultaneously ( script available on request ) . Lists of tiles reporting significant enrichment were converted in sets of chromatin domains by combining adjacent enriched tiles , allowing a maximal gap of 165 nucleotides . Only domains of at least 400 nucleotides were considered for further analysis . TAIR8 release was used for annotation of genes and transposable elements . Several loci were additionally tested for H3K27me3 and H3K4me3 enrichment as compared to input . Input was diluted 1∶100 prior to qPCR application . From the diluted input material and from the ChIP-material 1 µl was applied for each triple replicate reaction in the Roche Lightcycler 480 Real Time System using Roche SYBR green reagent according to the supplier's instruction ( Roche ) . Primers used for this assay are given in Table S6 . ChIP on chip data from this article were deposited at Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) , accession no . GSE24163 , direct link: ( GSE24163 , http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE24163 ) . 10–14 DAS wild type and fie seedlings were fixed and processed as described previously [28] , washed 3×5 min in 1× PBS before pre-incubation with BSA . Diluted rabbit polyclonal α- trimethyl H3K27 primary antibody ( 1∶100 , Millipore 07-449 ) was incubated for 1 h at 37°C , washed 3×5 min in 1× PBS and incubated with diluted Alexa Fluor 488 conjugated goat anti-rabbit polyclonal secondary antibody ( 1∶200 , Invitrogen ( Molecular Probes ) A-11008 ) for 1 h at 37°C , washed 3×5 min in 1× PBS and mounted in 1× PBS containing 1 µg/µl DAPI . Images were acquired using an Axioplan 2 Carl Zeiss Microscope with a cooled AxioCam HRc camera using a bandpass 515–565 nm emission filter ( Carl Zeiss # 488010-9901-000 ) and a longpass 397 nm emission filter ( Carl Zeiss # 488001-9901-000 ) for visualization of AF488 and DAPI , respectively . Fixed exposure settings for both florochromes were: AF488 , 196 ms , 402 ms and 1002 ms ( overexposure ) ; DAPI , 50 ms , 100 ms and 305 ms ( overexposure ) . For all analyses comparing array expression and ChIP chip data a reference gene set of 24901 genes was defined that included those genes for which data from both type of experiments were available ( Table S2 ) . The Transcription factor classification was taken form the Arabidopsis transcription factor database ( AtTFDB ) hosted on the Arabidopsis Gene Regulatory Information Server ( AGRIS , http://arabidopsis . med . ohio-state . edu/AtTFDB ) . Venn diagrams were generated using the VENN diagram generator designed by Tim Hulsen at http://www . venndiagram . tk/ and http://www . cmbi . ru . nl/cdd/biovenn/ ( BioVenn [81] ) . The test for statistical significance of the overlap between two groups of genes was calculated by using software provided by Jim Lund accessible at http://elegans . uky . edu/MA/progs/overlap_stats . html . A representation factor ( rf ) is given and the probability ( p ) of finding an overlap of x genes is calculated using a hypergeometric probability formula . When p was below the calculation limits of the software ( highly significant ) we noted p<1 . 0e−99* . The representation factor is the number of overlapping genes divided by the expected number of overlapping genes drawn from two independent groups . A representation factor >1 indicates more overlap than expected of two independent groups , a representation factor <1 indicates less overlap than expected , and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes . To determine which Gene Ontology ( GO ) categories are statistically overrepresented among the H3K27me3 targets that are up-regulated in fie , we used the BINGO 2 . 3 plugin for Cytoscape ( http://www . psb . ugent . be/cbd/papers/BiNGO/Home . html ) . A custom annotation file was created using the build in annotation file for GO biological process and our reference set of 24901 genes . Other than that default parameters were used . | Epigenetic regulation of gene expression through modifications of histone tails is fundamental for growth and development of multicellular organisms . The trimethylation of lysine 27 of histone 3 ( H3K27me3 ) is the landmark of Polycomb Repressive Complex2 ( PRC2 ) function and is associated with gene repression . Here we present the development of a genetic system to generate homozygous null mutants of Arabidopsis PRC2 . A first major finding is that H3K27me3 is globally lost in these mutants . Surprisingly , we found that initial body plant organization and embryo development is largely independent of PRC2 action , which is in sharp contrast to embryonic lethality of PRC2 mutants in animals . However , we show here that PRC2 is required to switch from embryonic to seedling phase , and mutant seeds showed enhanced dormancy and germination defects . Indeed , many genes controlling seed maturation and dormancy are marked by H3K27me3 and are upregulated upon loss of PRC2 . The invention of seed dormancy of land plants is regarded as one of the major reasons for the evolutionary success of flowering plants , and the here-discovered key role of PRC2 during the developmental phase transition from embryo to seedling growth reveals the adaptation of conserved molecular mechanisms to carry out new functions . | [
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"organism"... | 2011 | Polycomb Repressive Complex 2 Controls the Embryo-to-Seedling Phase Transition |
DNA modifications such as methylation and DNA damage can play critical regulatory roles in biological systems . Single molecule , real time ( SMRT ) sequencing technology generates DNA sequences as well as DNA polymerase kinetic information that can be used for the direct detection of DNA modifications . We demonstrate that local sequence context has a strong impact on DNA polymerase kinetics in the neighborhood of the incorporation site during the DNA synthesis reaction , allowing for the possibility of estimating the expected kinetic rate of the enzyme at the incorporation site using kinetic rate information collected from existing SMRT sequencing data ( historical data ) covering the same local sequence contexts of interest . We develop an Empirical Bayesian hierarchical model for incorporating historical data . Our results show that the model could greatly increase DNA modification detection accuracy , and reduce requirement of control data coverage . For some DNA modifications that have a strong signal , a control sample is not even needed by using historical data as alternative to control . Thus , sequencing costs can be greatly reduced by using the model . We implemented the model in a R package named seqPatch , which is available at https://github . com/zhixingfeng/seqPatch .
Modifications to individual bases like 5-methylcytosine , 5-hydroxymethylcytosine , and N6-methyladenine in DNA sequences are an important epigenetic component to the regulation of living systems , from individual genes to cellular function . Single molecule , real time ( SMRT ) sequencing provides a high throughput platform for direct DNA modification detection without the need for special sample preparation procedures such as bisulphite treatment or restriction enzyme digestion [1]–[3] . In SMRT sequencing , each base identity is read when fluorescently labeled nucleotides are incorporated into a DNA sequence being synthesized by DNA polymerase [4] . In this case , because the incorporation events are being directly observed in real time , the duration between the pulses of light ( referred to as inter-pulse duration or IPD ) that indicate an incorporation event can be precisely measured . IPD measures are a direct reflection of the DNA polymerase kinetics . This kinetic parameter for the enzyme has been shown to be sensitive to a wide range of DNA modification events , including 5-methylcytosine , 5-hydroxymethylcytosine , and N6-methyladenocine [1]–[3] , where variations in the kinetics are predictive of modification events . For each position in the DNA sequence being synthesized , the IPD distribution is empirically determined as each read covering a given position yields an IPD value for that position , so that for each position there are a number of IPD observations . In these previous demonstrations [1] , [2] , kinetic variations were detected using a case-control method in which the IPDs at a given site in the native DNA from a sample of interest ( case group ) are compared to the IPDs in whole-genome amplified ( WGA ) DNA corresponding to the native DNA ( control group ) . The WGA process erases all of the modifications by replacing any modified base with the corresponding standard base . The null IPD distribution can be determined from the IPDs in the control group and then the IPD distribution for the case group can be compared to this null distribution ( Figure 1A ) . If the IPD values between cases and controls differ significantly , then a kinetic variation event is called . Because SMRT sequencing reads are strand specific with respect to the detection of these kinetic variation events , modifications can be inferred in a strand specific manner . This approach to detecting kinetic variation events works well when there is sufficiently high numbers of reads covering each position , but is much less reliable in low coverage cases due to the high variability of IPD measures ( the IPDs are exponentially distributed ) . In addition , this case-control method requires sequencing a sample twice , so making these detections come at a significant cost . In this paper , we examine the correlation between polymerase kinetics and sequence context to demonstrate that polymerase kinetics can be well predicted by local sequence context , suggesting that baseline kinetics can be established for any sequence context to use as a null distribution in testing for base modification events . We demonstrate that this correlation between local sequence context and enzyme kinetics is highly consistent across independent experiments carried out on DNA from different species . Given this , we hypothesized that IPDs from positions with the same sequence context , referred to as homologous positions , including those from historical control data , could be used jointly to better estimate the null IPD distribution . Towards that end , we develop a hierarchical model to combine IPDs across homologous positions to enhance the detection of kinetic variation events . The hierarchical model can work with or without control data . When control data are available , for a given position , the hierarchical model combines IPDs of control data and IPDs of homologous positions to estimate the null IPD distribution . We refer to this type of model as a hierarchical model with control data . When there is no control data available , for a given position , the hierarchical model estimates the null IPD distribution using only IPDs of homologous positions from historical data . We refer to this as a hierarchical model without control data . We test these two hierarchical models on two high coverage plasmid datasets and a medium coverage E . coli K-12 MG 1655 dataset: 1 ) plasmid DNA isolated from a strain of E . coli engineered to methylate the 4th carbon in cytosine residues , referred to as 4-mC , in the GATC context; 2 ) plasmid DNA isolated from a strain of E . coli engineered to methylate the A residue in the GATC context , referred to as 6-mA; and 3 ) DNA isolated from a wild type E . coli reference strain ( K-12 ) ( Table 1 ) . We show that the hierarchical model with control data significantly increases the detection accuracy compared with the case-control design on all of the datasets . The hierarchical model without control data also achieves a good accuracy for N6-methyladenocine , which has a strong signal-to-noise ratio ( i . e . impact on the enzyme kinetics ) , but does not work well for methylcytosine , whose signal-to-noise ratio is relatively weak . In the case of the E . coli K-12 dataset , we were able to detect roughly 80% of the 6-mA events in the GATC context at a 5% FDR ( False Discovery Rate ) using the hierarchical model with control data , a context known to be methylated in a vast majority of the occurrences of the GATC motif in this strain [5] . In addition to detecting these known methyladenine events in the GATC context , we demonstrate the detection of thousands of kinetic variation events that occur at positions not previously described as having known methylation motifs , suggesting more extensive patterns of modification than had been previously observed .
We note that while the IPDs are observed to be exponentially distributed , tests based on this assumption are more sensitive to extreme outliers . Thus , we adopt a Box-Cox transformation to make the IPDs follow an approximate normal distribution ( Figure 2 ) , making it more robust to outliers . Formally , we used the following transformation , Because the chemistry of SMRT sequencing is being constantly improved , there are two different types of chemistry , FCR and C2 , represented in our datasets . The IPD characteristics of these different chemistries are quite different , so we used different and , which were estimated for each set . For data using the FCR chemistry , we used and . For data using the C2 chemistry , we used and . The and parameter values were chosen empirically such that the skewness distribution was approximately centered at 0 . A number of factors can influence enzyme kinetics in addition to sequence context ( see below ) and DNA modification , including reagent lot , temperature , SMRTcell lot and instrument operator . Just as we observe batch effects and other experimental noise factors with other technologies such as microarrays and RNA-seq that impact gene expression values , so these different effects can have strong effects on the IPD . Therefore , IPDs from different experiments are not necessarily directly comparable . For the current version of the Pacific Biosciences RS DNA sequencing instrument , DNA molecules are sequenced in zero mode waveguides ( ZMWs ) located on a SMRTcell [6] , with pulses of light in different color channels corresponding to the bases being incorporated into the sequence being synthesized . These signals are detected and recorded by a CCD camera operating at 100 Hz , resulting in a movie containing up to 150 , 000 pulse streams corresponding to the different ZMWs on the SMRTcell . Overall , the IPD distribution can be significantly different between movies even for identical DNA samples ( Figure 1B ) . Therefore , we applied a simple centering approach to normalize the IPD data before modification detection . where is any Box-Cox transformed IPD in a movie , and N is the number of alignable bases in that movie . In the rest of the paper , we refer to the normalized IPD as simply the IPD . The kinetic rate of DNA polymerase is known to be sensitive to sequence context [7] . Given the ability of SMRT sequencing to observe many thousands of individual molecules of DNA polymerase as they carry out DNA synthesis , we examined the relationship between the kinetic rate ( estimated from the IPDs ) and sequence context . For each position , the position-specific kinetic rate is defined as the mean of its Box-Cox transformed IPDs ( Methods ) . Sequence context is defined as the sequence flanking the incorporation site of interest , the boundaries of which are explored below . To avoid ambiguity caused by modification events , we explored enzyme kinetics using whole-genome amplified ( WGA ) E . coli K-12 data ( E . coli WGA-FCR in Table 1 ) , given the WGA process erases all chemical modifications . From the K-12 dataset , we extracted positions in which the single strand coverage was greater than 35 reads . We then applied MART [8] , a non-linear tree based regression method , to estimate the relationships between polymerase kinetics and sequence context . Here , position-specific kinetic rate is the response variable and sequence context is the predictor variable . The proportion of the variation in the response variable that can be explained by the predictor variable ( i . e . , the value ) , was used as the measure of dependence of enzyme kinetics on sequence context . We explored these relationships over different sequence context lengths and found that grows as the number of bases upstream of the incorporation site increases , but becomes saturated at 7 bases upstream . The bases downstream from the incorporation site have much smaller impact on the enzyme kinetic rate , with positions more than 2 bases downstream from the incorporation site having no observable impact on the values ( Figure 3A ) . Roughly 80% of the IPD variation can be explained by a 10 base pair sequence context ( 7 bases upstream and 2 bases downstream from the incorporation site ) . We refer to the average Box-Cox transformed IPDs corresponding to positions with the same sequence context as the context effect . We examined the consistency of the context effect between two independent experiments: 1 ) WGA data from the E . coli K-12 strain , and 2 ) WGA data from M . pneumoniae ( E . coli WGA-C and M . pneumoniae WGA-C2 in Table 1 ) . While these experiments were performed completely independently , carried out by two different groups at two geographically separated sites , the context effects were strikingly similar ( Figure 3B ) , with 80% of the IPD variation in one set explained by variation in the second set . Importantly , we compared context effects between two experiments using the same chemistry ( FCR chemistry ) , as the consistency of context effects will not hold when comparing experiments using different chemistries . Thus , in all the experiments carried out herein , only datasets with the same chemistry are used together . Given that a large percentage of variability of position specific enzyme kinetic rates can be explained by sequence context ( Figure 3A ) , IPDs of homologous positions can be combined together to estimate the null IPD distribution . In addition , because of the high consistency in context effects across different experiments , IPDs of homologous positions in historical WGA datasets can also be incorporated to enhance the power to detect kinetic variation events ( Figure 4 ) . However , the IPD distributions of homologous positions will not be exactly the same , and so , false positive calls may be introduced if the null IPD distribution is estimated without considering the heterogeneity in the IPD distributions that can exist between homologous positions . To deal with this type of heterogeneity , we developed an hierarchical model to incorporate IPDs of homologous positions in a robust fashion . In the hierarchical model , Box-Cox transformed IPDs of homologous positions were assumed to follow normal distributions , with differences in mean and variance allowed between these distributions . The mean and variance parameters were treated as random variables and were assumed to follow the same prior distribution . For the hierarchical model with control data , the model was fitted by both IPDs from the control data and as well as IPDs from all homologous positions . For the hierarchical model without control data , the model was fitted using only homologous positions in historical data . Then , we adopt a likelihood ratio to evaluate how likely a position is modified ( See Methods ) . To assess the utility of the hierarchical model in detecting kinetic variation events , we compared the naive case-control design with the hierarchical model using data from two data sets in which the sites that were modified were known a priori . The first set was generated from plasmid DNA isolated from a strain of E . coli engineered to methylate the 4th carbon of cytosine residues in each GATC context ( referred to as the 4-mC set ) , and the second was generated from plasmid DNA isolated from a strain of E . coli engineered to methylate adenine residues in each GATC context ( referred to as the 6-mA set ) . We use E . coli WGA-FCR and M . pneumoniae WGA-FCR in Table 1 as historical data and only contexts that have more than 5 positions with larger than 10x coverage in the historical data are used . We explored both the [−7 , +2] contexts ( 7 bp upstream , 2 bp downstream of the incorporation site ) and [−6 , +1] contexts , and found that their performances were similar ( Figure 5 ) . However , roughly one third of the positions in these datasets did not have the corresponding [−7 , +2] context in the historical data . Therefore , to make the comparisons fair , we only considered positions that had a corresponding context in the historical data . To maximize the number of sequence contexts in one dataset that would be represented in another , we restricted the sequence context to 8 bases ( the [−6 , +1] context ) for the remainder of our study . For the hierarchial model with control data ( see Methods ) , when the sequence coverage of the control sample is relatively low ( 15x35x single strand coverage ) , the hierarchical model compared to the case-control method is seen to increase the sensitivity by 10%30% under the same FDR ( Figure 5 ) . Performance of the case-control method and hierarchical model become similar as sequencing coverage of the control sample increases . For the hierarchical model without control ( See Methods ) , the accuracy is comparable to the case-control method for 6-mA , but does not perform as good for 4-mC . We further tested our method on datasets with partial modifications in which only a fraction of the molecules with respect to a given position were modified . Given one of the limitations with the modeling approach presented herein is that it assumes in the native sample a given position is either fully modified or not , understanding the sensitivity of this assumption on the detection rates is important . For each of the 6-mA set and 4-mC datasets , we constructed an artificial native sample , where only a certain proportion of reads were sampled from the native sample ( referred to as the modification proportion ) , while others were sampled from the control data . We tested the performance of our method on three different modification proportions: 50% , 70% and 90% . As expected , the detection accuracy decreases as the modification proportion decreases , however , in all cases our method was still able to make detections even when the fully modified assumption was clearly violated . We further note that it is possible to achieve accuracy that is comparable to the case of fully modified positions by increasing the sequence coverage of the native sample ( Figure S1 ) . To further evaluate the performance of the hierarchical model , we explored data from the E . coli K-12 strain in which there are not only modifications that are known to occur in certain sequence motifs ( e . g . GATC ) , but also potentially novel modification events that cannot be explained by known motifs . We applied both hierarchical modeling with and without control data to the SMRT sequencing data from native the E . coli K-12 MG 1655 strain ( E . coli native in Table 1 ) . For the hierarchical model with control data , we used data from a WGA E . coli K-12 MG 1655 sample as control ( E . coli WGA-C in Table 1 ) and a WGA M . pneumoniae data ( M . pneumoniae WGA-C2 in Table 1 ) , which is generated in another unrelated experiment , as historical data . For each given position , the IPD distribution in the native sample was compared to the null IPD distribution , which was estimated by fitting a hierarchical model that combines the IPDs of the corresponding positions in the control sample and IPDs of all of the homologous positions . Homologous positions were identified in two different ways: 1 ) find homologous positions in the WGA M . pneumoniae data , and 2 ) find homologous positions in the control data . For the hierarchical model without control , we estimated the null distribution by fitting the hierarchical model by the homologous positions in the WGA M . pneumoniae data only . A position was called modified if the generated likelihood ratio exceeded a certain threshold ( see Methods ) . As most adenines in the GATC context are expected to be methylated in wild type E . coli K-12 MG 1655 , we detected modifications in the regions within 20 bp around adenine positions in the GATC context to evaluate how well 6-mA could be detected . Here , the FDR is estimated as the ratio between the number of significant adenines detected that are not in the GATC context and the total number of significant adenines detected . We note that it is certainly possible that there are modified bases outside of the GATC context , so that treating only adenines detected in the GATC context as true positives and all other bases as true negatives , out estimated FDR can be considered as a conservative estimation , i . e . the actual FDR is lower than this . The receiver operating characteristic ( ROC ) curve ( Figure 6A ) shows that 95% of adenine of GATC can be detected under FDR of 5% by using the hierarchical model with control . The hierarchical model greatly increases the detection accuracy in this instance compared to the case-control method . We can also detect 6-mA without the control data , where the accuracy is lower than hierarchical model with control , but the results are comparable to the naive case-control method . If we apply this detection approach on genome-wide scale , we detect many putative modification events , with the ROC curve ( Figure 6B ) showing that at the 5% FDR we not only detect 80% of the adenine in the GATC context by using hierarchical model with control , but we also identify about 2000 other positions in other contexts that may reflect off target activity of the methyltransferase that makes the 6-mA modifications in the GATC context or perhaps reflects the activity of other enzymes capable of inducing base modifications . In the genome-wide study , to estimate FDR , we detected DNA modifications in another WGA sample ( E . coli WGA-N in Table 1 ) , where no modification should be found , and FDR is estimated by ratio between number of DNA modifications detected in the WGA sample ( E . coli WGA-N in Table 1 ) and number of modifications detected in the native sample ( E . coli native in Table 1 ) .
We examined the correlation between DNA polymerase kinetics and sequence context quantitatively and found that roughly 80% of the variation in the enzyme kinetics as measured by IPD variance can be explained by sequence context . Our data support that the most informative regions of sequence context for the enzyme kinetics at a given incorporation site is the region 7 bp upstream and 2 bp downstream of the incorporation site . In addition , we found that this context dependence is extremely consistent between independent SMRT sequencing experiments carried out using the same chemistry . IPDs of homologous positions , including those from historical control data can therefore be incorporated to improve DNA modification detection accuracy . However , because heterogeneity of the IPD distribution within the same sequence context can cause false positive events , we adopted a hierarchical model that can adaptively incorporate information from homologous positions . The hierarchical model is flexible in that it can be used with or without control data . We demonstrated that the hierarchical model with control data can greatly increase accuracy compared to the naive case-control method . For the types of modifications that have a relatively weak signal-to-noise ratio , such as 4-mC , the hierarchical model without control does not perform as good as the case-control method . This may be expected given the sequence context in such instances does not appear to explain all of the kinetic variation , with other factors such as fragment length and experimental condition perhaps dominating the estimation of the null distribution from historical data . However , for modification types with a strong signal-to-noise ratio , noisy null IPD distributions have a relatively small impact on accuracy . Our results suggest that the hierarchical model can reduce the requirement of control samples and thus provide a significant cost benefit . For detecting modifications with a strong signal-to-noise ratio , one can generate low coverage control data or even avoid the generation of the control data altogether . It may be possible in the future as more SMRT sequencing data obtains , given the dependence of local sequence context on enzyme kinetics , to build null models specific to each sequence context to leverage as a control in detecting base modification events . We anticipate as well that as more sequence data obtains across different species with larger genomes than the prokaryotic genomes represented in our study , that we will be able to re-evaluate whether a more expanded sequence context around the incorporation site better explains the DNA polymerase enzyme kinetics . It may be that with an expanded set that considers 9 bases upstream of the incorporation site and 3 bases downstream , for example , a better explanation of the enzyme kinetics obtains . Further , as the historical datasets get larger , we may also find that the historical data on its own achieves the same results as the combined historical and control data in all contexts and for all modification types .
For the th position in the genome , we assume that its Box-Cox transformed IPDs follow a normal distribution , which iswhere is the jth Box-Cox transformed IPD of the th position in the genome , and is the position specific polymerase kinetic rate , which is by its sequence context . We used ( is the single strand coverage of the th position ) , which are the estimated position specific polymerase kinetic rates , as the response , and the corresponding sequence context as the predictor to build a non-linear regression model using the MART method [8] . The dataset we employed for this characterization is whole genome amplified E . coli K-12 data after outlier removal and coverage filtering . Each data point in the dataset is a pair of estimated position specific polymerase kinetic rates and sequence contexts , which represent the upstream and downstream bases of the position of interest . Performance of the regression approach was evaluated using 5-fold cross validation in which 80% of the data points were randomly selected as the training set , MART was trained on this set , and then the predicted responses were carried out for the remaining 20% of the data set . The was the statistic used to measure the performance and was calculated as , where is the sample size , , and is the predicted . The hierarchical model without control data is a special case of the hierarchical model with control data , i . e . or vector is empty . We evaluated case-control method and hierarchical model on two different datasets: 3589 bases long plasmid with 19 known 4-methylcytosines , and 3591 bases long plasmid with 23 known N6-methyladenines ( Plasmid m4C native/control and Plasmid m6A native/control in Table 1 ) . Whole genome amplified E . coli and M . pneumoniae data were used as historical data ( E . coli WGA-FCR and M . pneumoniae WGA-FCR in Table 1 ) . A detection is called correct only if its distance to the nearest true modified position is less than or equal to 5 bp . Different thresholds of were set , and the corresponding false discovery rate and true positive rate were calculated . False discovery rate and true positive rate are defined asrespectively . To get the ROC under different coverage , we randomly sampled reads without replacement 100 times to get average FDR under different TPRs . The raw sequence data listed in Table 1 are available at http://www . ncbi . nlm . nih . gov/sra , under accession number SRA062773 and SRA058893 . ( SRA058893 was published in [10] ) . | DNA modifications have been found in a wide range of living organisms , from bacteria to human . Many existing studies have shown that they play important roles in development , disease , bacteria virulence , etc . However , for many types of DNA modification , for example N6-methyladenine and 8-oxoG , there is not an efficient and accurate detection method . Single molecule real time ( SMRT ) sequencing not only generates DNA sequences , but also generates DNA polymerase kinetic information . The kinetic information is sensitive to DNA modifications in the sequenced DNA template , and therefore can be used for detecting a wide range of DNA modification types . The usual detection strategy is a case-control method , which compare kinetic information between native sample and a control sample whose modifications have been removed . However , generating a control sample doubles the cost . We proposed a hierarchical model , which can incorporate existing SMRT sequencing data to increase detection accuracy and reduce coverage requirement of control sample or even avoid the need of a control sample in some cases . We tested our method on SMRT sequencing data of plasmids with known modified sites and E . coli K-12 strain to demonstrate our method can greatly increase detection accuracy and reduce sequencing cost . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
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"sequencing",
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] | 2013 | Detecting DNA Modifications from SMRT Sequencing Data by Modeling Sequence Context Dependence of Polymerase Kinetic |
The infectivity of rotavirus , the main causative agent of childhood diarrhea , is dependent on activation of the extracellular viral particles by trypsin-like proteases in the host intestinal lumen . This step entails proteolytic cleavage of the VP4 spike protein into its mature products , VP8* and VP5* . Previous cryo-electron microscopy ( cryo-EM ) analysis of trypsin-activated particles showed well-resolved spikes , although no density was identified for the spikes in uncleaved particles; these data suggested that trypsin activation triggers important conformational changes that give rise to the rigid , entry-competent spike . The nature of these structural changes is not well understood , due to lack of data relative to the uncleaved spike structure . Here we used cryo-EM and cryo-electron tomography ( cryo-ET ) to characterize the structure of the uncleaved virion in two model rotavirus strains . Cryo-EM three-dimensional reconstruction of uncleaved virions showed spikes with a structure compatible with the atomic model of the cleaved spike , and indistinguishable from that of digested particles . Cryo-ET and subvolume average , combined with classification methods , resolved the presence of non-icosahedral structures , providing a model for the complete structure of the uncleaved spike . Despite the similar rigid structure observed for uncleaved and cleaved particles , trypsin activation is necessary for successful infection . These observations suggest that the spike precursor protein must be proteolytically processed , not to achieve a rigid conformation , but to allow the conformational changes that drive virus entry .
To initiate infection , viruses must overcome the complex membranous system that surrounds and resides within the cell . The ability of the virus to penetrate this barrier is one of the elements that define virulence and host range . Entry into the host cell is thus a key factor in viral infectivity , and a natural target for the design of efficient strategies against virus infections [1] . Rotaviruses are non-enveloped , double-stranded ( ds ) RNA viruses of the Reoviridae family; they infect only vertebrates , via the oral-fecal route . Their replication is generally limited to terminally differentiated enterocytes of the intestinal tract , with severe gastroenteritis restricted in the great majority of cases to the young [2] . In humans , rotavirus infection is the leading cause of medical gastroenteritis in children under five years of age [3] , [4] . The rotavirus mature virion is a complex triple-layered particle ( TLP ) built around its inner capsid , a T = 1 icosahedral shell made of 60 asymmetric dimers of the VP2 protein [5] , [6] . Inside this core , each of the eleven dsRNA segments of the viral genome is associated , below the five-fold symmetry axes , with one copy of the RNA-dependent RNA polymerase VP1 , and the RNA capping enzyme VP3 [7] , [8] . The inner core is surrounded by a thick shell formed by 260 trimers of the VP6 protein ordered in an icosahedral T = 13 symmetry [5] , [6] , [9] . This double-layered particle ( DLP ) constitutes the rotavirus transcriptional machinery and , characteristically of Reoviridae family members , it does not disassemble during viral infection . Rotavirus infection is effectively initiated when the DLP is released into the cytoplasm and begins synthesis of the viral transcripts . The DLP are not infective , however , as they lack the ability to identify , bind and penetrate target cells; those functions reside in the external layer of the mature TLP [10] , [11] . This external shell is formed by 260 trimers of the VP7 glycoprotein , ordered in a T = 13 icosahedral lattice . Each VP7 trimer rests on one of the VP6 trimers of the underlying DLP , anchored to small protrusions of the VP6 layer by its flexible N-terminal arm [9] , [12] . Sixty spikes , formed by trimers of the VP4 protein , project from the VP7 shell . They are anchored in depressions in the VP6 layer that surround the five-fold axes , clamped by the VP7 shell that partially covers their base [6] . To become fully infectious , cell-released TLP must be digested by trypsin-like proteases from the intestinal lumen [13] , [14] . This activation step cleaves the VP4 protein after three defined sites ( Arg231 , Arg241 and Arg247 ) to produce two main fragments , the N-terminal VP8* and the larger C-terminal VP5* . Proteolytic processing of the spikes is thought to occur through an ordered cleavage cascade that culminates in scission at Arg247 . Cleavage after this residue is essential for membrane interactions and infectivity [15] , [16] . Analysis of the near-atomic structure of the cleaved TLP shows that the three VP4 molecules that form the spikes , termed VP4A-C [6] , are organized into a complex structure that is held in place by non-covalent interactions among its components ( Figure 1 ) . Structural and biochemical data have allowed formulation of a model for rotavirus entry in which VP4 plays a role similar to that of fusion proteins during enveloped virus entry [11] , [17]–[20] . Receptor binding and attachment take place through the distal lectin domains of the two VP8* molecules of chains A and B . Probably triggered by this binding , the spike components are reorganized into an extended intermediate in which hydrophobic loops of the three VP5* β-barrels , previously covered by the lectin domains ( chains A and B ) or by the spike body ( chain C ) , are inserted into the target cell membrane . An additional unknown triggering event would provoke the transition from this extended intermediate to a folded-back structure , in which the hydrophobic loops now point toward the virus particle . The remarkable similarity of the initial form , the extended intermediate , and the folded-back conformation to analogous structures involved in membrane fusion of enveloped viruses suggests that the energy released by these vast conformational changes is used by rotaviruses to disrupt the cell membrane . In this model , as with the fusion proteins of some enveloped viruses , proteolytic cleavage of the rotavirus spike protein VP4 into VP8* and VP5* primes rotavirus TLP for efficient infectivity [11] , [14] . Despite the availability of the atomic structure of the trypsinized rotavirus TLP , understanding of the structural changes involved in this process has been hampered by the lack of information regarding the structure of the undigested spike . Available single particle cryo-electron microscopy ( cryo-EM ) reconstructions of undigested TLP show no density for VP4 projecting from the VP7 shell [21] . This suggests that proteolytic processing of VP4 triggers undetermined structural changes in the spike that result in a more stable , rigid spike structure , as described by the atomic model , that mediates rotavirus entry . Here we used cryo-EM and cryo-ET to study the structure of the undigested rotavirus spike . Cryo-EM results showed that the structure of the uncleaved TLP of rotavirus strains SA11 and OSU is indistinguishable from that of the trypsin-digested particle , and concurs with the previously resolved near-atomic structure of the mature TLP . Cryo-ET analyses provided new insight into the organization of the uncleaved spike , and a model for its complete structure .
Rotavirus TLP were purified from cells infected with rotavirus strain SA11 , in the presence of trypsin ( TR-TLP ) , or in its absence in medium supplemented with the protease inhibitor leupeptin ( NTR-TLP ) . Purified particles were characterized by Coomassie blue staining of SDS-PAGE gels and by western blot analysis using an antibody specific for protein VP4/VP5* . In NTR-TLP samples , the VP4 spike protein was detected mainly as the 98 kDa unprocessed precursor form ( Figure 2A , S1 ) , whereas in TR-TLP , the trypsin proteolytic products VP8* ( 28 kDa ) and VP5* ( 55 kDa ) account for most of the VP4 protein mass ( Figure 2B , S1 ) . During virus purification , TLP spike stability depends both on viral strain and the proteolytic state of its VP4 components [22] . To estimate the amount of spike protein preserved in our preparations , we quantified VP4 ( in NTR-TLP ) or its product VP5* ( in TR-TLP ) relative to protein VP6 . Densitometric analysis of the Coomassie-stained gels produced values of 70±3% and 85±6% of the stoichiometric amount for NTR- and TR-TLP , respectively , which indicates that most spike protein was maintained to a similar extent in both samples . Cryo-EM analysis of NTR- and TR-TLP ( Figure 2C , D ) showed a homogeneous population of well-preserved rotavirus particles; in some , VP4 ( or VP8*/VP5* ) spikes can be visualized projecting from the virion surface ( Figure 2C , D , arrowheads ) . Three-dimensional reconstructions ( 3DR ) were calculated for NTR- and TR-TLP with a resolution of 12 . 8 Å and 11 . 9 Å , respectively ( Figure 3 ) , obtained at a Fourier shell correlation ( FSC ) threshold of 0 . 3 ( Figure S2 ) . At the resolution achieved , the 3DR for NTR-TLP ( Figure 3A–C ) and TR-TLP ( Figure 3D–F ) were virtually indistinguishable; a difference map calculated between them showed no significant differences . The molecular architecture of the spike in both particles ( Figure 3C , F ) is consistent with previous structural studies for TR-TLP [6] , [23] , in which the cleaved spike adopts a distinctive , rigid bilobulate shape divided into a head , body , stalk and foot domains [2] ( Figure 1 , S3 ) . Comparison of the relative density of spikes in both density maps using VP2-VP6-VP7 shell density as a reference ( Figure 3B , E; arrowheads ) showed an equivalent occupancy level ( 58 and 50% for NTR- and TR-TLP , respectively ) . The almost identical structure observed for NTR and TR spikes ( Figure 3C , F ) contrasts with a previous report for the SA11-4F rotavirus strain , in which the spikes were resolved in the cryo-EM 3DR of the TR-TLP , but were undetectable for undigested TLP [21] . This difference prompted us to verify whether the presence of the protease inhibitor leupeptin or the purification method affected our results . To exclude these possibilities , NTR-TLP were produced in the absence of leupeptin , following the purification method described previously [21] . Analysis of these capsids produced a virion map equivalent to previous NTR- and TR-TLP ( Figure S2 and S4 ) . To ascertain whether these differences are strain-specific , NTR- and TR-TLP were produced from the porcine strain OSU [24] and analyzed ( Figure S5 , S6 , S7 ) . Cryo-EM 3DR of OSU NTR- and TR-TLP are essentially indistinguishable from each other . There were no significant differences between the OSU strain density maps or when they were compared with the 3DR of the SA11 particles . These results show that spikes formed by trimers of undigested VP4 have a conformation similar to that of the trypsin-digested entry-primed rotavirus particles . For the simian and porcine strains analyzed in this study , ordering of the VP4 spike in a rigid bilobulate conformation is independent of trypsin digestion . To study the effect of trypsin cleavage on infectivity , we determined the specific infectivity of both TLP types , before and after trypsin treatment ( Figure 4 ) . In vitro trypsin treatment of NTR-TLP resulted in disappearance of the VP4 band and appearance of proteolytic products VP8* and VP5*; there were no detectable changes in the protein profile following similar treatment of TR-TLP ( Figure 4A , B , grey arrows ) . Due to the trypsin dependence for rotavirus plaque formation , the specific infectivity of mock-treated TLP was evaluated in a focus-forming assay in the absence of trypsin , in which expression of the viral protein NSP4 was used to detect infected cells ( Figure 4C , D ) . The background infectivity in NTR-TLP preparations is attributed mainly to the activity of proteases released during cell lysis [14] . Undigested NTR-TLP had ∼1 . 5 logarithmic units lower specific infectivity than undigested TR-TLP ( 1 . 89 for SA11 , p<0 . 02; 1 . 56 for OSU , p<0 . 005 ) . The specific infectivity of trypsin-treated TLP was determined in a plaque-forming assay that directly tests for infective particles able produce infective progeny . In this assay , trypsin-activated NTR- and TR-TLP showed specific infectivity levels with no significant differences ( Figure 4E , F ) . The results demonstrate that trypsin treatment enhances NTR-TLP specific infectivity to a level similar to that of trypsin-activated TR-TLP , as shown for several rotavirus strains [14] , [22] . Although we detected no structural differences between NTR- and TR-TLP by single particle cryo-EM 3DR , proteolytic processing of VP4 is necessary for efficient viral infectivity . The densities for the spikes in single particle cryo-EM analysis of NTR- and TR-TLP can be assigned to most of the three VP4 polypeptide chains ( A , B and C ) that compose the spikes , with the exception of the lectin domain of the VP4-C molecule ( Figure 1 ) . It is suggested that this lectin domain is lost during TR-TLP preparation [6] . In NTR spikes , it is covalently bound to the rest of the VP4 molecule , which indicates that the density for this domain is smeared due to the icosahedral averaging imposed during 3DR . We used cryo-ET to overcome this limitation and study the structure of SA11 strain NTR-TLP , a strategy used successfully to analyze surface proteins of enveloped viruses and non-symmetric elements in icosahedral viruses [25] , [26] . We collected several cryo-tomographic series of projection images of SA11 NTR- and TR-TLP covering the angular range from −66° to +66° . Tomograms from these tilt-series were reconstructed to obtain the averaged map of 607 and 242 single NTR and TR particles , respectively ( Figure 5A–D ) . Virtual sections from individual particles showed an electron-dense region near the geometric center of some particles ( ∼30% and ∼15% of NTR and TR , respectively , Figure 5A , C , white arrowheads ) , which can only be associated with the genomic dsRNA . This structure is reminiscent of the dsRNA condensation detected by cryo-EM analysis of TR-TLP in the presence of ammonium ions at high pH [27] , although the biological importance of this feature is not clear . Projecting densities that correspond to the virion spikes were clearly visible on the outer particle surface of both samples ( Figure 5A , C , black arrowheads ) . Subtomograms of individual virions were extracted ( Figure 5B , D ) , aligned and averaged , considering icosahedral symmetry to optimize determination of the origin and orientation of each virion subvolume . In accordance with our results in single particle cryo-EM 3DR ( Figure 3 ) , the spikes in the final averaged density maps of the NTR- and TR-TLP showed no significant differences ( Figure 5 ) . This alignment process not only generated an average structure for the virions , but also allowed determination of the origin and orientation of each particle subvolume relative to the average density . We used this information , combined with knowledge of each spike position in the average structure and of their icosahedral symmetry relationships , to computationally extract and orient 36 , 420 and 14 , 580 spike subtomograms from the original non-symmetrized densities of the NTR- and TR-TLP , respectively . The extracted spike subtomograms were then reference-free classified using a maximum-likelihood algorithm that takes into account the missing wedge information [28] . In this process , no spike density was detected projecting from the VP7 shell for 28% of the NTR and 40% of the TR spike subtomograms , which could correspond to positions where spikes have been lost and those in which they are flexible or disordered . For the remaining subtomograms , the classification process converged to two classes for the subtomograms of the NTR spikes , whereas there was only one class in the TR spike subtomograms ( Figure 6A , B ) . Positions in which no density was detected and those assigned to a class were distributed randomly at the virus particle surface . Class 1 contains the majority of the NTR and TR spike subtomograms ( 47% for NTR , 60% for TR ) and yielded averages that greatly resemble the structure of the NTR- and TR-TLP spikes obtained when icosahedral symmetry was imposed on the 3DR from cryo-EM ( Figure 3 ) or cryo-ET data ( Figure 5 ) . Fitting of the atomic coordinates of trypsinized VP4 [6] into class 1 averages showed good agreement for the spike stalk , body and head ( Figure 6C ) . The lectin domain of the VP4-C molecule is the only VP4 region not accounted for by either the atomic model or the density maps . Although for the TR spike it could be argued that this lectin domain is lost after proteolytic cleavage , the existence of this class for the NTR subtomograms , in which the lectin domain is covalently bound to the remainder of the VP4-C molecule , indicates that this domain is more flexible in this molecule than the equivalent domain of the other VP4 molecules . Class 2 was detected only for NTR spikes , and contained 25% of the subtomograms . The averaged spike density is similar to that of class 1 , with an additional bulge at the base of the spike stalk ( Figure 6A , arrowheads ) . When the atomic coordinates of the TR VP4 ( Figure 6D ) were fitted to this averaged volume , the unassigned bulge density was compatible in size and shape with a single lectin domain ( Figure 6E ) . The terminal residues of this domain ( Leu65 and Leu224 , cyan and yellow spheres , respectively , in Figure 6E ) were located just above the last defined residues in the atomic model for the VP4-C flanking regions ( Lys29 and Glu264 , purple and orange spheres , respectively , in Figure 6C–E ) [6] . The evidence suggests that this density corresponds to the lectin domain of the VP4-C molecule that contributes to the spike stalk , and that the average density for class 2 subtomograms reflects the complete structure of the undigested rotavirus spike .
Recent reports suggest that the conformational changes undergone by the rotavirus spike protein VP4 are the main driving force behind membrane disruption and virus entry into the host cell [11] , [17] , [20] . For this process to be efficient , the rotavirus particle must be primed by proteolytic cleavage of VP4 into its mature products , VP8* and VP5* . Despite the availability of an atomic structure for the trypsinized rotavirus particle , our understanding of the molecular mechanisms that underlie the proteolytic enhancement of rotavirus infectivity has been hindered by the lack of a structure of the undigested spike . The aim of this study was to determine , using cryo-EM and cryo-ET , the structure of the uncleaved rotavirus to improve comprehension of the structural mechanisms underlying the proteolytic enhancement of rotavirus infectivity . Single particle cryo-EM reconstructions of the NTR- and TR-TLP of the simian SA11 and porcine OSU rotavirus strains yielded structures that showed no differences among them and were consistent with the near-atomic structure of the rotavirus RRV strain TR-TLP [6] . This indicates that the overall spike conformation achieved by the three complete undigested VP4 molecules is essentially maintained after trypsin activation . The interactions of the unprocessed VP4 molecules with the VP6 and VP7 trimers during assembly in the six-coordinated cavity are thus sufficient to configure these molecules in the A , B or C conformations , according to their relative position . This structure for the undigested spike is consistent with the available structural data for the TR-TLP particle , since the length of the trypsin-released segment of the loops is sufficient to bridge the observed C and N termini of VP8* and VP5* , respectively [6] . This architecture would also explain the differential trypsin sensitivity of unassembled and spike-assembled VP4 [29] , as most putative trypsin-sensitive sites are protected in the latter , with the exception of the known cleavage sites Arg230 , Arg241 , Arg247 and the proposed cleavage site at Lys29 in VP8* of VP4-C [6] . The observation of an equivalent structure at the cell interaction domain of cleaved and uncleaved spikes is also consistent with the finding that both particle types bind similarly to cell membranes [30] . Although trypsin cleavage has only a limited effect on spike structure , infectivity experiments showed that protease cleavage of the spike protein is essential for high levels of specific viral infectivity . These data suggest that whereas the fold shared by NTR and TR particles is attachment-competent , the spike must be primed by cleavage for further conformational changes . In this dependence on proteolytic activation , as well as in the nature of the conformational changes during viral entry , VP4 has a striking similarity to some membrane fusion proteins of enveloped viruses [11] , [17] . The class 1 viral fusion glycoproteins are synthesized as precursors that require protease activation for virus infectivity [31] , [32] . This necessary activation step is associated with relatively little structural rearrangement of the fusion protein , similar to our observations for rotavirus . For example , the atomic structures of the uncleaved and cleaved forms of the influenza prefusion hemagglutinin protein are largely superimposable , except for the 19-residue segment that includes the protease cleavage site [33] , [34] . In the uncleaved form , these residues are in an exposed loop; after cleavage , the fusion peptide in the newly-formed N terminus is buried in a nearby hydrophobic cavity . In the paramyxovirus parainfluenza virus 5 , structural movements between the cleaved and uncleaved forms of the fusion protein are also limited to the residues that compose and surround the protease recognition site; since the residues that compose the hydrophobic fusion peptide are already packed in the uncleaved structure , the conformational changes are even more subtle [35] . The cryo-EM-derived atomic structure of the rotavirus TR-TLP does not account for the lectin domain of VP4-C [6] . Results were similar for the NTR- and TR-TLP 3DR of both strains used in this study . The absence of density for this domain , which in NTR-TLP is covalently bound to the rest of the VP4-C subunit , indicates greater flexibility of this part of the molecule , resulting in loss of the density due to the icosahedral averaging imposed during 3DR . The classification of cryo-ET subvolumes allowed us to overcome this limitation , and the averages for the distinct classes provides a deeper understanding of the spike structure . The atomic model of the TR-TLP spike was fitted with good agreement to the averaged density of class 1 , the most abundant class for NTR-TLP spikes and the only class detected in TR-TLP spikes . Neither the averaged maps for class 1 nor the atomic coordinates detect the VP4-C lectin domain . This domain is also absent in all 3DR derived from cryo-EM single particle analysis , as well as the in the icosahedrally averaged maps of virion volumes obtained by cryo-ET . In the case of NTR-TLP , this domain is covalently linked to the remainder of the VP4-C molecule; classes 1 and 2 thus contain three complete VP4 molecules in NTR samples . Nonetheless , we only identified a density compatible with this domain in the class 2 averaged maps , observed only in NTR-TLP subtomograms . This apparent contradiction could be a result of VP4-C lectin domain flexibility . As illustrated in Figure 7 , spike subtomograms in which this domain is located near a central position ( 25% , white asterisk in Figure 7 , top ) generate the class 2 averaged density . Class 1 subvolumes ( 47% ) are composed of densities in which the lectin domain swings away from this central position ( black asterisks in Figure 7 , top ) and whose averaging results in disappearance of the density . In the case of the spike subtomograms from TR-TLP , the lack of a class equivalent to class 2 might indicate that trypsin digestion further increases lectin domain flexibility or , as suggested by analysis of the TR-TLP atomic structure , that a second cleavage in Lys29 releases the domain from the spike ( Figure 7 , bottom ) [6] . In both samples , a fraction of the subtomograms ( 28% of NTR and 40% of TR ) rendered averaged maps that show no density in the regions in which the spikes are located ( Figure 7 , No Spike density ) . These subtomograms would include positions in which the spike is very flexible , has been lost , or its structure has been damaged due to the purification conditions ( particularly the organic extraction procedure [22] ) . Biochemical analysis of the TLP preparations ( Figure 2 ) shows that a percentage of the predicted VP4 molecules is not present in the purified NTR ( 30% ) or TR ( 15% ) particles . Although we cannot rule out the possibility that all volumes in these fractions correspond to positions at which the spike has been lost , the large percentage of subtomograms included in this group , especially in the case of TR-TLP positions , suggests that they also include positions in which the spike is present but is highly flexible and whose density is lost after averaging ( Figure 7 ) . It can also be argued that the greater percentage of tomograms in this fraction in TR-TLP reflects a greater degree of freedom induced by trypsin cleavage of VP4 into its products , VP8* and VP5* . The redundancy derived from the virion icosahedral symmetry could explain its tolerance for the presence of defective spikes in the particle . Indeed , the relatively low occupancy observed in in vitro recoated particles is sufficient for a very efficient infectivity [36] . Previous cryo-EM single particle analysis of the NTR-TLP structure did not detect a density corresponding to the spike structure [21] . These different results could be attributed to the nature of the SA11-4F strain used in the previous 3DR , which is unique in its ability to produce small clear plaques in the absence of trypsin , and for its extreme sensitivity to protease digestion [37] . These characteristics arose from the reassortment of a segment 4 that encodes a VP4 gene from a bovine rotavirus on a SA11 genetic background [38] , [39] . The molecular basis of the distinct behavior of SA11 and SA11-4F strains is thus probably due to changes in the sequence of the reassorted VP4 molecule ( 129 changes in a total of 776 residues ) . The large number of variations makes it impossible to determine the amino acids involved . Nonetheless , the VP4 region that interacts with VP6 , which mediates spike foot recruitment and trimerization , is conserved . There are several changes in the VP7-contacting region of VP4 , which dictates how the spike projects , as well as in the preceding linker , which is not resolved in the atomic structure [6] . The SA11 and OSU strains used in this study show more standard behavior , with no evidence of interspecies reassortment . Based on our results , we hypothesize that whereas most NTR-TLP spikes in SA11 and OSU strains are stabilized , the majority of VP4 molecules in the SA11-4F strain are not stabilized , and the spike density is lost when it is averaged and icosahedral symmetry is imposed . We suggest that the structures we observed for SA11 and OSU uncleaved spikes represent a more general architecture , and that SA11-4F is an extreme example of uncleaved spike flexibility . In summary , our cryo-EM studies of two unrelated model rotavirus strains show that in the absence of trypsin cleavage , most of the three VP4 molecules that compose the spike adopt a stable conformation , similar to that of the mature cleaved TLP . Cryo-ET results reinforce this conclusion and , additionally , evidence the great flexibility of the lectin domain of the VP4-C chain , providing us with a model for the complete structure of the uncleaved spike . Our findings indicate that cleavage of the spike proteins is important for infectivity because it influences later events , probably those conformational changes proposed to mediate membrane disruption .
The monkey epithelial cell line MA104 ( ECACC 85102918 ) was cultured in MEM with 10% fetal calf serum and used between passages 7 and 24 . The simian agent 11 rotavirus strain ( SA11 , [39] , [40] ) was obtained from Dr . J . Buesa , ( University of Valencia , Valencia , Spain ) , and the Ohio State University porcine strain ( OSU; [24] ) from Dr . O . Burrone ( ICGEB , Trieste , Italy ) . Both strains were cloned by four successive plaque isolation steps in MA104 cells . The clones SA11-C4111 and OSU-C5111 were selected and amplified . cDNAs of the complete genome segments of the two viral clones were obtained following procedures described by Potgieter et al . [41] , cloned in the plasmid pJET1 . 2 ( Fermentas ) and sequenced . Given the complex history of the SA11 family of viruses [39] , [42] , we analyzed the genome sequence of the SA11-C4111 strain . The results showed a SA11-like genome very similar to that of the N5 strain [43] , with no evidence of genomic reassortment . The amplified viruses were used within three passages of the last plaque isolation step . For simplicity , here we refer to these clones as SA11 and OSU . TLP were produced and purified by ultracentrifugation in CsCl gradients as described by Patton et al . [44] , with minor modifications ( see supporting Text S1 ) . In parallel experiments , aliquots of the TLP samples were vitrified ( below ) , treated with SDS-PAGE sample buffer for biochemical characterization or analyzed for infectivity . Viral infectivity was determined by plaque assays and fluorescent focus assays , essentially as described by Arnold et al . [45] with minor modifications ( see supporting Text S1 ) . NTR and TR-TLP samples ( 5 µl ) were applied to one side of acetone-washed Quantifoil R 2/2 holey grids , blotted , and plunged into liquid ethane using a Leica EM CPC cryo-fixation unit . Cryo-EM images were recorded in low-dose conditions ( ∼10 e−/Å2 ) , in a Tecnai G2 electron microscope operating at 200 kV . For SA11 NTR and TR samples , micrographs were recorded at a nominal magnification of 50 , 000X . SA11 NTR-TLP produced in the absence of leupeptin and OSU samples were imaged on a FEI Eagle 4k CCD at a detector magnification of 67 , 873X ( 2 . 21 Å/pixel sampling rate ) . General image processing operations were performed using Bsoft [46] and Xmipp [47] software packages . Graphic representations were produced by UCSF Chimera [48] . Micrographs were digitized using a Nikon Super CoolScan 9000 ED at a 6 . 35 µm step size , or a Zeiss TD scanner at a 7 µm step size , to yield 1 . 27 Å or 1 . 4 Å pixel size in the specimen , respectively . X3d [49] was used to manually select 3 , 802 , 2 , 980 , 2 , 150 , 4 , 100 and 2 , 100 individual images for SA11 NTR- , SA11 TR- , SA11 NTR - leupeptin , OSU NTR- and OSU TR-TLP , respectively . Defocus was double determined with bshow [46] and CTFfind [50] , and the CTF were corrected in the images by flipping phases in the required lobes . The published structure of the rotavirus VP7-recoated particle [12] , low-pass filtered to 30 Å , was used for the initial determination of the origin and orientation of each particle for all samples . As these recoated particles lack VP4 , any model bias at the spike density is avoided . Xmipp iterative projection matching was carried out to determine and refine the origin and orientation of each particle . Reconstructions were computed using interpolation in Fourier space . After each iteration , resolution was assessed by FSC , applying a correlation limit of 0 . 5 between two independent reconstructions . The final reconstructions combined 3 , 421 images for SA11 NTR , 2 , 682 for SA11 TR , 1 , 935 for SA11 NTR - leupeptin , 3 , 690 for OSU NTR and 1 , 890 for OSU TR . Amplitude decay was corrected by adjusting the spatial frequency components of the cryo-EM maps to the decay profile of the atomic map of rotavirus TLP ( PDBs 3N09 and 2GH8 ) . This adjustment was applied in the frequency range from 340 Å to the maximum resolution achieved , and a soft low-pass filter was applied . Amplitude decay was also calculated and corrected with Embfactor [51] , with similar results . Samples were mixed with 10 nm gold particles and vitrified as described above . Tomographic tilt-series were recorded in a Tecnai G2 electron microscope operating at 200 kV on a FEI Eagle 4k CCD using the FEI Xplore3D software at a detector magnification of 32 , 609X ( 4 . 6 Å/pixel sampling rate ) every 1 . 5 degrees . Images were acquired with a defocus ranging from 5 to 8 µm , and an accumulated total dose from 90 to 120 e/Å . Tilted series were processed using IMOD [52] and CTF corrected using TOMOCTF [53] . A final number of 4 and 3 tomograms were reconstructed for SA11 NTR and TR samples , respectively , using unfiltered weighted back projection algorithms implemented in the TOMO3D package [54] to recover all the high frequencies for subvolume averaging process . IMOD software was used to manually select , and extract 607 and 243 virions from SA11 NTR and TR samples , respectively . Subvolumes were aligned and averaged using the MLTomo routine [28] from Xmipp , considering icosahedral symmetry to optimize the origin and orientation determination at this step . This process was performed using the previously obtained cryo-EM 3DR as initial template , as well as in a reference-free manner . Both approaches yielded equivalent results . The final averaged volumes were used to determine the 3D position of the spikes . This information , together with the origin and orientation assigned to each particle , were used to automatically extract 36 , 420 and 14 , 520 subvolumes for each spike in the original asymmetric tomograms of SA11 NTR and TR , respectively . The spike subtomograms were classified and averaged with MLTomo . Independently of the initial number of classes used , the classification of the NTR spikes converged to 3 groups containing 10 , 084 ( 28% , no spike density ) , 17 , 281 ( 47% , class 1 ) and 9 , 055 ( 25% , class 2 ) volumes , whereas classification of the SA11 TR spikes converged to two groups with 5 , 810 ( 40% , no spike density ) and 8 , 710 ( 60% , class 1 ) volumes . Sequences corresponding to the different SA-C4111 and OSU-C5111 genomic segments are deposited in GenBank ( accession numbers in Table S1 ) . The 3DR and averaged subtomograms are deposited in the Electron Microscopy Data Bank ( EMDB; accession codes in Table S2 ) . | Rotavirus is responsible for more than 400 , 000 annual infant deaths worldwide . Its viral particle bears 60 protuberant spikes that constitute the machinery responsible for virus binding to and entry into the host cell . For efficient infection , the protein molecules that build the spike must be cleaved . Despite the importance of this activation step , the nature of the changes induced in the spike structure is unknown . According to the current hypothesis , the uncleaved spike is very flexible , and activation stabilizes the spike in an entry-competent conformation . Here we used distinct electron microscopy techniques to determine the structure of the uncleaved particle in two model rotavirus strains . Our results provide a complete structure of the uncleaved spike and demonstrate that cleaved and uncleaved spikes have similar conformations , indicating that proteolytic processing is not involved in stabilization of the spike . We suggest that spike processing is important for infection since it is necessary to allow the spike domain movements involved in rotavirus entry . | [
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"micro... | 2014 | New Insights into Rotavirus Entry Machinery: Stabilization of Rotavirus Spike Conformation Is Independent of Trypsin Cleavage |
Folds are the basic building blocks of protein structures . Understanding the emergence of novel protein folds is an important step towards understanding the rules governing the evolution of protein structure and function and for developing tools for protein structure modeling and design . We explored the frequency of occurrences of an exhaustively classified library of supersecondary structural elements ( Smotifs ) , in protein structures , in order to identify features that would define a fold as novel compared to previously known structures . We found that a surprisingly small set of Smotifs is sufficient to describe all known folds . Furthermore , novel folds do not require novel Smotifs , but rather are a new combination of existing ones . Novel folds can be typified by the inclusion of a relatively higher number of rarely occurring Smotifs in their structures and , to a lesser extent , by a novel topological combination of commonly occurring Smotifs . When investigating the structural features of Smotifs , we found that the top 10% of most frequent ones have a higher fraction of internal contacts , while some of the most rare motifs are larger , and contain a longer loop region .
Under physiological conditions most proteins self-assemble into unique structures that dictate their interactions with other molecules and determine their function . Protein structures can be decomposed into individually folding units , so called folds [1] . A fold is determined from the number , arrangement , and connectivity ( topology ) of secondary structure elements [2] . Manually curated [3] , semi–automated [4] and automated approaches [5] , [6] classify protein folds by organizing them into hierarchical systems . Due to the lack of a clear understanding of how to define and classify folds , these various subjective approaches carry substantial inconsistencies [2] , [7] . Meanwhile , recent studies paint a more nuanced picture of the fold universe of proteins , one that is more continuous in nature , where some higher density hubs formed by related structures correspond to and connect known folds [8] , [9] , [10] , [11] . Part of the motivation to rethink the nature of the protein fold universe is provided by the apparent success of molecular modeling efforts that use short amino acid segments from known protein structures to build up novel folds [12] . Additional motivation comes from anecdotal examples that identify structures representing transitions between previously described folds , which either results in a unification of different fold families or suggests removing fold definitions altogether [13] , [14] . One such example is described for the RIFT domain , where it is suggested that starting from an ancestral RIFT domain a strand invasion and a strand–swap event ( with subsequent duplication and fusion events ) resulted in the emergence of the swapped hairpin and double-psi beta barrel folds , respectively [15] . These folds cannot be interconverted with simple topological modifications , such as circular permutation , although their common evolutionary origin has been established . Since the definition of complete folds is ambiguous , one has to consider structural definitions of smaller ( local ) entities , such as supersecondary structure elements , that could describe protein folds and the structure universe in a more quantitative and systematic nature . Supersecondary structure elements are defined as a number of regular secondary structure elements that are linked by loops ( e . g . Rossmann , helix-turn-helix , four strand Greek key , β-meander motifs etc . ) . Folds are formed by the overlapping combination of various supersecondary elements , which are shared among different proteins and sometimes highly repeated within the same one . This observation prompted the theory of a relic peptide world [16] , which proposes that modern , stable proteins are the results of duplication , mutation , shuffling and fusion of a limited set of relic peptides . Various efforts have tried to explore possible tool sets of supersecondary elements , such as antiparallel ββ-sheets [17] , αββ and ββα motifs [18] , αα-turn motifs [19] , four helix bundles [20] and so on . Building on these earlier efforts , we introduced a new , general , supersecondary structure classification that fully describes all known protein structures [21] . In this schema a basic supersecondary motif , which we will refer to as Smotif , is composed of two regular secondary structure elements linked by a loop . Smotifs are characterized in protein structures by the types of sequential secondary structures and the geometry of the orientation of the secondary structures with respect to each other , as described by four internal coordinates [21] , [22] . The definition for supersecondary structure elements for Smotifs is different from other studies or from the above mentioned textbook examples and it is rooted in practical reasoning . In this study we explored Smotifs of only two connected secondary structures because for this subset we had indication from prior work that the number of possible combinations are limited . Also , if we used a definition that has higher number of connected secondary structures e . g . 3 or more , the number of combinations would be very large and would prevent us from a systematic classification . Recently , we demonstrated that Smotifs with loop fragments having lengths up to 12 residues , together with their bracing secondary structure elements are exhaustively sampled in the Protein Data Bank ( PDB ) . We also demonstrated that the available set of Smotifs has been essentially unchanged at least for the last 5 years , despite that during this time the sequence databases have doubled and a significant number of new folds have emerged [23] . These previous observations motivated us to analyze the occurrence of Smotifs among protein folds and explore the question of what is really unique about a structure that is identified as “novel” . Does the emergence of a novel fold coincide with the emergence of novel Smotifs that are integrated into a structure with known ones ? Is it possible to generate novel folds solely from existing Smotifs ? What are the rules that guide combinations of Smotifs to an apparently novel fold ? Is the novelty of a certain Smotif or the novelty of combining well-known Smotifs the driving force behind the appearance of novel folds ? These questions might be relevant to shed light on the rules governing protein structure evolution . There are practical considerations to understanding the actual limits of the definition and novelty of a fold . Exploring these issues can aid in developing more accurate structure modeling tools and support the design and realization of new and experimentally accessible molecular shapes .
We explored the frequency of occurrences of all Smotifs in all protein folds . We established an exhaustive library of 324 types of Smotifs , as classified by their geometry , for each of the four combinations of possible bracing secondary structure elements . We have shown that this geometrical classification of Smotifs correctly captures local structural similarity ( see Definition of optimal classification of Smotif geometry in Material and Methods ) . Previously we have shown that Smotifs are useful for loop prediction because loop conformations ( as defined by the orientation of the embracing secondary structures ) up to 10–12 residues are exhaustively sampled in PDB [21] , [23] . We further refined this observation by exploring the increase of coverage of Smotifs in PDB over time ( Fig . 1 ) . Approximately 10 years ago all categories of Smotifs were already represented by at least one example . The occurrence of Smotif geometries in different types of protein folds is uneven ( Fig . 2 ) . There are some Smotifs whose geometries are ubiquitous , and occur in many different folds , while others are specific to a few . Fig . 2 displays a ββ class Smotif ( a ) that is highly represented across different folds , corresponding to a geometry that tightly aligns two ββ-strands and , thus , allows many non-bonded contacts to be formed . Meanwhile another Smotif within the ββ class ( b ) , which is structurally similar but where one of the β-strands is tilted , has a very low occurrence within known folds . Similar trends can be observed for αα , αβ , and βα Smotifs: Smotifs forming extensive non-bonded interactions occur more frequently in known folds . We explored the normalized number of intra-motif non-bonded contacts as a function of Smotif frequency and found an exponential correlation between the number of contacts and frequency of motif usage ( correlation of r = 0 . 83 as fitted on a logarithmic scale ) , indicating that the most frequent motifs ( top 10% ) are forming more contacts . However , there is not a statistically significant correlation for the rest of the Smotif frequencies ( Fig . 3 ) . Another suspected factor for Smotif preferences is their size , as large Smotifs simply cannot fit into smaller folds . Here we found no clear tendency except once again the top 10% most frequent Smotifs , which indeed tend to be smaller ( on average 12 ( σ = 6 ) residues total within the bracing secondary structures , without counting the variable number of loop residues , while motifs at all other frequencies are generally formed by 16 residues ( σ = 8 ) ) . The longer the loop connecting the bracing secondary structures , the more likely that contacts will be formed between non-proximal secondary structures: e . g . a ββ-type Smotif that connects together strands of two β-sheets . A correlation was found between the length of the loop within Smotifs and the frequency of Smotif usage in folds among the 50% least frequent Smotifs . However , Smotifs extracted from new folds do not show correlation between Smotifs size or loops length and the frequency of Smotifs: i . e . new folds are not necessarily formed by large Smotifs and do not necessarily have particularly long loops ( data not shown ) . We also explored whether solvent accessibility is correlated with the frequency of Smotifs , as one could suspect that buried , conserved cores would be formed by frequently occurring Smotifs and structural regions outside the common core would have a trend to comprise a higher proportion of rare Smotifs , due to a less restrictive structural environment . However , we could not find any statistically significant correlation between the frequency of Smotifs and their exposure ( Fig . S1 ) . Since the repertoire of Smotifs seems to have come close to saturation ( Fig . 1 ) [23] , this prompts the question of what is really unique about a fold structure when it is identified as “novel” . Detecting novel folds is a non-trivial question . Automated structural comparisons are often followed by manual inspection to characterize new protein structures . We have explored proteins that were classified as novel at the time of their discovery in two expert validated sources , in the archives of SCOP [3] and in the series of CASP experiments [24] . We found that proteins that were considered novel folds at CASP 3–6 meetings ( years 1998–2004 ) and in SCOP 1 . 73 , 1 . 75 ( years 2007–2009 ) do not have any novel Smotif geometries that were not present in previously solved structures . In other words , none of the Smotifs of novel folds have a unique geometry ( Table 1 ) . For instance , as early as the third round of CASP Meetings in 1998 [25] , all of the targets identified as novel folds by the experts could have been reconstructed using Smotifs from known protein structures . If , in our Smotif comparison , we required not only a match in the geometry between the Smotifs in the novel structures and those in the solved structures , but also required identical lengths of the flanking secondary structures , still less than 6% of the Smotifs in novel folds at CASP meetings would not have a match in already known structures . Similarly , we have checked the motif composition of new folds from the archives of SCOP in the 1 . 73 ( 2007 November ) and 1 . 75 ( 2009 June ) releases . These contain a total of 233 new folds from 1140 proteins . Similar to the CASP targets , none of these novel folds had a Smotif that was not already observed in a previously known fold . With the stricter definition , that requires a fit of the length of the bracing secondary structures , still less than 1% proved to be novel Smotifs . Initially , we found 47 Smotifs ( out of the 8056 analyzed ) that appeared to be new . However , after manual inspection , it turned out that these are all explained by an artifact of replacing obsolete PDB entries with newer ones , with a corresponding newer date . The above observations suggest that recently solved novel folds do not imply the emergence of new Smotifs , and that a protein with a novel fold can be constructed using Smotifs from already existing protein folds . As an illustration , T0181 ( PDB code: 1nyn ) , a new fold submitted to CASP5 , can be constructed from 7 overlapping Smotifs , all of which can be located in previously solved structures of other proteins representing a variety of different folds ( Fig . 4 ) . When we explored the frequency of occurrence of Smotifs in the non-redundant set of known folds , we observed that novel folds have a larger fraction of Smotifs that have a low frequency of occurrence in the PDB ( Fig . 5 CASP dataset; see Fig . S3 and S4 for distribution of Smotif frequency calculated for SCOP 1 . 75 and SCOP 1 . 73 respectively ) . On the other hand , superfolds [26] , those that are adopted by many different sequences often with different functions , are built by Smotifs that occur with medium or high frequencies in existing folds . This implies that novel folds are composed of a new permutation of existing Smotifs and , specifically , a structure will have a greater likelihood of being “novel” if the structure is enriched with rarely occurring Smotifs . This phenomenon becomes especially apparent when the relative frequency of occurrences of Smotifs drops below 0 . 09 ( Fig . 5 , Fig . S2 , Fig . S3 ) . Two examples of the above observations are illustrated in Fig . 6 . The first example is the new fold target T0181 , discussed above ( PDB code: 1nyn; Fig . 6A ) . The second example is a member of the immunoglobulin fold ( PDB code: 1gyv; Fig . 6B ) , which is one of the most populated folds . Target 181 , a new fold structure , can be decomposed into 7 Smotifs , where five are considered low frequency ( i . e . frequency smaller than 0 . 01 , or less than 1% ) . On the other hand , for a representative structure of the immunoglobulin fold ( SCOP fold descriptor 48725 , Immunoglobulin-like beta sandwich ) , the opposite situation occurs . Five out of the 7 Smotifs that comprise the structure are very well represented ( high frequency ) in the pool of Smotifs ( Fig . 6B ) . One could speculate that some novel folds were recently discovered simply because of difficulty in experimental determination , i . e . these structures are harder to solve . We used the XtalPred program [27] to predict the crystallizability of 347 new folds and 2802 known folds , all solved approximately in the same time period ( since SCOP 1 . 73 released in 2007 ) . We found that new folds from the most recent SCOP release 1 . 75 indeed have a small tendency to be less feasible for experiments . However , XtalPred and other prediction methods for protein crystallizability heavily rely on known homologs of a query sequence . The rationale is that if a protein with a similar sequence has been solved before it usually indicates that this particular protein family is more experimentally tractable . This artifact is illustrated in our analysis by the fact that while new folds from SCOP 1 . 75 do show less favorable XtalPred scores as compared to known folds , this difference disappears in case of new folds of SCOP 1 . 73 ( Fig . 7 ) . Another plausible way to generate new folds is to combine , otherwise common Smotifs in an unusual sequence , to result in a new topology . To explore this , we calculated a Novelty Z-score for each protein , which was obtained from the product of individual Smotif frequencies . The hypothesis is that if the Novelty Z-score of some novel folds is similar to that of known folds , then the novelty for these cases must be a consequence of a never before seen combination of otherwise common Smotifs rather than a result of being constructed from rare Smotifs . And while new folds from the CASP dataset do show a distribution of Novelty Z-scores biased towards low values ( Fig . S4 ) , in the case of SCOP 1 . 75 ( Fig . S5 ) and SCOP 1 . 73 ( Fig . S6 ) , most novel folds are indistinguishable from already known structures in terms of their overall Novelty Z-scores , which indicates that these structures may indeed be a new topological arrangement of common Smotifs . However , one may note the more frequent extreme negative outliers in the distributions for the novel folds in these datasets ( averages and standard deviations are −1 . 03±1 . 1 , 0 . 25±1 . 35 and 0 . 0±1 . 0 for CASP dataset , SCOP 1 . 75 , and SCOP 1 . 73 , respectively ) . This means that although novel folds are often built using a higher proportion of rare Smotifs , in many cases these folds are novel because their Smotifs are assembled in an unusual sequence . This is illustrated with Target T0201 ( CASP 6 ) and the S50S ribosomal protein L6P ( PDB code 1s72 chain E ) that share 3 out of 6 of their Smotifs ( Fig . 8 ) . However the sequential arrangement of these shared Smotifs is different , yielding different topologies .
Since the early nineteen-nineties , it has been clear that the universe of protein folds is much more limited and redundant than the sequences adopting them [28] . Structural biology and the recently launched Structural Genomics efforts have discovered a large subset of possible fold shapes . Many predictions suggest that most of the folds are already known [28] , [29] , [30] . Meanwhile , by solving many of the possible folds , the characteristic differences earlier described among fold definitions has become more blurred [8] , [10] , [31] . In practice , discovering all possible folds may be an impossible task , partly because it is clear now that the definition of folds is highly subjective [2] , and partly because the distribution of folds is extremely uneven: while only a dozen superfolds seem to populate half of a typical genome , and only about 200 folds populate 2/3 of it , it is possible that many thousands of more rarely occurring shapes need to be discovered to reach 80–90% coverage of all possible shapes that were established during evolution [32][33] . In this work we explored the entirety of protein shapes from the perspective of their Smotif building blocks , which can be defined more objectively than the folds themselves , and which are observed to be nearly completely sampled in the currently known structures . Using this repertoire of Smotifs , we observed that novel folds can be distinguished from already discovered ones by the presence of rare Smotifs and , less often as an unusual combination of otherwise common Smotifs . The most frequently used motifs have a higher average number of internal contacts , while some of the rarest motifs are larger , and contain longer linker regions . These observations may be useful starting points for future works to identifying or designing sequences that are likely to constitute “novel” folds . While in this work we defined Smotifs according to practical considerations and did not investigate if these Smotifs or subset of them could also serve as possible units for structural evolution , it is noteworthy to mention other studies that identified similar structural elements as possible building blocks of structural hierarchy using different approaches . The so called Closed Loops were identified by their close Cα-Cα contacts from solution structures and found to have a nearly standard size ( 27 residues +/−5 ) . This typical size distribution of Closed Loops was supported by polymer statistics , as it is the theoretical optimal size for loop closure and subsequently suggested to be a universal building block of protein folds [34] , [35] . In another approach , dynamic Monte Carlo simulation of alpha carbon chain of the nearest 24 neighbor in a lattice model identified clusters of “most interacting residues” , which serve as anchors for protein folding [36] . These anchors were found to be conserved hydrophobic clusters of residues that keep together the so called Tightened End Fragments , which essentially correspond to the Closed Loop definition . Finally a most recent paper updates on the idea of ancient relic peptides of length 20–40 residues that co-occur in different structural contexts , and suggested to be an ancestral pool of peptide modules [37] .
All structures from CASP 3 , 4 , 5 , 6 meetings [38] that were manually identified as “novel folds” at the time of the experiment: CASP3 ( protein identification ( PDB code ) : T0052 ( 2ezm ) , T0059 ( 1d3b ) , T0063 ( 1bkb ) , T0067 ( 1bd9 ) , T0071 ( 1b9k ) , T0080 ( 1bnk ) , and T0083 ( 1dw9 ) ) , CASP 4 ( T0086 ( 1fw9 ) , T0116_3a ( 1ewq ) , T0116_3b ( 1ewq ) , T0120_1 ( 1fu1 ) , and T0124 ( 1jad ) ) , CASP5 ( T0129 ( 1izm ) , T0149_2 ( 1nij ) , T0161 ( 1mw5 ) , and T0162_2 ( 1izn ) ) and CASP6 ( T0201 ( 1s12 ) , T0209_2 ( 1xqb ) , T0216_1 ( 1vl4 ) , T0216_2 ( 1vl4 ) , T0238 ( 1w33 ) , T0242 ( 2blk ) and T0248_2 ( 1td6 ) ) were collected . Four tailored datasets of previously solved protein structures were generated for comparisons with the “novel” folds of each CASP experiment ( see below ) . The tailored datasets did not contain any structure that was deposited after June 1998 ( 6 , 366 entries ) , June 2000 ( 10 , 199 entries ) , June 2002 ( 15 , 234 entries ) and June 2004 ( 22 , 076 entries ) to compare with targets from CASP3 , CASP4 , CASP5 , and CASP6 respectively . Similarly , four SCOP [3] database releases were used for calculating motif frequencies ( see below ) : SCOP 1 . 39 ( CASP3 new fold set ) , SCOP 1 . 53 ( CASP4 new fold set ) , SCOP 1 . 61 ( CASP5 new fold set ) , and SCOP 1 . 69 ( for CASP6 new fold set ) . Since CASP meetings start in June and SCOP databases were released after June during the same year , all structures that were present in the SCOP database with a deposition date after June were removed . Similarly , we have downloaded all “new folds” from the SCOP 1 . 73 and 1 . 75 releases , 123 and 110 folds , respectively , that are part of a total of 1140 proteins . The list of new folds for earlier releases can be found at SCOP via History link ( http://scop . mrc-lmb . cam . ac . uk/scop/index_prevrel . html ) . A Smotif is defined by two consecutive regular secondary elements ( i . e . α-helix or β-strand ) , connected by a loop . The N and C-terminal regular secondary structures of a Smotif are referred as SS1 and SS2 , respectively . Motif geometry refers to the local spatial arrangement of SS1 with respect to SS2 as introduced in [22] using four internal coordinates . Briefly , SS1 and SS2 were represented by their principal moments of inertia ( M1 and M2 ) . If P1 and P2 are the end point of SS1 and start point of SS2 , and L is the vector between P1 and P2 , then plane Π is defined by M1 and L and plane Γ is defned by M1 and the normal to plane Π . Geometry of a Smotif is expressed by four measures: the distance ( D ) between the C-terminal of SS1 and the N-terminal of SS2 ( distance between P1 and P2 ) and three angles: a hoist ( δ ) : angle between L and M1 , a packing ( θ ) : angle between M1 and M2 , and a meridian ( ρ ) : angle between M2 and plane Γ ( Fig . 2 in [21] ) . A library has been established that classifies each Smotif in all PDB structures . This library is organized in a two-level hierarchy: in the first level of classification , ( i ) Smotifs are identified according to the type of bracing secondary structures: αα , αβ , βα and ββ according to the definition of secondary structure by the DSSP program [39] . At the second level , ( ii ) Smotifs are grouped according to their geometry , as described above [21] , [22] . A protein structure can , therefore , be expressed as a string of overlapping Smotifs where the SS2 from one Smotif constitutes the SS1 in the following Smotif . The geometrical values used in the second level of classification are distributed in a continuous space . Distance is distributed between 0 and 40 Å . ( values larger than 40 Å are assigned to 40 ) , δ and θ angles span from 0 to 180 degrees , and the ρ angle spans from 0 to 360 degrees . In order to compare Smotif geometries , the parameter spaces of geometrical values were binned , where each bin is defined by the 4 parameters described above . A range of binning sizes and parameter intervals were explored for the four variables in order to get the sharpest partitioning power of the geometrical space with the smallest number of possible bins ( Fig . S7 ) . The quality of the binning was assessed by calculating the RMSD ( Root Mean Square Deviation ) and the LGA scores [40] upon structural superposition for all Smotifs that were classified in the same or different geometrical bin . The optimal bin partitioning for each parameter was obtained by studying the distribution of distance and angle values of Smotifs in SCOP 1 . 71 proteins and resulted in only 324 types of Smotif definitions using the following binning values: 4 Å bins for distance , 60 degree bins for δ and θ starting at 0 degree , and 60 degree bins for ρ , starting at 30 degree . At this level of bin resolution the RMSD upon structural superposition of more than 75% of Smotifs that belong to the same geometrical bin falls below 1 Å ( Fig . S7 ) . A program that defines Smotifs is available upon request from the authors . All protein structures that were identified as “new folds” from SCOP releases 1 . 73 and 1 . 75 and CASP 3–6 meetings were decomposed into Smotifs . In case of SCOP , each release identifies the new folds in comparison to the rest of the folds while in case of the CASP sets a Smotif library extracted from a backdated PDB was prepared for each CASP meeting . Within the pairs of datasets , Smotifs in SCOP new and existing folds and Smotifs from CASP new folds and the corresponding Smotif library from previously solved structures , were compared to evaluate the existence of identical Smotifs in the novel folds and the previously defined folds . The first comparison was based on the type of secondary structures and the geometry ( D , hoist , packing , and meridian ) of Smotifs . In a second , stricter comparison , the lengths of the flanking secondary elements ( SS1 and SS2 ) were also compared . If these lengths differed by more than 2 or 4 residues in the case of strands or helices , respectively , the Smotifs were considered different . To avoid redundancy when calculating the frequencies of Smotif occurrences for each four-dimensional geometric bin , only a single protein was selected from each protein fold ( as defined by SCOP database ) . Since fold families contain more than one protein structure and structures that belong to the same fold may have a variable number of Smotifs this selection process was repeated 100 times , randomly selecting a different protein in each analysis . Therefore , the frequency of occurrence of a given geometrical bin is the average of counts computed from 100 rounds of analysis for each family . Each of the proteins in the database was converted into a string of Smotifs . Thus , a protein having 5 regular secondary structures would be expressed as a string of 4 overlapping Smotifs . For each protein , a normalized probability score of observing such a string of Smotifs was calculated: ( 1 ) where N is the number of Smotifs and fr is the frequency of the Smotif i as calculated previously . Individual scores were converted into statistical Z-scores using the mean ( μ ) and standard deviation ( σ ) of the population of scores , as ( 2 ) ( 2 ) Internal contact ratio was calculated as the number of non-bonded atomic contacts ( i . e . H-bonds , polar contacts , hydrophobic contacts ) between SS1 and SS2 divided by Smotif size . Contacts were defined by the Contact of Structural Units ( CSU ) program [41] . CSU is based on the detailed analysis of interatomic contacts and interface complementarity . For every structural unit CSU calculates the solvent accessible surface of every atom and determines the contacting residues and type of interactions they undergo including all putative hydrogen bond contacts . Protein crystallizability was predicted with the XtalPred server [27] . XtalPred predicts protein crystallizibility by combining nine features: length , length of predicted disorder , Gravy index , insertion score , instability index , percent of coil structure , isoelectric point . Based on these features the protein is assigned to one of five crystallization classes: optimal , suboptimal , average , difficult and very difficult . Each class represents different crystallization success rate observed in TargetDB [42] . Three SCOP domain datasets were compiled for submission to XtalPred; domains from “new folds” as defined in ( 1 ) SCOP 1 . 75 and ( 2 ) in SCOP 1 . 73 , respectively , and ( 3 ) domains in SCOP 1 . 75 that were added since the release of SCOP 1 . 73 and that were not new folds . This ensures that we are focusing on proteins that were solved approximately in the same time but were classified differently in terms of novelty . The amino acid sequences of the domains were obtained from the ASTRAL website ( astral-scopdom-seqres-gd-all-1 . 75 . fa , astral-scopdom-seqres-gd-all-1 . 73 . fa ) . Sequence redundancy was removed among the domains using CDHIT clustering [43] at 95% sequence identity threshold . The SCOP 1 . 75 and 1 . 73 “new fold” domains dataset contained 170 and 177 representative sequences ( 517 and 558 redundant sequences ) , respectively , and the SCOP 1 . 75 “known fold” dataset contained 2802 representative sequences ( out of 13 , 043 redundant ones ) . Each amino acid sequence was submitted to XtalPred to calculate the crystallizability class . The corresponding PDB structure , chain identification and residue range was located for each Smotif ( 369 , 859 Smotifs in total ) . We calculated ACC values ( water exposed surface area or number of water molecules in contact with the residue ) using the DSSP program [44] . The average solvent accessibility of Smotifs was calculated by averaging the ACC values over all residues of the Smotif . We also calculated average ACC values by excluding loop residues , which are usually exposed , for each Smotif , but the conclusions were not affected . | Structural genomics efforts aim at exploring the repertoire of three-dimensional structures of protein molecules . While genome scale sequencing projects have already provided us with all the genes of many organisms , it is the three dimensional shape of gene encoded proteins that defines all the interactions among these components . Understanding the versatility and , ultimately , the role of all possible molecular shapes in the cell is a necessary step toward understanding how organisms function . In this work we explored the rules that identify certain shapes as novel compared to all already known structures . The findings of this work provide possible insights into the rules that can be used in future works to identify or design new molecular shapes or to relate folds with each other in a quantitative manner . | [
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] | 2010 | Structural Characteristics of Novel Protein Folds |
The soil-transmitted helminths ( STH ) , Ascaris lumbricoides , Trichuris trichiura and hookworms , infect 1 . 5 billion people worldwide and cause an estimated burden of 3 . 3 million disability-adjusted life years ( DALYs ) . Current control strategies focus on morbidity reduction through preventive chemotherapy ( PC ) but the most commonly used recommended drugs ( albendazole and mebendazole ) are particularly inefficacious against T . trichiura . This , together with the threat of emerging drug resistance , calls for new control strategies , including co-administration with other anthelminthics . Ivermectin plus albendazole is widely used against lymphatic filariasis , but its efficacy and safety against STH infections has not yet been fully understood . We conducted a systematic literature review and meta-analysis on the efficacy and safety of ivermectin-albendazole co-administration in five different databases ( i . e . PubMed , ISI Web of Science , ScienceDirect , CENTRAL and clinicaltrials . gov ) from 1960 to January 2018 . Four studies reporting efficacy of ivermectin-albendazole against STH infections and five studies on its safety met the selection criteria and were included for quantitative analysis . Ivermectin-albendazole was significantly associated with lower risk ( risk ratio ( RR ) = 0 . 44 , 95% confidence interval ( CI ) = 0 . 31–0 . 62 ) for T . trichiura infection after treatment compared to albendazole alone . The co-administration revealed no or only a marginal benefit on cure and egg reduction rates over albendazole alone for A . lumbricoides and hookworm infections . Adverse events ( AEs ) occurring after ivermectin-albendazole co-administration were mostly mild and transient . Overall , the number of individuals reporting any AE was not different ( RR = 1 . 09 , 95% CI = 0 . 87–1 . 36 ) in co-treated and albendazole-treated patients . However , although not statistically significant , sub-group analysis showed a tendency for slightly more AEs in patients with filariasis treated with ivermectin-albendazole compared to those treated with albendazole alone ( RR = 1 . 29 , 95% CI = 0 . 81–2 . 05 ) . Our findings suggest a good tolerability and higher efficacy of ivermectin-albendazole against T . trichiura compared to the current standard single-dose albendazole treatment , which supports the use of this co-administration in PC programs . Large-scale definitive randomized controlled trials are required to confirm our results .
Soil-transmitted helminths ( STHs ) collectively cause the most widespread neglected tropical disease ( NTD ) : nearly 1 . 5 billion people are infected with Ascaris lumbricoides , Trichuris trichiura , and/or hookworm ( i . e . Necator americanus and Ancylostoma duodenale ) in over 100 endemic countries [1 , 2] and 3 . 3 million disability-adjusted life years ( DALYs ) are related to symptomatic infection , wasting , mild abdominopelvic problems and anemia [1 , 3] . The World Health Organization ( WHO ) recommends large-scale , periodic distribution of safe and efficacious anthelminthic drugs as preventive chemotherapy ( PC ) to at-risk populations in endemic areas for morbidity control of STH infections [4 , 5] . PC allows a reduction of infection intensities from heavy or moderate to light , hence preventing morbidity , rather than curing infection and/or interrupting transmission [5] . The groups at highest risk of STH infection-related morbidity are children , who are in a critical phase of growth and development , and women of childbearing age , including pregnant women , who have increased nutritional requirements during pregnancy and lactation [6] . Currently , STH infections are treated predominantly with the two benzimidazole drugs albendazole ( 400 mg ) or mebendazole ( 500 mg ) [7] . A meta-analysis published in 2017 showed that both drugs are highly efficacious against A . lumbricoides ( cure rate ( CR ) = 96% with albendazole and CR = 96% with mebendazole ) , but less efficacious against hookworm ( CR = 80% with albendazole and CR = 33% with mebendazole ) , and even less against T . trichiura ( CR = 31% with albendazole and CR = 42% with mebendazole ) [8] . Thus , it is crucial to increase efforts to explore alternative therapies to both increase efficacy for trichuriasis and delay the emergence of potential drug resistance in view of the massive drug pressure exerted by widespread use and dependence of these two drugs . An additional anthelminthic drug , ivermectin , has been used widely in humans , either alone against onchocerciasis or in combination with albendazole against lymphatic filariasis ( LF ) since the late 1980s [7 , 9] . This drug has played a key role in the elimination programs of these two NTDs [4] . In 2015 alone , more than 50 million school-aged children received ivermectin in addition to albendazole within the global program to eliminate LF [10] . It is not clear , however , how the LF program translates into clearing and/or reducing the intensity of STH infections [11] . There is indirect evidence of reduced STH burden in areas where albendazole and ivermectin have been co-administered [12] . While ivermectin alone is considered to have suboptimal efficacy against hookworm and T . trichiura infections [13–17] there are data indicating that the co-administration of ivermectin and albendazole can be more efficacious than single-drug regimens [18–20] . The co-administration of ivermectin and albendazole was therefore recently added to the WHO Essential Medicines List for the treatment of STH infection [21] . We conducted , for the first time , a systematic review and meta-analysis of the efficacy and safety of the co-administration of albendazole plus ivermectin compared to albendazole alone for treating STH infections . Post-treatment reactions are often related to disease triggered by parasite death [22] and it is thus important to know whether the tolerability is comparable in STH and LF infections . Furthermore , we analyzed efficacy measures based on individual patient data from three recent randomized controlled trials ( RCTs ) . Our findings will help to inform improved treatment guidelines for STH infections .
The protocol of this systematic review , which is provided as a supplementary file ( S1 File ) , was recorded and published in the International Prospective Register of Systematic Reviews ( PROSPERO ) online database , number CRD42017060710 ( S2 File ) . The review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis ( PRISMA ) statement [23] . Reporting according to PRISMA guidelines are summarized in the checklist provided as a supplementary file ( S3 File ) . A literature search without language restriction was performed in PubMed , ISI Web of Science and Science Direct ( from 1960 to January 24 , 2018 ) to identify clinical trials pertaining to the use of ivermectin in combination with albendazole for treating hookworm , A . lumbricoides and T . trichiura . The search terms included: “ivermect* [AND] albendaz* [AND] ( hookworm [OR] trichuri* [OR] ascari* [OR] soil-transmitted helminth* ) [AND] ( cure* [OR] trial ) ” . Additionally , we performed a search using the keywords “ivermectin” and “albendazole” in the following databases and online repositories: Cochrane Central Register of Controlled Trials ( CENTRAL ) and ClinicalTrials . gov maintained by the National Library of Medicine ( NLM ) at the National Institutes of Health ( NIH ) . The search strategy is detailed in supplementary file ( S1 Text ) . Individual patient data on efficacy of ivermectin combined with albendazole against STH infections from three published trials [18 , 20 , 24] were obtained through personal communication and were subjected to further in-depth analysis . To identify safety data from the co-administration of ivermectin and albendazole , a literature search was performed using databases from PubMed , ISI Web of Science and Science Direct ( from 1960 to January 24 , 2018 ) applying the following search terms: “ivermect* [AND] alben* [AND] combin* [AND] ( adverse [OR] side effect* [OR] symptom* ) ” . No restrictions with regard to language , parasite species or study type were applied . Likewise to efficacy , we additionally searched the online databases and repositories of CENTRAL and ClinicalTrials . gov for documentations on safety using the keywords “ivermectin” and “albendazole” ( S1 Text ) . All retrieved references were screened by title and abstract for efficacy and safety information on ivermectin-albendazole co-administration in humans using the eligibility criteria detailed below . From the studies assessing efficacy , we selected RCTs , which tested the co-administration of ivermectin and albendazole against at least one STH ( hookworm , T . trichiura and/or A . lumbricoides ) . We included only studies which administered the standard doses of the drugs ( ivermectin: 200 μg/kg; albendazole: 400 mg ) as recommended by the Essential Medicine List [21] , and which assessed drug efficacy ( follow-up survey ) between 7 days and six weeks post-treatment . According to WHO , follow-up assessment of drug efficacy should take place between two and three weeks post-treatment because reinfection is common and long follow-up periods may prevent a clear distinction between poor efficacy and new infections [25] . However , to be more inclusive , we extended this period from 7 days to six weeks . The diagnostic method used in the studies was not part of the selection criteria . The main eligibility criterion for potentially relevant studies on safety was reporting of any quantitative or qualitative data of adverse events ( AEs ) following administration of ivermectin in combination with albendazole in any clinical trial . Sample size varied among studies but was not considered as an inclusion/exclusion criterion . Case studies from medical reports were not considered due to non-representativeness of outcomes . Data published in reviews were included if they had not been identified in our literature search already . Additional relevant studies on safety identified through reviews or online repositories and not yet covered through the literature search were subsequently included . Due to the non-standardized approach to reporting safety information , we expanded the search to include different doses and different time points of AE assessment and follow-up ( vs . efficacy for which there is a standardized approach recommended by WHO ) . The quality and risk of bias of eligible efficacy studies was assessed at study level using the Cochrane risk of bias tool [26] . The assessment was based on six items included in the bias assessment tool: random sequence generation , allocation concealment ( both define the selection bias ) , blinding of participants and personnel ( performance bias ) , blinding of outcome assessment ( detection bias ) , incomplete outcome data ( attrition bias ) and selective reporting ( reporting bias ) . Each study was rated , for each of the items , as “high risk” or “low risk” of bias based on the criteria for judging risk of bias . If the study did not report sufficient detail to consider “high risk” or “low risk” , the risk of bias was classified as “unclear risk” . For safety studies included in the meta-analysis the same Cochrane training tool for quality assessment was applied as detailed above . As there were fewer than 10 studies in each of the meta-analysis , the risk of bias across studies could not be assessed , as recommended by Sterne et al . ( 2011 ) [27] . All references fulfilling the eligibility criteria were subjected to data extraction in duplicate by two independent reviewers ( MSP and EH ) . For each study information on the publication ( i . e . , authors and year ) , general study-specific data such as type of study , country where the study took place , parasite species , participant data ( i . e . , age group , number of individuals ) , follow-up period and data collection method ( i . e . , repeated stool sampling for efficacy , passive vs . active surveillance for safety ) was retrieved . For studies assessing efficacy , the main outcomes were the number of treated and infected participants ( before and after treatment ) , CRs ( the percentage of individuals who became helminth egg negative following treatment ) and egg reduction rates ( ERRs ) ( when available ) . Number of AEs and specific reported symptoms ( if detailed ) , type of AEs ( i . e . , symptom , observable or lab event ) and whether AEs were associated with baseline parasite infection status were recorded for appraisal of safety data . If AE data were provided as number of participants with AEs and number of AEs , respectively , the earlier was preferred for data extraction .
Among the six potentially relevant studies identified , two [29 , 30] were excluded because they did not use the recommended doses of ivermectin and/or albendazole ( albendazole: 400 mg , ivermectin: 200 μg/kg ) ( Fig 1 , Table A in S2 Text ) . As a result , we selected a total of four studies , of which one compared the co-administration of ivermectin-albendazole to albendazole and ivermectin alone [18] , two compared the co-administration to albendazole alone [19 , 20] and one compared ivermectin-albendazole to other therapies which were not considered in this review ( Fig 1 ) [24] . The features and methodological quality of the selected studies are summarized in Fig 2 . The more recent trials [20 , 24] reported more methodological details on the study design and measures for mitigation of potential bias and thus reached higher quality levels than the older ones [18 , 19] . Table 1 provides a brief overview on the four selected RCTs and their characteristics . Note that not all studies evaluated the efficacy of the drugs against all STHs: Ismail et al . [19] only assessed the efficacy against T . trichiura and Belizario et al . [18] did not evaluate efficacy against hookworms . The treatment outcome in all four selected studies was assessed between 7 and 39 days post-treatment ( 2/4 studies at +/- 21 days ) . This assessment was done by examining one or two stool samples . Two studies collected one sample , one of these studies does not report on how many slides were performed from the stool sample [19] and the other performed duplicate Kato-Katz thick smears [18]; the other two studies collected two samples and performed duplicate Kato-Katz thick smears on each one [20 , 24] . Table 2 summarizes the efficacy outcomes of each single and the combined drug regimen investigated against the different STH species in all four studies . Outcome measures were CRs and ERRs–calculated using geometric means in all four studies . The first three studies in Table 2 show an improvement of the CR against T . trichiura when using the combination of ivermectin-albendazole vs . ivermectin or albendazole alone . A total of 665 records were identified using the described search strategy ( see S1 Text ) . These articles were screened for safety data on the co-administration of albendazole and ivermectin . In total , 32 studies were retained and full-text articles checked on eligibility criteria as defined above ( see Fig 1 ) . Details on study characteristics and reasons for inclusion or exclusion are provided as a supplementary file ( Table B in S2 Text ) . Six studies were excluded due to non-extractability of the data or missing relevant information ( n = 3 ) [18 , 31 , 32] , consecutive instead of co-administration of ivermectin and albendazole ( n = 2 ) [16 , 33] and one study additionally administered diethylcarbamazine ( DEC ) together with the ivermectin-albendazole combination ( n = 1 ) [34] . A total of 26 studies were included and considered for quantitative or qualitative appraisal in this review . Among these , 24 provided quantitative information on AEs ( Table 3 ) of which 22 detailed specific information on symptoms ( Table 4 ) . One review [35] served as a supplementary quantitative and qualitative information source to complement data from included original research articles . Another study provided description of AEs with regard to pregnancy outcome [36] . All studies with quantitative data that provided the actual number of AEs , the total number of treated individuals in the co-administered ivermectin-albendazole group and that had at least one single drug comparator ( albendazole or ivermectin ) group were selected for further analysis by means of meta-analysis ( n = 5 ) ( Table 3 ) . Studies with zero AEs in all groups [37 , 38] or less than five individuals per treatment arm [39] were not considered . The quality and types of potential biases of these five studies is summarized in Fig 7 . Two studies reached the highest quality grading [20 , 40] , while one did not clearly state about blinding of outcome assessors [41] and two studies followed an open-label or only partly blinded study design [30 , 42] , provided incomplete information on random allocation measures and thus reached lower grading . Among the included safety studies providing original quantitative information on treated subjects ( n = 24 ) , the number of monitored individuals after treatment administration varied considerably and mainly depended on study type and design ( Table 3 , Table B in S2 Text ) . Twenty one studies were clinical trials of which the majority ( n = 16 ) applied an active surveillance approach and more than half ( n = 12 ) were RCTs . Four studies reported safety parameters assessed either using an observational [46 , 48 , 57] or a trial design ( including comparison between matched groups ) [45] embedded in regional or national control programs applying mass drug administration ( MDA ) against LF . Thus , these four studies had much larger sample sizes . Within the trials , most studies involved participants with filariasis such as LF due to Wuchereria bancrofti ( n = 7 ) [41 , 43 , 49 , 50 , 54–56] or Brugia malayi ( n = 2 ) [39 , 53] , onchocerciasis due to Onchocerca volvulus ( n = 1 ) [40] , mansonellosis due to Mansonella perstans ( n = 2 ) [37 , 38] or co-infections of the above ( n = 3 ) [42 , 47 , 51] . Three studies assessed the safety of ivermectin-albendazole co-administration in patients infected with STHs [20 , 24 , 30] and one study in patients with schistosomiasis caused by Schistosoma haematobium and/or S . mansoni [45] . Two studies assessed the safety of co-administered ivermectin and albendazole in healthy subjects [44 , 52] . Trials were conducted in ten different countries whereas observational data after MDA campaigns was available for 5 countries . Of the 21 trials , eight were from East Africa ( Malawi , Tanzania and Uganda ) , seven from West Africa ( Ghana and Mali ) , five from South-East Asia ( India , Sri Lanka and Thailand ) , one from Latin America and the Caribbean ( Haiti ) and one from North America ( USA ) . Post-MDA-treatment safety reporting was available for West Africa ( Burkina Faso , Mali , Nigeria and Sierra Leone ) and East Africa ( Tanzania ) .
Our results suggest that the co-administration of ivermectin and albendazole increases efficacy against T . trichiura , but most likely has no gain against A . lumbricoides and hookworm . Safety reports were very diverse in study design , target population and treatment indication but in summary confirmed its tolerability with mostly mild and transient AEs . Together , these findings support the recent WHO recommendations and inclusion in the WHO Model List of Essential Medicines . At the same time , they also point to the need for additional and more reliable information through well-conducted studies in the different contexts where the co-administration is to be deployed . A safety-related shortcoming of the ivermectin-albendazole co-administration is that it cannot be deployed in areas where also Loa loa is prevalent , since ivermectin is known to produce severe and possibly fatal adverse reactions such as neurological signs , encephalopathy and coma in heavily infected individuals and is thus contraindicated in endemic West and Central Africa [9] . Alternative treatments with excellent trichuricidal activity are therefore required . Oxantel pamoate might fill this gap . The drug has been thoroughly studied over the past years and in combination with albendazole has shown a high broad spectrum activity against all STH [24 , 71–73] and hence might serve as an excellent alternative to albendazole-ivermectin . | Millions of people worldwide are infected with intestinal worms known as soil-transmitted helminths ( STHs ) . These include Ascaris lumbricoides , hookworm ( Ancylostoma duodenale and Necator americanus ) and Trichuris trichiura . Globally , the current main strategy to control these parasites is the periodical distribution of treatment to populations which are at particular risk of infection . However , the two drugs exclusively used in these mass treatment campaigns ( albendazole and mebendazole ) do not perform well against some of the STH species . Adding another drug , such as ivermectin , to albendazole holds promise for improved performance . This combination is already being widely used for the treatment of lymphatic filariasis . However , policy makers need evidence that this co-administration is efficacious and safe when taken together for STH infections . To fill this knowledge gap , we systematically reviewed the scientific literature for studies on the efficacy and safety of the co-administration of ivermectin and albendazole . We identified four studies reporting on the efficacy of the co-treated and five studies assessing their tolerability . Our results suggest that the co-administration performs significantly better than albendazole alone against T . trichiura–the STH species which is most difficult to treat–and is generally well-tolerated . Yet , we conclude that definitive evidence to support the use of ivermectin together with albendazole for STH will require more high-quality studies . | [
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"neglect... | 2018 | Efficacy and safety of co-administered ivermectin plus albendazole for treating soil-transmitted helminths: A systematic review, meta-analysis and individual patient data analysis |
Rat somatosensory cortex contains a large sexually monomorphic genital representation . Genital cortex undergoes an unusual 2-fold expansion during puberty . Here , we investigate genital cortex development and female rat sexual maturation . Ovariectomies and estradiol injections suggested sex hormones cause the pubertal genital cortex expansion but not its maintenance at adult size . Genital cortex expanded by thalamic afferents invading surrounding dysgranular cortex . Genital touch was a dominant factor driving female sexual maturation . Raising female rats in contact with adult males promoted genital cortex expansion , whereas contact to adult females or nontactile ( audio-visual-olfactory ) male cues did not . Genital touch imposed by human experimenters powerfully advanced female genital cortex development and sexual maturation . Long-term blocking of genital cortex by tetrodotoxin in pubescent females housed with males prevented genital cortex expansion and decelerated vaginal opening . Sex hormones , sexual experience , and neural activity shape genital cortex , which contributes to the puberty promoting effects of sexual touch .
Early analysis of the development of visual cortex by Hubel and Wiesel focused on binocular interactions and showed that both anatomy and physiology of ocular dominance is plastic and shaped in a visually-driven , activity-dependent process [1] . In a similar vein , the development of circuits in the somatosensory cortex ( S1 ) was studied . It was recognized early on that precise topographic ( barrel ) representation of the whisker pattern in cortical input layer 4 [2] is imposed by peripheral inputs and has an early and brief critical period , after which it can no longer be changed [3] . Subsequent work identified neurogenetic mechanisms of cortical pattern formation [4] . With few exceptions , [5] most of the work provided little evidence for neural activity dependent processes in the development of S1 . From work on the barrel cortex a consensus emerged that cortical input layer 4 has an earlier critical period and shows less plasticity than other cortical layers [6] . In the light of aforementioned results , the recently described developmental pattern of cortical input layer 4 of genital S1 was very surprising . Specifically , layer 4 of rat genital cortex showed a major expansion during puberty [7] . We wondered if this very late development of genital cortex has implications for the role of activity in cortical development and might even allow early sexual experience to impact on cortical development . We were also interested in the relationship between somatosensory genital cortex development and female sexual maturation . In rodents , puberty has been intensely studied and much is known about changes in subcortical structures , such as the hypothalamus , that are associated with puberty [8]; there is , however , virtually no information available about changes in cortical circuits during puberty . A host of studies in a wide variety of species came to the conclusion that sexual maturation is not a purely age-dependent process but is also under social control . In mice , studies on female sexual development showed puberty advancing effects of male ( primer ) pheromones [9] and puberty delaying effects of adult female pheromones [10] . Most of the research on the social control of puberty has focused on pheromones [10] and identified the vomeronasal organ as key mediator of such effects in mice [11] . There is also evidence , however , that tactile interactions and sexual touch can powerfully influence sexual development . For example , the extreme reproductive suppression in the eusocial mole rat appears to be mediated by tactile rather than olfactory cues [12] . In a landmark study on mice , Bronson and Maruniak [13] showed that the puberty advancing effects of male pheromones alone are small . Bronson and Maruniak [13] suggested that the advance in female puberty caused by adult males results from a synergistic interaction of pheromones and tactile stimulation; Bronson and Maruniak [13] also ruled out a role of visual and auditory cues . The underlying neural mechanisms and pathways mediating male touch induced advance of female puberty are still unknown . In primates , the evidence for pheromonal effects on puberty is rather mixed [14] . Sexual touch , on the other hand , is strictly regulated in most human cultures and this is particularly true during development . It has also become painfully clear that sexual abuse and inappropriate sexual contact during development have long-lasting detrimental consequences [15 , 16] . Presumably the long-lasting problems from inappropriate sexual contact during development reflect brain changes resulting from sexual experience . Remarkably , structural brain imaging in humans with a history of sexual abuse identified a thinning of putative human genital cortex , as a cortical consequence of childhood sexual abuse [17] . Here we ask the following questions: ( 1 ) Are sex hormones required for the pubertal expansion of female genital cortex ? ( 2 ) What are the structural events underlying genital map changes ? ( 3 ) Does sexual experience affect the development of female genital cortex ? ( 4 ) Does activity in female genital cortex affect female puberty and does it mediate the female puberty advancing effects of male sexual touch ?
As a first step in our analysis we performed additional experiments to confirm our recently reported data on the growth of genital cortex during puberty [7] . To this end we analyzed the layer 4 cortical input maps in the S1 of 6 young ( approximate postnatal day [P] 21 ) and 7 old ( approximately P42 ) female rats . Specifically , we performed cytochrome oxidase staining , which reveals granular layer 4 regions ( S1A–S1D Fig ) . We confirmed our earlier conclusions: whereas the clitoris representation in young prepubescent animals was rather small ( Fig 1A ) , it appears to be twice as big in adult animals ( P42 , Fig 1B and 1E; P < 0 . 01 , Student t test ) . In contrast , the size of the entire S1 did not differ significantly between young and old females ( Fig 1G; P = 0 . 3 , Student t test ) . Next , we examined whether sex hormones play a role during the pubertal expansion of genital cortex . Hence , we ovariectomized females before ( at P21 ) and after puberty ( at P42 ) . Twenty days after the ovariectomy animals were killed , brains were removed and tangential sections through the S1 were prepared and stained for cytochrome oxidase activity ( S1C and S1D Fig ) . We obtained detailed anatomical maps of layer 4 from 7 prepubertal ( Fig 1C ) and 6 postpubertal ( Fig 1D ) ovariectomized females . Fig 1C shows a drawing of a complete S1 ( thick outline ) body map of a female aged P42 , in which we removed the ovaries before puberty ( at P21 ) . The size of the cortical clitoris representation is small and comparable to the one of the young female , as depicted in Fig 1A . The somatosensory cortical map obtained from a female rat ovariectomized after puberty at P42 ( Fig 1D ) allows 2 observations: ( 1 ) the clitoris representation is much larger than the one of the female rat ovariectomized before puberty; ( 2 ) the size of the genital cortex is comparable to the genital cortex size of an adult female ( Fig 1B ) . The population data ( Fig 1E ) suggest the same conclusions . The clitoris representation in females ovariectomized before puberty ( mean genital cortex of S1 1 . 07% ± 0 . 09 ) was comparable to young females ( 1 . 07% ± 0 . 06 ) but significantly ( P < 0 . 01 , Student t test ) smaller than the genital cortex size in animals , which were ovariectomized after puberty ( 1 . 6% ± 0 . 15; Fig 1F ) . Comparison of the genital cortex to the posteromedial barrel subfield ( PMBSF ) , instead of the whole S1 , led to the same results ( S2A–S2C Fig ) with no difference in the variability ( S1 Table ) . We conclude that sex hormones are required for the pubertal expansion of female genital cortex but not for the maintenance of an adult size female genital cortex . A strong impact of sex hormones on the onset of puberty has been reported using systemic estradiol injections during prepuberty [18] . We wondered to what extent systemic estrogen treatment can accelerate genital cortex growth . Female rats enter puberty typically at the age of P34 to P38 [19] . On that account and based on the study by Ramirez and Sawyer [18] , we chose to treat females aged P26 for 5 days with estrogen and to test a possible effect on genital cortex at P30 . Prepubescent females ( P26 ) were injected over 5 days with either in sesame oil dissolved estradiol ( Fig 2A , upper panel; n = 7 animals; 0 . 05μg estradiol , dissolved in 0 . 4 ml of sesame oil , per 100 g body weight ) or with sesame oil alone ( Fig 2B , upper panel; n = 7 animals; 0 . 4 ml of sesame oil , per 100 g body weight ) . During the fifth day of treatment animals were killed and cortical hemispheres were flattened , tangentially sectioned and processed for cytochrome oxidase activity ( S3A and S3B Fig ) . In order to obtain cortical body maps , granular somatosensory regions were reconstructed through serial sections . To exclude experimenter biases cortical maps were drawn and analyzed by an experimenter blind to the condition estradiol versus oil treated animals . The lower panel in Fig 2A shows a cortical map obtained from an oil-treated female . A cortical map obtained from a female , which was injected with estradiol , is shown in the lower panel of Fig 2B . The size of the clitoris representation is much larger in the estrogen treated female . Population data for all hemispheres confirm this result . The absolute area of genital cortex ( Fig 2C; mean absolute area in oil injected animals was 0 . 33mm2 ± 0 . 025 and in estradiol injected animals 0 . 5mm2 ± 0 . 028; P < 0 . 001 , Student t test ) and the mean percentage of genital cortex of S1 ( Fig 2D; mean genital cortex of S1 in estradiol treated animals was 1 . 6% ± 0 . 09 and in sesame oil injected animals 1 . 01% ± 0 . 06; P < 0 . 0001 , Student t test ) was significantly greater in estradiol injected animals compared with control animals ( oil treated ) . The size of S1 was not different ( Fig 2E; mean area of S1 in oil treated animals was 32 . 9mm2 ± 0 . 76 and in estradiol treated animals 31 . 2mm2 ± 0 . 68; P = 0 . 1 , Student t test ) . We also assessed parameters indicative of sexual maturation and the onset of puberty . Thus , we evaluated vaginal opening ( an open vagina is typically seen in females , which have entered puberty , [18] ) and the weight of the uterus , which is heavier in females after puberty [18] . Accordingly , we documented vaginal opening before , during and after the daily injections . In Fig 2F , 2 photographs show the clitoris and vagina of an oil treated female before the beginning of daily injections ( P25 , upper panel ) and afterwards ( P30 , lower panel ) . Vagina and clitoris for an estrogen treated animal are shown in Fig 2G , respectively . Whereas the vagina of the oil treated female was still closed at P30 , the estradiol injected animal shows an open vagina at this stage ( Fig 2G , lower panel ) , indicating that the onset of puberty took place . To quantify vaginal opening , we gave the following scores for every vaginal opening stage ( Fig 2H ) : a score of 0 points to a closed vagina , whereas a score of 1 indicates an open vagina . A score of 0 . 5 represents the intermediate state , during which the vagina was about to open . The majority of oil treated females ( 6 out of 7 ) showed a closed vagina at P30 , whereas most of the estrogen injected animals displayed an open vagina ( 6 out of 7; P < 0 . 001 , Mann–Whitney U test ) . We also removed and weighed the uteri . On average , the oil-treated animals had lighter uteri ( 0 . 15g ± 0 . 07 , Fig 2I ) compared to animals , which received daily estradiol injections ( 0 . 29g ± 0 . 08 ) , but this difference did not reach significance ( P = 0 . 08 , Student t test ) . Taken together these data suggest that systemic estradiol accelerates genital cortex growth and advances the onset of puberty . Which cellular changes underlie the unusual genital cortex expansion during puberty ? To answer this question , we first stained alternating tangential sections of flattened cortices for cytochrome oxidase activity ( S4A Fig ) and with vesicular glutamate transporter 2 ( VGluT2 ) antibodies ( S4B Fig ) . While cytochrome oxidase reports constitutive layer 4 metabolic activity , VGluT2 is expressed in thalamocortical terminals [20] and , hence , labels thalamic afferents . S4A Fig ( upper panel ) shows a tangential section through S1 of a young animal ( P14 ) stained for cytochrome oxidase activity and in S4B Fig ( upper panel ) the subsequent section is shown labeled for VGluT2 . The labeled structures have the same layout and size , as confirmed by quantitatively analyzed drawings ( S4A and S4B Fig , lower panels ) . In old animals , alternating staining for cytochrome oxidase activity and with VGluT2 also led to completely overlapping results . We conclude from these observations that pubertal genital cortex growth leads to an expansion of the cortical area innervated by thalamic afferents . Next , we asked , how the genital cortex is able to increase its thalamically innervated area so drastically . Does the genital cortex expand like a balloon , pushing the neighboring cortex aside ? Alternatively , do genital afferents invade neighboring territories ? To address this issue , we analyzed S1 maps from young and old animals in more detail ( Fig 1A and 1B ) . Specifically , we measured the space between fore- and hindpaw , as shown in Fig 3A and 3B , and named it interlimb cortex . The interlimb cortex ( grey zone ) is dysgranular in structure ( i . e . , does not have a distinct layer 4 ) and is larger in the map of a young animal ( P25; Fig 3A , upper panel ) than in the one of an old animal ( P48; Fig 3B , upper panel ) . This size decrease is very surprising , as S1 grows overall by approximately 15% during puberty ( note that this growth in S1 did not reach significance between young and old females; Fig 1 ) . Cytochrome oxidase stained sections ( Fig 3A and 3B , lower panels ) confirm this result . Whereas the absolute genital cortex area almost doubles in size from P21 to P42 ( Fig 3C ) , the absolute interlimb cortex area slightly decreases ( Fig 3D; mean interlimb cortex area in S1 maps of young animals was 0 . 64mm2 ± 0 . 06 and in old animals 0 . 56mm2 ± 0 . 1 ) . Interestingly , the ratio of the genital cortex to the interlimb cortex significantly increases during puberty ( Fig 3E; mean ratio of genital cortex to the interlimb area in young animals was 0 . 35 ± 0 . 035 and in old animals 0 . 51 ± 0 . 017; P < 0 . 001 , Student t test ) . The simultaneous increase of genital cortex and decrease of interlimb cortex suggest that the pubertal genital cortex growth reflects an invasion of dysgranular interlimb cortex by putative genital thalamic afferents . Although sex hormones have been identified as important players during the onset of puberty , there is also evidence that somatosensory stimuli ( olfactory or tactile ) can influence sexual development . Thus , we assessed if sexual experience affects the development of female genital cortex . To this end , we chose the following experimental paradigm , which is inspired by the seminal work of Bronson and Maruniak [13] . Prepubescent females ( P21 ) were cohoused for 9 days with ( 1 ) sexually experienced females ( Fig 4A , upper panel ) , or with ( 2 ) sexually experienced males ( Fig 4A , middle panel ) , or with ( 3 ) sexually experienced males separated by a wire mesh ( Fig 4A , lower panel ) . In the first 2 groups , the animals had direct contact to interaction partners . In the third group , animals were cohoused but had no tactile access to them because of a wire mesh dividing the cage ( Fig 4A , lower panel ) . Importantly , bedding was swapped between the 2 cage compartments daily , such that females received full exposure to pheromonal cues . Females were also able to see and hear the adult male . At the age of P30 animals were killed . Brains were removed and tangential sections through layer 4 of S1 were prepared and stained for cytochrome oxidase activity . The experimenter reconstructing and analyzing cortical maps was again blind to the experimental condition . In Fig 4B somatosensory cortical maps are shown for all 3 experimental conditions ( upper panel: map obtained from a female cohoused with a female; middle panel: map from a female cohoused with a male; lower panel: map from a female , which sat together with a male , but with a wire-mesh separating the animals ) . Note that the cortical clitoris representation is the largest in the map of the female cohoused together with a sexually experienced male . In fact , the cortical clitoris representation ( Fig 4C ) and the fraction of clitoris of the entire S1 ( Fig 4D ) increased significantly more , when prepubescent females received male tactile cues ( filled blue circles , mean genital cortex of S1 1 . 9% ± 0 . 1 ) compared to female tactile cues ( filled red circles , mean genital cortex of S1 1 . 36% ± 0 . 1 ) . Interestingly , pheromones and audio-visual contact alone were insufficient to drive genital cortex growth ( open blue circle , mean genital cortex of S1 1 . 3% ± 0 . 1 ) . A 1-way ANOVA also reported a significant difference between prepubescent females cohoused with either males , females , or males without having tactile contact ( P = 0 . 01 ) . The overall size of S1 ( Fig 4E ) did not differ between groups ( P = 0 . 67 , 1-way ANOVA ) . Note that the relative size of genital cortex of the young females , which were cohoused with sexually experienced males ( mean genital cortex of S1 1 . 9% ± 0 . 1 , Fig 4D filled blue circles ) , is similar to that of the adult females ( mean genital cortex of S1 1 . 8% ± 0 . 1 , Fig 1B ) , even though we killed these animals at P30 , which would correspond to midpuberty group raised animals . These findings suggest , that male sexual touch strongly advances female genital cortex growth . We were surprised to observe such big effects following cohousing with sexually experienced males , while male olfactory cues had no impact on genital cortex development . These observations made us wonder about the relative contributions of tactile and other cues on female sexual maturation and genital cortex development . What are the contact cues that drive genital cortex expansion and promote female sexual maturation ? It has previously been shown , that gentle touch of female genitals creates conditioned place preference in female rats [21] and increases 50kHz range trill calls emitted by hormonally primed females [22] . Similarly , we set up an experiment , where prepubescent female rats ( P23 ) were exposed to artificial genital touch ( Fig 5 ) . During a 10-minute session , animals were freely moving in a small U-shaped environment , while the female experimenter repeatedly touched the animals’ clitoris and vulva with a lubricated brush ( artificial genital touch , Fig 5B ) . Control animals were placed in the same environment for 10 minutes without genital touch ( Fig 5A ) . For 7 days , each animal completed 3 sessions distributed across the day . Animals were killed at P30 and S1 maps were reconstructed with the experimenter being blind to the condition . Control animals ( Fig 5C ) had a smaller genital cortex than animals , which received artificial genital touch ( Fig 5D ) . Such differences in absolute ( Fig 5E ) and relative size of genital cortex ( Fig 5F ) were significant . The effect size was comparable to the differences observed between male and female touch in Fig 4; the size of the entire S1 was not different ( Fig 5G ) . Artificial genital touch also affected female sexual maturation . While there was no significant change in vaginal opening ( Fig 5J ) , the uteri were significantly heavier following artificial genital touch , as compared with control rats ( Fig 5H and 5I ) . In order to better understand the role of female genital cortex during puberty , we blocked genital cortex activity over a certain time during prepuberty ( P23–P30 ) . To do so , P21 animals received Elvax implants over the area of genital cortex . Elvax sheets were developed for the slow , gradual release of drugs [23] . Elvax sheets were either soaked with tetrodotoxin ( TTX ) ( Fig 6B ) , which blocks voltage dependent sodium channels , or impregnated with Ringer , as a control condition ( Fig 6A ) . After recovery , the implanted females were cohoused with sexually experienced males until the age of P30 . S1 maps of the brains were obtained as described above . The experimenter reconstructing cortical maps was again blind to the experimental condition . A map from a control animal treated with ringer is shown in Fig 6C , while Fig 6D shows a cortical map obtained from a TTX treated female . In animals , in which genital cortex was blocked with TTX , the area of clitoris representation ( Fig 6E; mean area in maps of control animals was 0 . 48mm2 ± 0 . 02 and in S1 of TTX treated animals 0 . 32mm2 ± 0 . 013; P < 0 . 0001 , Student t test ) and the relative size ( Fig 6F ) was smaller than in control animals . The area of S1 did not show any differences ( Fig 6G; mean area of S1 in Ringer treated animals was 32 . 4mm2 ± 1 . 4 and in TTX implanted animals 33 . 1mm2 ± 1 . 1; P = 0 . 7 , Student t test ) . The difference between hemispheres from control ( mean genital cortex of S1 was 1 . 49% ± 0 . 05 ) and TTX treated animals ( mean genital cortex of S1 was 1 . 02% ± 0 . 05 ) was marked ( P < 0 . 0001 , Student t test ) . These results immediately suggest 2 conclusions . First , the fact that there was a difference between control and TTX treated animals indicates that our TTX treatment was effective . Second , the data indicate that the pubertal expansion of genital cortex requires cortical activity . Next , we wondered if an intact genital cortex is required for female sexual maturation . Therefore , we determined the status of puberty in control and TTX treated animals . Accordingly , pictures of vagina and clitoris were taken before implantation and after the behavioral experiment . Five out of 13 animals , which received a ringer soaked Elvax sheet above genital cortex , showed an open vagina at the end of the experiment . The vagina before ( left panel ) and after the experiment ( right panel ) for one of those females is shown in Fig 6H . In contrast , only 1 of the animals ( n = 11 ) , whose genital cortices were blocked with TTX , had an open vagina . Fig 6I shows the pictures of 1 TTX animal before ( left panel ) and after ( right panel ) the treatment . The scores of vaginal opening are plotted in Fig 6J . The vaginas were closed in 9 out of 11 animals treated with TTX , and we observed a vagina that was about to open in only 1 TTX treated animal . In contrast , only 2 out of 13 animals in the Ringer group had the vagina still closed at the end of the experiment . The uterine weights ( Fig 6K ) were not significantly different , however . Thus , genital cortex activity might relay effects of male sexual touch on vaginal opening in rat female puberty . In order to obtain insight in the relationship between female sexual maturation and genital cortex development , we plotted genital cortex size against uterine weight in all experiments , in which we collected such data ( S5 Fig ) . As shown in S5A Fig , there was no tight relationship between relative genital cortex size and uterine weight . Nonetheless , it was obvious that a large uterine weight ( ≥0 . 15 g ) is rarely associated with a small ( ≤1% ) relative genital cortex size . If one compared genital cortex size and uterine weight across specific experimental conditions ( S5B Fig ) , it was noticeable that animals with TTX treatment of genital cortex ( the experiment described in Fig 6 ) never had very large genital cortices , even for cases with a large uterus .
Our data confirm a major pubertal expansion of female genital cortex , which—unlike the maintenance of large genital cortex in adults—requires intact ovaries and sex hormones . The larger area of genital cortex in adults reflects an invasion of adjacent territories by thalamic afferents . Such changes in female genital cortex are advanced by sexual touch and require cortical activity . Most interestingly , blockade of genital cortex delays female sexual maturation , suggesting that genital cortex is the neural structure that mediates the puberty advancing effects of male sexual touch . The expansion of layer 4 of genital cortex in puberty [7] is an unusual pattern in the development of layer 4 in S1 . In contrast , the barrel representation is characterized by a brief directly postnatal critical period , after which the barrel pattern can no longer be changed [3] . Our data show that intact ovaries and , hence , presumably the sex hormones emitted by the ovaries are required for the pubertal expansion of genital cortex . The interpretation that sex hormones drive pubertal expansion is greatly strengthened by observations following the injection of estradiol , which mimics the pubertal expansion of genital cortex . The mechanisms , by which sex hormones , and in particular estrogens , drive pubertal expansion of genital cortex , are yet to be determined; both , a direct sex hormone effect on genital cortex and an indirect effect via growth stimulation of sex organs ( i . e . , the clitoris ) by sex hormones are conceivable . Thus , it is possible that cortical changes follow similar mechanism , as described for the hippocampus , in which a rapid potentiation of excitatory synapses is achieved by estrogen [24] with different underlying mechanism in male and female rats [25] . From human studies , it is known that the hippocampus changes in size along the reproductive cycle with the biggest hippocampus being present when blood estrogen levels are highest [26] . The data discussed below indicate that at least some stage of cortical activity seems to be required for genital cortex expansion . The visualization of thalamic afferents by VGluT2 antibodies showed that cytochrome oxidase staining reveals maps completely congruent with thalamic innervation . Thus , the size increase of genital cortex in adults indicates that a larger cortical area is innervated by thalamic afferents . The detailed analysis of body maps in young and adult animals is strongly suggestive that the size increase of genital cortex results from an invasion scenario , in which putative genital afferents innervate neighboring dysgranular cortex . Female genital cortex development is strongly affected by tactile sexual experience . Housing pubescent females with a sexually experienced adult male strongly advances the growth of genital cortex . Even though we killed such females at P30 ( which corresponds in group-housed animals to midpuberty ) , they had genital cortices larger than average adult size ( compare Figs 2D and 4D ) . This advancement of puberty was induced specifically by direct male contact and was not seen in animals cohoused but not touched by males , or in animals cohoused with females . In line with the idea that genital cortex is altered by sexual experience , we find that blockade of genital cortex prevents the pubertal layer 4 expansion of genital cortex . The requirement of experience and cortical activity for the appropriate development of adult somatotopy is similar to the requirement of cortical activity for the development of ocular dominance columns in the visual system [27] . It is notably different , however , from the development of the early postnatal development of the barrel pattern in S1 , which occurs despite manipulation of peripheral [28] or cortical inputs [29] . Thus , genital cortex does seem to differ from barrel cortex not only in the timing of the critical period , but also the cellular mechanisms mediating genital cortex plasticity seem to differ from barrel cortex . Whereas our blocking experiments show that genital cortex activity is crucial for the pubertal layer 4 expansion , it is questionable to what extent this plasticity is functionally meaningful . Decorticated animals are still able to mount and reproduce . However , subtle changes in the pattern of reproduction [30 , 31] are observed . Furthermore , somatosensory feedback from the penis was shown to be critical for the achievement of intromission , and somatosensory feedback from the preputial region is needed for the execution of copulatory thrusting [32] . Blocking genital cortex activity during the critical period of puberty may cause changes in the pattern of reproduction during adulthood , i . e . , that the number of intromissions and time to ejaculation might be affected ( in males ) ; lordosis or place preference behavior could be affected in females . As shown many decades ago , the social signals powerfully control the advance of puberty [33] . While it became clear that pheromonal stimuli mediated by the vomeronasal organ [11] contribute to the male induced advance in female puberty in mice , the hastening effects of puberty induced by male pheromones alone are minor . Bronson and Maruniak [13] suggested that tactile male cues synergistically with pheromones advance female puberty . Further work showed that androgenized female mice [34] , but not castrated male mice [13] , provide the tactile female puberty promoting cues . Our artificial genital touch experiment showed a major effect of genital touch on female sexual maturation . The effects of artificial genital touch on uterine weight ( Fig 5I ) were even larger than the male effects seen in some of our control experiments ( Fig 6K ) . Thus , our data point to genital touch as a dominant cue for inducing puberty and question the idea that a sensory synergism is required [13] . Our data show that an intact female genital cortex promotes vaginal opening . Thus , the data suggest that genital cortex might be a tactile gateway through which sexual touch promotes female puberty . This question requires further investigation , however , as we did not observe an effect of genital cortex blockade on uterine weight , as described previously in rats [33] . The receptive field properties of genital cortex appear to be tuned to sexual tactile contacts associated with mating [7] and , hence , seem well-suited to relay signals arising from sexual touch . The ensemble of our systemic female hormone application effects on genital cortex growth and our puberty advancing effects established by genital touch leads to speculation about a possible bidirectional connection between genital cortex and the medial preoptic nucleus of the hypothalamus . This region contains gonadotropin releasing hormone ( GnRH ) neurons whose activity produces high frequency of GnRH release which , in turn , causes gametogenesis and an increase in gonadal steroid hormone secretion [35] .
All experimental procedures were performed according to German guidelines on animal welfare under the supervision of local ethics committees ( animal permit numbers: G0193/14 and G0244/16 ) . All experiments were conducted on Wistar rats purchased from Janvier Labs . All animals were kept on a 12 hour to 12 hour , normal light/dark cycle with lights off at 10:00 pm . Rats had ad libitum access to food and water . Ovariectomies were performed in prepubescent ( P21 ) and adult Wistar rats ( P42 ) . For the surgery , animals were anesthetized by injection of an initial dose of 100 mg/kg ketamine and 7 . 5 mg/kg xylazine . Respiration , blink , and pinch reflex were observed throughout the surgery and , if needed , animals were injected with an extra shot ( 25% ) of ketamine/xylazine mixture ( Sigma-Aldrich , St . Louis , MO ) or a 25% dose of ketamine ( Sigma-Aldrich ) alone . Monitoring of temperature was done using a rectal probe and could be maintained with a heating pad ( Stoelting , Wood Dale , IL ) to 34°C–36°C . To remove ovaries a small incision was made bilaterally on the animal’s bag . The white fat pad , to which the ovaries are attached to , was pulled out through the body wall . Ovaries were grabbed with forceps and removed from the fallopian tube using small scissors . After successful removal , the white fat pad with fallopian tube was put back through the body wall . The incision was sutured using a self-resorbing thread . The wound was disinfected and looked after in the days following surgery . Immature Wistar rats ( P26 ) were divided randomly into groups of 3–4 animals . All animals were weighed daily and the vagina opening was assessed by visual inspection and defined as a complete separation of the membranous sheath covering the vaginal orifice [36] . Photos of clitoris and vagina were taken before the first injection and after the experiment . The assessment of vaginal opening was not blind but the different stages were very clear to detect . Animals in the testing group were injected subcutaneously every morning with 0 . 05 μg 17β-estradiol ( Sigma-Aldrich ) , dissolved in 0 . 4 ml of sesame oil ( Sigma-Aldrich ) , per 100 g body weight . Rats in the control group received the same amount of sesame oil . On day 5 of the treatment , animals were deeply anaesthetized , perfused , and their brains processed , as described below . In addition , uteri of every animal in experiment was taken out while perfusion and weighed . Wistar rats aged P21 were divided into 3 groups . Each animal of group 1 was housed for 9 days together with a sexually experienced adult female rat ( approximately P60 ) . Every rat of group 2 was put for 9 days together with a sexually experienced adult male rat ( approximately P60 ) . Group 3 rats were also housed together with a sexually experienced adult male rat ( approximately P60 ) , but the cages were separated by a wire-mesh . Whereas the animals of group 1 and 2 were able to interact fully with their housing partner , the rats in group 3 could not touch the male they were housed together with . However , they were able to smell , see , and hear the male through the wire-mesh . Vaginal opening was documented as described above , and pictures of clitoris and vagina were taken before and after the experiment . After 9 days , at the age of P30 , animals of all groups were anaesthetized , perfused , and their brains histologically processed as described below . Uteri of all animals were taken out while perfusion and weighed . Prepubescent female Wistar rats ( P23 ) were divided into 2 groups . Control animals were placed 3 times for 10 minutes in a small U-shaped arena over 7 days without further treatment and were then returned to their home cage . Animals in the artificial genital touch group were placed 3 times for 10 minutes in a small arena over 7 days , and their clitoris and vulva were contacted with a lubricated brush by a human ( female ) experimenter ( similar to Parada , 2010 , [21] ) . After 7 days ( at the age of P30 ) , animals of all groups were anaesthetized , perfused , and their brains histologically processed , as described below . Uteri of all animals were taken out while perfusing and weighed . Animals ( P21 ) were divided into 2 groups . The control group received a chronic Ringer-impregnated Elvax sheet above genital cortex and the rats in the testing group were implanted with a TTX-impregnated Elvax sheet above genital cortex . Elvax implants were prepared as described before [29 , 37 , 38] . Briefly Elvax 40p ( ethylene-vinyl acetate copolymer; DuPont , Wilmington , DE ) was washed for one week in 95% of Ethanol and afterwards dissolved in methylene chloride to obtain a 10% solution . TTX ( Abcam , Cambridge , UK ) or Ringer ( control ) was then added in order to achieve a final concentration of 2% . The TTX or Ringer containing Elvax mixture was poured into a glass mold and quickly frozen for 1 hour at −80°C . After 30 minutes , the blocks were removed from the mold and put for another 3 days into the −80°C freezer . On day 3 , the Elvax TTX or control blocks were transferred to the −20°C and stored for another 3–4 days . Subsequently , the TTX and Ringer impregnated blocks were cut on a vibratome ( Leica , Wetzlar , Germany ) into 150 μm sheets , which were cut into 2 mm squares using a scalpel . Before surgical implantation all Elvax sheets were washed for at least 8 hours in distilled water . For surgical implantation P21 Wistar rats were anesthetized by injection of an initial dose of 100 mg/kg ketamine and 7 . 5 mg/kg xylazine . Respiration , blink , and pinch reflex were observed throughout the surgery and , if needed , animals were injected with an extra shot ( 25% ) of ketamine/xylazine mixture or a 25% dose of ketamine alone . Monitoring of temperature was done using a rectal probe and could be maintained with a heating pad to 34°C–36°C . Lidocaine was locally injected in the scalp , which was then removed . A craniotomy was performed above genital cortex , and the dura was removed using a bend syringe . The TTX or Ringer impregnated sheets were placed on the brain surface and covered with silicone ( Kwik-Cast; World Precision Instruments , Sarasota , FL ) . The exposed skull was finally covered with dental cement . Animals were allowed to recover from surgery for 2 days . Photos of clitoris and vagina were taken before the behavioral experiment . At the age of P23 , implanted animals were put together with a sexually experienced male . After 7 days ( at the age of P30 ) , TTX and control animals were anaesthetized and their vaginal opening was documented as described above . Along with the perfusion , the uteri of the animals were cut out and weighed . Brains were histologically processed as described below . At the end of the above-described experiments , animals were anaesthetized using a 20% urethane solution and perfused with phosphate buffer followed by a 2% paraformaldehyde solution ( PFA ) . Brains were removed , hemispheres were separated , and cortices were flattened between 2 glass slides separated by clay spacers [39] . Glass slides were weighed down with small ceramic weights for approximately 3 hours . Afterwards , flattened cortices were stored overnight in 2% PFA and 80 μm sections were cut on a Vibratome ( Leica ) . Sections were stained for cytochrome-oxidase activity using the protocol of Divac et al . [40] . After the staining procedure , sections were mounted on gelatin coated glass slides with Mowiol mounting medium . Subsequently , pictures were taken on an Olympus BX51 microscope and layer 4 areas of S1 were drawn by using a Neurolucida software . S1 maps were reconstructed through serial sections . To exclude experimenter biases , cortical maps were drawn and analyzed by an experimenter blind to the conditions ( e . g . , estradiol versus sesame oil control group; TTX versus Ringer-treated group ) . For the alternating staining procedure with cytochrome c and VGluT2 , immunohistochemical labeling was performed using standard procedures . Briefly , brain sections , which should be labeled for VGluT2 , were preincubated for an hour at room temperature in a blocking solution ( 0 . 1 M PBS , 2% bovine serum albumin , and 0 . 5% Triton X-100 ) . Afterwards , primary antibodies were diluted in a solution containing 0 . 5% Triton X-100 and 1% bovine serum albumin . The primary antibody against VGluT2 was incubated with the free-floating sections for at least 24 hours under mild shaking at 4°C . Incubations with the primary antibody was followed by detection with a secondary antibody coupled to the fluorophore Alexa 488 . The secondary antibody was diluted ( 1:500 ) in 0 . 5% Triton X-100 and the reaction was allowed to proceed for 2 hours in the dark at room temperature . After the staining procedure , sections were mounted on gelatin coated glass slides with Mowiol mounting medium . The area of various somatosensory regions was measured by outlining the anatomical region of interest and calculating its area using Neurolucida area calculating tool . The area of the following cortical representations was measured: hindpaw , forepaw , trunk , interlimb cortex , and clitoris . The fraction of genital cortex of the whole S1 area was calculated by dividing the clitoris area by the value of the S1 area . The same was done for the fraction of genital cortex of the interlimb cortex . All statistic tests were conducted in Matlab . In order to quantify the state of vaginal opening after the above described experiments , we assigned different states with vaginal opening scores . A score of 0 points to a closed vagina , whereas a score of 0 . 5 describes a vagina , which was about to open . Finally , a score of 1 represents an open vagina . | We recently identified the somatosensory representation of rat genitals; remarkably , this cortical region—genital cortex—is sexually monomorphic , despite the marked sexual dimorphism of external genitals in rats . Most intriguing was the observation that genital cortex doubles in size during puberty . In order to shed light on this unusual expansion , we studied genital cortex development and sexual maturation in the female rat . We first showed that sex hormones are likely to cause the pubertal expansion of genital cortex . Next , we examined whether sexual experience affects the development of female genital cortex . Raising females together with adult males advanced genital cortex expansion , but cohousing with adult females or exposure to nontactile male cues was not sufficient to drive genital cortex growth . Surprisingly , artificial genital touch led to an early onset of female puberty and growth of genital cortex . In line with this finding , we find that if genital cortex activity is blocked , the advancing effects of adult males on puberty and genital cortex growth are inhibited . Together , our results point to an important role of genital cortex in the puberty-promoting effects of sexual touch . | [
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... | 2017 | Development of rat female genital cortex and control of female puberty by sexual touch |
Chagas disease , caused by the parasite Trypanosoma cruzi , develops into chronic Chagas’ cardiomyopathy in ~30% of infected individuals , characterized by conduction disorders , arrhythmias , heart failure , and even sudden cardiac death . Current anti-parasitic treatments are plagued by significant side effects and poor efficacy in the chronic phase of disease; thus , there is a pressing need for new treatment options . A therapeutic vaccine could bolster the protective TH1-mediated immune response , thereby slowing or halting the progression of chronic Chagas’ cardiomyopathy . Prior work in mice has demonstrated therapeutic efficacy of a Tc24 recombinant protein vaccine in the acute phase of Chagas disease . However , it is anticipated that humans will be vaccinated therapeutically when in the chronic phase of disease . This study investigates the therapeutic efficacy of a vaccine prototype containing recombinant protein Tc24 , formulated with an emulsion containing the Toll-like receptor 4 agonist E6020 as an immunomodulatory adjuvant in a mouse model of chronic T . cruzi infection . Among outbred ICR mice vaccinated during chronic T . cruzi infection , there is a significant increase in the number of animals with undetectable systemic parasitemia ( 60% of vaccinated mice compared to 0% in the sham vaccine control group ) , and a two-fold reduction in cardiac fibrosis over the control group . The vaccinated mice produce a robust protective TH1-biased immune response to the vaccine , as demonstrated by a significant increase in antigen-specific IFNγ-production , the number of antigen-specific IFNγ-producing cells , and IgG2a antibody titers . Importantly , therapeutic vaccination significantly reduced cardiac fibrosis in chronically infected mice . This is a first study demonstrating therapeutic efficacy of the prototype Tc24 recombinant protein and E6020 stable emulsion vaccine against cardiac fibrosis in a mouse model of chronic T . cruzi infection .
Chagas disease , caused by infection with the protozoan parasite Trypanosoma cruzi , is a leading neglected tropical disease globally [1] , and the cause of Chagas’ cardiomyopathy , the most common form of non-ischemic cardiomyopathy in Latin America [2] . An estimated 7 . 2 million people are infected with Chagas disease , with 180 , 000 new cases occurring annually [3] . Chagas disease is responsible for over $7 billion in lost productivity and health care costs annually [4] . Chagas disease is characterized by two clinically distinct phases of disease: acute and chronic . Acute disease is most often a self-limiting febrile illness , however up to 5% of cases develop severe disease including acute myocarditis , pericardial effusion , and meningoencephalitis , with an estimated 0 . 5% risk of mortality [5 , 6] . In chronic disease , 10–30 years after infection , 30% of patients develop chronic cardiomyopathy [2] . Chronic Chagas’ cardiomyopathy ( CCC ) clinically presents as conduction disorders and malignant arrhythmias , which can then progress to cardiomyopathy , heart failure , and even sudden cardiac death [7] . The disease is characterized histologically by post-inflammatory myocardial fibrosis [8] , and human studies have shown that systemic parasite persistence is associated with disease severity [9 , 10] . Clinical progression and survival are poorer in patients with CCC compared to patients with noninflammatory dilated cardiomyopathy , and myocardial fibrosis has been shown to be an independent predictor of adverse outcomes in CCC [11] [12] . The annual mortality of CCC is 4% [13] . In Latin America , an estimated 1 . 17 million people suffer from CCC [1] , and it is the leading cause of cardiovascular death in people aged 30–50 [14] . Current pharmacological treatments ( nifurtimox and benznidazole ) have inadequate efficacy beyond the acute phase of disease , as demonstrated by the recent BENEFIT trial [15] . Additionally , both drugs have a significant side effect profile in up to 50% of patients , most frequently gastrointestinal distress , cutaneous hypersensitivity reactions , and neurological symptoms [16] . In the quest to develop new therapeutics , vaccines offer an attractive solution . Production of the cytokine IFNγ by CD8+ T cells has been correlated with less severe cardiac disease [17]; therefore , a therapeutic vaccine which bolsters the TH1-mediated CD8+ T cell immune response to the infection , might slow or halt the progression of disease [18] . A therapeutic vaccine would be highly cost effective as demonstrated by economic modeling [19] . A promising antigen target is the T . cruzi 24kDa flagellar Ca2+ binding protein ( Tc24 ) [20] . In humans , recombinant Tc24 is already utilized for serodiagnosis of Chagas disease and to monitor treatment response [21 , 22] . Early studies of a DNA vaccine encoding Tc24 have demonstrated therapeutic benefit in mice [23 , 24] , showing high levels of antigen-specific IFNγ+ CD8+ cells , and protecting against parasitemia and cardiac pathology [25] . As a recombinant protein vaccine , Tc24 has shown prophylactic efficacy in mice when formulated with the Toll-like receptor 4 ( TLR4 ) agonist monophosphoryl lipid A [26] . More recently , nanoparticle-encapsulated Tc24 with the TLR9 agonist CpG oligodeoxynucleotides has shown therapeutic efficacy in the acute phase of disease [27] . However , little is known about the protective efficacy of a Tc24 recombinant protein vaccine in the chronic stage of Chagas disease . In this study , we utilize the TLR4 agonist E6020 , mixed into a squalene based stable oil-in-water emulsion , to modulate the immune response alongside recombinant Tc24 . E6020 is a synthetic lipid A derivative that has reduced pyrogenicity , while maintaining immunogenicity . E6020 has been proposed as a safe and cost-effective vaccine adjuvant [28] , and has been demonstrated to be effective in mouse models of a meningococcus vaccine and toxic shock syndrome [29 , 30] . E6020 has previously been proposed as an adjuvant for a Chagas disease vaccine [31] , and has demonstrated high levels of antigen-specific IFNγ when combined with recombinant Tc24 and protected from blood and tissue parasite burdens in the acute stage of a mouse model of T . cruzi infection [32 , 33] . Here , we investigate the TH1-mediated IFNγ+ immune response elicited by a Tc24 recombinant protein in a stable emulsion ( SE ) E6020 vaccine ( Tc24+E6020-SE ) and the resulting therapeutic efficacy in a mouse model of chronic T . cruzi infection .
In order to evaluate the therapeutic efficacy of the prototype Tc24+E6020-SE vaccine in mice in the chronic stage of T . cruzi infection , we investigated cardiac pathology and persistence of systemic parasitemia post-vaccination . Mice were infected with T . cruzi and allowed to progress past the acute phase of disease , characterized by elevated parasitemia resolving by 40 days post-infection ( Fig 1A ) , before vaccination at 70 days post-infection with Tc24+E6020-SE or a sham vaccine . T . cruzi infected mice vaccinated with Tc24+E6020-SE vaccine were significantly more likely to have undetectable systemic parasitemia at all measured time points post-vaccination , compared to mice in the sham control group ( Fig 1B ) . Additionally , the therapeutically vaccinated mice had significantly reduced cardiac fibrosis , with an average of 2 . 5% area of cardiac fibrosis compared to an average of 5% area of cardiac fibrosis in the sham vaccinated control group , as evidenced by analyzing histologic sections of the heart stained for collagen using Masson’s Trichrome ( Fig 2 ) . Overall , inflammatory cell infiltrate in the heart was low , approximately 1200 nuclei/mm2 in sham vaccinated mice , but there was a slight reduction in vaccinated mice compared to the sham control group when analyzing histologic sections of the heart stained using H&E ( Fig 3 ) . We conclude that the Tc24+E6020-SE vaccine is protective against detectable systemic parasitemia and cardiac fibrosis in chronic T . cruzi infection . To characterize the immune response of the vaccine , both antigen-specific IFNγ production and antibody titers were assessed in uninfected mice immunized with the Tc24+E6020-SE vaccine . The vaccine elicits a greater than 5-fold increase in Tc24-specific secreted IFNγ compared to the Tc24 control ( Fig 4 ) . IgG2a , a mouse antibody isotype associated with a TH1-bias , is most robust in the vaccine compared to the controls ( Fig 5A ) , further validating the cytokine results . In comparison , both the Tc24+E6020-SE vaccine and the Tc24 control produce a robust IgG1 antibody response ( Fig 5B ) . These results indicate that the Tc24 recombinant protein is capable of producing an antigen-specific immune response , but that the E6020-SE adjuvant is necessary to induce a favorable TH1-biasing of the resulting immune response . The protective immune response resulting in therapeutic efficacy was then investigated in mice in the chronic stage of T . cruzi infection , by characterizing both antigen-specific TH1- and TH2-associated cytokine production , as well as antibody titers . T . cruzi infected mice vaccinated with the Tc24+E6020-SE vaccine at 70 days post-infection have a two-fold increase in Tc24-specific IFNγ producing cells compared to the sham control group ( Fig 6A ) . Additionally , they have a six-fold increase in Tc24-specific secreted IFNγ compared to the sham control group ( Fig 6B ) , but no significant difference in Tc24-specific secreted IL-4 , a TH2-associated cytokine ( Fig 6C ) . Comparing the ratio of IFNγ to IL-4 in order to determine the extent to which the immune response is TH1-biased , the Tc24+E6020-SE vaccine produces a three-fold larger IFNγ/IL-4 ratio compared to the sham control group ( Fig 6D ) . Tc24-specific antibody isotype titers further corroborate the cytokine results demonstrating a favorable TH1-biased immune response . The Tc24+E6020-SE vaccine produces a significantly greater IgG2a antibody isotype response compared to the sham ( Fig 7A ) , as well as an overall robust IgG1 antibody response ( Fig 7B ) . These results demonstrate that the Tc24+E6020-SE vaccine produces a robust TH1-biased immune response in T . cruzi-infected mice vaccinated in the chronic stage of T . cruzi infection .
This work is a stride towards the development of a therapeutic Chagas disease vaccine that seeks to prevent or delay the onset of CCC in patients infected with T . cruzi [31] . Prior studies by this group have shown therapeutic efficacy of Tc24 protein vaccines in a mouse model of acute T . cruzi infection as evidenced by a reduction in both systemic parasitemia and cardiac parasite burden , and protection from cardiac inflammation [27 , 32 , 33] . However , it is anticipated that humans will be diagnosed and vaccinated in the chronic stage of disease , as the acute phase of disease is often asymptomatic or a self-limiting febrile illness [31] . Therefore , it is critical to investigate therapeutic vaccine candidates in a model of chronic T . cruzi infection to more closely replicate the proposed clinical vaccination strategy . Prior studies of a therapeutic Tc24 DNA vaccine administered at 70 days post-infection in the early chronic phase of disease in a mouse model of Chagas disease , similar to the model utilized here , showed improved survival and reduced cardiac inflammation [23] . More recently , an adenovirus-based therapeutic vaccine demonstrated improvements in cardiac histopathology and electrical conduction abnormalities as markers of reduction in CCC disease progression , similar to outcomes measured in this study [34] . However , while precedent exists for licensure of recombinant protein vaccines in humans , no DNA or adenovirus-based vaccines have progressed to market . This is the first study that demonstrates therapeutic efficacy of a Tc24 recombinant protein-based vaccine in a mouse model of chronic T . cruzi infection . In this study , we show that a Tc24 recombinant protein vaccine with a stable emulsion containing E6020 as an immunomodulatory adjuvant results in a statistically significant reduction in cardiac fibrosis and inflammation in vaccinated mice compared to mice receiving the sham vaccination . This reduction in cardiac fibrosis is evidence of vaccine protection from chronic Chagas’ cardiomyopathy , as supported by studies that show the cardiac disease is characterized by inflammatory infiltrate and extensive reactive and reparative fibrosis [8 , 35 , 36] . Additionally , the Tc24+E6020-SE vaccine results in a reduction in detectable systemic parasitemia in vaccinated mice . We propose this reduction and subsequent decrease in parasite-driven tissue damage is one mechanism by which fibrosis is prevented . These findings are supported by studies in human showing systemic parasite persistence is associated with CCC and disease severity [9 , 10] . We conclude that the Tc24+E6020-SE vaccine is protective from myocardial fibrosis when used therapeutically in a mouse model of chronic T . cruzi infection . A key challenge in the development of this vaccine is the induction of the necessary immune response; unlike most vaccines that rely on an antibody-mediated immune response , a Chagas vaccine will require a protective cell-mediated immune response to be efficacious against the parasite . In this study , to elicit a protective TH1-mediated IFNγ+ immune response we combined a previously validated protein antigen , Tc24 , with a stable emulsion of E6020 as an immunomodulatory adjuvant . In this study , the Tc24+E6020-SE vaccine produces a robust TH1-biased immune response , as measured by cytokine and antibody production , in both uninfected ICR mice and ICR mice in the chronic stage of T . cruzi infection . Our findings of a robust TH1-biased immune response are consistent with our previous observations using this adjuvant in other mouse models [32 , 33] . In contrast to Aluminum hydroxide vaccine adjuvants ( such as Alhydrogel ) , the adjuvant type utilized in 80% of currently licensed vaccines that produces a predominantly TH2-skewed immune response , [37 , 38] E6020 preferentially induces a TH1-skewed immune response through the TLR4 pathway [39] . It is key to note that chronically infected humans have high serum levels of circulating pro-inflammatory cytokines , including IFNγ , IL-6 , TNFα and IL-1β [40] , as well as antigen specific pro-inflammatory cells [17] . In pre-clinical models it has been demonstrated that T . cruzi derived glycoinositolphospholipid ( GIPL ) is a potent agonist of the TLR4 receptor , enhancing production of TNFα and MIP while increasing neutrophil recruitment , and conferring some resistance to T . cruzi infection [41] . However , TLR4 receptor engagement by GIPL does not provide long term benefit on disease pathogenesis as wild type TLR4 mice still succumb to infection , although at a later time than TLR4 deficient mice [41] . Additionally , GIPL has been shown to have immunomodulatory effects , downregulating IL-2 production and proliferation of T cells in a reversible manner , since removal of GIPL restores T cell proliferation to baseline levels [42] . Further , GIPL downregulates costimulatory molecule expression on APCs , including macrophages and dendritic cells [43] . These data indicate that while T . cruzi derived GIPL induces pro-inflammatory responses via TLR4 receptor engagement , it plays a larger role in subverting the immune response . In the face of T . cruzi derived GIPL being present in chronically infected mice , we hypothesize that the TLR4 agonist E6020 is a more potent stimulator of the TLR4 receptor , similar to LPS which has been shown to induce increased TNFα both locally and systemically , and for a longer duration , when compared to GIPL [41] . E6020 has been shown to have a promising safety profile based on studies in animal models [44] . Precedent exists for utilizing a TLR4 agonist in humans: the licensed vaccines Fendrix , for the prevention of hepatitis B , and Cervarix , the HPV vaccine , both utilize the TLR4 agonist monophosphoryl lipid A [45] . Compared with monophosphoryl lipid A , E6020 has a simplified structure , replacing the typical disaccharide backbone with a simple hexa-acylated acyclic backbone , allowing for faster compound synthesis and improved yield of high-purity material [28 , 46] . While small animal models do not mimic all aspects of human Chagas disease , the mouse model described here developed significant cardiac fibrosis , which is a key component of CCC [11 , 47] . In the model described in this manuscript mice developed significant cardiac fibrosis , which is a hallmark of chronic determinate disease in humans [35 , 48] . Further , it has been shown that up to 72% of patients in the clinically silent chronic indeterminate phase have evidence of cardiac fibrosis [49] , thus the mouse model described here does mimic a key component of human disease and can be used to screen novel therapies for efficacy prior to advancing to human studies . One limitation of this model is the overall low level of cardiac inflammation , which is a key finding in human cases of CCC [47] . Here we showed that infected sham vaccinated outbred ICR mice had an average inflammatory infiltrate of approximately 1200 nuclei per mm2 tissue ( Fig 3 ) , which is very low compared to our prior studies showing approximately 6000 nuclei per mm2 tissue in acutely infected inbred BALB/c mice [50] . This difference in cardiac pathology depending on mouse genetic background mimics the differences in cardiac inflammation found by Pereira and colleagues who showed that C3H mice had much greater cardiac inflammation when compared to C57BL/6 mice when both were infected with the Colombian T . cruzi strain [51] . However , despite the comparatively low cardiac inflammation , infected C57BL/6 mice did develop significant cardiac fibrosis which the authors concluded represented a mild CCC phenotype [51] . In the outbred ICR model of chronic T . cruzi H1 infection we report in this manuscript , we do see significant cardiac fibrosis where the infected untreated mice had an average of 5 . 0% fibrotic area compared to 1% in naïve age matched controls ( Fig 2 ) , demonstrating that this model does mimic the significant cardiac fibrosis seen in human disease and is useful for evaluating the effect of novel therapies for reducing cardiac fibrosis . Further , this finding of significant cardiac fibrosis in the outbred ICR model of chronic infection supports our previously published finding of significant cardiac fibrosis in acutely infected inbred BALB/c mice ( 2% ) compared to age matched uninfected controls ( ~0 . 5% ) [52] . Thus , while we predict that our findings of vaccine induced immunogenicity and therapeutic efficacy against cardiac fibrosis in a mouse model of chronic T . cruzi infection will be translatable to humans , additional studies in other models that develop CCC more characteristic of human disease , such as non-human primates , will be necessary before the vaccine can be moved into clinical trials . In the quest to develop a therapeutic vaccine against Chagas disease , only limited work has been conducted using therapeutic recombinant protein vaccine prototypes in the chronic stage of T . cruzi infection . This is the first reported study of a therapeutic vaccine utilizing Tc24 protein and a stable emulsion of E6020 as an immunomodulatory adjuvant in a mouse model of chronic T . cruzi infection . It is also an important proof of principle study that a vaccine administered in the chronic stage of disease reduces parasitemia and myocardial fibrosis , and may thus slow chronic Chagas’ cardiomyopathy disease progression . Ultimately , a vaccine-linked chemotherapy strategy may be employed in Chagas disease treatment , in which the vaccine is paired with reduced-dose chemotherapy to increase efficacy and reduce side effects [31 , 33] . Future studies could elucidate the efficacy of this strategy utilizing the Tc24+E6020-SE vaccine . Additionally , scale-up production of the Tc24 recombinant protein ( modified to avoid or limit intermolecular disulfide bond formation and aggregation ) suitable for non-human primate or human testing is in process [32 , 53] . In conclusion , the Tc24+E6020-SE vaccine demonstrates robust TH1-biased immunogenicity , decreased systemic parasitemia , and protection from chronic myocardial fibrosis in a mouse model of chronic T . cruzi infection .
All studies were approved by the Institutional Animal Care and Use Committee of Baylor College of Medicine ( Protocol AN-5973 ) , Assurance numbers D16-00475 ( current ) and 3823–01 ( previous ) and were performed in strict compliance with The Guide for the Care and Use of Laboratory Animals ( 8th Edition ) [54] . Recombinant Tc24 protein was expressed in an E . coli system and purified with Ni-column chromatography as has been described previously . [26 , 27] Briefly , codon-optimized DNA encoding full-length Tc24 from a Yucatan H1-strain of T . cruzi was cloned into a pET41a E . coli expression vector ( EMD Millipore , 70556 ) with deleted fusion GST ( NdeI/XhoI ) . The resulting plasmid DNA was transformed into BL21 ( DE3 ) cells ( EMD Millipore , 69450 ) and induced with IPTG for protein production . The recombinant Tc24 was purified with IMAC Ni-column chromatography ( GE Healthcare , Little Chalfont , United Kingdom ) , and then endotoxin contamination was removed with Q column purification ( GE Healthcare , Little Chalfont , United Kingdom ) . The synthetically produced TLR4 agonist E6020 was obtained from Eisai Inc . , Andover , MA , mixed into a stable oil-in-water emulsion ( 1mg/mL E6020 , 5% Squalene , 0 . 92% D-α-Tocopherol polyethylene glycol 1000 succinate , 0 . 76% Span 80 ) in PBS ( E6020-SE ) . The Tc24 protein sample , also in PBS , and E6020 adjuvant were mixed in a 1:1 ratio at bedside , immediately before injection ( Tc24+E6020-SE ) . For all experiments , 0 . 1mL of the final formulation was injected subcutaneously . In the study assessing therapeutic efficacy in chronic disease , the Tc24+E6020-SE vaccine contained 100μg Tc24 and 25μg E6020 and the sham contained only PBS . In the immunogenicity study , the Tc24+E6020-SE vaccine contained 25μg Tc24 and 5μg E6020 , a Tc24 control contained only 25μg Tc24 and an E6020-SE control contained only 5μg E6020 . The sham vaccine group contained only PBS ( Corning 21-040-CV ) . Female ICR mice ( Taconic Biosciences ) , aged 6–8 weeks , were used in all experiments . Animal experiments were performed in full compliance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals , 8th edition , under a protocol approved by Baylor College of Medicine’s Institutional Animal Care and Use Committee ( IACUC ) , assurance numbers 3823–01 and D16-00475 . Two studies were conducted , one investigating the vaccine efficacy and immunology in mice chronically infected with T . cruzi , and a second study elucidating the immune response to the vaccine in uninfected mice . T . cruzi H1 strain parasites , previously isolated from a human case in Yucatan , Mexico , [23 , 55] were maintained by serial passage in mice . To test therapeutic efficacy of the vaccine , naïve mice were infected intraperitoneally with 500 trypomastigotes then subsequently immunized in a prime boost model with vaccine or sham . The mice were first immunized subcutaneously at 70 days post-infection , and then a boost vaccination was administered four weeks later at 98 days post-infection . Mice were sacrificed at 180 days post-infection . For the immunogenicity study , mice were vaccinated in a prime boost model subcutaneously with vaccine , control groups , or sham , and then a boost vaccination was administered two weeks later . Mice were sacrificed two weeks after the boost vaccination . At the conclusion of both studies , mice were humanely euthanized using ketamine/xylazine-induced deep anesthesia followed by cervical dislocation and then blood , spleens , and hearts were collected . Throughout the studies , all efforts were made to minimize suffering . Blood was collected from infected mice semi-weekly through the acute phase of disease and then at five time points post-vaccination in the chronic phase of disease ( at 77 , 98 , 115 , 140 , and 180 days post-infection ) . Total DNA was isolated from blood using a DNEasy 96 blood and tissue kit ( Qiagen , 69581 ) . Parasitemia was assessed by quantitative real-time PCR as previously described [27] . Briefly , PCR was performed using 10ng purified DNA , TaqMan Fast Advanced Master Mix ( Life Technologies , 4444557 ) , and oligonucleotides specific for the satellite region of T . cruzi nuclear DNA ( primers 5’ ASTCGGCTGATCGTTTTCGA 3’ and 5’ AATTCCTCCAAGCAGCGGATA 3’ , probe 5’ 6-FAM CACACACTGGACACCAA MGB 3’ , Life Technologies , 4304972 , 4316032 ) [56 , 57] . Data were normalized to GAPDH ( primers 5’ CAATGTGTCCGTCGTGGATCT 3’ and 5’ GTCCTCAGTGTAGCCCAAGATG 3’ , probe 5’ 6-FAM CGTGCCGCCTGGAGAAACCTGCC MGB 3’ , Life Technologies , 4304972 , 4316032 ) [58] , and parasite equivalents were calculated from a standard curve [27 , 59 , 60] . For cytokine production analysis , whole spleens from sacrificed mice were passed through 40μm strainers ( BD Biosciences , 352340 ) to dissociate cells and then red blood cells were lysed with ACK lysis buffer ( Lonza , 10-548E ) . Cells were stained with AOPI Staining Solution and viable cells counted using a Cellometer Auto 2000 automated cell counter ( Nexcelom Biosciences , Lawrence , MA ) . Cells were diluted to appropriate concentrations in 10% FBS , 1X Pen/Strep in RPMI-1640 ( all from Corning , 35-011-CV , 30-002-CI , 10-040-CV ) for cellular assays . Antigen-specific cytokine release from splenocytes was quantified by ELISA as previously described [27] . Briefly , 2x106 splenocytes/mL were incubated with 50μg/mL Tc24 , 5μg/mL ConA , or media only for 72hrs , 37°C , 5% CO2 . Supernatant IFNγ and IL-4 was measured by a sandwich ELISA method using Mouse IFNγ and IL-4 ELISA kits ( eBioscience , 88–7314 , 88–7044 ) . Cytokine concentrations produced by antigen-specific cells were calculated by background subtraction of the media only stimulated cells . Antigen-specific IFNγ-producing splenocytes were quantified by ELISpot using an ImmunoSpot kit ( Cellular Technology Limited , MIFNG-1M ) . Briefly , 2 . 5x105 splenocytes were incubated with 50μg/mL Tc24 , 5μg/mL Concanavalin A ( ConA , Sigma-Aldrich , C0412 ) , or media only for 24hrs , 37°C , 5% CO2 . After the cytokine detection process , spots were analyzed using a CTL-ImmunoSpot S6 Macro Analyzer ( Cellular Technology Limited , Shaker Heights , OH ) . The frequencies of antigen-specific IFNγ-producing cells were calculated by background subtraction of the media only stimulated cells . Serum antibodies specific for Tc24 were measured by ELISA as previously described [27] . Briefly , blood samples from mice were allowed to coagulate in Serum-Gel clotting tubes ( SARSTEDT , 41 . 1378 . 005 ) and then centrifuged to separate serum per manufacturer’s instructions . Plates ( Thermo Scientific , 44-2404-21 ) were coated with 1 . 25μg/mL Tc24 in coating solution ( KPL , 50-84-00 ) , blocked , and serially diluted serum samples were added . Bound antibody was detected with HRP-conjugated goat anti-mouse IgG1 or IgG2a secondary antibody ( LifeSpan Biosciences , LS-C59107 , LS-C59112 ) and the reaction was developed with TMB Substrate ( Thermo Scientific , 34021 ) . Titers were recorded as the last dilution above a threshold O . D . , calculated by O . D . Avg+ 3SD of serum from naïve mice . For histopathological analysis , heart tissue fixed in 10% neutral buffered formalin was embedded in paraffin , cut into 5μm sections , and stained with either Masson’s Trichrome or hematoxylin and eosin ( H&E ) stain . To assess fibrosis representative tissue sections were chosen for each mouse and 30 images were acquired with a Micromaster microscope ( Fisher Scientific ) and Micron software at 20x magnification . Image analysis was performed using ImageJ software 1 . 48v ( National Institutes of Health , Bethesda , MD ) . Pixels corresponding to fibrosis were quantified and normalized to total pixels of the sample to assess the percentage of fibrotic area in the cardiac tissue . To assess inflammation , representative tissue sections were chosen for each mouse and 10 images were acquired with an EVOS microscope ( EVOS ) . Image analysis was performed using ImageJ software 1 . 48v ( National Institutes of Health , Bethesda , MD ) . The number of total nuclei was quantified and normalized to total tissue area analyzed in the cardiac tissue . Results were analyzed by the Kruskal-Wallis test with Dunn’s correction for multiple comparisons , or , when only two comparison groups were analyzed , Mann–Whitney U test . Results for serum antibody were log-transformed and analyzed by one-way ANOVA with Tukey’s correction for multiple comparisons , as has been previously described [27] . Results for systemic parasitemia were analyzed by Fischer’s exact test . Differences between treatment groups were considered statistically significant if the p-value was less than 0 . 05 . Statistical analysis was performed using Prism software 6 . 0 ( GraphPad Software , La Jolla , CA ) . | Chagas disease is a parasitic infection that can cause severe heart disease . Current treatments do not work well and have significant side effects . Because of this , the authors created a new vaccine prototype with the goal that it could be given to infected people to prevent Chagas-associated heart disease . The vaccine contains a manufactured protein identical to a protein in the parasite ( called Tc24 ) as well as a component to help the body produce a protective immune response ( a vaccine adjuvant called E6020 ) . The vaccine would boost the body’s natural immune response to the parasite infection , reducing the number of parasites in the body , and protecting the heart . Frequently , people are not diagnosed until later in the infection , because the early ( or acute ) stage of disease can be mistaken for a common cold . Because of this , it is important to test the vaccine when given in the later ( or chronic ) stage of infection . The authors tested the vaccine in a mouse model of chronic T . cruzi infection and found that the vaccinated mice had lower levels of parasites in their body and less damage to their hearts . This research shows promising value of a therapeutic vaccine to prevent Chagas-associated heart disease in a mouse model , with the hope that the same effect could be found in humans one day . | [
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"orga... | 2019 | A therapeutic vaccine prototype induces protective immunity and reduces cardiac fibrosis in a mouse model of chronic Trypanosoma cruzi infection |
We have previously shown that during pregnancy the E-twenty-six ( ETS ) transcription factor ELF5 directs the differentiation of mammary progenitor cells toward the estrogen receptor ( ER ) -negative and milk producing cell lineage , raising the possibility that ELF5 may suppress the estrogen sensitivity of breast cancers . To test this we constructed inducible models of ELF5 expression in ER positive luminal breast cancer cells and interrogated them using transcript profiling and chromatin immunoprecipitation of DNA followed by DNA sequencing ( ChIP-Seq ) . ELF5 suppressed ER and FOXA1 expression and broadly suppressed ER-driven patterns of gene expression including sets of genes distinguishing the luminal molecular subtype . Direct transcriptional targets of ELF5 , which included FOXA1 , EGFR , and MYC , accurately classified a large cohort of breast cancers into their intrinsic molecular subtypes , predicted ER status with high precision , and defined groups with differential prognosis . Knockdown of ELF5 in basal breast cancer cell lines suppressed basal patterns of gene expression and produced a shift in molecular subtype toward the claudin-low and normal-like groups . Luminal breast cancer cells that acquired resistance to the antiestrogen Tamoxifen showed greatly elevated levels of ELF5 and its transcriptional signature , and became dependent on ELF5 for proliferation , compared to the parental cells . Thus ELF5 provides a key transcriptional determinant of breast cancer molecular subtype by suppression of estrogen sensitivity in luminal breast cancer cells and promotion of basal characteristics in basal breast cancer cells , an action that may be utilised to acquire antiestrogen resistance .
The molecular subtypes of breast cancer are distinguished by their intrinsic patterns of gene expression [1] that have been refined to become prognostic tests under evaluation or in use [2] . Improving our understanding of the molecular events specifying these subtypes offers the hope of new predictive and prognostic markers , development of new therapies , and interventions to overcome resistance to existing therapies . The estrogen receptor ( ER ) positive luminal subtypes are characterized by patterns of gene expression driven by the combined direct and indirect transcriptional influences of ER and FOXA1 [3] . ELF5 , also known as ESE2 [4] is a member of the epithelium specific ( ESE ) subgroup of the large E-twenty-six ( ETS ) transcription factor family [5] , found in lung , placenta , kidney , and most prominently in the breast especially during pregnancy and lactation [6]–[8] . Placentation fails in Elf5 knockout mice [9] because de novo production of ELF5 acts with CDX2 and EOMES to specify and maintain commitment to the trophoblast cell lineage [10] . The early embryo continues to repress Elf5 expression in association with promoter methylation [11] . In the developing mammary epithelium Elf5 is re-expressed in a mutually exclusive pattern with ER [12] . Elf5−/− mice produced via tetraploid embryonic stem cell rescue [12] or conditional knockout [13] showed complete failure of mammary alveolargenesis , a developmental stage driven by prolactin and progesterone . These hormones induce Elf5 expression and re-expression of Elf5 in prolactin receptor knockout mammary epithelium rescued alveolargenesis [14] . Forced ELF5 expression in nulliparous mouse mammary gland produced precocious mammary epithelial cell differentiation and milk protein production . This was associated with erosion of the mammary CD61+ progenitor cell population , and conversely , Elf5 knockout caused accumulation of this population , establishing ELF5 as a key regulator of cell fate decisions made by this progenitor cell population [12] and explaining the developmental effects described above . The CD61+ progenitor cell is the cell of origin for basal breast cancers [15] , [16] and Elf5 is expressed predominantly by the ER− progenitor subset [17] , suggesting , together with the developmental effects of Elf5 outlined above , a role for ELF5 in determining aspects of molecular subtype of breast cancer . To examine this hypothesis we manipulated the expression of ELF5 in basal and luminal breast cancer cell lines and examined the phenotypic consequences .
In the UNC337 breast cancer series [18] ELF5 was expressed predominantly by the basal subtype in addition to normal breast and normal-like subtype ( Figure 1 ) , an observation confirmed in cohorts described by Pawitan [19] and Wang [20] ( Figure S1 ) . Oncomine ( www . oncomine . org ) revealed that ELF5 expression was low in tumors expressing ER , progesterone receptor ( PR ) , or ERBB2 and high in the “triple negative” subtype lacking these markers . ELF5 expression was correlated with high grade , poor outcomes such as early recurrence , metastasis , and death , response to chemotherapy , and mutations in p53 or BrCa1 , all characteristics of the basal subtypes ( Figure S2 ) . ELF5 expression was lower in cancer compared to patient-matched and micro-dissected normal mammary epithelium ( Figure S2 ) , and a series from Sgroi and colleagues [21] found ELF5 was one of the most consistently downregulated genes at all stages of breast carcinogenesis ( Figure S1 ) . To test the ability of ELF5 to drive estrogen insensitivity we used ER+ luminal breast cell lines T47D and MCF7 to construct DOXycycline ( DOX ) -inducible expression models of ELF5 ( Figure S3A ) . In humans , ELF5 is also known as ESE2 and 2 isoforms exist . The ESE2B isoform was expressed at 1 , 774- and 1 , 217-fold excess over the ESE2A isoform in MCF7 and T47D , respectively ( Figure S3B ) . We tagged ESE2B at its C-terminus with V5 ( referred to subsequently as ELF5-V5 ) , and demonstrated that this did not alter its ability to induce the transcription of its best characterized direct transcriptional target , whey acidic protein ( Wap ) in HC11 cells ( Figure S3C ) . We interrogated our inducible models using Affymetrix arrays . Functional signatures within these expression profiles were identified by gene set enrichment analysis ( GSEA ) [22] , [23] , and were visualized using the Enrichment Map plug-in for Cytoscape [24] . The original data are available via GEO ( GSE30407 ) , and GSEA and Limma analysis from the corresponding author . Figure 2 displays the GSEA networks derived from the effects of forced ELF5 expression in T47D or MCF7 cells and provides a comprehensive view of the functional consequences of forced ELF5 expression in the luminal subtype . Figure S4 provides the complete network as a fully scalable PDF allowing the identification of all nodes . Acute forced ELF5 expression caused enhancement ( positive enrichment-red nodes ) of oxidative phosphorylation , translation , proteasome function , and mRNA processing . We observed suppression ( negative enrichment-blue nodes ) of the DNA synthetic and mitotic phases of the cell cycle , intracellular kinase signaling , cell attachment , the transmembrane transport of small molecules , transcription , and a large set of genes involved in aspects of cancer , stem cell biology , and especially the distinction of breast cancer subtypes and estrogen sensitivity . The cancer-proliferation and breast cancer subtype sub networks , the subjects of further investigation , are shown in Figures S5 and S6 , and the expression of the individual genes forming the leading edges of example sets from these clusters are shown as heat maps in Figures S7 , S8 , S9 , S10 . We validated these findings using human breast cancers . Using luminal A breast cancers from the UNC337 series we produced a ranked gene list by Pearson correlation with ELF5 expression . This approach produced an enrichment map that was very similar to that produced above ( Figure 2 ) by forced ELF5 expression , with cell cycle sets , cancer sets , and sets describing luminal characteristics and estrogen responsiveness prominent among the suppressed gene clusters ( Figure S11 ) , demonstrating a very similar action of endogenous ELF5 in luminal A breast cancers compared to forced ectopic expression in luminal breast cancer cells . We used a mixture of antibodies against V5 and ELF5 to immunoprecipitate DNA bound by ELF5-V5 in T47D cells , which we then sequenced , allowing us to map the ELF5-bound regions of the human genome and to identify the direct transcriptional targets of ELF5 . Intersection of MACS and SWEMBL peak calls [25] , [26] identified 1 , 763 common sites of ELF5 interaction in the genome at 48 h . Data are available in Table S1 or via GEO ( GSE30407 ) . DNA binding was much higher at 48 h than 24 h ( Figure 3A ) , consistent with the observed changes in gene expression by Affymetrix arrays . Combination of the Affymetrix expression and chromatin immunoprecipitation of DNA followed by DNA sequencing ( ChIP-Seq ) data showed that ELF5 binding within 10 kb of a transcription start site ( TSS ) changed the expression level of that gene to a much greater extent than expected by chance ( Figure 3B ) , demonstrating that ELF5 has consistent transcriptional activity via association with DNA within this range . ELF5 bound mostly to distal intragenic regions of the genome ( 50% ) and to introns within genes ( 25% ) , but also at high frequency to promoter regions ( 20% ) mostly within 1 kb of a TSS ( 18% ) . Downstream ( Dstr ) sites were seldom used . The 5′ UTR was also a frequent target of ELF5 but the 3′ UTR was infrequently targeted ( Figure 3C ) . Transcription factor motifs ( Figure 3D ) contained within the DNA fragments precipitated by ELF5 were predominantly ELF5 and other ETS factor motifs; however , we also observed enrichment of sites for Stat1 and Stat3 , which contain a TTCC core ets motif . We also observed very significant enrichment of sites for the FOXA1 and NKX3-2 transcription factors . The binding of ELF5 to the FOXA1 promoter region is shown in Figure 3E . We validated the indicated peak on the FOXA1 promoter , and three other target transcription factors by ChIP-qPCR ( Figure 3F ) . FOXA1 , RUNX1 , GATA3 , and MEIS2 were validated as targets of ELF5 by comparison to input , indicating that ELF5 heads a transcriptional cascade . We searched for curated functional signatures among the ChIP targets using GSEA ( Figure 3G ) . Many of the functional signatures observed in the ChIP data were also present in the expression data , demonstrating a direct transcriptional action of ELF5 to exert these regulatory effects . We examined changes in phenotype observed in T47D-ELF5-V5 and MCF7-ELF5-V5 cells following DOX treatment . In control T47D and MCF7 cells carrying the puromycin-resistant , but otherwise empty expression vector , normal logarithmic accumulation of cells during culture continued with or without DOX ( Figure 4A ) . In contrast , when ELF5-V5 was induced ( denoted as T47D-ELF5-V5 and MCF7-ELF5-V5 ) , cells stopped accumulating between 24 and 48 h after DOX administration ( Figure 4B ) , regardless of the timing of induction ( Figure S12A ) . The 4-fold induction of ELF5-V5 expression by DOX in T47D cells was similar to that produced for endogenous ELF5 with R5020 , a synthetic progestin ( Figure S12A , inset ) , demonstrating that this model produces physiological increases of ELF5 expression . The effect was also reversible ( Figure S12B ) . Investigation of anchorage-independent growth in soft agar showed that induction of ELF5-V5 produced fewer colonies ( Figure S12C ) . Xenografts of T47D-ELF5-V5 cells in nude mice grew at a slower rate when mice received DOX ( Figure 4C ) . Knockdown of ELF5 expression by more than 80% had a small effect on total cell accumulation in T47D or MCF7 cells ( Figure S12D ) . We knocked down ELF5 in two basal breast cancer cell lines and observed a significant and sustained reduction in cell accumulation rate ( Figure 4D and 4E ) , which was not seen in luminal cells ( Figure S12D ) . This observation clearly demonstrates a subtype-specific role of ELF5 in breast cancer cells . Cells can fail to accumulate in culture via two main mechanisms , by reduced rates of cell division or by the loss of cells through detachment and apoptosis . We investigated these possibilities . We examined cell proliferation . Labeling of cells with BrdU and propidium iodide showed that induction of ELF5-V5 caused repartitioning of cells from S-phase into gap 1 of the cell cycle ( G1 ) ( Figure S13A ) . Western blotting showed a loss of phosphorylated forms of the pocket proteins , p130 , p107 , and Rb , accompanied by loss of cyclin proteins A2 , B1 , and D1 , and accumulation of the inhibitor p21 ( Figure S13B ) . Many of these changes also occurred at the mRNA level ( Figure S13C ) , indicating a transcriptional basis to these changes that together suggest inhibition of proliferation by G1 arrest . To test this we arrested T47D-ELF5-V5 cells in the G1 phase of the cell cycle using hydroxyurea ( HU ) and then released them , by HU wash out , into cycle in the presence and absence of induction of ELF5-V5 expression ( Figure 4F , corresponding flow cytometric plots in Figure S13D , and Western blot quantification in Figure S13E ) . Induction of ELF5-V5 reduced the percentage of cells exiting G1 into S-phase and was associated with a reduced accumulation of cyclin D1 protein and reduction in the expression of cyclin B1 , demonstrating that ELF5-V5 expressing cells failed to re-enter the cell cycle from G1 . We previously formed a set of 641 genes associated with cell cycle control by a combination of genes from cell cycle–related GO ontologies [27] . This set very significantly overlapped with 125 genes repressed , and 42 genes induced , by ELF5 expression ( Figure S14A ) , and of these 55 were ELF5 ChIP targets ( Figure S14A , Figure S14B heat maps ) indicating a direct transcriptional influence of ELF5 on proliferation . Upregulated ELF5 ChIP targets were characterized by the presence of tumor suppressor genes while downregulated genes were enriched in genes controlling cell proliferation . Upregulated genes included RB1CC1 ( promotes RB1 expression ) , TBRG1 ( promotes G1 arrest via CDKN2A ) , IRF1 ( initiates interferon response ) , COPS2 ( p53 stabilizer ) , CHFR ( prevents passage into mitosis ) , DAB2 ( lost in ovarian cancer ) , and RAD50 ( DNA damage checkpoint ) . Also in this group are DDIT3 ( promotes apoptosis due to endoplasmic reticulum stress ) and ERBB2IP ( disrupts RAF/RAS signaling ) . ELF5 ChIP targets repressed by elevated ELF5 were characterized by genes required for mitosis , such as GTSE1 ( microtubule rearrangement ) , KIF11 ( spindle formation ) , FBXO3 ( anaphase promoting complex ) , KNTC1 ( mitotic check point ) , PPP1CC ( PTW/PP1 complex member ) , and PMF1 ( MIS12 complex chromosome alignment ) . Other proproliferative ELF5 ChIP targets that were downregulated include EGFR and IGF1R ( potent mammary mitogen receptors ) , MAPK13 ( downstream signaling molecule ) , c-MYC ( key regulator of proliferation ) , KLF10 ( transcriptional repressor of proliferation ) , and NME1 and SLC29A2 ( required for nucleotide synthesis ) . This 55-gene signature is significantly enriched in many breast cancer series ( Figure S14C ) and showed differential expression between ER+ and ER− cancers ( Figure S14B , right-hand heat map ) . Interestingly the mitogenic genes that are repressed by forced ELF5 expression in ER+ T47D cells are generally highly expressed in ER− cancers ( Figure S14B ) , showing again that ELF5 has a subtype-dependent role in cell proliferation and may contribute to the proliferative drive in ER− cancers . A large number of detached and floating cells were observed in cultures after 48 h of DOX treatment and became most prominent by 72 h ( Figure 5A ) . Replating efficiency was greatly reduced , indicating that new adherence proteins could not be rapidly synthesized and deployed following their destruction with trypsin ( Figure 5B ) . Higher rates of apoptosis , measured using flow cytometry , were observed in T47D-ELF5-V5 and MCF7-ELF5-V5 cells ( Figure 5C ) . The levels of beta 1-integrin were much lower by 72 h ( Figure 5D quantitated in Figure S12E and S12F ) . Its signaling partner integrin-linked kinase ( ILK ) also showed reduced expression . Focal adhesion kinase ( FAK ) levels also fell slightly but phosphorylation of FAK was much reduced from 5 d , as was SRC kinase expression and especially phosphorylation , indicating reduced signal transduction in response to the lower levels of beta1-integrin and detection of the extracellular matrix . Together these results implicate loss of extracellular integrins in the detachment of cells in response to forced ELF5 expression . Among the direct transcriptional targets of ELF5 are a number with established roles in proliferation in response to estrogen , such as FOXA1 , MYC , CDK6 , FGFR1 , and IGF1R ( Table S1 ) . In addition , key genes associated with the estrogen-sensitive phenotype , such as ESR1 and estrogen-response genes , such as GREB1 and XBP1 , are downregulated ( Figure S9 ) . Western blotting showed that induction of ELF5-V5 expression caused falls in the levels of ER , the estrogen-induced gene progesterone receptor ( PGR ) , pioneer factor FOXA1 , and progenitor cell-regulator GATA3 ( Figure 6A ) . The activities of ER and FOXA1 transcriptional reporters ( ERE and UGT2B17 , respectively ) also fell ( Figure 6B ) , demonstrating that forced ELF5 expression suppressed estrogen sensitivity . These cell lines are dependent on estrogen for proliferation , raising the possibility that forced ELF5 expression inhibited proliferation simply by reducing ER expression . We tested this possibility by forced re-expression of ER and treatment with estrogen ( Figure 6C ) , but we did not observe any relief of the inhibition of proliferation caused by forced ELF5 expression . We further examined the effects of induction of ELF5 on estrogen-driven gene expression by intersecting our ELF5-regulated genes with a previously defined set of estrogen-regulated genes in MCF7 cells [27] . Among a set of 477 genes showing estrogen-induced expression in MCF7 cells ( Figure 6D , “E2 induced” ) , 115 showed loss of expression in response to ELF5-V5 , an overlap with a highly significant p-value ( p = 5E−84 ) and odds ratio ( OR = 16 ) . These genes ( heat map in Figure S14D , “E2I” ) , contained signatures for cell cycle control and DNA replication gene sets . Furthermore when we focused on 71 estrogen-induced genes previously defined as involved in proliferation [27] ( Figure 6D , “E2 Prolif” ) , we observed the same very significant enrichment ( p = 2E−32 ) , confirming the action of ELF5 to repress the expression of estrogen-induced genes involved in proliferation . The effect of ELF5 expression on 289 estrogen-repressed genes ( Figure 6D , “E2 repressed” and heat map Figure S14D , “E2R” ) was much less pronounced . Thus the predominant effect of forced ELF5 expression was suppression of estrogen-induced gene expression . Just 29 genes were direct transcriptional targets of both ELF5 and ER , a small fraction of the total number of genes showing changed expression , indicating that the actions of ELF5 and ER are largely executed by intermediaries , rather than direct action of ELF5 and ER at the same genomic locus . We used hypergeometric enrichment to discover previously defined experimental signatures among the direct transcriptional targets of ELF5 . Signatures indicative of estrogen action were prominent among ELF5 ChIP targets downregulated ( fold change [FC]>1 . 5 and false discover rate [FDR]>0 . 25 ) by ELF5 expression , including sets of genes that were ESR1 targets , involved in endocrine resistance or which distinguished the luminal from basal subtypes ( Figure 6E ) . Among the cancer-focused sets provided by Oncomine ( set names in lower case in Figure 6E ) were many associated with distinction of the triple negative and ER/PR/HER2-positive subtypes . Sets among the upregulated ChIP targets included metastasis , apoptosis , and high grade . Heat maps illustrating the changed expression of the individual ELF5 ChIP targets are shown using the top-hit breast cancer series ( * marked sets in Figure 6E shown as heat maps in Figure S14E ) . This investigation again illustrates the repression of estrogen action by induction of ELF5 , but indicates that many of the poorer prognostic aspects of the ER− subtypes may be due to ELF5-induced genes . Again ELF5 appears to have subtype-specific actions . We examined the ability of the direct transcriptional targets of ELF5 to predict aspects of breast cancer phenotype . A set of 164 genes was defined as ChIP targets with altered expression in response to induction of ELF5 in T47D cells . This gene set accurately predicted ER status ( Figure S15A ) in the Reyal breast cancer series [28] . The Confusion Matrix ( Figure S15B ) shows that the direct transcriptional targets of ELF5 accurately predicted intrinsic subtype , with nearly 100% of the luminal/basal distinctions correctly identified . Clustering of the NKI-295 set [29] , using the direct transcriptional targets of ELF5 , distinguished the intrinsic subtypes and produced a clear separation of tumor characteristics such as poor prognosis , early metastasis , early death , recurrence , survival , grade , mutation status , and marker expression , such as ER and PR ( Figure S15C ) . We assessed the ability of ELF5 expression to directly alter molecular subtype using two methods developed for this purpose , GSEA [30] and expression signature analysis [15] ( Figure 7 ) . Figure 7A shows a cytoscape network of gene sets distinguishing molecular subtype , which combines data from forced expression of ELF5 in MCF7 luminal breast cancer cells ( node center ) with data from knockdown of ELF5 in HCC1937 basal breast cancer cells ( outer node ring ) . This is a sub network of the complete cytoscape network ( Figure S16 ) and the T47D-HCC1937 sub network ( Figure S17 ) is almost identical . The gene sets clustered into four groups distinguishing luminal subtype , basal subtype , estrogen responsiveness , and the mesenchymal phenotype . ELF5 suppressed the mesenchymal phenotype in both luminal and basal cells , representing a subtype-independent action . In luminal cells forced ELF5 expression suppressed the luminal subtype and estrogen-responsive phenotype . In basal cells knockdown of ELF5 expression suppressed the basal subtype , illustrating subtype-specific actions of ELF5 . Figure 7B shows the expression signature analysis . In HCC1937 cells knockdown of ELF5 produced a very significant shift in molecular subtype away from the basal subtype toward the claudin-low and normal-like subtypes , consistent with the enrichment of the mesenchymal phenotype observed by GSEA and the suppression of patterns of basal gene expression . In both luminal cell lines a shift away from the luminal subtype was observed ( Figure 7C and 7D ) , consistent with the GSEA results . In MCF7 the shift was toward the basal and Her2+ subtypes and in T47D toward the normal-like and claudin-low subtypes . Expression studies and ChIP-Seq ( Figures 2 , 6E , and 7 ) showed that ELF5 transcriptionally regulated a number of genes involved in resistance to antiestrogens . We examined ELF5 expression in Tamoxifen ( TAMR ) - [31] or Faslodex ( FASR ) - [32] resistant cells , derived from MCF7 cells in Cardiff ( MCF7C ) . Greatly elevated levels of ELF5 mRNA were observed ( Figure 8A ) compared to their parental MCF7C cells , accompanied by loss of expression of key estrogen response genes . The 164-gene ELF5 transcriptional signature used to classify subtype in Figure 6 showed a response in TAMR cells ( 22 genes significantly suppressed , 24 significantly induced ) and FASR cells ( 34 genes significantly suppressed , 46 significantly induced ) . qPCR confirmed the elevation of ELF5 mRNA in TAMR and FASR cells compared to the parental MCF7 ( MCF7C ) and MCF7 from the Garvan Institute ( MCF7G ) used elsewhere in this study ( Figure 8B ) . When we intersected the genes from the antiestrogen sets enriched in the expression data in response to forced ELF5 expression ( Figure 2A ) with ELF5 ChIP targets , and asked using Oncomine what drug treatments produced similar profiles , we found a predominance of signatures resembling those resulting from inhibition of EGFR ( a key pathway driving Tamoxifen resistance in TAMRs [31] ) among overexpressed genes , and signatures indicative of the IGFR1 pathway and other kinases , or mitosis-disrupting agents , among under expressed genes ( Figure 8C ) . Both these pathways have been implicated in the development of resistance to antiestrogens . Treatment with estrogen greatly reduced ELF5 expression in MCF7C cells and this effect was blunted in the TAMR cells ( Figure 8D ) . Knockdown of ELF5 in TAMR cells completely stopped cell accumulation while in the parental MCF7C little effect on the rate of increase in cell number was seen ( Figure 8E ) . ELF5 IHC on TAMR cell pellets confirmed the knockdown . Measurements of S-phase showed that 25% of TAMR cells and 42% of MCF7C cells were in S-phase of the cell cycle during log-phase growth , consistent with the known characteristics of these lines . Knockdown of ELF5 reduced TAMR S-phase by 28% , and MCF7C S-phase by 12% ( Figure 8F ) , consistent with the observed effects on cell number . These observations demonstrate that elevation of ELF5 expression and greatly increased reliance upon it for cell proliferation is a key event in the acquisition of Tamoxifen insensitivity . Taken together , the results in this study show that ELF5 is involved in the proliferation of breast cancer cells in culture , that ELF5 suppressed the estrogen-responsive phenotype in luminal breast cancer cells , and induced aspects of the basal phenotype in basal breast cancer cells . In both subtypes ELF5 suppressed the mesenchymal phenotype . ELF5 specified patterns of gene expression that distinguished the breast cancer subtypes . Significantly for clinical management of breast cancer , elevation of ELF5 is a mechanism by which MCF7 cells can become insensitive to antiestrogen treatment .
In this report we show that ELF5 exerts wide transcriptional effects with functional outcomes on cell proliferation , adhesion , the molecular determinants of breast cancer subtype and phenotype , and acquired resistance to Tamoxifen . These outcomes are aspects of a general specification of an estrogen-insensitive cell fate exerted through modulation of ER , FOXA1 , and other transcriptional regulators in luminal cells , and the induction of basal characteristics in basal cells . Two key factors in determining the luminal phenotype are FOXA1 and ER . Recent findings show that ER-chromatin binding and the resulting transcriptional response to estrogens are dependent on FOXA1 expression and its action as a pioneer factor for chromatin-ER binding [3] . We show that forced expression of ELF5 in the luminal context directly represses FOXA1 expression and transcriptional activity . We also show that ER expression falls , as does the expression of many estrogen-responsive genes and ER-driven transcription . This mechanism allows ELF5 to suppress key aspects of the luminal phenotype , demonstrated by GSEA and by expression signature analysis . The resulting loss of proliferation is likely to result from multiple mechanisms . Although the proliferation of MCF7 and T47D cells is stimulated by estrogen-driven signaling and transcription , the loss of ER signaling was not the sole cause of proliferative arrest as forced ER re-expression did not effect a rescue ( Figure 6C ) . Rather , ELF5 may act directly to regulate genes controlling cell proliferation ( Figure S14 ) . In addition the loss of beta1-integrin was observed . Beta1-integrin acts in mammary cells via FAK and src to induce p21 and cell cycle arrest [33] , a mechanism that is also apparent in our data ( Figures 5D and S13C ) . There are additional large changes in the expression of many other key signaling molecules ( Figures 2 and S4 ) that may also act to suppress proliferation , including EGFR and IGFR signaling . Finally the changes in metabolic activity , including protein and RNA synthesis and oxidative phosphorylation are also likely to impinge on cell proliferation . Loss of ELF5 expression in the basal subtype HCC1937 cells resulted in reduced cell proliferation , loss of basal patterns of gene expression , and a shift toward the mesenchymal phenotype , demonstrated by the GSEA results and the expression signature analysis . These results show that ELF5 specifies key characteristics of the basal phenotype , but also prevents the expression of the mesenchymal phenotype , as it does in the luminal context . Thus we can discern both subtype-dependent and -independent effects of ELF5 . The subtype-dependent effects are a likely product of the differentiation state of the cell and the fate decisions made during differentiation produced by interactions of the ELF5 regulatory transcriptional network with other transcriptional regulatory networks present in the cell , while the independent effects are likely to result from direct transcriptional actions that lack these interactions and are thus subtype independent . We propose that the effects of ELF5 in the breast cancer cell lines represent a carry over of the normal developmental role of ELF5 into breast cancer ( Figure 8G ) . The primary developmental target for ELF5 is the mammary progenitor cell population ( P ) , produced from the stem cell population ( S ) , and which exhibits aspects of the two cell lineages that it produces ( drawn as P cell overlaps ) . Under the dominant influence of ELF5 a progenitor cell differentiates to become an ER− cell , and with further differentiation and hormonal stimulation ultimately produces a mature ( M ) alveolar cell capable of large-scale milk synthesis . By this process ELF5 establishes the secretory cell lineage [12] . It is likely that under a dominant estrogen influence the same progenitor cell differentiates to become an ER+ cell with different functions , such as regulation of the stem and progenitor hierarchy by paracrine influence . Recent findings support this mechanism [30] . It is likely that ELF5 and FOXA1 provide the key to the decision made by the progenitor cell . We hypothesize that the outcome of competing estrogen and ELF5 actions on a precancerous instance of the progenitor cell may play a significant role in determining the subtype of breast cancer that results . Additional events may occur subsequent to this decision that alter ELF5 expression and these may be involved in aspects of tumor progression , such as the acquisition of insensitivity to antiestrogens when ELF5 expression increases in the context of luminal breast cancer , or the acquisition of the mesenchymal phenotype when ELF5 expression is lost in basal breast cancer . Some tumors , such as the claudin low subtype , may be innately mesenchymal , as a result of the oncogenic transformation of late stem or early progenitor cells that do not yet express ELF5 or FOXA1 and ER . ELF5 may act to specify epithelial characteristics during the normal differentiation of the stem cell to become a progenitor cell . In this context forced ectopic expression of ELF5 may reduce the mesenchymal nature of the claudin low subtype . We have observed that progestin-induced inhibition of T47D cell proliferation is accompanied by an increase in ELF5 expression , and that this in turn acts to oppose the inhibitory action of progestins on cell cycle regulation [34] . A similar effect may protect some cells from complete growth inhibition by Tamoxifen , and prime them for later ELF5-driven escape of antiestrogen therapy . Further increases in ELF5 expression provide both an alternate source of proliferative signals and further suppression of sensitivity to ER-mediated signals , producing a mechanism allowing TAMR cells to escape TAM-induced growth inhibition . In this scenario the ELF5 ChIP target c-MYC may provide the proliferative drive . These experiments shed new light on the process of acquired resistance to antiestrogens , implicating ELF5 as a potential therapeutic target in antiestrogen-resistant disease and providing a potential marker predicting the failure of antiestrogen therapy . Overall we show that the transcriptional activity of ELF5 suppresses estrogen action in luminal breast cancer , enhances expression of the basal phenotype , specifies patterns of gene expression distinguishing molecular subtype , and exerts a proliferative influence that can be modified to allow luminal breast cancer to become resistant to antiestrogen treatment .
Mice were maintained following the Australian code of practice for the care and use of animals for scientific purposes observed by The Garvan Institute of Medical Research/St . Vincent's Hospital Animal Ethics Committee ( AEC ) . ESE2B was tagged at the 3′ end with V5 and incorporated into the pHUSH-ProEX vector [35] used as a retrovirus . Transient transfection used FuGENE ( Roche ) . Puromycin was used at 1 µg/ml for MCF7-EcoR and 2 µg/ml for T47D-EcoR , DOX at 0 . 1 µg/ml changed daily , R5020 at 10 nM . Colonies were visualized with the Diff Quick Stain Kit ( Lab Aids ) or crystal violet . Colony number and size measured with Image J 1 . 41o ( Wayne Rasband , US National Institutes of Health ) , excluding cells <0 . 1 mm . Protein lysates ( 40 µg per lane ) were prepared in NuPAGE LDS Sample Buffer and Sample Reducing Agent and separated on NuPAGE Bis-Tris acrylamide gels in MOPS buffer or Tris-Acetate gels run in Tris-Acetate SDS buffer , transferred to polyvinylidene difluoride membranes ( BioRad ) , blocked with 1% skim milk powder , 50 nM Na3PO4 , 50 mM NaCl , and 0 . 1% Tween 20 for 1 h , primary antibody for 2 h to overnight , and a horseradish peroxidase ( HRP ) -linked secondary antibody for 1 h , with four washes of 50 nM Na3PO4 , 50 mM NaCl , and 0 . 1% Tween 20 . Detection by enhanced chemiluminescence ( Perkin-Elmer ) on Fuji Medical X-ray Film ( Fujifilm ) . Primary antibodies used were anti-β-actin ( AC-15 , Sigma ) , anti-cyclin B1 ( GNS-11 , BD ) , anti-cyclin D1 ( DCS6 , Novacastra ) , anti-cyclin E ( HE12 , sc-247 , Santa Cruz ) , anti-ELF5/ESE2 ( N20 , sc-9645 , Santa Cruz ) , anti-ERα ( HC20 , sc-543 , Santa Cruz ) , anti-FAK ( 3285 , Cell Signalling Technologies ) , anti-ILK ( 3/ILK , BD ) , anti-integrin β1 ( 18 , BD ) , anti-p21 ( 70 , BD ) , anti-p27 ( C19 , sc-528 , Santa Cruz ) , anti-p107 ( C19 , sc-318 , Santa Cruz ) , anti-pFAK ( pY397 , BD ) , anti-pRb ( 554136 , BD ) , anti SRC ( Calbiochem 327 ) , anti pSRC ( Cell Signalling 2101 ) , and anti-V5 ( R960-25 , Invitrogen ) . Secondary antibodies were HRP-donkey anti-goat ( Santa Cruz ) , HRP-donkey anti-rabbit ( Amersham Biosciences ) , and HRP-sheep anti-mouse ( Amersham Biosciences ) . Reporter plasmids , consensus ERE were a kind gift from Malcolm Parker ( Imperial Cancer Research Fund , London ) ; FOXA1 responsive UGT2B17/-155ApGL3 a kind gift from Peter Mackenzie ( Flinders University , Australia ) [36]; and pRL-TK ( Promega ) , β-galactosidase a kind gift from Gerald Clesham , University of Cambridge , Cambridge , UK . Solubilization was in Passive Lysis Buffer ( Promega ) and measured with Dual Luciferase Reporter Assay System ( Promega ) and Galacto-Light reagents ( Applied Biosystems ) . Monolayers were detached with 0 . 25% trypsin , counted , and re-plated at equal density . Unattached cells were gently removed in PBS prior to counting with a haemocytometer . Asychronous cells were pulsed with 10 µM BrdU ( Sigma ) for 2 h ( MCF7 or 20 min ( T47D ) prior to harvesting . Where indicated cells were synchronised with 1 mM hydroxyurea treatment for 40 h . Cells were harvested via trypsinisation , and fixed in 70% ethanol for 24 h , stained with 10 µg/ml propidium iodide ( Sigma ) for 2–5 h , and incubated with 0 . 5 mg/ml RNase A ( Sigma ) . Flow cytometry was performed using FACS Calibur or FACS Canto cytometers ( BD Biosciences ) , and data analysis performed with FlowJo software ( Tree Star Inc . ) . Total RNA was extracted with the RNeasy Minikit ( Qiagen ) and DNase-treated with the DNase kit ( Qiagen ) . RNA quality was assessed using a RNA Nano LabChip and Agilent Bioanalyzer 2100 . Probe labeling and hybridization to Affymetrix Human Gene 1 . 0 ST Gene Arrays was done at the Ramaciotti Centre for Gene Function Analysis at the University of New South Wales . Microarrays were normalised using RMA via the NormalizeAffymetrixST GenePattern module http://pwbc . garvan . unsw . edu . au/gp . Differentially expressed genes were detected using Limma , using positive false discovery rate ( FDR ) multiple hypothesis test correction . GSEA ( version 2 . 04 ) used 1 , 000 permutations , in pre-ranked mode , using the t-statistic from Limma to rank each gene using gene sets from MSigDB version 3 . 0 . Data are available from GEO with accession number GSE30407 . Cells were fixed in 1% formaldehyde , at 37°C for 10 min , washed 2× with cold PBS , scraped into 600 µl PBS with protease inhibitors ( P8340 , Sigma ) , spun 2 min at 6 , 000 g , washed as before , and snap frozen in liquid nitrogen . ChIP-Seq as previously described [37] using a 50%–50% mixture of V5-specific antibody and the Santa Cruz N20 anti ELF5 antibody . DNA was processed for Illumina sequencing using 36-bp reads on a GAIIx . Sequences were aligned against NCBI Build 36 . 3 of the human genome using MAQ ( http://maq . sourceforge . net/ ) with default parameters . The aligned reads were converted to BED format using a custom script . ChIP-qPCR used the ABI Prism 7900HT Sequence Detection System . Balb/C Nude mice ( Jackson Lab ) were used as xenograft hosts . Potential as classifiers was investigated using the diagonal linear discriminant analysis ( DLDA ) or Naïve Bayes classifier , 100 iterations of 10-fold cross-validation ( CV ) and the misclassification rate recorded in each instance . Boxplots of ER misclassification rate were achieved for each of the 1 , 000 ( 100 iterations of 10-fold CV ) classifiers built to predict ER status . The confusion matrix shows as percentages the relationship between true intrinsic subtype classification , as defined by [1] and [38] and predicted by the Naïve Bayes classifier . Expression signature analysis [15] and GSEA [30] to examine changes in subtype was carried out as described . | The molecular subtypes of breast cancer are distinguished by their intrinsic patterns of gene expression and can be used to group patients with different prognoses and treatment options . Although molecular subtyping tests are currently under evaluation , some of them are already in use to better tailor therapy for patients; however , the molecular events that are responsible for these different patterns of gene expression in breast cancer are largely undefined . The elucidation of their mechanistic basis would improve our understanding of the disease process and enhance the chances of developing better predictive and prognostic markers , new therapies , and interventions to overcome resistance to existing therapies . Here , we show that the transcription factor ELF5 is responsible for much of the patterning of gene expression that distinguishes the breast cancer subtypes . Additionally , our data suggest that ELF5 may also be involved in the development of resistance to therapies designed to stop estrogen stimulation of breast cancer . These effects of ELF5 appear to represent a partial carryover into breast cancer of its normal role in the mammary gland , where it is responsible for the development of milk-producing structures during pregnancy . | [
"Abstract",
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"Discussion",
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"Methods"
] | [
"oncology",
"medicine",
"developmental",
"biology",
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] | 2012 | ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer |
Pathological aggregates of phosphorylated TDP-43 characterize amyotrophic lateral sclerosis ( ALS ) and frontotemporal lobar degeneration ( FTLD-TDP ) , two devastating groups of neurodegenerative disease . Kinase hyperactivity may be a consistent feature of ALS and FTLD-TDP , as phosphorylated TDP-43 is not observed in the absence of neurodegeneration . By examining changes in TDP-43 phosphorylation state , we have identified kinases controlling TDP-43 phosphorylation in a C . elegans model of ALS . In this kinome-wide survey , we identified homologs of the tau tubulin kinases 1 and 2 ( TTBK1 and TTBK2 ) , which were also identified in a prior screen for kinase modifiers of TDP-43 behavioral phenotypes . Using refined methodology , we demonstrate TTBK1 and TTBK2 directly phosphorylate TDP-43 in vitro and promote TDP-43 phosphorylation in mammalian cultured cells . TTBK1/2 overexpression drives phosphorylation and relocalization of TDP-43 from the nucleus to cytoplasmic inclusions reminiscent of neuropathologic changes in disease states . Furthermore , protein levels of TTBK1 and TTBK2 are increased in frontal cortex of FTLD-TDP patients , and TTBK1 and TTBK2 co-localize with TDP-43 inclusions in ALS spinal cord . These kinases may represent attractive targets for therapeutic intervention for TDP-43 proteinopathies such as ALS and FTLD-TDP .
Ubiquitinated , hyperphosphorylated inclusions of the protein TDP-43 characterize disease-affected neurons in patients with amyotrophic lateral sclerosis ( ALS ) and frontotemporal lobar dementia ( FTLD-TDP ) [1] , [2] . Mutations in the human gene coding for TDP-43 , TARDBP , were found to cause ALS in a subset of affected families , supporting a causal role for TDP-43 in disease initiation [3]–[7] . In addition to being the hallmark lesions in ALS and FTLD-TDP , inclusions containing TDP-43 are varyingly present in some other neurodegenerative diseases , including Alzheimer's disease ( AD ) , Parkinson's disease , dementia with Lewy bodies , Huntington's disease , and chronic traumatic encephalopathy ( CTE ) [8]–[12] , where the severity of TDP-43 pathologic change is associated with the rate of cognitive decline in affected patients [13] . Many model systems including C . elegans , Drosophila , zebrafish , mice , and rats have demonstrated neurotoxicity resulting from mutant TDP-43 [14]–[19] . Therefore , TDP-43 pathologic change is not merely a hallmark of disease , but TDP-43 dysfunction can cause neurodegeneration . TDP-43 undergoes a number of pathological modifications in disease-affected neurons including ubiquitination , phosphorylation , and proteolytic processing . These modifications may promote aggregation and the formation of detergent-insoluble inclusions . The precise molecular cause underlying neurotoxicity in most TDP-43 proteinopathies remains unclear , although the toxicity of mutant TDP-43 expressed in multiple model systems indicates it may be acting through a gain-of-function mechanism via aberrant interactions with proteins and/or nucleic acids [20] . Phosphorylation is a robust and consistent hallmark of pathological TDP-43 , and detection of phosphorylation at tandem serines 409 and 410 characterizes virtually all TDP-43 proteinopathy cases [21] , [22] . In order to investigate the causes driving pathological TDP-43 phosphorylation , we have developed a C . elegans model of TDP-43 proteinopathy exhibiting TDP-43 phosphorylation dependent neurodegeneration and neurotoxicity; in C . elegans , phosphorylation of TDP-43 at serines 409 and 410 suffices to promote TDP-43 mediated neurotoxicity [14] . Further , we have used the model to previously identify the kinase CDC7 as a direct modulator of TDP-43 motor phenotypes [23] . This work also showed multiple kinases regulate TDP-43 phosphorylation in C . elegans , because detectable phosphorylated TDP-43 remains in the absence of CDC7 . Inhibition of the kinases CDC7 or CK1 has also been shown to reduce but not eliminate TDP-43 phosphorylation in cultured cells [23] , [24] . Here we utilize the direct detection of changes in TDP-43 phosphorylation by immunoblot analysis of TDP-43 phosphorylation state to discover additional TDP-43 kinases in C . elegans . We have identified homologs of the tau tubulin kinases TTBK1 and TTBK2 and characterized their function as regulators of TDP-43 phosphorylation . TTBK1/2 may be attractive drug targets for therapeutic interventions in TDP-43 proteinopathies such as FTLD-TDP and ALS .
To identify TDP-43 kinases , we undertook a comprehensive survey utilizing kinase-targeting RNAi coupled with direct immunoblot detection of changes in TDP-43 phosphorylation in C . elegans . We have assembled an RNAi library targeting 451 predicted kinase genes in C . elegans ( 95% coverage of the predicted kinases found in the C . elegans genome , Table S1 ) . This library has been previously employed to identify kinase modifiers of TDP-43 dependent behavioral phenotypes , and identified CDC7 as a direct TDP-43 kinase responsible for promoting TDP-43 neurotoxicity [23] . However , CDC7 is not solely responsible for the phosphorylation observed in our C . elegans model as detectable phosphorylation at S409/410 is still observed in a cdc-7 ( −/− ) null mutant background . Thus other kinases play conserved roles phosphorylating TDP-43 , and previous behavior-based screening may have failed to uncover kinases with multiple roles in vivo , or kinases whose loss of function could adversely impact motor function or viability independent of TDP-43 . To identify additional TDP-43 kinases , a direct biochemical assay of TDP-43 phosphorylation in TDP-43 transgenic C . elegans was used to screen for alterations in pS409/410 TDP-43 phosphorylation . Populations of transgenic C . elegans expressing ALS-mutant M337V TDP-43 were grown on bacteria producing double stranded RNA targeting each kinase , then harvested and tested by immunoblot for changes in TDP-43 phosphorylation ( S1 Figure ) . Transgenic C . elegans expressing ALS mutant TDP-43 exhibit post-translational modification of TDP-43 including prominent phosphorylation [14] in addition to altered proteolytic processing and ubiquitination . Candidate TDP-43 modifying kinases were selected whose knockdown by RNAi robustly reduced the observed TDP-43 phosphorylation relative to control treated animals . Apparent hits were retested by RNAi and immunoblot to confirm decreased TDP-43 phosphorylation , and the identity of positive RNAi clones was confirmed by direct DNA sequencing . Candidate kinases with human homologs acting on serine and/or threonine residues ( S/T ) were selected for further analysis . A total of 7 candidate S/T kinases were identified that consistently decreased TDP-43 S409/410 phosphorylation following RNAi treatment ( Table 1 ) . Interestingly , two of these kinases , cdc-7 and mlk-1 , were identified previously in behavior-based screening for TDP-43 kinases [23] . Behavior-based screening also identified three additional homologs of the mammalian tau tubulin kinases TTBK1 and TTBK2 , in the CK1 group . The CK1 group of kinases has greatly expanded in C . elegans , from 12 members in humans to 86 members in C . elegans , including 32 TTBK and TTBKL ( TTBK-like ) family members [25] . The dramatic expansion of the CK1 family of kinases in C . elegans suggests a diversification of functional roles for the TTBK1/2 like kinases in the nematode . RNAi can inactivate multiple genes simultaneously depending on their sequence similarity , potentially confounding the identification of any single gene responsible for TDP-43 phosphorylation . To unambiguously determine the effects of single kinase gene loss of function on TDP-43 phosphorylation , we generated TDP-43 transgenic animals with viable deletion mutants eliminating the kinase active domain of each candidate gene of interest ( Table 1 ) . Each of these kinase mutants was tested for changes in the amount of phosphorylated TDP-43 by immunoblot . Three of the kinase loss of function mutations tested , cdc-7 ( −/− ) , H05L14 . 1 ( −/− ) , and dkf-2 ( −/− ) , dramatically reduce TDP-43 phosphorylation with only moderate or no changes in total levels of TDP-43 , consistent with the results from the initial RNAi screen ( Fig . 1A–C and S2 Figure ) . We observed a slight decrease in levels of a shorter 37 kDa isoform of TDP-43 ( Fig . 1A ) , but the appearance of higher or lower molecular weight species , including multimers , post-translationally modified protein species , or translational variants , appears relatively unchanged ( see S2 Figure for the full α-TDP-43 immunoblot ) , and after quantitation , only dkf-2 ( −/− ) exhibited significant differences in total TDP-43 levels . cdc-7 ( −/− ) has been previously characterized as a TDP-43 kinase [23] , but we are including analysis of its mutant phenotypes in Fig . 1 for comparison with H05L14 . 1 ( −/− ) and dkf-2 ( −/− ) . Changes in TDP-43 transgenic animal locomotion can be used as a sensitive measure of TDP-43 toxicity to motor neurons . In fact , we observe that the cdc-7 ( −/− ) ;TDP-43 , H05L14 . 1 ( −/− ) ;TDP-43 or dkf-2 ( −/− ) ;TDP-43 had a more natural and vigorous movement profile relative to the TDP-43 transgene alone . We assessed motor function by measuring the average dispersal velocity of the animals , and found significant improvements compared to TDP-43 ( Fig . 1D ) . These results are consistent with the hypothesis that phosphorylation at S409/410 promotes TDP-43 toxicity , and decreased phosphorylation of TDP-43 will ameliorate the deleterious motor effects resulting from pathological TDP-43 . To identify human homologs of H05L14 . 1 and dkf-2 , we performed an unbiased search for related proteins from eukaryotes within the phylum chordata , including all vertebrate animals . This search employed a basic local alignment search tool ( BLAST ) [26] , followed by automated construction of a phylogenetic tree with the top 50 hits from the search ( S3A Figure ) [27] . H05L14 . 1 is related to the human kinase TTBK1 , although it is one of many members from an expanded family in C . elegans and other ecdysozoa . The H05L14 . 1 kinase domain has 40% sequence identity to the highly homologous tau tubulin kinases TTBK1 and TTBK2 at the amino acid level ( S3C , D Figure ) [28] . Variants in the gene coding for TTBK1 are associated with Alzheimer's disease , while mutation in TTBK2 causes spinocerebellar ataxia 11 ( SCA11 ) , both of which are characterized by pathologic alterations of tau [26]–[28] . dkf-2 is related to the conserved protein kinase D family , and is the major representative of the family in C . elegans ( S3B Figure ) . The dkf-2 kinase domain has greater than 70% sequence identity to protein kinase D2 and D3 ( PRKD2 and PRKD3 ) ( S3E , F Figure ) . PRKD2/3 may be involved in cell proliferation , and dkf-2 has been shown to regulate C . elegans innate immunity ( Table 1 ) [29] , [30] . Interestingly , our previous search for TDP-43 kinases identified another C . elegans homolog of TTBK1/2 [23] . This kinase , C55B7 . 10 also decreased TDP-43 phosphorylation and improved locomotion in C . elegans , although we were unable to determine a direct relationship between human TTBK1/2 and TDP-43 at that time . However , since our last study , we learned TTBK1/2 require millimolar levels of bivalent metal ions Mg2+ or Mn2+ in the reaction buffer for effective kinase activation [31] . We changed our in vitro kinase assay buffer composition , optimizing the reaction conditions for TTBK1/2 kinase assays . The quality of purified TTBK1/2 kinases also affects their activity in vitro . We compared purified TTBK1/2 from different commercial sources side by side in an in vitro kinase assay against a known target , tau , and found major differences in kinase activity ( S4A Figure ) . Our previous characterization of TTBK1/2 as potential TDP-43 kinases used commercially available purified kinase with low activity against tau . Switching to a more active kinase preparation and modifying the buffer composition in the assay allowed a re-assessment of these potential TDP-43 kinases in vitro . TDP-43 kinases may act directly by phosphorylating TDP-43 S409/410 or may act indirectly by regulating the activity of other direct TDP-43 kinases . The amino acid sequence in the C-terminus of TDP-43 near S409/410 is consistent with the known CK1 family kinase consensus sequence S/TpXXS/T [32] . The PRKD kinase consensus sequence LXRXMSXXSFX [33] , does not conform well with the sequence of human TDP-43 . To empirically determine whether human TTBK1/2 or PRKD2/3 are direct TDP-43 kinases , we tested the ability of purified active kinase enzymes to phosphorylate TDP-43 at S409/410 and S403/404 in vitro ( Fig . 1E , F , S4B Figure ) . We found that TTBK1 and 2 can directly phosphorylate both wild-type ( WT ) and familial ALS mutant TDP-43 ( M337V TDP-43 ) under optimized reaction conditions that include magnesium . These conditions support robust phosphorylation of human tau protein , a known substrate of TTBK1/2 ( S4A Figure , [31] ) . Although our preparation of PRKD2 kinase was enzymatically active against a known phosphorylation substrate , histone H1 [34] ( S4C Figure ) , PRKD2 was unable to phosphorylate TDP-43 under any conditions tested , indicating its effect on TDP-43 phosphorylation may be indirect through the activation of other direct TDP-43 kinases or regulation of other downstream members of a TDP-43 regulatory pathway . If the kinases CDC7 , TTBK1/2 , or PRKD2/3 are in a common regulatory pathway , they may directly phosphorylate one another . Using an in vitro kinase assay with purified human kinases , we observed robust auto-phosphorylation by TTBK1 and modest auto-phosphorylation by TTBK2 and PRKD2 , consistent with known activities of these kinases [28] , [31] , [34] . We also tested pairwise combinations of these kinases to determine any relative increases in phosphorylation . However , we did not see any significant increases in phosphorylation on these kinases ( S4D Figure ) . Therefore , any indirect regulation of TDP-43 phosphorylation by PRKD2 may be through other unknown members of one or several regulatory pathways controlling TDP-43 phosphorylation . TTBK1/2 kinase hyperactivity may contribute to the pathological phosphorylated TDP-43 observed in both FTLD-TDP and ALS . To test whether increased cellular levels of TTBK1/2 activity suffice to drive TDP-43 phosphorylation , we transfected full-length TTBK1 and TTBK2 cDNAs into HEK293 cells . HEK293 cells have some neuronal characteristics and may be derived from a subpopulation of neuronal precursor cells in the embryonic kidney [35] . This cell line is especially useful for biochemical assays requiring high efficiency transfection rates . In the absence of other cellular stresses , we observed robust induction of TDP-43 phosphorylation by immunoblot following transfection with both TTBK1 and TTBK2 ( Fig . 2A–C ) . Likewise , we utilized SH-SY5Y cells , a human neuroblastoma-derived cell line , to determine the location of phosphorylated TDP-43 produced by TTBK2 transfection . The phospho-TDP-43 produced by TTBK2 overexpression is localized throughout the cytoplasm overlapping with TTBK2 ( Fig . 2D , E ) . Further , TTBK2 and phospho-TDP-43 appear concentrated in apparent aggregates , producing a pattern of TDP-43 and TTBK1/2 expression reminiscent of the neuronal cytoplasmic inclusion pathology observed in FTLD-TDP and ALS . SH-SY5Y cells are relatively recalcitrant to transfection; we observed less than 5% transfection efficiency with TTBK2 . However , all the cells with strong TTBK2::GFP expression also had inclusions of phosphorylated TDP-43 . We observed a similar pattern of TTBK2 transfection overlapping with large phospho-TDP-43 positive aggregates in HEK293 cells ( S5 Figure ) . Decreasing TTBK1/2 kinase activity may prevent TDP-43 phosphorylation . To test this hypothesis , we employed small interfering RNAs ( siRNAs ) to decrease levels of TTBK1 gene expression in mammalian cultured cells . We have modeled pathological TDP-43 phosphorylation in the mouse motor neuron-like NSC-34 cell line using the chemical trigger ethacrynic acid ( EA ) . EA acts by depleting cytosolic and mitochondrial glutathione , resulting in robust TDP-43 phosphorylation [36] , [37] . EA is a specific trigger of TDP-43 phosphorylation , because a variety of other cell stressors fail to induce phospho-TDP-43 ( S6A Figure ) . NSC-34 cells were transfected with siRNAs targeting TTBK1 , averaging 76% reduction in gene expression and 46% reduction in protein levels ( S6B–D Figure ) . These cells were then treated with EA to induce TDP-43 phosphorylation . We observed a robust decrease in TDP-43 phosphorylation following treatment with TTBK1 siRNA ( Fig . 3 ) . We also tested siRNAs targeting TTBK2 , but were unable to achieve significant reduction in gene expression . Both TTBK1 and TTBK2 are expressed in the brain , although TTBK2 is expressed in other tissues as well [31] , . If TTBK1 or TTBK2 promote TDP-43 phosphorylation in patients with ALS or FTLD , there may be alterations in kinase abundance or localization , and there should be co-occurrence of the kinase with pathological TDP-43 aggregates . Immunohistochemistry for TTBK1 , TTBK2 and phospho-TDP-43 was performed on frontal cortex sections from 6 FTLD-TDP cases , 6 ALS cases and 6 normal control cases to determine if there was overlap in the expression of these kinases and their purported target . Additionally , ALS spinal cord and hippocampus were also assessed . One FTLD case carried a progranulin mutation , the remaining 5 are of unknown etiology . FTLD cases were scored according to the harmonized FTLD-TDP classification of pathology [40] . Three of these cases were classified as Type A and three were Type B . All ALS cases were sporadic incidences of disease , and were negative for mutations in TDP-43 , SOD1 , FUS , and C9ORF72 . TTBK1/2 antibody specificity was confirmed against purified substrate , and by antibody competition on fixed tissue ( S7 Figure ) . Fig . 4A–D demonstrates that TTBK1 and TTBK2 immunoreactivity is present in a subset of pyramidal neurons in the frontal cortex of both normal and FTLD cases . Immunoreactivity is more prominent in cortical layers II–VI compared to cortical layer I , where immunoreactivity is relatively sparse , and the cellular localization appears both nuclear and cytoplasmic ( Fig . 4 , insets ) . Furthermore , the distribution of TTBK1 and TTBK2 immunoreactivity appears to be more widespread in FTLD cases compared to normal controls . Optical density measurements relative to the proportional area for TTBK1 and TTBK2 immunostaining in frontal cortex confirmed a statistically significant increase in both TTBK1 ( Fig . 4E ) and TTBK2 ( Fig . 4F ) immunoreactive distribution in disease-affected subjects . This increase was observed in all FTLD cases surveyed relative to controls . Importantly , the distribution of TTBK1 and TTBK2 in the frontal cortex is consistent with the distribution of phosphorylated TDP-43 pathology in FTLD cases , where aggregates are sparse in cortical layer I , and more abundant in cortical layers II–VI , depending on the FTLD classification ( Fig . 4G ) . To further demonstrate this relationship , we performed double label immunohistochemistry to determine if the tau tubulin kinases and phosphorylated TDP-43 co-expressed within the same neurons . Most neurons immunoreactive for phospho-TDP-43 were also immunoreactive for TTBK1 and TTBK2 ( Fig . 4H , I ) . Of the six ALS cases examined , only two had phospho-TDP-43 aggregates in the frontal cortex and hippocampus , while all six demonstrated phospho-TDP-43 aggregates within spinal cord . ALS spinal cord motor neurons immunoreactive for phospho-TDP-43 pathology also co-labeled with TTBK1 and TTBK2 ( Fig . 5A , B ) . Of the two ALS cases with pathologic changes in brain , a subset of neurons in the hippocampus and frontal cortex containing phospho-TDP-43 aggregates also co-expressed TTBK1 and TTBK2 , while other neurons appeared to be immunoreactive for phospho-TDP-43 alone ( Fig . 5 C–H ) . To test whether TTBK1/2 co-localize with phosphorylated TDP-43 , we performed double-label immunofluorescence on ALS spinal cord sections ( Fig . 6 and S8 Figure ) . In general , more neurons were immunofluorescent for TTBK1/2 than for phosphorylated TDP-43 . Similar to our double label immunohistochemical data , neurons immunofluorescent for phosphorylated TDP-43 usually co-localized with TTBK1/2 , although some neurons labeled with phosphorylated TDP-43 alone . Taken together Figs . 4 , 5 and 6 repeatedly demonstrate an overlapping expression pattern for TTBK1/2 and pS409/410 TDP-43 inclusions in ALS and FTLD-TDP consistent with TTBK1/2 participation in the genesis of TDP-43 lesions .
Tandem phosphorylation at TDP-43 serines 409 and 410 ( pS409/410 ) is a consistent and robust feature of TDP-43 pathology in ALS and FTLD-TDP . Our previous work in TDP-43 transgenic C . elegans demonstrated a causal relationship between neurodegeneration and S409/410 phosphorylation of TDP-43 [14] , [23] . We have utilized this model as a C . elegans behavior-based screening tool to identify TDP-43 kinases [23] . However , it is possible other relevant TDP-43 kinases remain unidentified . To uncover kinases responsible for the pathological phosphorylation of TDP-43 , we have re-screened the C . elegans kinome by RNAi knockdown for modifiers of TDP-43 phosphorylation . For this survey we employed sensitive and specific S409/410 phosphorylation dependent TDP-43 antibodies [41] to directly detect changes in TDP-43 phosphorylation state following RNAi treatment . Confirmation of identified candidate kinases in C . elegans was conducted by testing deletion mutations within the kinase genes of interest . Three identified candidate kinases , cdc-7 , dkf-2 , and H05L14 . 1 , reduced TDP-43 S409/410 phosphorylation and improved TDP-43 dependent behavioral phenotypes in C . elegans . TDP-43 is a known substrate of CDC7 , as it was previously uncovered in a reverse genetic screen to identify modifiers of TDP-43 behavioral phenotypes [23] , confirming the validity of this approach . We employed standard BLAST protein sequence homology searching algorithms [42] to identify the closest mammalian homologs of our novel TDP-43 kinases dkf-2 and H05L14 . 1 . Interestingly , H05L14 . 1 was a homolog of the mammalian tau tubulin kinases TTBK1 and TTBK2 . Our previous behavior-based screen for TDP-43 kinases identified a different C . elegans homolog of TTBK1/2 as a TDP-43 kinase , although at the time we were unable to demonstrate a direct relationship between human TTBK1/2 and TDP-43 [23] . We decided to re-evaluate TTBK1/2 as we had identified both as candidate kinases in independent assays . Using optimized in vitro kinase reaction conditions , we demonstrate here that human TTBK1/2 are able to directly phosphorylate TDP-43 . We then overexpressed TTBK1/2 in cultured human cells . TTBK1/2 overexpression in the absence of other stressors promoted robust phosphorylation of endogenous TDP-43 . Furthermore , this phosphorylated TDP-43 localized to the cytoplasm in inclusion-like aggregates . We also found that reduction of TTBK1 mRNA levels attenuated TDP-43 phosphorylation in a chemically induced model of pathological phospho-TDP-43 accumulation . Finally , to explore whether TDP-43 kinase hyperactivity could underlie the etiology of TDP-43 proteinopathies , we immunostained tissue from FTLD-TDP and ALS for TTBK1/2 . We observe increased TTBK1/2 in FTLD-TDP frontal cortex , and co-localization with TDP-43 positive aggregates in FTLD frontal cortex and ALS spinal cord . One possible explanation for these data is the observed differences in TTBK1/2 expression drives neurodegeneration in TDP-43 proteinopathies . Taken together these data support a pivotal role for TTBK1/2 hyperactivity in TDP-43 proteinopathy . A number of kinases have been identified to date with the ability to phosphorylate TDP-43 in vitro and in vivo . The kinases CK1 [43] , [44] , CKII [45] , CDC7 ( [23] , this study ) , TTBK1 and TTBK2 ( this study ) may all contribute to pathological TDP-43 phosphorylation in humans; regardless they all share target sequence conservation as the CK1 kinase domain is the prototypical model for this family of kinases . CK1 family kinases may act redundantly to regulate TDP-43 phosphorylation in a common signaling pathway . Alternatively , extracellular and intracellular signals may act as a trigger to specify kinase activity from one of the available TDP-43 kinases but not the others . We have observed that in the absence of each of these known TDP-43 kinases in C . elegans , mutant TDP-43 still exhibits varying but detectable degrees of phosphorylation ( Fig . 1 and [23] ) , indicating that no one kinase accounts for all observed TDP-43 phosphorylation . Exploring the functional relationships between and regulatory networks governing the TDP-43 kinases identified to date will be important future work . TTBK1 and TTBK2 were originally purified on the basis of their kinase activity on the microtubule binding protein tau at several pathological phospho-tau epitopes known to accumulate in Alzheimer's disease [31] , [38] , [39] , [46] . Tangles composed of insoluble hyperphosphorylated tau are a pathological hallmark of Alzheimer's disease ( AD ) , as well as a number of other neurodegenerative diseases including FTLD-tau , progressive supranuclear palsy ( PSP ) , and chronic traumatic encephalopathy ( CTE ) . Interestingly , phosphorylated TDP-43 is also present in a subset of patients with primary tauopathies such as AD , PSP , and CTE [8] , [47] , [48] , and either tau or TDP-43 are the diagnostic pathologic changes in the vast majority of frontotemporal lobar degeneration cases [49] . The relationship between TDP-43 and tau neuropathologic changes remains unclear . One hypothesis is that both proteinopathy disorders share a common etiology in TTBK1/2 activation leading to either TDP-43 or tau neuropathology depending on the vulnerable cell population affected by TTBK activation . The downstream toxic mechanisms for tau and TDP-43 appear distinct; however , inappropriate TTBK1 and TTBK2 activity may constitute a shared mechanistic link in initiating both tau and TDP-43 neuropathologies . Both TTBK1 and TTBK2 have been previously implicated in neurodegenerative diseases . Single nucleotide polymorphisms ( SNPs ) in TTBK1 are associated with decreased Alzheimer's disease risk in studies of Spanish and Han Chinese populations [50] , [51] . TTBK1 has been shown to co-localize with diffuse phospho-Ser422 tau in pre-tangle Alzheimer's disease neurons [52] , and increased levels of TTBK1 have been observed in AD frontal cortex [53] and enhance the toxicity of tau in a P301L mouse model [54] . Mutations in TTBK2 have been shown to cause spinocerebellar ataxia type 11 ( SCA11 ) [55] , a progressive neurodegenerative disorder characterized by tau pathology . Mouse models heterozygous for mutant TTBK2 exhibit decreased TTBK2 kinase activity and altered TTBK2 localization , while homozygous mutant TTBK2 is embryonic lethal [56] . Our results are the first demonstration of a potential role for TTBK1 and TTBK2 in primary TDP-43 proteinopathies . Kinases regulating TDP-43 phosphorylation present an attractive target for therapeutic intervention in both ALS and FTLD-TDP . No specific small molecule inhibitors targeting TTBK1 or TTBK2 has been reported to date , despite their potential roles contributing to tauopathies by hyperphosphorylating tau . Development of brain penetrant TTBK1 and TTBK2 inhibitors may also provide a viable strategy for intervening in TDP-43 proteinopathy disorders including ALS and FTLD-TDP .
N2 ( Bristol ) was used as wild type C . elegans and maintained as previously described [57] . Strains were maintained at 16°C . Experiments involving C . elegans were performed at room temperature unless otherwise noted . CK423 ( TDP-43 M337V ) and eri-1 ( mg366 ) ;lin-15b ( n744 ) ;TDP-43 M337V transgenic strains were generated previously [14] , [23] . Kinase mutants were crossed with CK423 to generate strains CK566 cdc-7 ( tm4391 ) ;TDP-43 , CK602 H05L14 . 1 ( tm4720 ) ;TDP-43 , CK600 dkf-2 ( tm4076 ) ;TDP-43 , CK597 nsy-1 ( ok593 ) ;TDP-43 , CK613 kin-20 ( ok505 ) ;TDP-43 , CK574 mlk-1 ( ok2471 ) ;TDP-43 , CK623 F39F10 . 3 ( tm4396 ) ;TDP-43 . The list of predicted kinase genes in C . elegans was derived from the C . elegans kinome project [58] , with library construction as described [23] . Testing was done in an eri-1 ( −/− ) ;lin-15 ( −/− ) RNAi enhancing mutant background [59] . Staged embryos were plated , grown at 16°C for 8–9 days , and then a mixed population of 1st generation gravid adults with 2nd generation L2–L3 animals were harvested by washing with M9 buffer into 96 well plates and frozen at −80°C , for subsequent immunoblot analysis . Each RNAi treated population was evaluated semi-quantitatively for reduction in phospho-TDP-43 relative to control treated animals . Positives candidates were retested for effects on TDP-43 phosphorylation by independent RNAi treatment and immunoblot , and the RNAi gene target for each plasmid was confirmed by sequencing . Equivalent mixed-stage worm lysate fractions were loaded and resolved on precast 4–15% gradient SDS-PAGE gels and transferred to PVDF membrane as recommended by the manufacturer ( Bio-Rad ) . On immunoblots , human TDP-43 was detected with a commercially available monoclonal antibody ab57105 ( Abcam ) directed against human TDP-43 amino acids 1–261 . TDP-43 phosphorylated at S409/S410 was detected by a monoclonal antibody called anti phospho TDP-43 ( pS409/410 ) available from Cosmobio ( catalog # TIP-PTD-M01 ) . C . elegans β-tubulin levels were measured using monoclonal antibody E7 as a loading control as previously described [60] , [61] . TTBK1 was detected by Abcam rabbit polyclonal antibody ab103944 at 1∶1000 dilution . TTBK2 was detected by Abgent rabbit polyclonal antibody AP12162a at 1∶1000 dilution . HRP labeled goat anti-mouse IgG was the secondary antibody ( GE Healthcare ) and used at a dilution of 1∶4000 . Dilutions were: 1∶7500 for ab57105 , 1∶1000 for pS409/410 , and 1∶10000 for E7 . Immunoblots shown are representative of at least 3 independent experiments . Quantitation was performed using ImageJ image processing and analysis software . GST-TDP-43 ( WT ) and GST-TDP-43 ( M337V ) fusion proteins were purified from BL21 ( DE3 ) expression host cells as previously described [62] . Active kinase enzymes were obtained commercially via purification from SF9 cells for PRKD2 , TTBK1 and TTBK2 ( Signalchem ) . Enzyme assays were carried out in a kinase reaction buffer containing 25 mM MOPS , 12 . 25 mM glycerol-phosphate , 25 mM MgCl , 5 mM EGTA , 2 mM EDTA , 0 . 25 mM DTT and 50 µM ATP . HEK 293 cells ( ATCC ) were cultured in Dulbecco's modified Eagle medium ( DMEM ) supplemented with 10% defined fetal bovine serum ( FBS ) and penicillin ( 50 IU/ml ) –streptomycin ( 50 mg/ml ) . NSC-34 cells ( Cedarlane Labs ) and SHSY-5Y cells ( ATCC ) were cultured in DMEM/HAM's F12 ( 50/50 ) with 10% FBS and penicillin ( 50 IU/ml ) –streptomycin ( 50 mg/ml ) . Cells were seeded onto poly-D-Lysine coated ( Sigma Aldrich ) 12 mm round glass cover slips in 24-well plates . Cells were transfected with the plasmid encoding TTBK2-GFP with GenePorter 2 ( Genlantis ) using the manufacturer's protocol . Cells were fixed for imaging in 4% formaldehyde 96 hours after transfection . Cells were washed 3×5 min in PBS/Ca2+/Mg2+ , then blocked in antibody buffer ( PBS , 0 . 5% Triton X-100 , 1 mM EDTA , 0 . 1% BSA , 0 . 05% NaN2 ) +10% normal goat serum . Primary antibody was applied and incubated for 1 hour at room temperature ( Cosmo Bio; 1∶1000 ) . Cells were washed 3×5 min in PBS/Ca2+/Mg2+ , then re-blocked for 10 min . Appropriate secondary antibody was applied and incubated for 20 min at room temperature . Cells were again washed 3×5 min in PBS/Ca2+/Mg2+ , counterstained with 300 nM DAPI and mounted with ProLong Gold antifade . Microscopy was performed on a Delta Vision microscope ( Applied Precision , Inc ) using a 60× oil immersion objective , a sCMOS camera , and 2×2 binning . Image analysis was performed using softWoRx 6 . 0 Beta software . HEK 293 cells were treated with 150 µM ethacrynic acid ( EA ) for 5 hours to induce endogenous TDP-43 phosphorylation [36] . NSC-34 cells were grown in differentiation medium ( DMEM/HAM's F12 ( 50/50 ) , 1% FBS , 1% non-essential amino acids ( NEAA ) , penicillin ( 50 IU/ml ) –streptomycin ( 50 mg/ml ) ) for one day prior to treatment with 50 µM EA for 5 hours . TTBK1 siRNA construct was MMC . RNAI . N001162864 . 12 . 1 ( Integrated DNA Technologies ) . RNAi experiments were carried out as per protocol in the TriFECTa Dicer-Substrate RNAi manual ( Integrated DNA Technologies ) . Transfection of plasmids containing full-length TTBK1 ( pWO:TTBK1 ) and TTBK2 ( TTBK2 GFP pFLAP dest ) sequences [63] was performed as specified by the manufacturer using the Geneporter 2 Transfection Reagent ( Genlantis ) . RNA was purified from flash-frozen cell pellets using TRIzol Reagent ( Life Technologies ) according to the manufacturer's protocol . cDNA was made using iScript Reverse Transcription Supermix ( Bio-Rad ) . qPCR was performed on an 7900HT Real Time PCR System ( Applied Biosystems ) using iTaq Universal SYBR Green Supermix ( Bio-Rad ) . De-identified post-mortem brain tissue used in this study was determined to be an exempt from IRB review by the VA Puget Sound Health Care System Human Research Protection Program Director on December 29 , 2011 . Tissue used for these studies was obtained from the University of Washington Alzheimer's Disease Research Center brain bank ( Seattle , WA ) , and the Indiana Alzheimer Disease Center brain bank ( Indianapolis , IN ) , where consent for autopsy and permission for use of tissue in scientific experiments was obtained . FTLD and ALS cases were selected on the basis of having an autopsy-confirmed diagnosis of FTLD and FTLD-related disorders or ALS . Control samples were from de-identified neurologically healthy control participants , who were of a similar age . Primary antibodies used for immunohistochemistry were anti-TTBK1 ( Abcam , 1∶100 ) , anti-TTBK2 ( Abgent , 1∶200 ) , and anti-phospho TDP-43 409/410 ( CosmoBio , 1∶1000 ) ) . In order to minimize variability , sections from all cases ( normal and affected subjects ) were stained simultaneously for each antibody . Immunostained sections were analyzed using the computerized image analysis system , MicroComputer Imaging Device ( MCID , Imaging Research , St . Catherines , Ontario , Canada ) . Blinded assessment of optical density measurements were obtained relative to the proportional area for TTBK1 and TTBK2 immunostaining in frontal cortex grey matter ( three separate readings per case ) . Data were averaged and are represented as mean +/− SEM . A two tailed Student's t-test was used to assess differences in TTBK1 and TTBK2 expression between cases and controls . For double label immunohistochemistry experiments , sections were first immunostained with anti-phospho TDP-43 and reaction product was visualized with nickel enhanced DAB ( black ) . Sections were then immunostained with anti-TTBK1 or TTBK2 and visualized with DAB alone ( brown ) . For double label immunofluorescence experiments , AlexaFluor 488 goat anti-rabbit and AlexaFluor 594 goat anti-mouse secondary antibodies ( Molecular Probes ) were used and autofluoresence was quenched with 0 . 1% Sudan Black [64] . To demonstrate specificity of the TTBK antibodies , TTBK1 and TTBK2 were blocked with 50-fold amount of immunizing peptide overnight at 4°C before proceeding with the immunostaining protocol ( see S5 Figure ) . | Aggregated proteins are a hallmark of many neurodegenerative diseases . In ALS and FTLD-TDP , these aggregates contain abnormal TDP-43 modified by phosphorylation . Protein phosphorylation normally controls protein activity , stability , or location , but in some neurodegenerative diseases the phosphorylated proteins accumulate in excess . Kinases are the enzymes responsible for protein phosphorylation . We have identified two TDP-43 kinases , TTBK1 and TTBK2 , using a novel approach combining reverse genetics and biochemical screening to identify the kinases responsible for changes in TDP-43 phosphorylation . We show TTBK1 and TTBK2 directly phosphorylate TDP-43 in vitro , and control TDP-43 phosphorylation in cellular and simple animal models of ALS . This has uncovered a molecular mechanism by which pathological phosphorylated TDP-43 can occur in disease . To determine whether changes in TTBK1/2 protein are contributing to TDP-43 pathology , we examined diseased brain and spinal cord tissue from patients with ALS or FTLD-TDP . We observed changes in the abundance of TTBK1 and TTBK2 in disease-affected neurons , and the coexistence of TTBK1/2 with phosphorylated TDP-43 aggregates in both FTLD-TDP and ALS . Therefore , increased abundance or activity of TTBK1 or TTBK2 may contribute to the neurodegeneration observed in ALS and FTLD-TDP . | [
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] | 2014 | The Tau Tubulin Kinases TTBK1/2 Promote Accumulation of Pathological TDP-43 |
Male infertility affects at least 5% of reproductive age males . The most common pathology is a complex presentation of decreased sperm output and abnormal sperm shape and motility referred to as oligoasthenoteratospermia ( OAT ) . For the majority of OAT men a precise diagnosis cannot be provided . Here we demonstrate that leucine-rich repeats and guanylate kinase-domain containing isoform 1 ( LRGUK-1 ) is required for multiple aspects of sperm assembly , including acrosome attachment , sperm head shaping and the initiation of the axoneme growth to form the core of the sperm tail . Specifically , LRGUK-1 is required for basal body attachment to the plasma membrane , the appropriate formation of the sub-distal appendages , the extension of axoneme microtubules and for microtubule movement and organisation within the manchette . Manchette dysfunction leads to abnormal sperm head shaping . Several of these functions may be achieved in association with the LRGUK-1 binding partner HOOK2 . Collectively , these data establish LRGUK-1 as a major determinant of microtubule structure within the male germ line .
Male infertility affects at least 5% men of reproductive age in the western societies [1] . Normal male fertility requires sufficient numbers of morphologically normal and motile sperm [2] . Oligoasthenoteratozoospermia ( OAT ) , is the term used to describe semen containing low numbers of sperm with poor motility and abnormal shape , and is the most common clinical phenotype in human male infertility [3] . The underlying aetiology in the majority of men presenting with OAT is unknown , and as such , there remains an absence of specific treatments , an absence of knowledge of associated somatic pathologies , and potential consequences for offspring conceived with OAT sperm via assisted reproductive technologies ( ART ) . The morphological and motility aspects of OAT likely have their origins in spermiogenesis , the process wherein round haploid germ cells are transformed into highly polarized sperm with the potential for motility and fertility . This process takes approximately two weeks in the mouse and involves several thousand different gene products [4] . Three of the major aspects of spermiogenesis are acrosome development , head shaping , and growth of the sperm flagellum [5 , 6] . These events are critically reliant upon complex microtubule structures , including the manchette and the axoneme , and a highly orchestrated series of protein transport mechanisms [7] . The manchette is a transient microtubule structure , which encircles the spermatid nucleus during the initial steps of elongation , and has a role in sculpting the species-specific nucleus shape . Abnormalities in manchette structure result in dysmorphic sperm heads [8–10] . We note that dynamic redistribution of the actin cytoskeletal system is also required for normal manchette function [8] . The axoneme forms the core of the sperm tail . It is composed of nine microtubule doublets surrounding a central microtubule pair ( 9+2 ) [11] . In contrast to motile cilia on other cells , the sperm tail axoneme is sheathed by accessory structures required for the production of ATP and protection against shear forces [12] . These structures include the outer dense fibers , fibrous sheath and mitochondrial sheath . Sperm tail axonemal development begins in round spermatids with the maturation of the mother centriole into a basal body , followed by plasma membrane attachment and axoneme extension . Several studies suggest that the extension of the basal body into an axoneme is dependent on the intra-flagella transport ( IFT ) system [13] . We note , however , that while this process is well defined in primary cilia [14] , its role in sperm tail biology requires more in-depth analysis . Defectives in germ cell axoneme formation leads to either an absence of a sperm tail or immotile sperm . Interestingly , research is increasingly indicating continuity between processes governing the development of the manchette and the sperm tail [13 , 15] . This may explain the extremely common association between abnormal sperm head morphology and motility in infertile men and mice [16] . Indeed , pioneering research from the Kierszenbaum lab has demonstrated a protein transport highway wherein proteins processed by the Golgi apparatus are transferred to the surface of the sperm acrosome at the cranial pole of the sperm head in a microtubule-dependent manner , then onto a cytoskeletal scaffolding plate known as the axoplaxome that anchors the developing acrosome to the nucleus [17] . Subsequently , proteins then localise to the microtubules of the manchette and ultimately into the growing sperm tail . The latter part of the highway has been termed intra-manchette transport and it appears to have mechanistic similarities with , and to interface with , the classical IFT pathway required for axoneme extension in most cilia types [13 , 18] . In an effort to understand these processes , we have undertaken a random mouse-mutagenesis screen to identify genes with critical roles in sperm formation . One of the genes identified encodes the previously uncharacterized gene leucine-rich repeats and guanylate kinase domain contain ( Lrguk ) . Here we have shown that LRGUK isoform 1 ( LRGUK-1 ) has a critical role in both sperm head shaping and basal body attachment to the plasma membrane , and in the early aspects of axoneme development . LRGUK is transported along the acrosome-acroplaxome-manchette-tail axis in a potential complex with the adaptor protein HOOK2 [19 , 20] . LRGUK-1 dysfunction leads to abnormal manchette formation and movement , and an absence of axoneme extension from the basal body . Collectively these data define LRGUK-1 as a crucial regulator of male germ cell basal body function , microtubule dynamics and fertility .
In order to identify critical regulators of male germ cell development and fertility , we undertook a random N-ethyl-N-nitrosourea ( ENU ) mouse mutagenesis screen [9 , 21] . The ‘Kaos’ mouse line was identified based on male-specific infertility and the presentation of chaotic spermatogenesis ( see below ) . Mapping of the mutation and sequencing of candidate genes revealed a C to T substitution in exon 14 of Lrguk ( Fig . 1A ) . Lrguk is predicted to encode 3 splice variants , Lrguk transcript 1 ( Lrguk-1 ) , -2 ( Lrguk-2 ) and -3 ( Lrguk-3 ) . Lrguk-1 is the longest transcript and the only isoform affected by the mutation ( Fig . 1A ) . The C→T mutation resulted in the conversion of an arginine ( R ) at position 528 to a premature termination codon ( R528Stop , the LrgukKaos allele ) and in turn the truncation of 293 residues from the C-terminal region of LRGUK-1 ( Fig . 1B ) . Orthologues of LRGUK can be observed in many species , and sequence alignment of LRGUK-1 from multiple species revealed that R528 residue is conserved in all ( Fig . 1C ) . LrgukKaos/Kaos testis showed a 75% reduction in the level of Lrguk-1 expression ( 8–12 weeks-of-age ) compared to LrgukWT/WT siblings ( Fig . 1D ) and a complete absence of both the native LRGUK-1 protein of 93 kDa and the predicted truncated LRGUK-1Kaos of 60kDa ( Fig . 1E ) . We note that the antibody used in these experiments is directed against an epitope present in both the native and truncated forms of LRGUK-1 , but C-terminal to LRGUK-2 and -3 sequences . These results suggested Lrguk-1Kaos mRNA was unstable . Quantitative PCR ( qPCR ) showed no evidence of a compensatory up-regulation of Lrguk-2 and Lrguk-3 mRNAs in the LrgukKaos/Kaos testis ( Fig . 1F-G ) . Collectively , these data revealed that LrgukKaos/Kaos males were sterile as a consequence of a specific absence of the LRGUK-1 protein . All LrgukKaos/Kaos males had chaotic and disorganised spermatogenesis and were sterile ( n>50 , aged 7–26 weeks ) , whereas LrgukWT/Kaos males and LrgukKaos/Kaos females had apparently normal fertility . LrgukKaos/Kaos males had a normal body weight ( S1A Fig . ) and were anatomically indistinguishable from wild type siblings . LrgukKaos/Kaos male sterility was characterized by a 13% reduction in testis weight ( Fig . 2A ) and an 81% reduction in daily sperm production ( Fig . 2B ) . Collectively these data suggest that the majority of missing germ cells were from the haploid phase of spermatogenesis wherein they contributed relatively little to testis weight . A similar reduction ( 79% ) in sperm content was observed in the epididymal sperm content ( Fig . 2C ) . The loss of germ cells from the seminiferous epithelium via sloughing was indicated by the presence of immature germ cells in LrgukKaos/Kaos epididymis ( Fig . 2F ) . In contrast , apoptosis levels were similar between genotypes ( S1B-C Fig . ) . Of the elongate spermatids present in the seminiferous epithelium , virtually none appeared to contain a sperm tail ( Fig . 2E ) , and of the very few sperm that were present in the epididymis , all had grossly misshapen heads and shortened tails ( Fig . 2D ) that displayed no capacity for motility . A closer examination of spermatid structure also revealed the presence of fragmented acrosome in early round spermatids ( Fig . 2E and below ) . A more quantitative stereological analysis of the dynamics of spermatogenesis confirmed the histological observations . LrgukKaos/Kaos adult testes contained normal numbers of supporting Sertoli cells , spermatocytes and early round spermatids ( S1 Table ) . They contained , however , a 37% reduction ( p<0 . 05 ) in elongated spermatids ( steps 13–16 ) . In addition , we noted a pronounced increase in the number of elongated spermatids retained in the basal crypts of Sertoli cells in stage VII-XII tubules that was suggestive of a failure of the early phases of sperm release ( spermiation ) ( S1D Fig . ) . Consistent with this interpretation , the levels of DNA double strand breaks , as determined by γH2AX staining , in the retained spermatid nuclei was notably elevated ( Fig . 2G ) in LrgukKaos/Kaos suggesting the initiation of degeneration [22] . Cumulatively , these data show that LrgukKaos/Kaos males were sterile as a consequence of germ cell sloughing and degeneration , abnormal sperm development and an inability of those sperm that were produced to ascend the female reproductive tract following mating . qPCR analysis revealed that Lrguk-1 mRNA was highly enriched in the testis compared to other adult tissues ( Fig . 3A ) . An analysis of mouse testes taken at defined periods during the establishment of the first wave of spermatogenesis also revealed that Lrguk-1 mRNA was detectable at low levels from birth , up-regulated at day 14 coincident with the appearance of pachytene spermatocytes , then maximal from day 18 coincident with the appearance of haploid germ cells ( Fig . 3B ) . This result was suggestive of Lrguk-1 being predominantly expressed in haploid germ cells . During spermatid development , and using an antibody that should detect all of LRGUK1–3 , LRGUK protein was initially localised to a supra-nuclear region of round spermatids , and was particularly evident at the leading edge of the developing acrosome and acroplaxome ( Fig . 3C ) . As maturation proceeded and nuclear elongation initiated , LRGUK moved distally to ultimately reside on the microtubules of the manchette ( Fig . 3D and S2 Fig . ) . LRGUK was also evident in the sperm basal body and the sperm tail ( Fig . 3E ) . These data , and the abnormal sperm head and tail morphology in LrgukKaos/Kaos germ cells , suggested that LRGUK-1 has a role in acrosome and tail biogenesis . We note that LRGUK protein was not detectable in our hands in spermatocytes . At present it is unknown if this was due to a lack of abundance or a translational delay as is often seen in spermiogenic genes [23] . LrgukKaos/Kaos germ cells showed reduced LRGUK immunolabelling compared to wild type cells ( S2 Fig . ) , however , residual , presumably LRGUK-2 and/or LRGUK-3 staining could be seen within mutant spermatids ( Fig . 3C-D and S2 Fig . ) . The possibility also remains that a small amount of truncated LRGUK-1 was detected by this antibody . Within these cells the distribution of residual LRGUK was notably perturbed . Specifically , the movement of LRGUK appeared to stall at the leading edge of the acrosome/acroplaxome complex ( Fig . 3C-D and S2 Fig . ) . LRGUK staining on the microtubules of the LrgukKaos/Kaos manchette was reduced and more variably distributed ( Fig . 3D and S2 Fig . ) . These data are consistent with the acroplaxome operating as a loading dock for cargo proteins prior to loading onto the microtubules of the manchette [15 , 17] and the C-terminal 293 amino acids of LRGUK-1 having a role in this transition . One of the features of the LrgukKaos/Kaos phenotype was the abnormal morphology of sperm heads . A detailed analysis of acrosome formation on periodic acid Schiff’s ( PAS ) stained sections revealed the presence of fragmented acrosomes in step 2–4 spermatids ( Fig . 4A ) . The acrosome is formed by the sequential fusion of Golgi-derived pro-acrosomal vesicles to form a cap overlying the nucleus . The membrane overlying the acrosome is essential for the initial binding to and penetration through the oocyte complex [15 , 24 , 25] . Electron microscopy also revealed ∼20% of acrosomes in elongated spermatids were detached from sperm nuclei ( Fig . 4B ) . A close inspection of these cells indicated that both the acrosome and the acroplaxome were detaching from the nuclear membrane suggesting that LRGUK-1 has a role in establishing the integrity of the connection between the acroplaxome and the nuclear membrane . LrgukKaos/Kaos spermatids also contained abnormal manchettes ( S2 Fig . , Fig . 4D and Fig . 5 ) . The manchette is a grass skirt-like structure that encircles the elongating spermatid nucleus . As indicated above , it has a role in both nuclear shaping and protein transport into the growing sperm tail via a process called intra-manchette transport [13 , 18] . In normal spermatids , the manchette contains a series of parallel microtubule bundles that extend from a perinuclear ring and lie in close proximity to , and are parallel with , the nuclear membrane into the distal cytoplasm ( Fig . 4C and Fig . 5 ) . An analysis of elongating LrgukKaos/Kaos spermatids , using α-tubulin as a microtubule marker , revealed that the manchettes formed at the correct time and that the perinuclear ring began to move caudally along the sperm head during spermiogenesis ( Fig . 5 ) . The microtubule bundles of the manchette skirt were , however , unevenly distributed and had a ‘raggedy’ appearance compared to wild type cells . Further , and based on both the light and electron microscopic images the distal movement of the manchette along the nucleus that normally occurs during elongation was also abnormal in LrgukKaos/Kaos spermatids ( Fig . 5 , S3 Fig . ) . In contrast the perinuclear ring of the manchette continued to constrict , as it would normally , thus leading to nuclear distortion ( Fig . 4C , Fig . 5 and S2 Fig . ) . Collectively these data illustrate a role for LRGUK-1 in acrosome attachment to the sperm head and in microtubule organisation within the manchette . LRGUK-1 contains multiple domains with known roles in protein-protein interactions i . e . a guanylate kinase-like domain ( GK ) , leucine rich repeats ( LRRs ) domains and a leucine rich repeat C-terminal domain ( LRRCT ) [26 , 27] ( SMART entry IPR000483 ) . In order to explore this potential , and to define pathways within which LRGUK-1 may be involved during haploid germ cell development , we performed a yeast two-hybrid screen to identify LRGUK-1 binding partners . One of the binding partners identified was HOOK2 ( Fig . 6 ) . The identified Hook2 clone encoded the C-terminal 348 amino acids of HOOK2 . Specific transfection of the full length HOOK2 with LRGUK-1 in a separate yeast two hybid assay confirmed this interaction and the introduction of the R528Stop mutation into the Lrguk-1 sequence completely abolished binding to HOOK2 ( Fig . 6A ) . An interaction between LRGUK-1 and endogenous HOOK2 was confirmed by co-immunoprecipitation , wherein full-length mouse Lrguk-1-GFP was transfected into HEK293T cells then the complex co-precipitated ( Fig . 6B ) . HOOK2 is a member of the HOOK family of proteins , which are adaptor-like proteins involved in loading cargos ( including protein complexes and organelles ) onto microtubules for transport [28] . Notably , HOOK2 has recently been found to function in the maintenance of centriole structure and primary cilia assembly [19] . Like sperm flagella , primary cilia contain a central axoneme , but rather than possessing a 9+2 microtubule structure , they lack the central microtubule pair ( 9+0 ) [16 , 29] . Specifically , within retinal epithelial cells HOOK2 bound to the essential cilia proteins PCMI and RAB8a and was required to initiate axoneme growth from the basal body [20] . These data raise the possibility that HOOK2 is involved in the delivery of LRGUK-1 to the basal body , or vice versa , and in the initiation of sperm tail growth . As for LRGUK , HOOK2 was localised to the Golgi-derived spermatid acrosome , the acroplaxome , the manchette and the sperm basal body ( Fig . 6C-E ) . HOOK2 localization was not appreciably altered in the presence of the LrgukKaos mutation , albeit in the presence of abnormal germ cell structure ( Fig . 6D ) , indicating that LRGUK-1 does not define HOOK2 localization . Unfortunately genetically modified Hook2 mouse lines are not available to test the dependence of LRGUK localization on HOOK2 . As such , and although the formal possibility remains that HOOK2 may be a LRGUK-1 cargo , it is more likely that HOOK2 functions in its established role to transport LRGUK-1 . The LrgukKaos/Kaos sperm phenotype has some similarities with that observed for HOOK2 depleted retinal cells , suggesting they lie in a common pathway . Greatly reduced axoneme development was evidenced in testis sections stained for the axoneme marker acetylated tubulin and the absence of 9+2 axoneme structure was seen at the electron microscopic level ( Fig . 7A-E ) . An analysis of the early steps of centriole/basal body movement and axoneme development , however , revealed abnormalities in LrgukKaos/Kaos germ cells , strongly suggestive of a critical role for LRGUK-1 beyond that currently documented for HOOK2 , specifically in the formation of the centriole appendages . In early wild type spermatids the mature centriole can be distinguished from the adjacent daughter centriole by the possession of accessory structures known as the sub-distal appendages ( SAP ) and distal appendages ( DAPs ) [30] . The mature centriole then migrates to the spermatid periphery and attaches to the plasma membrane before attaching to the nuclear pole opposite the acrosome [16] . Recent data has shown the DAPs are required for basal body-to-membrane docking [31] , and SAPs are believed to be where axoneme microtubules are anchored and are thus required for axoneme extension [32–34] . Electron microscopy of spermatids from LrgukWT/WT spermatids clearly showed the docking of mature centrioles to the plasma membrane and the associated DAPs and SAPs ( Fig . 7E ) . In contrast , the over-whelming majority of basal bodies in spermatids from LrgukKaos/Kaos mice contained SAPs that were overtly enlarged and plasma membrane attachments were very infrequent ( <1% of the time ) ( Fig . 7E ) . Consistent with abnormal SAP function , microtubule extension from the LrgukKaos/Kaos basal body into an axoneme was extremely rare ( Fig . 7D ) . Despite the absence of membrane attachment basal bodies did contain DAP-like structures . LrgukKaos/Kaos basal bodies did , however , appeared to attach to the nuclear membrane normally ( Fig . 7E ) . In comparison to the basal body phenotype seen in LrgukKaos/Kaos spermatids , the loss of HOOK2 function during retinal cell primary cilia formation had no reported effect on SAP formation [19] . These data suggest that LRGUK-1 is required for the formation / function of the DAPs and SAPs in spermatids . Currently it is unknown if these effects are independent of HOOK2 or if they are spermatid-specific functions and thus , not seen following HOOK2 knockdown in retinal cells . In contrast to the lack of axoneme development in LrgukKaos/Kaos spermatids , we observed considerable evidence of the assembly of outer dense fiber-like structures within the distal cytoplasm of elongated spermatids ( Fig . 7B ) . These data suggest that while the outer dense fibers sit in close apposition to the microtubules of the axoneme in normal germs cells , their development can occur independently .
The dynamic organisation of microtubules and the ability to transport proteins over long distances are fundamental processes required for many cell types , but perhaps none more so than haploid male germ cells , where sperm head shaping and tail development occurs in the virtual absence of transcription [35] . Here we have demonstrated that LRGUK-1 is a critical component of this process with roles that impact upon multiple facets of sperm structure . LRGUK-1 is required for normal acrosome attachment , manchette function , the initiation of the axoneme extension and ultimately male fertility . In accordance with these roles , we observed LRGUK-1 within a protein transport corridor [13] involving movement from the Golgi complex in round spermatids , to the acrosome/acroplaxome , onto the manchette in elongating spermatids then ultimately into the sperm tail . Collectively our data establish LRGUK-1 as a vital component for haploid germ cell development and male fertility . The earliest discernable abnormality seen in LrgukKaos/Kaos germ cells was in acrosome development . The acrosome is a vesicle-like structure at the caudal pole of the sperm head . The plasma membrane immediately above the acrosome is the first point of binding between the sperm and the cumulus oocyte complex prior to fertilisation , and the contents of the acrosome is required for sperm penetration through the outer vestments of the oocyte [36] . Data presented here suggests that LRGUK-1 is required for the appropriate attachment of Golgi-derived pro-acrosomal vesicles onto the nucleus and the full structural integrity of the acrosome-acroplaxome attachment to the nuclear membrane [15 , 17] . LRGUK-1 dysfunction resulted in the fragmentation and loss of some pro-acrosomal vesicles in early round spermatids , and the detachment of the acrosome-acroplaxome from the sperm head during late spermiogenesis . Clearly however , acrosome-like structures were formed in spermatids ( albeit with apparently reduced efficiency in early round spermatids ) indicating that the enhanced adhesion inferred by LRGUK-1 may only become critical when shear forces are applied , for example during stages I through to VIII wherein elongated spermatids are sequentially dragged down into Sertoli cell crypts then pushed up to the luminal aspect of the seminiferous epithelium [37] . The apparent absence of LRGUK-1 protein from the acroplaxome region in mature sperm suggests that this defect maybe mediated by an LRGUK-1 binding partner rather than LRGUK-1 itself , or that LRGUK-1 is part of a stepwise process resulting in firm acrosome-acroplaxome-nuclear attachment . Taken together our results suggest a role for LRGUK-1 in the trafficking of pro-acrosomal vesicles from the Golgi to the acroplaxome and in the attachment of acrosome-acroplaxome to the nuclear membrane . A second major defect , and almost certainly the cause of the head abnormalities in LrgukKaos/Kaos sperm , was a defect in the structure and movement of the manchette . The manchette is a complex microtubule array that forms around the spermatid nucleus concordant with the initiation of nuclear compaction . It is composed of a perinuclear ring and a fringe of microtubule bundles that extend into the distal cytoplasm . As spermiogenesis proceeds the manchette moves distally , and in the case of species such as the mouse that contain falciform shaped sperm heads , it pivots in a manner dependent on microtubule severing [22] . In parallel , the perinuclear ring constricts , likely contributing to the tapered shape of the post-acrosomal region of the sperm head . Our data show that LRGUK-1 is required for the distal movement of the perinuclear ring . In the presence of the LrgukKaos/Kaos mutation the perinuclear ring constricted more proximally than normal leading to abnormal sperm head shape . Interestingly the remaining LRGUK present within elongating spermatids ( LRGUK-2 and/or -3 or small amounts of truncated LRGUK-1 ) remained at the leading edge of the acroplaxome , suggesting that there are motifs C-terminal 293 amino acids of LRGUK-1 that are required for the transition to the manchette . Of relevance , a second member of the HOOK family is required for manchette function and ultimately male fertility . The azh mouse phenotype was caused by the deletion of exons 10–11 from the Hook1 gene [38] . Homozygous azh males displayed OAT characterised by severe head abnormalities and the frequent decapitation from the sperm tail . The latter is suggestive of a weakened connection between the nuclear membrane and the basal body-derived axoneme . This phenocopying and data suggesting that HOOK family members frequently function as heterodimers [39] raise the possibility that LRGUK-1 exists in a complex with both HOOK2 and HOOK1 . This possibility will be tested in future experiments . The most striking aspect of the Kaos phenotype , and the ultimate cause of male sterility , was the almost complete block of sperm tail development . LRGUK-1 dysfunction lead to abnormal SAP formation on basal bodies and an absence of plasma membrane attachment , likely associated with DAP dysfunction . As a consequence , basal bodies failed to nucleate axoneme microtubules . Within retinal primary cilia , HOOK2 is involved in the assembly of a complex containing PCMI and RAB8a , and the initiation of axoneme microtubule extension [19] . In contrast to HOOK2 action in primary cilia , however , our data revealed that LRGUK-1 also has a critical role in the formation of basal body-plasma membrane attachment and SAP formation . Currently it is unknown if these effects are independent of HOOK2 or if they are spermatid-specific functions and thus , not seen following HOOK2 knockdown in retinal cells . Our data do not , however , support a role for LRGUK-1 in cilia broadly . Notably , the Kaos mouse line showed none of the morphometric features characteristic of primary cilia disorders such as polydactyly and craniofacial abnormalities [40] , although the presence of Lrguk-1 mRNA in tissues containing motile cilia ( 9+2 axonemes ) raises the possibility of an age-related pathology associated with motile cilia dysfunction . The phenotypic similarity observed in LrgukKaos/Kaos and mice containing mutations in core proteins of the IFT pathway including Ift88 and Kif3a [41 , 42] highlights the continuity of the protein transport pathway underlying the movement of proteins involved in sperm head shaping and axoneme extension . Our data suggest that LRGUK-1 functions upstream/before the IFT pathway i . e . spermatids with defective LRGUK-1 will undergo a developmental arrest prior to the requirement for the IFT pathway . These data also highlight the exquisite value of using the testis as a model to define processes of likely fundamental importance to cell biology broadly . Collectively , we have identified LRGUK-1 as a protein critically involved in multiple aspects of sperm assembly and function . LRGUK-1 is required for appropriate acrosome attachment to the sperm heard , sperm head shaping via the manchette and tail growth from the basal body . During the initiation of sperm tail axoneme extension from the basal body , LRGUK-1 functions in plasma membrane attachment and the formation of SAP and ultimately microtubule extension . The specific loss of LRGUK-1 function results in OAT in mice and raises the possibility that LRGUK dysfunction leads to human OAT .
Animal procedures were performed in accordance with Australian NHMRC Guidelines on Ethics in Animal Experimentation and approved by the Australian National University and Monash University Animal Experimentation Ethics Committees . Point mutant mice were generated on a C57BL/6 background and outbred to CBA and individual lines screened for sterility causing mutations as described previously [9 , 21] . Mating behaviour , as indicated by the presence of copulatory plugs was normal . The sterility causing mutation in the Kaos line was initially linked to a region on chromosome 6 using a SNP-based microarray approach . The region was subsequently narrowed using additional mice and SNPs to a 12 . 9 Mb region ( 30872499–43776812 bp ) that contained 74 genes . Candidate genes were selected based on expression in haploid germ cells , i . e . the site of the phenotype , in EST expression databases . 28 genes were expressed within round spermatids . The full coding region of eight of these genes was sequenced and a single C to T point mutation within the Lrguk gene was identified . Following the identification of the causal mutation , mice were genotyped using the Amplifluor system ( Chemicon ) using a wild type-specific reverse primer 5’-GAAGGTCGGAGTCAACGGATTCCATAGGCACCACCAAGATATATCG-3’ , a mutant allele specific reverse primer 5’-GAAGGTGACCAAGTTCATGCTCCA TAGGCACCACCAAGATATATCA-3’ and a conserved forward primer 5’- CAGCCTTGGACTATTTATAGGGAGTGTG-3’ as described previously [9] . LRGUK orthologues were identified as described previously [7] . Sterility in the Kaos mouse line was characterized using the regime outlined in Borg et al [43] . Daily sperm production ( DSP ) in the testis and total epididymal sperm content was determined using the Triton X100 nuclear solubilization method as described previously [44] . Sperm ultra-structure was assessed using electron microscopy as described previously [45] . Sperm motility was assessed visually using sperm back-flushed from the cauda epididymis [46] . Cauda epididymal sperm morphology was visualized using haematoxylin and eosin staining . The stages of the epithelium tubule were judged by Periodic Acid Schiff ( PAS ) staining [47] . Apoptosis was evaluated by TUNEL Apoptosis Detection Kit ( Millipore ) according to the manufacturer’s instructions; n = 5 mice per genotype and the positive cells in 100 seminiferous tubules were counted for each mouse . Germ and Sertoli cell numbers were counted in 25μm-thick PAS stained methacrylate embedded testis sections using the optical dissector method as described previously [48] . Basal retained elongated spermatids were counted in stage VII-XII [22 , 48] . N = 5 mice per genotype and 240 counting frames for each mouse . Lrguk in adult tissues and at different time points during the establishment of the first wave of spermatogenesis was defined as outlined previously [49] . Lrguk expression was detected using the Taqman assay ( Mm01166701-m1 ) . Lrguk-2 expression was detected using a custom designed assay ( Forward primer 5'-CCCCAAAATCTCAAGGTATACTTATCAG-3'; reverse primer 5'–CCGCAGCTGAAGCAAAACTC-3'; probe 5'-CAAAGCACACAATGGT-3' ) . A custom designed assay was also used to detect both Lrguk2 and Lrguk3 transcripts ( Forward primer 5'-CTGGCCTATCTGTGGATGACATC-3'; reverse primer 5'-CCGCAGCTGAAGCAAAACTC-3’; probe 5'-CAAAGCACACAATGGT-3’ ) . All expression data was normalized to the Ppia house-keeping gene ( Mm02342429-gl ) . Germ cells were isolated using the Staput method described previously [50] . For immunofluorescence staining , the purified cells were fixed with 4% paraformaldehyde ( PFA ) and stained as described previously [9] . Primary antibodies used included: anti-LRGUK ( 1:200 dilution , Novus Biologicals , raised against amino acids 32–181 ) ; anti-HOOK2 ( 1:200 dilution , GeneTex ) , anti-acetylated tubulin ( 1:1000 dilution , Sigma ) , anti-α-tubulin ( 1:5000 dilution , Sigma ) . All primary antibodies were diluted in 10% non-immune horse serum ( NHS ) in PBS and incubated at 4°C overnight . Secondary antibodies included: Alexa Fluor 555 donkey anti-rabbit IgG and Alexa Fluor 488 donkey anti-mouse IgG , 1:500 dilution in 10% NHS in PBS for 45 minutes at room temperature . Nuclei were labelled with DAPI . The acrosome was visualized using FITC-PNA ( 1:2000 dilution , Sapphire Bioscience ) . Images were taken with a SP8 confocal microscope ( Leica Mircosystems ) . For consistence α-tubulin was artificially coloured green in all images . Paraffin-embedded testis sections were stained for acetylated tubulin as described previously [45] . The adult mouse testis cDNA library ( pDEST22 prey vector ) used for yeast two hybrid screen was as described previously [51] . The full length Lrguk-1WT and LrgukKaos cDNAs were cloned into pDEST32 vector using the Gateway cloning kit ( Invitrogen ) . For the initial identification of LRGUK binding partners , the LRGUKWT-pDEST32 vector was used as bait in a yeast two hybrid screen with the ProQuest Two-Hybrid System ( Invitrogen ) . Briefly , the LRGUKWT-pDEST32 vector and pDEST22 testis cDNA library constructs were co-transformed into Mav203 yeast strain . Putative interacting clones were isolated from the resulting yeast colonies and re-transformed into E . coli to obtain high purity plasmids for sequencing cDNA inserts . Sequencing of the longest HOOK2 clone revealed an open reading frame of 1078 bp that corresponded to the C-terminal amino acids 369–716 of the HOOK2 protein . To determine the effect of the LRGUKKaos mutation on the binding to HOOK2 , the identified HOOK2-pDEST22 prey vector was co-transformed into the Mav203 yeast strain along with either LRGUKKaos-pDEST32 , LRGUKWT-pDEST32 or pDEST32 empty vector only and plated on selection media . Full length mouse Lrguk-1 was amplified from wild type C57BL/6J testis cDNA using Lrguk-Fw: 5’-ATATAAAGATCTGCGGCCTTCGAGCGAAAT-3’ and Lrguk-Rev: 5’-ATATAAGGGCCCCTATCGCGGCCGTGCGGGAT-3’ primers than cloned into the pEGFP-C1 expression vector ( Clontech , Gen Bank Accession number U55763 ) . The LRGUK-1/pEGFP-C1 construct was transfected into HEK293 cells using Lipofectamine 3000 Reagent ( Life Technologies , Cat . No . L3000008 ) . Co-immunoprecipitation was carried out using anti-GFP-Trap-A beads as per the manufacturer’s instructions ( Chromotek , Cat . No . gta-100 ) . Empty pEGFP-C1 vector was used as a negative control . The presence of LRGUK-GFP and endogenous HOOK2 proteins were determined using anti-GFP ( Roche , Cat . No . 11814460001 and HOOK2 antibodies ( GeneTex , Cat . No . GTX115898 , corresponding with amino acids 197–380 of HOOK2 ) . For LRGUK-1 expression , protein was extracted from both wild type and mutant testes using 1% NP-40/PBS lysis buffer with 1:200 protein inhibitor cocktail ( Promega ) . Protein ( 40μg ) was separated on a 12% SDS-PAGE gel . Non-specific antibody binding was minimized by blocking the membrane with 5% skim milk for 1 hour room temperature and antibodies were diluted in 1% skim milk . The membrane was probed with a rabbit LRGUK-1 antibody ( Sigma , raised against amino acids 336–427 of LRGUK-1 and thus will not bind to LRGUK-2 or -3 ) . Bound antibody was detected using a goat anti-rabbit IgG HRP ( Dako ) secondary antibody . Antibody binding was detected using the enhanced chemiluminescence ( ECL Plus ) detection kit ( Amersham Biosciences ) . Protein loading was normalized against actin . | Male infertility affects one in six couples in western societies and approximately half of these are the result of male factor disorders . The most common clinical presentation for male infertility is a complex mixture of abnormal sperm output , shape and motility referred to as oligoasthenoteratozoospermia ( OAT ) . In an effort to define an origin of OAT we have analysed a mouse model of leucine-rich repeats and guanylate kinase-domain containing isoform 1 ( LRGUK-1 ) dysfunction . Herein we show that LRGUK dynamically redistributes during the process of haploid germ cell maturation ( spermiogenesis ) and that LRGUK-1 function is required for multiple aspects of sperm centriole and tail development and sperm head shaping . Further , we have identified HOOK2 as a novel LRGUK-1 binding partner , thus raising the possibility that several aspects of LRGUK-1 function are achieved in partnership with HOOK2 . | [
"Abstract",
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"Methods"
] | [] | 2015 | LRGUK-1 Is Required for Basal Body and Manchette Function during Spermatogenesis and Male Fertility |
Neglected tropical diseases ( NTDs ) account for a large disease burden in sub-Saharan Africa . While the general cost-effectiveness of NTD interventions to improve health outcomes has been assessed , few studies have also accounted for the financial and education gains of investing in NTD control . We built on extended cost-effectiveness analysis ( ECEA ) methods to assess the health gains ( e . g . infections , disability-adjusted life years or DALYs averted ) , household financial gains ( out-of-pocket expenditures averted ) , and education gains ( cases of school absenteeism averted ) for five NTD interventions that the government of Madagascar aims to roll out nationally . The five NTDs considered were schistosomiasis , lymphatic filariasis , and three soil-transmitted helminthiases ( Ascaris lumbricoides , Trichuris trichiura , and hookworm infections ) . The estimated incremental cost-effectiveness for the roll-out of preventive chemotherapy for all NTDs jointly was USD125 per DALY averted ( 95% uncertainty range: 65–231 ) , and its benefit-cost ratio could vary between 5 and 31 . Our analysis estimated that , per dollar spent , schistosomiasis preventive chemotherapy , in particular , could avert a large number of infections ( 176 , 000 infections averted per $100 , 000 spent ) , DALYs ( 2 , 000 averted per $100 , 000 spent ) , and cases of school absenteeism ( 27 , 000 school years gained per $100 , 000 spent ) . This analysis incorporates financial and education gains into the economic evaluation of health interventions , and therefore provides information about the efficiency of attainment of three Sustainable Development Goals ( SDGs ) . Our findings reveal how the national scale-up of NTD control in Madagascar can help address health ( SDG3 ) , economic ( SDG1 ) , and education ( SDG4 ) goals . This study further highlights the potentially large societal benefits of investing in NTD control in low-resource settings .
Neglected tropical diseases ( NTDs ) affect more than 1 billion individuals worldwide [1] . NTDs are typically a consequence of environmental and socioeconomic conditions and cause ill health and disability among the poorest and most marginalized people [2] . Moreover , the economic and social effects of NTDs are extensive [2 , 3] . NTDs affect household and worker productivity [4–6] and are associated with substantial loss of work time [7 , 8] . Interventions to control NTDs promise large economic pay-offs outside the health sector in agricultural productivity and educational benefits , and have been considered as investments in human capital and poverty reduction [9] . Given that the existing tools to control NTDs are effective , inexpensive , and the dividends are large , ending these diseases has been suggested as one of the most cost-effective interventions in population health [1] . As a result , a range of elimination and control initiatives for individual diseases has emerged , including the London Declaration on NTDs , inspired by the World Health Organization’s ( WHO ) 2020 roadmap on NTDs , and the Sustainable Development Goal ( SDG ) target 3 . 3 to end the epidemic of NTDs by 2030 [10] . Existing cost-effectiveness analyses of NTD control , however , have typically focused on the health gains associated with the scale-up of preventive chemotherapy in low-resource settings [1 , 2] . This is surprising given the wide array of economic and social benefits of investing in NTD control [11] . The first edition of Disease Control Priorities ( DCP ) already made this point in 1993 , further highlighting the broad impact of worm infections ( helminthiases ) [12]: The contents of the DCP served as powerful background information for the World Bank’s World Development Report 1993 [13] , the estimation of disability-adjusted life years ( DALYs ) , the ‘worm wars’ [14 , 15] , and the recently published third edition of DCP [16] . Furthermore , given limited resources , policymakers dealing with NTDs face difficult decisions often having to balance multiple sectoral goals beyond health . The typical framework used allocates resources to optimize population health . This approach risks missing the fact that health investments contribute to gains in other sectors and may lead to underestimating the broader benefits of NTD control [17] . If NTD control , for instance , contributes to educational gains , policymakers in the education sector may be willing to contribute to the cost of NTD control in a co-financing approach between the education and health sectors to achieve their respective goals jointly [16 , 18] . While previous work has documented the extensive benefits of NTD control across the SDG spectrum [13] , our study attempts to comprehensively quantify the extended cost-effectiveness of NTD control across multiple sectors . To address this objective , we assessed the potential health , financial , and education gains of national NTD control in Madagascar , where NTDs are highly endemic ( see S1 Text in the Appendix for contextual information ) . In the spirit of extended cost-effectiveness analysis ( ECEA ) methods [19 , 20] , we examine interventions for five NTDs which the government aims to scale-up nationally: “lymphatic filariasis” ( LF ) , “schistosomiasis” , and three intestinal parasites i . e . “soil-transmitted helminthiases” ( STH ) ( Ascaris lumbricoides , Trichuris trichiura , and hookworm ) . This study focuses on the cost of scaling up NTD control efforts nationally and its impact on morbidity and mortality , out-of-pocket ( OOP ) treatment costs for households , as well as on educational outcomes . The goal of this study is not to assess the costs and benefits of NTD elimination in Madagascar; rather we propose a modeling approach and illustrate it by assessing the potential costs and benefits of scaling up NTD control .
We summarize here the mathematical derivations for our key outcomes including: program costs , the number of infections averted , household OOP treatment expenditures averted , and cases of school absenteeism averted ( in years of educational attainment gained ) . For the five NTD interventions ( D = schistosomiasis , STH , LF ) , the program targets school-age children ( 5–14 year-olds , Pop5-14 ) . We denote pD the probability of treatment for disease D conditional on having D; cOOP , D the OOP costs for disease treatment; and cgov , D the government costs for disease treatment . Preventive chemotherapy ( PC ) has an effectiveness PCeff and the incremental coverage achieved is Cov . From the government perspective , the incremental costs of PC would be: TCPC=[ ( ndoses*cprev+cprog ) *Pop5−14] , ( 1 ) where ndoses is the number of treatment doses; cprev is the price per dose; and cprog is the cost of the program per individual . cprev = 0 when drugs are donated by pharmaceutical companies ( we relax this assumption in a sensitivity analysis where we include drug costs ) , and ndoses = 1 since the campaign included one annual dose . The number of infections averted is assumed to be: Prevpost , D=PCeff*Cov*Prevante , D , ( 2 ) where Prevante , D is the number of cases of D among Pop5-14 before program . The number of cases of school absenteeism averted would be: Schoolpost , D=PCeff*Cov*Schoolante , D , ( 3 ) where Schoolante , D is the number of cases of school absenteeism associated with NTDs among the school-going age population Pop5-14 before program ( i . e . , education burden associated with NTD infections ) . As we identified no data on school years lost due to NTD infections in Madagascar , we used data from a randomized deworming program in primary schools in Kenya to estimate Schoolante , which found that treatment among children would increase educational attainment by about 0 . 15 years in the long run [30] , and assumed: Schoolante , D = Pop5-14 * Prevante , D * 0 . 15 . The amount of household OOP expenditures averted by the program would be Epost = Prevpost * pS * pD * cOOP , D , where Prevpost is the number of infections averted , pS the probability of developing clinical symptoms resulting from D , pD the probability of seeking treatment for D ( conditional on having D ) , and cOOP , D the OOP costs for D treatment . We examined the ratio of the full spectrum of benefits of NTD control in monetary units divided by the total cost of investing in NTD control . We converted DALYs gained into a monetary value ( USD ) . We assessed a range of monetary values since there is no formal consensus on how much to spend to avert a DALY in low-resource settings [39 , 40] . To assess the monetary value of education gains , we used data from the Labor Force Surveys of Madagascar and evidence on the annual rates of return to schooling . The average monthly salary in Madagascar has been estimated at 55 , 000 Malagasy Ariary ( about USD20 ) , or 667 , 000 Malagasy Ariary ( about USD230 ) per year , whereas the estimated return to one additional year of schooling has been quantified at 11% ( of an individual’s wage ) [41] . To capture the present value of long-run wage benefits associated with preventive chemotherapy , we conservatively assumed wage benefits over 20 years discounted at 3% per year [42] . We used data on the average wage in Madagascar ( as opposed to the minimum wage ) since the labor market is dominated by non-wage earners ( only 11% of the labor force earns a salary ) [43] . The average wage is lower than the minimum wage in the private sector [44] . To assess the distributional impact , we examined the subnational variation in the effects of the program on health , financial , and education gains . Field studies conducted in Madagascar between 2015 and 2016 suggest that the prevalence of STH among school-aged children ranges from 0 to 94% ( Appendix , S1 Fig ) . A similarly large range has been observed for schistosomiasis , which ranged from 1 to 89% in endemic districts ( 106 out of 114 districts ) . The prevalence of LF ranged from 0 to 58% ( in 99/114 districts ) [22] . We examined the differential impact of rolling out the program using a range of values for prevalence that is representative of the distributions seen in Madagascar . Specifically , we used 5% , 25% , 45% , 65% , and 85% as prevalence for the five NTDs . For instance , in the districts Ampanihy , Beloha , Ihosy and Toliara II in South-Western Madagascar , the prevalence of STH ranges from 1 to 8% . Conversely , in the districts Mananara Avaratra , Maroantsetra , Toamasina I and Toamasina II in North-Eastern Madagascar , the prevalence of STH ranges from 77 to 99% . A similarly high prevalence of STH is found along the Eastern coast [22] . We expect that the combination of high prevalence and focus on smaller geographic areas increases the cost-effectiveness of NTD control in highly endemic districts . It is likely that national NTD interventions may ultimately focus on specific “hot spots” where NTDs are highly endemic using regionally targeted campaigns . Univariate and multivariate sensitivity analyses were conducted to explore the sensitivity of our findings to various parameter assumptions . Considerable uncertainty exists around NTDs , including prevalence and intensity of infection and of related conditions , their distributions , effectiveness of MDA to control NTDs , as well as on the effect of NTD control on economic and social outcomes . In particular , there has been some degree of controversy around the effect of NTD control on school participation [14 , 15 , 45] and previous cost-effectiveness calculations [46] . To acknowledge the uncertainty around our results , we conducted a probabilistic sensitivity analysis using Monte Carlo simulations ( n = 1 , 000 ) [47 , 48] , where we assumed selected distributions for each key input parameter including disease prevalence , treatment effectiveness , the percentage of paid workers in Madagascar , healthcare costs , and averted years of school absenteeism ( school years gained ) ( Appendix , S1 Table ) . We then extracted 95% uncertainty ranges ( UR ) capturing the uncertainty in our findings . We used R statistical software version 3 . 4 . 3 for all simulations . We also examined sensitivity to key input parameters , one at a time . First , we assumed that all drugs were donated by pharmaceutical companies , which may not always be the case , particularly after 2020 ( a number of large manufacturers have pledged to continue large medicinal donations under the London Declaration for the period 2014–2020 ) [49] . We therefore tested alternative input parameters for the drug costs: USD0 . 080/tablet for schistosomiasis ( praziquantel at 2 . 5 tablets of 600mg per person-year ) ; and USD0 . 045/tablet ( albendazole at 1 tablet of 400mg per person-year ) and USD0 . 004/tablet ( diethylcarbamazine ( DEC ) at 2 tablets of 100mg per person-year ) for STH and LF [50] ( Appendix , S2 Table ) . Second , we used the total cost of an entire NTD campaign to model each NTD intervention as an independent campaign with its own programmatic costs to further understand the contribution of each NTD subintervention ( as opposed to an ‘integrated’ program scenario ) . Our main model assumed that targeted individuals were independent of each other . In other words , we assumed that infections averted by preventive chemotherapy for LF infection were unrelated to those infections averted by preventive chemotherapy for STH . In practice , we may be “double-counting” the benefits of NTD interventions in cases where there is co-infection with multiple NTDs within the same individual . This may particularly be the case in contexts where individuals at risk of NTD infection are also those most likely to be co-infected . We therefore studied a conservative scenario where we assumed a “worst-case” scenario of 100% co-infection . In other words , we assumed that all NTD infections co-occurred within the same individuals . ( No data was available for Madagascar on the prevalence of co-infection with multiple NTDs within the same individual ) . To do so , we changed the following input parameters: we took the highest prevalence among NTDs in our target group and assumed that only those individuals were potentially infected with any of the other NTDs—in our application , the highest prevalence found was 26% among school-age children ( ascariasis ) ; and we used the lowest effectiveness for preventive chemotherapy among NTD interventions since the prevention of one NTD is insufficient without preventing other NTDs in co-infected individuals ( 13% , for trichuriasis preventive chemotherapy ) .
Our results were generally consistent across sensitivity analyses ( Appendix , S4–S6 Tables ) . When each NTD intervention was modelled independently with its own programmatic cost ( instead of an ‘integrated’ program ) , the benefit-cost ratio would range from 1 ( for trichuriasis preventive chemotherapy ) to 5 ( for schistosomiasis preventive chemotherapy ) . When adding drug costs to the campaign costs , the benefit-cost ratio would be reduced to about 4 ( S5 Table ) . Taking into account the possibility of co-infection with NTDs within the same individuals ( with the conservative 100% overlap ) , the benefit-cost ratio would be reduced to about 1 ( S6 Table ) .
We presented results for a comprehensive economic evaluation of five NTD interventions in Madagascar . We examined the likely consequences of scale-up of NTD preventive chemotherapy in averting infections , in addition to the potential household financial and education gains . This type of analysis distinguishes itself from a traditional cost-effectiveness analysis because it also includes non-health outcomes , allowing policymakers to make comprehensive decisions as they choose between alternative funding strategies given limited resources . The recent institution of the Sustainable Development Goals ( SDGs ) has garnered increasing attention to jointly improve health and financial protection ( SDG3 ) , reduce poverty ( SDG1 ) , and increase educational attainment ( SDG4 ) . Implementation of complementary investments across sectors is key to reducing and eliminating the NTD burden in the post-2015 development agenda [17] . This study examines the broader spectrum of societal benefits of NTD control . We modeled each NTD intervention in an ‘integrated’ scenario since NTD interventions are typically rolled out together to generate programmatic synergies [27 , 28] , including in Madagascar [21] . The cost of an NTD campaign targeted to school-going age children therefore covered the rollout of preventive chemotherapy for all five NTDs . As expected , the benefit-cost ratio increased substantially with integration . For schistosomiasis , for instance , mass treatment would have costed USD286 per DALY if rolled out independently of the other four NTDs . Similarly , NTD interventions may be rolled-out together or in combination with campaigns targeted to other diseases ( e . g . , immunization or nutrition fortification [2] ) . The integration of these services could further reduce costs through economies of scope , and produce synergistic effects not captured by our model . Our cost-effectiveness estimates are somewhat higher than those from previous studies [1] . For instance , a study estimated the cost-effectiveness of school-based mass treatment programs for STH with albendazole or mebendazole at about 2008 USD2-11 per DALY averted [2] . Mass treatment of school-age children in Côte d'Ivoire for STH and schistosomiasis together costed around 2014 USD118 per DALY averted relative to doing nothing [52] . Even though the variances around these estimates may still overlap , there may be a number of reasons for discrepancies between studies [2] . Our modeling , for instance , used effectiveness estimates from mass treatment campaigns in real-world settings that mirrored the scale-up of NTD control in Madagascar [34 , 35 , 38]; in more controlled settings , the efficacy of preventive chemotherapy for NTDs may be larger [53 , 54] . Other possible reasons for discrepancies include alternative choices of disability weights [46] or drugs [2] , as well as local social and environmental conditions [55] . A recent review on preventive chemotherapy for STH , however , suggests that most studies present results within the range of being highly cost-effective [56] , and NTD interventions seem one of the most cost-effective interventions in public health [1] . Nevertheless , our study presents a number of limitations . First , as with all cost-effectiveness analyses , our findings rely on the availability and quality of the evidence at hand . Limited robust evidence was available for the health , financial , and education burden assigned to NTDs , and the effectiveness of chemotherapy . In our review of the literature , we identified only limited evidence on the long-run education burden due to NTDs ( years of schooling lost ) [30 , 57 , 58] and we had no data on disease-specific healthcare usage and OOP spending for four out of five NTDs . Limited data was also available on the incidence of morbidity associated with chronic NTD infection . A recent systematic review on mass deworming , for instance , suggested that certainty in the evidence for long-term effects on educational outcomes was “very low” for STH control [59] . Consistent with the literature , uncertainty intervals around our estimates for cases of school absenteeism averted ( in school years gained ) were large . There is also controversy around the validity of evidence for schooling outcomes [60] . A trial in Kenya , in which school-based mass treatment with deworming drugs was randomly phased into schools found protective effects of NTD control on school absenteeism [15 , 30] . A recent replication study , however , found that deworming may be less effective than previously suggested [14 , 45 , 61] . Second , we did not capture all benefits or costs of NTD control . For instance , because preventive chemotherapy likely increases labor supply , it could create a fiscal externality through its impact on tax revenues [62] . Conversely , if deworming allows children to go back to school and attain a higher level of schooling , the government may need to invest more in education [30] . Third , the roll-out of NTD control in Madagascar is planned until at least 2020 [22] . The cost-effectiveness of NTD control will likely decrease over time as NTD prevalence reduces . Fourth , due to lack of data , we used disease prevalence although it may not be the best measure to examine interventions addressing macroparasites ( as opposed to viral or bacterial infections ) [63–65] . The morbidity associated with NTDs is typically experienced by individuals with high parasitemia , hence the impact of an MDA campaign on morbidity would come from reducing the intensity of infections with high parasitemia ( rather than prevalence ) . There may also be positive spillover effects for those not treated due to a reduction in the level of transmission [15 , 30] . In our modeling , we did not take into account benefits of curing morbidity in individuals who are still infected but with a lower intensity infection , or possible benefits for those who are not directly treated . These benefits are potentially large as well as long-term ( in the case of LF , chronic stages of disease such as hydrocele may be prevented providing health benefits accruing many years after MDA ) . Our modeling is static rather than dynamic , which would have otherwise captured additional synergies including transmission and indirect effects , but relied on additional data and assumptions around NTDs that is not available . Better data about the life history of NTDs is needed , including intensity of infection , disease severity , and their distributions , as well as transmission and indirect effects [65] . Fifth , the choice of drugs may affect our estimates . The government of Madagascar , for instance , has previously used mebendazole as antihelmintic instead of albendazole in a number of districts [21] , which may have fewer benefits due to its lower efficacy against hookworm infection [66] . Sixth , the disability weights for the DALYs are intended to be solely measures of losses of ‘optimal health’ , and are not intended to represent losses of economic productivity or well-being [63 , 65] . We used the disability weights in the absence of other data on productivity losses due to health , similar to the Copenhagen Consensus exercise [39] . Yet , we focused on school-age children with most long-run economic gains resulting from increased school attainment , which we took into account . Seventh , our analysis focused on the most prevalent NTDs in Madagascar but included little case management of NTDs with high rates of catastrophic expenditure ( average OOP treatment expenditures were used ) . We also did not examine impoverishment ( for example , the number of cases of poverty averted ) . Lastly , our economic evaluation approach is only one method for priority setting . Decision-makers should also consider ethical and political factors , health system constraints , and targeting individuals at high risk ( as opposed to the general population ) . Economic evaluations for health policy have typically focused on quantifying the health gains per given expenditure . Policymakers in low-resource settings , however , face difficult decisions balancing multiple sectorial goals and require evidence on how to jointly achieve health , economic , and education objectives . This study attempts to comprehensively model the health , financial , and education impact of national NTD control in a resource-limited setting , and contributes to our understanding of how health interventions can affect economic and education aims . | Neglected tropical diseases ( NTDs ) cause ill health and disability among the poorest people with extensive economic and social effects . Existing cost-effectiveness analyses , however , have typically focused on the health gains associated with the scale up of preventive chemotherapy . This misses the key fact that health investments can contribute to gains in other sectors leading to broader benefits of NTD control . This study determines the value for money of national NTD control across multiple sectors . We assess the potential health , financial , and education gains of NTD control in a setting where NTDs are highly endemic . We build on extended cost-effectiveness analysis methods to examine five interventions which governments aim to scale up nationally . We find that , per dollar spent , preventive chemotherapy could avert a substantial number of infections , disability-adjusted life years or DALYs , and cases of school absenteeism . Our analysis incorporates broader wealth and education gains into the economic evaluation of health interventions and therefore provides information about the efficiency of attainment of three Sustainable Development Goals . This study highlights the potentially large societal benefits of investing in NTD control . | [
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... | 2018 | Health, financial, and education gains of investing in preventive chemotherapy for schistosomiasis, soil-transmitted helminthiases, and lymphatic filariasis in Madagascar: A modeling study |
Cell elongation in rod-shaped bacteria is mediated by the Rod system , a conserved morphogenic complex that spatially controls cell wall assembly by the glycan polymerase RodA and crosslinking enzyme PBP2 . Using Escherichia coli as a model system , we identified a PBP2 variant that promotes Rod system function when essential accessory components of the machinery are inactivated . This PBP2 variant hyperactivates cell wall synthesis in vivo and stimulates the activity of RodA-PBP2 complexes in vitro . Cells with the activated synthase also exhibited enhanced polymerization of the actin-like MreB component of the Rod system . Our results define an activation pathway governing Rod system function in which PBP2 conformation plays a central role in stimulating both glycan polymerization by its partner RodA and the formation of cytoskeletal filaments of MreB to orient cell wall assembly . In light of these results , previously isolated mutations that activate cytokinesis suggest that an analogous pathway may also control cell wall synthesis by the division machinery .
Bacterial cells typically surround themselves with a cell wall exoskeleton made of the heteropolymer peptidoglycan ( PG ) . This structure is essential for cell integrity and understanding its biogenesis is of great practical significance because the pathway is a proven target for many of our most effective antibiotic therapies [1] . The PG layer is also the major determinant of bacterial cell shape such that studies of PG assembly are also of fundamental importance for determining the mechanisms responsible for bacterial growth and morphogenesis [2] . PG is composed of long glycan strands with a disaccharide repeating unit of N-acetylmuramic acid ( MurNAc ) -β-1-4-N-acetylglucosamine ( GlcNAc ) and a pentapeptide stem attached to the MurNAc sugar [3] . The strands are polymerized by membrane-embedded PG glycosyltransferase ( PGTase ) enzymes using the lipid-linked disaccharide-pentapeptide precursor called lipid II . The polymerized glycans are then crosslinked via the formation of amide bonds between attached peptides by transpeptidase ( TPase ) enzymes . Several different types of synthases with these activities work together to build what ultimately becomes a cell-shaped polymer matrix that envelops the cytoplasmic membrane and protects it from osmotic lysis . To direct PG matrix assembly during cell growth and division , most rod-shaped bacteria employ two multi-protein synthetic machineries organized by cytoskeletal filaments [2] . The Rod system ( elongasome ) utilizes the actin-like MreB protein to promote cell elongation and maintain cell shape , whereas the cytokinetic ring ( divisome ) uses the tubulin-like FtsZ protein to orchestrate cell division and the construction of the daughter cell poles . For many years , the main PG synthases of these machineries were thought to be the class A penicillin-binding proteins ( aPBPs ) [2] . These bifunctional synthases possess both PGT and TP activity to make PG , and until recently , the PGT domain of aPBPs was the only known family of PG polymerases . This view of PG biogenesis was called into question by the discovery of PG polymerase activity for the SEDS ( shape , elongation , division , and sporulation ) family protein RodA of the Rod system [4] . SEDS family proteins are widely distributed in bacteria [4 , 5] and are known to form complexes with class B PBPs ( bPBPs ) [6 , 7] , which are monofunctional TPases only thought to be capable of PG crosslinking . Thus , SEDS-bPBP complexes have been proposed to represent a second type of PGT/TP enzymatic system for PG synthesis , with FtsW-PBP3 and RodA-PBP2 functioning as the SEDS-bPBP pairs for the divisome and Rod system , respectively [4 , 8] . Although it remains possible that the SEDS-bPBP synthases work together with aPBPs in the same complexes , functional and localization studies suggest otherwise [8] . In both Escherichia coli and Bacillus subtilis , the aPBPs have been shown to display distinct subcellular localization dynamics from Rod system components and to be dispensable for the activity of the machinery [4 , 8] . It has therefore been proposed that a RodA-PBP2 complex forms the core PG synthase of the Rod system , an idea supported by recent evolutionary co-variation analysis [9] , and the finding that the aPBPs largely operate outside of the cytoskeletal system during cell elongation [8] . A similar division of labor between aPBPs and FtsW-PBP3 may also be taking place during cytokinesis , but the relative contributions of the two types of synthases to the division process requires further definition . The discovery that RodA is a PG polymerase raises many important questions about the function of the Rod system . Is the polymerase activity of this new synthase regulated , and if so , how is its activity controlled to maintain a uniform rod shape ? Does RodA work with PBP2 as proposed , and if so , how is the polymerase activity of RodA coordinated with the crosslinking activity of PBP2 ? Coupling of these activities is expected to be critical because its disruption by beta-lactam antibiotics is part of the lethal mechanism of action of these drugs [10] . For example , the beta-lactam mecillinam blocks the TP activity of PBP2 while leaving the activity of RodA unaffected . As a result , RodA generates uncrosslinked glycan strands that are rapidly degraded , causing a futile cycle of PG synthesis and degradation that is cytotoxic [8 , 10] . Thus , during its normal function , the Rod system is likely to possess a fail-safe that prevents RodA from initiating PG polymerization unless it is engaged with PBP2 to crosslink its product glycans . Finally , aside from MreB , RodA , and PBP2 , the Rod system typically includes the additional proteins MreC , MreD , and RodZ . Despite their broad conservation throughout cell wall producing bacteria , even in non-rod-shaped organisms lacking MreB [11] , the function of these additional Rod system components remains unclear . In this report , we describe the discovery of PBP2 variants that suppress the growth and shape defects of mreC hypomorphs . One of the altered PBP2 variants was shown to hyperactivate cell wall synthesis by the Rod system in vivo and to stimulate the polymerase activity of RodA-PBP2 complexes in vitro . Furthermore , studies of Rod system localization dynamics in the mutant cells indicate that the PBP2 variant promotes the formation of active Rod complexes by enhancing MreB filament formation . Overall , our results define an activation pathway for the cell elongation machinery in which PBP2 plays a central role in both stimulating PG polymerization by RodA and modulating MreB filament formation to orient new synthesis [12] . This mode of activation provides a built-in mechanism for coupling cell wall polymerization and crosslinking to prevent the toxic accumulation of uncrosslinked glycans . Moreover , the phenotypes of previously described cell division mutants [13–15] and our recent biochemical studies of FtsW in complex with its cognate bPBP [16] suggest that this activation pathway is conserved to control PG synthesis by the divisome .
In E . coli and other organisms , each protein within the Rod system is required for proper functioning of the complex [11 , 17–22] . Rod system defects result in a loss of rod shape and cell death under typical growth conditions , but spherical E . coli Rod- mutants can survive on minimal medium at low temperatures [18] . Thus , mutants inactivated for the Rod system can be constructed under permissive conditions ( minimal medium ) and suppressors of these defects can be isolated by plating the mutants on rich medium ( non-permissive conditions ) and selecting for growth . Starting with a ΔrodZ mutant background , this suppressor isolation strategy has been successfully used to investigate how the interaction between RodZ and MreB may modulate Rod system function [23 , 24] . We reasoned that similar selections for suppressors of other Rod system defects might help us understand how the PG synthetic enzymes within the complex are controlled . Defects resulting from a missense mutation are expected to be easier for cells to overcome in a suppressor selection than those due to a deletion allele . We therefore developed a strategy to rapidly identify missense alleles in Rod system genes that result in a stable yet defective gene product . In a report that will be published separately , we applied this method to mreC . Several defective mreC alleles were identified . The two mutants displaying the most severe defects encoded MreC proteins with a G156D or an R292H substitution ( Fig 1A ) . When the mreC ( G156D ) or mreC ( R292H ) alleles were constructed at the native mre locus , the resulting cells had a spherical morphology and failed to grow in rich medium ( LB ) , reminiscent of an mreC deletion ( Fig 1B and 1D ) . Although stable MreC protein accumulated in these mutants ( Fig 1C ) , the proteins were incapable of promoting Rod system activity . We therefore concluded that the MreC variants identified were functionally defective and therefore suitable for use in a suppressor analysis . Cells harboring the mreC ( G156D ) or mreC ( R292H ) alleles were plated on rich medium , the non-permissive condition for mutants defective for Rod system activity . Suppressors restoring growth arose at a frequency of 10−5 ( S1 Table ) . Many of these isolates remained spherical , indicating that they had likely acquired mutations that allow spheres to grow on rich medium . However , additional screening identified several isolates that grew with a long axis , indicating at least a partial restoration of rod shape . Of these suppressors , two displayed near normal rod shape and were chosen for further analysis . Whole-genome sequencing was used to map the location of the mreC suppressors . Both isolates harbored mutations in the pbpA ( mrdA ) gene encoding PBP2 , the PG crosslinking enzyme of the Rod system . Although the pbpA ( T52A ) allele was originally found to suppress mreC ( G156D ) and the pbpA ( L61R ) allele was first isolated as a suppressor of mreC ( R292H ) , neither suppressor was allele specific . Both were capable of suppressing the shape and viability defects of either mreC allele when the mutants were reconstructed in an otherwise normal parental strain background ( Fig 2A and 2B ) . However , pbpA ( L61R ) was more robust at restoring normal rod shape than the pbpA ( T52A ) allele . The changes in the altered PBP2 derivatives map to the membrane proximal region of the protein often referred to as the pedestal or non-penicillin-binding domain ( Fig 2C ) . In the solved structures of bPBPs [28–30] , this region consists of two interacting subdomains connected by a third subdomain forming a hinge that sits just underneath the catalytic TP domain . In a recently solved structure of an MreC-PBP2 complex from Helicobacter pylori , MreC interacts with the pedestal domain of PBP2 and in doing so causes its two interacting subdomains to swing open [27] ( Fig 2C ) . The alterations in PBP2 that suppress the MreC defects are not predicted to be at locations directly involved in the PBP2-MreC interface . Moreover , PBP2 derivatives with changes in the same region , PBP2 ( Q51L ) and PBP2 ( T52N ) , were previously shown to suppress a Rod system defect caused by a ΔrodZ mutation [24] . We therefore hypothesized that the conformational change in PBP2 induced by MreC may be part of a mechanism controlling PG synthesis by the core enzymatic components of the Rod system . We further reasoned that the PBP2 variants we identified might spontaneously achieve an activated conformation that stimulates PG polymerization and crosslinking such that they bypass the normal requirement for MreC and other components of the Rod machinery that may have regulatory functions . To begin testing our hypothesis , we assessed whether the strongest suppressor of mreC missense mutations , PBP2 ( L61R ) , could also suppress the shape and viability defects of mutants deleted for Rod system genes . This variant suppressed the growth defect of ΔrodZ cells and partially restored their shape as expected based on its similarity to previously isolated ΔrodZ suppressors [24] ( Fig 2E ) . PBP2 ( L61R ) also had the additional ability to suppress the growth defect of a ΔmreCD mutant and a ΔmreCD ΔrodZ triple mutant ( Fig 2D and 2E ) . Although rod shape was not fully restored in these cells , they displayed a long axis indicative of at least partial restoration of Rod system function ( Fig 2E ) . Notably , this PBP2 variant was incapable of suppressing the shape or viability defects of a ΔmreBCD mutation , even when the mreCD genes were expressed in trans ( Fig 2D , S1 Fig ) , indicating that the actin-like MreB protein remains essential for Rod system function in cells producing this altered PBP . These results are consistent with PBP2 ( L61R ) adopting an activated conformation that mimics that induced upon assembly of the complete Rod system . Furthermore , the observation that partial rod shape can be restored with just MreB , RodA , and a PBP2 variant suggests that these three proteins form the minimal and essential core of the system in cells that require MreB for rod shape . To determine whether the L61R variant of PBP2 generally promotes Rod system activity , the pbpA ( L61R ) allele was engineered into E . coli cells with an otherwise normal complement of Rod system components . The growth rate of these cells was indistinguishable from that of wild type in both rich and minimal medium ( S2 Table ) . However , the PBP2 ( L61R ) cells were ~20% longer and ~10% thinner than cells with PBP2 ( WT ) ( S2 Table ) , providing an early indication that the Rod system may be activated by the altered PBP2 [31] . To monitor Rod system activity more directly , we followed cell wall synthesis in cells radiolabeled with [3H]-meso-diaminopimelic acid ( mDAP ) , an amino acid unique to the PG stem peptide . For these studies , we used a previously described genetic background in which the divisome can be inactivated by an inducible copy of the FtsZ antagonist SulA and aPBP activity can be inhibited by the thiol-reactive reagent ( 2-sulfanatoethyl ) methanethiosulfonate ( MTSES ) [8] . Thus , when SulA is produced and MTSES is added , radiolabel incorporation is mediated principally by the Rod system and thus reflects its activity ( Fig 3A ) . Following divisome inhibition , PBP2 ( L61R ) cells synthesized PG at approximately twice the rate of wild-type cells ( 197 ± 10 nCi vs . 111 ± 2 nCi over ten minutes , p < 0 . 0001 , Fig 3B ) . This increased synthesis activity was retained upon MTSES inhibition of the aPBPs , indicating that it indeed reflected elevated PG incorporation by the Rod system ( 127 ± 1 nCi vs . 37 . 1 ± 0 . 3 nCi over 10 minutes , p < 0 . 0001 , Fig 3B ) . The increase radiolabel incorporation into PG was also accompanied by a corresponding decrease in the labeled pool of the precursor UDP-MurNAc-pentapeptide , indicating that flux through the PG synthesis pathway is likely increased in the PBP2 ( L61R ) cells ( Fig 3B , right ) . Immunoblot analysis and labeling with the fluorescent penicillin derivative Bocillin failed to detect any changes in MreB or PBP2 levels in cells harboring the altered PBP2 protein ( S2 Fig ) . We therefore conclude that PBP2 ( L61R ) is most likely activating PG synthesis by stimulating the activity of the Rod system . In addition to changes in PBP2 , RodA variants RodA ( A234T ) and RodA ( T249P ) were also previously identified as suppressors of a ΔrodZ mutation [24] . The rodA ( A234T ) mutant was reconstructed at its native locus and this suppression activity was confirmed . The change in RodA was also found to be capable of suppressing the growth and shape defects of mreC ( G156D ) and mreC ( R292H ) mutants ( Fig 4A and 4B ) . However , RodA ( A234T ) could not compensate for the deletion of Rod system genes other than rodZ , indicating that it is not as potent of a suppressor as PBP2 ( L61R ) ( Fig 4C and 4D ) . Nevertheless , the suppression results suggested that RodA ( A234T ) is also capable of activating PG synthesis by the Rod system . We therefore monitored PG synthesis in rodA ( A234T ) mutant cells and found that Rod system activity was indeed enhanced relative to wild-type ( 167 ± 3 nCi vs . 108 ± 6 over ten minutes , p = 0 . 001 , Fig 3C ) . In line with the relative suppression power of the variants , the observed PG synthesis activation by RodA ( A234T ) was not as great as that observed in cells producing PBP2 ( L61R ) . Based on the ability of RodA and PBP2 variants to stimulate PG synthesis by the Rod system we hypothesized that activation in both cases may ultimately result from the enhancement of PG polymerization by RodA . To test this possibility more directly , we used a modified radiolabeling assay in which the beta-lactam mecillinam was included . Mecillinam specifically blocks the TP activity of PBP2 but allows continued glycan polymerization by RodA [8] . We previously showed that the uncrosslinked glycans produced in mecillinam-treated cells are rapidly degraded by the lytic transglycosylase Slt to form soluble turnover products ( anhydromuropeptides ) [10] . Thus , in radiolabeled cells simultaneously inhibited for cell division and treated with mecillinam , the level of labeled turnover products produced provides a measure of RodA polymerization activity ( Fig 3D ) . Using this assay , we found that both RodA ( A234T ) and PBP2 ( L61R ) resulted in elevated PG turnover in mecillinam treated cells ( Fig 3E and 3F ) . Similar assays were performed to monitor the effects of Rod system variants on aPBP activity using the beta-lactam cefsulodin . This antibiotic specifically inhibits the transpeptidase activity of aPBPs such that PG turnover in cefsulodin-treated cells provides a measure of aPBP PG polymerase activity [8 , 10] . Cefsulodin-induced PG turnover was found to be reduced in both RodA ( A234T ) and PBP2 ( L61R ) containing cells ( S3 Fig ) , indicating a reduction of aPBP polymerase activity . This reduction in activity most likely reflects an increased competition for precursors between aPBPs and the activated Rod system . Based on the radiolabeling results we conclude that the RodA ( A234T ) and PBP2 ( L61R ) variants enhance Rod system function by promoting PG polymerization by RodA . The in vivo labeling results suggest the attractive possibility that changes in PBP2 structure , either through its interaction with MreC or the L61R substitution , can be communicated to RodA to activate PG polymerization . We therefore wanted to test this potential RodA activation mechanism in vitro using purified RodA-PBP2 complexes . To simplify purification of the complexes , we generated a RodA-PBP2 fusion protein with the two components connected by a linker ( GGGSx3 ) . A similar SEDS-bPBP fusion had been shown to be functional for Bacillus subtilis sporulation [7] . Our construct was also active in vivo as it largely restored rod shape to ΔpbpA-rodA cells ( S4 Fig ) . We therefore proceeded to purify a FLAG-tagged version of the wild-type fusion and fusions harboring either PBP2 ( L61R ) or RodA ( A234T ) . The fusions were produced in an E . coli expression strain lacking three of its four aPBP-type PG polymerases ( PBP1b , PBP1c , and MtgA ) to limit the potential for contaminating polymerase activity in the purified preparations . The resulting preparations were >90% pure with some observable lower molecular weight material ( Fig 5A ) . Most of this material is derived from cleavage of the fusion within the linker , as the ~70 kDa band corresponds to the molecular weight of PBP2 and can be labeled with bocillin , while the ~40 kDa band corresponds to the molecular weight of FLAG-RodA and binds to an anti-FLAG antibody ( S5 Fig ) . We first compared the polymerase activity of RodA-PBP2 ( WT ) with RodA-PBP2 ( L61R ) and RodA ( A234T ) -PBP2 . Purified lipid II substrate from E . coli was added to the fusions and the reactions terminated at various time points following initiation . The resulting products were then subjected to enzymatic labeling with biotin-D-lysine , separated using SDS-PAGE , transferred to a PVDF membrane , and detected with streptavidin conjugated to an infrared dye [32] . Mecillinam was included in the reactions to prevent glycan crosslinking by PBP2 so that polymer length could be determined without complications from crosslinking by PBP2 . All fusions promoted the production of glycan polymers that increased in abundance and apparent length over time ( Fig 5B and 5C ) . However , the RodA-PBP2 ( L61R ) generated product more rapidly than RodA-PBP2 ( WT ) and produced products that were longer ( Fig 5B and 5C ) . The length and amount of PG produced by RodA ( A234T ) -PBP2 was not statistically different than the wild-type fusion ( Fig 5B and 5C ) . Notably , the polymerase activity of all fusions was insensitive to moenomycin , an inhibitor that blocks aPBP-type PGT activity ( S6 Fig ) . Also , the polymerase activity of fusions with PBP2 ( WT ) and PBP2 ( L61R ) was completely blocked by a D262A substitution in RodA ( S6 Fig ) . An equivalent change was previously shown to inactivate the polymerase activity of B . subtilis RodA [4] . Therefore , the polymerase activity observed for the fusions is unlikely to be due to contaminating PBP1a , the only aPBP-type polymerase produced in the expression strain . We conclude that SEDS-bPBP complexes indeed form a functional PG synthase as proposed previously [4 , 8] , and that changes in the bPBP can be communicated to the SEDS protein to stimulate its PG polymerase activity . Fluorescent protein fusions to MreB and other Rod system components in E . coli and B . subtilis form multiple dynamic foci dispersed throughout the cell cylinder . These foci have been observed to rotate in a processive manner around the long axis of the cell [8 , 33–35] , and this motion is blocked by inhibitors of PG synthesis . Thus , the dynamic behavior of MreB and other Rod components is thought to be driven by the deposition of new PG material into the matrix with the speed of rotational movement reflecting the synthetic activity of the Rod complex . To further understand the mechanism of Rod system activation by the PBP2 ( L61R ) variant , we monitored its effect on the localization dynamics of MreB and PBP2 using total internal reflection fluorescence ( TIRF ) microscopy . An MreB sandwich fusion with mNeonGreen ( SWMreB-mNeon ) and an N-terminal monomeric superfolder-GFP fusion to PBP2 ( msfGFP-PBP2 ) were used for the imaging . Both fusions were previously shown to be functional [8] . SWMreB-mNeon foci displayed processive rotational movement in cells producing PBP2 ( WT ) or PBP2 ( L61R ) ( S1 and S2 Movies ) . The speed of rotational movement was unchanged by the PBP2 ( L61R ) variant ( Fig 6A and 6C ) . Similarly , msfGFP-PBP2 ( WT ) and msfGFP-PBP2 ( L61R ) formed foci that moved around the cell long axis with almost identical velocities ( S3 and S4 Movies , Fig 6B and 6C ) . Although the speed of particle motion was unchanged by the PBP2 ( L61R ) variant in each case , the number of moving particles per cell appeared to increase in cells producing the altered PBP2 . We therefore quantified the number of particle tracks per unit of cell surface area for each imaging experiment . Indeed , more directionally moving SWMreB-mNeon foci were observed per cell area in the PBP2 ( L61R ) producing cells versus those with PBP2 ( WT ) ( Fig 6D ) . Likewise , cells expressing msfGFP-PBP2 ( L61R ) possessed a greater number of directionally moving foci than those producing msfGFP-PBP2 ( WT ) ( Fig 6E ) . These results suggest that PBP2 ( L61R ) not only stimulates RodA polymerase activity , but also promotes the assembly of more active Rod complexes per cell . One possible way in which the PBP2 ( L61R ) variant could increase the number of active Rod complexes per cell is via enhancing the recruitment of MreB filaments to the membrane . To investigate this possibility , we measured the total SWMreB-mNeon fluorescence per cell by widefield illumination and the fluorescence at the cell surface using TIRF illumination . We then calculated the TIRF/widefield ratio for each cell as a measure of MreB membrane recruitment . To ensure equivalent illumination of cells producing PBP2 ( WT ) or PBP2 ( L61R ) , we introduced a cytoplasmic mCherry marker into one of the strains , mixed them , and performed the TIRF and widefield measurements on both strains simultaneously . Strain identity was then determined by the presence or absence of the mCherry marker ( S7 Fig ) . Two sets of measurements were made , one with the marked strain being PBP2 ( WT ) and the other with the PBP2 ( L61R ) strain being marked . The analysis revealed no significant change in the TIRF/widefield ratio of SWMreB-mNeon fluorescence between cells with either PBP2 ( WT ) or PBP2 ( L61R ) ( Fig 6F ) , indicating that the total amount of MreB recruited to the membrane is not altered by PBP2 ( L61R ) . The observation that the PBP2 ( L61R ) variant increases the number of directionally moving SWMreB-mNeon foci per cell without increasing the total amount of MreB at the membrane suggested that the altered synthase may be modulating MreB filament formation . To investigate this possibility , we imaged SWMreB-mNeon using structured-illumination microscopy combined with TIRF illumination ( SIM-TIRF ) . With this super-resolution method , clear filaments of SWMreB-mNeon were visible that displayed a dynamic circumferential motion like the foci observed at lower resolution ( Fig 6G , S5 Movie ) . Analysis of still images of cells with PBP2 ( WT ) or PBP2 ( L61R ) allowed us to measure the relative length of the fluorescent MreB filaments . Strikingly , the filaments observed in PBP2 ( L61R ) cells were on average significantly shorter than those found in cells producing PBP2 ( WT ) ( Fig 6H ) . This observation suggests that changes in PBP2 affect MreB polymer formation and/or dynamics . Accordingly , similar to previously isolated PBP2 and RodA variants , cells producing PBP2 ( L61R ) are resistant to the MreB antagonist A22 ( Fig 6I ) , indicating that MreB polymers are more stable in these cells in addition to being altered in length . Overall , the cytological results are consistent with a model in which the activation status of the core PG synthase of the Rod system is communicated to MreB to modulate filament formation so that PG synthesis promoted by the activated enzymes is properly oriented .
To gain insight into the regulation of the Rod system , we selected for suppressors of mreC missense mutants . Although the precise nature of the functional defect ( s ) caused by these mutations remains to be determined , they allowed us to identify two PBP2 variants that activate the Rod system . This activation both bypasses the need for some Rod system proteins , and hyperactivates the Rod system in otherwise wild-type cells . Characterization of the suppressor mutants combined with a recently solved structure of an MreC-PBP2 complex from H . pylori [27] supports a regulatory role for MreC in Rod system activation . In the structure of the MreC-PBP2 complex , MreC was found to induce a significant conformational change in the membrane-proximal pedestal domain of PBP2 , causing two of its subdomains to hinge open ( Fig 2C ) [27] . The amino-acid changes in PBP2 that suppress MreC defects mapped to the same region of the protein , suggesting that they may promote a conformation of PBP2 that mimics that induced by MreC . Biochemical and physiological results indicate that one of these altered PBP2 proteins , PBP2 ( L61R ) , not only suppresses MreC defects , it also stimulates Rod system activity in vivo and PG synthesis by RodA-PBP2 fusions in vitro . We infer from the combined set of results that the interaction between PBP2 and MreC is probably not just a scaffolding interaction as proposed previously [27] , but also likely serves a regulatory role in Rod system function by shifting the RodA-PBP2 PG synthase into an activated conformation ( Fig 7 ) . Although a direct role for MreC in promoting RodA-PBP2 synthase activity remains to be tested , such an activation mechanism would ensure that the PG synthase is only highly active in the context of the assembled Rod complex thereby providing spatiotemporal control over its function . In addition to suppressing the Rod system defect caused by missense alleles of mreC , the PBP2 ( L61R ) variant also promoted viability and partially restored rod-shape to mutants deleted for mreCD , rodZ , and a triple mreCD rodZ deletion . However , the same PBP2 variant failed to suppress an mreBCD deletion , indicating that MreB is needed for Rod system function even when the core enzymes are abnormally activated . This MreB-requirement most likely reflects the important role of MreB filaments in promoting rod-shape by orienting the motion of the synthetic enzymes [12] . In this regard , the ability of PBP2 ( L61R ) to promote partial Rod system function in the triple mreCD rodZ deletion is remarkable because it implies that MreB can interface directly with the RodA-PBP2 synthase . Thus , a cytoskeletal filament connected to a PG synthase complex appears to be the minimal functional unit of the Rod system in E . coli . The other components of the system are likely to be important for stabilizing the connection between RodA-PBP2 and MreB . However , because MreC , MreD , and RodZ are conserved along with RodA and PBP2 in ovoid and spherical bacteria lacking MreB , it seems unlikely that their sole function is to provide bridging interactions between the enzymes and MreB filaments . Instead , this conservation in combination with the suppression results with PBP2 ( L61R ) suggests that like MreC , MreD and RodZ are probably also involved in promoting the activation of PG synthesis by RodA-PBP2 , either directly or through an effect on the MreC-PBP2 interaction . PBP2 ( L61R ) cells were found to assemble more circumferentially moving MreB and PBP2 foci than PBP2 ( WT ) cells . Additionally , super-resolution microscopy revealed that the MreB filaments formed at the membrane were shorter in the cells with the activated PBP2 variant . An increase in polymer number with a corresponding decrease in length is expected if polymer formation is stimulated without a change in the monomer supply . PBP2 ( L61R ) was not found to alter the cellular MreB concentration or the total amount of MreB recruited to the membrane . Thus , the cytological results support a role for RodA-PBP2 activation in enhancing MreB polymerization , potentially by nucleating the formation of new polymers , either directly or through effects of the activated synthase on other Rod system components like RodZ [37] . Another connection between RodA-PBP2 activation and MreB polymerization comes from the observation that PBP2 ( L61R ) , and previously isolated PBP2 and RodA variants that are presumably also activated , confer resistance to the MreB antagonist A22 [24] , indicating that the altered synthetic machinery is likely to be directly or indirectly stabilizing MreB polymers in addition to promoting their formation . Finally , MreB filament formation at the membrane has previously been shown to be dependent on the availability of the RodA-PBP2 substrate lipid II in B . subtilis [38] . Taken together , these observations support a model in which factors upstream of MreB polymerization are important control points in Rod system assembly and activation . Given the regulatory roles for MreC , MreD , and RodZ implied by the genetic results , an attractive possibility is that the membrane and periplasmic domains of these proteins function as sensors that promote PG synthesis by the Rod system in response to chemical and/or physical signals from the cell envelope such as PG crosslinking status , membrane curvature , or physical strain [39 , 40] . In this scenario , MreB filaments would be polymerized at or recruited to sites where synthesis is activated by the membrane-embedded components . Once recruited , MreB could then act as a rudder to steer cell wall insertion along the circumferential axis [12] . It is also possible that the activation process is initiated by MreB polymerization induced by a different set of stimuli . Importantly , the two possibilities are not mutually exclusive , and it may well be that multiple inputs into the formation of active Rod complexes contribute to the robustness of the system in promoting rod shape . A major challenge moving forward will be to determine the molecular nature of the signals to which the Rod system is responding to trigger its synthetic activity . Complexes between SEDS and bPBPs have been well described for the divisome ( FtsW-PBP3 ) and sporulation ( SpoVE-SpoVD ) [6 , 7] . Therefore , following the discovery of PG polymerase activity for RodA , it was proposed that RodA-PBP2 and other SEDS-bPBP complexes form a functional PG synthase with both polymerase and crosslinking activity [4 , 8] . This possibility is supported by recent evolutionary coupling analyses and mutational studies indicating that a RodA-PBP2 complex formed through interactions between RodA and the pedestal domain of PBP2 is likely to be critical for Rod system function [9] . Here , we found that changes in the PBP2 pedestal domain can activate PG synthesis by RodA in vivo and stimulate the activity of RodA-PBP2 fusions in vitro . Together , these observations suggest that the RodA-PBP2 complex not only physically connects the two enzymes , but also serves as a regulatory conduit used to coordinate their activities . In this case , the genetic , biochemical , and structural data support a model in which conformational changes in the pedestal domain of PBP2 induced by MreC , likely in conjunction with other components of the system , are communicated to RodA to stimulate PG synthesis . This level of communication between the PGT and TP enzymes is attractive because it would provide a means to prevent RodA from robustly producing glycan strands without the ability to crosslink them . Otherwise , as revealed by experiments with the beta-lactam mecillinam , the production of uncrosslinked glycans by RodA when PBP2 is inactive results in a toxic futile cycle of glycan synthesis and degradation [10] . Based on analogy with RodA-PBP2 , FtsW-PBP3 has been proposed to be the core PG synthase of the divisome [4 , 8] . Recent biochemical studies from our laboratories indicate that FtsW indeed possesses PG polymerase activity and that this activity requires the formation of a complex with its cognate bPBP [16] . This finding is consistent with a required coupling between PG polymerase and crosslinking functions to prevent the formation of toxic uncrosslinked glycans . Genetic evidence in the literature also suggests that the FtsW-PBP3 complex is regulated by a mechanism analogous to that of RodA-PBP2 . Several gain-of-function alleles in the genes encoding FtsW and PBP3 were previously isolated as suppressors of division inhibitor overproduction in Caulobacter cresentus and E . coli [13–15] . Notably , FtsW ( A246T ) was one of the suppressors of division inhibition identified in C . cresentus [15] . This residue change corresponds to A234T in E . coli RodA , the exact change that we and others have found to activate PG biogenesis by the Rod system and suppresses defects in MreC and RodZ [24] . Moreover , the amino acid substitutions in PBP3 that suppress division inhibition in C . cresentus map to the N-terminal domain not far from where we have found alterations in PBP2 that hyperactivate the Rod system [14] . Thus , the genetic evidence points towards PG biogenesis by the divisome being activated by the FtsW and PBP3 variants such that normal regulatory controls governing the activity of the complex can be bypassed . The similarity of these changes to those in RodA and PBP2 that activate the Rod system suggest that SEDS-bPBP complexes within morphogenic machines are likely to be regulated by similar and broadly conserved mechanisms . This activation step therefore represents an attractive target for small molecule inhibitors for use in antibiotic development .
All E . coli strains used in the reported experiments are derivatives of MG1655 [41] . Strains were grown in LB ( 1% tryptone , 0 . 5% yeast extract , 0 . 5% NaCl ) or minimal M9 medium [42] supplemented with 0 . 2% casamino acids and 0 . 2% glucose ( abbreviated M9 CAA glu ) . Unless otherwise indicated , antibiotics were used at 25 ( chloramphenicol; Cm ) , 50 ( kanamycin; Kan ) , 50 ( ampicillin; Amp ) , or 5 ( tetracycline; Tet ) μg/mL . Growth conditions for microscopy experiments are described in the figure legends . Detailed information about strain and plasmid constructions can be found in S1 Text . All strains are listed in S3 Table and all plasmids are listed in S4 Table . Overnight cultures of PR5 [mreC ( R292H ) ] or PR30 [mreC ( G156D ) ] were grown at 30°C in M9 CAA glu . Serial dilutions of these cultures were plated on both permissive conditions ( M9 CAA glu agar at 30°C ) and conditions that are non-permissive for the growth and survival of spherical cells ( LB or LB supplemented with 1% sodium dodecyl sulfate ( SDS ) at 30°C or 37°C ) [19] . After 24 hours of incubation , colonies that appeared on the LB ( ± SDS ) plates were replica streaked on LB agar and LB agar supplemented with 10 μg/mL A22 . We reasoned that suppressor mutants that have restored Rod system function would be sensitive to A22 ( A22S ) , whereas mutants that had found an alternative means to survive on LB , such as overexpression of ftsZ , would be resistant to A22 ( A22R ) . All A22S isolates were visually screened to confirm restoration of rod cell shape using a Nikon Eclipse 50i microscope equipped with a 100x Ph3 DL 1 . 25 NA lens . We found that the A22S isolates tended to have elongated cell shape consistent with at least a partial restoration of Rod system function . Note that although the pbpA ( L61R ) mreC ( R292H ) double mutant identified in our suppressor selection and screen is A22S , a pbpA ( L61R ) mutant in an otherwise Rod+ cell promotes A22R . We infer from this differential A22 sensitivity that the pbpA ( L61R ) allele can promote Rod system function when either MreB or MreC function is disrupted but not when both proteins are disabled . Overnight liquid cultures of SDSR , A22S , rod-shaped isolates were grown in LB at 30°C , and genomic DNA was prepared using a Wizard Genomic DNA Purification Kit ( Promega ) and Genomic DNA Clean & Concentrator-10 Kit ( Zymo Research ) . Two different methods were used for whole genome sequencing of suppressor strains . Some suppressors were prepared for sequencing using a modified Nextera library preparation strategy , as described by Baym et al . [43] . Other suppressors were prepared for sequencing using the NEBNext Ultra DNA Library Prep Kit for Illumina according to manufacturer’s instructions . DNA concentrations were determined using the Qubit dsDNA HS Assay Kit and sizes were determined using a High Sensitivity D1000 screen tape run on an Agilent 4200 TapeStation system . Sequencing was performed using a MiSeq Reagent Kit v3 , with the Miseq System ( Illumina ) . Reads were mapped using the CLC Genomics Workbench software ( Qiagen ) . In each suppressor with a pbpA mutation that was sequenced , the alteration of pbpA was the only genomic change from the parental strain that was detected . Proteins were run on a 10% polyacrylamide gel and transferred to an activated PVDF membrane . The membrane was briefly rinsed , then blocked with 2% milk ( w/v ) in Tris-buffered saline , 0 . 1% Tween-20 ( TBS-T ) for 1 hour at room temperature . The membrane was then transferred to primary antibody solution , containing 0 . 2% milk ( w/v ) , rabbit anti-MreB [19] , rabbit anti-MreC ( 1:10 , 000 dilution ) , rabbit anti-FLAG ( Sigma cat# F7245 , 1 μg/mL ) , and/or mouse anti-RpoA ( BioLegend clone 4RA2 , 1:10000 dilution ) in TBS-T , and incubated for 16 hours at 4°C . The membrane was rinsed quickly , then washed three times for ten minutes in TBS-T . The membrane was transferred to a solution of secondary antibodies ( anti-rabbit 800CW and/or anti-mouse 680RD; Li-COR ) in 0 . 1% milk for 1 hour at room temperature . After four ten-minute washes in TBS-T , the membrane was imaged using either a Li-COR ODESSEY Clx scanner or a ProteinSimple FluorChem R imager . Bocillin-binding assays on membrane extracts were performed as described previously [8] . For bocillin binding assays of purified proteins , 8 . 3 μM of protein and 250 μM Bocillin-FL ( ThermoFisher cat# B13233 ) were incubated for 30 minutes at room temperature . The protein was then combined with sample buffer and 10 pmol/lane was run on a 4–20% polyacrylamide gel . Bocillin gels were imaged using a Typhoon 9500 fluorescence imager ( GE Healthcare ) with excitation at 488 nm and emission at 530 nm . Peptidoglycan precursor levels , synthesis , and turnover were determined as described previously [8 , 10] . The results were analyzed using a two-way ANOVA , followed by Tukey’s multiple comparisons test . His-SUMO-FLAG tagged versions of RodA-GGGSx3-PBP2 wild-type and mutant fusions ( encoded by pSS50 , pSS51 , pSS52 , pSS60 , and pSS62 ) were co-expressed with Ulp1 ( encoded by pAM174 ) in an E . coli C43 derivative of BL21 ( DE3 ) with deletions in ponB , pbpC , mtgA ( strain CAM333 ) [4] . CAM333/pAM174 cells with the desired pSS plasmid were grown at 37°C to an OD600 of 0 . 8 in 1L of Terrific Broth supplemented with 0 . 1% glucose and 2 mM MgCl2 . IPTG was then added to 1 mM to induce expression of the fusion protein , and arabinose was added to 0 . 1% to induce expression of Ulp1 . After induction overnight at 20°C , the cells were harvested by centrifugation . The cell pellets were resuspended in lysis buffer ( 50 mM HEPES pH 7 . 5 , 150 mM NaCl , 20 mM MgCl2 , 0 . 5 M DTT ) and lysed by passage through a cell disruptor ( Constant Systems Ltd . ) twice at 25 , 000 psi . Membranes were collected by ultracentrifugation at 100 , 000g for 1 hour at 4°C . The membrane pellets were mechanically resuspended with a Teflon dounce homogenizer and solubilized in buffer containing 20 mM HEPES pH 7 . 0 , 0 . 5 M NaCl , 20% glycerol , and 1% n-dodecyl-β-D-maltoside ( DDM ) for 2 hours at 4°C . Insoluble material was pelleted by ultracentrifugation at 100 , 000g for 1 hour at 4°C . The soluble fraction was removed and supplemented with 2 mM CaCl2 and applied to homemade M1 anti-FLAG antibody resin . The resin was washed with 25 mL of wash buffer ( 20 mM HEPES pH 7 . 0 , 0 . 5 M NaCl , 20% glycerol , 2 mM CaCl2 , 0 . 1% DDM ) . The FLAG-tagged constructs were eluted from the resin in 1 mL fractions with buffer containing 20 mM HEPES pH 7 . 0 , 0 . 5 M NaCl , 20% glycerol , 0 . 1% DDM , 5 mM EDTA pH 8 . 0 , and 0 . 2 mg/mL 3X FLAG peptide ( Sigma ) . The purity of the sample was assessed by SDS-PAGE . The final yield for each of the different fusion constructs was approximately 1 mg per 1 L of culture . A His-SUMO tagged version of the soluble domain of MreC ( amino acids 45–367 ) was purified and used for antibody production . Lemo21 ( λDE3 ) /pPR57 cells were grown in LB supplemented with ampicillin and 25 g/mL chloramphenicol and grown at 37°C until the OD600 reached 0 . 4 . Cells were then induced with 1 mM IPTG and grown for an additional 2 hours . Cells were pelleted and resuspended in buffer A ( 20 mM Tris-HCl ( pH = 8 . 0 ) , 300 mM NaCl , 0 . 5 mM DTT , 20% glycerol ) containing 30 mM imidazole . cells were disrupted by passing them through a French pressure cell twice at 15 , 000 psi . Cell debris and membranes were pelleted by centrifugation at 100 , 000 x g for 30 minutes at 4°C . The resulting extract was mixed with pre-equilibrated QIAGEN Ni-NTA agarose beads , then transferred to a column . The column was washed sequentially with buffer A containing 30 mM , 50 mM , and 100 mM imidazole , then eluted in buffer A containing 300 mM imidazole . The eluate was digested with His-Ulp1 to cleave the His-SUMO tag , dialyzed in buffer A , then run through the Ni-NTA column to obtain pure , untagged MreC . Purified protein was sent to Covance Inc . for the production of rabbit polyclonal antibodies . Purified proteins were concentrated to 10 μM using a 100 kDa MWCO Amicon Ultra Centrifugal Filter ( Millipore ) . Extraction of E . coli Lipid II was performed as described previously [32] . Peptidoglycan glycosyltransferase activity was assayed as previously described [44] . Briefly , Lipid II dissolved in DMSO ( μM ) was incubated with each purified protein ( 1 μM ) with 1X reaction buffer in a total volume of 10 μL for 20 minutes at room temperature , unless otherwise indicated . The reaction buffer contains 50 mM HEPES pH 7 . 0 , 20 mM MgCl2 , 20 mM CaCl2 , 200 μM mecillinam , and 20% DMSO . Moenomycin dissolved in DMSO was used at a final concentration of 3 μM . Reactions were quenched by incubation at 95°C for 2 minutes . Biotinylation of the peptidoglycan product was subsequently performed by addition of 2 μL of 20 mM Biotin D-Lysine ( BDL ) and 1 μL of 50 μM S . aureus PBP4 ( Kahne lab ) and incubation at room temperature for 1 hour . The reaction was quenched with 13 μL of 2X SDS-loading buffer . 5 μL of the final reaction was loaded onto a 4–20% polyacrylamide gel and was run at 180V for 35 minutes . The peptidoglycan product was transferred onto an Immune-Blot PVDF membrane ( BioRad ) . The Lipid II product , labeled with BDL , was detected by incubation with streptavidin-IRdye ( Li-COR , 1:10 , 000 dilution ) . To quantify blots of biotinylated products from glycosyltransferase assays , lane profiles were plotted using the Fiji gel analyzer tool [45] . Fragments larger than 48 kDa ( the molecular weight of PBP4 ) were defined as long PG fragments . Fragments smaller than 48 kDa but larger than lipid II were defined as short PG fragments . The signal intensity from long PG fragments , short PG fragments , and lipid II were quantified and normalized to the total signal intensity in the lane . Results were analyzed using a two-way ANOVA , followed by Dunnett’s multiple comparisons test . Growth conditions prior to phase-contrast microscopy are described in the figure legends . Where indicated , cells were fixed in 2 . 6% formaldehyde with 0 . 04% glutaraldehyde at room temperature for 1 h , followed by storage at 4°C for up to 3 days . Prior to imaging , cells were immobilized on 2% agarose pads containing the appropriate growth medium , and covered with #1 . 5 coverslips [46] . Phase-contrast microscopy was performed on a Nikon TE2000 microscope equipped with a 100x Plan Apo 1 . 4 NA objective , 0 . 90 NA condenser lens , and a CoolSNAP HQ2 monochrome camera ( Photometrics ) . Images were acquired using software NIS Elements AR 3 . 2 . Single-molecule tracking of MreB and TIRF:widefield determinations were performed on a Nikon Eclipse Ti microscope equipped with a 100x Plan Apo 1 . 45 NA phase contrast objective and a Hamamatsu ORCA-Flash4 . 0 V2 ( C11440-22CU ) sCMOS camera . Fluorescence imaging was performed using a 488 nm excitation laser ( Agilent Technologies ) and an ET525/50 bandpass emission filter ( Chroma Technology Corp ) . Image acquisition was performed using the Nikon Elements acquisition software . The microscope was maintained at 37°C using an environmental control chamber ( World Precision Instruments ) . All non-TIRF fluorescence imaging , as well as the single-molecule tracking of sfGFP-PBP2 variants were performed on a Nikon TiE instrument equipped with a 100x Plan Achromat 1 . 49 NA DIC objective , Andor Zyla 4 . 2 sCMOS camera , Ti-TIRF-EM Motorized Illuminator , a LUN-F laser launch with single fiber mode ( 488 , 561 , 640 ) , Chroma TRF-EM 89901 Quad band set , Ti stage up kit , and Sutter Emission filter wheel . Environmental conditions were maintained using an Okolab stage top incubator chamber and a Bioptechs objective heater . Laser intensity was optimized to minimize phototoxicity . Acquisition software was NIS Elements 4 . 30 . The purchase of this microscope was funded in part by grant S10 RR027344-01 . Sample preparation for fluorescence microscopy was performed as described previously [47] . Unless otherwise noted , cells were struck onto LB plates , inoculated in LB and grown overnight prior to back-dilution ( 1:500 ) into M9 minimal media on the day of imaging . Induction of Plac::SWmreB-mNeon ( from attλHC897 ) was achieved with 100 μM IPTG throughout the duration of liquid growth . Imaging of Plac::msfGFP-pbpA ( from attHKHC943 ) and Plac:msfGFP-pbpA ( L61R ) ( from attHKPR128 ) required streaking onto M9 plates supplemented with 15 μM IPTG , followed by similar liquid growth . All conventional TIRF imaging was performed at 1s intervals for 1min duration with continuous illumination . Analysis of phase-contrast images and widefield fluorescence was performed with Oufti [48] and MATLAB . Single-molecule tracking data was analyzed with the Fiji plugin TrackMate as described previously [8] . We discarded single-molecule trajectories if they consisted of < 5 consecutive frames and had a minimum displacement of < 70 nm . The number of tracks per cell was divided by the cell area determined by Oufti in order to normalize for cell shape differences . Cell areas were calculated as shown in S8 Fig . We acquired SIM-TIRF images on the DeltaVision OMX SR ( GE Healthcare Life Sciences ) . Imaging was performed using a 60x 1 . 42 NA PSF objective with N = 1 . 522 immersion oil , and a 1 . 3x tube lens to provide additional magnification . Images were captured using a pro . edge sCMOS camera . The sample was maintained at 37°C using the built-in Environmental Control Module . Fluorescence imaging was conducted using a 488 nm excitation laser and a bandpass emission filter ( 528±2 nm center wavelength , 48±2 nm bandwidth ) . Imaging was performed at 37°C using ~20 ms acquisitions ( 9 per frame , ~200 ms total ) at an interval of 1 s for 1–2 min duration . Images were acquired using the AcquireSR acquisition software ( Applied Precision ) . For each frame of a SIM-TIRF time lapse , 9 images were taken ( 3 phases at 3 angles ) ; these images were then reconstructed and the resulting time lapse was registered using the SI Reconstruction and Image Alignment functions in softWoRx ( Applied Precision ) . We determined SWMreB-mNeon polymer lengths from SIM-TIRF snapshots by applying custom MatLab software similar to that previously described for an alternative super-resolution imaging technique [49] . Briefly , individual filaments deemed by eye to be entirely within the illumination area were rotated to a central axis and line-scanned ( 2-pixel width ) . Length was defined as the total number of contiguous pixels above local threshold ( i . e . background + 50% ) and reported in nm . Note , however , that the resolution of the imaging method is unlikely to provide an accurate measure of absolute filament length . Nevertheless , given that all SIM-TIRF images result from the same fluorescent fusion protein and were imaged under the same conditions and reconstructed with the same parameters , we believe that these measurements provide a valid comparison of relative filament length between strains . Also note that the average measured MreB filament filled ~½ of the total cell width in WT cells versus ~⅓ of the total cell width for cells with PBP2 ( L61R ) . Thus , a greater percentage of MreB filaments in WT cells had endpoints extending beyond the cell perimeter relative to cells with PBP2 ( L61R ) . Many long filaments in WT cells were therefore not measured such that our analysis is likely to have underestimated the length difference for MreB polymers between the two strains . Widefield illumination provides a depth-of-field of ~800 nm , approximating the entire fluorescent population within a cell . TIRF illumination provides a narrow depth-of-field ( ~200 nm ) and approximates the membrane-associated population nearest the coverslip-sample interface . We assessed the relative abundance of the membrane-associated fraction of SWMreB-mNeon within individual cells by calculating the ratio of the cumulative fluorescence intensity under TIRF and widefield . However , since TIRF intensity is highly affected by small changes in incident angle and z-focus , it is difficult to accurately compare separate TIRF:widefield datasets . Consequently we imaged both samples simultaneously . To differentiate the two strains , we expressed cytoplasmic mCherry ( pAAY71 ) in either MG1655 attλHC897 or PR78 attλHC897 ( S7 Fig ) . We used data from both imaging pairs for analysis ( Fig 6F ) . | The cell wall of bacteria determines their shape and protects them from osmotic lysis . Two enzymatic activities are required for cell wall synthesis: glycan polymerization and crosslinking . A major new family of glycan polymerases was recently discovered and was proposed to work in complex with crosslinking enzymes called penicillin-binding proteins ( PBPs ) . How the activities of these enzymes are coordinated to prevent the toxic generation of uncrosslinked glycans has remained unknown . Our analysis of the cell elongation system of Escherichia coli has revealed that this coupling is mediated by changes in the PBP that activate glycan chain synthesis by the polymerase . Furthermore , we present genetic evidence that this activation event is mediated by a component of the elongation machinery with a previously unknown function . Discovery of this activation pathway provides new mechanistic insight into the cell wall biogenesis process and identifies a new avenue to disrupt it for antibiotic development . | [
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The modification of transcriptional regulation has become increasingly appreciated as a major contributor to morphological evolution . However , the role of negative-acting control elements ( e . g . silencers ) in generating morphological diversity has been generally overlooked relative to positive-acting “enhancer” elements . The highly variable body coloration patterns among Drosophilid insects represents a powerful model system in which the molecular alterations that underlie phenotypic diversity can be defined . In a survey of pigment phenotypes among geographically disparate Japanese populations of Drosophila auraria , we discovered a remarkable degree of variation in male-specific abdominal coloration . In testing the expression patterns of the major pigment-producing enzymes , we found that phenotypes uniquely correlated with differences in the expression of ebony , a gene required for yellow-colored cuticle . Assays of ebony’s transcriptional control region indicated that a lightly pigmented strain harbored cis-regulatory mutations that caused correlated changes in its expression . Through a series of chimeric reporter constructs between light and dark strain alleles , we localized function-altering mutations to a conserved silencer that mediates a male-specific pattern of ebony repression . This suggests that the light allele was derived through the loss of this silencer’s activity . Furthermore , examination of the ebony gene of D . serrata , a close relative of D . auraria which secondarily lost male-specific pigmentation revealed the parallel loss of this silencer element . These results demonstrate how loss-of-function mutations in a silencer element resulted in increased gene expression . We propose that the mutational inactivation of silencer elements may represent a favored path to evolve gene expression , impacting morphological traits .
The role of repression in transcriptional regulation dates back to our initial glimpses of its molecular mechanisms [1] . While activating transcriptional control sequences , referred to as “enhancers” , contain binding sites for both activating and repressive transcription factors [2] , some repressors act globally within gene loci to prevent the activation of multiple enhancers [3] . Such long-range inputs into gene regulation are contained within negative-acting sequences , often referred to as “silencers” [4] . Our current understanding of silencer function and evolution has lagged far behind that of the positive-acting enhancers . This is , in part , due to the difficulty associated with identifying negatively-acting elements in the expansive non-coding regions surrounding genes . A growing number of studies have demonstrated how the alteration of gene regulation is critical to the evolution of morphology [5] . Hundreds of examples of gene regulatory sequence evolution have now been identified [6 , 7] , and many of these have been shown to directly affect morphology [8–12] . In particular , many traits within Drosophila have provided a fruitful platform in which to connect phenotypic differences to changes in gene regulatory sequence [13–15] . These cases frequently require the characterization of complex regulatory regions that have multiple enhancer elements . However , published studies of gene regulatory evolution have generally focused on positively-acting enhancers , and have not addressed the role of negative-acting silencers in the evolution of gene expression , or their role in generating phenotypes . The varied pigment patterns of the Drosophilid abdomen have provided fertile ground for advancing an understanding of gene regulatory evolution and its impact on phenotype [16–21] . The Drosophilid abdomen is divided into flexible segments protected by cuticular plates known as tergites that are secreted by an underlying epithelium . Patterned expression of melanin synthesis enzymes within this epithelium determines the ultimate cuticle pigmentation phenotype . In particular , coordinated expression of the genes yellow , tan , and ebony are broadly associated with pigment patterns across a wide range of species [8 , 17 , 19 , 21] . Previous work on the regulation of ebony in the abdominal epithelium has revealed a complex architecture of enhancers and silencers that govern its patterning [18] . ebony mRNA is specifically restricted from the posterior body segments of Drosophila melanogaster males to promote sexually dimorphic pigmentation . In more anterior body segments , ebony transcripts are limited to the anterior portion of each tergite that will produce a yellow color . A positively acting enhancer located 3 . 7 kb upstream of the transcription start site drives expression throughout the abdomen , a pattern that is ectopic relative to the endogenous pattern of ebony mRNA . This ectopic activity is restricted in vivo by two silencers . One silencer is located between 1 . 5 and 1 . 3 kb upstream of the promoter , and is required for the sexually dimorphic restriction of ebony transcripts from the male abdomen . A second silencer element residing within the first intron of ebony further restricts activity from the posterior edges of tergites . In a previous study , we demonstrated that both silencer activities were conserved to D . prostipennis , a species closely related to D . melanogaster [21] . The complex regulatory apparatus of the ebony locus stimulates the question of how silencers participate in the evolution of gene regulation . Here , we explore the genetic basis of intraspecific variation in pigment patterns within the montium subgroup species D . auraria across Japan , and find that transcriptional silencers play a key role . Despite invariant patterns of tan and yellow expression , pigmentation patterns in this species correlated with ebony gene expression . Examination of the D . auraria ebony gene revealed that the upstream male-specific silencer element present in D . melanogaster is conserved , as it is located in a similar position relative to the ebony promoter . By localizing mutations in cis to ebony , we found that this conserved silencer was mutationally inactivated in a light D . auraria strain , an event that we found to be repeated in an additional montium subgroup species , D . serrata . The parallel inactivation of the same element suggests that the mutational loss of silencer elements may provide a simple and frequently traversed evolutionary path to increases in gene expression .
While the degree of female pigmentation is often highly variable within Drosophilidae species [22] , variation in male coloration is relatively rare [20 , 21] . Our examination of D . auraria strains from Japan revealed an unexpected diversity of male-specific pigmentation patterns . In the montium subgroup , males exhibit reduced pigmentation limited to the single posterior-most tergite , as exemplified by D . auraria ( Fig 1 ) . Pigmentation in this group is also marked by several parallel losses of melanic color , such as the case of D . serrata ( Fig 1 ) [16 , 21] . Among different D . auraria populations , the male phenotype continuously varied from dark individuals in which the entire A6 segment was pigmented to substantially lighter individuals in which dark pigmentation was limited to the posterior edge of the A6 tergite ( Fig 2B–2E ) . The fully pigmented dark phenotype mirrors other closely related outgroups within the montium subgroup ( Fig 1 ) , supporting the inference that light pigmentation is the derived state within this species . We were next curious how this variation might align with environmental variation . Many examples of clinal variability in insect pigmentation show trends of correlation between pigmentation and altitude or longitude [23] . In fact , within D . auraria , one such cline in female pigmentation was observed across Korea [24] . To determine whether male pigmentation varies clinally , we quantified the average pigmented area of A6 tergites for 29 isofemale lines of D . auraria across Japan ( Fig 2A and Table 1 ) . There was no significant correlation between this character and altitude , longitude , or latitude ( S1 Fig ) . However , we noted a high degree of variation within each line ( Table 1 ) , suggesting that the light phenotype may be quite prevalent among the natural populations . Each isofemale line contains not only the genetic composition of the female that was caught , but also that of one or more males . As isofemale strains are cultured for multiple generations in the lab , this genetic variation would be expected to drift somewhat randomly . Because of this , we cannot be sure if the average pigmentation of a line is representative of the population from which it was derived . To look at the geographic prevalence of different phenotypes , we assessed the presence or absence of the dark or light phenotype within each line . We observed that lines in which the dark phenotype was present were collected from higher latitudes compared to lines in which this phenotype was absent ( logistic regression: λ21 = 7 . 09 , p = 0 . 0078 , S1F Fig ) . This data suggests that the dark phenotype may be maladaptive at lower latitudes . We next set out to elucidate the molecular mechanisms underlying the observed phenotypic variation within the D . auraria population . Three genes , yellow , tan and ebony , are known to play a major role in the patterning of pigment through the enzymatic conversion dopamine derivatives [25–27] . The activity of Yellow is required for the production of dark , black pigment while Ebony converts dopamine intermediates to yellow-colored sclerotin . Tan promotes darker pigments by catalyzing the reciprocal reaction to Ebony . To date , these genes have been found to be expressed in a coordinated pattern in which yellow and tan are co-expressed [17] , while ebony is expressed in a reciprocal pattern [18 , 28] . Currently , these genes encode the only enzymes in the pathway known to exhibit sharp expression patterns during abdominal development . Previously , it was shown that these correlated and mutually excluded spatial relationships of yellow , tan , and ebony expression are preserved during evolutionary shifts in pigment pattern [8 , 17 , 21] . To evaluate how the pigmentation pathway had been modified within D . auraria , we compared the expression of yellow , tan and ebony in strains for which males consistently had dark or light pigmentation . Surprisingly , both yellow and tan expression was indistinguishable among strains , despite striking differences in phenotype . yellow was expressed throughout the A6 segment and in repeated patterns along the posterior edges of each tergite ( Fig 3E–3H and S2 ) . Regardless of phenotype , this pattern did not differ between light and dark strains . in situ hybridizations localizing tan revealed expression restricted to the stripe pattern along the posterior edges of tergites , as well as a pattern along the midline of the A6 tergite that strongly foreshadows the pigmentation phenotype of dark strains ( Fig 3I–3L and S3 ) . However , this midline pattern of tan also appeared in lighter strains that lack this pigmentation phenotype . Our expression data with tan and yellow provide an example in which these two genes exhibit non-overlapping patterns of expression . Further , this represents a rare example in which yellow and tan expression was found to poorly correlate with pigmentation phenotype . In contrast to yellow and tan , ebony expression correlated well with variation in male tergite pigmentation . Dark strains of D . auraria express ebony throughout the abdomen , save for the A6 tergite , in which only the lateral edges broadly accumulate transcript ( Fig 3M and 3N ) . The medial region of A6 lacks ebony transcript , correlating with the dark pigmentation that forms in this region . For light strains , we observed that ebony expression was expanded into the dorsal portion of the A6 tergite in a pattern that correlates with this derived phenotype ( Fig 3O and 3P ) . In variable strains that have mixtures of phenotypes , we observe both light and dark ebony expression phenotypes ( S4 Fig ) . These results are consistent with a role of ebony in patterning the variable pigmentation phenotypes of D . auraria . We next set out to characterize the D . auraria ebony regulatory region to determine what role it may play in the diversity of D . auraria male pigmentation phenotypes . The pattern of ebony expression in D . melanogaster is controlled by at least three interacting cis-regulatory elements [18] . These regulatory activities are revealed in transgenic reporter assays when , in isolation , the distal activating enhancer drives strong expression in both endogenous and ectopic abdomen regions [18 , 29] . The ectopic activity of this enhancer is counterbalanced by a promoter proximal silencer element that prevents expression in the pigmented posterior segments of males ( depicted in Fig 4A ) . Although this upstream enhancer and silencer architecture is conserved within the oriental lineage [21] , the full extent of its conservation remains unknown . Our finding that ebony transcript is reduced in the pigmented A6 body segment of D . auraria males raised the possibility that a conserved mechanism governs the dimorphic expression of this gene . We cloned the entire upstream region of ebony from a dark strain of D . auraria ( “PM” , Fig 3A ) into a green fluorescent protein ( GFP ) reporter vector ( Fig 4A and S5 Fig ) . This reporter construct , which included the region orthologous to the abdominal enhancer and the male-specific silencing element was tested in transgenic D . melanogaster . We found that the reporter transgene’s expression precisely recapitulated the lateral pattern of ebony expression observed in the A6 tergites of dark D . auraria males ( compare Fig 4B to Fig 3M ) . To determine if an orthologous male-specific silencer sculpts this pattern in D . auraria , we tested a series of truncations that would remove this potential silencer , leaving behind only sequences orthologous to the activating enhancer ( Fig 4A ) . The first truncation had no effect on the lateral pattern of expression ( Fig 4C ) . A larger truncation , CD2 resulted in marginally reduced , but visible repression along the dorsal midline ( Fig 4D ) . The third truncation , which removed all sequences orthologous to the D . melanogaster male-specific silencer , resulted in a nearly complete elimination of midline repression ( Fig 4E ) . These results establish the ancestrally conserved regulatory architecture at ebony , in which a conserved silencer collaborates with a pan-abdomen activating enhancer to sculpt out zones of contrast in expression . The presence of a conserved silencer in the ebony upstream region that controls the midline repression of ebony in the A6 segment raised the intriguing possibility that this silencer may have been inactivated in light strains . To compare the function of ebony regulatory sequences between light and dark strains , we cloned the orthologous upstream region of ebony from a light strain ( “00” , Fig 3D ) into our transgenic reporter system . The light and dark strains differed by several sequence polymorphisms , including a large insertion/deletion of repetitive sequence near the activating enhancer that is absent in the light strain sequence ( Fig 5A ) . We inserted a transgenic construct containing the light strain’s ebony upstream region into the same genomic landing site that was used for our tests of the dark strain sequence . Although the light and dark strains differed slightly in activity in the more anterior A4 body segment ( Fig 5G ) , the light strain’s regulatory region recapitulated its expanded expression throughout the A6 tergite relative to the dark strain ( Fig 5C ) . From this , we conclude that the observed differences in ebony expression between light and dark D . auraria strains are due to cis-regulatory mutations . Next , we were curious whether the mutations in the ebony upstream region were localized to the known activating or silencing CREs , or outside of these defined activities . To directly compare the activities of the abdominal enhancer region between light and dark strains , we cloned the CD3 truncation from the light strain construct ( Fig 5A ) . As expected , this region drove expression throughout the A6 tergite ( Fig 5F ) . The light and dark CD3 constructs subtly differed ( by 13% ) in the intensity of expression driven in the A4 body segment ( Fig 5H ) . These data indicate that some differences may exist in the abdominal enhancer between the light and dark strains . To localize the mutations responsible for differences in A6 midline repression between light and dark strains , we generated a series of chimeric reporter constructs in which a segment of the dark or light strain ebony upstream region was replaced with the analogous segment from the other strain ( Fig 5A ) . Among these chimeric reporters , the phenotype of expression was dictated by which allele was present at the promoter-proximal silencer element . This is exemplified by the phenotypes of two constructs ( Fig 5A ) , in which a 2 . 2 kb promoter proximal fragment containing the silencer could switch activity from the dark expression phenotype to the light phenotype or vice versa ( Fig 5D and 5E ) . Chimeric reporters that contained larger segments surrounding the silencer element similarly displayed the coinciding phenotype of the allele present at the silencer element ( Fig 5A and S6 Fig ) . However the degree of male repression quantitatively differed in subtle , but repeatable ways . Specifically , chimeras whose breakpoints were located at the center of the upstream region displayed more intermediate repression phenotypes ( “act ( L ) + sil ( D ) #2” , “act ( D ) + sil ( L ) #2 Fig 5A and S6 Fig ) . This suggests the presence of mutations in the light strain sequence that can enhance repression but are context dependent . Overall , these observations establish that the increase in ebony expression in the light strain occurred primarily through mutations affecting the ebony male-specific silencer element . The inactivation of existing functional elements is often a favored mechanism during evolutionary change [30] . We were therefore curious whether a similar evolutionary path marked parallel alterations in pigmentation . Drosophila serrata is a montium subgroup species that has secondarily lost male-specific pigmentation ( Fig 1 ) . Examination of ebony expression in D . serrata males revealed that four independent lines exhibited broad expression throughout the posterior segments ( Fig 6A and S7 Fig ) . To test whether this alteration in ebony expression in D . serrata was due to cis-regulatory mutations in the gene , we cloned its orthologous upstream region including the activating enhancer and promoter-proximal silencer into our transgenic reporter system ( S5 Fig ) . Consistent with a cis-regulatory basis for this expression phenotype , the ebony upstream reporter recapitulated the endogenous D . serrata ebony expression pattern ( Fig 6B ) . To test whether this was indeed due to a mechanism similar to that observed in D . auraria , we replaced a 1 kb segment containing the male-specific silencer of the D . auraria dark strain with orthologous sequences from D . serrata ( Fig 5A , “act ( D ) + sil ( serrata ) ” ) . This chimeric construct drove expression throughout the A6 body segment similar to that of the full D . serrata ebony sequence ( compare Fig 6C to 6B ) , confirming the parallel inactivation of this silencer element .
While many differences in female-specific or body-wide pigmentation have been described among Drosophilids [20 , 22 , 31 , 32] , examples of variation in male-specific pigmentation are comparably lacking . Intriguingly , a clear cline exists for D . auraria females in Korea , and yet the pigmentation phenotypes of males in this population were reported to be invariant [24] . From our survey across Japan , a distinct trend emerged in which females were relatively invariant , while males exhibited a remarkable degree of variability . Several adaptive mechanisms have been invoked to explain phenotypic variation in pigmentation ( e . g . thermoregulation [33] , desiccation resistance [34 , 35] , UV resistance [36] ) . However , examples that contradict these trends highlight how pigmentation does not confer a “one size fits all” universal benefit [37 , 38] . Our tests for geographical correlations failed to support a traditional cline , though this may have been hampered by the small number of lines tested and the high degree of phenotypic variation within each line ( Table 1 ) . Indeed , when we controlled for intra-line variation by characterizing the range of phenotypes contained within , we found that lines bearing the dark phenotype occurred at higher latitudes than those lacking this phenotype ( S1F Fig ) . This result follows the general trend of latitudinal clines for pigmentation [39 , 40] , and suggests that the dark phenotype may be maladaptive at lower latitudes . Given the high degree of variation present within the population , a further examination of wild-caught males , possibly taking into account other factors such as seasonal variation or habitat structure may reveal forces that have shaped the phenotypic variation observed within this species . The coordinated evolution of pigmentation enzyme expression has become the rule , rather than the exception with Drosophila coloration phenotypes [8 , 17 , 21 , 28 , 41] . Across the abdomen , expression of yellow and tan are highly correlated [17 , 21] , while ebony is typically anti-correlated with these two [18 , 21] . Our data on the variable pigmentation of D . auraria provides an exception to this rule in which both tan and yellow are expressed in the A6 tergite , regardless of the pigmentation phenotype ( Fig 3 ) . Indeed , these two genes show consistent discord in their expression patterns , as yellow is expressed throughout A6 in contrast to the highly patterned expression of tan in the dorsal portion of the tergite . An additional layer of uncoordinated expression is introduced by ebony , which is deployed in the same cells as yellow and tan in strains that display the light phenotype . The lack of correlation of tan and yellow with pigmentation ( Fig 3 ) , and the inability of ebony mis-expression to erase all dark pigmentation in D . melanogaster in isolation [28] suggests that additional genes likely contribute to the variation we have observed in D . auraria . Previously , we showed how a recent interspecific expansion of pigmentation involved coordinated changes in yellow , tan , and ebony [21] . In this example , the yellow gene was shown to have evolved an expanded pattern in cis , independent of tan and ebony , whose expression differences were due to changes in one or more upstream factors . Considering these results in light of our current findings , the structural genes of the Drosophila pigmentation gene network appear to quite readily evolve new domains of expression independent of one another . An emerging theme from endeavors to connect genotype to phenotype is a bias towards certain molecular paths of evolution [6 , 42] . An ever-growing body of work has established that changes in gene regulation represent a commonly traversed path during the evolution of morphological differences [5 , 7] . It is thought that the specific genes that contribute to phenotypic variation may also be biased , due to their positions within networks [7] . This trend extends to the Drosophila pigmentation system , as yellow , tan , and ebony have been repeatedly implicated in cases of phenotypic evolution [8 , 16–19 , 21 , 31 , 43 , 44] . One common source of genetic bias is the tendency for loss rather than gain of genetic elements [6 , 30 , 42 , 45] . This is thought to be due mainly to mutational target size , as there are many more possible mutations that would inactivate a genetic element than those which would build a new one [42] . Consequently , if a phenotype can be achieved through inactivation , there will undoubtedly be many more possible degenerative routes than constructive ones . The present work highlights how the trend of loss extends to negative acting gene regulatory elements whose inactivation will increase gene expression . Several examples of morphological evolution have been linked to the loss of transcriptional activating enhancer elements [9 , 13 , 17 , 43] . A striking example is that of the shavenbaby gene , in which multiple enhancers that contribute to its larval denticle patterning function were inactivated [13] . Despite the existence of many other loci that could contribute to this trait , some of these exact same elements were inactivated in an independent case of trichome loss , suggesting bias in the genetic path of evolution of this particular trait [46] . Because gene regulatory regions are subdivided into modular subunits that act relatively independently , the loss of an enhancer’s activity should be minimally pleiotropic , affecting only one or a small number of tissues . Similarly , the pleiotropic consequences of inactivating a single silencer element are predicted to be minimal , as effects will be limited to tissues where the silencer is actively suppressing an enhancer’s activity . While the existence of long-range repressors in metazoan regulatory architecture has been appreciated for nearly three decades [4 , 47] , their identification and characterization has lagged behind that of the enhancer elements that activate transcription . This disparity is almost certainly due to the way regulatory elements are experimentally characterized by fusing small ( generally less than 10kb ) overlapping fragments of potential regulatory DNA to reporter genes , and monitoring activity in the tissue of interest [29] . However , such tests will be at a disadvantage to uncover more complex relationships between elements , including insulators [48 , 49] , promoter-tethering elements [50 , 51] , and silencers [4 , 47] . As such , it is almost a certainty that many silencers have gone unnoticed within well-characterized regulatory regions . For example , ectopic activity is frequently observed when enhancers are trimmed down to minimal elements [52 , 53] . In the ebony regulatory region , ectopic activity of our reporter transgenes was conspicuous , given the large size of the adult abdominal epithelium and the sharply contrasting patterns of expression that we observed in vivo [18] . This stimulated a more comprehensive search of the locus for negative-acting elements . The complexity of regulatory architecture at ebony lends itself well to disentangling the interplay of gain and loss of regulatory inputs during evolution . For example , our previous study of intraspecific variation at the ebony gene revealed a gain-of-function mutation that caused reduced expression in D . melanogaster [18] . Of five function-altering substitutions that reduced expression in a high altitude population , we observed that the largest effect substitution paradoxically resided outside of the activating enhancer for the abdomen . This contradiction was reconciled by an experiment in which the altered residue was deleted , leading to a marked recovery of enhancer activity . As we obtain a more detailed understanding of the molecular events underlying gene regulatory evolution , the distinction between loss and gain of function at the molecular versus genetic levels will become more frequently resolved . This is a crucial step in interpreting and predicting how regulatory variants influence phenotype .
Fly stocks were maintained on standard media at room temperature . Isofemale lines of D . auraria were collected in hanging traps and GPS coordinates of the collection site were recorded . See Table 1 and S1 Table for a list of species and strains used in this study . Strain pigmentation phenotypes were measured by collecting flies without CO2 anesthetization on the day of eclosion and aging 5 days at 25°C to normalize cuticular tanning . We then anesthetized aged flies , mounted the adult abdomens to double-sided sticky tape on slides , and imaged the abdomen using standard settings on a Leica M205 microscope . Images were quantified using the ImageJ program [54] to measure the area of the tergite that was pigmented , divided by the total area of the tergite , yielding a percent pigmentation score . The relationship between strain pigmentation and latitude , longitude , and altitude was analyzed by nominal logistic regression . in situ hybridization was performed as previously described [17] . Templates for probes were cloned into the pGEM vector , and PCR amplified to contain an Sp6 or T7 promoter present in the pGEM multiple cloning site ( see S2 Table for probe primers used in this study ) . in vitro transcription of probes was performed using a 10X Dig labeling mix ( Roche Diagnostics ) in combination with T7 or Sp6 RNA polymerase ( Promega ) . Pupal samples were aged to differing extents for each probe ( 75–90 hours after pupal formation ( hAPF ) for yellow , 85–95 hAPF for tan , and at eclosion for ebony ) , dissected in cold PBS , and fixed in 4% paraformaldehyde ( E . M . S . Scientific ) . All in situ hybridizations were performed using an Insitu Pro VSI robot ( Intavis Bioanalytical Instruments ) . Fragments of the ebony gene were PCR amplified from genomic DNA using the primers presented in S3 Table . The light and dark strain constructs were amplified from the “00” and “PM” stocks ( Fig 3 and S1 Table ) , while the D . serrata reporter was cloned from the UCSD “03” strain ( S1 Table ) . Chimeric constructs were generated by overlap extension PCR to fuse light and dark strain non-coding regions together . PCR products were cloned via appended restriction sites into the S3aG vector [15] , which contains a minimal promoter driving enhanced nuclear GFP , flanked by gypsy and Sfb insulators . The S3aG vector contains an attB site for site-specific integration into the genome [55] . Transgene constructs were inserted into the 51D landing site on the second chromosome [55] by Rainbow Transgenics . Multiple independent lines were analyzed for each construct . Homozygous transformants were aged for 8–9 hours post-eclosion to maximize the signal to noise ratio of abdominal expression , as weak expression occurs in the abdomen during pupal development . Abdomens were mounted on slides in halocarbon oil , and imaged on an Olympus Fluoview 1000 confocal microscope using standardized non-saturated settings . Multiple images per line were acquired , and the degree of A6 midline expression was quantified by measuring the average intensity of a 50x50 pixel square at three positions along the A6 tergite ( left , right , middle ) . The intensity value of the midline was divided by the average of the left and right side measurements . | One of the greatest challenges in understanding the relationship between genotype and phenotype is to discern how changes in DNA affect the normal functioning of genes . Mutations may generate a new function for a gene , yet it is frequently observed that they inactivate some aspect of a gene’s normal capacity . Investigations focused on understanding the developmental basis for the evolution of anatomical structures has found a prevalent role for mutations that alter developmental gene regulation . In animals , genes are transcriptionally activated in specific tissues during development by regulatory sequences distributed across their expansive non-protein coding regions . Regulatory elements known as silencers act to prevent genes from being expressed in certain tissues , providing a mechanism for precise control . Here , we show how a silencer that prevents expression of a pigment-producing enzyme in certain Drosophila species has repeatedly been subject to inactivating mutations that increased this gene’s expression . This example illustrates how such negative-acting regulatory sequences can represent a convenient target for increasing gene expression through the loss of a genetic element . | [
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] | [] | 2015 | Genetic Changes to a Transcriptional Silencer Element Confers Phenotypic Diversity within and between Drosophila Species |
High-resolution HLA typing plays a central role in many areas of immunology , such as in identifying immunogenetic risk factors for disease , in studying how the genomes of pathogens evolve in response to immune selection pressures , and also in vaccine design , where identification of HLA-restricted epitopes may be used to guide the selection of vaccine immunogens . Perhaps one of the most immediate applications is in direct medical decisions concerning the matching of stem cell transplant donors to unrelated recipients . However , high-resolution HLA typing is frequently unavailable due to its high cost or the inability to re-type historical data . In this paper , we introduce and evaluate a method for statistical , in silico refinement of ambiguous and/or low-resolution HLA data . Our method , which requires an independent , high-resolution training data set drawn from the same population as the data to be refined , uses linkage disequilibrium in HLA haplotypes as well as four-digit allele frequency data to probabilistically refine HLA typings . Central to our approach is the use of haplotype inference . We introduce new methodology to this area , improving upon the Expectation-Maximization ( EM ) -based approaches currently used within the HLA community . Our improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood ( ML ) solution . These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner . We also show how to augment our method in order to incorporate ethnicity information ( as HLA allele distributions vary widely according to race/ethnicity as well as geographic area ) , and demonstrate the potential utility of this experimentally . A tool based on our approach is freely available for research purposes at http://microsoft . com/science .
HLA nomenclature is closely tied to the levels of possible HLA ambiguity . Each HLA allele is assigned a letter ( or letters ) which designate the locus ( e . g . , A , B , and C for class I; DRA , DRB1 , DRB2-9 , DQA1 , DQB1 , DPA1 , DPB1 , for class II . ) This letter is followed by a sequence of numbers , such as A*0301 , for one allele at the A locus . The first two digits describe the allele type; in most cases the first two digits correspond to the historical serological antigen groupings . Low resolution HLA typing refers to alleles which are reported at this two-digit level ( e . g . , A*03 ) . The third and fourth digits are used to designate the allele subtypes , wherein alleles are assigned numbers from 01–99 roughly according to their order of discovery . A minimum of four digits thus uniquely defines any allele: by definition , any two alleles which differ in their four-digit number , differ by at least one amino acid . For example , A*0301 and A*0302 do not encode the same protein sequence . Because two-digit names are exhausted after 99 alleles , there are a few oddities in the nomenclature . For example , A*02 and A*92 belong to the same two-digit class as do B*15 and B*95 [14] . ) See http://www . anthonynolan . org . uk/HIG/lists/nomenlist . html and [2] for more nomenclature details . Sometimes more than four digits are used to designate an allele: the fifth and sixth digits are used to distinguish alleles which differ only by synonymous substitutions ( i . e . , do not change the amino acid sequence of the protein ) , while the seventh and eighth digits distinguish alleles which differ in sequence in the non-coding regions of the gene ( i . e . , the introns or the 5′ or 3′ untranslated regions ) . For the purpose of our work , we omit this level of detail and limit our analysis to the four-digit level only . In any case , there is not enough data available at the six-to eight- digit resolution level to do any substantial statistical modeling . Assuming that HLA resolution beyond four digits are ignored , there are still various levels of ambiguity that can arise from molecular ( DNA ) -based HLA typing methods . For example , rather than knowing unambiguously which two A alleles a person has , one may instead know only a list of possibilities; for example , A*0301-A*3001 or A*0320-A*3001 or A*0326-A*3001 . Such intermediate resolution types may result from sequence-specific PCR ( SSP ) based typing where testing with the initial set of PCR primers will yield a list of possible genotypes that a particular person might have ( which may require further testing with additional combinations of allele-specific primers and/or cloning and sequencing of clones before an unambiguous type is achieved ) . As previously mentioned , even modern sequence-based methods may result in ambiguous allele combinations ( if sequenced alleles differ outside the genotyped region , or if different possible allele combinations result in the same pattern of observed nucleotide mixtures ) . Depending on the clinical and/or research purpose of the HLA typing , additional laboratory testing required for achieving high-level ( i . e . , four-digit ) resolution are often not performed for reasons relating to time and cost . In many cases , intermediate-level resolution data are truncated to two-digit resolution; in the previous example , this individual would be reported as having HLA alleles A*03 and A*30 . Although related but different HLA alleles ( for example , those alleles which share the same first two digits ) sometimes share immunogenic properties , higher resolution data allows for more precise and informative downstream use ( e . g . , [15] ) . We are thus motivated to develop low-cost techniques for improving resolution , such as the statistical method introduced here . The input to our statistical HLA refinement method consists of two data sets . The first is data of interest that have not been typed unambiguously to a four-digit resolution , but for which we would like to increase the resolution as much as possible . The second input is a set of training data consisting of four-digit resolution HLA types for individual people , where the population is drawn from one that is the same ( or , in practice , as similar as possible ) to the population of interest for which we wish to refine HLA types . First we train our model on the training data . Then we apply this trained model to our limited-resolution data of interest . For example , if a patient in our data set of interest was typed ambiguously at the A locus as having either ( 1 ) A*0243 , A*0101 , or ( 2 ) A*0243 , A*0122 , then our statistical model assigns a probability to each of these two possibilities . More generally , our model assigns a probability to any number of possibilities ( not just two ) , and over many loci . To date , we have used our method , without computational difficulty , to refine up to four loci with 20–130 alleles at each locus , and , on data sets with up to half a million possible haplotypes . To be precise about what kind of HLA typing ambiguities our approach can tackle , we emphasize that in principle , our approach can handle any kind of ambiguity , so long as that ambiguity has been resolved in the training data set , and so long as the ambiguity can be defined as an allele or set of alleles , taking on some number of clearly defined possibilities . Two common ambiguities that are of interest to researchers are i ) molecular allele ambiguities , in which we know that one allele , specified unambiguously ( e . g . , A*02 ) is actually one of several possibilities ( i . e . , A*0201 , A*0202 , A*0203 , etc ) , and ii ) genotype ambiguities , in which ambiguity arising when various combinations of alleles from both chromosomes produce the same patterns of heterozygous nucleotides in the chromatogram ) . In this paper , we focus our experiments on the first type of ambiguity , although our approach should work on the second kind as well . It may also be of interest to predict high-resolution HLA types from serological data . So long as it is known which serological types map to which molecular types , our model can , in principle , tackle these types of data . At the core of our HLA typing refinement model is the ability to infer and predict haplotype structure of HLA alleles across multiple loci ( from unphased data , since this is the data that is widely available ) . If certain alleles tend to be inherited together because of linkage disequilibrium between them , then clearly this information can help us to disambiguate HLA types—and far more so than using only the most common allele at any particular locus . We derive a method for disambiguating HLA types from this haplotype model . Existing methods for haplotype modeling fall into three main categories: ad hoc methods , such as Clark's parsimony algorithm [16] which agglomerates haplotypes starting with those uniquely defined by homozygous alleles; EM-based maximum likelihood methods , such as those belonging to the family introduced by Excoffier and Slatkin , and Hawley and Kidd [17] , [18] , which are related to the so-called gene-counting method [19]; and full Bayesian approaches , such as those introduced by Stephens et al . [20] , with more recent advances by others ( e . g . , [21] , [22] ) . Clark's method is no longer used , as it is outperformed by other methods . The full Bayesian methods are more principled than the EM-based methods because they average over all uncertainty including uncertainty about the parameters . However , full Bayesian methods are generally much slower than EM-based methods , and their convergence is generally more difficult to assess [23] , making them less attractive for widespread use . The haplotype modeling part of our approach is most closely related to the EM-based maximum-likelihood methods , although it differs in several crucial respects . To our knowledge , all implementations of EM-based maximum likelihood haplotype models use a full ( unconstrained ) joint probability distribution over all haplotypes ( i . e . , over all possible alleles , at all possible loci ) with the exception of the partition-ligation algorithms noted below . Furthermore , because they are maximum-likelihood based , they do not smooth the parameter estimates , thereby allowing for unstable ( i . e . , high variance ) estimates of rare haplotypes . Together , these two issues make existing methods difficult to scale to a large number of loci or to a large number of alleles per locus . This scalability problem is widely known ( e . g . , [17] , [24] , [25] ) , and several attempts to alleviate it have been suggested , such as eliminating posterior states which can never have non-zero probability [24] , or using a heuristic divide-and-conquer strategy , called partition-ligation [26] , [23] in which the joint probability distribution over haplotypes is factored into independent blocks of contiguous loci , and the solutions to each block are then combined . Although these approaches do help alleviate the problems of scalability , the former does so in a fairly minimal way , and the latter places heuristic constraints on the nature of the solution ( through use of the blocks ) . Furthermore , these methods do not address scaling in the number of alleles , which is the larger concern for HLA typing . In addition , these methods do not address the stability of the statistical estimation procedure . Our EM-based approach tackles the issues of scalability by using a parsimonious haplotype parameterization . This especially helps for scaling up to the large number of alleles in HLA data . Our approach also addresses stability by using MAP ( maximum a posteriori ) parameter estimation rather than an ML estimate . We note that within the HLA community , even recently , haplotype inference seems to be exclusively performed with the most basic EM-based algorithm of Excoffier and Slatkin , and Hawley and Kidd [17] , [18] ( e . g . , [27] , [28] , [29] , [30] , [31] , [32] , [33] ) . In fact , in one of the most recently available publications , Maiers et al . were unable to perform haplotype inference for more than three HLA loci , resorting to more heuristic techniques beyond this number . With our approach , such limitations are not reached . In addition , as we shall see , our approach is more accurate . There are two pieces of work which tackle the allele refinement problem using haplotype information: that of Gourraud et al . in the HLA domain [12] , and that of Jung et al . in the SNP ( single nucleotide polymorphism ) domain [34] . Although Gourraud et al . indirectly tackle the HLA refinement problem , their focus is on phasing of HLA data in the presence of ambiguous HLA alleles , and their experimental evaluation is restricted to the phasing task . Additionally , they use the standard , multinomial , EM-based haplotype inference approach , which we show to be inferior for the task of HLA refinement . Also , they do not investigate population-specific effects as we do here . Jung et al . , strictly speaking , don't refine their data . Rather , they impute it—that is , they fill in data that is completely missing . The SNP domain is quite different from the HLA domain—the problem of SNP haplotype inference often involves hundreds or thousands of loci , and there are usually only two alleles at each locus ( and at most four ) . HLA haplotype inference , in contrast , involves only a handful of loci with possibly hundreds of alleles at each locus ( because we define a locus on an HLA level , not a nucleotide level—although one could do HLA haplotype inference in the nucleotide domain ) . Thus , issues of scalability and the specific nature of haplotypic patterns are substantially different between these two domains . With respect to methodology , Jung et al . perform imputation in a sub-optimal way . First , they apply an EM-based haplotype inference algorithm ( [23] ) to obtain a single best phasing of their data ( i . e . , a ML point estimate ) . Next , using the statistically phased data , they compute linkage disequilibrium in the inferred haplotypes using the standard measure of Lewontin's linkage disequilibrium . Thus , they ignore the uncertainty over phases which is available from the EM algorithm . Also , they choose only the single best imputed value , ignoring the uncertainty there as well . Our approach incorporates both types of uncertainty . Lastly , the haplotype inference algorithm used by Jung et al . does not account for population-specific effects . Consequently , they do not investigate this area experimentally , as we do here , showing its potential benefits . One other study touches on statistical HLA refinement [31] . In order to estimate haplotype frequencies on serologically-derived HLA data , Muller et al . modify the standard EM-based haplotype inference approach to be able to use donors with unsplit serological HLA types . However , their main purpose is to estimate haplotype frequencies ( at a two-digit serological level ) rather than to perform HLA refinement; and their experiments focus on this former task .
First , we describe a model for p ( l1 , l2 , l3 , ) that uses far fewer parameters than the full table . Using the chain rule of probability , we can write ( 2 ) Equation 2 does not introduce any conditional independencies . If we were to use a ( conditional ) probability table for each of these three local distributions , then this model would capture exactly the same information as Equation 1 and would not reduce the number of parameters . However , instead of using conditional probability tables , we use softmax regression functions ( also known as multilogit regression ) [37] , [38] . A softmax regression function is an extension of logistic regression to more than two target classes . Using a softmax regression function to parameterize , the probability that the allele at the third locus is the kth allele , conditioned on the alleles at the other two loci , l1 , l2 , we have ( 3 ) where are parameter vectors of the softmax regression—one for each possible allele , j , at the third locus . Thus , the softmax regression function takes a linear combination of the input features , , plus a constant term , , to model each class , which produces a real-valued number for each class . Then , this real-value is exponentiated , and normalized relative to all of the other classes , to yield the probability of interest . Similarly , the softmax regression function for in Equation 2 is written as and for p ( l1 ) , trivially , aswith respective parameters , and . Because the alleles at each locus are discrete in nature , we use a binarized version of the inputs . That is , we use a one-hot encoding , wherein each discrete input , li = k is represented by a binary vector of length Li that contains all zeros , except at the kth position , which contains a one . Correspondingly , the parameter vectors are augmented in length to match this dimensionality . Thus , in this binary representation , the length of each wk would be L1+L2+1 , and the total number of scalar parameters required to represent p ( l1 , l2 , l3 , ) would be M = L3 ( L1+L2+1 ) +L2 ( L1+1 ) +L1 ( 1 ) . Note that M grows much more slowly here as compared to L for the multinomial tables . In particular , L grows exponentially in the number of loci and alleles , whereas M grows only linearly . Use of full tables versus the softmax regression function relates to the well known bias–variance trade-off [37] which states that the more flexible a model , the more variance one will have in estimating its parameters . To reduce variance , one can decrease the flexibility of the model ( as we have done by using softmax regression rather than multinomial parameterizations ) , thereby increasing the bias of the learned model ( because the family of possible models is more restricted ) . Whether one has chosen a suitable bias-variance trade-off is normally assessed empirically . In the experimental section , we show that the use of the softmax regression function improves the accuracy of the HLA refinement task over use of a multinomial parameterization . This softmax-based model can be easily extended , by direct analogy , to more than three loci , and far more efficiently than can the multinomial-based model . We note that the additive nature of the softmax regression functions leads to the property that similar haplotypes have similar joint probabilities . Coalescent priors used in some Bayesian approaches also have this property , whereas full tables do not . We use the EM algorithm to train our model—that is , to choose good settings of the softmax parameters ( wj , vj , and qj ) given observed genotype data . The way in which EM operates for our model is very similar to the way in which it works for the multinomial-based models . Again , we iterate between an E-step , where the posterior over possible phases is computed , followed by an M-step , where the parameters of the model are computed based on the posterior computations from the E-step . The difference , of course , is that the posterior uses our softmax model to compute the posterior , and our M-step estimates softmax-regression parameters rather than multinomial parameters . Formally , let gd be the observed genotype/HLA data for the dth person in our data set . For example , if we have data for three loci , HLA-A , HLA-B , and HLA-C , then we would have unphased data for each chromosome , for each locus , . There are 2number of loci−1 possible unique phase states , hid , that this data can take on ( assuming no ordering of the chromosomes ) : For the E-step , we compute for each data point , for each possible phase . This computation is easily accomplished by determining the likelihood of the data in each possible phase state , and then renormalizing these within each person so that . Here , we assume that each phasing is a priori equiprobable . The likelihood of one datum in a particular phase state , lid is given by the product of the likelihood under our haplotype model , for each of the two chromosomes . For example , the likelihood for the dth genotype to be in phase state 2 is given by ( 4 ) and renormalization of these likelihoods gives us the posterior over phase states for a single individual , For the M-step , we use the E-step posteriors to compute the parameter estimates . As mentioned , we use MAP parameter estimates which are generally more stable . For the prior distribution of each parameter , we use a zero-centered Gaussian distribution . The use of this parameter prior is sometimes referred to as L2 smoothing or L2 regularization , because its use is equivalent to adding a penalty term to the log likelihood that consists of the square of the L2 norm of the parameter vectors . Thus , whereas in a maximum likelihood setting we would , in the M-step , maximize the quantitywhich is the expected complete log likelihood , with respect to the softmax parameters , wj , vj , and qj , we instead maximize the quantitywhere denotes the L2 norm of vector x . This quantity is the regularized expected complete log likelihood . The regularization parameters , λ = ( λ1 , λ2 , λ3 , ) , which are ( inversely ) related to the variance of the Gaussian prior , are set empirically using a hold out set . Because this MAP estimation problem is embedded inside of an M-step , the regularization parameters are theoretically not independent ( except for λ1 because it does not depend on the phasing of the data ) , and hence must be adjusted jointly . We describe how we do so in the experimental section . The use of other parameters priors is possible . One commonly used alternative is the Laplacian prior or , equivalently , L1 regularization . In experiments not reported here , we have found L2 and L1 regularization to provide comparable performance on our task . By iterating between the E-step and the M-step from some chosen parameter initialization ( or , some posterior initialization ) , we are guaranteed to locally maximize the log posterior of the data , L , ( keeping the λj fixed ) , We note that one can smooth/regularize the parameters of the multinomial table using a Dirichlet prior . This smoothing has the effect of adding pseudo-counts to the observed counts of the data when computing the ML estimate during the M-step . In our experiments , we compare our model against both the traditional multinomial haplotype model and a Dirichlet regularized multinomial model . The ML ( and L2-regularized MAP ) softmax regression parameter estimation problem within a single M-step is a convex problem , and hence not subject to local minima . In contrast , L ( λ ) is not convex due to unobserved phase and is subject to local minima . Nonetheless , in our experiments , we did not find local minima to be a large problem , and leave further discussion of this to the Experimental section . As with the traditional algorithm used in the HLA community , our EM algorithm assumes random mating . In the discussion , we propose one way to remove this assumption . As discussed , we first train our model using the EM algorithm on a data set consisting of four-digit resolution HLA data from a population similar to that of our data of interest . We then use the model to probabilistically refine our lower-resolution data set . To do so , we refine each person's HLA type independently of the others . The way we do so , is to exhaustively write out a list of all possible unique four-digit phasings that are consistent with each person's observed genotype data . We do so by first writing out all possible ( mixed resolution ) phases , and then expanding each of these to all possible four-digit phases . For example , if one person's observed genotype in the data set of interest was , then we obtain ( 5 ) ( 6 ) ( 7 ) ( 8 ) Expanding Equation 5 , for example , we then obtain , Similarly , we expand each of Equations 6–8 to obtain an additional J2 , J3 , and J4 possible four-digit phasings . The total number of possible four-digit phasings consistent with this person's observed genotype is thus J = J1+J2+J3+J4 . Alternatively , if our data set of interest contains genotype-ambiguity ( in the form of possible pairs of alleles ) , then we expand the data in all possible ways consistent with those pairs . If our desired endpoint is a statistical estimate of phased four-digit data , then we need only compute and renormalize the likelihood of each member of the list ( to get the posterior probability of each pair of four-digit haplotypes ) . However , usually we are interested in a probability distribution over the possible four-digit genotypes . To obtain this distribution , we sum the posterior probabilities of those members of the list that are consistent with each observed genotype . For example , and would give rise to the same observed genotype: ( A*3030 , A*3002 , B*5713 , B*0801 , Cw*0401 , Cw*1502 ) , and so their posterior probabilities would be summed together ( along with any other entries in the list which mapped to the same observed genotype ) to obtain the posterior probability of that genotype . Because haplotype patterns are often population ( ethnicity ) -specific , a natural approach is to use separate models for each population , when the populations are known . For example , if the low-resolution data of interest pertained primarily to individuals of European descent , then one would train a model using data from a European population . Or , if the low-resolution data consisted of both European and Amerindian populations , then one would train a model on European and Amerindian populations separately , and then refine the data of interest using the appropriate model . Nonetheless , it is likely that some haplotype patterns are population-specific whereas others are not , or far less so . Consequently , it would be useful to combine data across populations , so that as much data as possible is available for parameter estimation . The challenge of course is how to combine data when appropriate , to maintain population-specific training data when appropriate , and to make good choices automatically . One way to achieve this goal is to augment the feature space ( which so far consists of binary encodings of HLA alleles ) with population features . We can , for example , include a one-hot encoding of the population labels in our features . Alternatively or in addition , we can add features that correspond to conjunctions of the one-hot encodings of allele and population label . Whereas the first type of augmentation , which we refer to as simple , allows us to weight the importance of a haplotype by a linear combination of populations , the second type of augmentation , which we call conjunctive , allows us to model specific haplotype–population interactions . In the evaluation section , we shall see that such leveraged population models can improve performance . Furthermore , we shall see that the first type of augmentation provides a winning effect over training populations separately and that adding the second type of augmentation leads to no additional improvement in the data set examined . The idea of leveraging information across multiple populations is closely related to some of our previous work on epitope prediction in which we show how to leverage information across HLA alleles [39] , and is an instance of what is sometimes called multi-task learning [40] . Xing et al . use a hierarchical Bayesian model to achieve a similar approach when inferring SNP haplotypes [22] . One could imagine using a mixed-resolution data set of interest ( which contains some four-digit HLA types ) as its own training data since EM naturally handles incomplete data . If the data that are missing four-digit resolution information are ignorable , then such an approach is straightforward [41] . By definition , data that are ignorable have the property that the probability that a particular datum is missing ( in this case , does not have a four-digit HLA type ) is independent of the true , underlying value of the missing datum ( in this case , the four-digit HLA type ) . Of course , if the data are not ignorable , then such a procedure can produce large errors . Unfortunately , missing high-resolution HLA data are not likely to be ignorable , and hence we require an independent data set with no missing data . To assess statistical significance of the difference of the performance of two models ( e . g . , softmax compared to multinomial ) , either in terms of the number of correct MAP predictions , or , in terms of the test log likelihood , we used a non-parametric , permutation-based , paired test , wherein the null hypothesis is that the average of the pair wise difference in scores is zero . Suppose the test set contains D individuals , 1 , , D , and that each model , m , assigns a score , , to each individual ( where again , this score is either the log probability of the correct assignment , or the number of correct MAP predictions ) . Then to compare two models , m1 and m2 , we do the following: We used data sets from two main sources , and denote the number of individuals in each by N . The first data set is a collection of private data derived from a large collection of disease cohorts and controls that were all typed in the laboratory of Mary Carrington . This data set comprises data from four populations , across three loci , as summarized in Table 1 . Note that most of the African data are derived from African-American individuals , with a small proportion from outside the United States ( N = 776 ) . The Hispanic and European data are solely US-based , while the Asian data originated in Asia . Because alleles C17 , C18 and A74 were almost never fully resolved to four digits in this data set , we left these as two digit designations . All but 0 . 1% of HLA alleles in the private data set represented common and well-defined alleles ( as classified in [42] ) . Because these large data sets comprise numerous smaller data sets ( and sub-populations ) , we tested each data set , at each locus , for deviance from Hardy-Weinberg Proportions ( HWP ) using the conventional MCMC approximation to the exact test [43] . The number of MCMC samples was chosen to ensure that the estimated p-value was within 0 . 01 of the true one with 99% confidence . Alleles deviating from HWE at a level p = 0 . 1 or stronger ( lower p-values ) were: European HLA-C locus ( p = 0 . 003 ) , African HLA-C ( p = 0 . 0001 ) , Asian HLA-A , -B , C ( p = 0 , p = 0 , p = 0 . 0004 ) . In all of these cases , except for the Asian HLA-C locus , the deviation was toward homozygosity . EM algorithms for haplotype frequency estimation have been shown to be robust against deviations toward homozygosity , with the explanation that increased homozygosity reduces the amount of missing phase information that the EM algorithm must overcome [25] . In any case , our experimental results demonstrate that this issue is not of such great concern as to invalidate our approach . Class I genotyping: Genomic DNA was amplified using locus-specific primers flanking exons 2 and 3 . The PCR products were blotted on nylon membranes and hybridized with a panel of sequence-specific oligonucleotide ( SS0 ) probes ( see http://www . ihwg . org/protocols/protocol . htm ) . Alleles were assigned by the reaction patterns of the SSO probes . Ambiguous SSOP typing results were resolved by sequencing analysis . Only exons 2 and 3 were examined during HLA typing . Any subtypes determined by sequences outside these exons were not distinguished . In these cases the earliest recognized alleles were assigned , normally the ones of the smallest digit in their names ( e . g . , B*5801 instead of B*5811 ) . The second data set was taken from the publically available dbMHC database ( http://www . ncbi . nlm . nih . gov/mhc/ ) , which we used to test our population-augmented model [44] , [45] , [46] , [47] , [48] , and also for use of our model on four-loci data [49] . These data are summarized in Table 2 .
Because the objective function we use , the penalized likelihood , is not convex , our parameter estimation and hence HLA refinement can be sensitive to the initial parameter setting . ( Note that by parameters , we mean wj , vj , and qj within the multi-logit functions , and not the regularization parameters , λi , nor the phasings , hi . ) To assess the sensitivity of performance to the initial parameters , we initialized the parameters randomly between 0 and 1 five different times . We performed this assessment on our Hispanic-labeled private data because this set corresponds to one of the smaller ethnicity-specific data sets , and because this ethnic label is less well defined than others . Both factors ( small data sets , and ethnicities that are not well-defined ) tend to produce greater sensitivity to parameter initialization . When training our softmax-based model , the geometric mean probability across the five initializations was aways 0 . 5255 . ( A larger geometric mean probability is better . ) In all five runs , 262 of the 306 masked alleles were correctly predicted , indicating little sensitivity to parameter initialization . Similarly , for the regularized multinomial-based model , the geometric mean probabilities across the five initializations was always 0 . 4180 . In all five runs , 262 of the 306 masked alleles were correctly predicted , again indicating little sensitivity . For the unregularized multinomial-based model , the geometric mean probabilities across the five initializations were: 0 . 0077 , 0 . 0117 , 0 . 0126 , 0 . 0092 , and 0 . 0105 . Of the 306 masked alleles , 260 , 265 , 260 , 266 , and 262 were correctly predicted across the five runs , indicating a far greater sensitivity to initial parameters . The geometric mean probability was best for the softmax-based model , followed by the regularized multinomial , followed by the unregularized multinomial model ( which does poorly due to its inability to make stable estimates for the huge number of parameters it requires ) . This is a pattern we shall see throughout our experiments . The sensitivity we see here will allow us to gauge how important observed differences are in the remainder of the experiments , where we always initialize the parameters to be all zero . Of course , when deploying this method in a real setting , it would be wise to try several parameter initializations , and then to choose the one that yields the highest likelihoods on hold-out data . Also note that , for the unregularized multinomial model , we regularize it with an equivalent sample size of 1×10−16 so that negative infinities do not appear when haplotypes not seen in the training sample appear in the test set . Next we used our large , private data set to measure the refinement performance of the various models we have discussed . We trained and tested within each ethnic population separately . The results are summarized in Figure 1 . The softmax model has the best performance overall and can correctly resolve a substantial number of ambiguous alleles . In terms of both criteria , the softmax model is significantly better than the other methods ( see Table 3 for p-values ) . The allele marginal model consistently has the worst performance in terms of number of correct MAP predictions , presumably because it does not make use of linkage disequilibrium . In contrast , it significantly outperforms the unregularized multinomial model in test log likelihood ( p = 1×10−4 ) , because the allele marginals are naturally regularized due to the small number of parameters . In realistic settings where our algorithm will be deployed , it is likely that the data set of interest is not drawn from exactly the same distribution as the training data . To get a sense of how robust our approach is to deviations from this idealized setting , we have performed several experiments more closely mimicking a realistic setting . In particular , we evaluated our refinement accuracy when the training and test distributions were drawn from different populations . First , we split the dbMHC Irish data set ( HLA-A , HLA-B , HLA-C alleles ) into 80% training data and 20% test and masked 30% of the test alleles to two digits . Then we trained a model using the training data , and tested on the test data . Next , we used the model we had previously trained on the ‘private North American European’ data , and used this model to predict the same masked , Irish alleles . Of the 200 people in the Irish test set , there was one person who contained one allele never observed in the European data ( B*2409 , which is actually a null allele , B*2409N , for which the typing of the private data was not capable of finding ) . After removal of this person , we then compared the performance when using the dbMHC Irish data set itself for traning , as compared to using our much broader private European data set for training . The resulting test geometric mean probabilities of the test set were 0 . 8851 when training with the dbMHC Irish , and 0 . 8891 with the private European . This difference was not significant ( p = 0 . 44 ) . Next , we used the model trained on the private Asian data to predict a 30% masking of 279 dbMHC Canton Chinese individuals [50] with HLA-A , -B , -C data ( we randomly chose this population among the Asian dbMHC populations available ) . Nine of these individuals had alleles not appearing in the training data ( A*0210 , B*1505 , B*1803 , B*3508 , B*3520 , B*4010 , B*5801 , B*7802 ) , and after their removal , we achieved a prediction accuracy of 441/487 = 91% , roughly equal to the 90% achieved when testing on the private Asian data set itself . Because this dbMHC data set was not large enough to partition into a training and test set , we were not able to measure accuracy achieved when training on itself . This is true for the next three dbMHC data sets as well , in which we perform similar experimentation . Next we used a model trained on the private North American African data set , to predict masked alleles in 251 dbMHC African American individuals , of which five individuals contained alleles not matching the training data ( A*6804 , B*1502 , B*1515 , B*5802 ) . After removal of these individuals , 321/373 = 86% of masked alleles were correctly predicted , which is lower than the 90% accuracy achieved when testing on the private North American African data itself . Results were comparable when we first removed individuals from Africa from the training data ( leaving only US-based individuals of Africans descent ) . Next , we used a model trained on the private North American European data set ( containig 776 individuals ) , to predict masked alleles in 287 dbMHC North American European individuals , of which three individuals contained alleles not matching the training data ( B*1802 , B*4408 , B*5202 ) . After removal of these individuals , 478/510 = 94% of masked alleles were correctly predicted , roughly equal to the 95% accuracy achieved when testing on the private North American European data set itself . Finally , we used a model trained on the private North American Hispanic data set , to predict masked alleles in 240 dbMHC North American Hispanic individuals , of which 13 individuals contained alleles not matching the training data ( A*0212 , A*0213 , A*2422 , A*2608 , A*3401 , A*6805 , B*5105 , B*3509 , B*4406 ) . After removal of these individuals , 344/400 = 86% of masked alleles were correctly predicted , comparable to accuracy achieved when testing on the private North American Hispanic data set itself . Based on this small set of experiments , we believe it may often be feasible to use our broadly defined ethnic categories for resolving ambiguity in other , independently created data sets falling in to the same broad category , or falling into a much more specific sub-category . Of course , this may not generally be true , and in particular , it may be less true for African-derived data . Additionally , a user of a trained model might have access to some high-resolution data for their population of interest , and could thus see how well the trained model works for the subset of their data ( by synthetically masking it ) before using the model to resolve ambiguity in their low-resolution data . Note that there are two statistical desiderata when using our method: 1 ) to use a training data set which mostly closely mimicks the HLA haplotype distribution of the data set of interest , and 2 ) to get as many training data as possible . Critically , these two desiderata are frequently odds with one another . That is , often a data set of interest is sub-population specific and therefore difficult to obtain high resolution data for in large quanitities . However , by loosening the strictness of the match between training and test populatations , one can often significantly increase the amount of data available . Without more data and experimentation , it is diffult to assess the optimal trade-off between these desiderata . However , as we see , using broad , even presumably admixed training data , can lead to useful results . To determine whether the availability of more training data may lead to improved refinements , we examined the sensitivity of performance to the size of the training set . For the European and the African private data sets , we iteratively halved the sample size of training data , where the largest available training data set sizes were , respectively , 6020 and 2836 . The results shown in Figure 2 suggest that more training data would improve the performance on the African data set , and to a smaller extent , on the European data set . Note that the African data set is smaller to start with than the European one , and also known to be more genetically diverse; both are explanations for the observed trends . To determine whether leveraging information across populations is useful , we compared our leveraged population models to those built separately on each population . We did so on data from dbMHC , which contains a diverse set of populations . ( We excluded the Irish population because this population is extremely homogeneous relative to the others . ) Recall that we introduced two types of leveraging features: simple and conjunctive . We used our softmax model both with the simple features alone , and with both the simple and the conjunctive features , as shown in Figure 3 . The performance of the population-augmented models are significantly better than the softmax model on test log likelihood ( e . g . , p = 0 . 02 when comparing softmax+simple to softmax ) . Although ethnicity labels are notoriously unreliable , they clearly provide beneficial information here . Also , the addition of conjunctive features lends to no apparent improvement . Because we use softmax regression functions in our haplotype model , the order in which we apply the chain rule ( Equation 2 ) to our loci will have an effect on predictive accuracy . We examined the sensitivity of performance to variable ordering on three loci ( A , B , C ) using the European and Hispanic data sets . The results are shown in Figure 4 in which a locus order of ‘B A C’ means we used . The experiments labeled ‘30% mask' denote the performance using the 30% random masking procedure we used in our earlier experiments . Additionally , we systematically masked all ( and only ) A alleles ( ‘A mask’ ) , and separately , all and only B alleles ( ‘B mask’ ) , and all and only C alleles ( ‘C mask’ ) . This procedure allows us to see if the variable ordering differentially affects our ability to predict particular loci . Statistical significance was measured only on the difference in test log likelihoods . For the ‘30% mask’ experiments , no statistically significant ( p⩽0 . 01 ) differences were found between variable orderings ( and hence the results of our previous experiments should not have been effected by this issue ) . For the locus-specific maskings in the European data set , only the B alleles showed significant differences ( order 1 vs . 4 , p = 0 . 0002; 1 vs . 6 , p = 0 . 001; 2 vs . 4 , p = 0 . 003; 2 vs . 6 , p = 0 . 004; 3 vs . 4 , p = 0 . 0006; 4 vs . 5 , p = 0 . 006 ) . For the locus-specific maskings in the Hispanic data set , the A alleles showed some significant differences ( order 1 vs . 2 , p = 0 . 004; 1 vs . 5 , p = 0 . 001; 3 vs . 5 , p = 0 . 004 ) , the B alleles did not show any , and the C alleles showed one ( order 4 vs . 5 , p = 0 . 003 ) . Note that it is possible to use a parsimonious model which is not dependent upon variable ordering ( a so-called ‘undirected’ model [51] in the parlance of the graphical models community ) . In particular , one can form pair-wise ‘compatibility’ functions between all pairs of HLA loci so thatwhere the are scalar parameters of the model and where the sum in the denominator is a normalizing constant and sums over all possible haplotypes , ( li , lj , lk , ) . However , brief experimentation of this model applied to the current problem did not indicate increased performance relative to our softmax-based model . In some domains , the ability to predict certain loci is of greater importance than others . For example , in HIV research , the ability to predict B alleles is often paramount ( e . g . , [15] ) . We measured locus-specific prediction accuracy for each locus by applying locus-by-locus masking to all four populations in the private data . Figure 5 shows the results , which do not indicate any particular pattern . Note that the number of possible alleles at each locus has a direct effect on our ability to predict ( as does the linkage between one locus and the others ) , and so we might expect , a priori , for the B alleles to be more difficult to predict , although this does not appear to be the case . Finally , in some instances , only low-resolution data ( i . e . , two-digit resolution ) is available . Consequently , we investigated the prediction accuracy of our algorithm in this situation—that is , when 100% of the alleles were masked to two-digit . The results for the private African , Asian , and Hispanic data sets are shown in Figure 6 . Because of the large number of allele combinations in the European data set , it was not possible to perform this experiment in a reasonable amount of time using the current sequential implementation of the algorithm . This problem should not be a big concern , however , as the algorithm can be easily parallelized . In order to gauge how much haplotype information is being used in this context , we compare the results to those from the allele marginal model . In all cases , the softmax model performs significantly better than the allele marginal model ( p = 1×10−4 for all three population comparisons on the test log likelihood ) . Thus , a large amount of haplotype information is being used by our model in this 100% masking context , and prediction of four-digits from strictly two-digit data is feasible . For comparison , Figure 6 includes the results presented earlier from the 30% masking experiments . To make the test log likelihoods comparable , we have normalized them by the number of alleles in the test set . Interestingly , the performance is comparable across the different maskings according to both criteria . We compared our methods on data with four loci , spanning the HLA-A , -B , -C and -DRB1 loci . The four-loci data available to us , with the largest sample size , was the Irish set in dbMHC . As shown in Figure 7 , we see that the relative performance of the methods is roughly the same as in earlier experiments . Given that LD may not be as strong between class I and class II alleles , it is of interest to determine how well each locus can be predicted . Thus we used a locus-specific masking , as described earlier . The accuracy at each of the HLA-A , -B , -C and -DRB1 alleles was respectively 97% , 98% , 99% , and 80% . This indicates that there is not sufficient linkage between the HLA-A , -B , -C loci and the HLA -DRB1 locus to accurately resolve ambiguity at the DRB1 locus . However , it may be the case that with additional class II loci , refinement of class II data would be feasible .
We have introduced a method for statistical refinement of low or intermediate resolution HLA data , when a full resolution training data set from a similar population is available . In doing so , we have also improved upon the EM-based approach to haplotype estimation by using a more parsimonious parameterization of the haplotype distribution . Experimentally , we show both that it is feasible to use statistical approaches for HLA refinement , and also that our method outperforms the standard multinomial-based models used throughout the HLA community for haplotype estimation . Our HLA refinement method helps to mitigate the limiting factor of cost in HLA typing today , and allows for lower/intermediate resolution , or historical data to be statistically refined when it cannot be refined by assay . A tool based on our approach is available for research purposes at http://microsoft . com/science . Although there is widespread caution about the use of assigned , or self-defined ethnicity labels [52] , we show that the labels associated with dbMHC data carry useful information . Furthermore , we show that by augmenting our softmax-based HLA model , we can make use of these labels to increase the amount of data available while automatically using it in a population-appropriate manner . Future work of interest would be to model the data in yet another way: using a mixture of haplotype models , in which each component of the mixture represents one well-defined population ( either as defined in the training data , or as uncovered in an unsupervised manner ) . Then , when data contain multiple populations without ethnicity labels or when labeled populations contain mixtures of latent ( unknown ) subpopulations , one can use these mixture models to uncover population structure and appropriate weightings of the different populations for individuals in a data set of interest . Because our modeling approach assumes that the training and testing populations are drawn from the same distribution , one should take care when trying to use this approach for case-control studies where case and controls are thought to be drawn from different distributions . One may also be wary of using this approach in the domain of transplantation , for similar reasons ( patients requiring transplants likely make up a specific sub-population ) . However , since HLA ambiguity resolution is applied in the area of transplants to potential donors in a registry , rather than the patients themselves ( who are routinely typed at high resolution ) , application in this domain should not be problematic . As with the traditional algorithm used in the HLA community , our EM algorithm assumes HWE . One could make a small change to our model which would allow us to circumvent making such an assumption . In the models discussed so far , the probability of data in a particular phasing is defined as follows . If a haplotype , h , is specified by partitioning the genoytpes , gA1 , gB1 , gC1 , gA2 , gB2 , gC2 into two sets: , then the probability of the data given this phasing is defined as the product of the probability of each haplotype: ( 9 ) where each of the probabilities p ( gA1 , gB1 , gC1 ) and p ( gA2 , gB2 , gC2 ) are specified by a haplotype model ( e . g . , softmax or multinomial ) . To circumvent the assumption of HWE , one could instead define a model which does not factor this probability into two independent terms: ( 10 ) where now we would not have a haplotype-based model , but instead a more generic , ordered-genotype model , which could itself be given a softmax-based parsimonious parameterization . The downside of such an approach is that we essentially halve the amount of available data , because we no longer have two independent data samples from each individual , and hence far more data would be required to effectively make use of such a model . Future work in probabilistic HLA refinement may involve comparing EM-based approaches to full Bayesian approaches . Also , an interesting , though perhaps computationally difficult avenue to pursue would be the use of HLA DNA sequences to better model rare haplotypes , or the use of SNP data to directly predict HLA types . | At the core of the human adaptive immune response is the train-to-kill mechanism in which specialized immune cells are sensitized to recognize small peptides from foreign sources ( e . g . , from HIV or bacteria ) . Following this sensitization , these immune cells are then activated to kill other cells which display this same peptide ( and which contain this same foreign peptide ) . However , in order for sensitization and killing to occur , the foreign peptide must be “paired up” with one of the infected person's other specialized immune molecules—an HLA molecule . The way in which peptides interact with these HLA molecules defines if and how an immune response will be generated . There is a huge repertoire of such HLA molecules , with almost no two people having the same set . Furthermore , a person's HLA type can determine their susceptibility to disease , or the success of a transplant , for example . However , obtaining high quality HLA data for patients is often difficult because of the great cost and specialized laboratories required , or because the data are historical and cannot be retyped with modern methods . Therefore , we introduce a statistical model which can make use of existing high-quality HLA data , to infer higher-quality HLA data from lower-quality data . | [
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"genomi... | 2008 | Statistical Resolution of Ambiguous HLA Typing Data |
A prevailing theory proposes that the brain's two visual pathways , the ventral and dorsal , lead to differing visual processing and world representations for conscious perception than those for action . Others have claimed that perception and action share much of their visual processing . But which of these two neural architectures is favored by evolution ? Successful visual search is life-critical and here we investigate the evolution and optimality of neural mechanisms mediating perception and eye movement actions for visual search in natural images . We implement an approximation to the ideal Bayesian searcher with two separate processing streams , one controlling the eye movements and the other stream determining the perceptual search decisions . We virtually evolved the neural mechanisms of the searchers' two separate pathways built from linear combinations of primary visual cortex receptive fields ( V1 ) by making the simulated individuals' probability of survival depend on the perceptual accuracy finding targets in cluttered backgrounds . We find that for a variety of targets , backgrounds , and dependence of target detectability on retinal eccentricity , the mechanisms of the searchers' two processing streams converge to similar representations showing that mismatches in the mechanisms for perception and eye movements lead to suboptimal search . Three exceptions which resulted in partial or no convergence were a case of an organism for which the targets are equally detectable across the retina , an organism with sufficient time to foveate all possible target locations , and a strict two-pathway model with no interconnections and differential pre-filtering based on parvocellular and magnocellular lateral geniculate cell properties . Thus , similar neural mechanisms for perception and eye movement actions during search are optimal and should be expected from the effects of natural selection on an organism with limited time to search for food that is not equi-detectable across its retina and interconnected perception and action neural pathways .
Neurophysiology studies of the macaque monkey [1]–[3] support the existence of two functionally distinct neural pathways in the brain mediating the processing of visual information . The behavior of patients with brain damage has led to the proposal that perception is mediated by the ventral stream projecting from the primary visual cortex to the inferior temporal cortex , and that action is mediated by the dorsal stream projecting from the primary visual cortex to the posterior parietal cortex [4]–[6] ( Figure 1a ) . Although there has been debate about whether this separation into ventral/dorsal streams implies that the brain contains two distinct neural representations of the visual world [7]–[12] , there has been no formal theoretical analysis about the functional consequences of the two different neural architectures on an animal's survival . Visual search requires animals to move their eyes to point the high-resolution region of the eye , the fovea , to potentially interesting regions of the scene to sub-serve perceptual decisions such as localizing food or a predator . What is the impact of having similar versus different neural mechanisms guiding eye movements and mediating perceptual decisions on visual search performance for an organism with a foveated visual system ? We consider two leading computational models of multiple-fixation human visual search , the Bayesian ideal searcher ( IS ) [13]–[15] and the ideal saccadic targeting model ( maximum a posteriori probability , MAP [16] , [17] ) for a search task of a target in one of eight locations equidistant from initial fixation ( Figure 1b ) . The ideal searcher uses knowledge of how the detectability of a target varies with retinal eccentricity ( visibility map ) and statistics of the scenes to move the fovea to spatial locations which maximize the accuracy of the perceptual decision at the end of search [13] ( Figure 1b ) . The saccadic targeting model ( MAP ) makes eye movements to the most probable target location [6] , [17] which is optimal if the goal was to saccade to the target rather than collect information to optimize a subsequent perceptual decision [1] ( Figure 1b ) . Depending on the spatial layout of the possible target locations and the visibility map , the IS and MAP strategies lead to similar ( Figure 1c ) or diverging eye-fixations ( Figure 1d–e ) . For example for a steeply varying visibility map ( Figure 1c ) both models make eye movements to the possible target locations while for a broader visibility map ( Figure 1d–e ) the ideal searcher tends to make eye movements in between the possible target locations attempting to obtain simultaneous close-to-fovea processing for more than one location . Covert attention allows both models to select possible target locations and ignore locations that are unlikely to contain the target when deciding on saccade endpoints and making perceptual search decisions [18] , [19] . Perceptual target localization decisions for both models are based on visual information collected in parallel over the whole retina , temporally integrated across saccades , and based on the location with highest sensory evidence for the presence of the target . Critically , we implemented the models to have two processing pathways , one determining where to move the fovea and the other stream processing visual information to reach a final perceptual decision about the target location . Rather than having a single linear mechanism or perceptual template ( Figure 1b ) , each pathway in the model had its own neural mechanism which is compared to the incoming visual data at each possible target location . Likelihood ratios [20] of the observed responses for each of the mechanisms under the hypothesis that the target is present or absent at that location are used to make decisions about where to move the eyes and perceptual decisions ( see Materials and Methods ) . We used a genetic algorithm as a method to find near-optimal solutions for perception and action mechanisms but also to simulate the effects of the evolutionary process of natural selection on the neural mechanisms driving saccadic eye movements and perceptual decisions during search . The computational complexity of the ideal Bayesian searcher makes it difficult to virtually evolve the model ( see note 1 in Text S2 ) and thus we used a recently proposed approximation to the ideal searcher that is computationally faster ( Entropy Limit Minimization , ELM [15] , [21] ) . The ELM model chooses the fixation location that minimizes the uncertainty of posterior probabilities over the potential target locations . The decision rule can be simplified to choose the fixation location with the maximum sum of likelihood ratios across potential target locations , each weighted by its squared detectability given the fixation location [15] . The ELM model can be shown to approximate the fixation patterns of the ideal searcher [15] and capture the main characteristics of the fixation patterns of the IS for our task and visibility maps ( Figure 1c–e; ELM ) ( see note 2 in Text S2 ) . The process of virtual evolution started with the creation of one thousand simulated individuals with separate linear mechanisms for perception ( ventral ) and eye movement programming ( dorsal; Figure 2a ) . Each pathway's template for each individual was created from independent random combinations of the receptive fields of twenty four V1 simple cells . Each simulated individual was allowed two eye movements ( see note 3 in Text S2 ) before making a final perceptual search decision about the location of the target . Performance finding the target in one of eight locations for five thousand test-images ( one thousand for natural images ) was evaluated and the probability of survival of an individual was proportional to its performance accuracy . A new generation was then created from the surviving individuals through the process of reproduction , mutation and cross-over ( Figure 2a ) . The process was repeated for up to 500 generations .
We first evolved the ideal searcher approximation ( ELM model ) for different shape luminance targets ( isotropic Gaussian , vertical elongated Gaussian and cross pattern consisting of a positive and negative polarity elongated Gaussian ) embedded in 1/f noise and a steep visibility map ( Figure 1c ) . Irrespective of the target shape , virtual evolution led to converging perception ( ventral ) and saccade ( dorsal ) mechanisms that are similar to the target ( Figure 2b; see Video S1 , Video S2 , and Video S3 for virtual evolution ) . To further investigate the generality of the result we evolved the ELM model to search a circular Gaussian target added to backgrounds with different statistical properties: white noise , 1/f noise and importantly , a calibrated set of natural image backgrounds [22] . Figure 3 ( 2nd row ) presents the distribution of perceptual decision accuracies across individuals in a generation and shows that perceptual performances of simulated individuals in the population improve with generations and then converge to an asymptote . We characterized the similarity between the perception and saccade mechanisms by computing the correlations between the 2 dimensional linear mechanisms for each individual in each generation . Figure 3 ( 3rd row ) shows that the distribution of correlations across individuals in the population evolves to unity irrespective of the background type . To visualize in detail the shape of the evolved templates , we analyzed the radial profile of the templates of the highest performing simulated individuals in the last generation ( Figure 3; 4th row ) . For all three backgrounds the saccade and perception templates converge to similar shapes ( perception and saccade 2-D template correlations for the best performing templates in the last generation: 0 . 990±0 . 006 , 0 . 986±0 . 013 , 0 . 982±0 . 013 ) . In addition , the linear mechanisms for the 1/f noise and natural scenes are narrower than those for the white noise and show an inhibitory surround ( Figure 3 ) . These previous results were based on a visibility map that steeply declines with eccentricity and rely on the assumption that humans are near-ideal searchers . We , thus , evolved the mechanisms for the case of a broader visibility map that is similar to that measured for human observers in 1/f noise [15] ( Figure 4a ) and showed that the convergence of neural mechanisms generalizes to different visibility maps ( Figure 4a ) and also to a model in which eye movement planning is assumed to follow a saccadic targeting strategy ( MAP ) rather than approximating an ideal strategy ( Figure 4a ) . Furthermore , Figure 4b shows that there is nothing particular about the symmetry of the eight location configuration search task since similar convergent evolution is observed for an asymmetric four location task ( Figure 1e ) . We also evaluated whether our results would change if the model included the increasing size of V1 receptive fields and lower frequency tuning with retinal eccentricity ( see note 4 in Text S2 ) . Figure 5a ( right graph ) shows the center frequency and bandwidth ( standard deviation ) of the oriented Gabor receptive fields as a function of retinal eccentricity . The computational time demands of this simulation restricted us to evaluate this model for a fixed set of receptive field weights across eccentricities ( see note 5 in Text S2 ) and limited set of scenarios: 1/f noise , steep visibility map and two targets: a low frequency Gaussian ( Figure 5b; left ) and a Difference of Gaussians ( DoG ) with a center frequency of 8 c/deg ( Figure 5b; right ) . Due to the fixed set of weights across eccentricity , in this model the spatial profile of the linear combination of receptive fields scales up with eccentricity . Thus , for each retinal eccentricity category there was a pair of evolved template profiles . Figure 5c shows that convergent evolution still results when receptive field size increases with eccentricity and irrespective of the spatial frequency of the target . Figure 5d presents the similar radial profiles of the of evolved perception and saccade mechanisms for the fovea and a sample peripheral retinal location ( perception and saccade 2-D template correlations for the best performing templates in the last generation averaged across retinal eccentricities were: Gaussian target: 0 . 963±0 . 008; DoG target: 0 . 961±0 . 004 ) . Do all scenarios lead to converging evolution of the perception ( ventral ) and action ( dorsal ) pathways ? No , if we take a case in which the sought target is equally detectable across the retina ( flat visibility map ) , the results show the correlations between the perceptual and saccade templates do not converge to unity ( Figure 6a ) . A second example is a case in which the organism makes a decision after eight eye movements rather than two eye movements ( Figure 6b ) . Because the organism gets to fixate on all eight target locations , there is little added benefit of an efficient saccadic system and the co-evolution is much slower ( Figure 6b ) . A third scenario of partial convergence results if we adopt a strong model of two visual processing streams which spatially pre-filter the visual input based on the properties of the cells in the parvocellular and magnocellular lateral geniculate nucleus ( LGN ) ( [23]; see Figure 6d ) and assume no further interaction across pathways . The differential spatial frequency filtering of the two pathways can introduce constraints in the frequency content of the evolved mechanisms preventing a full convergence of the templates ( Figure 6e; perception and saccade 2-D template correlations for the best performing templates in the last generation for: 1/f noise: 0 . 603±0 . 082 ) . A similar simulation with the same target but white noise instead of 1/f noise also resulted in partial convergence ( perception/saccade 2-D template correlation of 0 . 856±0 . 046 ) .
We used an approximation to an Ideal Bayesian Searcher ( Entropy Limit Minimization model; ELM ) to virtually evolve separate linear mechanisms for eye movements and perceptual decisions during visual search for a variety of targets embedded in various synthetic and natural image backgrounds . Evolved templates contain similarities to the target but for the 1/f and natural images they are narrower than the target and contain a subtle inhibitory surrounding not present in the signals but often present in monkey neuronal receptive fields and human behavioral receptive fields [9] , [19] ( see blue outline in Figure 2b ) . A previous study has shown that such inhibitory surrounds serve to suppress high amplitude noise in the low frequencies and optimize the detection of spatially compact signals in natural images [24] . The current result extends previous results [24] to show the optimality of inhibitory surrounds during visual search in natural images for an organism with a foveated visual system and saccadic eye movements . Central to this paper , the mechanisms for perception and saccades evolved to similar representations . This result is robust across different types of backgrounds , signals , visibility maps , and spatial distributions of possible target locations . Due to computational constraints we did not investigate the more general case of allowing the target to appear at any location within the image but there is no particular reason to suggest that our result would differ for this latter general case . In addition , similar convergence between mechanisms was found for what arguably are the most common contender algorithms to model how humans plan eye movements during search: an approximation to the ideal searcher , ELM and a saccadic targeting model; MAP model; [13] . For simplicity our original models did not include receptive fields that increased with retinal eccentricity but an implementation of such a model led to similar convergent evolution for a low and a higher spatial frequency target . The scenarios for which we did not find full convergent evolution of the linear mechanisms were for cases for which the target was either equi-detectable across the retina or the organism had enough time to fixate all of the possible target locations . Note , however , that for both cases , performance of the evolved individuals does improve with increasing generations ( Figure 6a–b ) through the evolution of the perceptual template to a target-like structure . Yet , there is no performance advantage for evolving a neural mechanism for saccades that encodes target information because , for these cases different eye movement patterns have little or no impact on perceptual performance . A third scenario which resulted in partial convergence was a two stream model with pathway-specific pre-filtering of the visual input . A strong assumption that there are no interconnections between the two pathways would result in processing constraints based on the early stages of visual processing of both pathways . Inclusion of pre-filtering properties of the parvocellular and magnocellular LGN cells restricted the full convergence of the evolved mechanisms . These finding suggest that if we adopt a strict separation of pathways and take into account properties of LGN cells we should not always expect similar mechanisms driving perception and saccadic decisions during search . The specific circumstances for which we will not find convergent evolution and the degree of similarity between evolved templates will depend on the spatial frequency of the target and background statistical properties ( see results for 1/f noise vs . white noise ) . Yet , is the strict separation of pathways and constraints to the filtering properties of parvocellular ( perception ) and magnocellular ( action ) LGN cells tenable for the case of eye movements and perceptual decisions during search ? A recent psychophysical study [9] used the same Gaussian target as in the simulations and reverse correlation to show that estimated underlying templates mediating human saccadic actions and perceptual search decisions are similar . Thus , these psychophysical findings would suggest that the strong assumption of no interconnections across pathways and constraints by the early LGN processing might not hold at least for the case of perception and eye movements during visual search . Together , our present results suggest a theory of why evolution would favor similar neural mechanisms for perception and action during search [9] and provide an explanation for the recent study finding similar estimated underlying templates mediating human saccadic decisions and perceptual decisions . Our findings and theory do not necessarily imply either that one pathway mediates both perception and action nor are they incompatible with the existence of separate magnocellular and parvocellular pathways . Instead , our theory would be consistent with the idea that pathways for perception and oculomotor largely overlap , leading to significant sharing of visual information across pathways [8] , [12] , [25] , [26] . For the case of saccadic eye movements , visual cortical pathways through the frontal eye fields [27] and the lateral intra-parietal cortex [28] play critical roles , as well as brainstem and cortical pathways through the superior colliculus [29] . In addition , studies have related areas in the ventral stream ( V4 ) to target selection of saccades [30] , [31] . In addition , the results do not prohibit small differences in visual processing for perception and saccadic action but provide functional constraints on how much discrepancy can exist between neural mechanisms without jeopardizing the survival of the organism . In the larger context , the similar neural mechanisms for perception and saccade actions should be understood as another effective strategy implemented in the brain , in addition to guidance by target properties [13] , [14] , [32] , [33] , optimal saccade planning [15] , contextual cues [34] , [35] and miniature eye movements [36] to ensure successful visual search . Finally , the approach of the present study demonstrates how the rising field of natural systems analysis [37] , [38] can be used in conjunction with virtual evolution and physiological components of the visual system to evaluate whether properties of the human brain might reflect evolved strategies to optimize perceptual decisions and actions that are critical to survival .
We assumed a viewing distance of 50cm for the models . Search targets for simulations were: a ) A Gaussian target with 0 . 5539 square root contrast energy ( SCE ) and a standard deviation of 0 . 1376 degrees ( Figure 1c; 2b left column; 3 ) ; b ) An elongated Gaussian with 0 . 9594 SCE , standard deviations of 0 . 4128 deg . in the vertical direction and 0 . 1376 degrees in the horizontal direction ( Figure 2b center column , Figure 4 ) ; c ) The difference of a vertically oriented and a horizontally oriented elongated Gaussians with 0 . 8581 SCE ( Figure 2b , right column ) . The white noise root mean square contrast ( rms ) was 0 . 0781 . The same rms was used for white noise filtered with the 1/f function ( 1/f noise ) . Possible target locations were equidistant 7 degrees from the center fixation cross . Independent external and internal noise samples were refreshed with each saccade for the white and 1/f noise . For the natural images the external backgrounds were fixed but the internal noise refreshed across saccades . Here , we briefly describe the models implementations ( see Text S1 for detailed mathematical development and details ) . The initial stage of all three models investigated ( ideal searcher , IS; entropy limit minimization , ELM; and saccadic targeting , MAP ) is the dot product of a perceptual and saccade template ( w ) with the image data ( g ) at all possible target locations , where r is the resulting scalar response and w and g are expressed as 1-D vectors . The templates for the perceptual decisions and saccade planning were independent and random linear combinations of 24 Gabor functions that spanned the targets: spatial frequencies , 0 . 5 , 1 , 2 , 4 cycles/degree for 6 different orientations , 30 degrees apart , and with octave bandwidths . A subset of simulations ( Figure 6 ) also modeled pre-processing of the image by separate LGN cells corresponding to the magnocellular ( dorsal ) and parvocellular ( ventral ) cells . The filtering was done using DoG functions with different center frequencies ( see Text S1 for mathematical details ) prior to the processing by the Gabor functions . Use of a larger number of Gabor functions did not significantly change the evolved templates for the targets considered but required prohibitively longer computational times due to the dimensionality explosion . For the template derived for the case of the isotropic Gaussian target we used an additional constraint of equal weighting for all orientations of the Gabor functions for a given spatial frequency . Most of the simulations used the fixed 24 Gabor functions irrespective of retinal eccentricity . A subset of simulations ( see Figure 5 ) used sets of 24 Gabor functions that increased linearly in size and also decreased in the central frequency tuning with retinal eccentricity ( see details in effects of retinal eccentricity section ) . Template responses were integrated across saccades . Calculation of likelihood ratios use Gaussian probability density functions which depend on the image parameters for the white and 1/f Gaussian noisy images . For the natural images , the likelihood calculation required estimating the probability density function from a training set of 3000 images and fitting the probability density functions with Laplacian distributions convolved with a Gaussian distribution representing the internal noise ( see Text S1 ) . Two methods were used to model the detrimental effect of retinal eccentricity on the detectability of the target . The first method which is similar to Najemnik and Geisler [13] was implemented by adding internal noise to the scalar template response: , where the additive internal noise scalar value is sampled from a Gaussian distribution which standard deviation ( ) is dependent on the distance ( i . e . retinal eccentricity ) between the tth fixation and the template response location i out of m possible target locations . Also the internal noise was proportional to the template's response standard deviation resulting from the external image variability . The visibility maps referred to as steep and broad ( see also Figure S1 ) were obtained with internal noise standard deviations given by: ( 1a ) ( 1b ) where σo is the standard deviation of the template response due to external noise , e is the eccentricity in degrees , and the subscripts k refer to the fixation location , and i to the possible target location . For all models , independent samples of internal noise were used for each saccade and pathways . The second method to model the effects of retinal eccentricity included internal noise ( see above ) and also varied the sets of 24 Gabor functions with retinal eccentricity . The size of Gabor functions increased with the retinal eccentricity ( e ) so that the standard deviation of the spatial Gaussian envelope is given by: ( 2 ) where is the bandwidth and is the center frequency of Gabor function in the fovea . Thus , the standard deviation in the frequency domain of each Gabor function ( Figure 5a; right graph ) decreases as: ( 3 ) The center frequency tuning of the Gabor functions ( s ) linearly decreased with retinal eccentricity: . The saccadic targeting or maximum a posteriori probability model ( MAP ) chooses the location of the next fixation with the maximum product of likelihoods ratios ( ) across previous and present fixation ( t = 1 , … , T ) : ( 4 ) For the case of white noise and 1/f Gaussian noise the expression can be simplified to the sum of log-likelihood ratios: ( 5 ) where Δμ is the difference in mean response of the template to the signal plus background and background only and all other symbols are defined above . The ideal searcher selects as the next fixation the location that will maximize the probability of finding the target after the eye movement is made: ( 6 ) where is the proportion correct ( PC ) given that the target location is i , and the next fixation is . The term is the prior that the ith location contains the target given the sensory evidence collected up to the present fixation: and m is the number of possible target locations . For white noise and 1/f noise Gaussian noise , becomes: ( 7 ) where is the probability density function of the Gaussian function in Equation ( 9a ) , the cumulative density function of the Gaussian function in Equation ( 9b ) , and , are the log-likelihood ratios which are known scalar values based on acquired visual information , ( 8a ) ( 8b ) while and are random variables describing log-likelihoods after the next fixation and described by normal probability density functions: ( 9a ) ( 9b ) where ( ) is the detectability at target location i ( j ) , given fixation at location . The present formulation is identical to that of Najemink and Gielser [13] but uses likelihood ratios rather than product of posteriors . The entropy limit minimization model chooses as the next fixation the locations that minimize the expected entropy and can be approximated by maximizing the expected information gain . This can be shown to be approximated by calculating for each potential fixation location , , a sum of the posterior probability for each location weighted by the squared detectability given the fixation location [15]: ( 10 ) where is the Shannon entropy of , and is the information gain . For all models , the final perceptual decision about the target location was obtained by combining the likelihood ratios for each possible target locations across all fixations and choosing the location with the highest product of likelihood ratios: ( 11 ) where the likelihoods of the responses given the background only and the target are given and which are the probability density functions ( pdf ) assumed to be Gaussian ( white noise and 1/f noise ) or empirically estimated from samples ( see next section ) for the natural images . The distribution of template responses for the natural image dataset [22] were estimated from 24 , 000 image patches extracted from the eight possible target locations for 3000 natural images . We fit the distribution of these responses for each template of each simulated individual with a Laplacian distribution: ( 12 ) where is the mean parameter and is a scale parameter . To take into account the effect of additive Gaussian internal noise on the probability density function of the template responses we convolved the Laplacian distribution with the Gaussian distributions: ( 13 ) where and are Gaussian and Laplace probability density functions respectively ( see Figure S2 ) . We used the Genetic Algorithm Optimization Toolbox ( GAOT ) [39] . Arithmetic crossover parameter was set to operate 50 times per generation , and uniform mutation to operate 50 times per generation . The selection process used a real-valued roulette wheel selection [38] . A generation consisted of 1 , 000 individual parameter settings . All individuals were randomly initialized , and allowed to evolve over 500 generations ( see Text S1 for additional details ) . Reported results for each scenario/model were averages across ten simulated evolution runs . | The brain has two processing pathways of visual information , the ventral and dorsal streams . A prevailing theory proposes that this division leads to different world representations for conscious perception than those for actions such as grasping or eye movements . Perceptual tasks such as searching for our car keys in a living room requires the brain to coordinate eye movement actions to point the high resolution center of the eye , the fovea , to regions of interest in the scene to extract information used for a subsequent decision , such as identifying or localizing the keys . Does having different neural representations of the world for eye movement actions and perception have any costs for performance during visual search ? We use computer vision algorithms that simulate components of the human visual system with the two separate processing streams and search for simple targets added to thousands of natural images . We simulate the process of evolution to show that the neural mechanisms of the perception and action processing streams co-evolve similar representations of the target suggesting that discrepancies in the neural representations of the world for perception and eye movements lead to lower visual search performance and are not favored by evolution . | [
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] | 2010 | Evolution and Optimality of Similar Neural Mechanisms for Perception and Action during Search |
Although collar cells are conserved across animals and their closest relatives , the choanoflagellates , little is known about their ancestry , their subcellular architecture , or how they differentiate . The choanoflagellate Salpingoeca rosetta expresses genes necessary for animal development and can alternate between unicellular and multicellular states , making it a powerful model for investigating the origin of animal multicellularity and mechanisms underlying cell differentiation . To compare the subcellular architecture of solitary collar cells in S . rosetta with that of multicellular ‘rosette’ colonies and collar cells in sponges , we reconstructed entire cells in 3D through transmission electron microscopy on serial ultrathin sections . Structural analysis of our 3D reconstructions revealed important differences between single and colonial choanoflagellate cells , with colonial cells exhibiting a more amoeboid morphology consistent with higher levels of macropinocytotic activity . Comparison of multiple reconstructed rosette colonies highlighted the variable nature of cell sizes , cell–cell contact networks , and colony arrangement . Importantly , we uncovered the presence of elongated cells in some rosette colonies that likely represent a distinct and differentiated cell type , pointing toward spatial cell differentiation . Intercellular bridges within choanoflagellate colonies displayed a variety of morphologies and connected some but not all neighbouring cells . Reconstruction of sponge choanocytes revealed ultrastructural commonalities but also differences in major organelle composition in comparison to choanoflagellates . Together , our comparative reconstructions uncover the architecture of cell differentiation in choanoflagellates and sponge choanocytes and constitute an important step in reconstructing the cell biology of the last common ancestor of animals .
Collar cells were likely one of the first animal cell types [1–3] . Defined as apicobasally polarised cells crowned with an actin-rich microvillar collar surrounding an apical flagellum [4] , they are conserved across almost all animal phyla ( Fig 1A ) as well as in their closest living relatives , the choanoflagellates [1] . In choanoflagellates and sponges , the undulation of the apical flagellum draws bacteria and other particulate material to the collar , where it can be phagocytosed for food . In many other animals , collar cells function as sensory epidermal cells , nephridial cells , and various inner epithelial cells [1] . Multicellularity evolved multiple times independently in eukaryotes [1 , 6] . Choanoflagellates are uniquely suited for investigating characteristics of the last common multicellular ancestor of animals and the origin of animal-specific innovations . Several independent phylogenomic analyses [7–9] have placed them as the closest branching lineage to the animals . It is thought that the transition from a free-swimming facultatively unicellular collar cell to one in an obligately multicellular animal condition emerged along the animal stem lineage [2] . While it has been hypothesised that the common ancestor of animals may have exhibited a complex , polymorphic life cycle [10 , 11] , parsimony suggests that at least one of these life stages would have possessed choanoflagellate-like collar cells [1] . Investigation of the choanoflagellate cell plan therefore has the potential to shed light on the evolution of one of the most ancient animal cell types . The colony-forming choanoflagellate S . rosetta [12] has emerged as a promising model organism to investigate the properties of the progenitor of the animals [13] . This species exhibits a complex life cycle , transitioning through both single and colonial collar cell types [12 , 14] ( Fig 1B ) . The development of rosette colonies can be induced by rosette-inducing factor ( RIF ) ( Fig 1B ) , which is a sulfonolipid from the bacterium Algoriphagus machipongonensis [15] . Most importantly , choanoflagellate colonies form by cell division , and cells within rosette colonies are held together by cytoplasmic bridges , filopodia , and extracellular matrix ( ECM ) [12] . Cell types of S . rosetta have been previously well investigated using molecular tools [16–18] , which have revealed that choanoflagellates possess a suite of genes essential for animal multicellularity and development . However , our structural understanding of how choanoflagellate cells like S . rosetta organise themselves into colonies—and how these compare to early-branching animal collar cells—remains unquantified relative to molecular investigations . Given the importance of cell differentiation for the origin of animals , we hypothesised that choanoflagellate colonial cells would not simply represent a cluster of single cells but would be morphologically differentiated from single cells . Our previous studies show that the proteins Flotillin and Homer colocalise in the nucleus of all single choanoflagellate cells , but not in all colonial cells providing preliminary evidence of cell differentiation within choanoflagellate rosette colonies [16] . In contrast , the nearly indistinguishable transcriptomes of single cells and colonies [17] speak against cell differentiation . In this study , we used serial ultrathin transmission electron microsocopy ( ssTEM ) sectioning to reconstruct the microanatomy of unicellular and colonial S . rosetta cells to identify structural differences between collar cells in a single versus a multicellular choanoflagellate condition . To place our choanoflagellate reconstructions into the context of collar cells from an early-branching animal phylum , we reconstructed a section of a sponge choanocyte chamber from the homoscleromorph sponge Oscarella carmela [19] ( Box 1 ) . Our characterisation of the microanatomy of choanoflagellates and sponge choanocytes sheds light on collar cell differentiation , has implications for the origin and evolution of animal cell types , and is an important step in reconstructing the putative biology of the last common ancestor of the animals .
Three randomly selected single cells and three randomly selected colonial cells from a single colony were chosen for the reconstruction of entire choanoflagellate cells and subcellular structures ( Fig 1 , S1–S3 Figs , S1–S6 Movies ) . Both single and colonial S . rosetta cells exhibited a prominent , central nucleus enveloped by a mitochondrial reticulum and basal food vacuoles—as well as intracellular glycogen reserves—consistent with the coarse choanoflagellate cellular architecture reported in previous studies [20 , 21] ( reviewed in [13 , 22] ) ( Fig 1 , S1–S3 Figs , S1–S6 Movies ) . However , with the increased resolution of electron microscopy , we detected three morphologically distinct populations of intracellular vesicles with distinct subcellular localisations ( Fig 1G , S1I–S1L Fig ) : 1 ) large vesicles ( extremely electron-lucent , 226 ± 53 nm in diameter ) ( S1J , S1J’ , and S1J” Fig ) ; 2 ) Golgi-associated vesicles ( electron-dense inclusions , 50 ± 10 nm in diameter ) ( S1I , S1I’ , and S1I” Fig ) ; and 3 ) apical vesicles ( electron-lucent , 103 ± 21 nm in diameter ) ( S1K , S1K’ and S1K” Fig ) . Extracellular vesicles were also observed to be associated with two of the single cells ( electron-lucent , 173 ± 36 nm in diameter ) and appeared to bud from the microvillar membrane ( S1L , S1L’ and S1L” Fig ) . Choanoflagellate cells subjected to fluorescent labelling were congruent with 3D ssTEM reconstructions in terms of organelle localisation ( Fig 1B and 1C ) , providing evidence that the 3D models presented herein are biologically representative . Our 3D ssTEM reconstructions allowed for detailed volumetric and numerical comparisons among single and colonial S . rosetta cells ( Fig 2 , S2 Fig , S1 and S2 Tables ) . Overall , the general deposition of major organelles was unchanged in both cell types ( Fig 1E–1L , Fig 2A and 2B , S2A–S2C Fig ) . In addition , single and colonial cells devote a similar proportion of cell volume to most of their major organelles ( nucleus: single cells 12 . 92% ± 0 . 58% versus colonial cells 11 . 56% ± 0 . 27%; nucleolus: 1 . 85% ± 0 . 33% versus 2 . 2% ± 0 . 22%; mitochondria: 5 . 08% ± 1 . 14% versus 6 . 63% ± 0 . 42%; food vacuoles: 9 . 22% ± 2 . 75% versus 6 . 85% ± 0 . 87%; and glycogen storage: 8 . 71% ± 2 . 36% versus 7 . 50% ± 1 . 12% ) ( Fig 2 , S2 Fig , S1 and S2 Tables ) . We did , however , uncover some interesting ultrastructural differences between single and colonial cells ( Fig 2C ) . Colonial cells devoted a higher proportion of cell volume to endoplasmic reticulum ( ER ) ( single: 3 . 27% ± 0 . 35% versus colonial: 6 . 86% ± 0 . 39% ) . This contrast was coupled to a differential ER morphology across cell types . The ER of colonial cells frequently displayed wide , flat sheets ( Fig 3E ) , which were not observed in the reconstructed single cells . Single cells exhibited a higher number of Golgi-associated vesicles ( single: 166 . 3 ± 32 . 7 versus colonial: 72 . 3 ± 26 . 5 ) and individual mitochondria than colonial cells ( single: 25 . 3 ± 5 . 8 versus colonial: 4 . 3 ± 4 . 2 ) ( Fig 2C , S2 Table ) despite lacking volumetric differences between cell types . Finally , we found that colonial cells are characterised by a more amoeboid morphology than single cells ( Fig 3A ) . Colonial cells exhibited a higher relative proportion of endocytotic vacuoles by volume ( single: 0 . 07 ± 0 . 07 versus colonial: 0 . 32 ± 0 . 12 ) —a phenomenon coupled to a higher overall number of endocytotic vacuoles ( single: 1 ± 1 versus colonial: 5 ± 2 ) and pseudopodial projections per cell ( single: 1 ± 1 versus colonial 8 ± 2 ) ( Fig 2C , S1 and S2 Tables ) . Many of the pseudopodial projections and endocytotic vacuoles bore the morphology of lamellipod ruffles and macropinosomes ( Fig 3A ) , suggesting that colonial cells are typified by high macropinocytotic activity . While high-magnification 3D ssTEM enabled the high-resolution reconstruction of individual colonial cells , their context and interactions with neighbouring cells were lost . To address this , we reconstructed the subcellular structures of a seven-cell rosette colony ( complete rosette , RC1 ) from 80-nm sections taken at lower magnification ( Fig 3A–3D , S7 Movie ) as well as the gross morphology of four larger rosettes ( RC2–5 ) from 150-nm sections to provide a more representative survey ( Fig 3E–3P ) . We found that individual cells in rosette colonies vary widely in volume ( Fig 3M and 3N ) , although no pattern was detected in the volumetric cellular arrangement along the rosette z-axis ( Fig 3M ) . In addition , mean cell size was comparable among different rosettes , including those that contained different numbers of cells ( S4B Fig ) . However , we did find a positive correlation between cell number and the number of intercellular bridges per cell across rosette colonies ( S4B Fig ) . Importantly , we uncovered the presence of unusually shaped cells in two of the five S . rosetta rosette colonies ( carrot-shaped cell 5 in RC3 and chili-shaped cell 5 in RC4 , both labelled orange with an asterisk ) ( Fig 3M ) . These unusual cells were both found at the same location along the rosette z-axis , exhibited an elongated morphology distinct from other colonial cells ( Fig 3O and 3P and S8 and S9 Movies ) , and were small in volume . Cells 5 from RC3 and RC4 were 9 . 87 μm3 and 13 . 35 μm3 , respectively ( Fig 3N ) —the mean volume of the cells in RC3 and RC4 was 27 . 38 μm3 and 27 . 25 μm3 , respectively ( Fig 3N ) . While each of these unusual cells possessed a flagellum , a collar , connections to neighbouring cells via intercellular bridges , and had a similar proportion of cell volume dedicated to most of their major organelles as observed in other colonial cells , these cells devoted a larger volumetric percentage of the cell body to the nucleus ( 29 . 8% and 30 . 78% , respectively , versus the mean colonial proportion of 13 . 76% ± 0 . 49% ) . Our 3D ssTEM reconstructions of rosette colonies also revealed the distribution of intercellular bridges and the connections formed between individual cells ( Fig 3M ) . We found intercellular bridges in all analysed rosette colonies ( RC1–5 ) , totalling 36 bridges . There was no detectable pattern regarding bridge networking across rosette colonies . Bridges were distributed from the cell equator to either of the poles along the cellular z-axis , and the average bridge was 0 . 75 ± 0 . 38 μm in length ( S4C Fig ) . Prior studies [12 , 17] of S . rosetta bridges suggested that bridges are typically short ( 0 . 15 μm ) , connecting two adjacent cells and containing parallel plates of electron-dense material . In contrast , the bridges detected in this study exhibited striking morphological diversity ( Fig 3M , 3Q–3U ) , with lengths ranging from 0 . 21–1 . 72 μm . The majority of bridges consisted of a protracted cytoplasmic connection between two cells , and in many cases , the septum was localised asymmetrically along the bridge ( S4C Fig ) . Most surprisingly , some bridges were not connected to any neighbouring cells at all , but rather the septum was situated on the end of a thin , elongated cellular protrusion ( Fig 3S ) . In addition , we observed asymmetric bridge width and degraded electron-dense structures proximal to bridge remnants being incorporated into the cell body of a contiguous cell ( Fig 3T and 3U ) . These data suggest that intercellular bridges could be disconnected from neighbouring cells and that the electron-dense septum may be inherited . Both choanoflagellates and sponge collar cells influence local hydrodynamics by beating their single flagellum to draw in bacteria that are captured by the apical collar complex [23] , however sponge choanocytes are part of an obligately multicellular organism ( Fig 4A ) . Sponge choanocytes therefore provide an excellent representative of an early-branching animal collar cell against which to compare choanoflagellate cell architectures . Our 3D ssTEM reconstructions allowed for the reconstruction of five choanocytes and for the volumetric and numerical comparison of choanocyte and choanoflagellate subcellular structures ( Fig 4B–4E , S5 and S6 Figs , S10 Movie ) . We detected little ultrastructural variability between the five choanocytes ( S5 Fig , S3 and S4 Tables ) . All five cells exhibited a prominent basal nucleus , small and unreticulated mitochondria , food vacuoles scattered around the entire cell , and an apical Golgi apparatus ( Fig 4B–4D , S5 and S6 Figs ) —consistent with the coarse choanocyte cellular architecture reported in previous studies [23 , 24] ( reviewed in [1 , 25] ) . Furthermore , our data showed many ultrastructural commonalities between sponge choanocytes and choanoflagellates . For example , the number of microvilli that surround the apical flagellum in single and colonial choanoflagellates is comparable to the number of microvilli in sponge choanocytes ( single: 32 ± 2 versus colonial: 35 . 3 ± 4 . 9 versus choanocytes: 30 . 6 ± 4 . 1 ) ( S6A Fig ) . We also found that the number of food vacuoles and the number and volumetric proportion of the Golgi apparatus are similar in all three cell types ( S6A Fig ) . Although sponge choanocytes did not appear to exhibit the same macropinocytotic activity as colonial choanoflagellates throughout the cell ( some micropinocytotic inclusions are present toward the cell apex [S6D and S6E Fig] ) , basal sections of choanocytes were heavily amoeboid ( S6B and S6C Fig ) . These amoeboid protrusions may not only be for mechanical anchorage into the mesohyl but may play a role in phagocytosis , as we observed bacteria in the mesohyl to be engulfed by basal pseudopodia ( S6F and S6G Fig ) . Thus , both choanocytes and colonial choanoflagellates are typified by high-amoeboid cell activity . We also observed some ultrastructural differences between choanocytes and choanoflagellates . In contrast with cells from choanoflagellate rosettes , sponge choanocytes lack filopodia and intercellular bridges . Choanocytes also do not possess glycogen reserves and devote significantly less of their cell volume ( 9 . 25% ± 0 . 39% ) than choanoflagellates ( single: 12 . 92% ± 0 . 58% and colonial: 11 . 56% ± 0 . 27% ) to the nucleus and less to mitochondria ( 2 . 5% ± 0 . 3% versus single: 5 . 08% ± 1 . 14% and colonial: 6 . 63% ± 0 . 42% ) ( S6A Fig ) . However , choanocytes devote significantly more of their volume to food vacuoles ( 20 . 7% ± 1 . 01% ) than choanoflagellates ( single: 9 . 22% ± 2 . 75% and colonial: 6 . 85% ± 0 . 87% ) ( Fig 4E ) . High-resolution reconstructions of the choanocyte and choanoflagellate apical pole ( Fig 4F and 4G , S11 and S12 Movies ) showed differences in terms of vesicle type and localisation , Golgi positioning , and collar arrangement ( conical in choanoflagellates while cylindrical in choanocytes , as previously noted [23] ) . The flagellar basal body has previously been meticulously characterised in both choanocytes and choanoflagellates , and some differences have been reported between the two by other authors [26–31] . These findings are reiterated by our reconstructions and observations ( Fig 4F and 4G ) .
While we recognise the limitations of our findings due to the morphological descriptive nature of this study and the small sample size , the comparative 3D reconstruction of collar cells from two different phyla , choanoflagellates and sponges , allowed for an unbiased view of their cellular architecture and for the reconstruction of key properties of the enigmatic ancestral collar cell . Our data reveal distinct ultrastructural features in single and colonial choanoflagellates and demonstrate that cells within rosette colonies vary significantly in their cell size and shape . The newly identified ‘carrot’ and ‘chili’ cells reveal that cells within choanoflagellate colonies do not simply consist of an assemblage of equivalent single cells , but some may represent a distinctly differentiated cell type displaying ultrastructural modifications . Likewise , our data suggest that sponge choanocytes are not simply an incremental variation on the choanoflagellate cell plan but are specialised feeding cells , as indicated by their high volumetric proportion of food vacuoles . Together , our data show a remarkable variety of collar cell architecture and suggest cell type differentiation may have been present in the stem lineage leading to the animals .
Colony-free S . rosetta cultures ( ATCC 50818 ) were grown with coisolated prey bacteria in 0 . 22 μm filtered choanoflagellate growth medium [66] diluted at a ratio of 1:4 with autoclaved seawater . Cultures were maintained at 18°C and split 1 . 5:10 once a week . Colony-enriched S . rosetta cultures ( PX1 ) were likewise maintained but monoxenically cultured with the prey bacterium A . machipongonensis [67] to induce rosette formation . To support the annotation of organelles from ssTEM sections , the microanatomy of S . rosetta cells was chemically characterised by fluorescent vital staining . Cells were pelleted by gentle centrifugation ( 500x g for 10 min at 4°C ) in a Heraeus Megafuge 40R ( ThermoFisher Scientific ) and resuspended in a small volume of culture medium . Concentrated cell suspension ( 500 μl ) was applied to glass-bottom dishes , coated with poly-L-lysine solution ( P8920 , Sigma-Aldrich ) , and left for 10–30 min until cells were sufficiently adhered . PX1 cultures were concentrated into 100 μl of culture medium to promote the adherence of rosette colonies . Adhered cells were incubated in 500 μl of fluorescent vital dye diluted in 0 . 22 μm filtered seawater . Cells were incubated with 4 . 9 μM Hoechst 33342 Dye for 30 min ( to label nuclei ) , 1 μM LysoTracker Yellow HCK-123 for 1 . 5 h ( to label food vacuoles ) , and 250 nM MitoTracker Red CM-H2Xros for 30 min ( to label mitochondria ) . All vital dyes were from ThermoFisher Scientific ( H3570 , L12491 , T35356 , and M7513 , respectively ) . Fluorescent-DIC microscopy was conducted under a 100x oil-immersion objective lens using a Leica DMi8 epifluorescent microscope ( Leica , Germany ) . Vital dyes were viewed by excitation at 395 nm and emission at 435–485 nm ( Hoechst 33342 Dye ) , 470 nm and emission at 500–550 nm ( LysoTracker Yellow HCK-123 and FM 1–43 Dye ) , and 575 nm and 575–615 nm ( MitoTracker Red CM-H2Xros ) . Micrographs were recorded with an ORCA-Flash4 . 0 digital camera ( Hamamatsu Photonics , Japan ) . All cells were imaged live . No-dye controls using only the dye solvent dimethyl sulfoxide ( DMSO ) ( D4540 , Sigma-Aldrich ) were run for each wavelength to identify and control for levels of background fluorescence . Chemical fixation during vital staining and TEM sectioning was avoided where possible in this study to reduce fixation artefacts . To visualise cell bodies , flagella , filopodia , and collar-adherent cells were fixed for 5 min with 1 ml 6% acetone and for 15 min with 1 ml 4% formaldehyde . Acetone and formaldehyde were diluted in artificial seawater , pH 8 . 0 . Cells were washed gently four times with 1 ml washing buffer ( 100 mM PIPES at pH 6 . 9 , 1 mM EGTA , and 0 . 1 mM MgSO4 ) and incubated for 30 min in 1 ml blocking buffer ( washing buffer with 1% BSA and 0 . 3% Triton X-100 ) . Cells were incubated with primary antibodies against tubulin ( E7 , 1:400; Developmental Studies Hybridoma Bank ) , diluted in 0 . 15 ml blocking buffer for 1 h , washed four times with 1 ml of blocking buffer , and incubated for 1 h in the dark with fluorescent secondary antibodies ( 1:100 in blocking buffer , Alexa Fluor 488 goat anti-mouse ) . Coverslips were washed three times with washing buffer , incubated with Alexa Fluor 568 Phalloidin for 15 min , and washed again three times with washing buffer . Coverslips were mounted onto slides with Fluorescent Mounting Media ( 4 ml; Prolong Gold Antifade with DAPI , Invitrogen ) . Images were taken with a 100x oil-immersion objective on a Leica DMI6000 B inverted compound microscope and Leica DFC350 FX camera . Images presented as z-stack maximum intensity projections . ssTEM sections were imported as z-stacks into the Fiji [71] plugin TrakEM2 [72] and automatically aligned using default parameters , except for increasing steps per octave scale to 5 and reducing maximal alignment error to 50 px . Alignments were manually curated and adjusted if deemed unsatisfactory . Organelles and subcellular compartments were manually segmented and 3D reconstructed by automatically merging traced features along the z-axis . Meshes were then preliminarily smoothed in TrakEM2 and exported into the open-source 3D software Blender 2 . 77 [73] . Heavy smoothing of the cell body in TrakEM2 sacrifices fine structures associated with cellular projections or does not remove all distinct z-layers , which exist as reconstruction artefacts . Therefore , cell bodies were manually smoothed using the F Smooth Sculpt Tool in Blender of final distinct z-layers for presentation purposes only ( S3 Fig ) . All organelles were subjected to the same smoothing parameters across individual cells . All analysis was conducted using unsmoothed , unprocessed meshes . Organelle volumes were automatically quantified by the TrakEM2 software and enumerated in Blender 2 . 77 by separating meshes in their total loose parts . The microvillar collar and flagellum were excluded from volumetric analysis , as their total , representative length could not be imaged at this magnification . Cytosolic volume was calculated by subtracting total organelle volume from cell body volume and is inclusive of cytosol , ribosomes , and unresolved smaller structures excluded from 3D reconstruction . Endocytotic vacuoles were distinguished from food vacuoles by connection to the extracellular medium in ssTEMs or by localisation to a cell protrusion . Cells in rosette colonies are numbered in order of their appearance along the image stack z-axis . Rosette colony diameters were calculated by measuring the largest distance of the z-axis midsection . Bridge length was measured in one dimension along the bridge midsection . Mean vesicle diameters were calculated from 20 measurements ( or as many as possible if the vesicle type was rare ) from single cells . Univariate differences in the volume and number of subcellular structures between the two cell types were evaluated using two-sample t tests . Shapiro–Wilk and Levene’s tests were used to assess normality and homogeneity of variance , respectively . Statistical comparisons were conducted using data scaled against total cell volume . Correlations between colony cell number , cell volume , and bridges per cell were assessed using Pearson correlation tests . All statistical analyses were conducted using R v 3 . 3 . 1 [74] implemented in RStudio v 0 . 99 . 903 [75] . | Choanoflagellates are microscopic aquatic organisms that can alternate between single-celled and multicellular states , and sequencing of their genomes has revealed that choanoflagellates are the closest single-celled relatives of animals . Moreover , choanoflagellates are a form of ‘collar cell’—a cell type crowned by an array of finger-like microvilli and a single , whip-like flagellum . This cell type is also found throughout the animal kingdom; therefore , studying the structure of the choanoflagellate collar cell can shed light on how this cell type and animal multicellularity might have evolved . We used electron microscopy to reconstruct in 3D the total subcellular composition of single-celled and multicellular choanoflagellates as well as the collar cells from a marine sponge , which represents an early-branching animal lineage . We found differences between single-celled and multicellular choanoflagellates in structures associated with cellular energetics , membrane trafficking , and cell morphology . Likewise , we describe a complex system of cell–cell connections associated with multicellular choanoflagellates . Finally , comparison of choanoflagellates and sponge collar cells revealed subcellular differences associated with feeding and cellular energetics . Taken together , this study is an important step forward in reconstructing the biology of the last common ancestor of the animals . | [
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... | 2019 | The architecture of cell differentiation in choanoflagellates and sponge choanocytes |
Cells of the myeloid lineage are significant targets for human immunodeficiency virus ( HIV ) in humans and simian immunodeficiency virus ( SIV ) in monkeys . Monocytes play critical roles in innate and adaptive immunity during inflammation . We hypothesize that specific subsets of monocytes expand with AIDS and drive central nervous system ( CNS ) disease . Additionally , there may be expansion of cells from the bone marrow through blood with subsequent macrophage accumulation in tissues driving pathogenesis . To identify monocytes that recently emigrated from bone marrow , we used 5-bromo-2′-deoxyuridine ( BrdU ) labeling in a longitudinal study of SIV-infected CD8+ T lymphocyte depleted macaques . Monocyte expansion and kinetics in blood was assessed and newly migrated monocyte/macrophages were identified within the CNS . Five animals developed rapid AIDS with differing severity of SIVE . The percentages of BrdU+ monocytes in these animals increased dramatically , early after infection , peaking at necropsy where the percentage of BrdU+ monocytes correlated with the severity of SIVE . Early analysis revealed changes in the percentages of BrdU+ monocytes between slow and rapid progressors as early as 8 days and consistently by 27 days post infection . Soluble CD163 ( sCD163 ) in plasma correlated with the percentage of BrdU+ monocytes in blood , demonstrating a relationship between monocyte activation and expansion with disease . BrdU+ monocytes/macrophages were found within perivascular spaces and SIVE lesions . The majority ( 80–90% ) of the BrdU+ cells were Mac387+ that were not productively infected . There was a minor population of CD68+BrdU+ cells ( <10% ) , very few of which were infected ( <1% of total BrdU+ cells ) . Our results suggest that an increased rate of monocyte recruitment from bone marrow into the blood correlates with rapid progression to AIDS , and the magnitude of BrdU+ monocytes correlates with the severity of SIVE .
Monocytes of bone marrow origin are circulating precursors that give rise to and replenish macrophage populations in tissues , including the brain [1] . Monocytes that originate from hematopoietic stem cells in bone marrow undergo three stages of differentiation from monoblasts to promonocytes and then monocytes where they are released into the circulation [2]–[4] . Current dogma defines that human and non-human primate monocytes do not divide out of the bone marrow [5] . Blood monocytes are thought to circulate in the vasculature for approximately 24–72 hours before differentiation into macrophages in tissues [2] , [6] . Continuous extravasation and differentiation of circulating monocytic precursors has long been considered the sole source of tissue macrophages [7] . Other mechanisms to maintain tissue macrophage homeostasis have been identified and described in rodents including: 1 ) self-renewal of differentiated resident cells and 2 ) homing and limited proliferation of bone marrow derived precursors in tissues [5] , [8]–[11] . Such mechanisms are not thought to function in humans . Nevertheless , in both rodents and primates in acute inflammation , monocytes are recruited to tissue compartments [2] , [12]–[14] . With acute inflammation , the half-life of circulating monocytes is decreased coincident with an accumulation of macrophages at the inflamed site [15] , [16] . The half-life of circulating monocytes in chronic inflammation is undefined . Prior studies of monocyte kinetics used autoradiographic analysis and radiolabeled thymidine or indium chloride incorporation , which was powerful but of limited utility due to the toxicity of radiolabel [6] , [15]–[18] . More recently , we and others used the thymidine analog 5′-bromo-2′-deoxyuridine ( BrdU ) to quantify the turnover and release of monocytes from bone marrow [19]–[24] . BrdU is incorporated into cellular DNA during replication , at the S-phase of the cell cycle . Monocytes are released from the bone marrow into the circulation shortly after the completion of S phase , thus BrdU is a reliable marker for monocytes newly released into blood [20] , [21] . We have shown that increased BrdU incorporation in monocytes with SIV infection is associated with macrophage cell death in lymph nodes [20] . Increased percentage of BrdU+ monocytes correlated with AIDS more so than CD4+ T lymphocyte loss or viral load [20] . In this report , we confirm and extend these observations in a serial pathogenesis study of monocyte expansion with emphasis on the severity of SIVE and identification of a plasma marker of monocyte expansion . Monocytes have been shown to play a critical role in HIV and SIV disease pathogenesis [25]–[29] . The expansion of the number and/or relative percentage of CD14+CD16+ monocytes correlates with the incidence of HIV encephalitis ( HIVE ) and accumulation of monocyte/macrophages in HIVE lesions correlates with dementia [25] , [30] , [31] . Similarly , our laboratory has shown that SIV-infected CD8+ T lymphocyte depleted rhesus macaques have a biphasic increase in the percentage and absolute numbers of CD14+CD16+ monocytes with viremia and later with the development of AIDS [32]–[35] . Whether this is from increased recruitment of monocytes from bone marrow or recirculation from tissue sources is not defined . We hypothesized that increased monocyte production from bone marrow and traffic into the brain during SIV infection correlates with rapid development of AIDS and severity of SIVE . To test this , we examined BrdU+ incorporation of monocytes in a longitudinal serial-sample pathogenesis study using SIV-infected CD8+ T lymphocyte depleted rhesus monkeys [36]–[38] . We show BrdU+ monocytes are negative for the proliferation marker Ki-67 , consistent with monocytes labeled with BrdU in the marrow that do not proliferate in the blood . We demonstrate a significant correlation between the increased percentage of BrdU+ monocytes in blood at necropsy and the severity of SIV disease . Moreover , we find within CD8+ T lymphocyte depleted animals the magnitude of BrdU+ monocytes is equal with the rate of disease progression . We have identified BrdU+ monocyte/macrophages accumulating in the CNS perivascular space and SIVE lesions . About 80–90% of BrdU+ cells are Mac387+ that are not productively infected and likely representative of recently recruited monocyte/macrophages . A rare population of CD68+ macrophages are BrdU+ and also productively infected . These results suggest that an increased number of monocytes emigrating from the bone marrow occurs with rapid progression to AIDS and correlates with the severity of SIVE at necropsy . These data further point to the traffic of BrdU+ cells into the CNS . We did not find a correlation between BrdU+ monocytes in blood and plasma LPS levels , but found a correlation with soluble CD163 ( sCD163 ) levels in plasma , consistent with monocyte activation and stimulation of innate immunity [39]–[45] . Overall these data suggest that increased monocyte production from bone marrow , traffic to the brain , and overall monocyte activation play major roles in HIV and SIV neuropathogenesis .
In this pathogenesis study , we utilized seven SIVmac251-infected rhesus macaques that were depleted of CD8+ T lymphocytes by three injections of a CD8-specific mouse-human chimeric antibody ( cM-T807 ) at 6 , 8 and 12 days post infection . Of these , one animal was CD8+ T lymphocyte depleted for 21 days ( “transiently” depleted ) and six for greater than 28 days ( “persistently” depleted ) ( Table 1 ) . Animals were sacrificed upon the development of AIDS ( criteria described in Materials and Methods ) . This cohort could be subdivided into slow and rapid progressors . Of the rapid progressors , five animals were sacrificed with AIDS ( 56 , 75 , 77 , 89 and 92 days post infection ) and four had SIV encephalitis ( SIVE ) ( criteria described in Materials and Methods ) . Of the two slow progressors , one was sacrificed at 131 days post infection and the other did not develop AIDS and is still alive ( Table 1 ) . To examine if the rate of monocyte turnover and traffic into the brain during SIV infection correlates with disease progression , we performed serial sample of monocytes 24hrs after BrdU injection at multiple time points . Flow cytometry on whole blood was used to identify BrdU+ monocytes with the gating strategy defined in Figure 1 . Monocytes were first identified by FSC versus SSC profiles , and selection of HLA−DR+ cells with exclusion of CD3+ , CD8+ , and CD20+ cells . The percentage of BrdU+ monocytes was calculated from total monocytes: CD14+CD16− , CD14+CD16+ and CD14−CD16+ ( excluding CD14−CD16− cells ) ( Figure 1 ) . We have previously shown that monocytes in the bone marrow were BrdU+Ki-67+ [20] . However , in blood we found that CD14+ monocytes are BrdU+Ki-67− ( Figure 1 ) . These results are consistent with non-proliferating blood monocytes labeled with BrdU in bone marrow that lose Ki-67 post-proliferation ( within 24–48 hours ) , when cells are in the blood [3] , [46]–[49] . The CD14−CD16− cells , likely comprised of CD34+ hematopoietic stem cells and dendritic cells ( DCs ) , are BrdU+ and Ki-67+ ( Figure 1 ) . These data are consistent with recent reports [20] , [21] . BrdU incorporation in monocytes 24hrs post-BrdU injection in control , uninfected CD8+ T lymphocyte depleted animals showed that CD8+ T lymphocyte depletion alone did not affect monocyte turnover ( Figure 2A; n = 4 ) . The percentage of BrdU+ monocytes after CD8+ T lymphocyte depletion was the same as pre-depletion ( approximately 2% ) . There was no correlation between the percentage of BrdU+ monocytes and days post CD8+ T lymphocyte depletion in uninfected animals ( r = 0 . 02427 , P = 0 . 9289 ) . There was an increase in BrdU+ monocytes in CD8+ T lymphocyte-depleted infected ( Figure 2B–C ) versus uninfected control animals ( Figure 2A ) and a higher percentage of BrdU+ monocytes in rapid ( Figure 2C ) versus slow progressors ( Figure 2B ) . Differences in the percentage of BrdU+ monocytes between animals with rapid versus slow progression were evident as early as 8 and consistent at 27 days post infection ( Figure 2B–C ) . No correlation was detected between the percentage of BrdU+ monocytes and days post infection in slow progressors ( Figure 2B; r = −0 . 1464 , P = 0 . 7294 ) . In fact , the percentage of BrdU+ monocytes in these animals was similar to non-infected controls . There was a dramatic increase in the percentage of BrdU+ monocytes in the rapid progressors and a significant correlation between the percentage of BrdU+ monocytes and days post infection ( Figure 2C; r = 0 . 7651 , P = 0 . 0006 ) . At end stage disease , the percentage of BrdU+ monocytes correlated with the severity of SIVE ( Figure 2C ) . In rapid progressors , the percentage of BrdU+ cells prior to infection ranged from 0 . 85% , to 2 . 77% . This percentage increased with infection and at necropsy was 6 . 27% in an animal with AIDS but no SIVE ( AIDS noE ) , 11 . 0% in an animal with mild SIVE , and 23 . 4% and 31 . 5% in animals with severe SIVE ( Figure 2C ) . Thus , the percentage of BrdU+ monocytes correlated with time after infection in rapid progressors and was increased with severity of SIVE at necropsy ( Figure 2C ) . To further study if increased monocyte turnover can predict rapid progression to AIDS , we examined other parameters previously linked to disease progression including CD4+ T lymphocyte numbers , CD4+ T lymphocyte turnover , and plasma viral load ( Figure 3A–D ) . Using our model of CD8+ T lymphocyte depletion and SIV infection , plasma viral loads peaked by day 8 and remained high throughout the course of disease , consistent with persistently depleted animals ( Table 1 ) [32] , [36] . No correlation was found between percentage of BrdU+ monocytes and percentage of BrdU+CD4+ T lymphocytes ( P = 0 . 2845 ) or numbers of CD4+ T lymphocytes ( P = 0 . 6641 ) ( Figure 3A and B , respectively ) . In addition , there was no correlation between plasma virus and the percentage of BrdU+ monocytes ( P = 0 . 7880 ) or percentage of BrdU+CD4+ T lymphocytes ( P = 0 . 3701 ) ( Figure 3C and D , respectively ) . Because the number of CD4+ T cells increase with CD8+ lymphocyte depletion , the CD4+ numbers are not comparable to non-CD8 depleted animals [38] . We examined the kinetics of BrdU+ monocyte subsets ( CD14+CD16− and CD14+CD16+ ) entering and exiting blood at four time points: pre-infection ( 9 days before infection ) , peak infection ( 7 days post infection ) , 26 days post infection , and either 88 days post infection ( slow progressors ) or 24hrs prior to necropsy ( rapid progressors ) ( Figure 4A–B and 4C–D ) . The percentage of BrdU incorporation was measured at 24hrs and 48hrs and either 96 or 120hrs after a single BrdU injection . First , BrdU incorporation was examined before SIV infection . In all animals , the percentage of “classical” CD14+CD16− monocytes that were BrdU+ peaked in blood 48hrs post BrdU ( Figure 4A and C; red lines ) , whereas the “inflammatory” CD14+CD16+ cells that were BrdU+ peaked at 96hrs post BrdU ( Figure 4B and D; red lines ) . This suggests that CD14+CD16+ cells might arise from CD14+CD16− monocytes in the blood after leaving the bone marrow or that the majority of the CD14+CD16+ cells leave the bone marrow later than the CD14+CD16− cells . Second , the effect of SIV infection on kinetics of BrdU+ monocyte subsets was examined . In contrast to slow progressors , a peak in the percentage of BrdU+CD14+CD16− monocytes in rapid progressors appeared at 24hrs post BrdU after infection ( Figure 4C; blue , green , black lines ) . The percentage of BrdU+CD14+CD16+ monocytes was increased after infection at 48hrs post BrdU in both slow and rapid progressors ( Figures 4B and D; blue , green , black lines ) , with a greater increase in the rapid progressors ( Figure 4D ) . There was no change in any of the monocyte subsets in the uninfected CD8+ T lymphocyte depleted animals ( data not shown ) . Consistent with previous literature describing an increase of CD14+CD16+ cell numbers in animals with SIVE [25]–[27] , [30] , [50] , [51] , the absolute number of CD14+CD16+ monocytes was elevated in the rapid progressors ( data not shown ) . There was no change in the absolute number of CD14+CD16+ monocytes in the slow progressors throughout infection ( data not shown ) . Recent studies have shown an association of high plasma LPS with increased sCD14 thus implicating monocyte activation in HIV infection [52] , [53] . Exact correlates between HIV dementia and plasma LPS were not found [53] . We therefore examined plasma LPS as a potential stimulus for emigration of monocytes from the bone marrow . There were no significant differences in plasma LPS levels between rapid and slow progressors ( Figure 5A; rapid progressors = solid lines , slow progressors = dotted lines ) and no significant correlation between the percentage of BrdU+ monocytes and plasma LPS levels ( Figure 5B; r = −0 . 2040 , P = 0 . 5038 ) . To examine whether increased circulating CCL2/monocyte chemoattractant protein 1 ( MCP-1 ) can result in enhanced monocyte emigration from bone marrow , plasma CCL2 levels in SIV-infected animals were examined ( Figure 5C ) . Plasma CCL2 levels increased at 9 days post infection and then moderately decreased in all animals , except one slow progressor whose CCL2 concentration returned to pre-infection levels ( Figure 5C; rapid progressors = solid lines , slow progressors = dotted lines ) . There was no correlation between the percentages of BrdU+ monocytes and plasma CCL2 ( Figure 5D; r = 0 . 1049 , P = 0 . 7456 ) . Interestingly , sCD163 did correlate with BrdU incorporation , consistent with activation of monocyte/macrophages and increased monocyte traffic from the bone marrow ( Figure 5E and F ) [35] , [39]–[42] , [45] , [54] , [55] . In all animals examined , plasma sCD163 levels increased by 9 days post infection , the time point when slow and rapid progressors can be distinguished by differences in the percentage of BrdU+ monocytes ( Figure 5E ) . At day 20 , in slow progressors sCD163 plasma levels decreased ( Figure 5E , dotted lines ) , but in rapid progressors sCD163 levels continued to increase ( Figure 5E , solid lines ) . There was a significant correlation between the percentage of BrdU+ monocytes and plasma sCD163 levels ( Figure 5F; r = 0 . 6391 , P = 0 . 02 ) . Thus , sCD163 levels , but not plasma LPS or CCL2 , correlated with the increased percentage of BrdU+ monocytes in the blood of CD8+ T lymphocyte depleted SIV-infected macaques . In a recent study , we showed that higher levels of BrdU+ monocytes in blood were associated with macrophage apoptosis in lymph nodes [20] . By flow cytometry , we did not find Annexin V+ BrdU+ monocytes suggesting that monocytes were not undergoing apoptosis in blood ( data not shown ) . Herein , we examined BrdU labeled cells in the CNS investigating their distribution in the brains of three animals , two with severe SIVE and one with mild SIVE ( Figure 6 ) . The majority of the BrdU+ cells in all brains were located within SIVE lesions and in the vasculature ( Figure 6A and B; BrdU: DAB ) . BrdU+ cells comprised 15 . 6 and 17 . 5% of total cells within SIVE lesions in two rapid progressors with severe SIVE ( Table 2 , Figure 6A ) . In the animal with mild SIVE , similar percentages of BrdU+ cells were found in lesions , but there were fewer overall lesions . To determine the identity of the BrdU+ cells , double immunohistochemistry was performed using antibodies against CD3 for T cells , GFAP for astrocytes , CD68 for resident macrophages and Mac387 for recently infiltrated monocyte/macrophages [56] , [57] . There was little to no CD3+ T lymphocytes found in any sections examined ( Figure 6C; BrdU: DAB and CD3: Vector Blue ) . BrdU+ cells were found in close proximity to GFAP+ astrocytes , but very few scattered double positive astrocytes ( GFAP+BrdU+ ) were found ( Figure 6D and E; BrdU: DAB and GFAP: Vector Blue ) . Approximately 10% of total BrdU+ cells in SIVE lesions were CD68+ and these BrdU+ cells comprised between 1 . 8 and 4 . 6% of all CD68+ macrophages in lesions ( Figure 6F and G; BrdU: DAB and CD68: Vector Blue and Table 2 ) . Between 81 to 92% of all BrdU+ cells in SIVE lesions were Mac387+ , representing approximately a third of the total Mac387+ monocyte/macrophages in lesions ( Figure 6H and I; BrdU: Vector Blue and Mac387: DAB and Table 2 ) . The animal with mild SIVE had similar percentages of BrdU+Mac387+ and BrdU+CD68+ cells in lesions as the animals with severe SIVE . In the brains of control non-infected CD8+ T lymphocyte depleted animals , few scattered BrdU+ macrophages were detected , representing normal monocyte traffic ( data not shown ) . Less than 1% of all BrdU+ cells in SIVE lesions were SIVp28+ and less than 0 . 2% of all SIVp28+ cells were also BrdU+ ( Table 2 ) . Double positive BrdU and SIVp28 cells are very rare events , thus , resulting in few productively infected BrdU monocyte/macrophages . Immunofluorescence confirmed the presence of numerous BrdU+ cells in blood vessels ( Figure 7A ) , perivascular cuffs ( Figure 7A ) , and SIVE lesions ( Figure 7B–D ) and showed that the majority of the BrdU+ cells were Mac387+ cells ( Figure 7C; BrdU: Vector Blue and Mac387: DAB ) that were not productively infected . Immunofluorescence was used to identify that the productively SIV infected BrdU+ cells were CD68+ macrophages ( Figure 7A–B and 7D; white arrow ) . Thus , the majority of the BrdU+ cells in the brain were Mac387+ that were not productively infected , representing monocyte/macrophages that were labeled with BrdU in the bone marrow and had recently trafficked to the brain ( likely from the last two BrdU pulses ) . These data are consistent with Mac387 as one of the earliest differentiation markers expressed on monocyte/macrophages as they enter tissues [56] , [57] .
Here we have presented data showing that increased monocyte turnover is predictive of rapid development of AIDS . We have demonstrated that an increased percentage of BrdU+ monocytes in blood correlated with the severity of SIVE at necropsy . Interestingly , the differences in the percentage of BrdU+ monocytes were apparent by 8 days post infection and differentiated between slow and rapid progression by 27 days post infection . This data lends support to the importance of early monocyte activation and deregulation in AIDS pathogenesis . Furthermore , sCD163 levels , but not plasma LPS or CCL2 , correlated with increased percentages of BrdU+ monocytes in the blood of SIV-infected macaques . In addition , we showed a differential rate of turnover in two major monocyte populations ( CD14+CD16− and CD14+CD16+ ) and the acceleration of their turnover in rapid progressors . BrdU+ cells were detected in the brains of animals with SIVE; the majority of these cells were Mac387+ that were SIV p28− and a minor population of CD68+ macrophages , few of which were productively infected . The data presented here underscore the importance of increased monocyte turnover and traffic to the brain during SIVE , and emphasize in this model that CNS lesion formation is an active process requiring monocyte/macrophage recruitment , likely a result of enhanced innate immune responses [27] , [35] . These data confirm and extend the observations recently reported by Hasegawa and colleagues , who examined BrdU incorporation in animals at different stages of SIV infection and found an increase in the percentage of BrdU+ monocytes with acute and chronic infection and a greater expansion with AIDS [20] . Our results are consistent with that finding , but add the observation that increased BrdU incorporation in monocytes correlates with the severity of SIVE and can distinguish between slow and rapid progressors . We have presented evidence that increased monocyte traffic from bone marrow into the circulation correlates with the rapid progression to AIDS and severity of SIVE . BrdU+ monocytes traffic from bone marrow through the circulation into the brain , fostering the development of AIDS and SIVE . An increase in monocyte traffic in uninfected animals or slow progressors was not found . These data underscore the important role of monocyte activation and augmented traffic from the bone marrow to the brain in SIV neuropathogenesis . Bone marrow diffusion has been reported to correlate with the incidence of HIV dementia [58] . Additionally , anemia before the onset of AIDS is predictive of HIV neuropathogenesis [35] , [58] . It has been demonstrated in SIV infected monkeys that rapid disease progression is the best correlate with the development of SIVE [59] . Our data support these observations and extend these to include that the rate of monocyte turnover , demonstrated by the percentage of BrdU+ monocytes , correlates with the rapid development of AIDS and the severity of SIVE . The CD8 depletion , SIV infection model produces rapid AIDS with a high incidence of SIVE by depleting cytotoxic T lymphocytes . Using this model , there were both slow and rapid disease progressing animals with varying degrees of severity of SIVE that correlated with the percentage of BrdU+ monocytes . However , CD4+ T lymphocytes , which are linked to CD8+ T lymphocytes , are not regulated in a normal fashion due to depletion of CD8+ T lymphocytes [38] , a possible reason for the lack of a correlation between CD4+ T lymphocytes with BrdU+ monocytes in our study . However , in a previous report using non-CD8 depleted SIV infected monkeys , high monocyte turnover also did not correlate with CD4+T cell number or plasma viral load [20] . We found that the percentage of BrdU+ monocytes does not correlate with LPS or CCL2 levels in plasma , but interestingly sCD163 did; this is consistent with the notion that activation of monocyte/macrophages and the increase of monocyte traffic from the bone marrow drive CNS pathogenesis [39] , [40] . Previous in vivo and in vitro studies have shown that CD163 expression on monocytes inversely correlated with sCD163 in plasma or tissue culture media directly linking sCD163 to monocyte activation [39] , [45] , [55] . In vitro studies show picogram levels of LPS results in sCD163 release from monocytes , underscoring the role of innate immune responses in AIDS pathogenesis [45] . In addition , the level of sCD163 has been shown to increase in association with macrophage mediated diseases , including sepsis [40] and Gaucher's disease [60] , characterized by macrophage accumulation in the liver and spleen [60] . Thus , increased traffic of monocytes from the bone marrow ( increased BrdU+ monocytes in the circulation ) and increased levels of sCD163 in the plasma are consistent with an inflammatory environment resulting from stimulation of innate immunity that may play important roles in the development of SIVE . Release of monocytes from the bone marrow could be triggered by increased apoptosis of monocytes in the blood . Although CD3+CD4+ T cells from HIV-1 subjects have been shown to undergo constitutive and induced apoptosis [61] , HIV-1+ monocytes are resistant [61] . Recently , it was demonstrated that peripheral blood monocytes from chronically HIV-1 infected individuals have a stable anti-apoptotic gene signature suggesting a greater resistance to apoptosis in circulating monocytes during HIV infection [61] . In this study , pro-apoptotic genes were down-regulated and anti-apoptotic genes were up-regulated in infected monocytes [61] . When we examined whole blood by flow cytometry for the presence of apoptotic monocytes , we did not detect monocytes that were Annexin V and propidium iodide ( PI ) positive 24hrs after BrdU injection ( data not shown ) . Thus , we could rule out apoptosis of peripheral blood monocytes as a trigger for the increased release of monocytes from the bone marrow . Apoptosis of tissue macrophages in lymph nodes has already been demonstrated to correlate with the percentage of BrdU monocyte label in blood [20] . A report by Serbina and Pamer suggested that monocyte emigration from bone marrow during bacterial infection requires signals mediated by the chemokine receptor CCR2 [62] . Using a Ccr2−/− mouse model , it was found that CCR2 is important for release of Ly6Chi monocytes ( equivalent to the CD14+CD16− monocytes in humans ) from bone marrow [62] . A more recent paper concluded that not only CCL2 , but also CCL7 ( MCP-3 ) was critical in monocyte mobilization from the bone marrow [63] . We did not see a correlation between CCL2 plasma levels and the percentage of BrdU+ monocytes , but that does not rule out the involvement of CCR2 and additional ligands . In addition , the chemokine CXCL12 ( SDF-1 ) and its receptor CXCR4 are known to be involved in the retention of hematopoietic stem cells in the bone marrow [64] , [65] . The roles of these additional factors are worthy of exploration in the SIV model of disease and may lead to further insight into the increased release of monocytes from the bone marrow during AIDS and SIVE progression . Not only did we find differences in the percent of BrdU+ total monocytes between slow and rapid progressors , but we found kinetic differences in BrdU incorporation of two monocyte subsets , CD14+CD16− and CD14+CD16+ entering the blood from the bone marrow . In the rapid progressors , the percentage of BrdU incorporation was increased dramatically with infection in both populations . The CD14+CD16− ( CCR2+ ) monocyte population may have accelerated release due to increased levels of MCP-3 , as discussed above . The CD14+CD16+ monocyte blood population has been shown to be phenotypically similar to perivascular macrophages in the brain , which supports the concept that the CD14+CD16+ monocytes transmigrate into the brain to differentiate further into perivascular macrophages [25] , [33] . Our data suggests that although CD14+CD16+ cells leave the bone marrow later than CD14+CD16− cells , the CD14+CD16+ cells spend less time in the circulation , possibly a result of traffic to tissues . This likelihood is supported by the finding that CD14+CD16+ monocytes are inflammatory mediators expressing high levels of pro-inflammatory cytokines and are potent antigen presenting cells . We have not ruled out the possibility that CD14+CD16− monocytes convert to CD14+CD16+ monocytes in blood [66] . The overall number of brain macrophages in HIVE and SIVE is increased despite evidence of proliferation in situ , supported by the notion that the majority of these macrophages are derived from the periphery [25] , [34] . Here , we present evidence that newly infiltrated BrdU+ monocyte/macrophages are a significant population of monocyte/macrophages in perivascular cuffs and lesions in brains of SIVE+ animals . Recruited monocytes may increase the number of viral target cells in the brain . Most of the BrdU+ cells were Mac387+ cells representing newly recruited and infiltrated monocytes/macrophages [56] , [57] . It is not known how long the BrdU+Mac387+ cells stay in the CNS with lesion formation nor at which BrdU pulse these cells were labeled in the periphery . This might , in part , explain why CD68+BrdU+ cells are found in the CNS; they might have trafficked earlier as less mature cells and undergone maturation within tissues . Additionally , the CD68+ BrdU+ cells could have migrated directly from the blood , thus bringing HIV into the CNS . Lastly , they may represent macrophages that divided in the CNS , although we believe this in unlikely since we found little evidence of BrdU+ microglia , astrocytes or epithelial cells in our studies . We have previously shown using specific markers for cell proliferation , including Ki-67 and topoisomerase II alpha , that macrophages within SIVE lesions were not undergoing significant active proliferation in the time frame studied [34] . Increased monocyte turnover correlated with high levels of sCD163 in plasma . These findings along with potential anti-inflammatory properties of sCD163 [44] , which is directly shed from the M2 anti-inflammatory alternative activated macrophages [39] , [67] , suggest that BrdU+ cells recruited to the CNS may aid in lesion resolution . Monocyte/macrophages may traffic to the brain as inflammatory cells in response to or causing neuronal injury or as anti-inflammatory vehicles to minimize injury to the brain during SIV infection . Although we detected very few SIVp28+ BrdU+ cells in SIVE brains , this does not rule out the possibility that the BrdU+ cells are not latently infected . In fact , our data suggests BrdU+ cells may act as viral reservoirs that may with maturation actively replicate virus . Our finding that only the BrdU+CD68+ monocytes are productively infected underscores the importance of monocyte/macrophage maturation ( possibly Mac387 to CD68 expression ) for active viral replication . Invasion of the CNS by BrdU+Mac387+ perivascular macrophages with concomitant viral infection of the CNS compartment upon maturation is a likely scenario for this . Overall , our data examining BrdU+ monocytes in blood and BrdU+ monocyte/macrophages with the brain , underscore the role of monocyte/macrophages derived from bone marrow in AIDS pathogenesis and CNS disease .
All animals were handled in strict accordance with good animal practice as defined by the Harvard University's Institutional Animal Care and Use Committee , and all animal work was approved by this committee . Eleven rhesus macaques were utilized in this study . Seven animals were infected with SIVmac251 ( 20 ng of SIV p27 ) by intravenous injection , kindly provided by Ronald Desrosiers . In order to achieve rapid disease progression with high incidence of SIVE , animals were CD8+ T lymphocyte depleted by treatment with a human anti-CD8 antibody cM-T807 administered s . c . ( 10mg/kg ) at 6 days post infection and i . v . ( 5mg/kg ) at 8 and 12 days post infection ( previously described [32] ) . Four uninfected animals were used as controls: two were CD8+ T lymphocyte depleted by treatment with a human anti-CD8 antibody cM-T807 administered once ( 50mg/kg ) i . v . and two were CD8+ T lymphocyte depleted by treatment with a rhesus anti-CD8 antibody cM-T807 administered once ( 50mg/kg ) i . v . These antibodies were provided by the NIH Non-human Primate Reagent Resource ( RR016001 , AI040101 ) . CD8+ T lymphocyte depletion was monitored by flow cytometry prior to antibody treatment and weekly thereafter during infection ( as previously described [32] ) . All animals were housed at Harvard University's New England Regional Primate Research Center in accordance with standards of the American Association for Accreditation of Laboratory Animal Care . Animals were anesthetized with ketamine-HCl and euthanized by an intravenous pentobarbital overdose and exsanguinated . Animals were sacrificed with any of the following 5 criteria: 1 . weight loss >15% body weight in 2 weeks or >30% body weight in 2 months , 2 . documented opportunistic infection , 3 . persistent anorexia >3 days without explicable cause , 4 . severe intractable diarrhea , progressive neurological signs or 5 . significant cardiac and/or pulmonary signs . The diagnosis of AIDS was determined by the presence of AIDS defining lesions: Pneumocystis pneumonia , Mycobacterium avium infection ( most commonly small intestine , liver and mesenteric lymph node ) , intestinal adenovirus infection ( most common in small intestine ) . Other , less common lesions include SIV giant cell disease in the lung , gut , and lymph nodes and SIV associated arteriopathy . SIV encephalitis ( SIVE ) was defined by the presence of multinucleated giant cells ( MNGC ) and accumulation of macrophages , some of which are infected [59] , [68]–[70] . No animals with opportunistic infections in the CNS were used in this study . Plasma SIV RNA was quantified using real-time PCR as previously described [71] . SIV virions were pelleted from 0 . 5ml EDTA plasma by centrifugation at 20 , 000 g for 1 hour . The fluorescently labeled , real-time PCR probe employed contained a non-fluorescent quencher , BHQ-1 , at its 3′ end . The threshold sensitivity was 100 copy Eq/ml , with an average interassay coefficient of variation of less than 25% . A 30 mg/ml stock of solution was prepared by adding 5-bromo-2′-deoxyuridine ( BrdU ) ( Sigma ) to 1× PBS ( without Ca2+ and Mg2+ ) , U . S . P . grade ( Aestus Pharmaceuticals ) and heated to 60°C in water bath ( as previously described [20] , [24] ) . BrdU was administered as a slow bolus i . v . injection at a dose of 60 mg BrdU/kg body weight . In the uninfected animals , BrdU was given four times throughout the study ( days −11 , 3 , 38 and 72 days post-CD8 antibody administration ) . In the infected animals , BrdU was administered pre-infection ( day −9 ) , peak infection ( day 7 ) , and days 26 , day 50 ( n = 1 ) and 88 ( n = 2 ) post infection and 24 hours prior to necropsy ( n = 4; days 55 , 76 , 88 and 91 ) . CM07 did not receive BrdU prior to necropsy . Flow cytometric analyses were performed with 100 µl aliquots of EDTA-coagulated whole blood . Erythrocytes were lysed using ImmunoPrep Reagent System ( Beckman Coulter ) , washed twice with PBS containing 2% FBS , then incubated for 15 minutes at room temperature with fluorochrome-conjugated surface antibodies including anti-HLA-DR-PerCp-Cy5 . 5 ( clone L243 ) , anti-CD16-PE-Cy7 ( clone 3G8; BD Biosciences ) , anti-CD3-APC ( clone SP34-2 ) , anti-CD8-APC ( clone RPA-T8; ) , anti-CD20-APC ( clone 2H7 ) and anti-CD14-Pacific blue ( clone M5E2 ) ( BD Biosciences ) . For intracellular staining , cells were fixed and permeabilized with BD Cytofix/Cytoperm™ buffer ( BD Biosciences ) for 30 mins at room temperature . Cells were again washed and incubated with BD Cytoperm Plus™ buffer for 10 mins on ice , then washed and incubated with DNase ( 30mg ) for 1hr at 37°C , washed and then stained for intracellular antigen with anti-BrdU-FITC ( clone 3D4; BD Biosciences ) and anti-Ki-67-PE ( clone B56; BD Biosciences ) for 20 mins at room temperature . For controls , BrdU naïve animals and isotype controls were used . To test for apoptotic monocytes anti-Annexin V ( Invitrogen ) and propidium iodine ( PI; BD Biosciences ) were used . Samples were acquired on a BD FACS Aria ( BD Biosciences ) and analyzed with Tree Star Flow Jo version 8 . 7 . Soluble CD163 ( sCD163 ) and CCL2 plasma levels were quantified by ELISA according to manufacturer's protocol ( Trillium Diagnostics and R&D Systems , respectively ) . The Diazo-coupled Limulus amebocyte lysate ( LAL ) assay ( Associates of Cape Cod Inc . ) was used to quantify endotoxin/liposaccharide ( LPS ) levels in plasma from SIV-infected animals , according to the manufacturer's protocol . Briefly , samples diluted 1/5 were inactivated for 30 min at 65°C and incubated with LAL for 30 min at 37°C . Addition of reagents led to formation of a magenta derivative that absorbs light at 570 nm . For LAL assay , samples were handled with non-pyrogenic plastic or glassware to avoid LPS contamination . Formalin-fixed , paraffin-embedded brain tissues were deparaffinized and assessed by immunohistochemistry for BrdU ( Mouse IgG1; Dako , 1∶50 , 1hr room temperature . Before primary antibody incubation , non-serum protein block was applied . The EnVision+ System- horseradish peroxidase ( HRP ) ( EnVision+ Kit; DAKO ) was used according to the manufacturers' instructions . The color reaction product was developed using 3 , 3′-diaminobenzidine tetrahydrochloride ( DAB; DAKO ) as the chromogenic substrate for HRP . The sections were counterstained with hematoxylin and then dehydrated and mounted . Controls consisted of the addition of isotype-matched immunoglobulin . To detect BrdU+ cells and CD3+ T lymphocytes , GFAP+ astrocytes , SIVp28+ infected cells , CD68+ macrophages and Mac387+ monocyte/macrophages in monkey brains , double-label immunohistochemistry was performed using the DAKO Double Stain System , according to the manufacturer's instructions . The color reaction product was developed using DAB and Vector Blue ( Vector Laboratories ) . Sections were visualized under a Zeiss Axio Imager M1 microscope ( Carl Zeiss MicroImaging , Inc . , Thornwood , NY ) using Plan-Apochromat ×20/0 . 8 and ×40/0 . 95 Korr objectives . Tissues were collected in 10% neutral buffered formalin , and embedded in paraffin . Tissues were sectioned at 6 µm and deparaffinized with xylene and hydrated in graded alcohols . Immunohistochemical staining followed a basic protocol using a citrate antigen retrieval method . For immunofluorescence , sections were blocked with 10% normal goat serum ( NGS ) in PBS with 0 . 2% Fish Skin Gelatin ( FSG ) ( Sigma ) for 40 min . Tissues were incubated with rat anti-BrdU ( IgG2a; BU1/75 , Novus Biologicals , 1∶50 , 1hr RT ) followed by AlexaFluor 568 conjugated goat anti-rat IgG ( Molecular Probes; 1∶500 ) , then with mouse anti-SIV p28 ( IgG1; Microbix Biosystems , 1∶500 ) followed by AlexaFluor 488 conjugated goat anti-mouse IgG1 ( Molecular Probes; 1∶500 ) and then CD68-biotin conjugated ( 1∶20 , overnight at 4°C ) followed by streptavidin conjugated AlexaFluor 568 ( Molecular Probes; 1∶500 ) . After immunofluorescence labeling and washing , sections were treated with 50 mmol/L CuSO4 ammonium buffer for 45 minutes to quench auto-fluorescence . Confocal microscopy was performed using a Leica TCS SP2 laser-scanning microscope equipped with 3 lasers ( Leica Microsystems , Exton , PA ) . Individual optical slices represent 0 . 2 µm . Optical slices were collected at 512×512 pixel resolution . The fluorescence of individual fluorochromes was captured separately in a sequential mode , after optimization to reduce bleed-through between channels ( photomultiplier tubes ) using Leica software . NIH Image v1 . 62 and Adobe Photoshop v7 software were used to assign correct colors of up to four channels collected ( 3 fluorochromes: Alexa 488 ( green ) , Cy3 , Alexa 568 ( red ) , and Alexa 647 ( far red ) , and the differential interference contrast image ( gray scale ) . For statistical analyses we used the Prism version 5 . 0a ( GraphPad Software , Inc . , San Diego , CA ) software . Spearman rank test was used for all correlations . | Human immunodeficiency virus ( HIV ) and the closely related simian immunodeficiency virus ( SIV ) can infect monocyte/macrophages , which enter and accumulate in the brain leading to neuronal dysfunction . Monocyte/macrophages exit the bone marrow , transit through the blood and enter the central nervous system ( CNS ) . What triggers these cells to traffic is undefined , but it occurs in normal non-infected conditions at a rate that is accelerated with viral infection . Here , we used 5-bromo-2′-deoxyuridine ( BrdU ) injection and incorporation into the DNA of monocytes prior to their departure from the bone marrow . We found that the percentage of BrdU+ monocytes leaving the bone marrow 24 hours after injection increased in animals that rapidly succumbed to AIDS and correlated with the severity of SIV encephalitis ( SIVE ) . Differences in BrdU labeled monocytes in slow and rapid progressors were revealed as early as 8 days and were consistent by 27 days post infection . Soluble CD163 , shed by activated monocyte/macrophages , directly correlated with BrdU+ monocyte expansion . Our study provides new insights into the development of HIV-related CNS disease and underscores the importance of monocyte/macrophage recruitment from the bone marrow as an AIDS defining event . | [
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"immun... | 2010 | Increased Monocyte Turnover from Bone Marrow Correlates with Severity of SIV Encephalitis and CD163 Levels in Plasma |
Understanding the molecular mechanisms responsible for the regulation of the transcriptome present in eukaryotic cells is one of the most challenging tasks in the postgenomic era . In this regard , alternative splicing ( AS ) is a key phenomenon contributing to the production of different mature transcripts from the same primary RNA sequence . As a plethora of different transcript forms is available in databases , a first step to uncover the biology that drives AS is to identify the different types of reflected splicing variation . In this work , we present a general definition of the AS event along with a notation system that involves the relative positions of the splice sites . This nomenclature univocally and dynamically assigns a specific “AS code” to every possible pattern of splicing variation . On the basis of this definition and the corresponding codes , we have developed a computational tool ( AStalavista ) that automatically characterizes the complete landscape of AS events in a given transcript annotation of a genome , thus providing a platform to investigate the transcriptome diversity across genes , chromosomes , and species . Our analysis reveals that a substantial part—in human more than a quarter—of the observed splicing variations are ignored in common classification pipelines . We have used AStalavista to investigate and to compare the AS landscape of different reference annotation sets in human and in other metazoan species and found that proportions of AS events change substantially depending on the annotation protocol , species-specific attributes , and coding constraints acting on the transcripts . The AStalavista system therefore provides a general framework to conduct specific studies investigating the occurrence , impact , and regulation of AS .
Alternative splicing ( AS ) is a fundamental molecular process regulating eukaryotic gene expression and involved in numerous human diseases [1]–[3] . It is usually postulated as the main mechanism to augment protein diversity from a somehow limited set of protein coding genes [4] . Consequently , over the recent years various large scale studies have been undertaken aiming at the exhaustive identification and analysis of AS events ( for recent reviews , see [5]–[7] ) . Current estimations claim around 60–75% of human multi-exonic genes to undergo AS [4] , [8] , [9] . Surprisingly , to some extent , the rigorous formalization of the concept of AS event and its categorization has received relatively little attention . Traditionally , terms for only five kinds of AS events have been coined: exon skipping ( ES ) , mutually exclusive exons ( ME ) , intron retention ( IR ) , alternative donor ( AD ) and acceptor ( AA ) sites [10] . However , currently available transcript evidence shows a plethora of variations in splicing patterns that involve multiple instances of these classical events in various combinations [11] . Figure 1 and Figure S1 give some examples of AS patterns observed in the manually curated RefSeq annotation [12] . Despite the ever growing availability of gene annotations the lack of a universal reference definition of AS and hence of the corresponding categories of AS events prevent AS databases ( e . g . , AEdb [13] , ASD [14] , ATD [15] , Hollywood [16] , PASDB [17] , SpliceNest [18] , PALS db [19] , SpliceDB [20] , AsMamDB [21] , HASDB [22] , ProSplicer [23] , EuSplice [24] , ASAPII [25] etc . … ) , from the automatic identification and update of the AS landscape that characterizes the transcriptome from a particular cell type or condition . Such a specific landscape may be revealing the underlying biological mechanisms responsible for the cell's phenotype . Towards that end the challenges to be addressed are ( i ) to define and identify single instances of AS events in complex exon–intron variations , ( ii ) to find an intuitive vocabulary to adequately characterize different AS events , and ( iii ) to develop methods to efficiently identify and classify AS events from sets of annotated transcripts . Concerning challenge ( i ) Malko and co-workers proposed to combine the classical terms for each exon observed in a given annotation [26] . While variations of each exon across the compared transcripts can be sufficiently described by this procedure , it does not permit an easy extension for splicing variations across the adjacent introns . However , some splicing evidence ( e . g . , the structures depicted in Figure 1A and 1C ) suggests a relation between splice sites across the intron as by means of intron definition mechanisms [27] , [28] . In another study , Nagasaki et al . propose to delineate AS events at exonic regions common to the compared transcripts [29] . Whereas in this approach intron-defined splicing variations are coherently modelled , events that could be connected by exon definition [30] are by definition assumed to be independent and are treated separately ( as for instance in Figure 1B ) . Furthermore , the separation at overlapping exonic positions does not allow for investigation of potential relations between transcription and splicing , i . e . , relative position of the initiation and polyadenylation site ( Figure 1D ) , for which increasing evidence is reported in literature [31] , [32] . The EnsEmbl databases on splicing , transcript , and exon diversity ( ASD , ATD , and AEdb ) have recently extended their definition of AS events ( e . g . , “complex intron retention” ) in order to allow for additional modifications upstream and/or downstream of a central event . However , this notation system still remains limited and fails to capture structures depicted in Figure 1E or larger . Addressing problem ( ii ) , only few attempts have been undertaken to univocally denote AS events . Malko et al . [26] proposed strings composed of 5 letters identifying each classical event to redundantly describe the variability separately for each exon observed in a certain annotation ( e . g . , “—AD” for combined variable acceptor and donor sites , Figure 1B ) . These 5-component strings naturally bear a high degree of redundancy as one is required for each different form of exon . Furthermore , the picture of the exon–intron structure can not be inferred solely from these strings , as can be seen by the structures in Figure 1A and 1C producing identical results . Nagasaki and co-workers proposed the so-called “bit matrices” , binary matrices to describe AS events where each row represents a transcript variant and each column represents a genomic position . Each position of the matrix is filled by “1” and “0” according to whether the respective transcript variant exhibits an exon or not at the corresponding position . Neighboring identical columns then are collapsed , such that variations in the exon–intron structure are represented non-redundantly as flip-flop changes . This representation draws a pictorial “bitmap” of the exon–intron structure from compared transcripts . Disadvantages are that the number of “bits” that have to be shown ( i . e . , the matrix area ) is relatively large even for simple events ( e . g . , 14 for the event in Figure 1B ) . Therefore , a condensed encoding of the bits in 2-dimensional integer vectors has been proposed , which however looses transparency of the exon–intron structure . Alternatively , the nomenclature of ASD/ATD/AEdb focuses up to a certain degree on the location of variations around a centric intron/exon up to a certain degree , but does not describe the relative connection between these variations . For instance , a name as “II-5p3p” ( i . e . , “intron isoform with modification at the 3′- and 5′-end” ) cannot distinguish the cases depicted in Figure 1A and 1C . Correspondingly , the term “EI-5p3p” is ambiguous considering the structures in Figure 1B and 1D . The number of such ambiguities grows with the number of concatenated terms: four different splicing structures for instance match the term “CIR-EB-5p3p” . Also , the identification of a “central event” becomes problematic in large splicing variations ( Figure 1E ) . With respect to issue ( iii ) , splicing graphs as a non-redundant data structure have gained popularity in AS over the recent years , but definitions vary across literature . Capturing the 5′→3′ directionality of transcription , they naturally all form directed acyclic graphs ( DAGs ) . Going back to [33] , matching ( parts of ) ESTs [22] , [34] , [35] have been used as nodes connected by edges representing the EST evidence , in order to cluster them and/or to allow the analysis of AS . Heber and co-workers [35] subsequently collapse ( remove ) vertices with indegree ( i . e . , the number of inedges ) = outdegree ( the number of outedges ) = 1 . Later on , two works from the same year proposed a graph structure where every vertex corresponds to a splice site and the connecting edges represent the intermediate exon/intron [36] , [37] , labelled according to the mRNA or EST evidence . Another kind of graph uses exons as nodes instead of splice sites [38] . Whereas intuitive for visualization , the graph structure may redundantly contain common exon flanks . Other graph-based approaches on exon–intron structures described in literature use similar techniques [25] , [39]–[41] . However , all these analyses focus exclusively on the four types of traditional AS events , and thus capture only a limited fraction of the splicing variation encompassed in the transcriptome—probably a main consequence of problem ( i ) . Indeed , without a universal definition of AS event , the retrieval of a single type of splicing variation requires to define its corresponding sub-graph pattern and to localize all occurrences of this pattern in the whole splicing graph . Consequently , a comprehensive characterization of AS needs an exhaustive set of such ad hoc patterns , which explains why usually only 4–6 types of events are considered . In this work , we propose a general definition of “AS event” and we present a novel notation based on the relative position of alternative exon boundaries to flexibly describe such events . Unlike traditional nomenclatures , this generic notation system allows the assignment of a univocal “AS code” to identify any possible variation of the exon–intron structure between two or more transcripts , and thus provides a platform for the automatic and exhaustive extraction of such variations from a dataset of annotated genes . Here , we also describe in detail the method implemented in AStalavista ( Alternative Splicing transcriptional landscape visualization tool ) for the dynamic characterization of AS events in splicing graphs . AStalavista is accessible as a web server at ( http://genome . imim . es/astalavista ) [42] . We have used AStalavista to characterize and compare the “landscape” of AS in different human reference annotations as well as in annotations of other metazoan species , i . e . , chimp ( Pan troglodytes ) , mouse ( Mus musculus ) , rat ( Rattus norvegicus ) , dog ( Canis familiaris ) , cow ( Bos taurus ) , chicken ( Gallus gallus ) , frog ( Xenopus tropicalis ) , zebrafish ( Danio rerio ) , honeybee ( Apis mellifera ) , fruitfly ( Drosophila melanogaster ) , and worm ( Caenorhabditis elegans ) . In contrast to previous large-scale studies , our approach focuses on splicing structure variations rather than on ( sequence ) attributes of alternative exons/introns [43] , [44] . Results indicate that while most AS events can be assigned to a few categories , the categorization of AS events in different structures is quite complex , with a plethora of minor AS configurations . Relative frequencies of particular patterns change with respect to the corresponding annotation protocol , species-specific attributes and coding constraints of the respective locus , and we present computational studies that investigate the reasons behind these fluctuations .
The concurrent and regulated molecular mechanisms of exon and intron definition are generally responsible for the splicing structure in a certain transcript variant . Although case studies for the mechanics of intron and exon recognition are given in literature [27] , [28] , [30] , no general rule could ( yet ) be deduced . Therefore , neither of the mechanisms can be excluded from occurring during the splicing process and both are to be considered in a generally robust definition of AS event that is applicable to any organism without being a priori restricted to exon or intron definition . In order to allow for possible interactions of parts of the splicing machinery across all exons and introns when delimiting AS events in exon–intron variations , our definition of AS events is based on sites: given an annotation , i . e . , transcript sequences aligned to the genome , we use the terminus “site” to describe genomic locations of aligned exon boundaries ( Definition 1 ) . We propose a novel notation system to allow a complete classification of AS events . The general idea is to assign to any AS event a string-based “AS code” that describes the structure of the splicing variation in a concise and univocal manner . AS events of the same type ( e . g . , exon skipping ) are given an identical code and thus can be classified in the same structural group . The codes are built dynamically with respect to each observed splicing variation without the requirement of an a priori defined catalogue of putative AS events . Our notation system is based on the relative position of the variable sites that are involved in the AS event and proceeds as follows: first , all the variable sites of an AS event ( see Definition 4 ) are considered in the order of their genomic position from 5′ to 3′ . The indices i ∈ N+ defined by this relative order are assigned to the corresponding variable sites . In addition , a symbol is attributed to each site depending on its type . We use the alphabet Σ = {[ , ˆ , - , ]} , where “[” denotes a TSS , “ ˆ” a splice donor , “-” an acceptor , and “]” a PAS . Therefore , each site is represented by a number ( the relative position i ) and a symbol ( identifying the type ) . To describe one of the splicing structures resulting from an AS event , the number and the symbol of all of the sites that are used by the corresponding mRNA within the event are concatenated into a string . The digit “0” is used if the transcript does not use any variable site ( for instance by skipping an exon ) . The AS code of the event corresponds to the concatenation of these strings , separating the descriptions of the variants by a comma . We order the strings according to the relative position of their first site . Examples are presented in Figures 1 and 2 . Using this notation , AS events with identical codes are structurally equivalent , e . g . , all exon skipping or all alternative donor events . Moreover , a specific AS code can always be defined for any splicing variation , which guarantees the exhaustiveness of the notation system . For instance , the nonconventional events observed in Figure 1 are assigned the codes ( A ) 1ˆ3- , 2ˆ4- , ( B ) 1–3ˆ , 2–4ˆ , and ( C ) 1ˆ4–5ˆ6–7ˆ8- , 2ˆ3- . Globally , the distribution of AS events into distinct structural classes forms the landscape of alternative splicing encompassed in a given annotation . AStalavista is a JAVA-based tool designed to extract and visualize the structural landscape of AS events as reflected by a given annotation . The input is provided in GTF format , containing the genomic coordinates of exons in the transcripts ( and , optionally , the coordinates of the coding regions ) . AStalavista can be applied to any species for delineating the AS landscape from a whole genome annotation , or to a subset of genes composed according to custom criteria . The output depicts the AS landscape by giving a summary of all pairwise AS events grouped into structurally equal classes which are ranked according to their observed abundances . The web server [42] ( http://genome . imim . es/astalavista ) has been upgraded and depicts the spectrum of AS structures as described in this manuscript , including variable TSSs/PASs as pointed out by Definition 3 and Definition 4 . This means that it is now possible to investigate for instance potential correlations between AS and alternative transcription initiation . Also , the number of species and reference annotations that are supported has been increased . To assess the agreement of AS events predicted according to our definition with data available from public sources , we compared the output of AStalavista for 5 well studied genes with the events classified for these in recently published or updated databases ( Table 1 ) . Since AStalavista is a method rather than a fixed database , the number of AS events that are predicted crucially depends on the transcript annotation ( s ) under consideration . Therefore , we conducted a first comparison of events extracted by AStalavista from mRNA annotations in Genbank [46] with the EuSplice database that is based on gene annotations . In another run , we enriched the input data by ESTs from dbEST [47] and compared the corresponding results to the EST-based databases ASD , ATD and Hollywood . In order to make the number of events in AStalavista quantitatively comparable with the number of events from public databases , we disregarded in either case AS events predicted in correlation with alternative transcription initiation or polyadenylation . Table 1 shows that AStalavista clearly finds more bona fide events in either dataset than is available from public databases . We additionally set off to investigate the overlap of the events in a case study ( Figure S2 ) and found that in the FOXP2 gene AStalavista ( Figure S2A ) finds 5 out of 6 events reported by Hollywood ( Figure S2B ) and 2 out of 3 events in EuSplice ( Figure S2C ) : in one instance Hollywood marked an alternative splice donor with a very untypical sequence that is supported exclusively by 2 ESTs ( Figure_S2B ) , and in the other case EuSplice predicted a cryptic exon based on the alignment of 2 nt in an intronic stretch which subsequently is tagged with the warning “short exon” and excluded from the analysis on splice site sequences ( Figure S2C ) . For those AStalavista events that are not retrieved from both reference databases ( 8 out of 10 for EuSplice and 19 out of 24 for Hollywood ) , we found in total 4 cases that—although the evidence is present in the reference database—have not been reported , probably due to a limitation of the applied classification scheme . These cases are: 0 , 1–2ˆ3–4ˆ ( i . e . , the skipping of two consecutive exons in events 14 and 15 ) , 1–2ˆ , 3–4ˆ ( the mutually exclusive exons in event 23 ) and 1–2ˆ3- , 4- ( the skipping of an exon when an alternative downstream acceptor is used , event 24 ) . We ran AStalavista on three human popular annotation datasets , namely RefSeq [12] , EnsEmbl [48] and Gencode [49] . With our clustering method ( see Materials and Methods ) , the 25 , 170 RefSeq transcripts clustered into 18 , 334 loci , the 43 , 102 EnsEmbl transcripts into 22 , 303 loci , and the 1 , 352 coding transcripts of Gencode into 381 loci ( Table 2 ) . The differences in the average number of coding transcripts per locus between these annotations ( 1 . 4 for RefSeq , 1 . 9 for EnsEmbl , and 3 . 6 for Gencode ) reflect the differences in exhaustiveness among them . We extracted all variations of the exon–intron structures according to Definition 4 . To compensate for artefacts that may occur in automatic annotation pipelines , we omitted AS events that involved introns with no canonical splice site dinucleotides ( i . e . , not GT/AG ) . Note that this filtering step consumes a considerable part of the observed running time ( Table 2 ) , since for each intron the splice site nucleotides are extracted from the genomic sequence . As expected , the observed running times reflect the number and distribution of transcripts in each input annotation and the longest run ( for EnsEmbl ) took a bit more than a minute ( Table 2 ) . Next , we analyzed the transcript diversity by characterizing the AS landscapes produced by AStalavista from the different annotations ( Figure 3 ) . To compare the results with other studies , we focused on the traditional AS events that present a “simple” splicing pattern—involving at most two alternative splice sites and not correlated with variable TSS/PAS . Agreeing with previously reported observations [29] , these simple events are equally ranked from the most abundant to the less in all annotations data sets in the order: exon skipping ( ES ) , alternate donor ( AD ) , alternate acceptors ( AA ) and intron retention ( IR ) . All other AS events are pooled together ( Figure 3 , grey sectors in the pie diagrams ) . These “complex” events form as a whole a substantial part of the AS landscape ( from 23 . 18% in RefSeq up to 35 . 4% in EnsEmbl ) , and each of them can be unambiguously described by the notation proposed herein . The composition of these events varies ( Table S1 ) : the 1 , 070 AS events detected in RefSeq correspond to 85 structural distinct classes ( A ) , whereas the 4 , 321 events in EnsEmbl show 388 classes ( C ) . The fairly most abundant of these complex event ( from 25 . 6% of them in EnsEmbl to 32 . 6% in Gencode ) is the skipping of two exons in a row ( 0 , 1–2ˆ3–4ˆ ) . Mutually exclusive exons ( 1–2ˆ , 3–4ˆ ) are less frequent ( from 12% to 14 . 5% ) , probably due to a more complex molecular mechanism that regulates them . As expected , the higher the complexity of an event—as measured by the number of splice sites involved—the lower its relative abundance . For instance , the “triple exon skipping” ( 0 , 1–2ˆ3–4ˆ5–6ˆ ) forms ∼7–9% of the complex events . The fact that this event still represents 93 reported cases in the RefSeq annotation ( Table S1 ) illustrates the need for an exhaustive AS notation system and for the corresponding retrieval method . Obviously , there are differences in the AS landscape between the different reference annotations . This probably reflects the differences in biological data and in the annotation process: manually reviewed full-length cDNA sequences in RefSeq , automatically annotated proteins/cDNAs in EnsEmbl and manually annotated transcripts including ESTs evidence augmented by experimentally verified computational predictions in Gencode . Nevertheless , the different proportions of events agrees with previous results ( e . g . , [29] , [37] ) and their ranking is consistent across the sets , which illustrates the general consistence in the AS taxonomies reflected by these annotation systems . Particularly relevant is , in our opinion , the consistency in the AS landscape between the RefSeq and the much richer Gencode annotation . Even though Gencode contains 2 . 5-fold the number of alternative transcripts per locus , it includes only a marginally larger proportion of the “other” complex AS events than the conservative RefSeq , indicating that while only a fraction of the protein coding transcripts in the human genome may be currently known , the broad AS landscape characterizing the RefSeq annotation is also likely to characterize the entire human transcript complement . We have investigated the differences in the type of AS events occurring in the CDS ( coding sequence ) from those occurring only in the 5′ UTR ( 5′ untranslated region ) . Figure 4 shows the distribution of the simple AS events in 5′ UTRs and in CDSs from the RefSeq annotation . The distribution in 3′ UTRs ( 3′ untranslated regions ) is not shown because of the low frequency of ( alternative ) splicing in these regions . The analysis here focuses on events completely included in a certain region ( see Methods ) —i . e . , in the 5′ UTRs or in the CDSs—but the same trends can be observed for events overlapping the 5′ UTR and the CDS ( Figure S3 ) . The distributions differ even in the ranking of the four most abundant events . In agreement with [29] , the proportion of ES is significantly higher in CDS ( 50 . 9% of the landscape ) than in the 5′ UTR ( 37 . 9% , p-value<10−4 , χ2 test ) . A straightforward explanation is the fact that ES requires at least two introns , which are present in a minority of 5′ UTRs . Coherently with this explanation , we observe the following low proportions of complex AS events in 5′ UTRs vs . CDS: 26 . 6% vs . 33 . 1% for 0 , 1–2ˆ3–4ˆ events ( skipping of two exons ) , 10 . 6% vs . 17 . 3% for 1–2ˆ , 3–4ˆ events ( mutually exclusive exons ) and—more drastically—1 . 3% vs . 10 . 7% for 0 , 1–2ˆ3–4ˆ5–6ˆ ( the joint skipping of 3 neighboring exons ) events . Expectedly , since retained introns in CDSs are likely to introduce in-frame stop codons , the relative proportion of IR is much higher in 5′ UTR ( 8 . 4% vs . 2 . 1% , p-value<10−4 , χ2 test ) . Strikingly , the relative frequency of AA and AD events shows a “reciprocal asymmetry” between the CDS and the 5′ UTRs . In the CDS , the proportion of AAs is nearly twice as high as the proportion of ADs ( 14 . 8% vs . 8% ) , while in the 5′ UTR regions the ratio is the other way around ( 13 . 7% vs . 22 . 5% ) . Considering findings on the possibly differing molecular mechanism for short range variations at the donor and acceptor site [50]–[52] , we repeated the analysis disregarding variations between AD or AA shorter than 5 bp and found a comparable asymmetry ( data not shown ) . The bias against AAs in 5′ UTRs can be explained by the shorter sequence span where alternate acceptor sites can appear without disrupting the downstream protein sequence . Indeed , if we consider the 5′ UTRs that contain exactly one intron ( 75% of the spliced 5′ UTRs ) , the length of the potential target for alternative upstream donor site creation , that is the first exon , is significantly larger than the length of the potential target for alternative downstream acceptor sites creation in 5′ UTR , that is from the acceptor site to the ATG codon ( 260 vs . 47 nucleotides on average ) . In order to confirm that the bias against AAs in the 5′ UTR is mainly due to constraints of the start codon , we considered in multi-intronic 5′ UTRs the AS events that do not affect the last intron . Then , the AD/AA ratio drops from factor >1 . 64 to factor 1 . 2 ( 30 AD events compared to 25 AA events in RefSeq ) . In our opinion , the remaining polarity stems from the fact that the first exon is significantly longer than the second ( median 149 vs . 137 , p-value ∼3e-6 , Kolmogorov-Smirnov-Test ) , probably resulting from differences in the mechanism for exon definition [27] . On the other hand , the observed asymmetry against ADs in the CDS can be explained by the propensity towards the creation of stop codons when considering alternative downstream donor sites , due to the peculiar composition of the donor site consensus sequence . As already reported in the past [53] , splicing consensus sequences harbor a high content of intrinsic stop codons ( shaded grey in Figure 5A and 5B ) . To test this hypothesis , we have artificially extended constitutively chosen exon boundaries into the intronic flanks and measured the frequency of in-frame stop codon occurrence separately for the 5′ and the 3′ end . As summarized in Figure 5 , the inclusion of one additional codon from the intronic sequence already interrupts the CDS at the donor site ∼50% more often than at the acceptor site . Interestingly , another—though lower—peak of potential stops at the acceptor site is observed after ∼9 codons of extension and coincides with the common location of the branch point consensus ( Figure 5C ) . This difference of potentially included stop codons biases against ADs up to 22 codons of extension ( Figure S4 ) and therefore gives strong evidence for the more frequent use of AAs at flanks of coding exons—albeit more complex mechanisms are also expected to play an additional role . Additional evidence of the strong effects of the protein coding constraints in shaping the AS landscape comes from the comparison of AS in protein coding and noncoding transcripts . For this comparison , the Gencode annotation is particularly appropriate: it contains many non protein-coding transcripts ( 2 , 247 vs . 1 , 332 coding transcripts ) , most of them actually occurring also in protein coding loci . In other words , protein coding loci seem to be able to encode both , protein coding and noncoding transcripts . Figure 6 shows the distribution of the AS events in protein coding regions ( i . e . , in the CDSs ) and in noncoding transcripts . The differences are substantial , interestingly also in comparison to the AS events in 5′ UTRs ( Figure 4 ) , not biased by the difference in size between the datasets ( Figure S5 ) . Almost one third ( 31 . 5% ) of the AS events observed in noncoding transcripts correspond to complex splice events , compared to only about one fourth ( 24 . 3% ) in CDSs . Also , the composition of the complex fraction in noncoding transcripts is richer ( 57 structural different classes vs . 22 in CDSs ) . Consequently , simple events that are frequently reported in the CDSs of Gencode transcripts are relatively less abundant in noncoding transcripts ( e . g . , from 48 . 5% to 34 . 4% for exon skipping ) . Naturally , we observe a relaxation of selective constraints against retained introns that make up ∼12% of the landscape in transcripts without an annotated reading frame . The AA/AD ratio is more balanced in noncoding transcripts ( 1 . 6 vs . 2 . 6 in CDSs ) . The remaining polarity stems from asymmetries in the first compared to the last intron: whereas an alternative TSS in the first exon is often associated with an alternative first donor site ( 87 instances ) , an alternative acceptor site in the last exon is less frequently observed with a different PAS ( 56 cases ) . When taking into account such events , the numbers for variable 5′ and 3′ flanks of exons are about equal ( 150 ADs and 159 AAs ) . This indeed underlines the very different selective constrains acting on coding and noncoding transcripts—even though they may be extensively sharing the same genomic space . To investigate the evolution of the AS landscape , we have applied AStalavista to the annotation of 12 different metazoan genomes: human ( Homo sapiens ) , chimp ( Pan troglodytes ) , mouse ( Mus musculus ) , rat ( Rattus norvegicus ) , dog ( Canis familiaris ) , cow ( Bos taurus ) , chicken ( Gallus gallus ) , frog ( Xenopus tropicalis ) , zebrafish ( Danio rerio ) , honeybee ( Apis mellifera ) , fruitfly ( Drosophila melanogaster ) , and worm ( Caenorhabditis elegans ) . While many of the fluctuations observed are likely due to the species-specific differences in amount and quality of the transcriptional data from which the annotations have been derived , our study reveals some interesting trends , suggesting overall that AS patterns did not change gradually but rather abruptly during metazoan evolution ( Figure 7 ) . More specifically , IR events are clearly more abundant in invertebrates than in vertebrates . This is consistent with the fact that invertebrates have much shorter introns . Indeed , one could think that IR events involving short introns are less likely to be negatively selected , since the probability for the protein sequence to get disrupted by the introduction of a stop codon is lower than with long introns ( Table S2 ) . On the other hand , vertebrates—and especially mammals—exhibit a higher proportion of ES events , while , in contrast , relying relatively less on the usage of alternative donors and acceptors . This may reflect a higher level of regulation of AS in vertebrates , possibly correlated with a higher frequency of exon shuffling and protein domains rearrangements [54] . Finally , we observe an accumulation of complex events in vertebrate genomes compared to the invertebrates ( Figure 7 ) . This could be due to the larger number of exons per gene on average in vertebrate genomes ( Table S3 ) , which allows to increase the combinatory level , but it also suggest a higher level of sophistication in the control of AS in vertebrate genomes when compared to invertebrates .
Alternative Splicing increases enormously the encoding capacity of the genome of the higher eukaryotic organisms . Its differential regulation is likely to play a substantial role in defining the phenotype of a given cell type , or cell state . We have developed a method to automatically catalogue the patterns of AS events occurring in a given gene/transcript annotation . The method ( and the resulting ) taxonomy relies on a precise definition of AS event . We have implemented the method in a publicly available software system , named AStalavista . As a proof of concept , the application of AStalavista to a number of popular annotations of the human genomes has revealed the existence of a plethora of AS types that are usually ignored in published analyses . Indeed , about one quarter of all AS events in these collections belong to this category . Some of these complex AS events , like double exon skipping or mutually exclusive exons , are likely to be under specific regulation . In addition , we report notable differences in the AS landscape between coding and noncoding regions and transcripts , with the landscape in coding regions being largely modelled by protein coding constraints and the landscape in noncoding transcripts suggesting a relaxation of selective constraints . Our comparison of the AS landscape across 12 metazoan genomes reveals strong differences between vertebrate and non-vertebrate genomes . We observe a higher fraction of intron retention events in invertebrates , while in contrast exon skipping and complex splicing events are more prevalent in vertebrates . While the latter could simply reflect the richer transcript data available for vertebrate , and specifically mammalian genomes , we think that the data is overall suggestive that AS is both more complex and more regulated there , an hypothesis which is compatible with recent studies , according to which there was a substantial increase in AS in the lineage leading to vertebrates , after the separation from invertebrates [55] . Our studies , which we have performed here as a proof of concept of our method , illustrate the potentiality of the AStalavista system to globally characterize the AS landscape of transcriptomes . One could think of many other scenarios—in addition to the basal characterization of the AS landscape in the genome of newly sequenced species—where the characterization of the AS landscape by our system could be of interest . For instance , the AS landscape could be compared across genes clustered in different functional classes , as defined for example by the Gene Ontology project [56] , or according to their level or their pattern of expression , or to their conservation across evolution , or to the analyzed tissue or cell type , etc . —in general modulus any biologically relevant partition of the genes from a given species that one can possibly delineate . With the generalization of the new generation of high throughput sequencing instruments , our capacity of effectively surveying various transcriptomes will be greatly enhanced . Differences in such AS landscapes may help to reveal the underlying biological mechanisms responsible for specific phenotypes of the cell ( for instance in cancer cells ) , by pinpointing general splicing de-regulation accidents leading to an alternation of the splicing patterns . One issue that may remain controversial is the grouping of transcripts into loci , within which the transcripts will be compared in order to identify the occurring AS events . Different groupings may indeed lead to different sets of AS events . Intuitively , one would expect AS to be investigated by comparing transcripts from the same gene . However , recent in-depth annotations projects have had the effect of blurring gene boundaries , up to challenging the definition of a gene [57] , [58] . Also , since cases of overlapping transcripts from hitherto distinctly annotated genes are increasingly reported [59] , [60] , genes can no longer be regarded as isolated units of transcription . Transcription Induced Chimeras [60]–[62] , i . e . , genes that are fused by a transcript sharing at least one splice site with either one of them , are to be respected when investigating the phenomenon of AS . Therefore , AStalavista includes its own clustering schema in order to ensure an exhaustive detection of AS events , by pooling in a single transcriptional locus all transcripts that overlap on the same strand of the genome sequence . Using these loci instead of the native gene names , we can objectively compare AS classifications across gene sets that involve different criteria for assigning transcripts to genes . In any case , we believe that the introduction of a consistent and rigorous definition of alternative splicing event , which allows in particular a standard characterization of the AS landscape of a given transcriptome , will certainly contribute to a better understanding of the phenomenon of Alternative Splicing .
Annotated transcripts for RefSeq and Gencode ( March 2007 freeze ) have been downloaded from the UCSC genome browser ( http://genome . ucsc . edu ) and the annotations for 12 metazoan genomes from EnsEmbl ( build 43 , http://www . ensembl . org ) . RefSeq is a nonredundant dataset of gene annotations generated by human supervised alignments of cDNA sequences to the genome [12] . EnsEmbl is a semi-automatic annotation system relying mainly on protein-to-genome sequence alignments [48] . Gencode ( http://genome . imim . es/gencode/ ) is based on the human supervised mapping of all available ESTs , cDNAs and protein sequences onto the Encode regions of the genome [63] , which is augmented with computational predictions , and subsequently verified experimentally by RT-PCR and RACE [49] . Additional data in the comparison of metazoan genomes has been obtained from the EnsEmbl web server , containing the version 43 ( February 2007 ) of the EnsEmbl annotation [48] for most of the species , the currently discontinued version 38 ( April 2006 ) of the EnsEmbl annotation for A . mellifera , the FlyBase ( March 2006 ) annotation for D . melanogaster [64] , and the WormBase ( May 2006 ) annotation for C . elegans [65] . In each annotation dataset , transcripts that align to genomic regions overlapping on the same strand are clustered into common loci . To avoid some alignment/annotation errors in the datasets , we applied a filtering step discarding all subsequently extracted AS events which contain intron ( s ) that do not exhibit the consensus dinucleotides GT/AG at their extremities . To assign AS events to a certain region of a gene ( e . g . , 5′ UTR or CDS ) , we required that all of the variable sites of the event are located in the respective region . Events spanning more than one region , by this , are excluded in the respective analysis . For the analysis of AS in noncoding transcripts , transcripts with an annotated reading frame have been filtered off the dataset before extracting AS events . In this section we present the method used in AStalavista to ( 1 ) build a splicing graph from a set of transcripts mapped to the genome and ( 2 ) efficiently process this graph to extract all pairwise AS events . To infer a splicing graph ( see Introduction ) , the first step is to retrieve the exon boundaries si from all transcripts in a locus C . To ensure that the sites of a transcript si ∈ St preserve the usual 5′→3′ directionality in the order given by pos ( si ) , we artificially invert the genomic coordinates of sites that align to the negative strand . Therefore , splicing graphs G = ( V , E ) herein are directed acyclic graphs with each node s ∈ V representing nonredundantly a site of the transcripts in C . Each edge ( si→sj ) ∈ E corresponds to an exon ( type ( si ) ∈ {α , σ} ) or intron ( otherwise ) delimited by pos ( si ) and pos ( sj ) and supported by the transcripts transcripts ( si ) ∩ transcripts ( sj ) ≠{} . Note that G is non-redundant , i . e . , each splice site si and each exon/intron ( si→sj ) is stored once , regardless of the number of transcripts that support it . In order to include AS events associated with variable TSSs and PASs ( Definition 4 ) , the graph is completed by the addition of two terminal nodes: a root node root ( pos ( root ) = −∞ , type ( root ) = Α , transcripts ( root ) = C ) that connects to all TSSs and a leaf node leaf ( pos ( leaf ) = ∞ , type ( leaf ) = Ω , transcripts ( leaf ) = C ) that connects from all PASs , where Α and Ω are unique types to identify the root/leaf . AStalavista implements the graph-theoretical approach as sketched in the previous section for extraction of pairwise AS events from a given annotation . In this approach initially time is required to build up G for each locus C by adding each site annotated in the input to V and checking a preceding exonic/intronic edge for eventual creation . Once completely constructed , G consumes memory . Making with appropriate data structures the operation {St , Su} ∩ transcripts ( si ) feasible in constant time and disregarding the overhead of the operations extract ( ) , respectively , insert ( ) in Figure 8 , the time complexity for the extraction of all pairwise events is , where k is the number of transcript variants in C , |W| the number of nodes that are supported by one of the transcripts in St and/or Su , outdegree ( si ) counting the number of outgoing edges for a node si ∈ V , and L denoting the set of redundant AS events found in C . Obviously , ∼k2 pairwise transcript comparisons are to be performed in a locus , for each one the nodes that describe a site of the transcripts are to be iterated and their outedges have to be checked whether they overlap with {St , Su} . Finally , all pairwise events found are to be checked for redundancy in an all-against-all comparison that costs additionally |L|2 . Both quadratic factors , k2 and |L|2 , grow naturally with the transcript diversity that is investigated . Reference annotations—even on the complete human genome—are computed in not much more than a minute ( Table 2 ) , but the time effort increases when including loci that are annotated extensively with mRNA/EST sequences . | The genome sequence is said to be an organism's blueprint , a set of instructions driving the organism's biology . The unfolding of these instructions—the so-called genes—is initiated by the transcription of DNA into RNA molecules , which subsequently are processed before they can take their functional role . During this processing step , initially identical RNA molecules may result in different products through a process known as alternative splicing ( AS ) . AS therefore allows for widening the diversity from the limited repertoire of genes , and it is often postulated as an explanation for the apparent paradox that complex and simple organisms resemble in their number of genes; it characterizes species , individuals , and developmental and cellular conditions . Comparing the differences of AS products between cells may help to reveal the broad molecular basis underlying phenotypic differences—for instance , between a cancer and a normal cell . An obstacle for such comparisons has been that , so far , no paradigm existed to delineate each single quantum of AS , so-called AS events . Here , we describe a possibility of exhaustively decomposing AS complements into qualitatively different groups of events and a nomenclature to unequivocally denote them . This typological catalogue of AS events along with their observed frequencies represent the AS landscape , and we propose a procedure to automatically identify such landscapes . We use it to describe the human AS landscape and to investigate how it has changed throughout evolution . | [
"Abstract",
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] | [
"computational",
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] | 2008 | A General Definition and Nomenclature for Alternative Splicing Events |
Addressing the transmission enigma of the neglected disease Buruli ulcer ( BU ) is a World Health Organization priority . In Australia , we have observed an association between mosquitoes harboring the causative agent , Mycobacterium ulcerans , and BU . Here we tested a contaminated skin model of BU transmission by dipping the tails from healthy mice in cultures of the causative agent , Mycobacterium ulcerans . Tails were exposed to mosquito ( Aedes notoscriptus and Aedes aegypti ) blood feeding or punctured with sterile needles . Two of 12 of mice with M . ulcerans contaminated tails exposed to feeding A . notoscriptus mosquitoes developed BU . There were no mice exposed to A . aegypti that developed BU . Eighty-eight percent of mice ( 21/24 ) subjected to contaminated tail needle puncture developed BU . Mouse tails coated only in bacteria did not develop disease . A median incubation time of 12 weeks , consistent with data from human infections , was noted . We then specifically tested the M . ulcerans infectious dose-50 ( ID50 ) in this contaminated skin surface infection model with needle puncture and observed an ID50 of 2 . 6 colony-forming units . We have uncovered a biologically plausible mechanical transmission mode of BU via natural or anthropogenic skin punctures .
Among the 17 neglected tropical diseases the World Health Organization ( WHO ) has targeted for control and elimination , only Leprosy and Buruli ulcer ( BU ) have unknown modes of transmission [1] . The search to understand how humans contract BU spans more than 70 years since the causative agent , Mycobacterium ulcerans , was first identified [2] . There are persistent and emerging foci of BU cases across the world , in particular Africa and Australia [3] . BU is characterized by necrotizing skin lesions , caused by localized proliferation of M . ulcerans in subcutaneous tissue . BU is rarely fatal , but untreated infections leave patients with significant disfigurement and disability , with damaging personal and economic consequences [4 , 5] . Researchers have long been struck by the characteristic epidemiology of BU , with cases occurring in highly geographically circumscribed regions ( sometimes less than a few square kilometres ) and risk factors for infection that include gardening , insect bites and proximity to ( but not necessarily contact with ) lacustrine/riverine regions [6–14] . Human-to-human spread is considered unlikely [14] . Disease transmission is thought to occur by contact with an environment contaminated with Mycobacterium ulcerans but exactly where the pathogen resides and why it appears so geographically restricted have yet to be determined . [15] . M . ulcerans is very slow growing ( doubling time >48 hrs ) and this poses a problem for source tracking efforts as it is difficult to isolate the bacteria in pure culture from complex environmental specimens [16] . M . ulcerans has only once been isolated from a non-clinical source , an aquatic water bug ( Gerridae ) from Benin [16] . Quantitative PCR targeting M . ulcerans-specific DNA is the most frequently used technique in surveys of environmental specimens . A comprehensive review of the many field and lab studies that have examined transmission of BU has highlighted the range of organisms from aquatic plants , snails , insects , fish , amphibia , and in Australia certain native marsupials that can serve as potential reservoirs for M . ulcerans [15 , 17–20] . Since the first observation that biting aquatic insects can harbour M . ulcerans [21] , studies of BU transmission have largely focused on the potential for insects to biologically vector M . ulcerans implying that M . ulcerans undergoes a propagative or reproductive mode of development in an insect [22–26] . Several case-control studies , including from both Australia and Africa have suggested insects may play a role in transmission [10 , 11] . For example , in southeastern Australia , we noted Buruli lesions on exposed areas likely to attract biting insects , some patients with every brief exposure times to endemic areas [27 , 28] and in 2004 we began a study that identified M . ulcerans DNA associated with mosquitoes captured in endemic areas [22] . However , there is no compelling experimental evidence for single-mode biological transmission of M . ulcerans via insect vectors .
The animal ethics committee ( AEC ) of the University of Melbourne approved all animal experiments under approval number AEC: 1312775 . 2 , in accordance with the National Health and Medical Research Council Australian code for the care and use of animals for scientific purposes 8th edition ( 2013 ) . M . ulcerans strain JKD8049 and bioluminescent M . ulcerans JKD8049 ( harbouring plasmid pMV306 hsp:luxG13 ) [29 , 30] were cultured in 7H9 broth or Middlebrook 7H10 agar , containing 10% oleic-albumin-dextrose-catalase growth supplement ( Middlebrook , Becton Dickinson , Sparks , MD , USA ) and 0 . 5% glycerol ( v/v ) at 30°C . Colony counts from bacterial cultures or tissue specimens were performed using spot plating . Five x 3μl volumes of serial 10-fold dilutions ( 10−1 to 10−5 ) of a culture or tissue preparation were spotted onto 7H10 agar plates with a 5x5 grid marked . The spots were allowed to dry , the plates loosely wrapped in plastic bags and then incubated as above for 10 weeks before counting colonies . Data analysis was performed using GraphPad Prism v 7 . 0a . All culture extracts were screened by LC-MS for the presence of mycolactones as previously described to ensure bacteria used in transmission experiments remained fully virulent [31] . BALB/c mice were purchased from ARC ( Canning Vale , Australia ) and housed in individual ventilated cages . Upon arrival , animals were acclimatizing for 5 days . Food and water were given ad libitum . Wild caught mosquitoes were sourced from around Cairns , Queensland , Australia . A . notoscriptus and A . aegypti colonies were reared in a Physical Containment Level 2 ( PC2 ) laboratory environment at 26°C using previously described methods , with the addition of brown paper used as the oviposition substrate for A . notoscriptus [32] . Females were aged for at least one week prior to blood feeding ensure maturity , during which they were mated ( seminal accessory fluid is required to stimulate searching and feeding behavior in females ) . The adults were provided with access to a 10% sucrose solution , which was withdrawn 24h prior to a blood feeding experiment . Six-week old female BALB/c mice were anaesthetized and their tails coated in a thin film of M . ulcerans wild type strain JKD8049 by dipping the tails in a Petri dish containing 20mL of bacterial culture ( concentration ~106 CFU/mL ) ( Table 1 ) . Tails were allowed to air-dry for 5 minutes after dipping . The tail only was then exposed to a 200mm x 200mm x 200mm cage of 20 adult female mosquitoes for a period of 15 minutes . Twenty mosquitoes were used per feeding bout to minimize stress on the mice . The number of insects biting each mouse was recorded over the exposure period by continuous observation . Tails were not wiped or disinfected post-biting . Mice were then observed weekly for up to six months for signs of tail lesions . Sterile needle stick ( 25G or 30G needle ) and no-trauma were used as controls . An additional control consisted of tails dipped in sterile culture broth only and subjected to mosquito biting or sterile needle stick ( See Table 1 for experiment design ) . The concentration of bacteria used was calculated by dilution plating as described above . Contingency tables and Fisher’s exact test were used to test if instances of mosquito-associated or needle stick-associated disease transmission were significantly different to no trauma ( GraphPad Prism v 7 . 0a ) . To estimate the infectious dose , we first measured the surface area of five dissected naïve mouse-tails to obtain an average surface area ( 493 . 3 ± 41 . 1 mm2 ) . Using ten naïve mouse-tails and a precision balance , we then calculated the average volume of M . ulcerans 7H9 Middlebrook culture adhering to the tail surface ( 32 . 4 ± 4 . 2 μL ) , the concentration of bacteria in the cultures used , and the surface area of the tips of 25G and 30G needles used to deliver the puncture wounds ( 0 . 207 mm2 and 0 . 056 mm2 respectively ) . These parameters were then used to calculate the infectious dose , assuming the bacteria were evenly distributed over the tail surface ( Fig 1B ) . A standard protocol to calculate an ID50 was followed . Four-week old female BALB/c mice were anaesthetized and their tails coated as described above for the transmission experiments with 10-fold dilutions of bioluminescent M . ulcerans JKD8049 from 106 to 10 CFU/mL in each Petri dish , using five mice per dilution , followed by a single needle stick puncture with a 25G needle . The mice were monitored using a Lumina XRMS Series III In Vitro Imaging System ( IVIS ) ( Perkin Elmer ) . Images were captured with the following settings: binning of 4 ( medium ) , Field of View ( FOV ) of 24 , Relative aperture at f1 . 2 and exposure time of 180s . Bioluminescence was calculated using Living Image software V4 . 1 . The number of mice per dilution developing BU up to six-months was recorded . Mice were observed up to six-months . The data were plotted and a standard curve was fitted using least squares non-linear regression . The ID50 and 95% confidence intervals were interpolated with reference to the standard curve using GraphPad Prism v 7 . 0a . For each mosquito that blood-fed DNA was individually extracted from the dissected head , abdomen and legs of each insect using the MoBio Powersoil DNA extraction kit following manufacturer’s instructions ( MoBio Laboratories Inc . , Carlsbad CA USA ) . The insects were held by the wings and each body portion ( legs , abdomen , head ) individually and separately removed with sterile , fine forceps to avoid cross contamination during dissections . Body parts were stored individually ( legs were pooled per insect ) in sterile 1 . 5mL tubes at -20°C until DNA extraction . DNA was similarly extracted from mouse tissue . Procedural extraction control blanks ( sterile water ) were included at a frequency of 10% to monitor potential PCR contamination , in addition to no-template negative controls . IS2404 quantitative PCR ( qPCR ) was performed as described [33] . IS2404 cycle threshold ( Ct ) values were converted to genome equivalents ( GE ) to estimate bacterial load within a sample by reference to a standard curve ( r2 = 0 . 9312 , y = [-3 . 000Ln ( x ) +39 . 33]*Z , where y = Ct and x = amount of DNA [fg] and Z = the dilution factor] ) , calculated using dilutions of genomic DNA from M . ulcerans strain JKD8049 , quantified using a fluorimeter ( Qubit , Invitrogen ) [33] . At the end of the experimental period or when a clinical end-point was reached mice were humanely killed . The region of a mouse-tail spanning a likely lesion was cut into three equal sections for histology , qPCR and CFU counts . Individual tail pieces for CFU counts were weighed and placed into sterile 2ml screw capped tube containing 0 . 5g of large glass beads and 600μl of sterile 1x PBS . Tissues were homogenized using four rounds of 2x 30second pulses in a high-speed tissue-disruptor at 6500 rpm , with tubes placed on ice for 5 minutes between each round . A 300μl volume of this homogenate was decontaminated with 300μl of 2% NaOH ( v/v ) and incubated at room temperature for 15 minutes . The preparation was neutralized drop-wise with a 10% solution of orthophosphoric acid ( v/v ) with added bromophenol blue until the solution changed from blue to clear . The mixtures were diluted in PBS and CFUs determined by spot plating as described above . Sections of mouse-tails were fixed in 10% ( w/v ) neutral-buffered-formalin and imbedded in paraffin . Each mouse-tail was sectioned transversely ( 4μm thick ) and subjected to Ziehl-Neelson and hematoxylin/eosin staining . The fixed and stained tissue sections were examined by light microscopy .
In experiment one , we established a murine model of M . ulcerans transmission that represented a skin surface contaminated with the bacteria and then subjected to a minor penetrating trauma , via either a mosquito bite or needle stick puncture . For this experiment , only Aedes notoscriptus mosquitoes were used , a local species previously associated with BU in south east Australia [22] . We first coated the tails of 12 mice with M . ulcerans then exposed only the tails to A . notoscriptus . Six of the 12 mice exposed to mosquitoes were bitten once each , and of these six mice , two developed BU lesions ( Table 1 , Fig 1B , Fig 2A ) . Histology of these lesions confirmed a subcutaneous focus of AFB , within a zone of necrotic tissue . There was also characteristic epithelial hyperplasia adjacent to the site of infection ( Fig 2B and 2C ) . Material extracted from the lesions was IS2404 qPCR-positive and culture positive for M . ulcerans ( S1 Table ) . Mice bitten by mosquitoes but with tails coated only with sterile culture media did not develop lesions ( Table 1 ) . In the same experiment , we also subjected five mice to a single needle stick puncture . Each mouse had their tail coated with M . ulcerans as for the mosquito biting . Four of these five mice developed M . ulcerans positive lesions ( Table 1 , Fig 2D ) , with subcutaneous foci of infection and viable bacteria ( Fig 2F ) . The histology of these lesions was the same as the mice subjected to mosquito blood feeding , however bacterial burden was higher following needle stick puncture ( Fig 2C compared with Fig 2F ) . Six mice with their tails coated with M . ulcerans but not subjected to a puncturing injury did not develop lesions and remained healthy until the completion of the experiment at six months . This experiment suggested that minor penetrating skin trauma ( defined here as a puncture <0 . 5mm diameter and <2mm deep ) to a skin surface contaminated with M . ulcerans is sufficient to cause infection . It also revealed a means by which mosquitoes could act as mechanical vectors of M . ulcerans . In experiment two , using approximately the same dose of bacteria to coat the mouse-tails , we repeated experiment-1 but with Aedes aegypti , because of the close association of this mosquito to humans world-wide and their potential to vector pathogens . Despite multiple mosquito bites per mouse in the second experiment compared to the first , none of the five Aedes aegypti-exposed mice developed lesions ( Table 1 ) . However , as for experiment 1 , four of five mice subjected to single , needle stick puncture developed M . ulcerans positive tail lesions ( Table 1 ) . A third needle stick puncture experiment was then conducted , this time using a smaller diameter , 30-gauge needle , to assess the impact of a smaller injury . There were 13/14 mice that developed BU when subjected to a single needle stick puncture through a contaminated skin surface , while eight mice with contaminated skin but no injury did not progress to disease ( Table 1 ) . Thus , across the three experiments there were 21/24 mice ( 88% ) with needle stick puncture that developed BU , suggesting that this is an efficient mode of disease transmission ( Table 1 ) . Either A . notoscriptus mosquito bite or needle stick trauma significantly increased the risk of developing BU in our mouse skin surface contamination model ( Tables 2 & 3 ) . We assessed the likely burden of M . ulcerans by individual IS2404 qPCR of the head , abdomen and legs for each mosquito that blood fed ( Fig 3 ) . A summary of these results is shown in Fig 3A . We noted that the bacterial load ( expressed as genome equivalents [GE] ) was significantly higher in the mosquito heads associated with mice that developed lesions ( p<0 . 05 ) ( Fig 3B , S1 Table ) . These data point to a threshold , above which some mosquitoes may become competent mechanical vectors for M . ulcerans transmission . Based on the time until a tail lesion was first observed , and when using the highest concentration of bacteria ( dose range 9–55 CFU , Table 1 ) we estimated a median incubation period ( IP ) of 12 weeks ( Fig 4A ) . This result overlaps with the IP in humans for BU , estimated in different epidemiological studies from 4–10 weeks in Uganda during the 1960s [14] and 4–37 weeks in south east Australia [28] . We then estimated the infectious dose-50 ( ID50 ) . We used six different concentrations of M . ulcerans to coat the tails of mice ( n = 5 mice/dilution ) , subjected each mouse-tail to a single needle stick puncture , and then observed the number of mice for each dilution that developed Buruli ulcer , allowing an ID50 estimate of 2 . 6 CFU ( 95% CI 1 . 6–3 . 6 CFU ) ( Fig 4B ) . To our knowledge this is the first estimate of an M . ulcerans infectious dose and indicates that like Mycobacterium tuberculosis and Mycobacterium leprae , a small quantity of this slow growing mycobacterium is sufficient to cause disease .
Pathogen transmission by arthropods is generally characterized by either biological transmission , such as malaria [34] or mechanical transmission , where replication or biological transformation of the pathogen within the vector is not necessary for disease spread [35 , 36] . Here , we show for the first time an efficient mechanical mode of transmission of Mycobacterium ulcerans to a mammalian host that implicates both puncturing injuries and arthropods . In our study , the uninfected host is externally contaminated with M . ulcerans that is certainly plausible in many areas of the world . We propose that a micro-puncture wound of any sort whether it is by natural means e . g . , a thorn , arthropod bite or artificially induced via a human-mediated puncture has the potential to inject M . ulcerans and generate an ulcer . This research was designed around established frameworks for implicating vectors in disease transmission and provides the necessary causational evidence to help resolve the 80-year mystery on how M . ulcerans is spread to people [15 , 37] . The efficient establishment of BU we have shown here via minor penetrating trauma such as a needle puncture through a contaminated skin surface helps fulfil one of four Barnett Criteria [37] . In vector ecology , mechanical transmission is defined as a non-circulative process involving accidental transport of the pathogen [36] . That is , the pathogen , in some fashion , nonspecifically associates or contaminates the mouthparts ( stylet ) of an arthropod vector . Insect mechanical transmission of BU implies that if M . ulcerans were ingested and then egested via regurgitation or salivation , the mechanism would act more like a syringe than a needle [38] . Such a mode of M . ulcerans disease transmission is supported by previous laboratory studies in which Naucoris and Belostmatid water bugs were contaminated via feeding on maggot prey that had been injected with M . ulcerans or fed naturally on dietary contaminated larval mosquito prey [26 , 39] . Our demonstration in the current study of mechanical transmission suggests there are potentially multiple or parallel pathways of M . ulcerans infection [37] . Examples of bacterial diseases with multiple transmission modes include tularemia , plague and trachoma [40 , 41] . Support for our mechanical transmission model also comes from the many field reports over the decades of M . ulcerans infection following trauma to the skin . Case reports have noted BU following a suite of penetrating injuries ranging from insect bites ( ants , scorpions ) , snake bite , human bite , splinters , gunshot , hypodermic injections of medication and vaccinations [42–44] . Epidemiologists in Uganda during the 1960s and 70s suggested sharp-edged grasses might introduce the bacteria [45] . However , a recent laboratory study established that abrasions of the skin in Guinea pig models and subsequent application of M . ulcerans was not enough to cause an ulcer , however , this same study established that a subcutaneous injection would cause an ulcer [46] . As a sequel to this study in Guinea pigs , we raised the question of how likely it was that mammalian skin could be sufficiently coated in M . ulcerans that an injury from natural or anthropogenic sources could lead to infection . Other explanations for the transmission of M . ulcerans include linkages with human behavior that increase direct contact with human skin and contaminated water [15] . A recent study from Cameroon recorded the persistence of M . ulcerans over a 24-month period in a waterhole used by villagers ( including BU patients ) for bathing [47] . A similar study in Ghana documented a 90% positivity rate for MU for water bodies frequented by community members for bathing and washing purposes [48] . Hence , it is reasonable to envisage a scenario where a villager’s skin surface becomes contaminated after bathing in such a water body and is primed for infection if ( i ) the concentration of bacteria is sufficiently high , and ( ii ) an inoculating event occurs . Whereas , in Australia , earlier studies have shown that M . ulcerans contamination of possum feces in and around the gardens of BU patients might present a similar skin surface contamination model in this region [17 , 49] . Future experiments will address the possibility that insect vectors may be able to move M . ulcerans from one source and inject it into an animal or human . Our focus on mechanical mosquito transmission arose from previous surveys in southeastern Australia where a strong association between M . ulcerans positive mosquitoes and human cases of BU has shown that M . ulcerans has not only been found on adult mosquitoes from both lab and field studies but also a biological gradient , where maximum likelihood estimates ( MLE ) of the proportion of M . ulcerans-positive mosquitoes increased as the number of cases of BU increased [22 , 39 , 50–53] . However , a recent study in Benin , West Africa found no evidence of M . ulcerans in association with adult mosquitoes [54] . The authors concluded that the mode of transmission might differ between southeastern Australia and Africa . Although , laboratory and fieldwork in West Africa suggest that aquatic insects , including mosquito larvae , play a role as reservoirs in nature for M . ulcerans that may be indirectly tied to transmission by serving as dispersal mechanisms [21 , 26 , 55] . Epidemiological studies have shown that direct contact with water is not a universal risk factor for BU [8 , 11] . Prior exposure to insect bites and gardening are also independent risk factors for developing BU , while use of insect repellent is protective [11 , 56] . Laboratory support to show mosquitoes can be competent vectors to spread BU is important additional evidence required to satisfy accepted vector ecology criteria for implicating insects in disease transmission [15 , 37] . We found that infection was established following very minor penetrating trauma . Mosquitoes , in general , feed by insertion of a stylet , sheathed within the proboscis , beneath the skin of a host . The stylet has an approximate diameter 10 μM tapering to 1 μM at its tip and extending 1–2 mm below the skin surface . We estimated the density of M . ulcerans on the mouse-tails surface was 100–200 CFU/mm2 . Thus , the number of bacteria potentially injected during mosquito feeding through this contaminated surface is likely to be low , but this is consistent with our infectious dose estimates from needle-stick punctures , indicating an ID50 of only 2 . 6 CFU ( Fig 4B ) . Aedes notoscriptus mosquitoes are approximately twice as large as Aedes aegypti . Larger size may imply a longer stylet length , longer blood feeding time with a deeper penetration to a depth that may initiate M . ulcerans infection more frequently than that from Aedes aegypti mosquitoes that are smaller and do not blood feed as long . Such subtle differences in mosquito morphology and behavior may indicate why mechanical transmission in any form may be uncommon . There are strong parallels here with Mycobacterium leprae , the agent of leprosy . Like BU , the mode of transmission of the leprosy bacillus is unclear , but the infective dose is known to be very low ( 10 bacteria ) and epidemiological evidence suggests multiple transmission pathways , including entry of the bacteria after skin trauma [57 , 58] . Our infective dose estimate for M . ulcerans is consistent with observations that pathogens producing locally acting molecules to cause disease ( e . g . the polyketide toxin mycolactone of M . ulcerans ) have lower infective doses [59] . In summary , we have uncovered a highly efficient ( 88% rate ) for needle stick skin punctures and a lower rate for mosquito punctures , suggesting a plausible mechanical transmission mode of M . ulcerans infection via anthropogenic or natural skin-puncturing microtrauma . We conclude from these experiments that reduction of exposure to insect bites , access to clean water for bathing , and prompt treatment of wounds and existing BU are concrete measures likely to interrupt BU transmission . | Buruli ulcer is a neglected tropical disease caused by infection with Mycobacterium ulcerans . Unfortunately , how people contract this disease is not well understood . Here we show for the first time using experimental infections in mice that a very low dose of M . ulcerans delivered beneath the skin by a minor injury caused by a blood-feeding insect ( mosquito ) or an experimental needle puncture is sufficient to cause Buruli ulcer . This research provides important laboratory evidence to advance our understanding of Buruli ulcer disease transmission . | [
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"syst... | 2017 | Mycobacterium ulcerans low infectious dose and mechanical transmission support insect bites and puncturing injuries in the spread of Buruli ulcer |
Genetic transformation of bacteria harboring multiple Restriction-Modification ( R-M ) systems is often difficult using conventional methods . Here , we describe a mimicking-of-DNA-methylation-patterns ( MoDMP ) pipeline to address this problem in three difficult-to-transform bacterial strains . Twenty-four putative DNA methyltransferases ( MTases ) from these difficult-to-transform strains were cloned and expressed in an Escherichia coli strain lacking all of the known R-M systems and orphan MTases . Thirteen of these MTases exhibited DNA modification activity in Southwestern dot blot or Liquid Chromatography–Mass Spectrometry ( LC–MS ) assays . The active MTase genes were assembled into three operons using the Saccharomyces cerevisiae DNA assembler and were co-expressed in the E . coli strain lacking known R-M systems and orphan MTases . Thereafter , results from the dot blot and restriction enzyme digestion assays indicated that the DNA methylation patterns of the difficult-to-transform strains are mimicked in these E . coli hosts . The transformation of the Gram-positive Bacillus amyloliquefaciens TA208 and B . cereus ATCC 10987 strains with the shuttle plasmids prepared from MoDMP hosts showed increased efficiencies ( up to four orders of magnitude ) compared to those using the plasmids prepared from the E . coli strain lacking known R-M systems and orphan MTases or its parental strain . Additionally , the gene coding for uracil phosphoribosyltransferase ( upp ) was directly inactivated using non-replicative plasmids prepared from the MoDMP host in B . amyloliquefaciens TA208 . Moreover , the Gram-negative chemoautotrophic Nitrobacter hamburgensis strain X14 was transformed and expressed Green Fluorescent Protein ( GFP ) . Finally , the sequence specificities of active MTases were identified by restriction enzyme digestion , making the MoDMP system potentially useful for other strains . The effectiveness of the MoDMP pipeline in different bacterial groups suggests a universal potential . This pipeline could facilitate the functional genomics of the strains that are difficult to transform .
Experimental genetic manipulation has been an essential tool for gaining insight into the significance of bacterial metabolism , physiology and pathogenesis [1] , [2] and has been instrumental in developing microbial biotechnology [3] . To date , only a limited proportion of the laboratory culturable bacterial species are amenable to genetic manipulation . Among these manipulation-friendly species , many strains are refractory to transformation by exogenous DNA . The currently available laboratory model species satisfied the research need for genetic uniformity , but the handicap in genetic manipulation is a challenge when exploring the unique traits of these non-model species/strains [4] . Restriction-Modification ( R-M ) systems are composed of restriction enzymes ( REases ) and DNA methyltransferases ( MTases ) . These systems are widespread in both bacteria and archaea . Approximately 95% of the genome-sequenced bacteria harbor R-M systems , and 33% carry more than four REases [5] . R-M systems have been classified into four groups depending on their subunit composition , cleavage sites , sequence specificity and cofactor requirement [6] . Type I , II and III REases cleave unmethylated DNA at specific sites , and Type IV cut methylated DNA with foreign patterns [6] . R-M systems are believed to act as defenses to protect the prokaryotic cells against invading DNA; exogenous DNA with foreign methylation patterns are recognized and rapidly degraded [7] . Inevitably , this defensive machinery hinders the experimental genetic manipulation of many bacteria species . Moreover , genetic modification becomes even more difficult when the targeted bacteria carry multiple R-M systems . The Nitrobacter hamburgensis X14 strain oxidizes nitrite to conserve energy and is commonly used in nitrification research [8] . Although the strain was isolated more than 100 years ago [9] , limited research on this strain has been published due to the lack of genetic manipulation tools . Genomic sequencing has revealed eleven sets of R-M genes in N . hamburgensis X14 [10] . Bacillus cereus ATCC 10987 is a non-lethal strain in the same genetic subgroup as B . anthracis [11] . Although genetic manipulation has been routine in many other B . cereus strains [12] , limited research has been performed in B . cereus ATCC 10987 due to its resistance to genetic manipulation . Transformation of B . cereus ATCC 10987 has been performed with DNA prepared from Bacillus subtilis with low efficiency [13] , [14] , and four REases have recently been characterized [15] . Bacillus amyloliquefaciens TA208 is an industrial guanosine-producing strain [16] and has been reported to be transformed at low efficiencies with plasmids prepared from Escherichia coli [17] . Here , we describe a mimicking-of-DNA-methylation-patterns ( MoDMP ) pipeline . An E . coli strain lacking all of the known six characterized R-M systems and orphan MTases was generated to prevent unintentional modification of propagated plasmids or cleavage of DNA with foreign methylation patterns . After expressing multiple active MTases from the target bacteria in the E . coli strain lacking known R-M systems and orphan MTases , the DNA methylation patterns of E . coli were altered to reflect the patterns of the target bacteria . Plasmids prepared from these hosts escaped the host REases , and genetic manipulation could be readily achieved . The pipeline was shown to be effective in all of the three aforementioned strains which are difficult to transform using conventional methods . We report the first genetic transformation of Nitrobacter , the improvement of transformation efficiency by exogenous plasmids in B . cereus ATCC 10987 and B . amyloliquefaciens TA208 using the MoDMP pipeline , and direct mutagenesis using non-replicative plasmids in B . amyloliquefaciens TA208 . The MoDMP pipeline may be readily adapted to bacteria carrying multiple R-M systems .
To avoid the unintentional activation of the Type IV R-M systems in the target bacteria , plasmids that are to be used for genetic transformation should be prepared from an E . coli host that does not methylate DNA ( dam- dcm- hsdRMS- ) . Moreover , the expression of MTases in E . coli would induce foreign patterns of modification on the E . coli chromosomal DNA; therefore , the REases that restrict methylated DNA ( Mrr , McrA and MrcBC ) should be inactivated in the MoDMP host . To date , three E . coli strains that do not methylate DNA or restrict DNA with foreign methylation patterns have been described ( E . coli DB24 [18] , E . coli HST04 from Clontech and E . coli JTU007 [19] ) . In this study , an E . coli mutant lacking all of the six characterized R-M systems and orphan MTases genes , namely strain EC135 , was generated in the E . coli TOP10 background by deleting the dam and dcm genes . A wild-type recA allele was introduced into the strain prior to dam inactivation to counteract the inviability of the dam recA double mutant strain [20] . The construction of the E . coli EC135 strain is explained in detail in the Supporting Information Methods ( Text S1 ) , and validation of the strain is described in the Supporting Information Results ( Text S1 and Figure S1 ) . MTases modify DNA by adding a methyl group to the individual bases , thereby preventing DNA cleavage by the corresponding REases . In the MoDMP procedure , MTases from the difficult-to-transform bacterial strains were used to protect DNA from being degraded by the REases . The genes of 24 putative MTases including two belonging to Type I R-M systems , 19 belonging to Type II R-M systems , two belonging to Type III R-M systems , and one orphan MTase were cloned from the genomes of the three difficult-to-transform strains into the pBAD43 vector ( Table 1 ) . To date , three types of methyl-transferring activity have been described for bacterial DNA MTases , namely N6-methyladenine ( m6A ) , N4-methylcytosine ( m4C ) and 5-methylcytosine ( m5C ) modifications . Dot blot assays were conducted to detect the modified bases in the total genomic DNA of the E . coli EC135 strains expressing individual MTase using antibodies against m6A , m4C and m5C . In total , 13 of the putative MTase genes exhibited methyl transfer activity to DNA ( Figure 1 ) , and the bases they modified are summarized in Table 1 . The spots of the dot blots were also scanned and quantified , and the relative intensity of each spot is shown in Figure S2 . The hybridization signals of BCE_0392 , Nham_0582 , Nham_0803 and Nham_3225 were weak in the dot blot experiments . To confirm their activity , the total DNA of the E . coli EC135 strains expressing these four MTases individually were digested to deoxynucleosides , and Liquid Chromatography-Mass Spectrometry ( LC-MS ) assays were performed to detect N6-methyl-2′-deoxyadenosine ( m6dA ) in the DNA . In High Performance Liquid Chromatography-Quadrupole Time-of-Flight/Mass Spectrometry ( HPLC-QTOF/MS ) analysis , m6dA ( m/z 266 . 12 ) was readily detected in the digested DNA of the BCE_0392- , Nham_0582- and Nham_3225-expressing strains in the MS spectrum at the corresponding retention time of standard m6dA , validating that BCE_0392 , Nham_0582 , and Nham_3225 displayed DNA m6A modification activity in E . coli ( Figure 2 ) . Xu et al . has reported that MTase activity was not detected for in vivo translated BCE_0392 protein using [H3]AdoMet and phage λ DNA or pXbaI plasmid DNA as substrate [15] . This might either be caused by the mis-folding of in vivo translated BCE_0392 protein or by the absence of BCE_0392 recognition sites from the substrate DNA they used . Although m6dA was not detected for Nham_0803 in the HPLC-QTOF/MS analysis ( Figure 2 ) , the MTase activity of Nham_0803 could not be ruled out , since the DNA of the Nham_0803-expressing strain displayed slight but noticeable signal increase compared with the E . coli EC135 strain harboring empty vector ( Figure S2 ) . Other more sensitive and targeted MS approaches could be useful in detecting the possible modified nucleoside conferred by Nham_0803 [21] . It is noteworthy that the E . coli strain EC135 expressing the Nham_0569 MTase grows much slower than the control strain or strains expressing other MTases ( Nham_0803 and Nham_3225 ) , and the final biomass of strain EC135 carrying Nham_0569 was about 60% of that for the control strains ( Figure S3 ) . This growth retardation in E . coli may be attributed to the toxicity of the Nham_0569 MTase . The E . coli EC135 strain lacks methylation-dependent REases activity , which will cleave its own DNA when foreign methylation patterns are detected , leading to cell death; however , the modification of m6A by the Nham_0569 MTase may occur on sequences overlapping with Dam sites in E . coli , which participates in DNA mismatch repair and replication initiation . Consequently , the premature and untimely methylation of DNA may interfere with strain proliferation [22] . Subsequent sequence specificity analysis has revealed that Nham_0569 modified GATC sequences ( see below ) . To mimic the DNA methylation patterns of the strains that are difficult to transform , we co-expressed the active MTases from each strain . By taking advantage of the high rates of recombination in Saccharomyces cerevisiae , MTase genes , with optimized ribosome binding site ( RBS ) for expression in E . coli , were inserted into the pWYE724 backbone to form three operons . The diagrams of the pMoDMP plasmids are shown in Figure 3 . The insertion of the MTase genes was verified by multiple methods , including PCR analysis of plasmids , restriction digestion ( Figure S4 ) and DNA sequencing . The protocol for DNA assembly in S . cerevisiae is very powerful , and up to eight MTase genes from Nitrosococcus oceani ATCC 19707 could be readily assembled in our lab ( Zhang et al . , unpublished ) . DNA from the E . coli EC135 strain expressing multiple MTases was also tested by dot blot assay , with the DNA of the parent strains as the positive controls ( Figure 4 ) . DNA from the co-expression strains exhibited multiple methylation signals , indicating the alteration of the DNA methylation patterns in E . coli . It is worth noting that the m4C and m5C signals in B . amyloliquefaciens strain TA208 , the m5C signal in B . cereus strain ATCC 10987 and the m4C signal in N . hamburgensis strain X14 were much weaker when compared with their corresponding MTase over-expressing E . coli strain . This signal weakness could be attributed to the different number of MTase target sequences between the genomic sequences of E . coli and the parent strains or to the fact that the B . amyloliquefaciens TA208 strain is an adenine auxotroph , which limits the availability of S-adenosylmethionine ( AdoMet ) . However , pMK4 plasmid DNA prepared from the TA208 strain is resistant to BamHI digestion , which is a homolog to the restriction subunit of the BAMTA208_16650-BAMTA208_16660 systems ( see below ) . Thus , regulational expression of the R-M systems could also explain the weak blot signals in the parent strains; Hegna et al . has reported that the R-M system is activated when B . cereus is grown in the presence of exogenous DNA [23] . To determine the efficacy of the MoDMP pipeline , various shuttle plasmids carrying divergent replicons and conferring different antibiotic resistance were used to transform B . amyloliquefaciens TA208 and B . cereus ATCC 10987 . Prior to transforming Bacillus , the shuttle plasmids were methylated in vivo when transformed into the E . coli EC135 strain harboring the pMoDMP plasmids . B . amyloliquefaciens TA208 and B . cereus ATCC 10987 were transformed by these plasmids , and the transformation efficiencies were calculated . The B . amyloliquefaciens TA208 strain could not be transformed with plasmids prepared from E . coli TOP10 cells but could be transformed with plasmids from the E . coli EC135 strain with low efficiency; this result indicates that a methylation-dependent Type IV R-M system may exist in B . amyloliquefaciens TA208 , although its coding gene was not found during annotation of the genome sequence [16] . Hence it may also be that the plasmids methylated at the Dam and Dcm sites would not be inherited in B . amyloliquefaciens TA208 , e . g . , methylated replication origin would not be bound by the replication protein . The MoDMP protocol increased the transformation efficiencies of all the plasmids tested in B . amyloliquefaciens TA208 . The pMK4 plasmid from MoDMP hosts showed the highest transformation efficiency ( 3×106 CFU/µg DNA ) , representing a 104-fold increase compared to that of the plasmids from the E . coli EC135 strain . The MoDMP procedure also enabled two previously untransformable plasmids , pAD123 and pDG148StuI , to be transformed at an efficiency of 1×105 CFU/µg DNA ( Figure 5A ) . For the B . cereus ATCC 10987 strain , the MoDMP pipeline increased the transformation efficiency of the pMK4 plasmid to 2×107 CFU/µg DNA and increased the transformation efficiency of pMK3 by 103 fold compared to those from strains E . coli TOP10 or EC135 ( Figure 5B ) . The plasmids prepared from E . coli TOP10 and EC135 strains showed similar transformation efficiencies , indicating that the putative Type IV R-M systems ( BCE_1016 and BCE_2317 ) in B . cereus ATCC 10987 may be inactive . These results were the same as those obtained in the B . cereus ATCC 14579 strain , which could be transformed by methylated DNA ( DNA from non-dam dcm mutant strains ) [24] , though some researchers prefer to use unmethylated DNA [25] . The high transformation efficiency achieved with the MoDMP method in both Bacillus strains would allow for the direct inactivation of genes using non-replicative integration plasmids . To further validate the efficacy of the MoDMP procedure , the gene coding for uracil phosphoribosyltransferase ( upp ) in B . amyloliquefaciens TA208 was selected for inactivation using non-replicative integration plasmids . The B . amyloliquefaciens TA208 strain was transformed with pWYE748 plasmids that had been through the MoDMP host . The pWYE748 plasmid recombines with chromosome of B . amyloliquefaciens TA208 at the upp locus with a low rate ( 10−6 ) because it lacks a replication origin for Bacillus ( Figure 6A ) . BS043 was obtained and PCR and sequencing analyses revealed the successful replacement of the upp gene with the chloramphenicol resistance gene in this strain ( Figure 6B ) . Uracil phosphoribosyltransferase converts 5-fluorouracil ( 5-FU ) to 5-fluoro-UMP , which is ultimately metabolized to the toxic compound 5-fluoro-dUMP capable of inhibiting the activity of thymidylate synthetase . The upp/5-FU module has been widely used in many bacterial species for deletion of genes without introducing antibiotic resistance markers [26] . In contrast with the B . amyloliquefaciens TA208 strain , the BS043 strain could grow on minimal medium ( MM ) supplemented with 5-FU ( Figure 6C ) . These findings suggest that the MoDMP system elevated transformation efficiencies of exogenous plasmid to enable direct gene inactivation , and the upp gene could be used as a counter-selection marker for the in-frame deletion of genes in B . amyloliquefaciens . N . hamburgensis X14 harbors 11 putative R-M systems , and successful genetic transformation of this strain has not been reported [27] . In this study , the N . hamburgensis X14 strain was transformed with plasmids carrying the Green Fluorescent Protein ( GFP ) encoding gene gfpmut3a using the MoDMP procedure . Total genomic DNA was extracted from 10 mL of the transformed bacteria cells . The plasmid was rescued to E . coli TOP10 cells , and subsequent plasmid preparation ( Figure S5A ) and restriction digestion with SalI and PstI ( Figure S5B ) verified the existence of pWYE561 in the transformed bacterial cell lines . During the subculture process , the bacterial cell lines were monitored for contamination by microscopy and culturing on LB plates at 30°C , and no contamination was observed . Green fluorescent signals were observed in the cytoplasm of Nitrobacter , thereby revealing the successful transformation of Nitrobacter ( Figure 7A ) . The culture may contain multiclonal cell lines because the transformants were enriched twice through successive sub-inoculation of the transformation cell mixture in liquid culture ( see Materials and Methods for details ) . Using flow cytometry , the ratio of fluorescent cells was determined to be 50 . 37% ( Figure 7B ) , demonstrating that 50 . 37% of the cells were positive transformants . Clonal cell lines could be obtained by streaking the transformant-enriched culture on nylon membranes placed on solid medium and periodically transferred to fresh plates , as described by Sayavedra-Soto et al . in Nitrosomonas europaea [28] . To make the MTase expression vectors more useful , the modification sequences of MTases were determined when expressed individually or co-expressed . As shown in Figure S6A , BAMTA208_6525 protected plasmid from cleavage by BamHI ( GGATCC ) , BglII ( AGATCT ) , and partially from BclI ( TGATCA ) , indicating that BAMTA208_6525 modifies RGATCY and partial TGATCA sequences . BAMTA208_6715 protected pMK4 from cleavage by HaeIII ( GGCC ) , Fnu4HI ( GCNGC ) and Bsp1286I ( GDGCHC ) , and BAMTA208_19835 and BAMTA208_16660 protect pMK4 from TseI ( GCWGC ) and BamHI ( GGATCC ) cleavage , respectively . When co-expressed , the four active MTases from B . amyloliquefaciens TA208 could protect the plasmids from cleavage by all of the REases tested in the individual expression experiments . However , DNA from the B . amyloliquefaciens TA208 strain was only resistant to BamHI cleavage and partially resistant to Fnu4HI and TseI cleavage ( Figure S6B ) , indicating that the expression of BAMTA208_16660 in the native strain was complete , whereas those of BAMTA208_6715 and BAMTA208_19835 were incomplete , and BAMTA208_6525 was not expressed . For the B . cereus ATCC 10987 strain , BCE_0393 could protect plasmid from cleavage by at least 12 REases , i . e . , Fnu4HI ( partial ) , TseI , BbvI ( GCAGC ) , HaeIII , EaeI ( YGGCCR ) , HpaII ( CCGG ) , MspI ( CCGG , partial ) , NlaIV ( GGNNCC ) , BssHII ( GCGCGC ) , HhaI ( GCGC , partial ) , AvaII ( GGWCC ) and PspGI ( CCWGG , partial ) , and the modification sequences of BCE_0393 were concluded as GCWGC , GGCC , CCGG , GGNNCC , GCGCGC , GGWCC and CCWGG ( partial ) . BCE_0365 protected DNA from cleavage by TseI and BbvI , indicating that it modifies GCWGC sequence , BCE_4605 protect DNA from cleavage by AvaII via modification of GGWCC sequence , and BCE_5606 and BCE_5607 both protect DNA from cleavage by BceAI [ACGGC ( N ) 12/14] ( Figure S7A ) . These results are consistent with the reports of Xu et al . [15] , except for that “GGWCC” was added to the modification sequences of BCE_0393 in this study . The multi-specificity nature of the prophage MTase BCE_0393 and its sequence overlapping with other MTases from B . cereus ATCC 10987 indicated that it plays a major role in the MoDMP pipeline of this strain . The pMK4 plasmids prepared from the E . coli strain expressing BCE_0392 was challenged with various REases which might be sensitive to m6A modification , including AvaII , BamHI , BbvI , BceAI , BglII , BsiEI , Bsp1286I , BspDI , BstNI , BspHI , DpnII , EaeI , EcoRI , Fnu4HI , HincII , HindIII , HpaII , HinfI , NlaIV , PstI , PshAI , PspGI , SalI , ScrFI , SwaI , SpeI , TaqI and TseI , but resistance to cleavage was not observed . Therefore BCE_0392 might modify sequences that are not recognized by these REase , and new techniques like single-molecule DNA sequencing other than restriction analysis using commercialized REases should be useful in identifying the sequence specificity of BCE_0392 [29] . DNA nicking-associated concatenation activity was also detected for BCE_0392 in vivo [15] , suggesting that this ParB-Methyltransferase might participate in phage DNA replication or phage packaging , since BCE_0392 was located in a prophage region in the chromosome of the B . cereus ATCC 10987 strain [11] . When co-expressed , BCE_0393 , BCE_0365 , BCE_4605 , BCE_5606 and BCE_5607 protected all of the pMK4 plasmid from AvaII and BceAI digestion , protected most of the pMK4 plasmids from Fnu4HI , TseI , BbvI , HaeIII , EaeI , HpaII and NlaIV cleavage , provided pMK4 partial protection from HhaI digestion and provided pHCMC05 full protection from BssHII cleavage ( Figure S7B ) . However , pMK4 plasmid prepared from the B . cereus ATCC 10987 strain was only resistant to TseI , BbvI , AvaII and BceAI digestion , and partially resistant to Fnu4HI digestion ( Figure S7B ) , indicating that BCE_0393 is not completely expressed in its native host . For N . hamburgensis X14 , Nham_0569 could protect DNA from cleavage by at least 10 REases sensitive to m6A modification , i . e . , DpnI ( GAmTC ) , DpnII ( GATC ) , PvuII ( CAGCTG ) , SspI ( AATATT ) , SpeI ( ACTAGT ) , MfeI ( CAATTG ) , NlaIII ( CATG ) , AseI ( ATTAAT ) , HinfI ( GANTC ) and TfiI ( GAWTC ) , but full protection was not achieved ( Figure S8A ) . Therefore , Nham_0569 might be a multi-specific enzyme harboring at least eight modification sites , i . e . , GATC , CAGCTG , AATATT , ACTAGT , CAATTG , CATG , ATTAAT and GANTC , or a new member of the recently characterized non-specific DNA adenine MTase [30] . Nham_3225 protected DNA from HinfI and TfiI cleavage by modifying GANTC sequence ( Figure S8A ) . The pMK4 plasmids prepared from the E . coli EC135 strains expressing Nham_0582 and Nham_0803 were not resistant to the cleavage by DpnII , EcoRI , DraI , PvuII , SspI , HinfI , HindIII , BspHI , BamHI , SpeI , KpnI , SacI or ApaLI , and the specificity of Nham_0582 and Nham_0803 was not identified . The four active MTases from N . hamburgensis X14 provided DNA partial protection from cleavage by DpnI , DpnII , PvuII , SspI , SpeI , MfeI , NlaIII , AseI , HinfI and TfiI when co-expressed , and the genomic DNA of the N . hamburgensis X14 strain was sensitive to DpnII digestion , partially resistant to DpnI digestion and resistant to SpeI , AseI , HinfI and TfiI digestion ( Figure S8B ) . These results indicated that Nham_0569 was only partially expressed in its native host . The modification sequences of MTases are summarized to Table 1 . The MoDMP hosts and difficult-to-transform bacteria showed similar DNA methylation patterns based on the REase digestion analysis , but the DNA from MoDMP hosts have more modification sites than corresponding difficult-to-transform bacteria . And this was mainly caused by the limited expression of some MTases in their native hosts , especially some prophage-derived MTases , i . e . , BAMTA208_6525 , BCE_0393 and Nham_0569 , which are multi-specific MTases .
Genetic transformation of bacteria harboring multiple R-M systems has been problematic using conventional methods . It has been long recognized that the exogenous MTases over-expressed in E . coli could modify DNA in vivo and protect them from digestion by their cognate REases [31] . Strategies based on this fact have been developed to overcome the restriction barrier of bacteria , including in vitro or in vivo plasmid modification prior to transformation [32] , [33] , heat inactivation of the REases [34] or gene knock-outs [35] . However , it has been reported that the inactivation of the SauI Type I R-M system is insufficient for Staphylococcus aureus to efficiently accept foreign DNA [36] . In this study , a strategy has been developed to mimic the DNA methylation patterns of the difficult-to-transform bacteria in a modified E . coli strain . To achieve this goal , active MTases from the difficult-to-transform bacteria were co-expressed in an E . coli host lacking all of the characterized R-M systems and orphan MTases . The protocol for genetic transformation of difficult-to-transform bacteria using a plasmid prepared in a different E . coli host is diagramed in Figure S9 . As indicated in strain B . amyloliquefaciens TA208 , DNA from the E . coli hosts with Dam and Dcm contains methylated bases in GAmTC and CCmWGG sequences but is not methylated at the recognition sequences of the host Type I–III REases; this DNA would then be recognized by Type I–IV REases in the target bacteria ( upper left panel in Figure S9 ) . Plasmids prepared from dam dcm EcoKI mutant E . coli would make the strains transformable at a low efficiency due to the plasmids being able to avoid restriction by the Type IV REases in the target bacterium ( lower left panel in Figure S9 ) . Many bacterial species have been reported to restrict DNA containing Dam and Dcm methylation; for example , B . anthracis could be transformed by DNA from an E . coli dam dcm mutant strain but not by DNA from E . coli host strains with the wild type alleles [37] , [38] . Additionally , DNA prepared from the E . coli SCS110 strain was more accessible to Corynebacterium glutamicum than DNA from E . coli hosts with Dam and Dcm [39] . However , not all difficult-to-transform bacteria behave like this . Bacteria lacking functional Type IV REases could be transformed by DNA prepared from E . coli hosts with Dam , Dcm or EcoKI , albeit at a low efficiency . Currently , it has been shown that the B . cereus ATCC 10987 strain does not restrict DNA with Dam and Dcm methylation . It has also been reported that the plasmids methylated in E . coli TOP10 cells using the MTases of the target bacteria can allow for the genetic manipulation of Bifidobacterium breve [40] . Ryan et al . showed that the bbe02 and bbq67 loci limited the transformation of Borrelia burgdorferi by shuttle vector DNA prepared from E . coli , irrespective of its Dam , Dcm or EcoKI methylation status [41] . The N . hamburgensis X14 strain used in this study may restrict DNA with Dcm methylation; the plasmid-borne putative Type IV R-M system Nham_4502-Nham_4503 has been annotated in the REBASE database [5] , though its activity and specificity remain unclear . As shown in the upper right panel in Figure S9 , expression of exogenous MTases in E . coli would result in methylation of chromosomal DNA , and Mrr , McrA and McrBC would recognize and cleave the DNA with foreign patterns , making the strain inviable or resulting in poor MTase expression [42] , [43] . Therefore , an E . coli strain lacking all of the known R-M systems and orphan MTases was generated with MTases expressed . The plasmids prepared from this host could escape the REases that recognize unmethylated DNA or DNA methylated in foreign patterns ( lower right panel in Figure S9 ) . The MoDMP concept could greatly improve genetic transformation efficiency . Recently , four REases from the B . cereus ATCC 10987 strain have been cloned and characterized , namely BceSI , BceSII , BceSIII and BceSIV [15] . Only faint and non-specific hybridization blots were observed using the antibodies against m6A and m5C for the MTase of BceSI ( BCE_1018 ) in this study; these faint blots may be caused by the vagaries of dot blot approaches . It might also be that BCE_1018 modifies the DNA in a way other than methylation , such as hydroxymethylation or glucosyl-hydroxymethylation . BCE_1018 was not included in the downstream MoDMP application . Nevertheless , the highest transformation efficiency was achieved using the plasmids modified by six other MTases and was within the acceptable range for gene knock-out experiments ( 107 CFU/µg DNA ) . This efficiency may be caused by the low abundance and the weak REase activity of BceSI in strain B . cereus ATCC 10987 , as described by Hegna et al . [23] . BceSI was induced only when the strain B . cereus ATCC 10987 was grown in the presence of exogenous DNA . Nham_3845 ( NhaXI ) has been reported to be a fused enzyme harboring both restriction and modification subunits , but the m6A or m4C modification activity was not detected [44]; in this study the MTase activity was not detected either . It might be that Nham_3845 modified DNA in ways other than methylation , which could not be detected using immunoblot assays . The contribution of individual MTases to genetic transformation was not evaluated in this study because a shuttle plasmid containing all of the MTase recognition sequences cannot be defined . A MTase that does not modify one particular plasmid might be useful when other plasmids are to be used . Therefore , to make a universal system for all plasmids , all of the identified active MTases were employed for MoDMP . The orphan MTase BAMTA208_06715 , which lacks a counterpart REase , was also used in the MoDMP pipeline of B . amyloliquefaciens TA208 . Orphan MTases , such as CcrM , may participate in methylation-directed DNA mismatch repair [45] . Methylated DNA could potentially escape inspection from the host mismatch repair machinery and eventually exhibit an elevated transformation performance , hence the use of BAMTA208_06715 in the MoDMP pipeline . The use of DNA mimic protein Ocr ( overcome classical restriction ) alongside the plasmid ( TypeOne Restriction Inhibitor , Epicentre; [46] ) which specifically inhibits Type I REase activity , also enhances transformation efficiency in bacterial species [47] . Combination of this method with the MoDMP pipeline could further elevate transformation performance in strains which are difficult to transform . Recently , a novel R-M system has been shown to phosphorothioate DNA , preventing the degradation of the DNA by its REase counterparts [48] . The MoDMP concept may also be adapted to those bacteria restricting unphosphorothioated DNA . In conclusion , we devised a system in E . coli that mimics the DNA methylation patterns of bacterial strains harboring multiple R-M systems . Eventually , the R-M barrier of three represented bacterial strains were overcome , including Gram positive , Gram negative , chemoheterotrophs and chemoautotrophs . The adaptability of this pipeline to different bacterial groups suggests a universal potential . This protocol is very fast; a MoDMP plasmid can be generated in less than one week using the S . cerevisiae assembler , if the MTase activity assay step is omitted and the putative MTases are cloned and expressed directly . We expect that the pipeline will be applicable to other strains of known genome sequence that are resistant to genetic transformation .
The strains E . coli TOP10 and EC135 were used for the cloning and expression of the MTases . S . cerevisiae DAY414 was used for in vivo assembly of the MTase genes . The plasmid pBAD43 was used for the cloning and expression of individual MTases , and pWYE724 was used for co-expression of multiple MTases . Several E . coli-Bacillus shuttle plasmids were used for MoDMP procedure evaluation purposes in the B . amyloliquefaciens TA208 and B . cereus ATCC 10987 strains . Inactivation of upp in B . amyloliquefaciens TA208 was performed with pWYE748 . Expression of the GFP variant gfpmut3a in N . hamburgensis was carried out using pBBR1-MCS5 . The strains and plasmids used in this study are listed in Table S1 . Putative MTase encoding genes were retrieved from the REBASE database [5] . Genes were PCR amplified and ligated into pBAD43 . Individual genes that encode the methylation and specificity subunits of BCE_0839–BCE_0842 system were joined to operons using Splicing by Overlapping Extension ( SOE ) PCR . All recombinant plasmids were verified by sequencing before use . The E . coli EC135 strain was transformed with pBAD43 plasmids encoding MTase genes . Single colonies were used to inoculate LB medium and cultured until an OD600 reading of 0 . 2 was reached , and then arabinose was added to a final concentration of 0 . 2% to induce MTase expression . Expression was induced overnight at 30°C . The DNA methylation activity of the putative MTases was analyzed using a southwestern dot blot assay as described previously [18] . Total genomic DNA from the E . coli EC135 strains expressing individual or multiple MTases was prepared using a DNeasy Blood and Tissue Kit ( Qiagen ) . DNA concentrations were determined using a Nanodrop 2000C spectrophotometer ( Thermo Scientific ) . The DNA was then denatured at 100°C for 3 min and immediately cold shocked in an ice-water bath . Samples were spotted onto Protran BA85 nitrocellulose membrane ( Whatman ) and fixed by UV cross-linking . The membrane was blocked in 5% non-fat milk and incubated with rabbit antisera against DNA containing m6A at a dilution of 1∶10 , 000 ( New England Biolabs ) , rabbit antisera against m4C at a dilution of 1∶10 , 000 ( New England Biolabs ) , or a mouse monoclonal antibody against m5C diluted 1∶20 , 000 ( Zymo Research ) . After washing , the membrane was incubated with secondary goat anti-rabbit or anti-mouse antibodies conjugated with horseradish peroxidase ( HRP ) ( Jackson ImmunoResearch ) at a dilution of 1∶10 , 000 . The blots were visualized using the ECL prime Western blotting detection reagent ( GE Healthcare ) , and DNA methylation signals were exposed to Kodak X-Ray film . For quantification of the hybridization signals , the films were scanned and the gray scale of the spots was quantified using Quantity One ( Bio-Rad ) . After normalization , the values were plotted as bar charts . To obtain the nucleoside samples of genomic DNA for LC-MS analysis , 30 µg of DNA prepared from the E . coli EC135 strain or strains expressing MTases were digested to deoxynucleosides with 50 U of DNA Degradase Plus ( Zymo Research ) ; the digestion was carried out in 100 µL volume at 37°C for 18 h . The m6dA standard was purchased from Santa Cruz Biotechnology . The characterization of m6dA was performed on an Agilent 6520 Accurate-Mass QTOF LC/MS system ( Agilent Technologies ) equipped with an electrospray ionization ( ESI ) source . 30 µL of the samples were injected to the Agilent 1200 HPLC using an Agilent Zorbax Extend-C18 1 . 8 µm 2 . 1×50 mm column with the column temperature kept at 35°C . Water with 0 . 1% formic acid and methanol were used as mobile phases A and B , respectively , with a flow rate of 0 . 2 mL/min . The following gradient was used: 0% B for 3 . 0 min , increase to 60% B in 4 . 5 min , 60–95% B over 2 . 5 min , 95% B for 5 min , and then decreased to 0% B over 0 . 5 min prior to re-stabilization of 14 . 5 min before the next injection . The MS data were collected in positive ionization mode with nitrogen supplied as the nebulizing and drying gas . The temperature of the drying gas was set at 300°C . The flow rate of the drying gas and the pressure of the nebulizer were 600 L/h and 25 psi , respectively . The fragmentor and capillary voltages were kept at 90 and 3 , 500 V , respectively . Full-scan spectra were acquired over a scan range of m/z 80–1000 at 1 . 03 spectra/s . Multiple MTase genes were rapidly assembled by taking advantage of the high DNA recombination activity in S . cerevisiae [49] . The CEN6 replicon was added to pBAD43 followed by TRP1 allele from pDDB78 at the ClaI site to yield pWYE724; the addition of these elements enables replication and screening in S . cerevisiae . The active MTase genes were amplified using PCR primers that contained 50 bp of overlapping sequence to the adjacent gene from their corresponding pBAD43 plasmids . S . cerevisiae DAY414 was transformed with the DNA fragments encoding the active MTases from the individual bacterial strains and the pWYE724 plasmid linearized at the EcoRI and SalI loci . S . cerevisiae DAY414 was then selected for tryptophan autotrophy on synthetic complete ( SC ) medium lacking tryptophan . S . cerevisiae transformation was performed using the lithium acetate method [50] . Plasmids were rescued into E . coli TOP10 cells as described by Robzyk et al [51] . All recombinant plasmids were verified by restriction digestion and DNA sequencing before subsequent use . The plasmids carrying multiple MTase genes from B . amyloliquefaciens TA208 , B . cereus ATCC 10987 and N . hamburgensis X14 were named pM . Bam , pM . Bce and pM . Nham , respectively . The homologous DNA sequences flanking the upp gene of B . amyloliquefaciens TA208 ( 641 bp upstream and 669 bp downstream ) and the chloramphenicol resistance gene of pMK4 were amplified and joined using SOE-PCR . This cassette was ligated into the pMD19-T vector ( Takara ) and verified by DNA sequencing . The resulting plasmid was named pWYE748 . A 216 bp promoter region of the Nham_3450 gene was PCR amplified from the genome of the N . hamburgensis X14 strain and joined to gfpmut3a by SOE-PCR . The resulting GFP expression cassette was ligated into pBBR1-MCS5 at the SalI and PstI sites to yield pWYE561 . Various shuttle and integrative plasmids were transformed into the E . coli EC135 strains carrying MTase encoding genes . MTase expression was then induced by incubation with 0 . 2% arabinose at 30°C to allow the in vivo methylation of these plasmids . Transformation of B . cereus ATCC 10987 was carried out as described previously with the following modifications [24] . The B . cereus ATCC 10987 strain was cultured in LB medium until the culture reached an OD600 of 0 . 2 and was then incubated on ice for 10 min . Cells were harvested by centrifugation at 8 , 000 g at 4°C for 10 min . After washing four times with ice-cold transformation buffer ( 10% sucrose , 15% glycerol , 1 mM Tris-HCl , pH 8 . 0 ) , the electro-competent cells were resuspended in 1/125 volume of the original culture . The cells ( 90 µL ) were mixed with 100 ng of the column-purified plasmids and loaded into a pre-chilled 1 mm gap cuvette . After a brief incubation on ice , the cells were shocked with a 2 . 1 kV pulse generated by a BTX ECM399 electroporator ( Harvard Apparatus ) . The cells were immediately diluted with 1 mL NCMLB medium ( 17 . 4 g/L K2HPO4 , 11 . 6 g/L NaCl , 5 g/L glucose , 10 g/L tryptone ( Oxoid ) , 5 g/L yeast extract ( Oxoid ) , 0 . 3 g/L trisodium citrate , 0 . 05 g/L MgSO4·7H2O , 69 . 2 g/L mannitol and 91 . 1 g/L sorbitol , pH 7 . 2 ) and incubated at 37°C for 3 h to allow the expression of the antibiotic resistance genes . Aliquots of the recovery mix were spread onto LB plates supplemented with 5 µg/mL chloramphenicol or 10 µg/mL kanamycin and cultured overnight at 37°C . Electroporation of B . amyloliquefaciens TA208 was performed using the combined cell-wall weakening and cell-membrane fluidity disturbing procedure described previously [17] . The N . hamburgensis X14 strain was grown in DSMZ 756a medium ( 1 . 5 g/L yeast extract , 1 . 5 g/L peptone ( BD Biosciences ) , 2 g/L NaNO2 , 0 . 55 g/L sodium pyruvate , 1 mL/L trace element solution ( 33 . 8 mg/L MnSO4⋅H2O , 49 . 4 mg/L H3BO3 , 43 . 1 mg/L ZnSO4⋅7H2O , 37 . 1 mg/L ( NH4 ) 6Mo7O24 , 97 . 3 mg/L FeSO4⋅7H2O and 25 mg/L CuSO4⋅5H2O ) and 100 mL/L stock solution ( 0 . 07 g/L CaCO3 , 5 g/L NaCl , 0 . 5 g/L MgSO4⋅7H2O , 1 . 5 g/L KH2PO4 ) , pH 7 . 4 ) at 28°C in the dark until reaching an OD600 of 0 . 1 . The cells were then harvested by centrifugation at 8000 g at 4°C for 10 min and washed four times with ice-cold 10% glycerol . The cells were resuspended in 10% glycerol at a 1 , 000-fold greater concentration compared to that of the original culture volume . The cell suspension ( 90 µL ) was mixed with 150 ng of the pWYE561 plasmid and electroporated with an ECM399 electroporator at 1 . 2 kV . The cells were washed into 100 mL 756a medium and recovered at 28°C with gentle shaking for one day . The bacteria were then grown in the presence of 20 µg/mL gentamycin for one day . The bacterial culture was used at a ratio of 1∶100 to inoculate fresh 756a medium containing antibiotics and was shaken at 180 rpm at 28°C . After about three weeks , the culture became turbid . The bacterial culture was subcultured once more to enrich for transformed cells and took one week to reach an OD600 of 0 . 1 . The culture was tested for contamination microscopically and by streaking the culture onto LB plates . Successful transformation of strain X14 was verified by plasmid preparation using the Plasmid Mini Kit ( OMEGA Bio-tek ) , PCR amplification of gfpmut3a and plasmid rescue . Expression of GFP was observed using a Leica TCS SP2 confocal laser scanning microscope ( Leica Microsystems ) , and the ratio of fluorescent cells was determined using a BD FACS Calibur flow cytometer ( BD Biosciences ) . The pWYE748 plasmid was transformed into the E . coli EC135 strain harboring pM . Bam . After induction of MTase expression , 1 µg of the pWYE748 plasmid was transferred to B . amyloliquefaciens TA208 , and the cells were selected for chloramphenicol resistance . Positive clones were verified by PCR and sequencing using primers ( WB605 and WB606 ) specific to the flanking sequences of the homologous arms . The upp knock-out strain B . amyloliquefaciens BS043 was validated by growth on MM plates supplemented with 10 µM 5-FU [26] and 100 mg/L adenosine . All of the PCR primers used in this study are listed in Table S2 . The modified plasmid DNA was challenged by the cognate REases to determine the modification sequences of the cloned MTases . To facilitate the identification , the high-copy plasmid pMK4 was transformed to E . coli EC135 harboring individual or multiple MTase genes , and in vivo methylated pMK4 plasmids were prepared and challenged by the cognate REases after linearization by REases that have sole cutting sites in pMK4 ( NcoI , EcoRI , SpeI or BamHI ) . The pMK4 plasmids prepared from E . coli EC135 , and the plasmids from B . amyloliquefaciens TA208 or B . cereus ATCC 10987 was used as the negative and positive controls in the experiments of individual MTase and multiple MTases , respectively . The plasmids pWYE690 and pHCMC02 were tested for their resistance to BclI cleavage conferred by BAMTA208_6525 when it was expressed individually and co-expressed due to the lack of BclI site in pMK4 . For the same reason , pWYE699 and pHCMC05 were used in testing the protection conferred by BCE_0393 from BssHII cleavage . Since the broad-host-range plasmid derivative pWYE561 showed a low copy number in E . coli , pMK4 was also used in identification of the modification sites of the MTases from strain N . hamburgensis X14 . Genomic DNA of the strain was used as a control for co-expressed MTases . | Approximately 95% of the genome-sequenced bacteria harbor Restriction-Modification ( R-M ) systems . R-M systems usually occur in pairs , i . e . , DNA methyltransferases ( MTases ) and restriction endonucleases ( REases ) . REases can degrade invading DNA to protect the cell from infection by phages . This protecting machinery has also become the barrier for experimental genetic manipulation , because the newly introduced DNA would be degraded by the REases of the transformed bacteria . In this study we have developed a pipeline to protect DNA by methylation from cleavage by host REases . Multiple DNA MTases were cloned from three difficult-to-transform bacterial strains and co-expressed in an E . coli strain lacking all of the known endogenous R-M systems and orphan MTases . Thus , the DNA methylation patterns of these strains have become similar to that of the difficult-to-transform strains . Ultimately , the DNA prepared from these E . coli strains can overcome the R-M barrier of the bacterial strains that are difficult to transform and achieve genetic manipulation . The effectiveness of this pipeline in different bacterial groups suggests a universal potential . This pipeline could facilitate functional genomics of bacterial strains that are difficult to transform . | [
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"mo... | 2012 | A Mimicking-of-DNA-Methylation-Patterns Pipeline for Overcoming the Restriction Barrier of Bacteria |
Auxin controls a myriad of plant developmental processes and plant response to environmental conditions . Precise trafficking of auxin transporters is essential for auxin homeostasis in plants . Here , we report characterization of Arabidopsis CTL1 , which controls seedling growth and apical hook development by regulating intracellular trafficking of PIN-type auxin transporters . The CTL1 gene encodes a choline transporter-like protein with an expression pattern highly correlated with auxin distribution and is enriched in shoot and root apical meristems , lateral root primordia , the vascular system , and the concave side of the apical hook . The choline transporter-like 1 ( CTL1 ) protein is localized to the trans-Golgi network ( TGN ) , prevacuolar compartment ( PVC ) , and plasma membrane ( PM ) . Disruption of CTL1 gene expression alters the trafficking of 2 auxin efflux transporters—Arabidopsis PM-located auxin efflux transporter PIN-formed 1 ( PIN1 ) and Arabidopsis PM-located auxin efflux transporter PIN-formed 3 ( PIN3 ) —to the PM , thereby affecting auxin distribution and plant growth and development . We further found that phospholipids , sphingolipids , and other membrane lipids were significantly altered in the ctl1 mutant , linking CTL1 function to lipid homeostasis . We propose that CTL1 regulates protein sorting from the TGN to the PM through its function in lipid homeostasis .
Dynamic endomembrane trafficking delivers proteins and other cargo molecules to a variety of organelles and thus controls almost all aspects of plant development and physiology , including gravitropism , epidermis differentiation , guard cell movement , cell wall remodeling , defense against pathogens , and hormone signaling [1] . In this context , exocytosis and endocytosis determine the abundance and dynamics of signaling receptors and transporters at the plasma membrane ( PM ) , which in turn afford cells the ability to respond to extracellular stimuli . For example , PM-located auxin transporters PIN-formed ( PINs ) and AUXIN RESISTANT 1 ( AUX1 ) have been shown to continuously cycle between PM and endosomal compartments , resulting in dynamic changes in localization and abundance at the PM , where they function to control auxin gradients between cells . Many components have been shown to affect the trafficking and PM abundance of auxin transporters . These include the nucleotide exchange factor for ADP-ribosylation-factor-type GTPases ( ARF-GEFs ) [2–4] , retromer proteins [5] , adaptor protein complex 3 ( AP-3 ) [6 , 7] , endosomal sorting complexes [8 , 9] , the trans-Golgi network/early endosome ( TGN/EE ) protein ECHIDNA [10] , and several protein kinases [11–13] . The trafficking regulators safeguard the polarity and dynamics of auxin transporters , making possible the spatiotemporal variations in auxin distribution that act as an instructive signal for a wide variety of cellular events , ranging from polarity establishment during the earliest phases of plant embryogenesis to other morphogenetic events , including root development and the formation of the apical hook during seedling development [2–5 , 10–14] . Because of the dynamics of these auxin transporters in the endomembrane system , they can be used as cargo proteins to study the regulation of the membrane trafficking process in cell biology . In genetic analysis , the mutations in genes encoding these transporters are often trackable because the mutants often show severe phenotypic changes in plant growth and development . In a screen for mutants defective in phloem development , Dettmer et al . [15] identified choline transporter-like 1 ( CTL1 ) to be essential for sieve tube formation and thus overall plant development . The CTL1 gene encodes a protein with multiple transmembrane domains that has been shown to mediate choline transport [15] . However , the cellular mechanism for CTL1 function in plant development remains unknown . In tracking down the mechanism of CTL1 function , we discovered that CTL1 is closely associated with auxin signaling in the control of plant developmental processes . We further found that disruption of CTL1 function impaired endomembrane trafficking of several auxin transporters and probably some other unidentified cargo proteins as well . CTL1 acts at both the secretory vesicles ( SVs ) and the clathrin-coated vesicles ( CCVs ) of the TGN to regulate the trafficking of PIN1 and PIN3 , which may explain the phenotypes of the ctl1 mutant in seedling growth and apical hook development . As a choline transporter , CTL1 plays a crucial role in the homeostasis of membrane lipids , including phospholipids and sphingolipids . As lipid compositions of cell membranes influence vesicular transport , CTL1 function provides the mechanistic link between choline transport , lipid remodeling , and vesicular trafficking of PM proteins . We conclude that CTL1 is a previously unrecognized regulator of endomembrane trafficking in plants .
A significant portion of plant genomes encode proteins with multiple transmembrane domains that may function as transporters . However , a large majority of these open reading frames ( ORFs ) are designated as “proteins of unknown function . ” We took a comprehensive reverse genetic approach to identify the function of these proteins by screening Arabidopsis SALK transfer deoxyribonucleic acid ( T-DNA ) insertion lines disrupting the expression of corresponding genes . One of the lines , SALK_065853C in Columbia-0 ( Col-0 ) background , was recovered for its severely stunted growth phenotype . This line contains a T-DNA insertion in the At3g15380 gene , previously named CHOLINE-TRANSPORTER-LIKE 1 ( CTL1 ) for its biochemical function as a choline transporter and its function in sieve tube formation [15] . The insertion in CTL1 occurred in the first intron ( 281 bp from the start codon ) to generate a transcriptional knockout ( S1A–S1C Fig ) . We backcrossed the ctl1 mutant with the wild type for 2 generations to segregate other possible T-DNA insertions and found that the isolated homozygous ctl1 mutant lacking other insertions consistently showed the typical ctl1 phenotype observed with the original SALK line . We further confirmed that the phenotype of the ctl1 mutant resulted from lack of CTL1 function by complementation using a genomic fragment of the CTL1 gene and a CTL1- enhanced green fluorescent protein ( EGFP ) fusion construct driven by the CTL1 promoter , respectively ( S1D Fig and S2A Fig ) . The transgenic plants expressing CTL1 genomic fragment or CTL1-EGFP fusion protein in the ctl1 mutant background displayed a similar growth phenotype to that of the wild-type plants ( Fig 1A , S1E Fig and S2D Fig ) , supporting the conclusion that disruption of the CTL1 gene rendered the dwarf phenotype of the mutant plants . We examined the ctl1 phenotype in detail and found that 30-day-old ctl1 seedlings grown in the soil displayed smaller , round , and dark green epinastic leaves with short petioles ( Fig 1A and 1B and S1F–S1H Fig ) and that 2-month-old adult ctl1 mutants exhibited a dwarfed phenotype ( Fig 1C ) . To examine root growth , we planted seeds on half-strength Murashige and Skoog ( MS ) agar medium and found that 5-day-old ctl1 seedlings had shorter roots as compared to the wild type ( Fig 1D and 1E ) , consistent with previous observations [15] . We further examined the cell size in both wild-type and mutant plants and found that the stunted growth phenotype in the ctl1 mutant resulted from a defect in cell elongation . To determine cell size , we expressed AUX1-GFP in wild-type , ctl1 , and complemented lines ( ctl1C ) so that the cell periphery lit up with the GFP for confocal imaging . The images collected from confocal laser scanning microscopy revealed that the size of leaf epidermal cells in ctl1 was smaller than that of those in the wild type and ctl1C ( Fig 1F–1H ) . Typically , the cell size in the ctl1 mutant plants was only 49% of the wild type ( S1 Table ) . As hypocotyl cells elongate quickly without cell division , hypocotyls grown in the dark are excellent models for examining cell elongation [16] . We thus analyzed the hypocotyl length of etiolated seedlings and found that the hypocotyls of ctl1 mutant seedlings elongated more slowly compared with the wild type and ctl1C ( Fig 1I and 1J ) . Moreover , the epidermal cell length of ctl1 hypocotyls was only about half of that of the wild type ( Fig 1K ) . Taken together , these results demonstrate that CTL1 is an essential regulator of cell elongation in Arabidopsis . This finding explains an overall dwarf phenotype of the ctl1 mutant seedlings beyond the defect in phloem development observed earlier [15] . To further study the cellular mechanism of CTL1 function , we determined the subcellular localization of CTL1 in root cortex cells of Arabidopsis seedlings by using a CTL1-EGFP transgenic line in the ctl1 mutant background . Real-time quantitative reverse transcription PCR ( qRT-PCR ) assay showed that this transgenic line had levels of CTL1 transcript that were similar to those in the wild-type plants ( S2B Fig ) . Furthermore , the CTL1-EGFP construct in this transgenic line complemented the dwarfed phenotype of the ctl1 mutant ( S2D Fig ) , indicating that this line expressed functional CTL1-EGFP fusion proteins in the same compartments as the native CTL1 protein . Therefore , we used this line to track down the subcellular location of CTL1-EGFP protein using confocal microscopy . The fluorescence signal generated by CTL1-EGFP fusion appeared at the PM and also displayed a punctate pattern in the cytosol ( Fig 2A and S2E Fig ) . To identify intracellular punctate structures at which CTL1-EGFP is localized , we crossed this CTL1-EGFP transgenic line with the transgenic lines that stably express fluorescent markers for several organelles . We found that most of the punctate signals of CTL1-EGFP colocalized with vacuolar proton ATPase subunit VHA-a isoform 1 monomer red fluorescent protein ( VHA-a1-mRFP ) ( Fig 2B ) , a TGN/EE marker [17] . The linear Pearson correlation coefficient ( rp ) for the colocalization was 0 . 87 ( Fig 2I ) . We did not observe colocalization of CTL1-EGFP fluorescence signals with Syntaxin of plants 32 ( SYP32 ) -mCherry ( rp = 0 ) ( Fig 2C and 2J ) , the Golgi apparatus marker [18] . In addition , some CTL1-EGFP fluorescence signals overlapped with those of Arabidopsis Rab homolog F2A ( Rha1 ) -mCherry ( rp = 0 . 16 ) ( Fig 2D and 2K ) , the PVC marker [18] . We conducted more experiments to further examine the subcellular localization of CTL1 . First , we stained root tips with FM4-64 for a short time to label the PM [19] and found that the CTL1-EGFP fluorescence colocalized with the FM4-64 signal ( Fig 2E ) . Secondly , we treated root tips with fungal toxin brefeldin A ( BFA ) , which blocks trafficking from the TGN to the PM , leading to the formation of enlarged endosomal compartments referred to as BFA bodies [20] . We detected both CTL1-EGFP and VHA-a1-mRFP fluorescence in the BFA bodies ( Fig 2F ) . However , the CTL1-EGFP and SYP32-mCherry signals did not overlap in the presence of BFA ( Fig 2G ) . Finally , we treated root tips with wortmannin ( Wm ) , a drug that preferentially triggers the swelling of PVC but has little effect on the morphology of the Golgi apparatus and the TGN/EE [21] . After 1 hour of treatment with 33 μM Wm , the morphology of some organelles labeled by CTL1-EGFP became swollen and showed a PVC-specific ring-like structure ( Fig 2H ) , indicating that CTL1 is also sorted to the PVC . We also quantified the colocalization of CTL1-EGFP with various organelle markers in root tip cells of 4-day-old seedlings . This analysis revealed a large proportion ( 78% ± 4 . 6% ) of colocalization between CTL1-EGFP and the TGN marker VHA-a1-mRFP , a smaller proportion ( 19% ± 2 . 6% ) of colocalization between CTL1-EGFP and the PVC marker Rha1-mCherry , and no colocalization with SYP32-mCherry ( Fig 2L ) . The TGN is subdivided into 2 structure forms , SVs and CCVs [22] . We also detected that CTL1-EGFP colocalizes with mCherry-clathrin light chain 2 ( CLC2 ) ( S3 Fig ) . As VHA-a1 and CLC2 reside in the SVs and the CCVs , respectively [22] , colocalization with both VHA-a1-mRFP and mCherry-CLC2 illustrated that CTL1 is localized to both subdomains of the TGN . We used the CTL1-EGFP transgenic line to study the expression pattern of CTL1 , since the expression of CTL1-EGFP was driven by the CTL1 promoter region ( S2 Fig ) . The GFP fluorescence was ubiquitously distributed in the meristem and elongation zones but restricted to vascular tissues in the mature zone of roots ( Fig 3A ) . Cross sections through the root meristem zone displayed the distribution of CTL1-EGFP signal in all cell layers ( Fig 3B and 3C ) . Furthermore , GFP was also highly expressed in the newly initiated lateral roots ( Fig 3D and 3E ) . In dark-grown seedlings , CTL1 was expressed in the whole cotyledon with enrichment at the blade tips , the vasculature of the hypocotyl , and the concave side of the apical hook ( Fig 3F ) . When grown on the half-strength MS medium under dark conditions , Arabidopsis apical hook development proceeds through 3 phases: the hook formation phase , the maintenance phase , and the opening phase [10 , 23 , 24] . CTL1-EGFP signals appeared at both the convex and the concave sides of the hook , with the maximum in the concave side ( S4G and S4H Fig ) , and the expression at the concave side gradually disappeared during the opening phase ( S4A–S4F and S4J Fig ) , suggesting that CTL1 function may be associated with apical hook development . To further confirm the expression pattern of CTL1 , we generated transgenic plants harboring the CTL1pro:CTL1:GUS construct in which the EGFP reporter was replaced by the β-glucuronidase ( GUS ) reporter . In the apical hook region , CTL1-GUS shows the same expression pattern as the CTL1-EGFP in the concave side of the apical hook ( S4I Fig ) . In the roots of 5-day-old seedlings , GUS activity was detected in the similar tissues labeled by EGFP signals ( Fig 3G–3J ) . In shoots of 7-day-old seedlings , the expression pattern of CTL1 was ubiquitous , but a relatively higher level of GUS activity was detected in the apical meristem , at the tips of cotyledon and true leaves , and in vascular tissues ( Fig 3K–3N ) , largely overlapping with the GFP signals detected earlier ( Fig 3F ) . Phenotypic analyses of the ctl1 mutant in detail provided insights into CTL1 function in growth and development . The ctl1 mutant showed reduced primary root growth , whereas the lateral roots reached approximately the same length as the primary root , apparently resulting from lack of apical dominance [15] . In addition , we found that the ctl1 showed a severe defect in apical hook development , consistent with high levels of expression of CTL1 in the apical hook ( Fig 3F and S4 Fig ) . In particular , etiolated ctl1 seedlings never formed the fully closed apical hook , and the hook quickly opened without an apparent maintenance phase ( Fig 4A and 4B ) . ctl1 defects in cell elongation ( described earlier ) and defects in primary and lateral root growth all point to relevance with the auxin response . Furthermore , apical hook development is the result of differential cell elongation mediated by uneven auxin distribution [23] . These auxin-related phenotypes of ctl1 prompted us to investigate the connections between CTL1 and auxin . We went on exploring whether there are other auxin-related phenotypes altered in the ctl1 mutant . One process we studied was phototropism , a well-characterized light response mediated by asymmetric auxin distribution in plants [4] . As shown in Fig 4 , ctl1 had a reduced hypocotyl phototropic response to unilateral light as compared with the wild type and the complemented line ( Fig 4C and 4D ) . In addition , we also found that ctl1 seedlings were less sensitive to high levels of 1-naphthylacetic acid ( NAA ) that inhibit root elongation . Compared to the wild type , ctl1 roots were resistant to auxin inhibition over a range of auxin concentrations ( 0 , 0 . 1 , and 0 . 3 μM ) ( Fig 4E and 4F ) . We also tested the sensitivity to salicylic acid ( SA ) and found that both the wild type ( WT ) and the ctl1 mutant were sensitive to SA ( S5 Fig ) , unlike the situation with auxin . All these findings support the hypothesis that CTL1 is involved in auxin-related processes . To study auxin distribution in the ctl1 mutant , we crossed it with a transgenic line harboring DR5::GUS , a reporter of auxin levels [5] . In the ctl1 mutant background , the DIRECT REPEAT5 ( DR5 ) -driven GUS expression was greatly enhanced in the cotyledons , especially at the tips , but was dramatically reduced in the vascular tissues of the hypocotyls and roots , as compared to the pattern of DR5::GUS in the WT background ( Fig 5A–5H and S6A Fig ) . In the roots , the DR5::GFP signal in the WT and the ctl1 mutant showed a similar distribution pattern , with a condensed signal in the primary root tips . However , after being treated with NAA ( 0 . 1 , 0 . 3 , 0 . 5 , and 1 μM ) for 12 hours , the DR5::GFP signal was enhanced in the meristem and elongation zones of WT roots with increasing NAA concentrations , but the level of this response was reduced in ctl1 , suggesting reduced transport or reduced response of auxin ( Fig 5I and S6B Fig ) . Moreover , a maximum DR5::GFP signal was detected in the concave side of the apical hooks of the WT , but this was largely diminished in the mutant ( Fig 5J and S6C Fig ) . We showed that disruption of CTL1 function appears to affect auxin transport and distribution ( Figs 4 and 5 ) . Together with the finding of CTL1 subcellular localization to the PM and endomembranes ( Fig 2 ) , we speculated that CTL1 may regulate the trafficking of PM-localized proteins so that distribution of auxin transporters may be altered in the ctl1 mutant . In order to test this hypothesis , we examined the expression and localization of several auxin transporters in the ctl1 mutant by using auxin transporter-GFP markers . We crossed the ctl1 mutant with transgenic lines containing PIN1pro:PIN1:GFP , PIN2pro:PIN2:GFP , PIN3pro:PIN3:GFP , AUX1pro:AUX1:GFP , or LAX3pro:LAX3:GFP and monitored the GFP signals by confocal microscopy . We found a dramatically reduced accumulation of PIN1-GFP and PIN3-GFP in the ctl1 mutant as compared to the WT . More specifically , the abundance of PIN1-GFP in the mutant was about half ( 56% ± 14 . 2% ) of the WT , and for PIN3 it was only a quarter ( 26% ± 19 . 3% ) of the WT ( Fig 6A , 6C and 6F ) . However , other auxin transporters , including PIN2 , AUX1 , and Like AUX1 protein 3 ( LAX3 ) , were not affected by the CTL1 mutation ( Fig 6B and 6D–6F ) . We also found that the brassinosteroid receptor BRI1 showed no difference in the WT and the ctl1 mutant ( S8 Fig ) . Because PIN-mediated auxin efflux also plays a major role during apical hook development [24 , 25] , we also examined GFP signal in the apical hook and again found reduced levels of PIN1-GFP and PIN3-GFP , but not of AUX1-GFP , in the ctl1 mutant as compared to the WT ( S7 Fig ) . The loss of PIN3 can cause an enhanced DR5 signal in the cotyledons of Arabidopsis [25] . As we also detected an enhanced DR5 signal in the cotyledons of ctl1 mutant , we proposed that reduced abundance of PIN1 and PIN3 may lead to changed auxin transport and distribution ( shown by DR5::GUS/GFP lines earlier ) that in turn causes changes in auxin-related phenotypes in the ctl1 mutant . To determine whether the reduced abundance of PIN1 and PIN3 proteins in the ctl1 mutant results from a decrease in the transcript level , we examined the RNA levels of auxin transporter genes in the WT and the ctl1 mutant . The qRT-PCR analysis showed that the mRNA levels of PIN1 and PIN3 in ctl1 were slightly higher than those in the WT ( S9 Fig ) , suggesting that down-regulation of PIN1 and PIN3 proteins in ctl1 occurs at the post-transcriptional level . The reduced abundance of PIN1 and PIN3 in the ctl1 mutant , together with CTL1 localization to the TGN , suggests that CTL1 protein may affect the recruitment of PINs from the TGN to the PM . In the study of protein trafficking , BFA is often used to block protein sorting from the TGN to the PM and to induce protein internalization from the PM to the TGN . Thus , BFA treatment of cells results in the formation of large endosomes called BFA bodies that contain PM-destined proteins . These BFA bodies are rapidly disintegrated , and the proteins are targeted back to the PM again after BFA washout [26–28] . Therefore , BFA washout has been widely used to measure the speed of trafficking from the TGN back to the PM [26–29] . We analyzed the trafficking of PIN1-GFP and PIN3-GFP using a similar approach . Upon treatment of WT and ctl1 roots with 50 μM BFA for 60 minutes , similar percentages of cells with BFA bodies were detected in the WT and the ctl1 mutant ( Fig 7A , 7B and 7I ) . However , after BFA washout for 90 minutes , we detected 9 . 7% and 21 . 6% of root cells containing PIN1-GFP-decorated BFA bodies in the WT and ctl1 , respectively ( Fig 7C , 7D and 7I ) . Similarly , about 7 . 6% and 23 . 5% of cells contained PIN3-GFP-labeled BFA bodies in the WT and ctl1 , respectively ( Fig 7E–7H and 7J ) . We also did the BFA washout experiment using the PIN2-GFP/WT and PIN2-GFP/ctl1 transgenic lines and found no difference between the WT and the ctl1 mutant ( S10 Fig ) . These data indicate that loss of CTL1 causes a delay of trafficking in PIN1 and PIN3 proteins , which may in turn lead to the auxin-related developmental defects we observed in the ctl1 mutant plants . It has been reported that sphingolipids are involved in the trafficking of auxin transporters [30–32] . Choline is predominantly utilized for the synthesis of essential lipid components of the cell membranes , including sphingolipid [33] . A defect in choline transport may impair the homeostasis of these lipids , thereby affecting vesicle trafficking . To test if CTL1 functions in lipid homeostasis , we first monitored the lipid content in situ in the WT and mutant seedlings using Nile Red staining [32 , 34] . The results showed that both polar and nonpolar lipids were reduced in the apical hook region of the ctl1 mutant as compared to the WT ( S11 Fig ) . To provide a more detailed analysis of lipid content , we used ultra-performance liquid chromatography coupled with mass spectrometry ( UPLC-MS ) to survey the lipid profiles of WT and ctl1 plants . In the ctl1 mutant , the total lipids were reduced to about 84% of the WT level ( Fig 8A ) . In further analysis , we found that the glycerophospholipids ( lysophosphatidylethanolamine , phosphatidylcholine , and phosphatidylinositol ) in the ctl1 mutant were reduced ( Fig 8B ) . The content of total glycerophospholipids in ctl1 mutant was about 77% of the level in the WT ( Fig 8C ) . Although the total sphingolipid contents were similar between the WT and the ctl1 mutant ( Fig 8C ) , we found that the content of some specific types of sphingolipids were significantly altered in the ctl1 mutant ( Fig 8D ) . In particular , the abundance of sphingolipids containing very-long-acyl-chain fatty acids ( C > 18 carbons ) was altered in the ctl1 mutant ( S12 Fig ) , consistent with the earlier finding [31] that these sphingolipids are required for the targeting of specific auxin carriers to the PM . To link the sphingolipids metabolism to CTL1 function further , we used the sphingolipid synthesis inhibitor fumonisin B1 ( FB1 ) to treat the WT seedlings and found that this treatment induced apical hook defects as observed in the ctl1 mutant ( S13 Fig ) . Taken together , CTL1 , as a choline transport protein , plays a role in homeostasis of lipids , including sphingolipids . The disturbed homeostasis of sphingolipids and other lipids in ctl1 mutant may affect the delivery of PIN1 , PIN3 , and other cargos from the TGN to the PM .
Auxin is the most investigated phytohormone and plays a pivotal role in virtually every aspect of plant growth and development , and such function often depends on its differential distribution within plant tissues [35] . At the whole plant level , auxin controls organogenesis , apical dominance , lateral root emergence , apical hook development and tropism , vascular development , and many other developmental processes [23 , 36–39] . At the cellular level , auxin regulates cell elongation , cell division , and cell differentiation [40] . We showed that Arabidopsis CTL1 plays a key role in a number of auxin-regulated processes , including cell elongation , apical hook development , root morphology , and hypocotyl phototropic response to unilateral light in Arabidopsis . CTL1 expression corresponds to the auxin maxima in the shoot apical meristems , the tips of leaves , the lateral root primordia , the vascular system , and the concave side of apical hook . The dynamic changes in the CTL1 expression pattern strongly resemble the changes in auxin distribution during apical hook development [24] . Moreover , CTL1 is required for maintaining a normal pattern of DR5 expression , a marker for auxin distribution . Loss of function of CTL1 results in enhanced DR5 signals in the tips of cotyledons and reduced signals in the vascular system of hypocotyls , roots , and the concave side of the apical hook . The auxin-related phenotypes and altered auxin distribution observed in the ctl1 mutant provide insights on the cellular and physiological processes that underpin the role of CTL1 in plant development . Auxin action depends on its differential distribution in plant tissues through a process called polar auxin transport [41] . A number of PM auxin transporters , such as PINs , AUX1 , LIKE AUX1 ( LAX ) , and subfamily B of the ATP-binding cassette proteins ( ABCB ) , contribute to the influx and efflux of auxin and subsequently determine the distribution of auxin among different tissues and cells . Therefore , auxin homeostasis requires accurate subcellular targeting of these auxin transporters through secretory trafficking processes . In plant cells , the TGN is a central traffic hub responsible for protein trafficking in both biosynthetic and endocytic pathways . The endocytosed cargos from the PM were received by the TGN , and also through the TGN , biosynthetic cargos were sorted to the PM , cell wall , cell plate , PVC , tonoplast , and vacuole [42] . Protein composition and localization at the PM are regulated by exocytosis and endocytosis in response to developmental and environmental cues . Here we provide strong evidence that CTL1 is located at multiple subcellular sites associated with secretory trafficking , including the TGN , PVC , and PM . As an endosomal protein , CTL1 may contribute to the trafficking of proteins from the TGN to the PM , especially those PM-localized auxin transporters , as supported by the finding that the abundance of some PIN-type auxin transporters was reduced in the ctl1 mutant , which displays a number of auxin-related phenotypes . In particular , CTL1 is required for the efficient trafficking of PIN1 and PIN3 from the TGN to the PM . As a consequence of losing CTL1 function , the abundance of PIN1 and PIN3 is reduced , and auxin distribution is altered in the root and the apical hook . Further , the CTL1 expression pattern largely overlaps with those of PIN1 and PIN3 in roots and apical hooks [43] [44] . Loss of function of PIN1 or PIN3 causes defects in apical hook development , primary and lateral root growth , and response to unilateral light , which are also the defects found in the ctl1 mutant [4 , 45 , 46] . Together , results on expression pattern , CTL1 contribution to PIN1 and PIN3 trafficking , and similar mutant phenotypes all support the conclusion that CTL1 regulates the trafficking of PIN1 and PIN3 , thereby controlling auxin-related plant developmental processes . CTL1 has been recently identified as a choline transporter required for sieve plate development [15] , although the cellular mechanism underlying CTL1 function is not clear . Our discovery that CTL1 functions in promoting the trafficking of PIN1 and PIN3 may provide a mechanism for CTL1 function in auxin-related developmental processes , including previously described sieve plate biogenesis . In eukaryotic cells , lipid-dependent protein sorting is a major delivery mechanism for cargo proteins from the TGN to cell surface [47] . However , the mechanism by which lipids control vesicular trafficking remains unclear . As membrane lipids provide the microenvironment for protein actions , each membrane system consists of different domains with a specific composition of lipids , such as the sphingolipid-rich microdomains and lipid rafts . Recent studies also reveal various TGN subdomains with different sphingolipid and sterol compositions [48] . Choline is one of the precursors for the synthesis of membrane lipids , including phospholipids and sphingolipids . It is conceivable that CTL1 , as a choline transport protein , would play a role in choline delivery to various cell membranes and thus modulate lipid composition of multiple organelles in plant cells . The defect in the homeostasis of membrane lipids in the ctl1 mutant would cause the trafficking defects of some cargo proteins such as PIN1 and PIN3 . Although we cannot detect any differences between the WT and the ctl1 mutant on the morphology , size , and number of the compartments labelled by different fluorescence-tagged organelle markers using confocal microscopy ( S14 Fig ) , there might be other defects on the endomembrane system in ctl1 that we were not able to identify . It remains unclear whether CTL1 functions as a transporter-like protein that prefers choline over other substrates [15] . Further investigations will be required to determine whether CTL1 transports choline specifically or can also transport other substrates . CTL1 is localized to different cellular compartments , including the TGN , PM , and PVC , and its trafficking is sensitive to BFA , suggesting that CTL1 itself is a cargo protein that goes through the secretory pathway . We found that CTL1 affects the trafficking of some special cargo proteins such as PIN1 and PIN3 , but not PIN2 . This indicates that CTL1 is not required for the proper function of global trafficking machinery; instead , it affects subgroups of proteins . Further survey on the cargo proteins that are affected by CTL1 and identification of proteins that interact with CTL1 will help further understanding of the mechanisms of CTL1 function .
Arabidopsis thaliana ecotype Col-0 was used in this study . Arabidopsis WT , the T-DNA insertion line ( SALK_065853C ) , and the transgenic lines expressing SYP32-mCherry ( CS781677 ) or Rha1-mCherry ( CS781672 ) were obtained from the Arabidopsis Biological Resource Center . The transgenic lines expressing VHA-a1-mRFP [17] , DR5::GFP [49] , DR5::GUS [50] , PIN1pro:PIN1:GFP [51] , PIN2pro:PIN2:GFP [52] , PIN3pro:PIN3:GFP [52] , mCherry-CLC2 [53] , AUX1pro:AUX1:GFP [24] , and BRI1pro:BRI1:GFP [29] have been described previously . Homozygous individuals were screened by PCR using the primers described in S2 Table . The surface-sterilized Arabidopsis seeds were plated on half-strength MS medium containing 1% ( w/v ) sucrose . The pH of the medium was adjusted to 5 . 7 and solidified using 1% ( w/v ) agar . For soil culture , 7-day-old Arabidopsis seedlings grown on half-strength MS medium were transferred to nutrient-rich soil ( Pindstrup Mosebrug , Denmark ) . The seedlings were grown in a greenhouse under 150 μmol/m2/s light intensity with a 16-hour light/8-hour dark photoperiod at 22°C , unless otherwise indicated . For dark culture , the seeds were planted on half-strength MS and then transferred to white light for 6 hours to enhance germination; subsequently , the plates were wrapped with 2 layers of aluminum foil . For the unilateral light response experiment , seedlings were grown in darkness for 2 days and then exposed to unilateral white light ( 150 μmol/m2/s ) for another 2 days , according to the published procedure [54] . The seedlings were incubated in liquid half-strength MS medium containing a final concentration of 50 μM BFA ( Sigma-Aldrich ) or 33 μM wortmannin ( Sigma-Aldrich ) for 60 minutes , unless described otherwise in the figure legends . Labeling with FM4-64 ( Molecular Probes ) was carried out as described [29] . For BFA washouts , the seedlings were treated with 50 μM BFA for 1 hour , rinsed 3 times with water , and then incubated in half-strength MS liquid medium for 90 minutes before the imaging procedure . Images of individual seedlings were acquired using the OLYMPUS stereoscopic microscope equipped with a DP27 camera . The root length , hypocotyl length , and hook angle were then measured using the ImageJ software . The bending angles of the apical hook were scored as previously described [24] . For each time-lapse experiment , 6 seedlings were analyzed . For genetic complementation , a 6 , 107-bp genomic DNA fragment containing a 1 , 918-bp promoter region , a 3 , 117-bp coding region , and a 1 , 072-bp terminator region after the stop codon of the CTL1 gene were amplified from WT genomic DNA and then cloned into the binary vector pCAMBIA-1300 . To generate the CTL1pro:CTL1:EGFP construct , we fused the EGFP and NOS terminator sequence with the 5 , 032-bp genomic DNA of CTL1 , including the 1 , 918-bp promotor region and the 3 , 114-bp coding region , and then cloned this recombinant DNA into the binary vector pCAMBIA-1300 . A 10-alanine ( Ala ) linker sequence ( GCT GCT GCC GCT GCC GCT GCG GCA GCG GCC ) was also inserted between CTL1 and EGFP . To generate the CTL1pro:CTL1:GUS construct , we fused the GUS and NOS terminator sequence to the CTL1 gene as described for the CTL1pro:CTL1:EGFP construct . The organization of these 2 constructs is shown in S1D and S2A Figs , respectively . To generate the LAX3pro:LAX3:EGFP construct , a 3 , 007-bp genomic DNA of LAX3 including the promotor region and the coding region was fused with the EGFP and NOS terminator sequence and then cloned into pCAMBIA1300 . The constructs were introduced into the Agrobacterium tumefaciens GV3101 strain for transformation into Arabidopsis by the floral dipping method [55] . The primers used for plasmids constructions are listed in S2 Table . Transgenic lines expressing various markers including DR5::GFP , DR5::GUS , PIN1pro:PIN1:GFP , PIN2pro:PIN2:GFP , PIN3pro:PIN3:GFP , AUX1pro:AUX1:GFP , LAX3pro:LAX3:GFP , BRI1pro:BRI1:GFP , VHA-a1-mRFP , SYP32-mCherry , and Rha1-mCherry were individually crossed into the ctl1 mutant background . Homozygous ctl1 plants harboring various markers were isolated from F2 populations by scoring the specific phenotype of the mutant . The F3 and later generations were used for analyses . For colocalization analysis , transgenic lines expressing VHA-a1-mRFP , SYP32-mCherry , Rha1-mCherry , and mCherry-CLC2 were individually crossed with transgenic lines expressing CTL1pro:CTL1: EGFP . Imaging was performed on an LSM-710 confocal microscope ( Zeiss ) equipped with an argon/krypton laser . For the quantitative fluorescence intensity , confocal pictures were acquired using strictly identical acquisition parameters ( laser power , photomultiplier , offset , zoom factor , and resolution ) among the experimental seedlings . The excitation wave lengths for the GFP , FM4-64 , mRFP , and mCherry signals were 488 , 514 , 543 , and 587 nm , respectively . For colocalization analysis , the Colocalization Finder plugin of ImageJ was used . The linear Pearson correlation coefficient ( rp ) was used to indicate the extent of colocalization , with the value of +1 . 0 as complete colocalization . Detection of nonpolar lipids ( excitation at 514 nm , emission at 520–560 nm ) and polar lipids ( excitation at 534 nm , emission at 600–700 nm ) after Nile red staining was performed according to the published protocol [56] . The staining was conducted according to the published protocol [57] , with slight modifications . Briefly , transformed Arabidopsis seedlings were treated with 90% ( vol/vol ) acetone on ice for 30 minutes and then incubated in GUS staining solution ( 0 . 5 mM 5-bromo-4-chloro-3-indolyl-β-D-glucuronide , 100 mM Na3PO4 , 10 mM EDTA , 0 . 1 mM K3[Fe ( CN ) 6] , 5 mM K4[Fe ( CN ) 6] and 0 . 1% [vol/vol] Triton X-100 , pH 7 . 0 ) at 37°C in darkness for 12 hours . After being sufficiently decolorized with 75% ( vol/vol ) ethanol , the plant tissues were photographed with an Olympus SZX12 microscope equipped with a camera . Total RNA was extracted from plant samples using TRIzol reagent ( Invitrogen ) , followed by synthesis of Poly ( dT ) complementary DNA using the M-MLV Reverse Transcriptase ( Promega ) . qRT-PCR was performed using the SYBR Green I Master kit ( Roche Diagnostics ) according to the manufacturer’s instructions on a CFX Connect Real-Time System ( Bio-Rad ) . All individual reactions were done in triplicate . The primers used for qRT-PCR are listed in S2 Table . Plant lipids from 5-day-old WT and ctl1 mutant seedlings were extracted according to the published method [58] , and the extracts were directly subjected to LC-MS analysis . The lipidomic data were recorded on an ESI-QTOF/MS ( Xevo G2-S Q-TOF , Waters ) coupled with a UPLC ( ACQUITY UPLC I-Class system , Waters ) . Parameters for mass spectrometry were as follows: scan range , m/z 50–1 , 500; ion source , ESI; loop time , 0 . 2 seconds; cone voltages , 25 KV; capillary voltage , 3 KV; collision energy , 15–60 V; source temperature , 120°C; desolvation temperature , 400°C; desolvation gas flow , 500 L/h; and cone gas flow , 25 L/h . Raw data were imported into the commercial software Progenesis QI ( Version 2 . 3 ) for data processing , including peak picking and acquiring compounds’ associated information such as m/z , retention time , and intensity . Next , data filtering was performed to delete low-quality data . R project was also applied in further data processing and statistical analysis . | Auxin , a plant hormone , controls many aspects of plant growth and development . The precise transport and distribution of auxin hold the key to its function . A number of transport proteins are known to be involved in auxin translocation , and the PIN proteins , which are an integral part of membranes in plants , play a pivotal role in this process . Several PIN proteins are localized in the plasma membrane to mediate auxin efflux from cells , but their regulation is not well known . In this report , we analyze the role of a choline transport protein , choline transporter-like 1 ( CTL1 ) , and find that it controls the trafficking of Arabidopsis PM-located auxin efflux transporter PIN-formed 1 ( PIN1 ) and Arabidopsis PM-located auxin efflux transporter PIN-formed 3 ( PIN3 ) to the plasma membrane , thereby regulating auxin distribution during plant growth and development . In addition , we show that CTL1 has a role in lipid homeostasis in the membrane; thus , these findings provide a mechanistic link between choline transport , lipid homeostasis , and vesicle trafficking in plants . We conclude that CTL1 is a new factor in secretory protein sorting and that this finding contributes to the understanding of not only auxin distribution in plants but also protein trafficking in general . | [
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"hormones"... | 2017 | Arabidopsis choline transporter-like 1 (CTL1) regulates secretory trafficking of auxin transporters to control seedling growth |
Prion diseases are fatal neurodegenerative diseases of humans and animals characterized by gray matter spongiosis and accumulation of aggregated , misfolded , protease-resistant prion protein ( PrPres ) . PrPres can be deposited in brain in an amyloid-form and/or non-amyloid form , and is derived from host-encoded protease-sensitive PrP ( PrPsen ) , a protein normally anchored to the plasma membrane by glycosylphosphatidylinositol ( GPI ) . Previously , using heterozygous transgenic mice expressing only anchorless PrP , we found that PrP anchoring to the cell membrane was required for typical clinical scrapie . However , in the present experiments , using homozygous transgenic mice expressing two-fold more anchorless PrP , scrapie infection induced a new fatal disease with unique clinical signs and altered neuropathology , compared to non-transgenic mice expressing only anchored PrP . Brain tissue of transgenic mice had high amounts of infectivity , and histopathology showed dense amyloid PrPres plaque deposits without gray matter spongiosis . In contrast , infected non-transgenic mice had diffuse non-amyloid PrPres deposits with significant gray matter spongiosis . Brain graft studies suggested that anchored PrPsen expression was required for gray matter spongiosis during prion infection . Furthermore , electron and light microscopic studies in infected transgenic mice demonstrated several pathogenic processes not seen in typical prion disease , including cerebral amyloid angiopathy and ultrastructural alterations in perivascular neuropil . These findings were similar to certain human familial prion diseases as well as to non-prion human neurodegenerative diseases , such as Alzheimer's disease .
Transmissible spongiform encephalopathies ( TSE diseases ) or prion diseases are fatal neurodegenerative diseases of humans and animals . These diseases include scrapie in sheep , bovine spongiform encephalopathy ( BSE ) in cattle , and chronic wasting disease ( CWD ) in cervids , as well as several human diseases including kuru , Gerstmann-Sträussler-Scheinker syndrome ( GSS ) , and sporadic , familial and variant forms of Creutzfeldt-Jakob disease ( CJD ) ( see [1] for review ) . TSE diseases are transmissible within a species , but can also cross to new species in some cases . For example , variant CJD appears to be a form of BSE transmitted to humans . In addition , experimental transmission to rodents such as mice , hamsters and , more recently , bank voles [2] , [3] , has provided numerous models for laboratory research . In prion diseases brain pathology is characterized by spongiform degeneration of the gray matter together with neuronal loss and gliosis . During disease there is an accumulation in brain of an abnormal partially protease-resistant form of prion protein ( PrPres ) derived from host-encoded protease-sensitive prion protein ( PrPsen ) . PrPres can be detected by immunoblot or immunohistochemistry , and this detection is often used as an important diagnostic feature of prion disease . PrPres can be deposited in brain either as large fibrillar amyloid plaques and/or as small diffuse punctate deposits of non-amyloid aggregated protein . The diffuse non-amyloid PrPres form is prevalent in many human sCJD cases and most prion disease animal models [4]–[7] . However , both amyloid and non-amyloid forms of PrPres coexist in some human and animal prion diseases [6] [8]–[13] , and both forms may contribute to prion disease pathogenesis . A variety of proteins are capable of forming amyloid deposits in nervous system tissues as well as other organs . Amyloid deposits often displace organ structure resulting in dysfunction and cell death . In cerebral amyloid angiopathy ( CAA ) , associated with Alzheimer's disease ( AD ) and several genetic CNS amyloid diseases , vascular amyloid deposits can damage the structure of blood vessel walls leading to hemorrhage or thrombosis [14] , [15] . However , in AD , oligomeric pre-amyloid Aß aggregates are also thought to have important neuropathogenic effects . For therapy of diseases such as AD and prion diseases , where both amyloid and non-amyloid may be pathogenic , it will be important to understand the contribution of both types of abnormal protein aggregates to the various pathogenic processes present in these complex diseases . Therefore , we focused on the pathogenic effects of PrPres amyloid versus non-amyloid induced by prion infection in mice . In uninfected animals PrPsen is anchored to the plasma membrane by a glycosylphosphatidylinositol ( GPI ) moiety [16] . In prion disease PrPres is found on plasma membranes of neurons and other brain cells , where it is associated with morphological membrane changes that are common to different animal TSEs [7] [17] , [18] . Membrane attachment of PrP may have an important influence on the prion disease process . To study the role of PrP membrane linkage on pathogenesis of prion disease we previously generated 2 lines of transgenic mice ( tg44+/− and tg23+/− ) , which express PrP lacking the GPI anchor at similar levels and do not express GPI membrane–anchored PrP . Anchorless PrP in these mice is secreted by cells and is not attached to the plasma membrane [19] . After scrapie infection , both lines of transgenic mice developed high titers of prion infectivity and extensive PrPres amyloid deposits in brain at late times after infection; however , typical scrapie clinical signs and gray matter spongiosis characteristic of prion diseases were not seen [19] . In the present paper we studied homozygous anchorless PrP transgenic mice , which expressed two-fold more anchorless PrPsen than the above mentioned heterozygous transgenic mice . In these experiments scrapie infection of homozygous mice produced a fatal clinical disease . However , this disease differed in incubation period , clinical signs , and neuropathology from typical prion disease seen in non-transgenic mice , which express anchored PrP , and thus appeared to be a distinct pathogenic process . Therefore , depending on the presence or absence of anchored PrP , scrapie infection could induce two different fatal brain diseases: PrPres amyloidosis without gray matter spongiosis in anchorless PrP transgenic mice , and diffuse non-amyloid PrPres with gray matter spongiosis in mice with anchored PrP .
Since PrPsen expression is known to influence scrapie incubation period [20] [21] , it is possible that low PrP expression might account in part for the lack of clinical scrapie disease in previous experiments using heterozygous tg44+/− and tg23+/− mice [19] . Therefore , in the present study we generated homozygous anchorless PrP transgenic mice from both lines 44 and 23 . These mice each expressed two anchorless PrP transgene alleles and no normal mouse PrP alleles . PrPsen levels were analyzed by immunoblotting in brain homogenates of uninfected transgenic and non-transgenic mice . Homozygous tg44+/+ mice expressed 2-fold higher levels compared to tg44+/− mice ( Figure 1A ) . Non-transgenic C57BL/10SnJ mice homozygous for the PrP gene ( Prnp+/+ ) were used as controls , and these mice expressed 2-fold higher PrP levels than did Prnp+/− mice ( generated by crossing Prnp+/+ mice to Prnp-null mice also on the C57BL/10SnJ background ( see methods ) ) ( Figure 1A ) . Quantitative comparisons between transgenic and non-transgenic mice were difficult due to PrP glycosylation differences ( Figure 1A ) . Therefore we compared these mice using PrPsen deglycosylated with PNGase F ( Figure 1B ) . In these experiments Prnp+/− mice had approximately four-fold higher PrPsen levels than tg44+/+ mice ( compare lanes 2 vs . 4 and lanes 7 vs . 10 ) . Given the 2-fold difference between Prnp+/+ and +/− mice , tg44+/+ expressed 8-fold lower levels of brain PrPsen than did Prnp+/+ mice . Brain PrPsen levels in tg44+/+ and tg23+/+ mice were indistinguishable ( data not shown ) . Scrapie-induced clinical disease was analyzed in transgenic and non-transgenic mice using two different scrapie strains , RML and 22L . After intracerebral ( IC ) inoculation of scrapie strain 22L , Prnp+/+ and +/− mice developed clinical scrapie at 150–165 dpi and 245–260 dpi respectively ( Figure 2A ) . Similar results were also seen using the RML scrapie strain in Prnp+/+ mice ( Figure 2B ) . Prnp+/− mice were not tested with the RML strain . In contrast to experiments with non-transgenic mice , all tg44+/+ and tg23+/+ mice infected with strains 22L or RML developed neurological signs and required euthanasia from 300 to 480 dpi ( Figure 2 ) . Homozygous transgenic mice differed from non-transgenic mice in incubation period , duration and progression of clinical signs , as well as gait and postural abnormalities ( Table 1 ) . The most obvious signs in homozygous transgenic mice were the presence of a wide-based gait , rear extremity weakness with low posture , and lack of kyphosis . The signs seen in homozygous transgenic mice differed from the narrow-based tippy-toed gait and frequent kyphosis seen in infected Prnp+/+ and +/− mice ( Table 1 ) . The gait and postural differences probably reflected different patterns of neurological damage . Overall the differences between non-transgenic mice and homozygous transgenic mice suggested that there might be different pathogenic mechanisms operating in these two scrapie-induced disease models . In our earlier studies , heterozygous tg44+/− and tg23+/− mice did not manifest the usual clinical signs of scrapie during 600 days of observation after infection with scrapie strains 22L or RML ( Table 1 ) [19] . However , in the present experiments with the experience of observing the clinical signs described above in homozygous transgenic mice , we noted similar clinical signs in the infected heterozygous transgenic mice starting around 480 dpi . Clinical diagnosis in these mice was difficult due the erratic presence of signs in the initial stages , the longer duration of signs , and the possibility of confusion with signs of old age . These mice were euthanized between 480 and 700 dpi , but the indication for euthanasia was primarily debilitation ( weight loss , dermatitis , bladder distention , cancer and infections ) , rather than neuromuscular dysfunction . PrPres deposition in brain is a major hallmark of prion diseases , and PrPres is often associated with areas of brain degeneration . Therefore brain PrPres levels in scrapie-infected mice were analyzed by immunoblot . As shown in Figure 3 , tg44+/+ mice with clinical neurological disease had higher amounts of PrPres at 348–408 dpi than tg44+/− mice had at 567–594 dpi , which was when these mice had to be euthanized due to debilitating signs as described in Table 1 . A similar difference was seen between tg23+/+ and tg23+/− mice ( data not shown ) . The difference between tg44+/+ and tg44+/− mice in timing and levels of PrPres correlated with the higher PrPsen expression level seen in homozygous mice ( Figure 1A ) , and appeared to explain the earlier onset and more prominent clinical signs seen in homozygous transgenic mice . The PrPres detected in these immunoblots had a molecular weight of 19 kD . In our earlier study this band was found to react with an anti-PrP peptide antibody ( R20 ) directed at the C-terminal region of PrP ( residues 218–232 ) [19] . Therefore , there was no evidence for loss of these C-terminal residues as often occurs in human GSS [6] , [22] . Interestingly tg44+/+ and tg44+/− mice had higher PrPres levels than did non-transgenic Prnp+/+ or +/− mice , but the non-transgenic mice died earlier than the tg44+/+ mice ( Figure 2 ) . This suggested either that amyloid PrPres in tg44+/+ mice might be less pathogenic than the non-amyloid PrPres in non-transgenic mice , or that transgenic mice might be less susceptible to the pathogenic effects of PrPres amyloid due to the absence of membrane-anchored PrP . Previously we showed that scrapie-infected tg44+/− mice lacked signs of clinical scrapie but had infectivity titers in brain as high as 4 . 6×108 ID50/gram brain at 120–286 dpi as measured by end-point titration in C57BL/10 mice [19] . In the present experiments we passaged brain from infected tg44+/− ( passage 1 ) mice into other tg44+/− mice ( passage 2 ) , and at 512 and 531 dpi we found brain infectivity titers of 1 . 1–1 . 3×1010 ID50/gram brain ( Table 2 ) . These mice also had brain PrPres levels similar to those shown in other tg44+/− mice ( Figure 3 ) . Similar high titers were detected in passage 1 homozygous tg44+/+ mice at 384 dpi ( Table 2 ) . Thus in the transgenic anchorless PrP model , scrapie infectivity was present in brain at very high titers . Furthermore , the agent did not appear to develop new strain-like properties selective for tg44+/− mice as it could passage easily from tg44+/− mice to either C57BL/10 or tg44+/− mice . We compared the PrPres deposition and neuropathology after scrapie infection in transgenic tg44+/+ mice and non-transgenic C57BL/10 control mice ( Table 3 ) . Following scrapie infection in C57BL/10 mice typical TSE-specific diffuse deposits of PrPres were found in many brain areas ( Figure 4A , 4B ) . This PrPres did not stain with the amyloid stain , Thioflavin S [19] . In many brain regions by H&E staining we observed gray matter spongiosis ( Figure 4C ) , which is an important feature of TSE/prion diseases . In scrapie-infected tg44+/+ mice PrPres accumulated as large dense plaque-like deposits , usually in a perivascular location around capillaries , veins and arteries in numerous brain regions , including leptomeninges , cerebral cortex , corpus callosum , forebrain , hippocampus , thalamus , hypothalamus , midbrain , colliculi , brainstem , and spinal cord ( Figure 4D , 4E , 5A , 5B ) After infection with the 22L scrapie strain , the cerebellar molecular layer and granular layer were also involved [19] , but this was not seen after infection with the RML strain ( Figure 4D ) . These deposits were Thioflavin S-positive [19] , and no areas of diffuse non-amyloid PrPres were observed . The most distinguishing histopathological feature in tg44+/+ mice at the time of clinical signs was distortion of brain structures adjacent to large amyloid plaques in many areas ( Figures 4D , E , H–L ) . These areas had intense micro- and astrogliosis ( Figures 4G ) . Small blood vessels showed occasional micro-hemorrhages , or perivascular haemosiderin accumulation , but no lymphocyte infiltration of blood vessel walls was detected . Marked neuronal loss was seen around edges of some gray matter plaques ( Figure 4H , I ) ; however , no gray matter spongiosis typical of prion diseases was seen ( Figure 4C vs 4F ) . In addition , tg44+/+ mice had focal areas of abnormal staining of amyloid precursor protein ( APP ) ( Figure 4K ) , non-phosphorylated neurofilament protein ( NFP ) ( Figure 4L ) , and phosphorylated NFP ( not shown ) , all of which indicated a process of severe axonal dystrophy . These latter effects were rarely seen in scrapie-infected C57BL/10 mice ( Table 3 ) . These results suggested that scrapie-infected anchorless PrP transgenic mice had a different pathogenic process compared to non-transgenic C57BL/10 mice . For higher resolution of details , scrapie-infected tg44+/+ mice were also studied using immunohistochemistry on 1 micron thick plastic-embedded sections as well as immunogold labeling at the ultrastructural level . Light microscopy on thin sections showed both perivascular and vascular PrPres labeling ( Figure 5A ) , as well as occlusion of vessels in some cases ( Figure 5B ) . By electron microscopy abundant PrPres labeling of blood vessels was seen most predominantly at basement membranes . In some larger vessels smooth muscle cells of the media were atrophied and replaced by extensive PrPres accumulation ( Figure 5C ) . Vascular and plaque PrPres accumulation could be seen to be of a fibrillar amyloid nature at high magnification ( Figure 5D ) . In smaller vessels PrPres was seen at both endothelial and pericyte basement membranes ( Figure 5E ) . PrPres was also observed within the extracellular space along the borders of swollen astroglial and neurite processes in the absence of visible fibrillar amyloid ( Figure 5F and G ) . No PrPres labeling was seen in uninfected control mice . Using staining with uranyl acetate/lead citrate large areas of distended swollen processes could be seen ( Figure 6A ) , which were similar to the areas of immunogold-labeled PrPres shown above ( Figure 5G ) . At higher magnification swollen perivascular glial processes were often seen ( Figure 6B ) , and fibrils were visible in the endothelial basement membrane ( Figure 6C ) and/or pericyte basement membrane ( Figure 6D ) . The initial site of aggregation into fibrils was in the ablumenal basement membranes ( Figure 5D ) . Dystrophic neurites were also frequently noted in gray matter ( Figure 6E ) . These were most conspicuous surrounding perivascular amyloid plaques and corresponded to sites of APP labeling . In white matter we observed degeneration of axons , including empty distended myelin sheaths ( Figure 6F ) ( Table 3 ) which could be seen as white matter vacuoles by light microscopy ( Figure 4F ) . In contrast to transgenic mice , infected C57BL/10 mice at the time of clinical disease had numerous TSE vacuoles with broken or “hanging” membranes ( not shown ) [23] [24] . Such vacuoles were never seen in infected transgenic mice ( Table 3 ) . In C57BL/10 mice other ultrastructural hallmarks specific for classical prion diseases including membrane accumulation of disease-specific PrPres and TSE-specific membrane alterations were also seen , as reported previously in other prion disease models [17] [7] , [18] , [24] ( Table 3 ) . However , none of these prion disease-specific features was seen in infected tg44+/+ mice . The ultrastructural differences between scrapie-infected C57BL/10 and tg44+/+ mice supported the conclusion that the pathogenesis of disease in these transgenic mice was not typical TSE/prion disease . The reasons for the different types of scrapie-induced pathogenesis in C57BL/10 mice and anchorless PrP transgenic mice are not known . Two possibilities include: first , PrPres amyloid and diffuse non-amyloid PrPres might have different neurotoxic effects; second , PrPsen anchoring might influence neurotoxicity induced by infection . To test whether PrPres derived from GPI-anchored PrPsen could induce gray matter vacuoles in tissue expressing anchorless PrPsen , brain tissue from C57BL/6 mice at embryonic day E12–E14 , which expressed green fluorescent protein constitutively in all tissues [25] , was grafted into the brain of adult tg44+/− mice or PrP null mice as controls [26] . One month after grafting , mice were infected IC with scrapie , and at 132–511 dpi the brain tissue was examined by histopathology . Recipients had from 1–6 detectable grafts per mouse ( Table 4 ) . Representative grafts are shown in Figure 7 . At 261 dpi in the control PrPnull recipient , C57BL/6 graft tissue , identified by presence of green fluorescent protein ( GFP ) ( Figure 7A ) , had easily detectable PrPres ( Figure 7B ) present both within the graft and at the interface between the graft and the host tissue , but PrPres did not appear to spread extensively into the PrPnull tissue . TSE gray matter vacuolation was seen only within the graft tissue ( Figure 7B and 7C ) . This was similar to a previous report [26] . In tg44+/− recipient mice receiving C57BL/6 grafts , PrPres and gray matter vacuolation was also seen in the graft ( Figure 7F and 7I ) . In the adjacent host tissue expressing anchorless PrP , amyloid PrPres and white matter vacuoles were noted; however , the C57BL/6 PrPres present at the edges of the graft appeared to be unable to induce gray matter vacuoles in the adjacent transgenic tissue ( Figure 7F ) . In some cases the graft cells were not well-demarcated from the host ( Figure 7G ) , and it was not clear whether the PrPres and vacuoles were in the graft or the host ( Figure 7H and 7I ) . These results were representative of observations in 25 grafts in tg44+/− recipients where PrPres was detected in the graft ( Table 4 ) . In summary , we found no grafts where expression of anchored PrPres from the C57BL/6 graft could be associated with gray matter spongiosis in adjacent transgenic host tissue . This result suggested that expression of anchored PrPsen in gray matter might be a fundamental requirement for the induction of the typical TSE/prion disease pathogenic process .
In the present experiments scrapie infection of transgenic mice expressing anchorless PrP resulted in a slow fatal brain disease . These results demonstrated new mechanisms of prion-induced pathogenesis associated with the presence of PrPres amyloid and the absence of GPI-anchored PrP . This disease lacked gray matter spongiosis and differed in this respect from scrapie infection in non-transgenic mice , where the disease is characterized by extensive gray matter spongiosis and non-amyloid PrPres deposition . The current results raised the question of how lack of GPI-linked membrane anchoring of PrP might facilitate formation of PrPres amyloid . GPI anchorless PrP has a longer biological half-life [27] and is secreted by the cell . Both of these attributes might allow more effective and extensive interactions between soluble PrP molecules . In addition , the minimal amount of carbohydrates and the absence of the GPI group on anchorless PrP might favor amyloidogenic hydrophobic protein-protein interactions , particularly at a time of partial protein unfolding during PrP conversion . These features of anchorless PrP are likely to contribute to its enhanced tendency to form amyloid during conversion to PrPres . Anchorless protease-resistant PrP , cleaved at residue 228 , comprises 15% of the PrPres in hamster scrapie brain extracts [28] , but it is unclear whether this material contributes to the amyloid PrP seen in this model . Our results differed from those of two interesting mouse prion disease models where PrPres was also found almost entirely in an amyloid form . In the GSS PrP-8kd model [29] and the G3-ME7 model [30] , which both used PrP mutant mice , PrP amyloid was seen primarily in the corpus callosum , but did not spread significantly to other brain regions . There was no clinical disease in these models , and transmission experiments suggested very low infectivity titers in the GSS PrP-8kd model . Compared to these two models , the three main distinguishing features of the anchorless PrP model are the ability of the PrPres amyloid to accumulate widely throughout the brain ( Figure 4 ) , the resulting fatal brain disease ( Figure 2 ) , and the high titer of transmissible agent ( Table 2 ) [31] . The association of amyloid deposition without gray matter spongiosis in our system is reminiscent of the neuropathology seen in certain human familial prion diseases . For example , GSS patients with PrP mutations Y145Stop and Y163Stop had both CAA and parenchymal perivascular amyloid without gray matter spongiosis [32] [33] . Both these mutations result in C-terminally truncated PrP lacking the GPI anchor . Parenchymal amyloid deposition without gray matter spongiosis has also been seen in GSS patients with several other PrP mutations including P102L , P105L , A117V and F198S [6] . Recently two human GSS patients with new PrP mutations producing nonsense codons at positions 226 and 227 were described [34] . Both patients had widespread PrPres amyloid deposition in the absence of gray matter spongiosis , and one had CAA . These patients expressed a nearly full-length form of PrP lacking 6–7 C-terminal residues and the GPI anchor , which was quite similar to the PrP expressed in our anchorless PrP tg mice . In many GSS patients , amyloid PrPres purified from brain was truncated resulting in a 7–11 kDa protease-resistant fragment from the central region of PrP ( approximately residues 81–150 ) [6] , [22] , [34] . Interestingly , presence of this truncation has been correlated with the lack of gray matter spongiosis [8] , [9] . In contrast , based on previous immunoblot studies , the proteinase K-resistant PrPres amyloid in our model appeared to contain residues 88–231 [19] , which was similar to the PrPres found in human and animal prion diseases with extensive gray matter spongiosis . Furthermore , PrPres in tissue sections could be stained with anti-PrP serum R24 , specific to residues 23–37 ( data not shown ) suggesting that there was no significant truncation at the N-terminus beyond the signal peptide . Thus , lack of spongiosis in our model appeared dependent on the absence of GPI-anchoring rather than truncation of the PrPres . Two possibilities might explain the correlation between lack of GPI- anchored PrP and lack of gray matter spongiosis in our infected transgenic mice: ( 1 ) anchorless amyloid PrPres might be less neurotoxic than diffuse PrPres , and/or ( 2 ) anchored PrPsen might be required for PrPres-mediated neurotoxic membrane interactions . The former explanation could not be proven or excluded by our results . However , the latter interpretation was supported by data from brain graft experiments . After scrapie infection of tg44+/− mice grafted with C57BL/6 brain expressing normal anchored PrPsen , we observed gray matter spongiosis and non-amyloid PrPres deposition in C57BL/6 grafts , but not in adjacent host tissue expressing only anchorless PrPsen . Tissue expressing only anchorless PrPsen appeared to be unable to respond to the presence of GPI-anchored PrPres produced in the nearby grafts , and no gray matter spongiosis was produced . Therefore , lack of anchored PrPsen might by itself explain the lack of gray matter spongiosis in transgenic mice . However , even in the absence of anchored PrPsen , the amyloid PrPres was able to induce additional pathogenic processes capable of causing fatal neurological disease . By both light and electron microscopy we observed evidence for three distinct pathogenic processes not seen in typical prion disease in C57BL/10 mice ( Box 1 ) : ( 1 ) Brain damage caused by tissue distortion by large amyloid plaques . These plaques were associated with neuronal loss , axonal pathology and gliosis ( Figure 4E , H–L Figure 6A , E , F ) . The more rapid accumulation of PrPres in tg44+/+ mice compared to tg44+/− mice ( Figure 3 ) suggested a faster growth of large space-occupying plaques which might explain in part the clinical neurological signs leading to death of tg44+/+ and tg23+/+ mice ( Figure 2 ) . ( 2 ) A second pathogenic process in scrapie-infected transgenic mice was suggested by ultrastructural studies finding that the early aggregation of PrPres into fibrillar amyloid was located at or within vascular basement membranes ( Figures 5C , 5D , 6C , 6D ) . This was associated with vascular damage including occlusion ( Figure 5B ) , amyloid replacement of basement membrane and tunica media , and occasional micro-hemorrhages . This pathology was similar to that observed in CAA seen in Alzheimer's disease and several familial amyloid diseases including two prion diseases [14] , [15] , [32] , [33] . ( 3 ) Evidence of a third pathogenic process in the transgenic mice was suggested by finding of small deposits of immunogold-labeled PrPres at the ultrastructural level in the extracellular spaces between glial and neuritic processes in gray matter ( Figures 5D , 5E , 5F ) . These PrPres deposits were small , and there was no distortion of the extracellular space or visible aggregation into amyloid fibrils . However , the adjacent processes were often highly dystrophic ( Figure 6E ) or swollen and devoid of organelles , and they appeared to coalesce to form empty spaces larger than the original processes ( Figures 5G , 6A , 6B ) . These abnormal areas , which were also noted in heterozygous tg44+/− and tg23+/− mice , appeared to represent a form of damage related to small , rather than large , PrPres deposits , and they did not require the presence of anchored PrPsen for their formation . The early localization of PrPres at basement membranes ( Figures 5A , C , D ) , suggested that the PrP conversion process might initiate at these sites , and implied that basement membrane molecules might facilitate PrP conversion . For example , basement membrane might filter or trap soluble PrPsen molecules or small PrPres oligomers from the extracellular interstitial fluid of brain increasing their local concentration , thus favoring conversion to larger PrPres amyloid aggregates . Serum amyloid P-component which binds to all amyloids and is a constituent of basement membranes might also contribute to local PrP conversion [35] . In addition , collagen , laminin and heparin sulfate-containing proteoglycans are major components of basement membranes , and PrP can bind to both the laminin receptor and heparan sulfate which can associate directly or indirectly with PrP [36]–[38] . Heparan sulfate and other glycosaminoglycan ( GAG ) moieties can delay scrapie disease in vivo [39]–[42] [43] , [44] , and some GAG molecules can alter PrP conversion in vitro [45] . A scaffolding mechanism might account for this effect . For example , soluble anchorless PrPsen monomers might be held in place by GAG polymers to increase local concentration and facilitate conversion by PrPres , analogous to the tethering of anchored PrPsen on cell membranes [46] , [47] . In addition , attachment of small mobile PrPres oligomers to GAG polymers might assist conversion at the basement membrane . Subsequently newly formed larger less mobile PrPres could serve as an efficient scaffold for further conversion allowing the process to extend out into the brain parenchyma . Eventually this process might form very large PrPres amyloid plaques with blood vessels at the center as we observed ( Figure 4E and 5A ) . The vascular amyloid pathology seen in our scrapie-infected transgenic mice ( Figures 4E , 5A–D , 6B–D ) was similar to CAA seen in Alzheimer's disease as well as several familial amyloid diseases [14] , including two forms of familial prion disease [32] [14] . In Alzheimer's disease , amyloid fibrils within vascular basement membranes are thought to impede interstitial fluid drainage leading to an increase in Aβ concentrations within the extracellular space . Such increased soluble Aβ and oligomeric proto-amyloid fragments are considered a likely contributory factor in the cognitive decline of Alzheimer's disease patients [15] . Similar processes might contribute to the clinical disease seen in the anchorless PrP scrapie model . Since all these diseases with CAA show amyloid localization with basement membranes , drugs capable of blocking amyloid-basement membrane interactions might be effective treatments for some of these diseases . In the case of prion diseases , one such compound , pentosan polysulfate , a small GAG oligomer , was effective in blocking PrPres generation in an infected cell line [48] and delayed onset of clinical scrapie in vivo [41] [42] [44] . Similarly a decoy molecule preventing PrP interaction with the laminin receptor ( LRP/LR ) reduced PrPres levels and delayed disease in vivo [37] . Determining the precise glycans and proteins involved in the protein interactions leading to amyloid deposition in all the CAA diseases might be important in designing new therapeutic approaches .
Ethics statement: All mice were housed at the Rocky Mountain Laboratories ( RML ) in an AAALAC-accredited facility , and research protocols and experimentation were approved by the NIH RML Animal Care and Use Committee . C57BL/10SnJ mice ( Prnp+/+ ) were obtained from Jackson Laboratories ( Bar Harbor , Maine ) . C57BL/10SnJ PrP−/− mice were created at RML by crossing 129/Ola PrP−/− mice [49] with C57BL/10SnJ mice , followed by nine serial backcrosses to C57BL/10SnJ with selection for the Prnp+/− genotype using previously described PCR reactions to detect both the Prnp+ and Prnp null alleles [19] . One intercross was then done , and C57BL/10SnJ Prnp−/− ( PrP−/− ) mice were selected and interbred . Heterozygous Prnp+/− mice were obtained by intercrossing C57BL/10 ( Prnp+/+ ) mice with C57BL/10 Prnp−/− mice . Transgenic GPI anchorless PrP mice ( tg44+/− and tg23+/− ) were made as described previously [19] and then backcrossed to C57BL/10SnJ-Prnp−/− mice for six to nine generations with selection for the Prnp−/− genotype and the tg44 or 23+/− genotype . Thus these mice contained one anchorless PrP transgene allele and did not express any normal anchored mouse PrP allele . Heterozygous transgene lines tg23+/− and tg44+/− were each interbred to create homozygous lines ( tg44+/+ and tg23+/+ ) . Offspring were tested for transgene zygosity using real-time DNA PCR on an ABI Prism 7900 HT Sequence detection system and SDS 2 . 2 . 2 software . The following probes and primers were designed to amplify the mouse Prnp sequence: probe ( moPrPlower418T ) : ( 5′-CGGTCCTCCCAGTCGTTGCCAAA ) , forward primer ( moPrP-396F ) : ( 5′-CGTGAGCAGGCCCATGATC ) , reverse primer ( moPrP-465R ) : ( 5′GCGGTACATGTTTTCACGGTAGT ) . Individual mice identified by rtPCR as transgene homozygous were then bred to Prnp−/− mice to confirm homozygosity . Homozygous mice were then interbred to create additional mice for experimentation . Both tg44 and tg23 lines were used in the present experiments to demonstrate that the observed findings were consistent with transgene expression rather than a result of an integration site artifact . Four to six week old mice were inoculated intracerebrally with 50 µl of a 1% brain homogenate of 22L or RML scrapie containing 0 . 7–1 . 0×106 ID50 . One ID50 is the dose causing infection in 50% of C57BL/10 mice . Animals were observed daily for onset and progression of scrapie . Mice were euthanized when clinical signs were consistent and progressive . Signs differed somewhat in C57BL/10 and tg44+/+ and tg23+/+ mice ( Table 1 ) . In heterozygous tg44+/− and tg23+/− mice many mice developed signs of debilitation such as weight loss , dermatitis and infections requiring euthanasia prior to severe neurological signs . For detection of PrPsen from uninfected brains , tissues were homogenized ( 20% w/v ) using a bead beater in ice-cold 0 . 01 M Tris-HCl pH 7 . 6 containing protease inhibitors ( 10 µM leupeptin , 1 µM pepstatin , and 1 µM aprotinin ) . Each sample was vortexed for 1 minute followed by sonication for 1 minute . Insoluble debris was removed by centrifugation at 2700 g for 10 minutes at 4°C . Samples were mixed 1∶1 with 2X SDS-PAGE sample buffer and boiled for 3–5 minutes . PNGase F reactions were done using 4 . 4 mg tissue equivalents in a total volume of 20 µl SDS-PAGE sample buffer [50] . Samples were serially diluted two-fold in sample buffer to give the amount of brain tissue ( mg brain equivalents ) indicated for each lane . Immunoblots were probed by using monoclonal anti-PrP D13 at a dilution of 1∶5000 ( InPro Biotechnology , South San Francisco , CA ) , followed by secondary antibody sheep anti-human Ig ( dilution 1∶5000 ) ( GE Healthcare , formerly Amersham Biosciences , Piscataway , NJ ) and enhanced chemiluminescence according to the manufacturers instructions ( Amersham-Pharmacia , Uppsala , Sweden ) . For detection of PrPres either with or without PNGase F , samples were prepared as described [51] . Blots were probed as described above . Embryonic brain tissue was obtained from E12–E14 C57BL/6 embryos which expressed green fluorescent protein ( GFP ) in all tissues [25] . Mice were purchased originally from Jackson laboratories and were bred at Rocky Mountain Laboratories by Dr . Kim Hasenkrug . Pregnant mothers were euthanized and embryos dissected with forceps in media under a dissecting microscope to obtain the mesencephalon and telencephalon . Tissue was partially disrupted by pipetting to generate small fragments . This suspension ( 30 µl ) was inoculated intracerebrally through the skull into the parietal brain region of 3–4 week old PrPnull mice or tg44+/− mice . One month later recipient mice were infected intracerebrally with 22L scrapie as described above . At various times thereafter mice were euthanized and brain tissue was examined histologically for GFP and PrPres by specific immunohistochemistry and for typical scrapie-induced gray matter spongiosis by H&E staining . Mice were euthanized and brains were placed in 3 . 7% phosphate-buffered formalin for 3 to 5 days before dehydration and embedding in paraffin . Serial 4 µm sections were cut using a standard Leica microtome , placed on positively charged glass slides and dried overnight at 56°C . Slides were stained with a standard protocol of hematoxylin and eosin ( H&E ) for observation of overall pathology . For PrPres detection , slides were rehydrated in 0 . 1 M citrate buffer , pH 6 . 0 and then heated at 120°C , 20 psi for 20 minutes in a decloaking chamber ( Biocare , Walnut Creek , CA ) . Immunohistochemical staining was performed using the Ventana automated Nexus stainer ( Ventana , Tucson , AZ ) . Staining for PrP used a standard avidin-biotin complex immunoperoxidase protocol using anti-PrP antibody D13 ( In-Pro Biotechnology , South San Francisco , CA ) at a dilution of 1∶500 and incubated at 4°C for 16 hours . Biotinylated goat anti-human IgG ( Jackson Immuno Research , West Grove , PA ) was used at a 1∶500 dilution as the secondary antibody . Detection was performed with Ventana streptavidin-alkaline phosphatase with Fast Red chromogen . Tissue sections for microglia staining were pretreated and stained with anti-Iba1 as described [52] except that detection was done using the Ventana Fast Red chromagen as above . Astroglia were stained with anti-GFAP as described [52] , and detection was completed with Ventana streptavidin-alkaline phosphatase using Fast Red . Tissue sections for staining with anti-amyloid precursor protein ( APP ) were pretreated as described for anti-PrP antibody D13 . Anti-APP ( Zymed Laboratories , San Francisco , CA ) was used at a 1∶500 dilution followed by a 1∶250 dilution of biotinylated-goat anti-rabbit IgG ( Vector Laboratories , Burlington , CA ) , and detection with Ventana streptavidin-horseradish peroxidase plus amino ethyl carbazol ( AEC ) chromagen . Staining of phosphorylated neurofilament proteins was performed using a monoclonal antibody cocktail pan-axonal neurofilament marker SMI-312 ( Covance , Princeton , NJ ) at a 1∶250 dilution . Monoclonal antibody to nonphosphorylated neurofilament proteins was also used ( SMI-311 ) . Primary antibodies were followed by biotinylated horse anti-mouse IgG secondary antibody at a 1∶250 dilution . Ventana AEC reagent was used for detection . Green fluorescent protein ( GFP ) was detected using a mixture of two mouse anti-GFP monoclonal antibodies ( clones 7 . 1 and 13 . 1 ) at dilution of 1∶200 ( Roche Applied Science , Indianapolis , IN ) , followed by biotinylated horse anti-mouse IgG ( Vector Laboratories , Burlington , CA ) at a dilution of 1∶250 and detected with AEC chromogen ( Ventana ) as described above . All histopathology slides were read using an Olympus BX51 microscope and images were obtained using Microsuite FIVE software . Mice were perfused with fixative containing 3% paraformaldehyde and 1% glutaraldehyde in PBS . Excised tissues were then immersed in this fixative and held overnight at 4 degrees C . Tissue pieces were processed further using a Lynx® automated tissue processor with agitation as follows: one wash in PBS for 3 hr at 20 degrees , one wash in 0 . 1 M sodium phosphate buffer pH 7 . 2 at 20 degrees for 4 hr , post-fix in 2% osmium tetroxide in phosphate buffer at 20 degrees for 6 hr , one wash in phosphate buffer at 20 degrees for 3 hr , three washes in water at 20 degrees for 3 hr each , in-block staining with 1% uranyl acetate in water at 20 degrees for 6 hr , 3 washes in water at 20 degrees for 3 hr each , dehydration in 70% , 100% , and 100% acetone at 10 degrees for 3 hr each , and infiltration at 20 degrees in Araldite resin ( Structure Probe , Inc . , West Chester , PA ) at 50% for 8 hr , 75% for 12 hr , and two changes of 100% for 20 hr each . Further tissue blocks were processed using a Leica EM TP processor using the procedure above with the omission of the uranyl acetate . Tissue blocks were then transferred to fresh resin in molds and polymerized at 65 degrees for 24 to 48 hr . Thick ( 1 µm ) sections were stained by toluidine blue or were immunolabelled using the avidin-biotin technique . Sections were deplasticized with saturated sodium ethoxide for up to 30 minutes . Endogenous peroxidase was blocked and sections were de-osmicated with 6% hydrogen peroxide for 10 minutes , followed by pre-treatment with neat formic acid for 5 minutes . Normal serum was then applied for 1 hour to block non-specific labeling . 1A8 anti-PrP serum [53] at a dilution of 1∶6000 , or pre-immune serum were then applied for 15 hours and reaction product developed using 3-3′ diaminobenzidine . For routine electron microscopy areas were selected from 1 µm thick toluidine blue stained sections and counterstained with uranyl acetate and lead citrate . For ultrastructural immunohistochemistry , serial 65 nm sections were taken from blocks previously identified from immuno-labeled 1 µm thick sections as described above . The 65 nm sections were placed on 600 mesh gold grids and etched in sodium periodate for 60 minutes . Endogenous peroxidase was blocked and sections de-osmicated with 6% hydrogen peroxide in water for 10 minutes followed by enhancement of antigen expression with formic acid for 10 minutes . Residual aldehyde groups were quenched with 0 . 2 M glycine in PBS , pH 7 . 4 for 3 minutes . Preimmune serum or anti-PrP primary antibody 1A8 [53] or R30 [54] at a 1∶500 or 1∶1500 dilution respectively in incubation buffer were then applied for 15 hours . After rinsing extensively , sections were incubated with Auroprobe 1 nm colloidal gold diluted 1∶50 in incubation buffer for 2 hours . Sections were then post-fixed with 2 . 5% glutaraldehyde in PBS and labeling enhanced with Goldenhance ( Universal Biologicals , Cambridge , UK ) for 10 minutes . Grids were counterstained with uranyl acetate and lead citrate . | Prion diseases , also known as transmissible spongiform encephalopathies , are infectious fatal neurodegenerative diseases of humans and animals . A major feature of prion diseases is the refolding and aggregation of a normal host protein , prion protein ( PrP ) , into a disease-associated form which may contribute to brain damage . In uninfected individuals , normal PrP is anchored to the outer cell membrane by a sugar-phosphate-lipid linker molecule . In the present report we show that prion infection of mice expressing PrP lacking the anchor can result in a new type of fatal neurodegenerative disease . This disease displays mechanisms of damage to brain cells and brain blood vessels found in Alzheimer's disease and in familial amyloid brain diseases . In contrast , the typical sponge-like brain damage seen in prion diseases was not observed . These results suggest that presence or absence of PrP membrane anchoring can influence the type of neurodegeneration seen after prion infection . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"infectious",
"diseases/prion",
"diseases",
"pathology/neuropathology",
"neurological",
"disorders/prion",
"diseases"
] | 2010 | Fatal Transmissible Amyloid Encephalopathy: A New Type of Prion Disease Associated with Lack of Prion Protein Membrane Anchoring |
The addition of asparagine ( N ) -linked polysaccharide chains ( i . e . , glycans ) to the gp120 and gp41 glycoproteins of human immunodeficiency virus type 1 ( HIV-1 ) envelope is not only required for correct protein folding , but also may provide protection against neutralizing antibodies as a “glycan shield . ” As a result , strong host-specific selection is frequently associated with codon positions where nonsynonymous substitutions can create or disrupt potential N-linked glycosylation sites ( PNGSs ) . Moreover , empirical data suggest that the individual contribution of PNGSs to the neutralization sensitivity or infectivity of HIV-1 may be critically dependent on the presence or absence of other PNGSs in the envelope sequence . Here we evaluate how glycan–glycan interactions have shaped the evolution of HIV-1 envelope sequences by analyzing the distribution of PNGSs in a large-sequence alignment . Using a “covarion”-type phylogenetic model , we find that the rates at which individual PNGSs are gained or lost vary significantly over time , suggesting that the selective advantage of having a PNGS may depend on the presence or absence of other PNGSs in the sequence . Consequently , we identify specific interactions between PNGSs in the alignment using a new paired-character phylogenetic model of evolution , and a Bayesian graphical model . Despite the fundamental differences between these two methods , several interactions are jointly identified by both . Mapping these interactions onto a structural model of HIV-1 gp120 reveals that negative ( exclusive ) interactions occur significantly more often between colocalized glycans , while positive ( inclusive ) interactions are restricted to more distant glycans . Our results imply that the adaptive repertoire of alternative configurations in the HIV-1 glycan shield is limited by functional interactions between the N-linked glycans . This represents a potential vulnerability of rapidly evolving HIV-1 populations that may provide useful glycan-based targets for neutralizing antibodies .
Developing an efficient and accurate method to detect interactions between components of the same protein , or between different proteins , is an important and unresolved problem in computational biology . One of the first approaches was to apply a measure of the correlation in amino acid composition at different codon positions in related protein sequences [18 , 19] . However , this approach was limited to pairwise interactions and could not readily distinguish functional from phylogenetic relationships [20] . A complete representation of interactions in a phylogenetic context can be achieved by modeling the evolution of the entire sequence through a state space of all possible sequences [21 , 22] . This approach involves an excessive number of parameters—i . e . , on the order of O ( 20L ) parameters for protein sequences of length L—requiring approximate methods of parameter estimation that are not necessarily statistically robust ( e . g . , Markov Chain Monte Carlo , MCMC ) . Another class of phylogenetic models include the simplifying assumption that the overall rate of evolution at a site depends on the states of adjacent sites [23 , 24] , contrary to the intuition that an interaction drives substitutions to specific states . Even so , these models remain computationally inefficient . In sum , there are a number of diverse methods that can be applied towards identifying nonindependent evolution between positions in a sequence , but no consensus on which method performs most reliably in practice . Furthermore , other potentially useful approaches ( e . g . , Bayesian networks ) that can address specific weaknesses of existing methods have yet to be applied to the study of covariation within evolving sequences . We propose to employ new methods that complement each other's strengths , while addressing the weaknesses of previous methods , to determine the subset of detectable interactions that are robust to varying assumptions . In this study , we evaluate whether the evolution of PNGSs in the HIV-1 envelope has been significantly influenced by glycan–glycan interactions , and identify specific interactions between PNGSs in the envelope glycoproteins gp120 and gp41 by the application of phylogenetic and graphical models to a published alignment of HIV-1 sequences . First , we verify that the distribution of PNGSs is consistent with heterotachy , in which site-specific rates of evolution vary over time due to genetic or environmental interactions [25] . This is accomplished by evaluating a hidden rate-switching or “covarion” model [26 , 27] against constrained phylogenetic models of PNGS evolution in a nested analysis based on maximum likelihood . Second , we propose a stochastic model to directly identify genetic interactions , using a new paired-character model of PNGS evolution named the disequon model ( where sequon refers to the sequence motif defining a PNGS ) . We use maximum likelihood estimates of the disequon model parameters to quantify the type and magnitude of interactions between every pairwise combination of PNGSs in the alignment , within a phylogenetic context . However , because each pairwise interaction is evaluated in isolation from all other PNGSs , the model is unable to identify higher-order interactions among PNGSs , and therefore cannot guarantee that specific pairwise interactions persist in the context of the entire glycan shield . To capture these higher-order interactions , we investigate interactions among PNGS using a probabilistic graphical model . A graph consists of a number of nodes , each one representing a variable ( e . g . , presence/absence of a PNGS ) , that are connected by directed or undirected arcs . The conditional dependence of one variable upon another is represented by a directed arc connecting the corresponding nodes , usually depicted as an arrow . Nodes that are not connected by arcs are conditionally independent . In practice , a directed graph is required to be acyclic so that a chain of directed arcs does not form a feedback loop to its parent node—such a graph is commonly referred to as a tree or “forest” of unrelated trees . Probabilistic models based on directed acyclic graphs originate from the formulation of path analysis by the evolutionary biologist Sewall Wright in 1921 [28] , but are currently more widely known as Bayesian networks [29] . There is an ongoing proliferation of studies that apply Bayesian networks to problems in biology , such as the analysis of gene expression data to infer the structure of regulatory networks [30] . Bayesian networks confer several advantages for analyzing biological data: ( i ) networks provide an intuitive visual representation of biological complexity; ( ii ) they can explicitly incorporate experimental uncertainty and missing observations; and foremost , ( iii ) an abundance of algorithms for the inference of Bayesian networks from empirical data is already available ( reviewed in [31] ) .
We located 224 positions at which PNGSs occurred in at least one sequence , out of 1 , 049 possible positions in an alignment of 711 full-length HIV-1 envelope sequences . The frequency of PNGS per codon position was highly variable , with more than 65% of PNGSs present in fewer than 10% of the sequences . About one-quarter of PNGSs ( n = 57 ) were unique to a single sequence in the alignment and represented either spurious variation in the position of a PNGS due to uncertainty in the alignment of sequences or genuinely rare glycosylation sites . An individual sequence encoding both gp120 and gp41 contained 29 . 9 PNGS on average . We fitted a generalized linear model to the number of PNGS per sequence ( using the R function glm [32] ) , which revealed subtype to be a significant factor ( Wald test: χ42 = 12 . 7 , p = 0 . 012 ) . This analysis was restricted to subtypes that were represented by at least 40 nonrecombinant sequences in the data ( viz . A , B , C , D , and O ) to avoid spurious results due to small sample size . This effect of subtype was largely due to an elevated number of PNGSs ( ≈31 . 9 ) in O group sequences ( n = 44; z = 2 . 8 , p = 0 . 005 ) . For example , the PNGSs N59 and N229 ( numbered according to their positions in the HxB2 reference sequence ) were essentially unique to group O sequences , as noted in a previous study [7] . Likelihood and parameter estimates for the covarion model and constrained models of PNGSs evolution are summarized in Table S1 . Variation among sites in the overall rate of gain or loss of PNGS ( α−1 ) was strongly supported by the data ( χ12 = 960 . 4 , p ≪ 0 . 001 ) . This result was consistent with prior observations that while some PNGSs are highly conserved in HIV-1 envelope sequences , others are under strong host-specific selection [7 , 11] . We found strong support for rejecting the noncovarion model in favor of a model with an unconstrained rate of switching between hidden states ( son , soff > 0; χ22 = 639 . 8 , p ≪ 0 . 001 ) . Allowing variation among sites in the hidden-state switching rates ( σ−1 ) provided an additional significant improvement of fit to the data ( χ12 = 174 . 2 , p ≪ 0 . 001 ) . Although the mean switching rates ( son and soff ) appeared to be roughly symmetric in the full model , the nested model with the constraint soff = son was rejected by a likelihood-ratio test ( LRT ) ( χ12 = 6 . 6 , p = 0 . 01 ) . In sum , the full covarion model was favored by all criteria evaluated ( AIC , AICc , and BIC; Table S1 ) with the following parameter estimates: son = 0 . 08 , soff = 0 . 06 , r01/r10 = 0 . 29 , σ = 0 . 75 , and α = 0 . 46 . Removal of sequences that were annotated as subtype recombinants ( n = 219 ) had no discernible effect on our results . Overall , the hypothesis that evolutionary rates for the gain or loss of PNGSs were variable over time , i . e . , heterotachy , was strongly supported by the data . We detected significant interactions between PNGSs in the disequon model for 22 out of 6 , 455 pairwise combinations after applying a deliberately conservative Bonferroni correction for multiple comparisons ( see Materials and Methods ) . Nine of these pairs consisted of PNGSs that overlapped by one or three residues and were located either in the variable loops of gp120 ( i . e . , V1/V2 and V4 ) or gp41 ( i . e . , N624–N625 ) . Estimates of the interaction parameter ( ɛ ) indicated that the interactions between all overlapping pairs were negative ( ɛ < 1 ) , with a single exception . This exception involved PNGSs introduced by insertions into the V1/V2 loop ( alignment positions 252 and 253 ) that were present at low frequencies in the alignment ( 1 . 1% and 1 . 4% , respectively ) . However , both PNGSs occurred together in a single subtype B sequence , resulting in an unusually high estimate of ɛ = 15 . 3 ( χ12 = 17 . 5 , p = 2 . 91 × 10−8 ) . It is worth noting that an unusually high localized density of PNGSs was introduced into this sequence by the insertion of the motif NNTSNNTSY into the V1/V2 loop , defining four distinct PNGSs . This particular outcome was handled as an outlier in subsequent analyses . Table 1 summarizes the parameter estimates from the disequon model for all nonoverlapping pairwise combinations of PNGSs with a significant interaction component ( ɛ ≠ 1 ) . Unlike the overlapping PNGSs , positive interactions between nonoverlapping PNGSs ( ɛ > 1 , n = 8 ) occurred about as often as negative interactions ( ɛ < 1 , n = 5 ) . Indeed , we found that ɛ increased significantly with respect to the intramolecular distance ( measured in angstroms , Å ) , separating the asparagine residues of PNGSs with significant pairwise interactions ( linear regression: F = 15 . 8 , df = 1 , p = 0 . 001; Figure 1 ) . A similar trend was observed between ɛ and the primary distance ( i . e . , the number of residues separating the PNGSs in the amino acid sequence; F = 10 . 0 , df = 1 , p = 0 . 005 ) . In other words , positive interactions tended to be restricted to PNGSs that were sufficiently distant from one another in the HIV-1 envelope glycoproteins . Many pairwise interactions detected by the disequon model involved PNGS that were located in the V4 loop of the HIV-1 envelope protein gp120 ( i . e . , N406 , N411 , N413 ) . Also , several PNGSs were involved in multiple pairwise interactions ( e . g . , N234 , N295 , and N411 ) . The insertion of the sequon N411 in the V4 loop , for example , was involved in eight of the 13 significant pairwise interactions between nonoverlapping PNGS , which suggested that N411 has a broad influence on formation of a functional glycan shield . To reduce the computational complexity of the analysis while retaining our power to detect higher-order interactions , we restricted our network search to a subset of 17 PNGS that occurred at intermediate frequencies ( 20%–80% ) in the alignment ( Table S2 ) . Figure 2A summarizes the frequencies at which arcs connecting two PNGS in either direction occurred in a total of 25 , 000 Bayesian networks ( inferred from 250 replicate optimizations times 100 random samples from the alignment ) . Arcs between ten specific pairs of PNGS occurred in more than 67% of the networks generated from random samples . The next most frequent undirected arc occurred in only 47% of the networks ( Figure 2A ) . Consequently , we applied the ten arcs with strongest support towards assembling a majority-rule consensus Bayesian network . Figure 2B illustrates the consensus network assembled from the ten undirected arcs with support values above the threshold , which connected 14 of the 17 PNGSs . Several PNGSs were conditionally dependent on more than one other PNGS in the network , implying higher-order interactions that would not have been captured by the disequon model . The posterior-odds ratios ( see Materials and Methods ) associated with the consensus arcs N134–N136 and N332–N334 indicated that PNGSs were mutually exclusive at these sites , which in both cases overlapped by two residues in the amino acid sequence . This outcome was hardly surprising because it is impossible for two well-defined PNGSs to overlap by two residues . However , the majority of arcs in the consensus network represented long-range interactions . The most acute instance of this occurred between the PNGSs N295 , N362 , and N816 , in which the latter is located on the cytoplasmic tail of the transmembrane glycoprotein gp41 , and the other two are located on the outer surface of gp120 . This network analysis could not account for phylogenetic relationships between sequences . To identify potential effects of phylogeny in the consensus network , we generated networks for subsets of HIV-1 envelope sequences that were annotated as belonging to subtypes A , B , C , and D , or circulating recombinant forms CRF01 and CRF02 , using an MCMC-based procedure that was designed for inferring networks from small datasets . Because the number of CRF02 sequences ( n = 17 ) was far too small to perform any rigorous network analysis on 17 variables , the results from this network were omitted . Overall , five out of the ten arcs from the consensus network were recovered in more than one subtype-specific network ( Table 2 ) . This subset included every interaction that was identified by both the consensus network and the disequon model . The absence of the remaining consensus network interactions was possibly either caused by subtype-founder effects , or represented an artifact of limited sample size within subtypes . We mapped PNGS from the consensus network to the predicted three-dimensional structure of the folded glycoprotein gp120 ( Figure 3 ) . Because several regions of gp120 were truncated in the structural analysis ( e . g . , variable loop V1/V2 ) , only seven PNGSs from the consensus network ( N230 , N295 , N332 , N339 , N362 , N442 , and N465 ) could be mapped to the structural model [33] . Of the four arcs from the consensus network defined by these PNGSs , two represented positive interactions ( N332–N339 and N230–N442 ) and the remaining two negative interactions ( N362–N465 and N295–N442 ) . Only one of these four interactions ( N295–N442 ) had been previously detected by our disequon analysis . Although this was an insufficient sample for a robust comparison , the asparagine residues within PNGSs that participated in negative interactions were located closer together ( 8 . 7 Å and 10 . 8 Å ) than those in positive interactions ( 14 . 8 Å and 42 . 0 Å ) . This trend lent further support for our observation that negative interactions tended to occur between co-localized PNGSs , and positive interactions between distant PNGSs .
Although there is substantial evidence that the distribution of PNGSs in the HIV-1 envelope glycoproteins is a perpetually evolving phenotype , little is known about the complexities of how it responds to host-specific selection . The existence of negative interactions between PNGSs implies that there is more than one way for the glycan shield to adapt to the selective pressures of a given environment . To determine whether this prediction is borne out empirically , we evaluated the extent of convergent evolution of PNGSs in a longitudinal study of 11 macaques that were experimentally infected with a chimeric simian/human immunodeficiency virus strain ( SHIV-86P ) containing an HIV-1 subtype B–derived envelope coding region , as reported recently by Blay et al . [34] . Despite substantial divergence in the amino acid sequences from the replicate populations , convergent evolution occurred at several PNGSs ( N141 , N188 , N276 , N386 , N397 , and N462 ) , suggesting that the selective response was highly constrained at those positions . In other words , the selective advantage of these changes was apparently independent of the presence or absence of other PNGS in the envelope sequence . We have found no evidence in our study that these PNGSs are involved in any interactions . However , three out of the four PNGS at which highly divergent evolution occurred ( N136 , N234 , and N362 ) have been implicated by our study in interactions with other PNGSs . Hence , the complexity of the adaptive response of the glycan shield can be predicted by the interactions that we have identified between PNGSs . Moreover , we have found evidence of a novel association between the distance separating PNGSs and the type of interaction between them , which represents an additional layer of constraints on the glycan shield . Negative , or “mutually exclusive , ” interactions tended to occur between PNGSs that occupied similar locations on the glycoprotein . This tendency for overlapping or adjacent PNGS to be mutually exclusive may have been caused by either steric hinderance or functional redundancy . Because of the large molecular weight of N-linked glycans , steric hindrance could conceivably prevent glycans attached to overlapping PNGSs from occupying the same space [2] . However , it is possible for overlapping PNGSs offset by one residue to become simultaneously glycosylated [35] . Functional redundancy , on the other hand , implies that having additional glycans at a given location on the envelope glycoprotein would fail to provide any further protection from neutralization while accruing a debilitating cost to the normal functioning of the glycoprotein [36] . Either mechanism would enforce a maximum limit on the number of PNGSs in the sequence , which could be maximized by evenly distributing PNGSs across the protein surface or functional space . Positive interactions , on the other hand , tended to occur exclusively between PNGSs that were separated by greater distances . The observed relationship between spatial distance and the interaction value ( ɛ ) suggested a minimum distance threshold of 20 Å , separating glycans for them to become nonredundant , i . e . , to achieve complete coverage of the antigenic surface of gp120 ( Figure 1 ) . For comparison , high mannose and complex carbohydrates were estimated to extend from the glycoprotein surface to a distance of approximately 30–40 Å and to have a maximum diameter of about 15–40 Å [37] . Evidence of positive interactions between distant PNGS implies that the glycan shield is a biological gestalt , unable to function until it achieves complete coverage of HIV-1 envelope glycoproteins . These spatial constraints predicted by our study complements a similar constraint that was previously put forth on the basis of experimental results from Ohgimoto et al . [17] , in which the infectivity of a strain of SIV was sensitive to the cumulative depletion of N-linked glycans specifically when they were removed from a similar location on the gp120 glycoprotein . In other words , this experiment revealed a selective advantage for maintaining a minimum local density of glycans . Here we find evidence of similar constraints preventing the local density of glycans from exceeding a maximum threshold , and maintaining a minimum overall density of glycans on the HIV-1 envelope glycoproteins . The third variable loop ( V3 ) is an immunologically and functionally important region of the HIV-1 gp120 amino acid sequence ( reviewed in [38] ) . There are several conserved PNGSs located within or adjacent to V3 ( N289 , N295 , N301 , N332 , and N339 ) , which may function primarily to mask the large number of neutralizing antibody epitopes defined in this region . Additionally , the PNGSs N295 and N332 contribute to the formation of a glycan-dependent epitope that is recognized by the human monoclonal neutralizing antibody 2G12 [14] . In light of these factors , we are particularly interested in describing interactions involving PNGSs that are associated with V3 . For instance , our disequon analysis revealed a strong negative interaction between the PNGSs N295 and N337 , where the latter replaces N339 in a small number ( n = 21 ) of sequences belonging mostly to subtypes B and C . In the presence of N337 , the PNGS at N295 was intact in only two sequences , suggesting that N337 may provide an infrequently used alternative that can provide similar protection for epitopes on V3 , by shifting the N-linked glycan from N339 closer to the space normally occupied by N295 . A second alternative for N295 may also be provided by the PNGS N442 , which is also located near the base of V3 in the folded gp120 glycoprotein ( Figure 3 ) . An intriguing result from our phylogenetic and Bayesian network analyses on the distribution of PNGS in HIV-1 env sequences was the strong evidence of interactions involving PNGSs that were located in the V4 loop of gp120 ( N406 , N411 , N413 ) . Previous empirical studies have noted that the modification of PNGSs in V4 was prominent during adaptation of HIV-1 and SIV to a novel host [11 , 34 , 39] and that the addition or removal of PNGSs in V4 affected neutralization sensitivity in a context-dependent fashion , involving interactions with PNGSs located elsewhere in gp120 [11] . The V4 loop is an accessible and flexible region in the gp120 structure [33] . Glycans in V4 are apparently nonessential for CD4 binding , and the V4 region has not been associated with any other known biological function of gp120 [40] . Therefore , the V4 region may exist solely to facilitate viral escape as a component of the evolving glycan shield [41] . Using a disequon model , we found significant interactions between N411 and eight other PNGSs in the HIV-1 envelope glycoproteins , of which six were located outside of V4 ( Table 1 ) . Six of these eight interactions were positive , suggesting that N411 might represent a central component in a high-density configuration of the glycan shield . Indeed , sequences in which a PNGS was present at N411 contained a significantly greater number of PNGSs in the rest of the sequence ( generalized linear model , Wald test: χ12 = 8 . 44 , p < 0 . 004 ) . Curiously , one of these positive interactions implicated a PNGS ( N824 ) located on the cytoplasmic tail of the transmembrane envelope glycoprotein gp41 . This evidence of a functional interaction between PNGSs situated on the gp120 V4 loop extruding outward and the inner face of gp41 suggests that the glycosylation state can be transmitted between these noncovalently associated glycoproteins of the HIV-1 envelope , perhaps by inducing a cascade of conformational change , which has been postulated for amino acid substitutions and deletions within gp41 in previous studies [42 , 43] . The N-linked glycosylation of the HIV-1 envelope glycoproteins is one of the most important protective mechanisms to overcome in order to develop an effective neutralizing antibody-inducing vaccine . Because several N-linked glycosylation sites are relatively constant across HIV-1 subtypes , there is a great deal of interest in developing a carbohydrate-based antigen designed to elicit a humoral immune response to HIV-1 . However , even the N-linked glycan-dependent epitope of the archetypal neutralizing antibody 2G12 is prone to evolve to alternate glycans , as revealed in this study by the negative interactions involving N295 or N332 . It is imperative , therefore , to identify vulnerabilities in the form of functional constraints that limit the evolution of N-linked glycosylation sites in HIV-1 gp120 . Ultimately , the characterization of constraints in the glycan shield could enable us to drive an evolving population of HIV-1 into a corner . Although our phylogenetic and graphical models make very different assumptions about the evolution of PNGSs , we find that these complementary approaches consistently identified a set of interactions among N-linked glycosylation sites in HIV-1 envelope glycoprotein sequences . Furthermore , the results from both methods support the hypothesis that PNGSs that are located closer together in the glycoprotein tend to be mutually exclusive , and that positive interactions tend to occur between PNGSs that are more remote . Not only is this pattern intuitively appealing , but it may also represent a new and all-inclusive constraint on the evolution of PNGSs in the HIV-1 envelope sequence . Specifically , the tendency for negative interactions to occur primarily between spatially localized PNGSs implies that many N-linked glycans of divergent HIV-1 envelope glycoproteins are constrained to appear in very similar locations . Furthermore , any analysis on the frequencies of individual PNGSs in an alignment—especially those relating such quantities to a viral phenotype such as neutralization sensitivity—should count overlapping motifs as being effectively the same PNGS , because these pairs tend to manifest strong negative interactions that imply structural or functional redundancy .
We obtained an alignment of published full-length HIV-1 envelope sequences from the Los Alamos National Laboratory HIV database ( http://hiv-web . lanl . gov/content/hiv-db/ALIGN_04/ALIGN-INDEX . html ) . This alignment comprised 711 sequences , including 660 sequences representing all HIV-1 main ( M ) group subtypes , 44 sequences from group O , two sequences from group N , and four sequences from chimpanzee isolates of SIV . Conditional on the availability of patient or isolate annotation , this alignment had been prescreened for redundant sequences so that nearly every sequence represented a unique individual [44] . PNGSs were identified in the amino acid sequences by the occurrence of a sequence motif ( i . e . , sequon ) NX1 ( S/T ) X2 , where X corresponds to any amino acid other than proline [2] . The position-specific frequencies of PNGSs in the alignment are reported in Figure S1 . Any number of gaps in an aligned sequence was permitted to occur between residues within this motif . Amino acid sequence motifs defining overlapping PNGSs ( e . g . , NNSS ) were counted as two distinct occurrences . Codon positions that defined a PNGS in at least one sequence were removed from the nucleotide alignment , which was subsequently used to reconstruct the phylogeny by neighbor-joining [45] using the Tamura-Nei [46] distance measure . Nonparametric bootstrap support values for the branches of this tree are reported in Figure S2 . The HIV-1 envelope amino acid alignment was converted into binary sequences indicating the presence ( 1 ) or absence ( 0 ) of an asparagine ( N ) residue that initiated a PNGS at that position . We filtered all columns from the binary alignment in which no 1 entries occurred , and applied the remaining columns to the covarion and disequon model analyses that were implemented using the HyPhy batch language ( available from http://www . hyphy . org/pubs/PNGS ) [47] . The covarion model evaluated variation over time in the site-specific rates that PNGSs were gained or lost , i . e . , r1→0 and r0→1 , respectively . Each position in the binary alignment was permitted to switch between two hidden states , such that one state was on ( r0→1 , r1→0 > 0 ) and the second was off ( r0→1 , r1→0 > 0 ) . Switches between these hidden states occurred at instantaneous rates son and soff . Both sets of rates were allowed to vary among positions according to factors drawn from discretized one-parameter gamma distributions . Further details on the covarion model and the constrained alternative models are provided in Protocol S1 . For the disequon model analysis , we generated all pairwise combinations of columns , resulting in four possible binary paired-character states: {00 , 01 , 10 , 11} . Simultaneous substitutions at both sites were assumed to occur at a negligibly low rate , leaving eight possible substitution rates to parameterize . The full disequon model depended on four parameters ( Figure 4 ) : b1 and b2 , which quantified the asymmetry in the rate of loss over gain at the respective sites ( e . g . , b1 = r1•→0•/r0•→1• ) ; the difference ( d ) in the overall evolutionary rate between the first and second sites; and an interaction parameter ( ɛ ) . When ɛ > 1 , the gain of a PNGS at one site elevated the rate of gain at the other site , and the loss of a PNGS elevated the rate of loss at the other site . Conversely , when ɛ < 1 , the gain of a PNGS at one site elevated the rate of loss at the other site , and vice versa . We also evaluated a version of this model with an additional interaction parameter acting specifically on the rates r01→11 and r10→11 , decoupling effects of interactions on the coupled gain and loss of PNGSs . However , the additional parameter produced no significant improvement of likelihood and we proceeded with the simpler model . The disequon model was hence represented by the following time-reversible rate matrix: in which the rows list substitution rates from their respective states to the state indicated above each column , and the diagonal elements ( * ) assumed values such that each row summed to 0 . Note that estimation of the rate r00→10 is confounded by branch length estimates; hence , it was fixed at 1 . The stationary distribution for this model is given by πd ∝ {b1b2ɛ , b1 , b2 , ɛ} , normalized to sum to 1 . We fitted the disequon model to each pairwise combination of PNGSs from the alignment , using branch lengths that were constrained to be proportional to the lengths from the non-PNGS tree , given a global scaling factor . Pairwise combinations in which at least one of the four states was absent were excluded from the analysis , reducing the total number of comparisons from 49 , 952 to 6 , 455 pairs and improving the stability of model inference . A pair had a significant interaction component ( ɛ ≠ 1 ) if the likelihood of the full model was significantly greater than that of the nested model in which ɛ was constrained to 1 , i . e . , by evaluating the LRT against the asymptotic null χ2 distribution with 1 degree of freedom . We applied a Bonferroni correction to account for multiple comparisons . This procedure is far more conservative than alternative procedures such as the false discovery rate [48] . Using the false discovery rate would have also required accurate estimation of the distribution of p-values under the null hypothesis , which was limited by the complexity of the likelihood surface for this model . We chose a subset of PNGS that were present in at least 20% but fewer than 80% of the sequences in the alignment . This requirement for intermediate frequencies greatly reduced the number of PNGSs , and hence the total number of possible networks , while retaining statistical power for detecting intersite dependencies . Each PNGS was represented as a discrete ( binary state ) variable indicating the presence or absence of the N-linked glycosylation sequence motif at a given position in an amino acid sequence . Context-dependence between PNGSs were represented by directed arcs in a Bayesian network , so that an arc originating from A and terminating at B indicated that the probability of finding a PNGS at position B was conditionally dependent on whether or not a PNGS occurred at position A . Likewise , the absence of a directed arc indicated conditional independence between PNGSs . Our objective was therefore to estimate the joint probability distribution ( encoded by the structure of directed arcs in the Bayesian network ) that provided the best explanation for the distribution of PNGSs in the alignment of HIV-1 envelope sequences . To infer , or “learn , ” the structure of the network from the data , we used a parallel implementation of a greedy heuristic search algorithm with random restarts in Java [49] . We used a heuristic search algorithm because it was computationally infeasible to iterate over all possible networks ( ≈6 . 3 × 1052 possible networks for 17 PNGSs ) . Our greedy heuristic search algorithm was based on the K2 algorithm , which assumed that the dataset contained no missing values and that the prior probability distributions were uniform ( i . e . , such that the conditional probability P ( A = 1 | B = 1 ) was equally likely to assume any real value within the interval [0 , 1] ) [50] . Each search was initialized with a randomized network assembled by applying 100 modifications ( i . e . , addition , removal , or reversal of a directed arc ) to an unconnected set of nodes , provided that the graph remained acyclic . Subsequently , the search algorithm iteratively evaluated the relative improvement in the posterior probability of the network from the addition , removal , or reversal of a directed arc to the current network structure , and the best modification was incorporated into the network . This iterative process continued until no further improvement in posterior probability was possible . We applied this search algorithm to 100 random samples of 200 sequences from the alignment to evaluate the variation in the optimal network structure among sequences . The greedy search algorithm was applied to each sample with 250 random restarts to explore multiple local maxima in the scoring metric ( i . e . , posterior probability ) . Networks evaluated by the search algorithm were restricted to the subset of all possible networks in which each node had a maximum number of five parents . The restriction of the number of parent nodes to five or fewer per node was necessary to reduce the size of the search space . However , none of the locally optimal models found by our search algorithm included nodes with five parents , suggesting that the data favored simpler models . The number of occurrences of each arc , irrespective of its direction , was tabulated across all networks obtained by the search algorithm for every sample . From this table , we generated a majority-rule consensus network into which an undirected arc between the nodes A and B was incorporated if the sum of tabulated frequencies of the directed arcs A → B and B → A exceeded a threshold value of 50% . Posterior odds-ratios for each arc in the consensus network were calculated from 2 × 2 contingency tables of posterior parameters . For this calculation , undirected arcs in the consensus network were assigned directionality according to which directed arc had been sampled at a greater frequency . Undirected arcs in the consensus network were classified as representing either positive ( inclusive ) or negative ( exclusive ) associations between PNGS , as determined by calculating the posterior odds-ratios from the corresponding 2 × 2 contingency tables of posterior parameters . For example , the contingency table for the PNGSs N411 and N413 contained the following: from which the posterior-odds ratio was calculated as: indicating that N411 was only one-third as likely to occur in a sequence that also contained a PNGS at position N413 . Hence , an odds-ratio greater than 1 implied that the PNGSs were inclusive , whereas an odds-ratio less than 1 implied that they were mutually exclusive . Because of the limited number of sequences within the HIV-1 subtypes , our analysis of subtype-specific networks was carried out using an MCMC-based procedure that is designed for inferring networks from relatively small datasets [51] . When the amount of data is small relative to the number of network variables , an exceedingly large number of networks may explain the data equally well . Rather than attempting to find an optimal network , this procedure estimates the overall posterior probability for the presence of each arc given the data . To traverse the enormous network search space more efficiently , a hierarchical order of network variables is proposed at each step , corresponding to a subset of networks in which every node is preceded by its parent in the ordered list [51] . We applied this procedure with a coupled Metropolis-Hasting sampling algorithm with at least four chains [52] to analyze subtype data . We obtained structural coordinates for the HIV-1 glycoprotein gp120 in complex with a CD4 receptor from the Research Collaboratory for Structural Bioinformatics [33] . The location of PNGSs in the gp120 structure was visualized using the software package UCSF Chimera [53] . Note that several of the gp120 variable loops are absent from this structural prediction .
The accession numbers used in this paper are from Genbank ( http://www . ncbi . nlm . nih . gov/Genbank ) for [NNTSNNTSY outlier] subtype B sequence ( M17451 ) and from Protein Databank ( http://www . rcsb . org/pdb/home/home . do ) for folded CD4-bound gp120 protein ( 1G9M ) and for HIV-1 glycoprotein gp120 ( 1G9M ) . | Many viruses exploit the complex machinery of the host cell to modify their own proteins , by the enzymatic addition of sugar molecules to specific amino acids . These sugars , or “glycans , ” play several important roles in the infective cycle of the virus . The envelope of the human immunodeficiency virus type 1 ( HIV-1 ) , for example , becomes coated with so many glycans that the virus can become invisible to the protein-specific immune response of the host . Although some glycans are evolutionarily conserved , many others may be present within some hosts but absent in others , and may even appear or disappear over the course of an infection in a single host . To understand this variability , we have analyzed HIV-1 envelope sequences to identify cases where the presence of one glycan was dependent on the presence or absence of another ( called glycan–glycan interactions ) . We used two newly developed computational methods to detect these interactions , thereby providing conclusive evidence of a new fundamental pattern: the glycans that exclude each other tend to occur near the same spot on the envelope , whereas glycans that occur together tend to be far apart . | [
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] | 2007 | Evolutionary Interactions between N-Linked Glycosylation Sites in the HIV-1 Envelope |
The monosaccharide N-acetylglucosamine ( GlcNAc ) is a major component of microbial cell walls and is ubiquitous in the environment . GlcNAc stimulates developmental pathways in the fungal pathogen Candida albicans , which is a commensal organism that colonizes the mammalian gut and causes disease in the setting of host immunodeficiency . Here we investigate GlcNAc signaling in thermally dimorphic human fungal pathogens , a group of fungi that are highly evolutionarily diverged from C . albicans and cause disease even in healthy individuals . These soil organisms grow as polarized , multicellular hyphal filaments that transition into a unicellular , pathogenic yeast form when inhaled by a human host . Temperature is the primary environmental cue that promotes reversible cellular differentiation into either yeast or filaments; however , a shift to a lower temperature in vitro induces filamentous growth in an inefficient and asynchronous manner . We found GlcNAc to be a potent and specific inducer of the yeast-to-filament transition in two thermally dimorphic fungi , Histoplasma capsulatum and Blastomyces dermatitidis . In addition to increasing the rate of filamentous growth , micromolar concentrations of GlcNAc induced a robust morphological transition of H . capsulatum after temperature shift that was independent of GlcNAc catabolism , indicating that fungal cells sense GlcNAc to promote filamentation . Whole-genome expression profiling to identify candidate genes involved in establishing the filamentous growth program uncovered two genes encoding GlcNAc transporters , NGT1 and NGT2 , that were necessary for H . capsulatum cells to robustly filament in response to GlcNAc . Unexpectedly , NGT1 and NGT2 were important for efficient H . capsulatum yeast-to-filament conversion in standard glucose medium , suggesting that Ngt1 and Ngt2 monitor endogenous levels of GlcNAc to control multicellular filamentous growth in response to temperature . Overall , our work indicates that GlcNAc functions as a highly conserved cue of morphogenesis in fungi , which further enhances the significance of this ubiquitous sugar in cellular signaling in eukaryotes .
Cellular differentiation is an essential process for the development and growth of complex multicellular eukaryotic organisms . Similarly , many unicellular eukaryotic organisms undergo a program of cellular differentiation to produce a new cell type that is specialized for survival in a distinct environmental niche . In response to environmental stimuli , the family of thermally dimorphic fungal pathogens undergoes a program of cellular differentiation to transition between a saprophytic soil form and a parasitic host form [1] . The soil form is comprised of multicellular filaments that produce infectious spores . The parasitic form for the majority of thermally dimorphic fungi consists of a unicellular yeast form that is capable of evading host immune defenses . Temperature is the predominant environmental cue that promotes cellular differentiation of thermally dimorphic fungi; however , additional factors including CO2 , reactive oxygen species , and steroid hormones are also thought to influence morphogenesis [2]–[5] . The ability of thermally dimorphic fungi to transition between two distinct morphological states in response to environmental stimuli is important for the maintenance of their disparate lifestyles as soil saprobes and mammalian pathogens [6] . Thermally dimorphic fungal pathogens , such as Histoplasma capsulatum and Blastomyces dermatitidis , grow in the soil in a filamentous or “mold” form that produces vegetative spores known as conidia . Upon inhalation of hyphal fragments or conidia by a human host , and subsequent growth at mammalian body temperature , H . capsulatum and B . dermatitidis transition into a budding yeast form capable of growth and pathogenesis in mammals . Since thermally dimorphic fungi can persist in mammals after an acute infection is resolved , it is thought that the parasitic host form returns to the soil after the death of infected animal hosts , thus facilitating a transition to the filamentous form and serving to maintain an infectious reservoir [7]–[9] . Maintenance of an environmental reservoir is crucial for the pathogenic lifestyle of thermally dimorphic fungi since these organisms are not directly transmitted between mammalian hosts [10] . Recently , some progress has been made in understanding the molecular mechanisms by which environmental signals stimulate morphological transitions in thermally dimorphic fungi . Comparative gene expression profiling of H . capsulatum has revealed that approximately 15% of predicted genes are differentially expressed between the two morphological forms ( multicellular filaments and unicellular yeast cells ) , indicating that a significant fraction of transcripts exhibit yeast-phase or filamentous-phase enrichment expression patterns [11]–[13] . In addition , forward genetic screens have identified regulators of yeast- and filamentous-phase growth in thermally dimorphic fungi , namely , the Ryp ( required for yeast-phase growth ) master regulators ( Ryp1 , Ryp2 , and Ryp3 ) , the histidine kinase Drk1 ( dimorphism-regulating kinase 1 ) , and the GATA-family transcriptional regulator Sre1/SreB [12] , [14]–[18] . However , it remains to be elucidated how these regulators sense and integrate environmental signals into phenotypic and genotypic outputs . One challenge in studying the molecular events involved in the morphogenesis of thermally dimorphic fungi has been establishing a robust and synchronous morphological phase transition in vitro . For example , in laboratory cultures of H . capsulatum , the conversion between yeast cells and filaments is recapitulated by switching the temperature from 37°C to room temperature ( RT ) [5] , [19] . The switch is bidirectional , so H . capsulatum filaments can be switched to yeast cells by shifting the temperature in the opposite direction ( RT to 37°C ) . Under these laboratory conditions , temperature is sufficient to promote morphogenesis; however , the interconversion between yeast cells and filamentous cells in the laboratory is slow and asynchronous , suggesting that other environmental cues that promote morphogenesis are missing from in vitro culture . Establishing a robust and synchronous phase transition of thermally dimorphic fungi in vitro would allow an easier and more robust examination of the temporal series of events that occurs during morphogenesis , and permit identification of factors important for cellular differentiation . To identify potential inducers of morphogenesis in the thermally dimorphic fungi , we contemplated developmental pathways in other fungi . The yeast-to-filament transition is well studied in the human commensal fungus Candida albicans , and can be induced by a variety of signals [20] . For example , the ubiquitous monosaccharide N-acetylglucosamine ( GlcNAc ) is known to promote filamentation through an unidentified pathway in C . albicans [21] . Fungi are likely to encounter environmental sources of GlcNAc since this carbohydrate is a major component of insect exoskeletons and bacterial peptidoglycan . Additionally , the innermost layer of the fungal cell wall is composed of chitin , which is a polymer of β1–4 linked GlcNAc that undergoes turnover during the remodeling of the cell wall that accompanies cell division . Thus , GlcNAc derived from chitin that is released by growing fungal cells is also likely to be available extracellularly . GlcNAc is an interesting monosaccharide to promote cell fate determination in fungi as it has been implicated as a conserved signaling molecule across all kingdoms of life including its ability to promote morphogenesis in bacteria [22] and also function as a dynamic intracellular signaling modification akin to phosphorylation in metazoans ( O-GlcNAc signaling ) [23] . Herein we describe the role of GlcNAc as a potent inducer of the yeast-to-filamentous phase transition at RT in thermally dimorphic fungi . Culturing H . capsulatum and B . dermatitidis yeast cells in the presence of exogenous GlcNAc promoted a rapid and more synchronous phase transition of yeast cells to filaments . GlcNAc also promoted faster growth of differentiated H . capsulatum filaments at RT , indicating that GlcNAc influences both the morphogenesis and growth rate of H . capsulatum filaments . In addition to implicating GlcNAc as a critical signal for filamentation , these studies allowed us to examine the temporal regulation of the H . capsulatum transcriptome during morphogenesis in a synchronous population of cells . The resulting analysis provided the first view of transcriptional changes of a thermally dimorphic fungus undergoing yeast-to-filament differentiation and revealed candidate genes that may play roles in establishing and maintaining the filamentous growth program . Furthermore , we found that GlcNAc-promoted filamentation of H . capsulatum is dependent on two genes ( NGT1 & NGT2 ) that encode putative GlcNAc major facilitator superfamily ( MFS ) transporters . These proteins have homology to C . albicans Ngt1 , the only previously characterized eukaryotic GlcNAc transporter [24] . We show that H . capsulatum Ngt1 and Ngt2 can each serve as a GlcNAc transporter . Additionally , NGT1 and NGT2 were required for efficient yeast-to-filament conversion even in the absence of exogenously added GlcNAc . These data suggest that the ability to sense and respond to endogenous GlcNAc through Ngt transporters could be a critical regulatory step during filamentous growth . Finally , taken together with previous work in Candida species , our results indicate that GlcNAc functions as a highly conserved cue to signal morphogenesis in the fungal kingdom .
To determine whether GlcNAc can stimulate morphogenesis of thermally dimorphic fungi , we grew H . capsulatum and B . dermatitidis yeast cells in liquid culture in the presence or absence of exogenous GlcNAc ( HMM/100 mM GlcNAc , see Materials and Methods for complete media descriptions and note that HMM medium contains residual 10 mM glucose from the F12 nutrient supplement even before further supplementation of the sugar source ) at 37°C or at RT . GlcNAc did not affect yeast-phase morphology at 37°C ( Figure 1 A , B ) , but it triggered a remarkably rapid transition of yeast cells to filaments at RT ( Figure 1 C , D ) . This robust filamentation was in stark contrast to the usual laboratory transition experiment in glucose medium , where it takes weeks to yield a large , homogenous population of filaments from yeast cells ( Figure 1 C , D ) . To assess the concentration-dependence of GlcNAc-enhanced filamentation , we plated serial dilutions of H . capsulatum yeast cells at RT on standard glucose medium containing increasing concentrations of GlcNAc . The enhanced filamentation of H . capsulatum at RT in response to GlcNAc occurred at micromolar concentrations , as evidenced by larger colony diameter and fuzzy colony morphology that was in contrast to yeast cells grown in these media conditions at 37°C , which exhibited no morphological changes ( Figure 2 A , B ) . Since these concentrations are too low for GlcNAc to be utilized as the major carbon source , these data suggested that H . capsulatum cells may be sensing GlcNAc , or one of its catabolic byproducts , to promote morphological differentiation . To confirm that supplementing cultures with an additional carbon source was not sufficient to promote filamentation , we grew H . capsulatum yeast cells in equimolar amounts of glucose or GlcNAc and monitored their conversion to filaments at RT . Cells grown in additional glucose did not show enhanced filamentation at RT in comparison to GlcNAc-grown cells ( Figure S1 ) , indicating that simply providing an additional carbon source during aerobic growth is not sufficient to promote morphogenesis of H . capsulatum . Furthermore , the ability of GlcNAc to promote filamentous growth in H . capsulatum was a unique property of GlcNAc as other carbohydrates , including fructose and the amino sugar glucosamine ( GlcN ) , did not enhance morphogenesis at RT ( Figure 2 C , D ) . In addition to the ability of GlcNAc to promote a faster yeast-to-filament transition , we also examined the effect of GlcNAc on yeast and filamentous cell growth rates at RT . First , we examined the growth of yeast cells at RT before they converted to filaments in GlcNAc and glucose media . We observed that yeast cells grew at a very slow rate at RT prior to conversion to filaments irrespective of whether GlcNAc was present in the medium ( Figure S2 A , B ) . Thus , GlcNAc does not affect the growth rate of yeast cells at RT before their conversion to filaments . However , monitoring the rate of increase in diameter of filamentous colonies revealed that GlcNAc did augment the growth rate of filaments at RT ( Figure S2C ) even at low concentrations ( 10 mM GlcNAc ) . These data suggested that in addition to promoting a faster yeast-to-filament transition , GlcNAc also enhanced the growth rate of filamentous cells . Overall , these conversion and growth experiments show that GlcNAc promotes a specific , rapid , and synchronous switch of thermally dimorphic fungal yeast cells to filaments at RT and that growth in the filamentous form is stimulated by GlcNAc . The ability of GlcNAc to promote a faster and more synchronous transition of H . capsulatum yeast cells to filaments at RT enabled us to examine the transcriptome of H . capsulatum cells as they underwent the transition from the yeast form to filaments using whole-transcriptome microarray profiling . Previous transcriptional profiling experiments that defined yeast- and filament-enriched transcripts in H . capsulatum have profiled the transcriptomes of fully differentiated yeast cells or filaments grown at 37°C or RT , respectively [11]–[13] , which is distinct from deciphering the dynamic changes in transcript expression patterns in cells undergoing a morphological transition . To identify transcripts that are regulated during morphological differentiation as well as to begin to understand how H . capsulatum responds to GlcNAc to promote filamentation , we monitored the transcriptome of yeast cells as they began to form filaments at RT in the presence and absence of GlcNAc . We grew yeast cells at 37°C in standard HMM glucose medium to early-log phase ( t = 0 ) , resuspended the cells in fresh glucose or GlcNAc medium ( HMM/100 mM GlcNAc ) , and then shifted the yeast cells from 37°C to RT ( see Figure 3A ) to monitor transcriptional changes that occurred during the yeast-to-filament transition . For technical reasons , two time-courses were performed: the first ( 1 h , 4 h , 24 h ) to capture early transcriptional changes , and the second ( 4 d , 7 d ) to capture later transcriptional changes ( see Figure 3A ) . As a point of comparison , yeast cells were also grown at 37°C in GlcNAc ( HMM/100 mM GlcNAc ) or glucose medium for the duration of the time-course; these samples allowed us to identify genes that were induced by growth in GlcNAc at both RT and 37°C , independent of temperature . At each timepoint , RNA was harvested and cellular morphology was examined by microscopy . Morphological examination of yeast cells shifted to RT revealed that GlcNAc-grown cells were predominantly filamentous after 4 days of growth at RT while glucose-grown cells remained predominantly yeast-like for the duration of the time-course ( Figure S3A ) . Yeast cells grown at 37°C in either GlcNAc or glucose medium remained as budding yeast for the duration of the time-course ( Figure S3B ) . Gene expression ratios from cells grown at RT in the presence of GlcNAc or glucose were subjected to k-means clustering , which revealed distinct cases of dynamically controlled transcript expression during morphogenesis . Although a small number of genes were induced or repressed only in glucose or in GlcNAc medium ( e . g . , Groups 1 , 4 , 8 , and 9 , respectively; Figure 3B ) , the majority of genes showed similar patterns of expression over replicate time courses in the presence of both sugars ( Figure 3B ) . Namely , early repressed , late repressed , early induced , late induced , and GlcNAc induced transcript expression patterns emerged as yeast cells transitioned to filaments in GlcNAc and glucose media ( Figure 3B ) . Overall , these data highlighted the complex reprogramming that yeast cells employ during cellular differentiation . Closer examination of the identities of temporally regulated transcripts during morphogenesis uncovered genes that may play a role in establishing the filamentous growth program . Factors involved in fatty acid biosynthesis ( FAS1 , FAS2 , ACC1 , & OLE1 ) [25] , which could serve to alter plasma membrane fluidity in response to a change in temperature or cell wall structure , were upregulated in glucose- and GlcNAc-grown yeast cells transitioning to filaments ( Figure 4A ) . We also found genes upregulated during cellular differentiation that could play a role in signal transduction including HMK1 , which is predicted to encode a mitogen activated protein kinase , RYP4 and CPH1 , which are predicted to encode Zn2C6 and C2H2 transcription factors , respectively , and PHK1 , a predicted two component sensor kinase . Notably , the S . cerevisiae homolog of HMK1 ( named KSS1 ) is involved in signal transduction pathways that control filamentous growth [26] . Interestingly , many of the transcripts depicted here ( Figure 4A ) that were upregulated during morphogenesis are not strongly enriched in fully differentiated filaments , further suggesting that these transcripts may play a role in establishing , but not maintaining , the filamentous growth program . To put the transcriptional expression patterns observed during morphogenesis in context with what is already known about transcript levels in fully differentiated filaments , we examined the expression patterns of canonical filament-phase specific ( FPS ) transcripts ( MS95 , TYR1 , HYD1 , EFG1 , NIR1 , and FBC1 [11] , [12] ) during morphogenesis . Transcript levels of MS95 were upregulated immediately ( t = 1 h ) upon shifting yeast cells to RT in both GlcNAc and glucose growth conditions , suggesting that MS95 is responsive to the decrease in temperature , either at an extremely early point in the yeast-to-filament transition or even before that developmental program has initiated ( Figure 4B ) . MS95 is homologous to the C . albicans DDR48 gene , which is a stress-response gene that is important for filamentous growth in C . albicans [27] . In contrast to MS95 , upregulation of the predicted tyrosinase-encoding TYR1 transcript in yeast cells transitioning to filaments was not observed at early timepoints after temperature shift ( 1 h or 4 h; Figure 4B ) , signifying that TYR1 may be induced once the filamentous growth program has initiated , and is not directly regulated by temperature . To further examine the transcriptional expression kinetics of TYR1 during filamentation , we introduced a GFP reporter construct in which expression of GFP was controlled by approximately 1 kilobase ( kb ) of the TYR1 promoter ( PTYR1 - GFP ) into H . capsulatum and monitored levels of GFP by confocal microscopy as yeast cells transitioned to filaments at RT in glucose or GlcNAc medium . In accordance with our microarray data , yeast cells converting to filaments in GlcNAc medium exhibited earlier PTYR1 - GFP expression ( robust GFP signal detected by 36 h ) than glucose-grown cells ( Figure S4 ) . Furthermore , PTYR1 - GFP expression was not detected in yeast cells grown at 37°C ( data not shown ) , nor was PTYR1 - GFP expression immediately observed upon the transition of yeast cells to RT ( t = 12 h or 20 h , Figure S4 ) . Together , these data confirm the enhanced rate of filamentation in GlcNAc medium , and indicate that the TYR1 transcript is turned on during the filamentous growth program and not directly in response to changes in temperature . The FPS HYD1 , EFG1 , NIR1 , and FBC1 transcripts , in contrast to MS95 and TYR1 , were not robustly upregulated in either glucose- or GlcNAc-grown yeast cells transitioning to filaments despite being highly enriched in fully differentiated glucose-grown filaments ( Figure 4B ) . Thus , HYD1 , EFG1 , NIR1 , and FBC1 transcripts may not be involved in establishment of the filamentous state , and may instead play a role in maintenance of this cell type . We also examined the temporal expression patterns of canonical yeast-phase specific ( YPS ) transcripts in our transcriptional time-course with the expectation that we would see expression of YPS transcripts such as CBP1 , SID1 , SSU1 , YPS21 , CATB , and MFS2 [11] , [28]–[30] downregulated as the yeast cells converted to filaments . SSU1 , YPS21 , CATB , and MFS2 transcripts behaved as we expected , being unchanged or downregulated in expression upon shifting yeast cells to RT ( Figure 4B ) . CBP1 and SID1 , however , were unexpectedly more upregulated in GlcNAc- versus glucose-grown yeast cells transitioning to filaments ( Figure 4B; upregulation of CBP1 was confirmed by qRT-PCR ( data not shown ) ) . CBP1 , a gene of unknown molecular function , and SID1 , a monooxygenase involved in siderophore biosynthesis , are required for the virulence of H . capsulatum yeast cells [31]–[33] . The upregulation of CBP1 and SID1 transcripts in GlcNAc-grown filaments may reflect a previously unappreciated function for these transcripts in the biology of filamentous cells . Additionally , since GlcNAc-stimulated filaments also grow more rapidly than glucose-grown filaments ( see Figure S2C ) , these data could reflect a correlation between increased growth rate of cells and increased expression of CBP1 and SID1 . The unexpected expression patterns of these previously identified phase-specific genes highlight the importance of investigating the temporal regulation of transcripts during morphogenesis . In addition to the aforementioned transcripts temporally regulated in both GlcNAc- and glucose-grown yeast cells transitioning to filaments , we also identified a class of transcripts robustly induced only in GlcNAc medium ( Group 1 , Figure 3B ) . This group of genes was of interest , as it represents a means to understand the mechanism of GlcNAc-promoted filamentation . Further analysis of GlcNAc-induced genes using hierarchical clustering identified a subset of genes that is robustly induced in GlcNAc but not glucose medium at RT ( Figure 5A ) . Whereas many of the GlcNAc-induced transcripts are of unknown function , we noted that OGA1 was particularly intriguing because it could play a signaling role in GlcNAc-promoted filamentation . OGA1 encodes a putative O-GlcNAcase with homology to the human OGA enzyme that cleaves the O-GlcNAc signaling modification from serine and threonine residues [23] . This modification is involved in a variety of signaling processes in metazoan cells [34] , but has not been functionally investigated in fungal cells . OGA1 has not previously been identified as a filament-enriched transcript [12] and is induced during the rapid and synchronous transition to filaments in GlcNAc medium . Therefore , we hypothesize that it could play a role in the robust morphologic transition to filaments that occurs in GlcNAc-treated cells . Of note , the H . capsulatum homologs of GIG1 and the galactose catabolic genes were not found to be induced by GlcNAc in H . capsulatum as they are in C . albicans [35] , indicating that their regulation may not be significant for GlcNAc-promoted filamentation of thermally dimorphic fungi . GlcNAc also induced the expression of putative GlcNAc utilization genes in H . capsulatum , including a GlcNAc transporter ( NGT1 ) , GlcNAc hexokinase ( HXK1 ) , GlcNAc-6-phosphate deacetylase ( DAC1 ) , and GlcN-6-phosphate deaminase/isomerase ( NAG1; Figure 5 A , B and see Figure S5 ) . These genes were induced in GlcNAc at both RT and 37°C independent of cellular morphology ( Figure 5B ) . H . capsulatum Ngt1 , Hxk1 , Dac1 , and Nag1 are the best BLASTP hits to the functionally characterized C . albicans GlcNAc utilization machinery ( see Materials and Methods ) [24] , [36] , [37] . Analysis of the genomic positions of H . capsulatum NGT1 , HXK1 , DAC1 , and NAG1 genes showed that they are clustered in a 75 kb region in the H . capsulatum genome similarly to the C . albicans NAG1 , DAC1 , and HXK1 GlcNAc catabolic genomic cluster [38] ( see Figure S6 and Table S6 ) . We identified a fifth putative GlcNAc utilization gene ( HISTO_ZL . Contig1131 . fgenesh_plus . 101 . final_new ) by its location in the H . capsulatum GlcNAc utilization genomic cluster ( Figure S6 and Table S6 ) and its transcriptional induction by GlcNAc ( Figure 5B ) . This gene , which we named GIT7 ( GlcNAc-Induced Transcript 7 ) , is predicted to encode a β-hexosaminidase domain ( Panther Accession: PTHR30480 ) . Despite the conservation of Git7 across many fungal species , including C . albicans , Aspergillus fumigatus , and B . dermatitidis , the biological function of Git7 in GlcNAc utilization is unknown . Together , these data suggest that the H . capsulatum genome encodes and transcribes all of the genes known to be necessary for GlcNAc catabolism as well as an additional uncharacterized gene , GIT7 , which could be involved in GlcNAc utilization . After identifying H . capsulatum Ngt1 , we also noticed a second previously uncharacterized gene ( HISTO_ER . Contig17 . eannot . 1311 . final_new ) with strong sequence homology to the C . albicans Ngt1 transporter by BLASTP analysis ( E = 8 . 2×10−90 ) . Since this gene is predicted to encode a second Ngt-like transporter in H . capsulatum , we named it Ngt2 . Similarly to the C . albicans Ngt1 [24] , Ngt2 is predicted to be a MFS transporter ( Interpro Accession: IPR011701 ) with 12 transmembrane-spanning regions . However , in contrast to NGT1 , NGT2 mRNA is not robustly induced by GlcNAc ( Figure 5B ) nor is NGT2 clustered in the genome near other H . capsulatum GlcNAc utilization genes ( see Figure S6 and Table S6 ) . The presence of two putative GlcNAc transporters in the H . capsulatum genome ( NGT1 & NGT2 ) is surprising as C . albicans requires only one transporter , Ngt1 , to transport GlcNAc across its cell membrane [24] . To determine the prevalence of multiple GlcNAc transporters across fungal species , we assessed the phylogenetic conservation of H . capsulatum Ngt1 and Ngt2 . We used Bayesian analysis to build a phylogenetic tree with aligned BLASTP homologs to H . capsulatum Ngt1 and Ngt2 ( E≤1×10−5 ) from 20 Ascomycetes and Basidiomycetes species with sequenced genomes ( Figure S7 ) . From this analysis , an Ngt1/Ngt2 clade was identified and the phylogenetic model was simplified and then rebuilt to include only species with Ngt1 or Ngt2 orthologs ( Figure 6 and Table S5 ) . Ngt1 orthologs were found throughout the Ascomycetes; notably , however , the model yeast S . cerevisiae lacks a homolog to Ngt1 and experimentally has been shown to be unable to efficiently transport GlcNAc across its cell membrane [24] . Conversely , the presence of Ngt2 in fungi is more restricted than the occurrence of Ngt1 , with Ngt2 orthologs found only in the Onygenales ( H . capsulatum , B . dermatitidis , Coccidioides spp . , Trichophyton verrucosum , and Uncinocarpus reesii ) and Eurotiales ( Penicillium marneffei and Aspergillus spp . ) orders of Ascomycetes ( Figure 6 ) . Many of the species that have multiple identifiable GlcNAc transporters ( i . e . , Ngt1 and Ngt2 ) are human fungal pathogens ( H . capsulatum , B . dermatitidis , Coccidioides spp . , T . verrucosum , A . fumigatus , and P . marneffei ) , which is interesting given that the majority of characterized Ascomycetes are plant pathogens or plant saprobes [39] . To investigate whether H . capsulatum Ngt1 and Ngt2 are capable of transporting GlcNAc , we expressed H . capsulatum NGT1 and NGT2 in the C . albicans ngt1Δ strain , which is unable to grow in medium where GlcNAc is the sole carbon source [24] . We overexpressed either H . capsulatum NGT1 or NGT2 in the C . albicans ngt1Δ mutant and examined the ability of these strains to grow in GlcNAc medium as compared to vector control strains . Expression of either H . capsulatum NGT1 or NGT2 in the C . albicans ngt1Δ mutant conferred growth on GlcNAc medium ( Figure 7A ) , indicating that both H . capsulatum Ngt1 and Ngt2 can mediate GlcNAc transport independently . As expected , complementation of the C . albicans ngt1Δ mutant with either H . capsulatum NGT1 or NGT2 did not affect growth on other carbon sources including glucose and galactose ( Figure 7A ) . To probe whether NGT1 and NGT2 function in GlcNAc transport and utilization in H . capsulatum , we attempted to disrupt each gene , but were unsuccessful since targeted gene disruption in H . capsulatum is highly inefficient . Thus we used RNA interference ( RNAi ) to deplete levels of NGT1 and NGT2 transcripts . We confirmed knockdown of NGT1 and NGT2 transcripts by qRT-PCR and noted that wild-type levels of NGT1 mRNA were dependent on NGT2 whereas depleting levels of NGT1 had little effect on NGT2 transcript levels ( Figure S8 A , B ) . Nucleotide regions that were unique to either NGT1 or NGT2 were chosen for targeting by RNAi to minimize the possibility of cross-silencing of NGT1 by the NGT2 RNAi construct , or vice versa . With NGT1 and NGT2 RNAi strains in hand , we evaluated the ability of these strains to grow in medium where GlcNAc was the only carbohydrate source . We grew vector control , NGT1 , and NGT2 RNAi strains in minimal medium ( 3M ) using either GlcNAc or glucose as the only carbohydrate source . As predicted , NGT1 and NGT2 RNAi strains exhibited no growth defects in glucose medium , indicating that NGT1 and NGT2 do not affect overall fitness of H . capsulatum at 37°C ( Figure 7B ) . However , in medium where GlcNAc was the only carbohydrate source , both NGT1 and NGT2 RNAi strains were unable to achieve the same growth density as control cells ( Figure 7C ) . In contrast , the baseline level of growth exhibited by H . capsulatum in minimal medium containing no exogenous sugar source was indistinguishable for NGT1 and NGT2 RNAi strains and controls ( the carbon source for these cells is presumed to be the proline and cystine present in 3M minimal media; Figure 7D ) . Given that H . capsulatum cells respond to GlcNAc by upregulating GlcNAc utilization genes ( Figure 5B ) , we predicted that NGT1 and NGT2 RNAi strains would be defective in the upregulation of NAG1 , DAC1 , and NGT1 transcripts in response to GlcNAc . We first examined the responsiveness of NGT1 and NGT2 expression levels to GlcNAc . Whereas NGT1 is induced approximately 13 fold by GlcNAc in control cells , GlcNAc induction of NGT1 is reduced in strains that target either NGT1 or NGT2 by RNAi ( Figure 8A ) . In contrast , as observed by microarray and qRT-PCR , the expression level of NGT2 was only minimally affected by GlcNAc ( Figure 5B and 8B ) , and was not dependent on NGT1 ( Figure 8B ) . Maximal induction of NAG1 and DAC1 transcripts by GlcNAc was abolished in NGT1 and NGT2 RNAi strains ( Figure 8 C , D ) , suggesting that Ngt1 and Ngt2 play a role in GlcNAc catabolism and utilization in H . capsulatum . Interestingly , we also noticed that NGT1 RNAi strains exhibited a slight defect in upregulation of the GlcNAc catabolic genes NAG1 and DAC1 even in the absence of adding exogenous GlcNAc to the medium ( Figure S9 A , B ) . These data support the idea that cells might scavenge endogenous GlcNAc that becomes available as cells divide ( i . e . , from cell wall turnover during growth in glucose as the major carbon source ) and indicate that NGT1 is required for this process . In sum , these data indicated that Ngt1 and Ngt2 most likely contribute to GlcNAc catabolism in H . capsulatum by mediating GlcNAc transport . In addition to examining the role of NGT1 and NGT2 in regulating genes involved in GlcNAc catabolism , we also examined whether they regulate the expression of GlcNAc-induced transcripts ( Figure 5A ) that do not have a predicted role in GlcNAc catabolism . We examined the upregulation of PTR2 and OGA1 transcripts in response to GlcNAc in the NGT1 and NGT2 RNAi strains by qRT-PCR . We observed that OGA1 expression was dependent on NGT1 and NGT2 while PTR2 expression was dependent only on wild-type levels of NGT2 ( Figure S10 ) . Similarly to the GlcNAc catabolic genes NAG1 and DAC1 , OGA1 expression was dependent on NGT1 even in the absence of exogenous GlcNAc ( Figure S9 C , D ) , providing more evidence that Ngt1 influences the expression of GlcNAc-induced transcripts even when glucose is the major carbon source . In C . albicans , GlcNAc-mediated filamentation is dependent on Ngt1 , but independent of Hxk1 [24] , [40]; Hxk1 is required for catabolism of GlcNAc as a carbon source and utilization of GlcNAc in glycan biosynthesis ( see Figure S5 ) . These data indicate that GlcNAc is likely being recognized intracellularly by C . albicans as opposed to being catabolized or utilized in glycan biosynthesis to promote filamentous growth . Furthermore , in H . capsulatum we found that Ngt1 and Ngt2 were necessary for the induction of transcripts that were upregulated during the GlcNAc-promoted yeast-to-filament transition . Thus , to investigate the role of H . capsulatum Ngt1 and Ngt2 in morphogenesis , we first confirmed that expression of H . capsulatum NGT1 or NGT2 in the C . albicans ngt1Δ strain restored filamentation in response to GlcNAc ( Figure S11 ) . Next , we evaluated whether the H . capsulatum NGT1 and NGT2 RNAi yeast cells were defective in GlcNAc-induced filamentation . Vector control , NGT1 , and NGT2 RNAi yeast cells grown at 37°C were inoculated into either HMM glucose medium or HMM glucose medium supplemented with 10 mM GlcNAc and switched to RT to monitor their conversion to filaments over time by live-cell imaging . Depletion of NGT1 or NGT2 transcripts resulted in a dramatically slower conversion of yeast cells to filaments in GlcNAc medium as compared to vector control strains ( Figure 9 ) , indicating that NGT1 and NGT2 mediate GlcNAc-promoted filamentation . To investigate whether NGT-mediated GlcNAc filamentation was dependent on the catabolism or utilization of GlcNAc by H . capsulatum cells , we depleted transcript levels of the GlcNAc kinase , HXK1 , using RNAi ( Figure S8C ) . Depletion of HXK1 severely reduced the ability of H . capsulatum cells to grow in minimal medium ( 3M ) containing GlcNAc as the only carbohydrate source ( Figure S12A ) , demonstrating that HXK1 functions as a GlcNAc kinase during catabolism . Next , we evaluated the ability of HXK1 RNAi yeast cells to filament in response to GlcNAc and noted no defect in the ability of HXK1 RNAi yeast cells to transition to filaments in response to GlcNAc as compared to vector control cells ( Figure S12 B , C ) . Thus , in H . capsulatum NGT-mediated filamentation in response to GlcNAc does not require GlcNAc catabolism or utilization . Unexpectedly , NGT1 and NGT2 RNAi yeast cells also exhibited a defect in the ability to convert to filamentous cells at RT in glucose medium ( Figure 10 ) , indicating that Ngt1 and Ngt2 play a general role in mediating the yeast-to-filament transition at RT in H . capsulatum . We hypothesized that the GlcNAc polymer chitin found in fungal cell walls could be a source of endogenous GlcNAc for H . capsulatum cells; thus , we examined whether chitin could stimulate morphogenesis similarly to GlcNAc . Indeed , H . capsulatum yeast cells grown in the presence of chitin more robustly converted to filaments at RT ( Figure S13 ) , suggesting a potential endogenous source of GlcNAc that H . capsulatum cells could be monitoring . Taken together , our experiments indicate that exogenously added GlcNAc stimulates a morphogenetic pathway in H . capsulatum that facilitates temperature-dependent filamentous growth in a Ngt1- and Ngt2-dependent manner . Additionally , our data reveal that Ngt1 and Ngt2 are required for efficient filamentation in the absence of GlcNAc supplementation , likely due to the role of endogenous GlcNAc in the regulation of morphogenesis .
Here we demonstrated that the ubiquitous amino sugar GlcNAc robustly promotes morphogenesis of the thermally dimorphic fungal pathogens , H . capsulatum and B . dermatitidis . Historically , temperature has been thought of as the only signal necessary to induce morphogenesis of thermally dimorphic fungi; however , the discovery that exogenous GlcNAc represents a secondary signal important for efficient yeast-to-filament conversion indicates that combinatorial signals are integrated by thermally dimorphic fungi to cue morphogenesis . In addition to its role in promoting morphogenesis , GlcNAc also stimulated faster growth of differentiated H . capsulatum filamentous cells at RT . This was surprising as GlcNAc does not appear to be the optimal carbon source for H . capsulatum ( glucose is a more efficiently utilized carbon source by H . capsulatum yeast cells in vitro ) , and suggests that GlcNAc stimulates filamentous growth by a mechanism independent of metabolic flux . In trying to understand the mechanism of GlcNAc-promoted filamentation , we focused on genes that were transcriptionally co-regulated in response to GlcNAc . Interestingly , this analysis led to the observation that GlcNAc-promoted morphogenesis of H . capsulatum is dependent on two GlcNAc transporters , Ngt1 and Ngt2 . Furthermore , Ngt1 and Ngt2 were necessary for efficient yeast-to-filament morphogenesis even in the absence of exogenous GlcNAc , suggesting that Ngt1 and Ngt2 may function as part of a general autoregulatory mechanism in H . capsulatum , presumably dependent on endogenous GlcNAc ( i . e . , GlcNAc that could be turned over from the remodeling of chitin in the cell wall that accompanies cell division ) , that serves to control multicellular filamentous growth . The kinetics and synchrony of the temperature-induced morphologic switch were greatly enhanced by GlcNAc supplementation , which allowed more robust profiling of the yeast-to-filament transition . Classifying transcript expression patterns based on their temporal regulation during the yeast-to-filament transition of H . capsulatum yielded distinct categories of regulated transcripts . Surprisingly , we noticed similar expression patterns for regulated transcripts in H . capsulatum yeast cells transitioning to filaments at RT in GlcNAc and glucose medium in spite of their disparate cellular morphologies . This could indicate that many of the transcriptional changes that occur during morphogenesis are induced by temperature as opposed to after initiation of the morphologic program . Alternatively , the transcriptional changes we described may not be sufficient to establish morphogenesis , and key transcriptional or post-transcriptional controls of morphogenesis could remain to be identified . Some genes that were induced during the yeast-to-filament transition , but not during static , long-term growth of the filamentous form , included genes that are known to influence filamentation in other , better characterized fungi , making these genes attractive candidates for conserved regulators of filamentous growth across dimorphic fungi . Of note , the transcription factor Cph1 ( alias Ste12 in S . cerevisiae ) , which we found upregulated during the yeast-to-filament transition in H . capsulatum , is required for filamentous growth in both C . albicans [41] and S . cerevisiae [42] . Intriguingly , we also noted the upregulation of a mitogen-activated protein kinase , HMK1 , during H . capsulatum morphogenesis . Hmk1 homologs ( Kss1 and Cek1 in S . cerevisiae and C . albicans , respectively ) function directly upstream of the Cph1 and Ste12 transcription factors in the pathways controlling filamentous growth in C . albicans [43] and S . cerevisiae [26] . In addition to implicating genes in the regulation of morphogenesis in thermally dimorphic fungi , our temporal transcriptome analysis revealed surprisingly dynamic expression patterns for genes that were originally characterized as showing differential expression in static samples of either yeast or filaments . We hypothesize that this reflects unanticipated roles for these transcripts in other aspects of fungal cell biology , highlighting the need to profile expression patterns of dimorphic fungal transcripts over a variety of cellular conditions and timepoints to fully characterize phase-specific changes in gene expression . From our transcriptional profiling data , we chose to focus on the class of genes transcriptionally co-regulated by GlcNAc to begin to understand the mechanism underlying GlcNAc-stimulated morphogenesis . Our work indicated that the H . capsulatum GlcNAc transporters , Ngt1 and Ngt2 , are required for efficient GlcNAc-mediated filamentation . Whether Ngt1 and Ngt2 ultimately mediate GlcNAc-promoted filamentation by directly sensing GlcNAc or controlling GlcNAc transport for intracellular sensing is unclear . We found that micromolar amounts of GlcNAc were sufficient to promote filamentous growth in H . capsulatum even in the presence of 100 mM glucose , suggesting that GlcNAc does not need to be the main carbon source to exert its effects . This also indicates that thermally dimorphic fungi are exquisitely sensitive to levels of extracellular GlcNAc such that low levels of this amino sugar are sufficient to promote robust filamentous growth . Furthermore , we found that knocking down HXK1 , the GlcNAc kinase which phosphorylates intracellular GlcNAc as the first enzymatic step necessary for utilizing GlcNAc in glycan biosynthesis or catabolism ( see Figure S5 ) , does not alter the ability of H . capsulatum to filament in response to GlcNAc . Thus , we favor the idea that thermally dimorphic fungi are remarkably sensitive to levels of GlcNAc , such that low levels of this amino sugar are sufficient to promote robust filamentous growth in conjunction with the appropriate temperature signal . External GlcNAc might be sensed by Ngt1/Ngt2 , or alternatively , GlcNAc could be transported into the cell and sensed by an intracellular mechanism . To date , no GlcNAc sensing mechanism has been identified in fungi and thus , how GlcNAc fits into the complex regulatory networks that control fungal morphogenesis is unknown . The identification of GlcNAc-induced transcripts may provide clues into a mechanism for GlcNAc-promoted filamentation . Most notably , we identified OGA1 as a GlcNAc-induced transcript in H . capsulatum and demonstrated that Ngt1 or Ngt2 was necessary for its upregulation in response to GlcNAc . OGA1 shares homology with the metazoan O-GlcNAcase ( OGA ) enzyme that functions as a regulator of the dynamic intracellular metazoan signaling modification termed O-GlcNAcylation [34] . In metazoans , O-GlcNAcylation is a ubiquitous post-translational modification , akin to phosphorylation , that regulates basic cellular processes such as cellular development , transcription , protein turnover , and the cell cycle [34] . It is unknown whether fungi modify proteins with O-GlcNAc , let alone utilize O-GlcNAc as a signaling modification . Future work will examine whether the O-GlcNAc modification exists in fungi , and ultimately , whether the putative H . capsulatum OGA1 enzyme alters O-GlcNAcylation levels to influence morphogenesis . Interestingly , while homologs of genes that mediate O-GlcNAc signaling in metazoans ( OGT and OGA1 ) can be found in H . capsulatum , they are conspicuously absent from S . cerevisiae and C . albicans [44] , making H . capsulatum a useful model system in which to study O-GlcNAc signaling . Overall , it will be important to understand how GlcNAc controls cells fate determination in fungi , as this may contribute to our understanding of the role of GlcNAc in cell signaling and developmental processes across all kingdoms of life . Our study and other recent work in fungi provide insights into the regulation of intracellular GlcNAc levels . In most cells , GlcNAc is thought to primarily exist as UDP-GlcNAc [45] , [46] , which is the universal nucleotide-sugar donor for glycan biosynthesis . Most eukaryotic cells have long been thought to salvage GlcNAc from glycans in lysosomal compartments and synthesize UDP-GlcNAc de novo via the hexosamine pathway [45] , as opposed to salvaging free , extracellular GlcNAc across their plasma membranes using dedicated carbohydrate transporters [47] . However , the recent discovery of functional plasma membrane GlcNAc transporters in fungi suggests that at least some eukaryotic cells can take up extracellular GlcNAc via a transporter-mediated process . Interestingly , homologs of Ngt1 can be found in some metazoans , including humans [24] , and it remains to be investigated whether these homologs represent functional GlcNAc transporters . The implications of extracellular , transporter-mediated uptake of GlcNAc in eukaryotic cells changes our understanding of the overall cellular flux and regulation of the essential metabolite UDP-GlcNAc . Our work highlights that some fungi possess multiple MFS GlcNAc transporters , Ngt1 and Ngt2 , potentially allowing these organisms to more precisely control levels of intracellular GlcNAc and thus , UDP-GlcNAc . MFS transporters can exist either as oligomers or monomers in the plasma membrane; however , the oligomeric state for most characterized MFS transporters is unknown [48] . We hypothesize that the H . capsulatum Ngt1 and Ngt2 GlcNAc transporters could be acting ( 1 ) in cooperation as a heterooligomeric complex to transport GlcNAc; ( 2 ) with complementary functions , e . g . , one directly senses GlcNAc and the other transports GlcNAc; or ( 3 ) as transporters with different affinities for GlcNAc . Consistent with this latter hypothesis , it was recently proposed that yeast utilize dual-transporter systems with differing affinities for the same substrate to optimize nutrient homeostasis when environmental resources fluctuate [49] . Interestingly , only a subset of fungi that have Ngt1 transporters also have Ngt2 . Additionally , in many of the fungi with both transporters , Ngt1 is located in the same genomic regions as other GlcNAc catabolic genes , whereas that is not the case for fungal species that only have Ngt1 . Perhaps this differential genomic location reflects the need for alternate transcriptional regulation of GlcNAc utilization genes in organisms that have both Ngt1 and Ngt2 . In support of this idea , our data indicates that GlcNAc utilization genes ( NGT1 , HXK1 , NAG1 , and DAC1 ) in H . capsulatum are not repressed by glucose , which is in contrast to C . albicans GlcNAc utilization genes that are highly repressed by glucose . Furthermore , many of the fungi with identifiable Ngt2 transporters are known human fungal pathogens ( H . capsulatum , B . dermatitidis , Coccidioides spp . , T . verrucosum , A . fumigatus , and P . marneffei ) , suggesting that Ngt2 might play a role in pathogenesis . Of note , GlcNAc can be utilized as a carbon source in vivo by some mammalian pathogens and commensals including the parasite Leishmania major that resides in macrophage phagolysosomes [50] , the commensal bacteria Escherichia coli that resides in the gastrointestinal tract [51] , and the bacterial pathogen Salmonella enterica serovar Typhimurium , which is found intracellularly within macrophage vacuoles [52] . It is hypothesized that these microbes , each of which occupies a very different niche within its host , are able to acquire host GlcNAc intracellularly from glycans being recycled within cellular lysosomal and endosomal compartments [45] or extracellulary from mucins [53] . It will be interesting to determine whether Ngt1 and Ngt2 play a role in nutrient acquisition during H . capsulatum macrophage colonization and growth . One of the most intriguing observations from this work is that Ngt1 and Ngt2 are necessary for efficient morphogenesis in the absence of exogenous GlcNAc . Thus , we hypothesize that Ngt1 and Ngt2 may be sensing levels of extracellular , endogenous GlcNAc to monitor population density and/or signal filamentous growth . It has long been appreciated that microbial cells can regulate their growth in response to changing local environmental conditions as well as fluctuations within their own population density via autoregulatory factors [54] . In fungi , a handful of autoregulatory small molecules and peptides that control density-dependent growth or morphology , interspecies communication , and biofilm formation have been proposed [55] . As the building block of the fungal cell wall polysaccharide chitin , GlcNAc fits the definition of a small molecule that could serve as an autoregulatory factor as its extracellular concentration would be proportional to the number of actively dividing cells due to the extensive remodeling of chitin that accompanies fungal cell division . Since chitin appears to be a more broadly distributed component of the cell wall in filamentous fungi [56] as compared to yeast cells , which primarily accumulate chitin around septa and bud scars [57] , it is compelling to speculate that GlcNAc levels could regulate multicelluar filamentous growth . Furthermore , GlcNAc may trigger other changes beyond morphogenesis as it has been implicated as a signal in interspecies communication in the Gram-negative bacterial pathogen Pseudomonas aeruginosa . P . aeruginosa utilizes a two-component response regulator to sense environmental GlcNAc ( one source proposed is GlcNAc shed from peptidoglycan of Gram-positive bacteria ) to control the production of an antimicrobial factor [58] , [59] . Notably , a major conclusion of our work is that widely diverged fungal species are capable of responding to GlcNAc to initiate filamentous growth . GlcNAc-induced filamentation has been observed previously [60] in some members of the Saccharomycetes fungal class ( including C . albicans , Candida lusitaniae , and Yarrowia lipolytica ) , which are much more closely related to each other than to thermally dimorphic fungi ( including H . capsulatum and B . dermatitidis from the Eurotiomycetes class ) [61] . Equally noteworthy is that C . albicans and thermally dimorphic fungi occupy disparate environmental niches: C . albicans colonizes the mammalian gut and forms filaments at mammalian body temperature during invasive , pathogenic growth whereas thermally dimorphic fungi form filaments in the soil at the ambient environmental temperature . Thus , in spite of the distinct biological milieu occupied by these organisms , filamentation of fungal cells in response to exogenous GlcNAc appears to be deeply conserved , and therefore is likely to play a fundamental role in fungal biology . Finally , we note that the life cycle of thermally dimorphic fungal pathogens , which includes the ability to switch between a parasitic form ( disease-causing state ) and a multicellular filamentous form ( infectious state ) , is crucial to their pathogenesis and infectivity . Temperature is the best characterized cue that governs this reversible morphogenesis; however , as we demonstrated with GlcNAc , additional signals facilitate the efficient morphogenesis of thermally dimorphic fungi . It is critical to define the regulatory networks that integrate multiple environmental cues ( i . e . , GlcNAc and temperature ) into a morphogenetic program for the cellular differentiation of these organisms . Ultimately , understanding how H . capsulatum yeast cells transition to filaments will provide insight into the establishment and maintenance of the infectious environmental reservoir of this human fungal pathogen .
Histoplasma capsulatum strains G217B ( ATCC26032 ) , G217Bura5Δ ( WU15 ) , both gifts from the laboratory of William Goldman , University of North Carolina , Chapel Hill , were grown in HMM ( Histoplasma-macrophage medium ) broth or plates [62] . Blastomyces dermatitidis strain SLH14081 ( gift of Bruce Klein , University of Wisconsin , Madison ) was grown in HMM broth . HMM medium , which contains 110 mM glucose , was supplemented when necessary with uracil ( Sigma-Aldrich ) ( 200 µg/ml ) or as indicated with GlcNAc ( Sigma-Aldrich ) ( referred to as HMM medium supplemented with the mM concentration of GlcNAc indicated throughout the text ) . In some experiments , GlcNAc was used as the major carbohydrate source in HMM broth and plates by substituting 100 mM GlcNAc in place of the usual major carbon source , 100 mM glucose , to provide an equal molarity of carbon source ( referred to as “HMM/100 mM GlcNAc” throughout the text ) ; however all HMM medium retains 10 mM glucose from the Gibco's F12 nutrient supplement ( Life Technologies ) that is used to make HMM medium [62] . H . capsulatum and B . dermititidis cultures were grown at 37°C under 5% CO2 for yeast-phase growth or at room temperature ( RT ) for filamentous-phase growth with continuous shaking of liquid cultures on an orbital shaker . For the microarray time-course study , G217B yeast cells were grown at 37°C in HMM medium and subjected to passage at 1∶25 dilution into HMM medium . After 1 day of growth to early log phase , a portion of cells were harvested for the t = 0 timepoints and the remaining cells were washed in PBS and then resuspended with no dilution into 200 mL HMM ( contains 110 mM glucose ) and HMM/100 mM GlcNAc ( contains 10 mM glucose and 100 mM GlcNAc ) media for t = 1 h , 4 h , and 24 h timepoints or resuspended with a 1∶10 dilution into 200 mL HMM ( contains 110 mM glucose ) and HMM/100 mM GlcNAc media ( contains 10 mM glucose and 100 mM GlcNAc ) for t = 4 d and 7 d timepoints . Cultures for all timepoints were allowed to continue to grow at 37°C under 5% CO2 for yeast-phase growth or transferred to RT for filamentous-phase growth . For the endpoint microarray experiment , G217B yeast cells were grown for 2 days at 37°C in HMM medium and filamentous cells were grown for 4–6 weeks with passaging 3 times ( 1∶5 dilution ) into fresh HMM medium at RT before reaching a sufficient density of cells for harvesting . At each indicated timepoint , cultures were harvested and processed as described below . For quantitative reverse transcriptase PCR ( qRT-PCR ) , strains were grown at 37°C in 5 mL HMM medium to log phase . Cultures were synchronized to reach early-log phase ( OD600 = 4 . 0–6 . 0 ) the day of the experiment . Cells were washed once in PBS , and a 1∶10 dilution of each strain was inoculated into HMM ( 110 mM glucose ) and HMM/100 mM GlcNAc ( contains 10 mM glucose and 100 mM GlcNAc ) media . After 2 days of growth , cultures were harvested by centrifugation and total RNA was harvested using a guanidine thiocyanate lysis protocol as previously described [11] . A 457 bp region of NGT1 , 517 bp region of NGT2 , and a 464 bp region of the HXK1 coding sequences were amplified using G217B cDNA and oligonucleotides OAS2880-81 , OAS2876-77 , or OAS4193-94 , respectively . All primer sequences are included in Table S7 . Using Gateway cloning and the entry vector pDONR/zeo ( Life Technologies ) , these PCR products were used to generate BAS662 containing a hairpin repeat of NGT1 and BAS1198 containing a hairpin repeat of HXK1 in backbone vector pFANTAi4 ( gift of Bruce Klein , University of Wisconsin , Madison; [63] ) or BAS643 containing a hairpin repeat of NGT2 in vector pSB23 ( a Gateway-compatible destination plasmid derived from pCR186 , which was a gift from Chad Rappleye , Ohio State University ) . The vector control ( BAS506 ) , BAS662 ( NGT1 RNAi ) , and BAS1198 ( HXK1 RNAi ) constructs were integrated into H . capsulatum strain G217Bura5Δ by the use of an Agrobacterium-mediated gene transfer method as described previously [12] , [64] . The episomally-maintained vector control ( BAS538 ) and BAS643 ( NGT2 RNAi ) were electroporated into G217Bura5Δ as previously described [31] . The method chosen for RNAi plasmid maintenance ( i . e . , episomal versus integrating ) was determined empirically by assessing which method gave the strongest and most consistent decrease of NGT1 and NGT2 expression . Yeast form cultures of SLH14081 , G217Bura5Δ , vector control , NGT1 , or NGT2 RNAi strains were grown to early log phase at 37°C in HMM medium , washed once in PBS and sonicated for 3 s to disperse clumps . For the H . capsulatum G217Bura5Δ and B . dermititidis SLH14081 wild-type time-course , 10 µl of 5×106 yeast cells/mL ( G217Bura5Δ ) or 10 µl of 1×106 yeast cells/mL ( SLH14081 ) were loaded into 28 mm×120 µm M04S CellASIC microfluidic cell culture plates ( Millipore ) in HMM ( contains 110 mM glucose ) or HMM/100 mM GlcNAc ( contains 10 mM glucose and 100 mM GlcNAc ) medium and transferred to RT to monitor conversion to filamentous cells or to 37°C to monitor yeast form growth . For the NGT and HXK1 RNAi time courses , 10 µl of 5×106 yeast cells/mL of H . capsulatum NGT1 RNAi , NGT2 RNAi , HXK1 RNAi , or vector control strains were loaded into 28 mm×120 µm M04S CellASIC microfluidic cell culture plates ( Millipore ) in HMM medium ( contains 110 mM glucose ) and HMM medium supplemented with 10 mM GlcNAc ( contains 110 mM glucose and 10 mM GlcNAc ) . At each indicated timepoint , cell morphology was examined using live-cell differential interference contrast ( DIC ) microscopy with 65 , 1 . 2 µm-thick Z-stack images acquired using a Yokogawa CSU-X1 spinning disk confocal mounted on a Nikon Eclipse Ti inverted microscope with an Andora Clara digital camera and a CFI APO TIRF 60× oil or PLAN APO 40× objective . Images were acquired by and processed in NIS-Elements software 4 . 10 ( Nikon ) . For the NGT RNAi yeast to filament transition experiment , the number of yeast cells remaining at each timepoint was scored by counting the total number of yeast and filamentous cells visible in a maximum intensity projection of the Z-stack image covering a 37 . 5×37 . 5 µm area . Images with no visible yeast cells ( i . e . , only filamentous cells present ) were scored as 0% yeast cells . Yeast form cultures of G217B were grown to early log phase in HMM medium at 37°C . 10-fold serial dilutions of G217B yeast cells were spotted onto HMM solid medium containing 110 mM glucose in the absence ( 110 mM glucose only ) or presence of 0 . 1 mM , 0 . 25 mM , or 1 mM GlcNAc and HMM/100 mM GlcNAc ( contains 10 mM glucose and 100 mM GlcNAc ) and transferred to RT to monitor filamentous growth or grown at 37°C to monitor yeast phase growth . To monitor growth on various carbon sources , cells were spotted onto HMM solid medium containing 110 mM glucose in the absence or presence of 1 mM GlcNAc , 1 mM fructose ( Sigma-Aldrich ) , or 1 mM glucosamine ( Sigma-Aldrich ) . Cells were also analyzed in liquid medium by inoculating a 1∶10 dilution of G217B yeast cells into 10 mL of HMM medium containing 110 mM glucose and supplemented with 10 mM GlcNAc or 10 mM glucose ( Sigma-Aldrich ) and then incubated at RT to monitor the transition to filamentous cells or at 37°C to monitor yeast phase growth . Dilution series on plates as well as liquid cultures were monitored for growth and morphology by light microscopy between 6 and 14 days after inoculation . H . capsulatum homologs to the C . albicans GlcNAc catabolic genes ( NGT1 = orf19 . 5392; HKX1 = orf19 . 2154; DAC1 = orf19 . 2157; and NAG1 = orf19 . 2156; gene identities from http://www . candidagenome . org/ ) were identified by BLASTP [65] . For phylogenetic analysis , homologs of H . capsulatum Ngt1 and Ngt2 in each indicated fungal species were identified by BLASTP using a cut-off value of E≤1×10−5 . After alignment of protein sequences with MUSCLE [66] , an unrooted phylogenetic model was generated using MrBayes [67] . NCBI protein accession numbers are given in Table S5 and Figure S8 . Cells were harvested by centrifugation or filtration and total RNA was isolated using a guanidine thiocyanate lysis protocol as previously described [11] . Fluorescently labeled cDNA was synthesized by incorporating amino-allyl dUTP during reverse transcription with Superscript II ( Life Technologies ) of 15 µg total RNA with oligonucleotide-dT and random hexamers used as primers . Cy3 or Cy5 dyes ( GE Life Sciences ) were coupled to the amino-allyl group as described previously [68] . For each time-course sample , cDNA was coupled to Cy5 and a reference cDNA pool was made by combining RNA from t = 0 and all late time course samples , which was coupled to Cy3 . For end point microarray experiments ( i . e . , established yeast samples compared to established filamentous samples ) , G217B yeast cDNA was coupled to Cy5 and filament cDNA was coupled to Cy3 . Samples were hybridized to H . capsulatum G217B 70-mer oligonucleotide microarrays . Each microarray contained one or two 70-mer oligonucleotides for each predicted gene in the G217B genome ( 11 , 088 gene predictions and a total of 14 , 820 oligonucleotides per array ) . Arrays were scanned on a GenePix 4000B scanner ( Axon Instruments/Molecular Devices ) and analyzed using GenePix Pro , version 6 . 0 ( Molecular Devices ) , NOMAD 2 . 0 ( http://derisilab . ucsf . edu/microarray/software . html ) , Cluster 3 . 0 [69] , and Java Treeview 1 . 1 . 4r4 ( available at http://jtreeview . sourceforge . net ) . To eliminate elements with low signal , we analyzed only elements for which the sum of the medians for the 635 nm and 532 nm channels was ≥150 intensity units . Gene expression data was filtered for 80% completion and a cut-off value for change in gene expression of >2 . 0 ( log2 ) for all clusters is shown unless otherwise indicated . Hierarchical or k-means clustering were used as indicated for unsupervised clustering . For k-means clustering , k = 10 and n = 100 parameters were empirically chosen . All microarray data have been deposited at Gene Expression Omnibus ( GEO ) database at the National Center for Biotechnology Information ( http://www . ncbi . nlm . nih . gov/geo/ ) and are available through the accession number GSE48044 . Yeast form cultures of NGT1 RNAi , NGT2 RNAi , HXK1 RNAi and corresponding vector control strains were grown in HMM medium at 37°C and synchronized to mid log phase for the day of the experiment . Cells were washed in PBS and then resuspended in 3M minimal medium [62] containing no carbohydrate ( without glucose ) and grown overnight to starve cells . After starvation , cells were inoculated to an OD600 = 0 . 6 into 3M medium containing equal molarities of glucose or GlcNAc ( 55 mM ) , or no carbohydrate . Growth was monitored by measuring the OD600 at each indicated timepoint . Total RNA was treated with DNase I ( Promega ) . cDNA was synthesized using 3 . 3 µg of DNase I-treated RNA , Affinityscript reverse transcriptase ( Agilent ) , and oligo ( dT ) and random hexamer primers . qRT-PCR was performed using 1∶100 dilutions of cDNA , 0 . 8× FastStart Universal SYBR Green Master Mix ( Roche ) , and 200 nM primers . Reactions were performed using an Mx3000P qPCR system ( Agilent ) with the Comparative Quantitation program . Cycling parameters were 95°C for 10 min and then 40 cycles of 95°C ( 30 s ) and 55°C ( 1 min ) ; cycling was followed by dissociation curve analysis . Reactions were analyzed using MxPro software ( Agilent ) . Primer sequences of each qRT-PCR probe are included in Table S7 . Coding sequences of H . capsulatum NGT1 and NGT2 were codon optimized by gene synthesis ( GENEWIZ ) for expression in C . albicans using the most frequent S . cerevisiae codon and excluding use of the CUG codon ( to avoid translation of CUG as serine instead of the canonical leucine which occurs C . albicans [70] ) . Plasmids for complementation were constructed using PCR and homologous recombination in S . cerevisiae [71] . H . capsulatum codon optimized NGT1 and NGT2 were put under the control of the C . albicans TDH3 promoter and ACT1 terminator followed by the C . albicans URA3 gene . A vector control construct was made identically except it lacked NGT1 or NGT2 coding sequence . All primers are listed in Table S7 . Complementation fragments containing ∼350 bp of homology to RPS10 were excised by digestion with PmeI and then integrated into the C . albicans ngt1Δ strain at the RPS10 locus via homologous recombination . Strains were verified by PCR to contain the appropriate NGT gene and then 10-fold dilutions of cells were spotted onto solid Yeast Nitrogen Base minimal medium containing 50 mM of GlcNAc , glucose , or galactose . Growth results were reproducible with separate isolates obtained from independent transformations . C . albicans strains used in this study are listed in Table S8 . Supplementary Materials and Methods can be found in Text S1 . | In stark contrast to most fungal pathogens , thermally dimorphic fungal pathogens cause systemic infections in immunocompetent humans . Thermally dimorphic fungi grow in the soil as a multicellular filamentous form specialized for replication in this particular environmental niche . Upon infection of a human , these fungi transition to a parasitic cell type that is adapted for replication and pathogenesis within a mammalian host . In this work , we examined factors that are important for growth of the infectious , environmental form of thermally dimorphic fungi . We discovered that N-acetylglucosamine ( GlcNAc ) , a ubiquitous carbohydrate with cellular roles across all kingdoms of life , stimulated a switch to the environmental form for two thermally dimorphic fungal pathogens , Histoplasma capsulatum and Blastomyces dermatitidis . Analysis of how fungal cells respond to GlcNAc revealed that these fungi possess two GlcNAc transporters that are important for controlling their ability to switch between infectious and parasitic states . Overall , our work begins to elucidate the pathways that promote growth in the infectious form of these organisms , which is critical to our understanding of environmental signals that promote disease transmission of thermally dimorphic fungi . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | N-acetylglucosamine (GlcNAc) Triggers a Rapid, Temperature-Responsive Morphogenetic Program in Thermally Dimorphic Fungi |
Transfer RNA ( tRNA ) modifications enhance the efficiency , specificity and fidelity of translation in all organisms . The anticodon modification mcm5s2U34 is required for normal growth and stress resistance in yeast; mutants lacking this modification have numerous phenotypes . Mutations in the homologous human genes are linked to neurological disease . The yeast phenotypes can be ameliorated by overexpression of specific tRNAs , suggesting that the modifications are necessary for efficient translation of specific codons . We determined the in vivo ribosome distributions at single codon resolution in yeast strains lacking mcm5s2U . We found accumulations at AAA , CAA , and GAA codons , suggesting that translation is slow when these codons are in the ribosomal A site , but these changes appeared too small to affect protein output . Instead , we observed activation of the GCN4-mediated stress response by a non-canonical pathway . Thus , loss of mcm5s2U causes global effects on gene expression due to perturbation of cellular signaling .
Transfer RNAs ( tRNAs ) from all domains of life contain numerous post-transcriptional modifications , many of which are highly conserved . These modifications enhance the efficiency , specificity and fidelity of translation [1]–[3] . In the budding yeast Saccharomyces cerevisiae , three tRNAs are modified by addition of 5-methoxycarbonylmethyl ( mcm5 ) and 2-thio ( s2 ) groups to uridine at the 5′ nucleotide of the tRNA anticodon ( U34 ) , resulting in an mcm5s2U nucleotide . The mcm5s2U modification ( MSUM ) and many of the responsible modifying enzymes are conserved across eukaryotes , having been identified in fungi [4] , [5] , plants [6] , worms [7] and mammals [8] . Despite widespread conservation , and extensive biochemical characterization , the physiological role of MSUM is unknown . Genes required for MSUM are unusual among tRNA modification genes in the number and severity of their mutant phenotypes . Most yeast strains lacking tRNA modifications are viable and show no growth impairment [2] , [3] , but S . cerevisiae and C . elegans double mutants lacking both mcm5 and s2 are not viable [7] , [9] . In yeast , single mutants lacking either mcm5 or s2 have numerous phenotypes including temperature sensitivity , various chemical stress sensitivities , exocytosis defects , and transcriptional defects [10] , [11] . In C . elegans , mutants of the Elongator complex ( comprised of elp1 through elp6 ) , which is required to produce the mcm5 modification , display neurological defects [7] . In humans , mutations in IBKAP , the elp1 homolog , cause familial dysautonomia ( FD ) [12] , and mutations in elp4 are associated with Rolandic epilepsy [13] . The molecular connection between these cellular/organismal phenotypes and the lack of specific tRNA anticodon modifications is currently unknown . Loss of either mcm5 or s2 impairs reading of both Watson-Crick ( VAA ) and wobble ( VAG ) cognate codons by the modified tRNAs [14] , [15] , and chemical removal or modification of the s2 moiety leads to a reduction in the rate of tRNA charging in vitro [16] , [17] . The MSUM phenotypes were originally attributed to a proposed role of the Elongator complex in transcriptional elongation [18] before its function in tRNA modification was discovered [4] . However , the phenotypes of yeast MSUM mutants , including the lethality in mutants lacking both mcm5 and s2 , can be suppressed by overexpression of unmodified versions of two tRNAs that normally contain mcm5s2U – and [11] . These observations indicate that at least a subset of the yeast cellular phenotypes are tied to tRNA function . It has been argued that loss of MSUM leads to codon-specific translation defects leading to insufficient protein production , either from many genes , or from a few genes required to carry out particular cellular processes or stress responses , but this hypothesis has not been directly tested . In this study , we examined codon level ribosome distributions genome-wide using ribosome footprint profiling ( Ribo-seq ) . We found that loss of mcm5 or s2 leads to slow translation elongation specifically at codons that Watson-Crick pair with MSUM tRNAs , but the magnitude of these changes appeared insufficient to affect protein output . Surprisingly , all of the MSUM strains showed gene expression signatures consistent with activation of the Gcn4p-mediated stress response pathway . We demonstrate that disruption of this pathway suppresses the MSUM mutant phenotypes independently of tRNA concentration .
We set out to determine whether MSUM mutants display codon-specific translation defects . Translational activity genome-wide was determined using Ribo-seq , which consists of isolating and sequencing ribosome-protected mRNA fragments from RNase-treated whole-cell lysates [19] . This method reveals ribosome positions at single nucleotide resolution , and thus has the potential to identify translational defects affecting single codons [19] , [20] . Wild type ( WT ) yeast , as well as strains lacking the s2 moiety ( ncs2Δ , ncs6Δ , and uba4Δ ) , or mcm5 ( elp3Δ ) ( Figure 1A ) , were profiled by Ribo-seq , as well as RNA-seq . To assess the impact of these modifications on translation , the ribosome dwell time at specific codons was determined as follows . The positions of the A , P and E site codons within ribosome footprints of various lengths ( 25–31 nt ) were determined by examining the 5′ ends of footprints mapping to start codons , where initiating ribosomes are expected to contain start codons in their P sites ( Figure 1B ) [21] . Next , to determine the genome-wide average ribosome dwell time for a given codon ( Figure 1C , left ) , all instances of that codon in the genome were aligned , and 5′ ends of reads mapping to the surrounding positions ( Figure 1C ) were summed ( see Materials and Methods ) . The resulting metacodon plots show the relative number of ribosome footprints , and thus the relative amount of time the ribosome spends at each position , as the codon moves through the A , P and E sites . Codon identity is not expected to affect translation from the outer sites ( ±1 , ±2 ) , so the entire plot was normalized to the height of these peaks . The height of each peak is the bulk occupancy for that codon in that ribosomal site , similar to a previously described metric [20] . The metacodon distributions for ATG and stop codons indicated that the reads were properly assigned to the ribosomal sites ( Figure 1C , right ) . We observed distinct and reproducible patterns of ribosome density for different codons in WT yeast ( Figure 1C , S1A , B ) , consistent with the single-nucleotide resolution of this technique . The metacodon plots of WT yeast provided insights into the determinants of translation rate for specific codons . Notably , all four proline codons spent over 2-fold more time in the P site than the average codon , while glycine codons spent ∼40–50% more time in the A site ( Figure S1C ) . This effect was additive for Pro-Gly pairs in the P and A sites , but not if the codon order was reversed ( Figure S1D ) , indicating that the effects of Pro and Gly were specific to the P and A sites , respectively . This proline effect is reminiscent of the proline/glycine pausing recently discovered in bacteria lacking elongation factor P [22]–[24] . The observed effects were consistent with in vitro data which showed that peptidyl transfer can be rate limiting for A-site glycine and proline codon translation at physiological pH [25] , and that proline induces particularly slow peptide bond formation when it is at the carboxyl terminus of the growing peptide chain [26] ( Figure S1E ) . These results suggest that peptidyl transfer is rate limiting for certain Pro and Gly codons in yeast cells as well . Experiments in recombinant systems have led to the strong expectation that translation times for codons should be inversely proportional to the concentrations of their cognate tRNAs [27] , [28] . To investigate potential sources of the distinctive metacodon distributions we observed , we performed unsupervised hierarchical clustering on them ( Figure S2A ) . This analysis clustered many codons together based on their encoded amino acid or the first two nucleotides of the codon . Notably , codons did not cluster by tRNA adaptation index ( tAI ) , a proxy for cognate tRNA abundance [27] . More directly , the bulk occupancies did not show a negative correlation with tAI in the A site ( Figure S2B ) . There was also no correlation of codon occupancy with tRNA abundance measurements , genomic copy number , or a more recent codon usage metric which accounts for tRNA competition [29] ( data not shown ) . These results demonstrate that translation rates for particular yeast codons are not determined by the cellular concentrations of their cognate tRNAs , consistent with findings from Ribo-seq experiments in mice and bacteria [30] , [31] and from protein synthesis reporters ( containing codon repeats ) in yeast [32] . Having established the ability to detect differences in the translation of different codons , we next examined changes in codon-specific translation in the MSUM strains . Bulk occupancy for each codon in each ribosomal site ( the height of the peaks in the metacodon plots ) was determined for each mutant . All of the strains lacking the s2 modification showed increases in ribosome density corresponding to CAA and AAA in the A site , while the elp3Δ strain showed an increase in the CAA and GAA codons ( Figure 1D ) . The magnitude of the changes was largest when the affected codon was found in the ribosomal A-site . The magnitude and direction of change for the GAA codon was variable between mutants lacking the same modification , and even between biological replicates ( Figure 1D ) , indicative of some underlying biological or technical noise in this measurement . Nonetheless , in all but one replicate , the largest increases in each mutant were for codons decoded by Watson-Crick pairing with MSUM tRNAs . MSUM is necessary for wobble decoding of G-ending codons in strains that lack other cognate tRNAs [14] , but it is not clear whether the modified tRNAs contribute to decoding in the WT state where these other tRNAs are present . In our datasets AAG , CAG , and GAG codons showed smaller increases in bulk occupancy ( and some net decreases ) compared to their A-ending counterparts , suggesting that MSUM is mainly required for translation of VAA codons ( Figure 1E ) . In order to assess the statistical significance of these changes , a metric for ribosome dwell time at individual codons was developed ( Figure 2A ) . This metric normalizes the read counts at a particular codon by the mean read density of the open reading frame that contains it . The genome-wide distributions for all instances of each codon were compared between mutant and WT strains using the K-S test ( Figure 2B , C ) . Due to the noise inherent in read sampling , many codons showed statistically significant changes . However , the VAA codons had p values many orders of magnitude smaller than all other codons , particularly in the ncs6Δ and uba4Δ datasets , which were from pooled biological replicates ( Figure 2C ) . The pooled datasets provided data for approximately twice as many codons and may have averaged out biological and technical noise . Consistent with our analysis of bulk codon occupancy , the effect of MSUM loss was strongest in the A site for all 3 VAA codons . We did not see a corresponding statistical significance for the VAG codons ( Figure 2C ) , indicating that mcm5s2U does not significantly contribute to the decoding of these codons in vivo . This result does not contradict previous evidence that the modifications are required for translation of VAG codons by wobble pairing [14] , but indicates that tRNAsUUB contribute minimally to the translation of VAG codons in vivo , where tRNAsCUB with Watson-Crick complementarity are available . Despite the statistical significance of the increased ribosome dwell times at VAA codons in MSUM mutants , the magnitude of the changes does not seem to be large enough to generally affect protein output . Initiation , not elongation , is the rate-limiting step of eukaryotic translation in most circumstances [33] , [34] , and the mean ribosome density is only 1 per 164 nts [35] . Given this sparse spacing of ribosomes on yeast mRNAs , transcripts with mean ribosome density would require an elongation delay greater than the average translation time of 50 codons in order for an MSUM mutation to make elongation rate limiting . The most densely populated messages would require a 20-fold elongation delay . The average bulk increase observed for VAA codons was less than 17% ( Figure 1D ) , and the largest confidently assigned ( ≥32 reads ) single-codon change was less than 5-fold ( Figure 3A , S3A ) . In the event of an elongation delay long enough to affect protein output , ribosome queuing should occur behind AAA and CAA codons with increased occupancy . However , no queuing was observed ( Figure 3B , S3B ) . Codons with more read coverage display smaller changes than codons with low read coverage , indicating that the range of this metric is not being limited by sequencing depth ( Figure 3A , S3A ) . We also did not observe increased ribosome density at stretches of 2 or more VAA codons ( data not shown ) . These results were consistent with the polysome gradient profiles of the MSUM strains , which were indistinguishable from WT ( data not shown ) , indicating that translation elongation in bulk was unaffected . In search of an alternative explanation for MSUM mutant phenotypes , we examined global ribosome footprint densities and transcript levels for perturbations in the MSUM mutant strains . Consistent with previous reports [19] , [36] , gene expression values from Ribo-seq were highly reproducible ( Figure S4A ) . Furthermore , all of the mutant strains showed similar RNA-seq and Ribo-seq changes when compared to WT strains ( Figure S4B , C ) , indicating that these gene expression changes are likely to be downstream of a common defect . Replicate data for ncs6Δ and uba4Δ enabled us to assess the significance of particular changes using counting statistics [37] . This analysis identified a set of genes with significant changes in ribosome footprint density , which were largely shared between ncs6Δ and uba4Δ ( Figure 4A , 4B , S4D ) . The changes in ribosome footprint density were correlated with changes in transcript levels ( r = 0 . 59 for ncs6Δ , 0 . 64 for uba4Δ ) , indicating that these gene expression changes were largely due to changes in the mRNA pool ( Figure 4A , 4D ) . Intriguingly , a significant fraction ( 24/68 ) of the affected genes are known targets of the GCN4 transcription factor [38] ( Figure 4A , 4B , S4D ) . To investigate the specificity of the observed induction of GCN4 targets in MSUM mutants , we examined the behavior of GCN4 targets in 1 , 924 yeast microarray studies using data from the SPELL curated yeast microarray compendium . This compendium includes experiments sampling a broad range of environmental and genetic perturbations [39] . We determined the significance of overlap between GCN4 targets and the set of upregulated ( ≥2-fold ) genes in each of these 1 , 924 datasets . Notably , the overlap between GCN4 targets and induced genes in MSUM strains was more statistically significant than the overlap between GCN4 targets and induced genes in 82% of the SPELL datasets . The datasets with a higher degree of overlap consisted mostly ( at least 276/343 ) of gene deletions and stress conditions in which GCN4 is known to play a role ( e . g . heat , nutritional perturbation , osmotic stress and DNA damage ) ( Table S4 , data not shown ) . Furthermore , GCN4 targets as a whole showed increased ribosome footprint density in all MSUM strains ( Figure 4C , data not shown ) . We further confirmed this enrichment for functional GCN4 targets by examining the predicted Gcn4p binding affinity of the promoters for the affected genes [40] . The promoter regions of the upregulated genes were enriched for Gcn4p binding motifs ( Figure 4D ) . Using the same sets of upregulated genes from the SPELL compendium as above , less than 6% of these upregulated gene sets had a mean predicted Gcn4p occupancy greater than the genes upregulated in the MSUM strains ( Table S4 ) . Thus , GCN4 target genes are transcriptionally upregulated in all MSUM strains . To provide context for these gene expression changes , the same analyses were performed on Ribo-seq data from yeast subjected to amino acid ( AA ) starvation , a well-characterized GCN4-inducing condition [19] . 20 minutes of amino acid starvation leads to a 4-fold increase in ribosome footprints on the GCN4 ORF ( data not shown ) . A larger number of genes displayed changes in AA starvation compared to MSUM ablation , and GCN4 targets as a group had larger fold changes ( median 2 . 0-fold induction vs . 1 . 2 and 1 . 1-fold for uba4Δ and ncs6Δ respectively ) . ( Figure S5A , S5B ) . However , a smaller fraction of the significantly changing genes are GCN4 targets ( 13% in AA-starved cells , vs 29% and 30% for uba4Δ and ncs6Δ respectively ) ( Figure 5B , S5C ) . Furthermore , the starvation-induced genes had a smaller enrichment for predicted Gcn4p occupancy in their promoters compared to genes upregulated in the MSUM strains ( Figure 5D ) . The limited induction of high-affinity Gcn4p targets in MSUM mutants is consistent with a weak but specific activation of the GCN4 pathway . We next sought to identify the mechanism of GCN4 pathway induction in MSUM strains . GCN4 is known to be translationally regulated in response to a variety of insults , most notably by amino acid starvation [41] . Translational repression of GCN4 is mediated by four upstream open reading frames ( uORFs ) , which prevent ribosomes from initiating on the protein-coding ORF . Conditions that decrease the efficiency of re-initiation allow some ribosomes to scan through the uORFs and initiate at the GCN4 ORF . All four MSUM mutants showed ∼2-fold translational upregulation of GCN4 , as evidenced by increased ribosome footprint density in the ORF with no increase in mRNA levels ( Figure 5A ) . A reporter construct containing the transcript leader of GCN4 fused to lacZ verified that the uORF-containing leader was sufficient to recapitulate the translational induction observed in MSUM strains ( Figure 5B ) . The magnitude of this induction ( 2–4 fold ) is consistent with a weak activation of the GCN pathway , as a 3 hr shift to SC-Ura , and a constitutive GCN2 allele [42] induced GCN4-lacz 7-fold and 50-fold , respectively ( data not shown ) . The best-characterized pathway of inducing GCN4 involves the activation of the Gcn2p kinase by uncharged tRNA , leading to phosphorylation of eukaryotic initiation factor 2α ( eIF2α ) and reduced efficiency of initiation and re-initiation . We therefore tested the effect of gcn2Δ on GCN4 induction by MSUM mutants . Surprisingly , GCN4-lacZ was still induced in MSUM strains lacking GCN2 ( Figure 5C ) . In addition , basal eIF2α phosphorylation levels were not increased in the MSUM strains , consistent with a GCN2-independent mechanism ( data not shown ) . Thus , GCN4 translational induction in MSUM strains occurs by a non-canonical pathway . In addition to the canonical GCN2-dependent response , some tRNA charging and modification defects have been shown to cause induction of GCN4 by a GCN2-independent mechanism [43]–[45] . MSUM mutations may affect charging . In vitro experiments have shown that loss of the s2 moiety of MSUM tRNAs reduces the efficiency of tRNA charging [16] , [17] , although steady state tRNA charging levels are unaltered in MSUM mutants [14] . We reasoned that a kinetic defect in tRNA charging could lead to compensatory increases in tRNA synthetase gene expression [46] , which could suppress steady-state charging defects . We examined synthetase expression by unsupervised hierarchical clustering of mRNA abundance changes in all of the mutant strains . GlnRS , LysRS , GluRS and AspRS formed a cluster of increased expression in the MSUM mutants ( Figure S6 ) . Three of these synthetases ( Gln , Lys , and Glu ) have MSUM tRNAs as substrates . The specific upregulation of this set of tRNA synthetases , along with the global activation of GCN4 targets , suggests that MSUM mutants have adjusted their cellular state to cope with the loss of the mcm5s2U modification ( see Discussion ) . To investigate the functional significance of GCN4 misregulation in MSUM mutants , double mutants were constructed between gcn2Δ or gcn4Δ and ncs6Δ or elp3Δ , and tested for growth under conditions where MSUM mutants grow poorly . Under heat ( 40°C ) , caffeine and diamide stress , gcnΔ/MSUM double mutants showed some increase in growth compared to the single MSUM mutants ( Figure 6A , S7A ) . On rapamycin , the suppression by gcn deletion was similar in magnitude to the suppression by high-copy ( hc ) -tRNA ( Figure 6A ) . We did not observe any rescue of slow growth on YPD at 30°C with either GCN deletion or hc-tRNA expression ( Figure 6A , S7B ) . Expressing hc-tRNA in the double mutant strains conferred additional resistance in all stress conditions , indicating that the GCN pathway contributes to the MSUM phenotypes independently of the pathway affected by hc-tRNA expression ( Figure 6B ) .
MSUM tRNA modifications are conserved throughout eukarya and are required for organismal fitness in yeast , C . elegans , and humans . Due to the striking phenotypes of MSUM mutants , as well as the reported suppression by hc-tRNA [11] , we expected to find large increases in ribosome density at codons decoded by MSUM tRNAs . We did detect increased ribosome density at VAA codons , and the largest effects of MSUM ablation occurred in the ribosomal A-site , the only site where tRNA binding , and thus concentration , is expected to play a role [21] . Thus , our analysis was capable of detecting codon-level translation defects in these mutants . However , the small magnitude of the observed effect makes it unlikely that protein output is generally affected . Additionally , suppression by hc-tRNA was incomplete in our hands , and the extent of both phenotypes and suppression varied between elp3Δ and ncs6Δ mutants when they were directly compared , as opposed to examined separately as in previous studies [11] . This suggests that MSUM genes may play additional roles in the cell , or create tRNA defects that are not suppressible by tRNA overexpression . Overall , we found complex and varied patterns of ribosome density surrounding the different codons of the genetic code . These patterns appear to be determined not by cognate tRNA concentrations , but by intrinsic properties of aminoacyl tRNAs or peptidyl transfer kinetics , consistent with previous data showing that synonymous codon usage had little effect on protein output when mRNAs were expressed at physiological levels [28] , [47] . This overall result is also consistent with the results of a systematic study of protein output from codon-repeat reporters [32] . Our data do not recapitulate all of the findings of that study , most likely because the reporters contained unnaturally long stretches of rare codons and were expressed at levels high enough to deplete the native tRNA pool . Furthermore , unlike reporter gene assays , Ribo-seq is able to detect changes in translation rate that are too small to be detected in an assay for protein output . Since tRNA concentrations vary over an order of magnitude [27] , yet had little effect on ribosome distributions at different codons , it is hard to understand how a ∼2–3 fold overexpression of hypomodified tRNA [48] could strongly affect the rate of ribosome movement . Our data do not rule out the possibility that one or more lowly expressed genes have elongation defects in MSUM mutants that are sufficient to reduce protein output . If so , there must be additional features that make codons in those genes unusually sensitive to the lack of the mcm5s2U modification . Indeed , loss of MSUM has been shown to cause a reduction in protein output in artificially sensitized conditions , such as the readthrough of stop codons by a suppressor tRNA [4] , [49] . It is also possible that larger codon-specific translation defects were not manifest in our growth conditions , which would be consistent with the inability of hc-tRNA to rescue the slow growth of MSUM mutants on YPD . Our data also do not rule out the possibility that a slight increase in ribosome dwell time could lead to amino acid misincorporation [50] , misfolding of the protein product [51] , or degradation of the mRNA and/or protein by the mRNA surveillance machinery [52] . Further experiments are needed to understand the mechanism ( s ) of phenotypic suppression by hc-tRNAs . The largest changes detected in the MSUM mutants were transcriptional effects consistent with activation of the GCN4 pathway . The gene expression signature of GCN4 induction was noticed previously in elpΔ mutants [10] , and was attributed to the presumed role of Elongator in transcription . However , the similarity of the elp3Δ gene expression changes to those of ncs6Δ , ncs2Δ and uba4Δ , which have clear roles in an independent tRNA modification pathway [5] , [53] , [54] , argues against this explanation . Instead , it appears that improperly modified tRNAs elicit a cellular stress response . There is precedent for GCN2-independent activation of the GCN4 pathway by perturbations of tRNAs . Nuclear aminoacylation of tRNAs facilitates export to the cytoplasm in yeast and Xenopus oocytes [55] , [56] , and disruption of this process can lead to nuclear accumulation of tRNA , as well as GCN2-independent GCN4 induction [43] , [44] . Loss of the s2 modification has been previously shown to reduce the rate of in vitro aminoacylation reactions for MSUM tRNAs [16] , [17] . This charging defect could lead to nuclear accumulation of tRNA and the observed GCN2-independent induction of GCN4 , despite the normal steady-state levels of charged tRNA in MSUM strains [14] . The apparent transcriptional upregulation of all three synthetases that recognize MSUM tRNAs may reflect a cellular response to such a defect in tRNA charging . Consistent with a role for the GCN pathway in mediating physiologically relevant signaling in response to loss of MSUM , deletion of GCN2 or GCN4 partially suppressed the phenotypes of MSUM strains . The observation that GCN deletion suppresses MSUM phenotypes independently of the phenotypic suppression conferred by hc-tRNA suggests that there are at least two independent pathways contributing to the MSUM phenotypes . This may have implications for Elongator complex mutants in higher eukaryotes . In C . elegans , rescue of MSUM phenotypes by hc-tRNA has not been demonstrated . Furthermore , the translational effects reported in C . elegans MSUM strains [7] are more consistent with a global decrease in translation initiation , as might be expected in conditions leading to GCN4 activation , than with codon-specific elongation defects . Such secondary effects on gene expression may also play a role in the neurological symptoms of patients with mutations in elp genes . Indeed , induced pluripotent stem cells from FD patients with hypomorphic alleles of elp1 display numerous transcriptional changes during differentiation compared to controls [57] . It will be important to determine the extent to which tRNA-responsive signaling and transcriptional changes , in addition to codon-specific translation defects , contributes to the phenotypes of MSUM mutants in higher eukaryotes , and the severe and varied symptoms of FD patients .
All strains ( Table S1 ) were in the s288c BY4742 background ( MATα his3Δ1 leu2Δ0 lys2Δ0 ura3Δ0 ) . MSUM and GCN deletions strains were constructed by PCR-mediated gene replacement as previously described [58] . All strains were grown in YPD ( 1% Yeast extract , 2% Peptone , 0 . 01% Adenine hemisulfate , 2% Dextrose ) unless otherwise indicated . For growth assays with hc-tRNA plasmids , strains were grown in SC-Leu to maintain selection . Strains were then plated onto YPD . Yeast strains were grown from an OD600 of ∼0 . 001–0 . 004 in aerated flasks at 30°C to mid-log phase ( OD ∼0 . 7 ) , treated with 0 . 1 mg/ml cycloheximide for 2 minutes , and harvested by centrifugation . Cells were lysed by vortexing with glass beads , and libraries were prepared essentially as described [19] , [36] . For the WT-2 , elp3Δ , ncs2Δ , uba4Δ-2 , ncs6Δ-2 libraries , triton was omitted until after lysis . For any analysis in which only 2 libraries are compared , the mutant was always compared to the WT sample processed identically . Sequencing data were deposited in the GEO database with the accession number GSE45366 . Data analysis was performed using custom Python and Bash scripts developed in-house , unless otherwise indicated . Reads were mapped based on their 5′ 21 nt using Bowtie [59] . Reads were first mapped to S . cerevisiae rRNA , allowing up to 3 mismatches , and any mapping multiplicity . Any reads mapping to rRNA were discarded . Reads were then mapped to the S . cerevisiae genome downloaded from the saccharomyces genome database ( SGD ) on 5/26/2010 , allowing up to 3 mismatches and requiring unique mapping . Read lengths were determined by comparing the original read sequence to the genomic sequence . Reads for which the beginning of the in vitro poly-A tail coincides with a genomic A have ambiguous length , and were excluded from length-specific analyses . Open reading frame ( ORF ) annotations downloaded from SGD were used to produce mappings of reads relative to the start codon for each ORF , which were used for all downstream calculations . For all codon-level analyses , reads of each length were processed separately , and 5′ end mapping locations were subsequently pooled , and shifted 5′ with the appropriate offsets ( 25:0 , 26:0 , 27:0 , 28:0 , 29:-1 , 30:-1 , 31:-2 , negative numbers imply a 3′ shift ) to put them in frame with 28 mer reads . When computing RPKMs ( reads per kilobase of ORF sequence per million ORF reads ) and read counts for each ORF , an unsplit pool of reads was used . The ORF positions are defined from 12 nt upstream of the start codon to 14 nt upstream of the stop codon . The first 8 codons of each ORF were excluded from all gene expression calculations to exclude possible artifacts from cycloheximide incubation . The value of position i in the metacodon vector for codon NNN is computed as follows:Where the 21 nt offset is the 28 mer P-site offset ( 12 nt ) plus the distance from the p-site to the first nt in the metacodon plot . The normalized metacodon vector is computed by normalizing to the peak heights of the outer sites:The mapping of metacodon peaks to ribosomal sites is: ( 0:-2 , 3:-1 , 6:A , 9:P , 12:E , 15:+1 , 18:+2 ) . For Figure S1D , the summation is performed over all codon positions for the given amino-acid pair , using the position of the first nucleotide of the first codon in the pair . The single codon occupancy for codon i in gene j in ribosomal site k is computed as:For both the numerator and denominator , only in-frame reads ( those whose 5′ ends fall a multiple of 3 from the first nt of the site ) were counted , and the first 4 codons , as well as codons with no in-frame reads were excluded . For Figure S2 , the normalized metacodon vectors for each codon were used as inputs for cluster 3 . 0 [60] . Codons were clustered using spearman correlation and single linkage . Heatmaps were generated using Java Treeview [61] . The tAI column was not used for clustering , and was only added afterwards for comparison . For Figure S5 , centroid linkage was used for clustering . For each AAA and CAA codon with ≥2-fold increase , the reads at each surrounding position were normalized by the mean read density for the entire ORF . These values were summed relative to all of the codons analyzed , offset so that the 0 position corresponds to the codon in the A site , and the value at each position was divided by the total number of codons whose host gene overlapped the given position . A secondary ribosome pileup is expected to occur approximately one ribosome footprint width ( ∼28 nt ) upstream of the slow codon . Due to the use of polyadenylation in library preparation , any read ending in an adenosine cannot be assigned a length , and is not included in this analysis . Because of this , there is a depletion of read density at ∼−10 nts , corresponding to reads that end with 1 or more adenosines . Significant Ribo-seq changes were called using edgeR [37] . Significance was assessed using a Bonferroni-corrected p-value cutoff of 0 . 05 . The significance of overlap with GCN4 targets was assessed using the hypergeometric test , and the definition of target genes derived from Natarajan et al [38] . The background for the hypergeometric test was defined as the set of genes with confident expression values for all datasets ( 5034 genes for MSUM datasets , 2780 for amino acid starvation ) . Starter cultures containing the GCN4-lacZ reporter plasmid ( Table S2 ) were grown to saturation in SC-URA , then diluted into YPAD and grown in conditions identical to the Ribo-seq samples . At an OD600 of 0 . 7–0 . 8 , 1 ml aliquots each were taken for qPCR and β-galactosidase assays , spun down , media aspirated , and frozen . Pellets were resuspended in Z buffer and permeabilized as previously described [62] . Cell suspensions were transferred in triplicate to a transparent 96-well plate , and 1/5 volume of 4 mg/ml ONPG was added . OD420 was measured every minute for 1 hour in a Bio-Tek synergy HT plate reader . β-galactosidase activity was defined as the slope of the linear portion of the OD420 vs . time graph , normalized by the OD600 of the culture at harvest . RNA was purified from yeast pellets as described [63] . Reverse transcription and quantitative PCR was performed using Avian Myeloblastosis Virus Reverse Trancriptase ( AMV-RT; Promega ) and real-time reagents ( Invitrogen ) according to manufacturer's instructions using a Roche Lightcycler 480 . See Table S3 for gene-specific primer sequences . Liquid growth assays were carried out as previously described [64] , except that saturated selective media starter cultures were diluted to an OD of 0 . 01 in YPD , then diluted 20-fold in YPD to a final volume of 100 µl . | Ribosomes translate the messages of the genetic code into functional proteins with the help of transfer RNAs ( tRNAs ) , which carry a specific amino acid at one end and recognize three letters of the genetic code ( a codon ) with the other . tRNAs are subject to extensive chemical modifications , which are thought to enhance the efficiency , fidelity and specificity of translation . Many of these modifications are conserved across all domains of life , underscoring their biological importance . Despite intensive biochemical characterization , the physiological roles of most tRNA modifications are unknown . The tRNA modification mcm5s2U34 is required for normal growth and stress resistance in yeast; mutants lacking this modification have numerous phenotypes . Mutations in the homologous human genes are linked to neurological disease . The yeast phenotypes can be ameliorated by overexpression of specific tRNAs , suggesting that the modifications are necessary for efficient translation of specific codons . In order to test this model , we determined ribosome distributions at each codon in yeast strains lacking mcm5s2U . The changes we found appeared too small to affect protein output . Instead , we observed a non-canonical activation of a yeast stress response pathway . Thus , loss of mcm5s2U causes widespread perturbation of cellular signaling , independent of any codon-specific translation defects . | [
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] | 2013 | Loss of a Conserved tRNA Anticodon Modification Perturbs Cellular Signaling |
Hereditary sensory and autonomic neuropathy type 2 ( HSNAII ) is a rare pathology characterized by an early onset of severe sensory loss ( all modalities ) in the distal limbs . It is due to autosomal recessive mutations confined to exon “HSN2” of the WNK1 ( with-no-lysine protein kinase 1 ) serine-threonine kinase . While this kinase is well studied in the kidneys , little is known about its role in the nervous system . We hypothesized that the truncating mutations present in the neural-specific HSN2 exon lead to a loss-of-function of the WNK1 kinase , impairing development of the peripheral sensory system . To investigate the mechanisms by which the loss of WNK1/HSN2 isoform function causes HSANII , we used the embryonic zebrafish model and observed strong expression of WNK1/HSN2 in neuromasts of the peripheral lateral line ( PLL ) system by immunohistochemistry . Knocking down wnk1/hsn2 in embryos using antisense morpholino oligonucleotides led to improper PLL development . We then investigated the reported interaction between the WNK1 kinase and neuronal potassium chloride cotransporter KCC2 , as this transporter is a target of WNK1 phosphorylation . In situ hybridization revealed kcc2 expression in mature neuromasts of the PLL and semi-quantitative RT–PCR of wnk1/hsn2 knockdown embryos showed an increased expression of kcc2 mRNA . Furthermore , overexpression of human KCC2 mRNA in embryos replicated the wnk1/hsn2 knockdown phenotype . We validated these results by obtaining double knockdown embryos , both for wnk1/hsn2 and kcc2 , which alleviated the PLL defects . Interestingly , overexpression of inactive mutant KCC2-C568A , which does not extrude ions , allowed a phenocopy of the PLL defects . These results suggest a pathway in which WNK1/HSN2 interacts with KCC2 , producing a novel regulation of its transcription independent of KCC2's activation , where a loss-of-function mutation in WNK1 induces an overexpression of KCC2 and hinders proper peripheral sensory nerve development , a hallmark of HSANII .
Hereditary sensory and autonomic neuropathies ( HSAN ) are rare inherited neuropathies predominantly characterized by sensory dysfunction associated with variable degrees of autonomous and motor involvement . HSANs were first classified in five distinct types according to clinical presentation of symptoms as well as age of onset and mode of inheritance 1 . These distinct categories were later confirmed by identification of causative mutations by genome linkage studies , revealing heterogeneity amongst HSAN types both clinically and genetically . HSAN type 2 ( HSANII , OMIM#201300 ) is of autosomal recessive inheritance and is characterized by an early onset sensory neuropathy , causing patients to lack all sensory modalities in a strictly peripheral glove-and-stocking distribution leading to a diagnosis in the first two decades of life 2 . Other characteristics include a loss of tendon reflex , skin ulceration , Charcot joint , and spontaneous amputations while excluding motor involvement 3 , 4 , 5 . In addition , upon sural nerve biopsy in affected patients , a reduction in the number of myelinated fibers is observed as well as a slight decrease in the number of non-myelinated fibers 6 , 7 . In the absence of evidence suggesting degenerative changes in the peripheral nerves , HSANII is believed to be non-progressive and has been argued as being due to improper development 5 . Despite there being published cases of HSANII since the last century , the mechanism leading to this disorder is still not understood . Mutations restricted to an intron within the WNK1 ( lysine deficient protein kinase 1 ) gene were found to be responsible for HSANII ( location 12p13 . 33 , gene/locus OMIM #605232 ) . This sequence was at first attributed to a new gene-within-a-gene and named ‘HSN2’ for hereditary sensory neuropathy type 2 8 but it was later revealed to be an alternatively spliced exon of the serine/threonine kinase WNK1 , nestled between exon 8 and 9 of the 28 exon gene 9 . WNK1 ( NCBI Gene ID: 65125; HGCN:14540 ) is one of four members of the with-no-lysine ( K ) kinases , characteristic among other serine/threonine kinases by a uniquely placed lysine involved in ATP binding . Each WNK member contains a well-conserved kinase domain and multiple coiled-coil domains as well as a host of proline-rich regions and potential SH3 domain binding-sites , pointing to an involvement in protein complex formation and modulation of signaling 10 . A large section of the WNK1 gene , including exon HSN2 , has no reported motifs suggesting any particular function . However , the isoform including the HSN2 exon , termed WNK1/HSN2 , has been found to be selectively expressed in the nervous system whereas other isoforms of the WNK1 kinase are quite ubiquitously expressed in the CNS and other tissues 9 , 10 . Within the neuron , WNK1/HSN2 is also sublocalized differently being found in the axon and cell body while isoforms lacking the HSN2 exon are confined to the cell body 9 . All mutations in the HSN2 exon reported to date are loss-of-function mutations , producing an early terminated mRNA which leads to a truncated protein 7 , 11 . While a WNK1 knockout has proved to be lethal in mouse embryos , suggesting an important role in early development , selective knockout of the HSN2 exon has not been attempted thus far 12 . The functions of WNK1 in the nervous system are not well understood . This kinase has been reported to interact with KCC2 , potassium-chloride cotransporter type 2 ( SLC12A5 gene for ‘solute carrier family 12 , ( potassium-chloride transporter ) member 5’ , NCBI Gene ID: 57468 , HGCN:13818; 13 , which is selectively expressed in neurons and participates in the regulation of the chloride gradient . WNK1 phosphorylation of KCC2 occurs in immature neurons but is absent in adult neurons 13 , 14 , emphasizing a developmental role . Interestingly , KCC2 has been shown to regulate neurogenesis in the zebrafish ( Danio rerio ) spinal cord 15 , 16 , which suggests it may also play a role in peripheral neurogenesis . We therefore used this simple model to investigate whether WNK1 is implicated , perhaps via KCC2 , in the development of the peripheral nervous system of zebrafish .
To investigate whether loss-of-function mutations in WNK1/HSN2 led to improper development of the peripheral nervous system , we used the zebrafish as it is a well-established model that is ideal for developmental biology since the first day post-fertilization roughly corresponds to the first trimester of mammalian development 17 . It is also a model that has proven efficient in the study of functional genomics and pathogenesis of neurodegenerative disorders , with a relatively simple nervous system eliciting stereotyped responses 17 , 18 , 19 , 20 . We first identified the zebrafish orthologs of the WNK1 kinase . Two separate loci were identified , named wnk1a ( NCBI Gene ID: 100318736 , ZFIN ID: ZDB-GENE-080917-49 , chromosome 25 ) and wnk1b ( NCBI Gene ID: 561159 , ZFIN ID: ZDB-GENE-030131-2656 , chromosome 4 ) . These two genes were confirmed via Ensembl ( Ensembl : ENSDARG00000078992 ) . Only wnk1b conserves the HSN2 target exon ( Figure 1A ) and wnk1a appears to also be missing exons 11 , 20 , 21 and 22 . Both copies have a split exon 10 , and exons 11 to 13 of wnk1b are fused , which also appears in the Xenopus laevis ortholog sequence . We next examined the developmental expression pattern of wnk1b . As the expression of the WNK1/HSN2 isoform had previously been assessed by Western blot in adult mouse tissue only 9 , and there was no data available for its expression during embryogenesis . We first obtained an mRNA expression profile for both wnk1a and wnk1b by RT-PCR for zebrafish from the 16 cell stage to 7 days post-fertilization ( dpf ) ( Figure 1B ) . Both orthologs were expressed early on with wnk1b expression increasing during the first few days whereas wnk1a expression was high from the start and maintained . The presence of the wnk1 and its wnk1/hsn2 isoform at the 16 cell stage ( 1 . 5 hpf ) likely corresponds to a maternal transcript which leads early development prior to transcription of the zygotic genome at 3 . 5 hpf 21 , 22 . To localize the specific wnk1/hsn2 isoform within the nervous system , we performed whole-mount immunohistochemistry on 4 dpf zebrafish embryos using the previously described anti-HSN2 antibody 9 . This revealed localization of the wnk1/hsn2 isoform ( transcribed from the wnk1b gene ) at the level of the posterior lateral line ( PLL ) neuromasts ( Figure 1C ) and not in the spinal cord . The wnk1/hsn2 protein was found within the two major neuromast cell types: hair cells and the support cells ( inset , Figure 1C ) . This localization is consistent with HSANII to the extent that the neuropathy affects the peripheral sensory system and that the PLL is a peripheral mechanosensory system , albeit specific to aquatic animals . In order to replicate the pathogenic loss-of-function of the WNK1/HSN2 isoform linked with HSANII causative mutations , we designed antisense morpholino oligonucleotides ( AMO ) targeting the start codon of wnk1b ( AMO targets , Figure 1A ) . We also designed AMOs targeting the splice junction sites of exon hsn2 of the wnk1b gene , MO-hsn2-SB5′ and MO-hsn2-SB3′ , respectively targeting the splice donor and splice acceptor sites . As the wnk1/hsn2 protein was detected by immunohistochemistry at the level of the PLL , we started by observing this mechanosensory system upon knockdown . Knockdown embryos for all three conditions were morphologically indistinguishable from non-injected animals at 72 hpf but staining of the lateral line with the fluorescent vital dye 4-di-2-ASP revealed defects in the formation of the PLL ( Figure 2A ) . In order to quantify this phenotype , we attributed a score to each PLL neuromast depending on fluorescence to account for both their presence and composition , as was done previously 23 . The scores were attributed accordingly: Full , fluorescent neuromast = 2 points; smaller or dim neuromast = 1 point; absent neuromast = 0 point . As the data was non-parametric , medians values were used to compare groups . In the wild-type non-injected fish ( PLL neuromasts mid-body to tail , n = 108 embryos ) we obtained a median value of 28 . 0 for the 4-di-2-ASP score . All three knockdowns , although with varying efficiency , revealed a significantly lower score , with median values of 3 . 0 , 12 . 0 and 19 . 0 for MO-hsn2-SB3′ ( n = 135 embryos ) , MO-hsn2-SB5′ ( n = 166 embryos ) and MO-wnk1b-ATG ( n = 141 embryos ) respectively , when compared with wild-type embryos ( one-way ANOVA with Dunn's multiple comparison , Figure 2B ) . We further confirmed the specificity of the knockdown phenotype by rescuing it with wild-type human WNK1 mRNA . Two constructs were assembled for the human sequence: a complete construct spanning exons 1 to 28 ( but skipping small exons 11 and 12 which were unavailable ) and a partial construct composed only of exons 1 to HSN2 ( i . e . lacking exons 9 to 28 , Figure 2C ) tested over a range of concentrations ( Figure S1 ) . The complete construct was co-injected with the most efficient AMO , namely MO-hsn2-SB3′ and significantly alleviated the PLL defect phenotype , without however bringing it back to wild-type level , at concentrations of 50 and 75 ng/µl ( Figure 2D green boxes ) . The partial construct proved unable to rescue the knockdown phenotype when co-injected at similar concentrations with the AMO and thus confirmed the predicted loss-of-function of WNK1 following HSANII truncating mutations in the HSN2 exon 7 , 11 ( Figure 2D blue boxes ) . To further characterize the defects in PLL formation , we examined the structure of individual neuromasts by knocking down wnk1/hsn2 in transgenic embryos expressing GFP under the Xenopus laevis neuron-specific beta-tubulin promoter Tg ( NBT:MAPT-GFP ) 24 which allowed us to visualize structural hair cells based on the presence of beta-tubulin as revealed by expression of GFP ( Figure 3A ) . An effort was made to count all PLL neuromasts of observed embryos , disregarding terminal neuromasts found at the tip of the tail because they arise from fragmentation of the primordium at the end of migration , and not by deposition of pro-neuromasts along the dorsal midline 25 . The number of structural hair cells per PLL neuromast for all three types of wnk1/hsn2 knockdown embryos was significantly lower than for non-injected transgenic embryos , with median values of 4 . 0 , 6 . 0 and 5 . 0 hair cells per neuromast for MO-hsn2-SB3′ ( n = 80 neuromasts , 38 embryos ) , MO-hsn2-SB5′ ( n = 73 neuromasts , 19 embryos ) and MO-wnk1b-ATG ( n = 56 neuromasts , 16 embryos ) respectively , when compared with wild-type embryos which had a median value of 10 . 0 hair cells per neuromast ( n = 106 neuromasts , 20 embryos; non-parametric distributions , one-way ANOVA with Dunn's multiple comparison; Figure 3B ) . We then confirmed this decrease by looking at the number of functional hair cells revealed by the vital styryl dye FM-464FX 26 . Knockdown for wnk1/hsn2 was obtained in transgenic embryos expressing GFP under the claudin-b promoter Tg ( -8 . 0cldnb:lynEGFP ) , which allows membrane labeling of primordium cells as well as neuromast hair cells and support cells 27 . The knockdown and non-injected transgenic embryos were then incubated in FM-464FX and observed under fluorescence , where whole neuromasts would be seen in green ( GFP ) and hair cells , in red fluorescence ( FM-464FX ) ( Figure 3C ) . While the number of support cells ( labeled only in green ) did not seem to decrease , the number of functional hair cells per neuromast decreased in a similar fashion to what had been observed for structural hair cells , where knockdown embryos had median values of 0 . 0 , 3 . 0 and 2 . 0 hair cells per neuromast for MO-hsn2-SB3′ ( n = 21 neuromasts , 9 embryos ) , MO-hsn2-SB5′ ( n = 69 neuromasts , 16 embryos ) and MO-wnk1b-ATG ( n = 62 neuromasts , 12 embryos ) respectively , when compared with non-injected embryos which had an median value of 8 . 0 hair cells per neuromast ( n = 85 neuromasts , 15 embryos; non-parametric distributions , one-way ANOVA with Dunn's multiple comparison; ( Figure 3D ) . The PLL defect phenotype thus seemed to leave support cells unaffected , suggesting a problem in neural maturation with only the hair-cell-fated neuromast progenitors failing to become functional . The activity of the neuronal-specific KCC2 had recently been shown to be regulated by the WNK1 kinase , where phosphorylation decreased KCC2 activation 14 . Because of this , we predicted the knockdown phenotype could increase the activity of the cotransporter , as it is usually downregulated by WNK1 kinases . In zebrafish , it has previously been shown that KCC2 ( slc12a5 gene , Ensembl: ENSDARG00000078187 , ZFIN ID: ZDB-GENE-080707-1 ) becomes expressed in parallel with neuronal maturation . Its delayed expression allows a timely reversal of the chloride gradient and is essential for appropriate neuronal differentiation 15 . In the absence of an antibody detecting kcc2 specifically in zebrafish , we examined mRNA levels by RT- PCR . At 72 hpf , when the PLL defect phenotype is visible in wnk1/hsn2 knockdown embryos , we indeed found a higher expression of slc12a5 ( Figure 4A ) . To determine if this overexpression was also a premature expression , which has been found to cause dendritic spine defects 28 , we also looked at mRNA levels at 24 hpf and found early overexpression , shown for the most effective knockdown condition ( Figure 4A ) . To confirm that KCC2 is implicated in the wnk1/hsn2 PLL phenotype , we overexpressed human KCC2 mRNA in WT embryos as was previously described 15 . At 72 hpf , embryos showed a normal morphology , though some animals had a shorter tail ( Figure 4B ) . Upon labeling of the PLL with 4-di-2-ASP , we observed defects similar to the ones of wnk1/hsn2 knockdown embryos and confirmed a decrease in hair cell number , both structurally ( Figure 4C ) and functionally ( Figure 4D , black boxes ) upon overexpression of KCC2 . If the increase in slc12a5 expression ( coding for kcc2 ) following knockdown of wnk1b is indeed responsible for the loss of neuromasts , then we reasoned that knockdown of both slc12a5 and wnk1b should rescue the phenotype . First we examined the effect of knockdown of slc12a5 on its own using a previously described AMO ( MO1-slc12a5 , 29 ) for which knockdown is viable but leads to embryos with altered morphology , often exhibiting a shorter tail and curved spine ( Figure 4B ) . Nonetheless , upon 4-di-2-ASP staining , these embryos had a structurally sound PLL , though with fewer neuromasts , which was probably due to their shorter length ( score relative to WT , Figure 4D ) . Finally , we tested co-knockdown of wnk1b and slc12a5 and observed a partial rescue of the PLL defect phenotype , as visualized with 4-di-2-ASP ( Figure 4D , green boxes ) , confirming that the KCC2 cotransporter is implicated in the establishment of the wnk1/hsn2 knockdown PLL phenotype . As the presence of kcc2 has never been assessed in the zebrafish nervous system , we performed an in situ hybridization against slc12a5 , revealing its expression in the hindbrain , in the rostral spinal cord and in neuromasts of 4dpf embryos ( Figure 5A ) . Prior to kcc2 functional expression in the early zebrafish embryo , the chloride gradient is depolarizing due to the high chloride content 30 . As a result , brief glycine application depolarizes the cells and evokes a Ca2+ transient 31 . In contrast , we expected that if kcc2 is functionally expressed in neuromasts , the chloride content in its cells will be low and application of glycine will fail to evoke Ca2+ transients . We therefore loaded neuromasts with the Ca2+ indicator Rhod-2 AM and visualized their hair cells in 3–4 dpf transgenic Tg ( tub:MAPT-GFP ) embryos expressing GFP in axons . We observed that application of glycine onto these neuromasts ( Figure 5C ) failed to evoke Ca2+ transients ( as shown in Figure 5B top image and traces; n = 4 neuromasts ) whereas glutamate application did ( Figure 5B middle image and traces ) , indicating that these neuromast cells were viable but unresponsive to glycine presumably due to the presence of kcc2 and a low intracellular chloride level . In contrast , application of glycine onto the primordium of 2dpf embryos visualized in Tg ( -8 . 0cldnb:lynEGFP ) 27 expressing GFP under the claudin-b promoter in cells composing the migrating primordium , progenitors of PLL neuromasts , and co-labeled with Rhod-2 AM evoked clear calcium transients ( Figure 5B bottom image and traces; 6 cells in 2 primordia ) . This observation suggests a high chloride content in neuromast progenitor cells , the migrating primordium , much like the observations in spinal cord progenitors of equivalent stage zebrafish embryos 15 , 32 . In summary , the lack of glycine evoked Ca2+ transients in neuromasts contrasted to their presence in the primordium and suggests that , as for spinal cord progenitors , kcc2 expression in neuromasts is functional and could be implicated in neural differentiation . This corroborates our previous results , showing an implication of KCC2 in WNK1/HSN2 knockdown phenotype , affecting the PLL . Previous experiments in zebrafish reported that overexpression of KCC2 leads to impaired neurogenesis by perturbing neuronal maturation 15 , 16 . KCC2 has also been reported to be involved in mammalian neural development as a premature overexpression disrupts development of the neural tube by diminishing neuronal differentiation , leading to mouse embryos with a thinner neural tube and abnormal body curvature 33 . To characterize the effect of KCC2 overexpression on PLL progenitors , we injected Tg ( -8 . 0cldnb:lynEGFP ) embryos and observed the primordium in live embryos in order to assess its size after departure from the cephalic placode but before deposition of the first pro-neuromast . It was not possible to count each individual cell as the primordium is a highly motile structure that is constantly reorganizing its cells . In an effort to quantify the observed effect , we embedded live animals in agarose while positioning them on their side , allowing us an optimal view of the primordium . We then captured images and measured the surface area of the primordium as revealed by GFP expression . WNK1/HSN2 knockdown embryos , as well as embryos overexpressing human KCC2 , showed a significantly smaller primordium ( Figure 5D ) . As the size of primordium cells and organization seemed conserved for all conditions ( close-up , Figure 5C ) , we conclude that an overexpression of KCC2 , whether it be by injection or induced by wnk1/hsn2 knockdown , resulted in a lower number of PLL progenitors . While the size of the primordium was reduced both in wnk1/hsn2 knockdown and in KCC2 overexpressing embryos , the organization and size of primordium cells seemed to be conserved ( Figure 5C ) . KCC2 has been shown to have a role independent of its transporter activity , for example by influencing the development of dendritic spines through interaction with cytoskeleton protein 4 . 1 N 33 , 34 , where loss 35 or premature expression 28 of KCC2 respectively induced abnormal morphology ( lower number of functional spines ) and an increase in dendritic spine density . Furthermore , phosphorylated KCC2 is found in neurons before the GABAergic response switch 36 and the implication of KCC2 in neuronal differentiation of the embryonic mouse neural tube was also shown to be independent of KCC2 activation and therefore independent of its chloride extruding function 33 . To determine whether the PLL defect phenotype resulting from KCC2 overexpression was due to its transporter function as a modulator of intracellular chloride concentration , we synthesized RNA for KCC2-C568A as this dominant-negative mutation has been shown to impair the chloride extruding function of the cotransporter and was used successfully as a control in the zebrafish spinal cord model 15 . Here we show that overexpression of this inactive KCC2 mutant impairs proper PLL development in a similar manner to wild-type KCC2 , as observed by 4-di-2-ASP staining ( score , Figure 4E ) . We therefore suggest that loss of WNK1/HSN2 leads to an overexpression of KCC2 by a novel mechanism to regulate its transcription and that this overexpression impairs proper peripheral nervous system development in an activity-independent manner .
In this study , we show that WNK1/HSN2 truncating mutations associated with HSANII lead to a loss-of-function of this kinase isoform which causes developmental defects in a relevant structure in zebrafish , by impairing PLL formation . By immunohistochemistry , we showed localization of this isoform in the neuromasts composing the PLL and presented evidence of early mRNA expression for both zebrafish WNK1 orthologs , suggesting a role in early development . We showed that knockdown of wnk1b resulted in a defect of the peripheral nervous system manifested by fewer PLL neuromasts each containing fewer hair cells , measured both by their structural presence and by functional assessment , and that this specific phenotype could be partially rescued upon co-injection of wild-type human WNK1 . The low efficiency of the rescue for the wnk1/hsn2 knockdown phenotype by human WNK1 RNA injection could be due to the fact that the human and zebrafish sequences are only 47% identical . Additionally , the constructs were made with no regard to endogenous patterns of alternative splicing as the HSN2 exon is poorly characterized and splicing data is sparse . It is possible that it is inadequately processed in zebrafish and can therefore only be of limited use in rescuing the knockdown phenotype . By injection of a partial construct mimicking truncating mutations in exon HSN2 we also confirmed the loss-of-function of this isoform in HSANII . We found an overexpression of neuronal cotransporter kcc2 ( slc12a5 gene ) in wnk1/hsn2 knockdown embryos , both at 72 hp and at 24 hpf . We replicated the PLL defect phenotype obtained in wnk1/hsn2 knockdown by overexpressing human KCC2 RNA in embryos , confirming a pathological link . To verify this link , we knocked down both wnk1/hsn2 and slc12a5 by co-injecting AMOs , which partially rescued the PLL defect phenotype , thereby validating that this overexpression led to improper PLL development . The slc12a5 knockdown yielded morphologically abnormal embryos which still had a nicely developed PLL , though comprised of fewer neuromasts due to their shorter length . This observation is expected as KCC2 is known to be essential for proper neural development 15 , 36 , 37 , 38 , 39 . Indeed , Kcc2 knockout in mice is embryonic lethal , causing defects in the development of the motor system leading to asphyxiation , as a reversal in GABAergic response necessary for proper neuronal maturation is never achieved 40 . Knockdown of Kcc2 in neurons was also proven to compromise survival , by loss of its chloride extruding function 41 . Both of these studies divulge a crucial for KCC2 in development and it is therefore not surprising to find abnormal morphology in embryos lacking a large proportion of their Kcc2 . In contrast , overexpression of KCC2 leads to a neurogenic defect in the spinal cord of the early zebrafish embryo 15 . Together , these observations support an important role of KCC2 regulation of the chloride gradient during development of the central nervous system . We also demonstrated that kcc2 was localized to the peripheral nervous system ( by in situ hybridization ) at the level of the mature neuromast . Since KCC2 is known to be involved in neuronal maturation and proliferation , we assessed its effect on PLL progenitors . We found that embryos knocked down for wnk1/hsn2 ( which overexpress kcc2 ) and embryos overexpressing human KCC2 had a smaller primordium , while maintaining normal cell size and organization , which led us to the conclusion that they contain fewer progenitor cells . However , the impact of this result on PLL formation is not clear . Indeed , the effect of primordium size on pro-neuromast deposition is a debated subject . It was previously reported 42 that ablation of up to two-thirds of the primordium leads to a defective PLL . This observed pattern is similar to the one observed in embryos lacking lef1 , a major effector of Wnt signaling involved in the control of cxcr4b and cxcr7b , two chemokine receptors involved in PLL migration . The ablated and lef1-defficient primordium size is reduced after each deposition , and eventually disappears , having presumable run out of cells to deposit 42 . Another study 43 has however discovered that a reduction of Notch activity gives rise to a smaller primordium , but the neuromasts deposited are of smaller size , rather than of regular size but fewer in number . This suggests a mechanism controlling the number of deposited pro-neuromast rather than one maintaining the size of deposits 43 . The data was only acquired for the L1 pro-neuromast deposit and therefore it is possible that proliferative mechanisms taking place at the head of the migrating primordium 44 , compensating for the deposits during migration , would be affected , leading to more severe defects further along in the PLL . While we did observe smaller primordia in wnk1/hsn2 knockdown and KCC2 overexpressing embryos , we can only suggest a possible role in progenitor proliferation , where as previously proposed , the deposition is triggered when the primordium reaches a threshold size 42 . In this instance , progenitor proliferation would be affected at the placode and at the level of the mitotic head of the migrating primordium either by WNK1 as previously suggested ( effect on proliferation , 45 ) , or through interference of Notch signaling 43 . We therefore propose that loss of WNK1/HSN2 deregulates the levels of KCC2 . Mechanisms controlling KCC2 expression are only beginning to be uncovered and due to a strikingly rapid turnover of the cotransporter at the cell membrane studies mostly looked at how activation influences transcription . For instance , it was previously shown that BDNF induces Egr4 expression , which rapidly activates the KCC2b promoter in immature neurons , increasing the expression of the KCC2 protein . In mature neurons , the BDNF/TrkB signaling pathway involving a downstream cascade implicating Shc/PRS-2 and PLC-gamma 46 was also found to reduce KCC2 expression , in an activity-dependent manner 47 . As for the downregulation of KCC2 , it has been observed upon functional loss , where various stresses induced tyrosine dephosphorylation , resulting in decreased levels of KCC2 protein and mRNAs 48 . These results also suggest KCC2 transcription could be controlled by its levels of activation , where rapid inactivation leads to a decreased production of mRNAs . We were also able to mimic the PLL defect phenotype upon injection of an inactive KCC2 mutant ( C568A ) although it was achieved with statistical difference from both the wild-type embryos and the ones overexpressing hKCC2 . These results suggest that a novel regulation of transcription , independent of KCC2 activation , may contribute to the phenotype . It will be therefore important to consider other roles of KCC2 with regards to its implication in neuronal development . For instance , this cotransporter has been reported to play a morphogenic role in dendritic spine formation 28 and is known to interact with cytoskeleton-associated protein 4 . 1 N 35 ) . This interaction has also been shown to be diminished for the KCC2-C568A mutant where an overexpression could not replicate aberrant actin and 4 . 1 N patterns observed upon overexpression of WT KCC2 33 . This could explain why we could not obtain a PLL phenotype as severe following injection of KCC2-C568A in zebrafish as what is observed when embryos overexpress KCC2 ( Figure 4E ) . Since proteins like 4 . 1 N anchor the cytoskeleton to the plasma membrane 49 , interaction with KCC2 , possibly regulated by WNK1 phosphorylation , could prove crucial at this level . HSANII mutations found in the KIF1a kinesin 50 could also affect transport of cargo along the microtubules or unloading at axonal tips . Previous studies localizing KCC2 mRNAs in rat have been unable to find staining in the primary sensory neurons of the dorsal root ganglia ( DRG ) and of the trigeminal nucleus presumably because these neurons have depolarizing responses to GABA , where the high intracellular chloride concentration is maintained by expression of NKCC1 38 . However , another KCC family member KCC3 is also expressed in neurons , some interneurons , as well as in the spinal cord and in radial glia-like cells 51 . This cotransporter has been studied in the context of hereditary motor and sensory neuropathy with agenesis of the corpus callosum ( HMSN/ACC ) , where causative mutations have been identified in SC12A6 ( coding for KCC3 ) 52 . Truncating as well as loss-of-function mutations have been reported to cause mis-trafficking of proteins , decreasing their plasma membrane expression 53 . This neuropathy is characterized by progressive sensory-motor deficits , where axonal swelling can be observed in patients . Since it is also found in radial glia-like cells , a role for KCC3 in migration and proliferation has been proposed 51 . Additionally , KCC3 has homologous regulatory sites to the ones found on KCC2 , phosphorylated by WNK1 ( T991 and T1048 in KCC3 ) 13 , but it has been reported to be unable to interact with cytoskeleton-associated protein 4 . 1 N 35 . Both KCC2 and KCC3 deregulation could therefore be involved in improper development of the peripheral sensory nervous , with KCC2 leading to HSANII pathogenesis . This article presents the first findings of the molecular basis for HSANII . The zebrafish model we have developed by use of AMO technology exhibited defects in a peripheral sensory system ( the PLL ) which were apparent during embryonic development , similar to the clinical description of HSANII . Motor defects were also absent upon observation of motor neurons in our wnk1/hsn2 knockdown embryos , which is also a characteristic of HSANII ( Figure S2 ) . Likewise , overexpression of KCC2 was shown previously to affect spinal cord interneuron populations but not motoneurons or intrinsic ( Rohon-Beard ) sensory neurons 15 , 16 and wnk1/hsn2 was not detected in the spinal cord , consistent with a selective role in sensory lateral line development . We hypothesized that the mutations identified in the HSN2 exon of HSANII patients , producing a truncated protein , would lead to a loss-of-function of this WNK1 and have validated this by using an AMO targeting the start codon of the wnk1 gene , blocking translation of all isoforms in the zebrafish embryos . However , by modifying the splicing patterns by use of the splice blocking AMOs , we confirmed that loss of the hsn2 exon was enough to induce the pathogenic phenotype . It is important to point out that this model is a transient one , due to the use of AMO technology , and that it does not provide full knockdown efficiency . It is therefore possible that the phenotype is not as severe as it would be in knockout animals and in future studies a zebrafish knockout could be obtained by genome editing . We have also identified a pathway involving the KCC2 cotransporter as a downstream target of the WNK1/HSN2 isoform . This cotransporter has been linked to neural differentiation and its regulation by WNK1 has previously been reported , but the interaction between them has not been investigated . Our results suggest the HSN2 exon is critical for normal development to take place and it would be very interesting to understand how its loss influences KCC2 expression or affects WNK1 binding to the cotransporter . Our results in the zebrafish indicate that KCC2 regulation by WNK1 is an important factor in promoting peripheral nerve development , which may be compromised in HSANII . Whether this is due to regulation of the chloride gradient and peripheral neurogenesis or in addition to a transport-independent KCC2 action in concert with related transporters remains to be determined .
A colony of wild-type zebrafish ( Danio rerio ) was bred and maintained according to standard procedures 54 . All experiments were performed in compliance with the guidelines of the Canadian Council for Animal Care and the Comité de déontologie de l'expérimentation sur les animaux ( CDEA ) of the University of Montreal . Embryos were anesthetized in 0 . 02% tricaïne ( MS-222 , Sigma ) in Embryo medium prior to all experiments . We used embryos from transgenic lines expressing green fluorescent protein ( GFP ) under various promoters as neuronal population markers . Tg ( -8 . 0cldnb:lynEGFP ) : membrane-tethered EGFP ( enhanced GFP ) is under the claudinB promoter labeling the migrating lateral line primordial , the neuromast organs as well as the chain of interneuromast cells deposited during migration 27 . Tg ( NBT:MAPT-GFP ) : GFP is expressed under the Xenopus laevis neuron-specific beta-tubulin promoter 24 . The sequence of human WNK1 was used to find homolog sequences in GenBank , leading to the identification of the Xenopus laevis ortholog of WNK1 . We then used this ortholog sequence to search the zebrafish assembly using the BLAT genome browser from UCSC ( http://genome . ucsc . edu/ ) . The identified genomic sequence from zebrafish was then analyzed , and exons were identified through EST alignments or comparative genomic techniques . cDNA sequences were reconstituted based on the predicted exons and ORFs from the predicted cDNAs were used to derived the predicted peptide sequences . Exons were numbered from 1–28 and the HSN2 name was conserved for the target exon present only in the zebrafish wnk1b ( chromosome 4 ) . Orthologous protein sequences were aligned using CLUSTALW and amino acid identity/similarity was calculated using MatGAT program v2 . 01 . Exons 11 to 13 are fused , as is the case with Fugu and Tetradon , and exon 10 has been split in two smaller exons . The human WNK1 and zebrafish wnk1b orthologs are 47 . 4% identical and 56 . 8% similar along the full length of the proteins . We also compared the HSN2 exon sequence , but since the human putative exon 8b sequence 9 contains several frameshifting mutations , the chimp sequence was used instead for comparison purposes . Chimp and zebrafish wnk1b HSN2-like peptide sequences are well conserved , being 54 . 7% similar and 38 . 2% identical . In order to obtain a knockdown of the wnk1/hsn2 isoform , we designed splice-block ( SB ) AMOs specific to the donor and acceptor splice sites of the HSN2 exon to interfere with pre-mRNA splicing ( MO-hsn2-SB3′: 5′ - CGAGAACGAGTATTTCTAGGTACCA - 3′ and MO-hsn2-SB5′: 5′ - TGCAGTGACAATAACATACAGCATC - 3′ ) . We also designed an AMO targeting the initiation codon of wnk1b , inhibiting protein translation from the only copy of the gene containing the HSN2 exon ( MO-wnk1-ATG: 5′ - TTGGGATTTCCGATGACATCTTC - 3′ ) ( Gene Tools , Philomath , OR ) . To knockdown zebrafish kcc2 we used two AMOs targeting the initiation codon , the first of which had been previously used in another study ( MO1-slc12a5 : 5′ - TGGATGTTGCATCTCCTGTGAACAT - 3′ from 29 ) and the second was designed according to the latest zebrafish genome assembly as a different target , confirming specificity of the resulting phenotype ( MO2- slc12a5 : 5′ – CTCCTTTGATCTCCAGTGTCTGCAT- 3′ ) . Human KCC2 mRNAs ( hKCC2 ) were transcribed from the Nhe1-linearized pGEMHE-KCC2 and pGEMHE-KCC2-C568A constructs using the T7 polymerase with the mMESSAGE Machine T7 Kit ( Ambion , Austin , TX ) as described previously 15 . Both constructs were injected at the same concentration known to cause an overexpression phenotype 15 , 16 . Human WNK1 constructs were assembled in the pCS2 vector with a Cytomegalovirus promoter and a Xenopus laevis beta-glotine UTR region . A partial construct ( containing exon 1 to HSN2 ) and a complete construct ( containing exon 1 to 28 , but missing exons 11 and 12 ) were both flanked with 6 myc tags . Exon 1 was amplified from human genomic , as well as exon HSN2 , while sequences from exons 2–9 and 10–28 were obtained from clones ( CF142377 and BC141881 respectively ) . mRNAs were transcribed from the KpnI-linearized plasmids using the mMESSAGE Machine SP6 Kit ( Ambion , Austin , TX ) . All AMOs and mRNAs were diluted in nuclease-free water ( Ambion ) with 0 . 2% FastGreen vital dye ( Sigma ) to judge of injection volume . Injections were performed in 1–4 cell stage zebrafish eggs using a Picospritzer III ( Parker Hannifin , Cleveland , OH , USA ) pressure ejector . Immunohistochemistry was performed as previously described 15 against the HSN2 exon with the anti-HSN2 antibody previously used 9 . The secondary antibody was a goat anti-rabbit Alexa Fluor 488 ( Invitrogen ) . Imaging was performed using a compound fluorescence microscope ( Nikon ) . All RT–PCR were performed using the Expand Long Template enzyme kit ( Roche ) against control housekeeping gene GAPDH performed with a 1∶2 cDNA dilution to avoid saturation . All samples were run on a 1% agarose gel containing ethidium bromide . Total RNA from embryos of different developmental stages was extracted using the TRIzol reagent ( Invitrogen , Carlsbad , CA ) and cDNA was synthesized using the RevertAid H Minus First Strand cDNA Synthesis kit ( Fermentas ) . Expression pattern of wnk1a and wnk1b was assessed using primer pairs amplifying the sequence between exon 1–8 and within exon HSN2 respectively . wnk1a_exon1_f: CTACAAGGGACTGGATACGGAAACTAC wnk1a_exon8_r: GAGCCTCGAGGATGGTCACTG wnk1b_hsn2_f: GGGATGCCGGCTCAAAGATT wnk1b_hsn2_r: TGATGGGACAAGGCAGGCTCGTG In order to permit a comparison of levels of endogenous kcc2 in our various wnk1/hsn2 knockdown embryos , several precautions were taken in the RT-PCR protocol . Batches of injected embryos from each different group were obtained for the same clutch and staged . The same number of embryo was taken from each condition to perform total RNA extraction using the TRIzol reagent . RNA extraction as well as cDNA synthesis for each experiment was done in parallel , using master mixes whenever possible . Prior to this , we tested PCR parameters for kcc2 primers using only wild-type cDNA in order to make sure the amplification would stay within the exponential amplification segment of the reaction in conditions where an overexpression occurs . The RT-PCR reaction was first tested using wild-type cDNA to establish the optimal condition for annealing temperature , elongation time as well as number of amplification cycles for comparison between conditions using the specific primer pair targeting endogenous kcc2 ( slc12a5 ) . Forward primer ( slc12a5_f ) : TTTCACCGAGGGCCACATTGACG . Reverse primer ( slc12a5_r ) : TCCACCTCCACGCACAAGAAGGAC . All samples from each experiment , as well as the GAPDH controls were run on the same 1% agarose gel . Hybridization was performed using sense and antisense probes designed against the zebrafish ortholog of KCC2 to view endogenous localization of slc12a5 mRNA . Embryos of 4dpf and 7dpf were processed for in situ hybridization using fluorescent FastRed as previously described 55 with minor modifications , allowing for conservation of the superficial lateral line structure . The lateral line was labeled using the vital dye 4- ( 4-diethylaminostyryl ) -N-methylpyridinium ( 4-di-2-ASP , Invitrogen ) diluted to 0 . 5 mM in embryo medium . Embryos were dechorionated and staged at 72 hpf then incubated in the solution for 30 minutes at 28 . 5°C . They were then washed 3 times 10 minutes in fresh embryo medium and anesthetized before imaging on an epifluorescence dissection microscope ( Olympus ) equipped with a Flea2 CCD Camera ( IEEE 1394 , Point Grey Research Inc . Richmond , BC , Canada ) . This protocol , adapted from 56 , 57 , 58 allows for visualization of full neuromasts , as the dye gets incorporated into hair cells as well as support cells during a longer incubation period . FM-464FX ( Invitrogen ) , a styryl dye fixable analog , was also used as a vital dye for labeling functional hair cells . Embryos were dechorionated and staged at 72 hpf , then incubated for 1 minute in a 5 µM solution made from a diluted stock in DMSO . Embryos were then washed in embryo medium and anesthetized before being imaged by confocal microscopy . Calcium imaging experiments were done using live transgenic embryos . To visualize the lateral line primordium and the neuromasts we used the Tg ( -8 . 0cldnb:lynEGFP ) embryos and to visualize the innervations of hair cells , we used the Tg ( NBT:MAPT-GFP ) expressing GFP under the neuron-specific promoter . 2–4 dpf embryos were anaesthetized in 0 . 02% tricaine ( MS-222 , Sigma ) diluted in Evans solution ( 134 mM NaCl , 2 . 9 mM KCl , 2 . 1 mM CaCl2 , 1 . 2 mM MgCl2 , 10 mM HEPES , 10 mM glucose , pH 7 . 8 , 290 mOsm ) . The embryos were then embedded in 2% low-melting-point agarose ( Invitrogen ) and placed on their sides in the recording chamber . Membrane-permeable Ca2+ indicator dye Rhod-2 AM ( Invitrogen/Molecular Probes ) was dissolved in DMSO with 20% Pluronic ( Invitrogen/Molecular Probes ) to yield a 10 mM stock solution and further diluted in Evans solution to a final concentration of 1 mM , as described previously 31 . A small volume of the Ca2+ indicator was then pressure injected ( Picospritzer III , General Valve Fairfield , N . J . , USA ) into the primordium or to the neuromast hair cell . Recordings were performed at room temperature in the presence of tricaine to block movement related Ca2+ transients 59 ( Ashworth and Bolsover , 2002 ) and started recordings 60 min after the dye injection . Evoked Ca2+ transients were acquired for 20 minutes at 0 . 5 Hz ( Volocity software , PerkinElmer ) by confocal microscopy . To evoke calcium transients , glycine ( 1 M ) or glutamate ( 100 mM , Na-glutamate , Sigma ) were ionophoresed ( MVCS-02 , npi , Tamm , Germany ) from a fine glass pipette ( 20–30 MΩ ) 31 . Background-corrected images were analyzed off-line with Volocity software and average changes in Ca2+ levels within regions of interest were calculated as ΔF/F , which is the ratio between the fluorescence change ( ΔF ) and the baseline fluorescence before stimulation ( F ) . The images of the primordium presented in Figure 5 C were created by overlaying images taken from the green ( GFP ) and red ( Rhod-2 AM ) channels , while a bright field image of the neuromasts was added to better illustrate the location of the structure . Embryos were anesthetized in 0 . 02% tricaïne ( MS-222 ) in embryo medium and embedded in 1% low melting point agarose . Imaging was performed on a Quorum Technologies spinning-disk confocal microscope ( Quorum WaveX Technology Inc Guelph , On , Canada ) mounted on an upright Olympus BX61W1 fluorescence microscope with water-immersion lenses . The setup was fitted with a Hamamatsu ORCA-ER camera and image acquisition was done with the Volocity software ( Perkin-Elmer ) and analyzed with the ImageJ software ( NIH ) . Stacks were acquired at 1 µm thickness and assembled in ImageJ before analysis . Merged images were obtained in Volocity and exported as TIFF files to be used in figures . Images were resized , cropped and brightness was adjusted using Photoshop CS2 ( Adobe ) , the figures were assembled in Illustrator CS2 ( Adobe ) . Data was plotted and analyzed using the Sigma Plot 11 software ( Systat Software Inc . , San Jose , CA , USA ) and statistical significance was determined using one-way ANOVA combined with the Holm-Sidak method of comparison ( normal distribution ) or using Kruskall-Wallis one way ANOVA on ranks combined with Dunn's method of comparison ( non-parametric distribution ) . Non-parametric data are presented using medians , data ranges in a box plot diagram . Each box features a central line representing the median value , where the box itself delineates 25–75% of the data range and error bars represent 10–90% of the data range . Outlying data points are represented as circles outside the box . Significance was established at p<0 . 05 . | Hereditary sensory and autonomic neuropathy type 2 ( HSANII ) is a rare human pathology characterized by the early loss of sensory perception . It arises from expression of autosomal recessive mutations confined to an alternatively spliced exon of the WNK1 ( with-no-lysine protein kinase 1 ) serine-threonine kinase , which confers nervous system specificity . In zebrafish embryos , wnk1/hsn2 is expressed in the neuromasts of the posterior lateral line ( PLL ) , a peripheral mechanosensory system of aquatic animals . Defects in the development of this system , both in the number of individual neuromasts and of the hair cells they possess , were observed upon knockdown of the wnk1/hsn2 isoform . We investigated interactions between the WNK1 kinase and the neuronal potassium chloride cotransporter 2 ( KCC2 ) in the context of HSANII , as KCC2 has been implicated in regulating neurogenesis . WNK1 is known to phosphorylate KCC2 , regulating its activity and possibly its expression levels . We found that kcc2 is expressed in mature neuromasts and observed an increased level of kcc2 RNA in wnk1/hsn2 knockdown embryos . We suggest that the loss-of-function mutations in WNK1/HSN2 linked with HSANII lead to an imbalance in the levels of KCC2 , deregulating its levels of transcription and hindering proper peripheral nervous system development . | [
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] | 2013 | WNK1/HSN2 Mutation in Human Peripheral Neuropathy Deregulates KCC2 Expression and Posterior Lateral Line Development in Zebrafish (Danio rerio) |
The retromer mediates protein trafficking through recycling cargo from endosomes to the trans-Golgi network in eukaryotes . However , the role of such trafficking events during pathogen-host interaction remains unclear . Here , we report that the cargo-recognition complex ( MoVps35 , MoVps26 and MoVps29 ) of the retromer is essential for appressorium-mediated host penetration by Magnaporthe oryzae , the causal pathogen of the blast disease in rice . Loss of retromer function blocked glycogen distribution and turnover of lipid bodies , delayed nuclear degeneration and reduced turgor during appressorial development . Cytological observation revealed dynamic MoVps35-GFP foci co-localized with autophagy-related protein RFP-MoAtg8 at the periphery of autolysosomes . Furthermore , RFP-MoAtg8 interacted with MoVps35-GFP in vivo , RFP-MoAtg8 was mislocalized to the vacuole and failed to recycle from the autolysosome in the absence of the retromer function , leading to impaired biogenesis of autophagosomes . We therefore conclude that retromer is essential for autophagy-dependent plant infection by the rice blast fungus .
Rice blast is one of the most serious and recurrent diseases destroying rice production worldwide [1 , 2] . The ascomycete fungus Magnaporthe oryzae infects rice tissues by forming a dome-shaped and melanized infection structure called appressorium [3 , 4] . Differentiation of appressorium is regulated by cell cycle progression that is accompanied by autophagy in the conidium leading to its programmed cell death [5 , 6] . In this process , most of the stored glycogen and lipids are quickly transported from the conidium into the developing appressorium in order to establish a high turgor pressure necessary for successful host penetration by the mature appressorium [7–9] . Subsequently , a narrow penetration peg emerges from the mature appressorium and enters the rice epidermis and differentiates into bulbous , branched invasive hyphae , which are bound by the host plasma membrane in the invaginated cell , allowing the fungus to proliferate within the living plant cells [4 , 10] . Macroautophagy is a highly conserved bulk degradation process required for stress response and nutrient signaling in eukaryotes . Autophagy requires the formation of double-membrane bound autophagosomes that engulf bulk cytoplasm ( nonselective ) or specific target cargos ( selective autophagy ) . The autophagosomes fuse with endosomes or the vacuoles to form autophagolysosomes to deliver the sequestered material for recycling and/or degradation [11 , 12] . A set of evolutionarily conserved autophagy-related genes ( ATG genes ) was initially identified in yeast [13 , 14] . In total , 22 ATG genes were identified in the rice blast fungus , and MoATG8 expression has been used to investigate the spatial pattern of autophagy induction during infection-related development [5] . Punctate autophagosomes are found to be enriched in infection-related structures such as conidia , germ tubes and appressoria [15 , 16] . Deletion of MoATG8 led to significant reduction in conidiation and defects in glycogen autophagy during conidiogenesis [15 , 16] . Furthermore , the MoATG8-deficient appressoria are nonfunctional and noninfectious due to an inability to undergo autophagic cell death and nuclear degeneration in conidia [5] . Genome-wide characterization of autophagy genes [15] further supports the critical role of autophagy in conidial cell death and the function of the appressorium in M . oryzae . However , the mechanisms regulating autophagy in M . oryzae remain elusive . The retromer complex is a conserved vital element of the endosomal protein sorting machinery [17] . It consists of two subcomplexes: a trimer of Vps35 , Vps29 and Vps26 for cargo selection , and a dimer of Vps5 and Vps17 for tubule or vesicle formation [18] . The retromer complex is known to participate in intracellular retrograde transport of cargos from the endosome to the proper organelles [19 , 20] . Loss or malfunction of retromer is associated with various pathological states due to protein mistargeting [17] . Serving as the core of retromer , Vps35 directly interacts with cargo proteins for sorting [19 , 20] . Recently , it was found that retromer played a role in the degradation of autophagic cargo to maintain lysosome function in Drosophila [21] . To our knowledge , the role of Vps35 or retromer in regulating autophagy and plant infection in plant fungal pathogens has not been assessed thus far . In this study , we report a crucial role for the retromer cargo recognition subcomplex in regulating the autophagic process during appressorial development and pathogenesis in the rice blast fungus . We demonstrate that loss of any of these retromer components , MoVps35 , MoVps26 , or MoVps29 , led to similar defects in fungal conidiogenesis and pathogenesis , which phenocopied the defects of ATG mutants including reduced turgor pressure , delayed turnover of glycogen and lipid bodies , and failure in autophagic cell death during conidial germination , and compromised pathogenicity of the blast fungus . Furthermore , our data suggest that MoVps35 regulates the autophagic process through retrieving the cleaved form of MoAtg8 from the vacuole after autolysosome formation . Therefore , our findings uncover a new function of retromer and shed light on the regulation of autophagy biogenesis in one of the most important fungal pathogens of rice and cereal crops .
We identified a single Vps35 ortholog MoVps35 in the M . oryzae proteome using BLASTP analysis . MGG_05089 ( hereafter MoVps35 ) showed 57% sequence identity to the yeast Vps35 ( S1 Table ) . To determine its function , two MoVPS35 null mutants were generated through targeted gene replacement with the hygromycin resistance cassette in the Δku70 background ( S1A and S1B Fig ) . Phenotypic analyses revealed that the mutant ΔMovps35 grew marginally slower ( about 72 . 4% of the WT , P<0 . 01 ) than the wild type on various culture media ( S1C Fig ) . This suggests that the loss of MoVPS35 likely reduces vegetative growth and/or overall fitness of M . oryzae . Given an important role for the cell wall in maintaining hyphal development and adaptation to the environment [22] , we further investigated the growth under cell wall or membrane stress conditions . In such growth assays , the ΔMovps35 showed decreased resistance to Calcofluor White ( CFW ) , congo red ( CR ) and sodium dodecyl sulfate ( SDS ) compared to the wild-type strain ( S2 Fig ) , suggesting that MoVps35 is involved in maintaining the integrity of the cell wall . We also found that in comparison to the wild type , ΔMovps35 showed a 19-fold decrease in conidiation ( S1D Fig and S1E Fig; P<0 . 01 ) . The differentiation of conidiophores is critical for conidial development [23 , 24] . Although the sympodial arrangement of the resultant mutant conidia remained unchanged ( S1D Fig ) , conidiophore differentiation was highly reduced in ΔMovps35 at 24 h post conidial induction ( S1F Fi . ) . Thus , the dramatic reduction of conidiogenesis in the ΔMovps35 likely results from decreased conidiophore formation . Genetic complementation via introduction of MoVPS35 restored proper growth and conidiation in the ΔMovps35 strain ( S1 Fig and S2 Fig ) . We conclude that MoVps35 , and by inference the retromer function , is essential for proper vegetative growth and asexual development in the blast fungus . We then assessed the pathogenicity of ΔMovps35 mutant on rice seedlings ( Oryza sativa cv . CO39 ) . When spray-inoculated on rice seedlings , the wild type as well as the complementation strain caused numerous typical blast lesions on leaves , whereas the ΔMovps35 mutant caused only a few small and isolated lesions ( Fig 1A ) . ΔMovps35 formed only 1 . 2 ± 1 lesions per 5 cm of leaf ( P<0 . 01 ) , whereas 69 . 7 ± 15 . 3 lesions were evident in leaves inoculated with wild-type conidia ( Fig 1A ) . Likewise , the barley infection assays ( cv . Golden Promise ) showed severe blast symptoms seven days after inoculation with wild-type conidial suspension or mycelia , whereas the ΔMovps35 mutant failed to cause blast disease in barley seedlings ( Fig 1B and Fig 1C ) . To investigate if the pathogenicity defects in ΔMovps35 were due to a block in penetration or invasive growth , we inoculated mycelia from the wild type or ΔMovps35 through abraded barley leaves . This allows for invasive growth independent of appressorium function . We found that the ΔMovps35 mycelia were able to invade the wounded tissue and caused weak lesions on the wounded leaves compared to the WT ( Fig 1D ) . These results suggested that the ΔMovps35 mutant were unable to infect rice and barley , owing mainly to their inability to penetrate the plant cuticle . In yeast , plant and mammals , Vps26p and Vps29p form the cargo-selective subcomplex of the retromer via interaction with Vps35p [25 , 26] . Therefore , we assessed whether these proteins cooperate in common pathogenic pathways in M . oryzae . Using orthologous yeast sequences , we identified MGG_04830 and MGG_02524 as MoVps26 and MoVps29 , respectively , in M . oryzae ( S1 Table ) . We first investigated whether such a retromer subcomplex occurs in M . oryzae . In the yeast two-hybrid assay , MoVps35 was found to physically interact with MoVps26 and MoVps29 ( Fig 1E ) . Furthermore , we constructed ΔMovps26 and ΔMovps29 deletion mutants by gene replacement . The ΔMovps26 and ΔMovps29 deletion mutants ( S2 Table ) were identified by PCR and confirmed by DNA gel blot analysis ( S3 Fig ) . Like the ΔMovps35 mutant , ΔMovps26 and ΔMovps29 mutants were also impaired in conidiation and pathogenicity on the seedlings of the susceptible rice cultivar CO39 ( S4 Fig , Fig 1F and Fig 1G ) . Finally , we expressed WT MoVPS26 and MoVPS29 gene in the corresponding null mutants . As expected , the complementation strains showed suppression of mutant defects in conidiation and pathogenicity ( S4 Fig , Fig 1F and Fig 1G ) . The data suggest that MoVps35 , MoVps26 and MoVps29 function together in the retromer pathway and play a key role in plant infection by the rice blast fungus . To understand why the retromer subcomplex ( MoVps35 , MoVps26 and MoVps29 ) is required for pathogenicity in M . oryzae , we first chose the core retromer component MoVps35 for a detailed functional analysis . Based on the above observations , we reasoned that MoVps35 either controls proper appressorium formation or appressorium-mediated infection in M . oryzae . We first assayed for appressorium formation on artificial hydrophobic surfaces , wherein the ΔMovps35 conidia produced abundant melanized appressoria ( Fig 2A ) . No obvious morphological defects in appressorium formation were evident in ΔMovps35 ( Fig 2A–2C ) . The ΔMovps35 exhibited normal appressorium formation on onion epidermal cells as well ( Fig 2B ) . However , such ΔMovps35 appressoria were defective in the penetration of onion epidermal cells and subsequent differentiation into invasive hyphae ( Fig 2B ) . By 48 h , the wild-type strain penetrated and formed invasive hyphae in onion epidermal cells ( Fig 2B ) . A vast majority of the appressoria ( 95% , P<0 . 01 ) failed to penetrate the onion epidermal cells even at 72 hpi . Aniline blue staining and further quantification of penetration efficiency was carried out on barley leaves inoculated with conidia of WT or ΔMovps35 ( Fig 2C ) . The efficiency to form penetration pegs on barley leaves was about 62% in WT , while only 3 . 6% ( P<0 . 01 ) appressoria showed host entry in the ΔMovps35 mutant at 48 h time point . Even upon extended incubation , ΔMovps35 appressoria were still unable to penetrate the host surface ( Fig 2D and 2H ) . Similar defects were also evident in invasive growth in ΔMovps35 inoculated on barley leaves ( Fig 2E ) . We conclude that MoVps35 is not required for appressorium formation but is essential for appressorium-mediated host penetration by the rice blast fungus . Since establishment and maintenance of high internal turgor pressure is necessary for appressorium-mediated host penetration by M . oryzae [9] , we examined the turgor pressure in ΔMovps35 using the incipient cytorrhysis assays [27] . These appressorial collapse assays revealed that the ΔMovps35 appressoria generate significantly lower turgor compared to wild type ( Fig 3; P<0 . 01 ) . In 2 M glycerol , 75% of ΔMovps35 appressoria collapsed at 24 h compared to 27% and 25% of the appressoria in the wild type and complementation strains , respectively ( Fig 3B ) . Upon increasing the glycerol to 3 M and extending the incubation , appressoria of ΔMovps35 mutant remained severely collapsed compared to those from the wild-type or the complemented strain ( Fig 3B ) . Further analysis revealed that the wild-type strain completely transferred the cytoplasm from conidia into the appressoria , leading to collapsed conidial morphology , while a large proportion of the cytoplasm was still intact in the mutant cells and consequently the conidia remained intact and turgid at 24 h after incubation ( Fig 3A; black arrows ) . The delayed mobilization of cytoplasmic content into the appressoria prompted us to further investigate the germinating conidia . In M . oryzae , conidia contain several sources of stored energy such as glycogen and lipids [7] , and effective transfer of such materials is required for appressorial maturation and appressorium-mediated host penetration [7 , 28] . We therefore examined the cellular distribution of glycogen and lipid bodies during appressorium development . Upon iodine-staining abundant glycogen was seen in conidia , germ tubes , and incipient appressoria of the WT and ΔMovps35 from 0 h to 4 h during germination of conidia on a hydrophobic surface ( Fig 4A ) . However , mobilization of glycogen was notably retarded in ΔMovps35 mutant after 8 h conidial germination ( Fig 4A ) . Even after 24 h , a significantly higher proportion of mutant conidia contained glycogen ( Fig 4B ) . Therefore , glycogen catabolism/hydrolysis was greatly delayed in the ΔMovps35 mutant ( Fig 4A–4C ) . Next , we investigated the distribution of lipid bodies by Bodipy staining and confocal microscopy . The distribution of lipid bodies showed the same pattern as glycogen in the ΔMovps35 mutant , as shown in Fig 4D and Fig 4E . The data indicate that the mobilization of glycogen and lipid bodies from conidia to the appressoria is greatly reduced or blocked in the ΔMovps35 mutant . Like MoVps35 , the other two components , MoVps26 and MoVps29 , of the retromer subcomplex were also found to be necessary for proper initiation of blast disease , as judged by the similar phenotypic defects in glycogen distribution , lipid droplet turnover , and appressorial turgor generation shown by the requisite ΔMovps26 and ΔMovps29 ( S5 Fig ) . Taken together , these results indicate that the cargo-recognition subcomplex of the retromer comprising of MoVps35 , MoVps26 and MoVps29 , functions in mediating critical physiological/metabolic processes associated with pathogenic differentiation in M . oryzae . Studies in M . oryzae have shown that proper conidiation and appressorium formation/function requires autophagy-assisted utilization of carbohydrate ( s ) , glycogen or stored lipids [16 , 29 , 30] . Autophagy-deficient mutants ( Δatg1 , Δatg2 , Δatg4 , Δatg5 , Δatg8 , Δatg9 and Δatg18 ) show delayed breakdown of glycogen and lipid bodies , reduced turgor pressure and complete loss of pathogenesis in M . oryzae . [29 , 31–35] . Similar defects in ΔMovps35 prompted us to investigate whether MoVps35 is directly involved in regulating autophagy function ( s ) during appressorium-mediated host penetration . To test this idea , an Hh1-GFP ( encodes nuclear localized Histone H1 ) was introduced into the wild type and ΔMovps35 strains to allow live cell imaging of nuclear degeneration associated with autophagic cell death [5] ( S2 Table ) . In WT , the number of Hh1-GFP marked nuclei gradually decreased due to autophagy-based degeneration in conidial cells during appressorial maturation . As a result , a single nucleus remains intact in the mature appressorium of the wild-type strain at 24 hpi ( 84% , P<0 . 01 ) ( Fig 5A ) . However , the majority of the Hh1-GFP expressing ΔMovps35 conidia ( 71% ) contained more than one nucleus ( Fig 5A ) . These data suggest that MoVps35 deficiency affects the autophagic cell death in conidia of M . oryzae . A key event in autophagy is the formation of a double-membrane autophagosome , which engulfs portions of cytosol and entire organelles [36 , 37] . Thus , we sought to determine whether retromer plays a role in the formation of autophagosomes during appressorium development . We used the RFP-MoAtg8 as an epifluorescent marker for autophagosomes [16 , 38–40] . MoAtg8 is a ubiquitin-like protein that marks autophagosomal structures and is required for the formation of autophagosomes . RFP-MoAtg8 was expressed under the control of the endogenous MoATG8 promoter in the ΔMoatg8 or ΔMovps35 background . Analysis of ΔMoatg8 RFP-MoATG8 showed typical punctate autophagosomes and vacuolar autolysosomes widely distributed in conidia , germ tubes and appressoria ( Figs 5B and S6 ) . However , the ΔMovps35 RFP-MoATG8 strain showed no obvious punctate autophagosomes in germ tubes and appressoria , except for aggregated red epifluorescence signal in the vacuoles ( Figs 5B and S6 ) . We reasoned that RFP-MoAtg8 was probably retained in the vacuole and subsequently degraded by the vacuolar hydrolase upon loss of MoVps35 function . The dynamics of autophagic structures was investigated using time-lapse microscopy . In ΔMoatg8 RFP-MoATG8 strain , mobile spherical autophagosomes ( about 1 μm diameter ) fuse with vacuolar structures ( 2–5 μm diameter ) and also dissociate from these structures ( S1 Movie ) , indicating that autophagosomes cooperatively act to form autophagolysosomes or are recovered once autophagy is completed . By contrast , there are no obvious spherical autophagosomes in the ΔMovps35 RFP-MoATG8 strain ( S2 Movie ) . These results suggest that MoVps35 is necessary for the proper localization of MoAtg8 and consequently required for autophagosome formation during appressorial maturation . To investigate the mechanism by which retromer participates in the regulation of autophagosome formation , we monitored the dynamics of MoVps35 trafficking in M . oryzae using a ΔMovps35 pMoVPS35::MoVPS35-GFP strain ( S2 Table ) . The pMoVPS35::MoVPS35-GFP construct complemented all the defects found in ΔMovps35 mutants ( Fig 1 ) , indicating that MoVps35-GFP is fully functional . MoVps35-GFP exhibited a mostly punctate pattern at or near the vacuolar membrane in conidia and mycelia ( Fig 6A and 6B ) . The association with vacuoles was confirmed by staining with the lipophilic styryl dye FM4-64 ( Fig 6A and 6B ) . Furthermore , we investigated the spatiotemporal dynamics of MoVps35-GFP during infection-related development . MoVps35-GFP consistently localized to small punctate/vesicular compartments ( approximately 0 . 5–2 . 0 μm ) in conidia , germ tubes and nascent appressoria by 2 h and 4 h , respectively ( S7 Fig ) . During 8–24 h , the fluorescent signal was predominant in developing appressoria and gradually diminished in the conidia , consistent with conidial autophagic cell death ( S7 Fig ) . Next , we monitored the dynamics of MoVps35-GFP movement in conidia and appressoria during conidial germination upon staining with FM4-64 . MoVps35-GFP was present on highly mobile punctate structures in germinated conidia and developing appressoria ( Fig 6C; S3 Movie ) . Strikingly , the movement of MoVps35-GFP-containing structures was not random but inherently associated with vacuolar membranes or late endosomes as judged by FM4-64 staining ( Fig 6C; S3 Movie ) . We interpret these epifluorescence traces of MoVps35-GFP as evidence for vesicular trafficking in the late endosomal compartments . Moreover , the mobility of MoVps35-GFP depends on microtubules but not the F-actin cytoskeleton , because it was disrupted by the microtubule-destabilizing agent MBC ( Methyl Benzimidazol-2-yl-Carbamate ) but not by actin-depolymerizing drug LatA ( latrunculin A ) ( S8 Fig and S4–S6 Movies ) . In addition , like MoVps35-GFP localization , MoVps26-GFP and MoVps29-GFP both exhibited a similar dynamic and punctate pattern on the vacuolar membrane ( Fig 6D and 6E ) . Spatiotemporal dynamic of MoVps26-GFP and MoVps29-GFP distribution during infection-related development was also reminiscent of the MoVps35-GFP localization ( S9 Fig , S7 and S8 Movies ) . These data suggest that retromer may function in the retrieval of cargo associated with vacuoles or autolysosomes in M . oryzae . Given the essential role of retromer in the formation of autophagosomes and the apparent association with late endosomes , we suspected that MoVps35-GFP motility might contribute to the retrieval of MoAtg8 to pre-autophagosomal structures and autophagosomes . To test this hypothesis we first determined whether MoVps35 colocalizes with MoAtg8 . pMoVps35::MoVPS35-GFP was introduced into the ΔMoatg8 RFP-MoATG8 strain ( S2 Table ) for localization and dynamic association analysis . In fresh harvested conidia , most of MoVps35-GFP vesicles were arranged adjacent to RFP-MoAtg8 labeled organelles , implying a potential association between these two compartments ( Fig 7 ) . Remarkably , a proportion of MoVps35-GFP punctae colocalized with the cytosolic RFP-MoAtg8 compartments as determined by line-scan and 3D reconstruction analysis ( Fig 7A and 7B , see also S9 Movie ) . In order to test whether the colocalization existed during other developmental stages of M . oryzae , conidia from the dual-labeled ΔMoatg8 RFP-MoATG8 MoVPS35-GFP strain were incubated in vitro to observe germination and appressoria formation using confocal microscopy . At 2 h , many germ tubes initiated appressorium formation . In addition to the partially colocalized/overlapping RFP and GFP fluorescent signals detected in conidia , a small proportion of such colocalized signals were also apparent in the germ tubes ( S10A Fig ) . A similar localization pattern was also found in developing appressoria ( S10B Fig ) . Furthermore , RFP-MoAtg8 partially co-localized with MoVps35-GFP in vegetative hyphae under nitrogen starvation conditions that induce autophagy ( S10C Fig ) . In order to directly record spatial and temporal association between MoVps35-GFP and RFP-MoAtg8 , a real time imaging was applied . S10 Movie or time-lapse Fig 7C shows a conidium undergoing autophagy , RFP-MoAtg8 fluorescent were highly associated with oblong vacuoles ( approximately 2–5 μm diameter ) and spherical structures ( approximately 1 μm diameter ) . Interestingly , we observed that mobile RFP-MoAtg8 puncta showed a rapid dissociation from the adjacent vacuoles , and at the same time the MoVps35-GFP also displayed very close colocalization with the punctate RFP-MoAtg8 ( Fig 7C , arrows ) . This suggests that MoVps35 might play an important role for retrieving MoAtg8 from the vacuole , avoiding unnecessary degradation by vacuolar hydrolases . To test whether MoVps35 contributes to the retrieval of MoAtg8 in vivo , we applied a GFP-trap/co-immunoprecipitation assay to pull down MoVps35-GFP and found that anti-RFP antibody was able to specifically detect a clear band of about 37 kD , the size of the truncated variant of RFP-MoAtg8 ( Fig 8A ) . No unmodified full-length RFP-MoAtg8 band was detected from the proteins pulled down with MoVps35-GFP ( Fig 8A ) . In the control experiment , both truncated RFP-MoAtg8 variant ( approximately 37 kD ) and full-length RFP-MoAtg8 ( approximately 48 kD ) were detected with an anti-RFP antibody with input protein isolated from the ΔMoatg8 RFP-MoATG8 MoVPS35-GFP strain ( Fig 8A ) . These results indicate that MoVps35 is able to specifically interact with the truncated variant of MoAtg8 , which is consistent with the time-lapse microscopy results of MoVps35-GFP and RFP-MoAtg8 in M . oryzae . Taken together , the MoVps35 acts through a direct interaction with truncated variant of MoAtg8 and contributes to its retrograde transport in M . oryzae . Autophagy can be measured by examining the intracellular levels of cleaved and lipidated Atg8 , viz Atg8PE , which is the key protein known to associate specifically with autophagosomes , as its levels correlate with the number of autophagosomes [38–40] . If MoVps35 is required for the retrieval of MoAtg8 to phagophore assembly sites ( PAS ) /autophagosomes , we would anticipate that the level of cleaved and lipidated MoAtg8 ( ie . , MoAtg8PE ) would be reduced in ΔMovps35 under the conditions that induce autophagy . Therefore , we further used immunoblot assays to analyze the levels of the cleaved MoAtg8 protein in ΔMoatg8 and ΔMovps35 strains expressing RFP-MoATG8 ( Fig 8B ) . We detected two forms of RFP-MoAtg8 using anti-RFP antibody , inferring that these represented the full-length and lipidated form , MoAtg8PE . Under nitrogen starvation condition , the amount of RFP-MoAtg8PE gradually increased in the ΔMoatg8 RFP-MoATG8 , which correlated well with the extent of autophagosome formation ( Fig 8B ) . However , in the ΔMovps35 RFP-MoATG8 strain , the levels of RFP-MoAtg8PE were greatly reduced and delayed in both CM and MM-N medium compared to the ΔMoatg8 RFP-MoATG8 strain , indicative of fewer autophagosomes ( Fig 8B ) . Interestingly , the autophagy flux was not completely blocked in the ΔMovps35 since some RFP-MoAtg8PE still accumulated in the cells upon nitrogen starvation ( Fig 8B ) . These findings are consistent with the microscopy results of scarce spherical autophagosomes in the ΔMovps35 RFP-MoATG8 strain . Besides , the compromised expression levels of MoATG8 in the ΔMovps35 mutant could also lead to the lack of MoAtg8-marked autophagosome . Therefore , we further used qRT-PCR to assess the expression levels of the MoATG8 gene in ΔMovps35 and wild-type strains under the MM-N conditions . Compared to the wild-type strain , the expression levels of MoATG8 do not differ significantly in the ΔMovps35 , but appear to be mildly upregulated ( S11A Fig ) . We further analysed the expression levels of MoATG4 which is a key cysteine protease responsible for the cleavage of the carboxy terminus of MoAtg8 during the biogenesis of autophagosomes in M . oryzae [31] . Similar to MoATG8 , the expression of MoATG4 was slightly higher in the ΔMovps35 as compared to the wild type ( S11A Fig ) , suggesting that MoVps35 regulates the biogenesis of punctate autophagosomes primarily via modulating the retrieval of MoAtg8 , but not by compromising the expression of MoATG8 and MoATG4 in M . oryzae . These results also explain why increased expression of MoATG8 is unable to rescue the phenotypic defects in ΔMovps35 mutant ( S111B–S11F Fig ) . Overall , the retrograde transport function of retromer complex , the close association between retromer core component MoVps35 and the key autophagy protein MoAtg8 , and their tight functional link in autophagocytosis , asexual differentiation and plant infection provides an insight into a novel function of regulating the biogenesis of autophagosomes by retrieving cleaved MoAtg8 from the vacuolar compartments for targeting to the proper structures in the rice blast fungus ( Fig 9 ) .
In this work , we have addressed the outstanding question about the mechanism of Atg8 retrieval during autophagosome biogenesis . It was previously reported that the majority of Atg8 molecules were released into the cytoplasm before autophagosome–vacuole fusion , suggesting that Atg8 is retrieved for the formation of autophagosomes [41 , 42] . However , the molecular mechanisms for Atg8 retrieval remained unclear . Our results show that MoVps35 , a retromer core component that functions in endosomal sorting , directly interacts with MoAtg8 and is associated with MoAtg8 retrieval process from the periphery of vacuoles ( Fig 9 ) . Loss of retromer function leads to the mistargeting of RFP-MoAtg8 to the vacuole and thus the impairment of the biogenesis of autophagosomes . Moreover , the phenotype of all retromer component mutants mimic the morphological disturbance observed with ΔMoatg8 , including failure to undergo autophagic cell death during conidial germination , and defects in fungal appressorium-mediated pathogenesis . Taken together , our results provide the first clear linkage between the retrograde transport mediated by retromer complex and the autophagy-dependent plant infection . The highly conserved retromer is well known to function in the retrieval of recycling cargos to TGN in the retrograde pathway , but its unconventional roles are now beginning to emerge . In Arabidopsis thalliana , the retromer complex components Vps35 , Vps26 and Vps29 localize to the prevacuolar compartment ( PVC ) and are essential for normal PVC morphology [43 , 44] . Mutations in VPS35 or VPS29 in A . thalliana lead to a dwarf phenotype and defects in PIN protein repolarization , embryogenesis , plant growth , and leaf senescence [45 , 46] . In Drosophila melanogaster , Vps35 function is necessary for normal endocytic trafficking and organization of the F-actin cytoskeleton [47] . Loss of Vps35 severely affects endocytosis and the localization of a number of endocytic proteins , causes defects in signaling pathways in haemocytes and at the neuromuscular junction , and leads to increased levels of F-actin [47] . Interestingly , a recent report found that the mammalian retromer regulates trafficking and subsequent incorporation of HIV-1 envelope glycoprotein ( Env ) into virions [48] . Inactivating retromer alters Env localization , cell surface expression and incorporation into virions , and the binding of retromer to the Env cytoplasmic tail is required for these functions [48] . Our study suggests an important role in retromer is essential for the autophagy-dependent plant infection in M . oryzae , thus expanding the functions of retromer . Interestingly , although the retromer is important for appressorium-mediated host penetration , it is not essential for colonization therein . This suggests that the retromer and efficient autophagy is not required for suppression of host defense , invasive growth within the rice cells , or spread from cell-to-cell in the host . It will be interesting to investigate whether the retromer plays a similar role in autophagy and infection-related development in other fungus-plant pathosystems . Our cell biological , biochemical and genetic analyses demonstrate that the retromer is essential for autophagy by activating the formation of autophagosomes through the Vps35’s direct interaction with and retrieval of MoAtg8 in the M . oryzae . This role of the retromer could be widespread throughout the eukaryotic kingdom . Recently , two studies have implicated a role for the retromer in autophagy in yeast and mammalian cells . Dengjel and his colleagues used quantitative proteomics to identify Vps35/retromer as a stimulus-dependent interacting partner of autophagosomes in human breast cancer cells [49] . A further test for autophagic response revealed that a significantly lower autophagic activity in the yeast vps35 null mutant [49] . Another study identified that the mutant VPS35 allele that causes Parkinson’s disease ( PD ) , VPS35 D620N , also impairs autophagy and alters the trafficking of the multi-pass transmembrane autophagy protein Atg9A in mammalian cells [50] . However , none of these studies addressed the mechanism by which the retromer regulates autophagocytosis . Here , we provide genetic , live-cell imaging and biochemical evidence that MoVps35-GFP positively regulates the autophagy process via recycling or retrieving truncated MoAtg8 to the appropriate compartments , likely PAS , for regeneration of autophagosomes . In a previous report in M . oryzae , EGFP-MgAtg9 and DsRed2-MgAtg8 displayed significant colocalization [35] , suggesting that these components interact in conidia . Although our data identified that MoAtg8 mislocalization is a likely contributor to the impaired autophagosome formation in the ΔMovps35 mutant , it is conceivable that other MoAtg proteins are subjected to the retromer complex mediated retrograde transportation too . Given the conservation of the retromer and its role in autophagy , this mechanism likely provides a paradigm for a novel role of retromer in the regulation of autophagy in various eukaryotic organisms . Autophagy plays an important role in recycling cellular components in eukaryotic cells . Although more than 30 genes have been described for involvement in autophagy , in yeast [13 , 14] , the mechanisms for the activation of this process and for the recycling of its components for autophagosome formation remain poorly understood . A ubiquitin-like system mediates the conjugation of the cleaved Atg8 to the lipid phosphatidylethanolamine ( PE ) , and this conjugate ( Atg8PE ) is then tethered to autophagosome membrane , where it is necessary for phagophore expansion during autophagosome formation [36 , 39] . In addition to the lipidation of Atg8 , delipidation of Atg8 is also required for autophagosome maturation [41] . In yeast , the cleaved Atg8 has a C-terminal glycine residue that exists in two different forms: a lipidated ( Atg8PE ) and a deconjugated form [51] . The former is involved in autophagosome formation; the role of latter is to release outer membrane-bound Atg8 upon completion of the autophagosome , presumably for reuse in subsequent rounds of autophagosome formation [41] . However , how the deconjugated Atg8 gets to the PAS for autophagosome formation is currently unknown . Our data indicate a direct interaction between vacuolar membrane conjugated MoAtg8 and Vps35 and suggest a novel mechanism for lipidated MoAtg8 recycling via retromer-mediated transport in M . oryzae . It is possible that the retrieval machinery and/or the cargo-recognition complex of the retromer recognize the lipidated MoAtg8 as a specific cargo/substrate .
All strains used in this study were listed in S2 Table . M . oryzae wild-type Δku70 [15] and all mutant strains were grown on complete medium ( CM ) , starch yeast medium ( SYM ) , oatmeal agar medium ( OAT ) and rice-polish agar medium ( RPA ) for mycelial growth assays and on RPA medium for conidiation assays as previously described [52] . To test the sensitivity against cell-wall-disrupting agents , vegetative growth of fungal strains was monitored on CM plates with 200 μg/mL congo red ( CR ) or 200 μg/mL Calcofluor White ( CFW ) or 0 . 01% sodium dodecyl sulfate ( SDS ) . For oxidative stress sensitivity assays , M . oryzae strains were grown on CM containing 5 mM H2O2 and the sensitivity was evaluated by measuring the colony diameter of 6-day-old cultures . Experimental results were verified with a minimum of two strains of the same genotype . All experiments were repeated at least three times . The M . oryzae protoplast preparation and fungal transformation were performed by following standard protocols [53] . Hygromycin- or neomycin-resistant transformants were selected on media supplemented with 250 μg/mL hygromycin B ( Roche Applied Science ) or 200 μg/mL G418 ( Invitrogen ) . To generate ΔMovps35 mutant , a 1 , 176-bp fragment upstream from MoVPS35 was amplified with primers MO05089AF and MO05089AR , and this amplicon was subsequently cloned into the XhoI and EcoRI sites upstream of the hph cassette on pCX63 [24] . Then , 1 . 14 kb fragment downstream of MoVPS35 was amplified with primers MO05089BF and MO05089BR , and cloned into the BamHI and XbaI sites downstream of HPH cassette , and this plasmid was transformed into protoplasts of the wild-type Δku70 strain . Hygromycin-resistant transformants were screened by PCR with primers MO05089UA and H853 and primers MO05089OF and MO05089OR ( S3 Table ) . At least two isolates that tested positive with PCR were further verified by Southern blot analysis performed with the DIG-High Prime DNA Labeling and Detection Starter Kit I Roche ( Roche , Mannheim , Germany ) . The split-marker approach was used to generate gene replacement constructs for other components of the retromer complex [54] . Primers used to amplify the flanking sequences of MoVPS26 and MoVPS29 are listed in S3 Table . Each construct was transformed into protoplasts of Δku70 to generate the ΔMovps26 and ΔMovps29 deletion mutants ( S2 Table ) . Putative knockout mutants were identified by PCR screening and confirmed by DNA gel blot analysis . The MoVps35-GFP fusion vector , named pGM-MoVps35-GFP , was constructed by amplification of 5 , 027-bp fragment including 2 , 944-bp MoVps35 coding sequence and a 2 , 083-bp native promoter region using primers MO05089CF and MO05089CR ( S3 Table ) . The 5 , 027-bp PCR product was then cloned into pGEM-T easy vector ( Promega ) to generate pGM-MoVps35 . The GFP allele [55] was amplified using primers Bgl II-GFPF and Bgl II-GFPR ( S3 Table ) , then cloned into pGEM-T easy vector . It was subsequently digested with BglII to release the GFP allele with BglII sticky ends , which was inserted into BglII site of pGM-MoVps35 to create pGM-MoVps35-GFP . We verified the orientation of GFP insertion and in-frame fusion by sequencing the pGM-MoVps35-GFP vector . To generate MoVps35-GFP strain , pGM-MoVps35-GFP construct was co-transformed into protoplasts of the target mutant along with a vector harboring neomycin-resistance marker ( pKNT ) . Transformants carrying a single insertion were screened by PCR with requisite primer pairs ( S3 Table ) and further confirmed by Southern blot analysis . The same approach was used to generate gene fusion GFP constructs for other components of the retromer complex . Primers used to amplify the complementation sequences of MoVPS26 and MoVPS29 are listed in S3 Table . For appressorial assays , conidia were harvested from 10-day-old OAT or RPA cultures . Aliquots ( 30 μL ) of conidial suspensions ( 5×104 conidia/mL in sterile water ) were applied on the hydrophobic side of Gelbond film ( Cambrex Bio Science ) and incubated under humid conditions at room temperature . Conidial germination and appressorium formation were examined at 0 . 5 , 1 , 2 , 4 , 8 and 24 h post incubation . For penetration assays , conidial suspension in sterile water was inoculated on onion epidermal cells or barley leaf and assessed after 24 h , 48 h and 72 h . Penetration pegs and infection hyphae were detected by staining for papillary callose deposits using Aniline blue [56] . For pathogenicity assays , two-week-old seedlings of rice ( Oryza sativa L . ) cultivar CO39 were used for spray inoculation assays as described [52] . Eight-day-old seedlings of barley cultivar Golden Promise were also used for drop inoculation and mycelial plug assays on the non-wounded or wounded barley leaves [57] . For glycogen staining , the M . oryzae conidia were inoculated on hydrophobic plastic coverslips for different time points and stained with a solution consisting of 60 mg/mL of KI and 10 mg/mL of I2 in distilled water [7] . Yellowish-brown glycogen deposits became visible immediately in bright field . For lipid bodies staining , samples were stained with Bodipy ( D3922 , Invitrogen ) to detect neutral lipids . Bodipy was used at 10 μg/mL ( stock 1 mg/mL in ethanol ) in PBS buffer . All samples were examined and photographed by using an Olympus-BX51 fluorescence microscope with a cooled CCD camera ( DP72 , Olympus , Japan ) . Calcofluor White ( Sigma-Aldrich , USA ) was used at 3 μg/mL to visualize cell wall and septa of conidia . To visualize the vacuolar membrane , conidia , vegetative hyphae and germinated conidia were treated with 4 μg/mL FM4-64 solution for 30–60 min before observed under the confocal microscope . To examine the effects of microtubule inhibitor methyl 1- ( butylcarbamoyl ) -2-benzimidazolecarbamate ( MBC ) or the actin inhibitor latrunculin A ( LatA ) on trafficking ability of MoVps35 in cells , The MoVps35-GFP strain was inoculated on hydrophobic plastic coverslips and treated for 30 minutes with MBC ( final concentration 10 μM ) or LatA ( final concentration 10 μM ) at the hooking stage . A 0 . 1% DMSO solvent control was used in these assays . Standard molecular manipulations were performed as described [58] . Total RNA was isolated from mycelia with TRIzol reagent ( Invitrogen ) . Purified RNA was treated with DNase ( Takara ) and was verified as DNA free by using it directly as template in a PCR assay . First-strand cDNA was synthesized with the M-MLV reverse transcriptase ( Invitrogen ) , and qRT-PCR was performed with the Eppendorf Mastercycler ep Realplex2 PCR system using SYBR Premix Ex TaqTM ( RR420A , Takara ) . Primers used to amplify selected genes in qRT-PCR reactions are listed in S3 Table . Yeast two-hybrid assay was carried out as indicated in MATCHMAKER GAL4 Two-Hybrid System 3 ( Clontech ) . The full-length cDNA of MoVPS35 was amplified with the primer pair MO05089BDF/MO05089BDR ( S3 Table ) and cloned into pGBKT7 as the bait vector BD-Movps35 . The full-length cDNAs of MoVPS26 and MoVPS29 were amplified with the primer pairs MO04830ADF/MO04830ADR and MO02524ADF/MO02524ADR ( S3 Table ) , respectively , and were cloned into pGADT7 as the prey vectors AD-Movps26 and AD-Movps29 . The resultant bait and prey vectors were confirmed by sequencing and were co-transformed into the yeast strain AH109 . The Leu+ and Trp+ yeast transformants were isolated and assayed for growth on SD-Trp-Leu-His-Ade medium at specified concentrations . Yeast strains for positive and negative controls were as described in the Matchmaker kit . For total protein extraction , mycelia grown in liquid CM and MM-N medium ( used for nitrogen starvation , 0 . 5 g/L KCl , 0 . 5 g/L MgSO4 , 1 . 5 g/L KH2PO4 , 10 g/L glucose , pH 6 . 5 ) were ground into a fine powder in liquid nitrogen and resuspended in 0 . 6 mL extraction buffer ( 50 mM Tris-HCl ( pH 7 . 4 ) , 150 mM NaCl , 1 mM EDTA , 2 mM PMSF and 1% Triton X-100 ) . The supernatants were centrifuged 15 , 000 g for 25 min at 4°C to remove cell debris . Total protein concentration was measured using the Bio-Rad Protein Assay and separated on a 12 . 5% SDS PAGE gel and transferred to PVDF membranes for Western blot analysis . The expression of RFP-Atg8 was detected with anti-RFP ( Clontech , USA ) . The horseradish peroxidase–conjugated secondary antibody and the ECL kit ( Amersham Biosciences , Germany ) were used to detect the chemiluminescent signals . For the immunoprecipitation of GFP-fusion-proteins from cellular extracts , equal concentration of total proteins were isolated and incubated with 20–30 μL of GFP-Trap agarose beads ( ChromoTek , Germany ) and carried out as manufacturer’s instructions . Proteins eluted from GFP-Trap agarose beads were analyzed by immunoblot detection with the anti-RFP ( Clontech , USA ) , anti-GFP ( Sigma-Aldrich ) antibodies and anti-Actin ( Sigma-Aldrich ) . Conventional epifluorescence and differential interference contrast ( DIC ) microscopy was performed with a Olympus BX51 microscope ( Olympus , Japan ) , using a 40x 1 . 3 NA ( numerical aperture ) , 60x 1 . 35 NA or 100x 1 . 40 NA Olympus oil immersion objective lens . Images were acquired using an Olympus DP72 camera and analyzed with DT2-BSW image-processing software . Fluorescence was observed with Olympus U-RFL-T mercury lamp source . The filter sets used were: DAPI , GFP and RFP or FM4-64 . Alternatively , confocal microscopy was used for time-lapse or live cell fluorescence imaging by using the Nikon TiE system ( Nikon , Japan ) as described [59] . The elapsed time is indicated in seconds . Image processing and figure preparation was performed using Image J , Adobe Photoshop , PowerPoint and Microsoft Excel . Sequence data from this article can be found in the GenBank/EMBL databases under the following accession numbers: S . cerevisiae VPS35 ( NP_012381 ) , S . cerevisiae VPS29 ( NP_011876 ) , S . cerevisiae VPS26 ( NP_012482 ) , S . cerevisiae VPS17 ( NP_014775 ) , S . cerevisiae VPS5 ( NP_014712 ) , M . oryzae MoVPS35 ( XP_003712611 ) , M . oryzae MoVPS29 ( XP_003709334 ) , M . oryzae MoVPS26 ( XP_003713759 ) , M . oryzae MoVPS17 ( XP_003714383 ) , M . oryzae MoVPS5 ( XP_003709457 ) . | The rice blast fungus Magnaporthe oryzae utilizes key infection structures , called appressoria , elaborated at the tips of the conidial germ tubes to gain entry into the host tissue . Development of the appressorium is accompanied with autophagy in the conidium leading to programmed cell death . This work highlights the significance of the Vps35/retromer membrane-trafficking machinery in the regulation of autophagy during appressorium-mediated host penetration , and thus sheds light on a novel molecular mechanism underlying autophagy-based membrane trafficking events during pathogen-host interaction in rice blast disease . Our findings provide the first genetic evidence that the retromer controls the initiation of autophagy in filamentous fungi . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Retromer Is Essential for Autophagy-Dependent Plant Infection by the Rice Blast Fungus |
Extreme precipitation events are increasing as a result of ongoing global warming , but controversy surrounds the relationship between flooding and mosquito-borne diseases . A common view among the scientific community and public health officers is that heavy rainfalls have a flushing effect on breeding sites , which negatively affects vector populations , thereby diminishing disease transmission . During 2014 in Montpellier , France , there were at least 11 autochthonous cases of chikungunya caused by the invasive tiger mosquito Aedes albopictus in the vicinity of an imported case . We show that an extreme rainfall event increased and extended the abundance of the disease vector Ae . albopictus , hence the period of autochthonous transmission of chikungunya . We report results from close monitoring of the adult and egg population of the chikungunya vector Ae . albopictus through weekly sampling over the entire mosquito breeding season , which revealed an unexpected pattern . Statistical analysis of the seasonal dynamics of female abundance in relation to climatic factors showed that these relationships changed after the heavy rainfall event . Before the inundations , accumulated temperatures are the most important variable predicting Ae . albopictus seasonal dynamics . However , after the inundations , accumulated rainfall over the 4 weeks prior to capture predicts the seasonal dynamics of this species and extension of the transmission period . Our empirical data suggests that heavy rainfall events did increase the risk of arbovirus transmission in Southern France in 2014 by favouring a rapid rise in abundance of vector mosquitoes . Further studies should now confirm these results in different ecological contexts , so that the impact of global change and extreme climatic events on mosquito population dynamics and the risk of disease transmission can be adequately understood .
Extreme precipitation events are envisaged to increase as a result of ongoing global warming [1] . Heavy rains have consequences for infectious diseases , with , in particular , some vector-borne disease outbreaks being associated with flooding [2 , 3] . However , the relationships between flooding and vector-borne diseases are mired in controversy and need to be clarified [4] . A common belief among the scientific community and public health officers is that “heavy rainfalls produce a flushing effect of immature mosquitoes ( larvae and pupae ) in breeding containers , diminishing the mosquito abundance” [3 , 5] , in turn diminishing disease transmission . The common view in most works on climate and mosquito-borne diseases is that “Intense rainfall may wash out breeding sites and thus have a negative effect on vector populations” [6] . During September-November 2014 , French health authorities reported a cluster of 11 autochthonous cases of chikungunya in the city of Montpellier in the vicinity of a recently imported case [7 , 8] . This was the first report of locally transmitted chikungunya in France since 2010 , adding to the 4 cases of dengue reported earlier that year in the neighbouring PACA region , and dengue cases in 2010 and 2013 [7–9] . Abundances of the tiger mosquito Aedes albopictus , the competent disease vector , in an increasing number of places and the large number of imported cases of chikungunya ( 443 cases ) , dengue ( 163 cases ) and co-infections ( 6 cases ) in France [7] , did indeed concur to increase the risk of autochthonous transmission in Southern France . The objective of this study was to analyse the influence of climatic variables , including an extreme rainfall event , on Ae . albopictus abundance in Montpellier in 2014 , and its impact on the risk of autochthonous chikungunya transmission .
Mosquitoes were sampled in the municipalities of Montpellier and Castelnau-le-Lez in the Province of Hérault , region Languedoc-Roussillon , southern France , with a Mediterranean climate and a resident human population of 400 . 470 inhabitants spread over 14 . 62 Km2 . Adult mosquitoes were collected using 24 BG-Sentinel traps ( BioGents , Regensburg , Germany ) , with the attractant BG lure , a synthetic lure developed to mimic human odors , consisting of lactic acid , ammonia , and caproic acid on a long-lasting lure . Traps were located in 8 sampling sites separated by a mean geographic distance of 2 . 2 Km . Each sampling site consisted of a private house with garden , and three trap replicates set 5–10 m apart were operated in each site . Each trap was connected to a battery ( 12 V ) , and the captures were conducted for 24 H , once a week , from the 21th week ( 2nd week of May ) to the 50th week ( 2nd week of December ) of 2014 . Sampled mosquitoes were transported live to the laboratory in an insulated thermal bag filled with ice and frozen at -20°C . The species and sex of each individual were identified in the laboratory with a stereomicroscope using the appropriate taxonomic keys [10] . Although several species were captured , including Ae . albopictus , Culex pipiens , Culiseta longiareolata , Aedes caspius and Anopheles maculipennis s . l . , only Ae . albopictus females were included in the analysis . The mean weekly abundance of Ae . albopictus females captured in the 24 traps was used as the dependent variable . In parallell , eggs of Ae . albopictus were collected using oviposition traps ( ovitraps ) placed in each of the 24 locations where the adult population was monitored . Bacilus thuringiensis var . israeliensis granules ( VectoBac , ValentBioSciences ) were added to the water to prevent larval development and traps were checked once a week . Eggs were counted under a stereomicroscope and averaged across traps and over collection sites . Daily mean , minimum and maximum air temperatures , daily total precipitation and insolation time for the study period were obtained from the Montpellier Fréjorgues meteorological station ( http://www . meteociel . fr/climatologie/villes . php ? code=7643&mois=6&annee=2014 ) , located 6 Km from the city centre . For the purposes of our study , these data were pooled by week . Then , for temperature , weekly means and weekly range were computed , and for rainfall , total weekly precipitation was calculated . Environmental variables may have a strong influence on mosquito populations not only at the time of adult capture but also , and mainly , at egg-laying and larval development which occur 1–4 weeks earlier . Therefore , accumulated temperature and rainfall were calculated over the 4 weeks preceding the week of sampling . Growing Degree Days ( GDD ) were calculated with a baseline temperature of 11°C to compute weekly accumulated Growing Degree Days ( GDD ) . Based on our previous work , we also assessed a ‘bounded’ estimate of the accumulated GDD ( Bounded accumulated GDD ) , with a maximum threshold of 1350 accumulated GDD above which any further increase in GDD is considered detrimental and counted negatively [11 , 12] . We developed a Generalized Linear Model with negative binomial distribution ( as the data were over-dispersed ) to investigate whether Ae . albopictus adult female abundance was influenced by temperature and rainfall before and after the extreme rainfall event . The response variable was the total weekly Ae . albopictus adult female abundance , and the selected explanatory variables were the average weekly temperatures ( minimum , mean and maximum ) , the total weekly precipitation , all the accumulated temperature and rainfall variables ( see Climatic data section for details ) , Weekly Growing Degree Days , Accumulated Growing Degree Days and Bounded Accumulated Growing Degree Days . Due to the highly expected co-linearity between the explanatory variables , different univariate models were built and the best model was selected on the basis of AIC ( Akaike Information Criterion ) , ΔAIC and Akaike weights . We calculated the explained deviance as: ( Null deviance-Residual deviance ) / Null deviance . Statistical analysis was performed in R version 2 . 14 . 2 [13] with the packages MASS [14] and MuMin[15] .
We developed a close monitoring of the adult population of the chikungunya vector Ae . albopictus in Montpellier through weekly sampling over the entire mosquito breeding season ( i . e . , May to November 2014 ) . Although mosquito densities steadily declined after peaking in late August , extreme rainfall events flooding the area at the end of September and beginning of October ( Week 39 ) , with up to 252 mm of rain falling in just 3 hours ( recorded on 29th September in Montpellier ) , resulted in an explosive mosquito population growth extending into October and surpassing the abundance peak recorded earlier in August ( Fig 1 ) . Statistical analysis ( Table 1; Fig 2 ) revealed that , before the inundations , temperature ( Accumulated Growing Degree Days ) was the most important variable predicting the seasonal dynamics of Ae . albopictus , with 69 . 3% of the variance explained . However , after the inundations , accumulated rainfall over the 4 weeks before capture predicted Ae . albopictus seasonal dynamics , explaining 92 . 3% of the variance ( Table 2; Fig 2 ) . The seasonal pattern of eggs abundance in the ovitraps closely matched that of female abundance , with a lag of several days ( Fig 1 ) .
We have shown that the extreme precipitation event clearly contributed to increasing and extending the abundance of the disease vector Ae . albopictus , and hence to extending the period of autochthonous transmission of chikungunya in Montpellier in 2014 . Female density increased rapidly after the extreme event , soon followed by a rise in the number of eggs collected in ovitraps . Therefore , and contrary to common belief [3 , 4 , 5 , 6] , our empirical data suggest that heavy rainfall events do not , in fact , decrease but instead may increase the global risk of chikungunya ( and other arboviruses ) transmission , by extending the transmission season . This is the first evidence to support the relationship between heavy rainfall and chikungunya transmission . Our observations before and after the extreme precipitation event , suggest that heavy rains after a dry period with low precipitations have filled all the peridomestic containers where desiccated eggs of Ae . albopictus were to be found , and that it was this situation which gave rise to the increase in mosquito numbers several weeks later . Indeed , the majority of breeding sites colonized by Ae . albopictus larvae in Mediterranean Europe are small peridomestic containers of less than 10 L . such as scuppers , flowerpot saucers , drums , buckets , solid waste and others , whereas the productivity of catch basins is generally much lower [16 , 17 , 18] . In Southern France , more than 80% of breeding sites are situated in the private domain and only 12% of the immature stages were detected in catch basins [16] . The outcome of such extreme climatic events might therefore be different in different ecological contexts , depending on the larval ecology of the species . For example , West Nile virus ( WNV ) outbreaks have been associated with flooding , in Romania , the Czech Republic and Russia [19 , 20 , 21] . However , these outbreaks were related to flooded building basements , resulting in an increase in populations of the WNV vector Culex pipiens , which thrives in large water collections that are not suitable for Ae . albopictus development . Further studies are needed to explore the general relevance of our findings and their implications for diseases transmission by Aedes albopictus in Europe , as well as elsewhere where the species has established . Because our data showed that heavy rains in Mediterranean cities impacted on Ae . albopictus abundances , we propose that an effort on source reduction campaigns must be implemented after such heavy rainfall event . In fact , these high-volume rainfall events , referred to as Cévenol episodes , are relatively frequent in the south of France . We further encourage tropical countries that are endemic for Chikungunya and Dengue to develop similar studies in order to explore the relevance of enforcing source reduction approaches following extreme climatic events and we believe that our results should be brought to the attention of those involved in the surveillance and control of vectors and vector-borne diseases in the context of global change in temperate as well as tropical areas of the world . | During last years , we have seen an astonishing expansion of Chikungunya virus and an increase in dengue cases worldwide , together with the worldwide expansion of the Asian tiger mosquito Aedes albopictus . In addition , extreme rainfall events are envisaged to become increasingly likely as a result of ongoing climate change , but controversy surrounds the relationship between extreme rainfall events and mosquito-borne diseases . The common view in most works on climate and mosquito-borne diseases is that heavy rainfalls produce a flushing effect of immature mosquitoes in breeding containers , diminishing the mosquito abundance and in turn diminishing disease transmission . We analysed the relationships between the autochthonous chikungunya transmission in Montpellier ( Southern France ) in 2014 , an extreme rainfall event that flooded the city , and a close monitoring of the vector Ae . albopictus , revealing an unexpected pattern . This extreme rainfall event did not , in fact , decrease but instead had increased the global risk of chikungunya transmission by sustaining high abundance of the disease vector Ae . albopictus , hence extending the transmission period . We propose that an effort on source reduction campaigns must be implemented after heavy rainfall events . These results are relevant to those involved in the surveillance and control of chikungunya and dengue transmission in temperate as well as tropical areas . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Autochthonous Chikungunya Transmission and Extreme Climate Events in Southern France |
Human cytomegalovirus ( hCMV ) is a highly prevalent pathogen that , upon primary infection , establishes life-long persistence in all infected individuals . Acute hCMV infections cause a variety of diseases in humans with developmental or acquired immune deficits . In addition , persistent hCMV infection may contribute to various chronic disease conditions even in immunologically normal people . The pathogenesis of hCMV disease has been frequently linked to inflammatory host immune responses triggered by virus-infected cells . Moreover , hCMV infection activates numerous host genes many of which encode pro-inflammatory proteins . However , little is known about the relative contributions of individual viral gene products to these changes in cellular transcription . We systematically analyzed the effects of the hCMV 72-kDa immediate-early 1 ( IE1 ) protein , a major transcriptional activator and antagonist of type I interferon ( IFN ) signaling , on the human transcriptome . Following expression under conditions closely mimicking the situation during productive infection , IE1 elicits a global type II IFN-like host cell response . This response is dominated by the selective up-regulation of immune stimulatory genes normally controlled by IFN-γ and includes the synthesis and secretion of pro-inflammatory chemokines . IE1-mediated induction of IFN-stimulated genes strictly depends on tyrosine-phosphorylated signal transducer and activator of transcription 1 ( STAT1 ) and correlates with the nuclear accumulation and sequence-specific binding of STAT1 to IFN-γ-responsive promoters . However , neither synthesis nor secretion of IFN-γ or other IFNs seems to be required for the IE1-dependent effects on cellular gene expression . Our results demonstrate that a single hCMV protein can trigger a pro-inflammatory host transcriptional response via an unexpected STAT1-dependent but IFN-independent mechanism and identify IE1 as a candidate determinant of hCMV pathogenicity .
Human cytomegalovirus ( hCMV ) , the prototypical β-herpesvirus , is an extremely widespread pathogen ( reviewed in [1] ) . Primary hCMV infection is invariably followed by life-long viral persistence in all infected individuals . The groups most evidently affected by hCMV disease are humans with acquired or developmental immune deficits including allograft recipients receiving immunosuppressive drugs , human immunodeficiency virus-infected individuals , cancer patients undergoing intensive chemotherapy , and infants infected in utero ( reviewed in [2] ) . In immunologically normal hosts , clinically relevant symptoms rarely accompany acute infections ( reviewed in [3] ) , but viral persistence may contribute to chronic disease conditions including atherosclerosis , cardiovascular disease , inflammatory bowel disease , immune senescence , and certain malignancies ( reviewed in [4] , [5] , [6] , [7] , [8] ) . The pathogenesis of disease ( e . g . , pneumonitis , retinitis , hepatitis , enterocolitis , and encephalitis ) associated with acute hCMV infection in immunocompromised people is most readily attributable to end organ damage either directly caused by cytopathic viral replication or by host immunological responses that target virus-infected cells . In contrast , chronic disease associated with persistent hCMV infection in immunocompetent individuals as well as in the allografts of transplant recipients is most likely related to prolonged inflammation ( reviewed in [9] ) . In fact , hCMV has been frequently detected in the midst of intense inflammation , and a myriad of studies from transplant recipients and normal hosts have presented a strong case for this virus as an etiologic agent in chronic inflammatory processes , particularly those resulting in vascular disease ( reviewed in [4] ) . At the molecular level , this is reflected by the fact that , in both human cells and animal models , cytomegalovirus infections activate numerous host genes many of which encode growth factors , cytokines , chemokines , and adhesion molecules with pro-inflammatory and immune stimulatory activities [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] . A number of these virus-induced proteins are released from infected cells forming the viral “secretome” [4] , [24] , [25] . A large proportion of human genes that undergo activation during hCMV infection are normally controlled by interferons ( IFNs ) ( reviewed in [26] , [27] ) . The IFNs constitute a distinct group of cytokines synthesized and released by most vertebrate cells in response to the presence of many different pathogens including hCMV . They are divided among three classes: type I IFNs ( primarily IFN-α and IFN-β ) , type II IFN ( IFN-γ ) , and type III IFNs ( IFN-λ or interleukin 28/29 ) . The type I IFNs share many biological activities with type III IFNs , especially in host protection against viruses . IFN-γ , the sole type II IFN , is one of the most important mediators of inflammation and immunity exerting pleiotropic effects on activation , differentiation , expansion and/or survival of virtually any cell type of the immune system ( reviewed in [28] ) . A significant body of research has identified the primary IFN pathway components and has characterized their roles in “canonical” signaling ( reviewed in [29] , [30] ) . In this pathway , IFNs bind to their cognate cell surface receptors to induce conformational changes that activate the receptor-associated enzymes of the Janus kinase ( JAK ) family . The post-translational modifications that follow this activation create docking sites for proteins of the signal transducer and activator of transcription ( STAT ) family with seven human members . In turn , the STAT proteins undergo JAK-mediated phosphorylation at a single tyrosine residue ( Y701 in STAT1 ) , which triggers their transition to an active dimer conformation . The STAT dimers accumulate in the nucleus where they may recruit additional proteins , and these complexes then bind sequence-specifically to short DNA motifs termed IFN-stimulated response element ( ISRE ) or gamma-activated sequence ( GAS ) . ISREs are usually bound by a ternary complex composed of a STAT1-STAT2 heterodimer and IFN regulatory factor ( IRF ) 9 , which forms upon induction by type I and type III IFNs and is referred to as IFN-stimulated gene factor 3 ( ISGF3 ) . In contrast , type II IFN typically signals via STAT1 homodimers that associate with GAS elements . Finally , promoter-associated STAT proteins stimulate transcription of numerous IFN-stimulated genes ( ISGs ) via their carboxy-terminal transcriptional activation domain . Within this domain , phosphorylation of a serine residue ( S727 in STAT1 ) can augment STAT transcriptional activity . To some extent , the complex responses elicited by type I , type II , and type III IFNs are redundant as a consequence of partly overlapping ISGs . Since many ISGs , especially those induced by type I IFNs , exhibit potent anti-viral activities most viruses have evolved escape mechanisms that mitigate IFN responses . In fact , both hCMV and murine cytomegalovirus ( mCMV ) are known to disrupt IFN pathways at multiple points ( reviewed in [26] , [27] ) . For example , JAK-STAT signaling is inhibited by the hCMV 72-kDa immediate-early 1 ( IE1 ) gene product [31] , [32] , [33] , a key regulatory nuclear protein required for viral early gene expression and replication in fibroblasts infected at low input multiplicities [34] , [35] , [36] . IE1 orthologs of mCMV and rat cytomegalovirus ( rCMV ) also contribute to replication and virulence in the respective animals [37] , [38] . The hCMV IE1 protein counteracts virus- or type I IFN-induced ISG activation via complex formation with STAT1 and STAT2 resulting in reduced binding of ISGF3 to ISREs [31] , [32] , [33] , [39] . STAT2 interaction contributes to hCMV type I IFN resistance and to IE1 function during productive infection [33] , but the viral protein undergoes many additional host cell interactions ( reviewed in [2] , [40] , [41] ) . For example , IE1 targets subnuclear structures known as promyelocytic leukemia ( PML ) bodies or nuclear domain 10 ( ND10 ) ( [42] , [43] , [44]; reviewed in [45] , [46] , [47] , [48] ) . In addition , IE1 associates with chromatin [49] and interacts with a variety of transcription regulatory proteins [50] , [51] , [52] , [53] , [54] , [55] , [56] , [57] . Consequently , IE1 stimulates expression from a broad range of viral and cellular promoters in transient transfection assays . However , IE1-mediated activation or repression of merely a few single endogenous human genes has been demonstrated so far [58] , [59] , [60] , [61] , [62] , [63] , [64] . Here we present the results of the first systematic human transcriptome analysis following expression of the hCMV IE1 protein . Surprisingly , the predominant response to IE1 was characterized by activation of pro-inflammatory and immune stimulatory genes normally controlled by IFN-γ . We further demonstrate that IE1 employs an unusual mechanism , which does not require induction of IFNs but nonetheless depends on activated ( Y701-phosphorylated ) STAT1 , to up-regulate a subset of ISGs .
The hCMV IE1 protein exhibits complex activities , and results obtained from experiments with IE1 mutant virus strains are inherently difficult to interpret . In fact , regarding the phenotype of IE1-deficient viruses at low input multiplicities , it seems almost impossible to discriminate between effects directly linked to any of the IE1 activities and indirect effects caused by delays in downstream viral gene expression and replication . On the other hand , following infection at high multiplicity , many consequences of absent IE1 expression are compensated for by excess viral structural components , such as tegument proteins and/or DNA , and therefore undetectable ( [35] , [36]; reviewed in [2] , [40] , [41] ) . Thus , it is apparent that cells with inducible expression of functional IE1 at physiological levels would be highly useful by allowing a definite assessment of the viral protein's activities outside the confounding context of infection . Furthermore , such cells would avoid potential difficulties typically associated with transient transfection , including variable frequency of positive cells and protein accumulation to non-physiologically high levels . Importantly , an inducible expression system would also preclude cells from adapting to long-term IE1 expression . In fact , the continued presence of IE1 is reportedly incompatible with genomic integrity and normal cell proliferation [65] , [66] , [67] . We used a tetracycline-dependent induction ( Tet-on ) system built into lentivirus vectors to generate cells in which IE1 expression can be synchronously induced and compared to cells not expressing the viral protein . The first component of this system is a lentiviral vector ( pLKOneo . CMV . EGFPnlsTetR; [68] , [69] , [70] ) that includes a hybrid gene encoding the tetracycline repressor ( TetR ) linked to a nuclear localization signal ( NLS ) derived from the SV40 large T antigen and the enhanced green fluorescent protein ( EGFP ) to produce an EGFPnlsTetR fusion protein [68] . In addition , this vector encodes neomycin resistance . The second component is a lentivirus vector ( pLKO . DCMV . TetO . cIE1 ) conferring puromycin resistance , in which a fragment of the hCMV promoter-enhancer drives expression of the IE1 ( Towne strain ) cDNA . In this vector , tandem tetracycline operator ( TetO ) sequences are present immediately downstream of the TATA box . For the lentivirus transductions , we chose MRC-5 primary human embryonic lung fibroblasts , because they support robust wild-type hCMV replication , whereas IE1-deficient virus strains exhibit a severe growth defect after low multiplicity infection of these cells ( [31] , [33] and Figure 1 C ) . Initially , low passage MRC-5 cells were transduced with lentivirus prepared from plasmid pLKOneo . CMV . EGFPnlsTetR , and a neomycin-resistant polyclonal cell population ( named TetR ) was isolated in which almost all cells expressed the EGFP fusion protein located in the nucleus ( data not shown ) . Next , TetR cells were transduced with lentivirus prepared from pLKO . DCMV . TetO . cIE1 and a mixed cell population ( named TetR-IE1 ) exhibiting both neomycin and puromycin resistance was selected . Finally , fluorescence-activated cell sorting was performed to collect cells with high levels of EGFPnlsTetR and , consequently , low levels of IE1 in the absence of inductor . To characterize the newly generated cells , TetR-IE1 cells were treated with doxycycline for 24 or 72 h and examined for IE1 expression by indirect immunofluorescence microscopy ( Figure 1 A ) . Before induction , the majority ( 67 . 0% ) of cells was IE1 negative , and most other cells expressed barely detectably levels of the viral protein . Interestingly , in the latter proportion of cells IE1 was present in a predominantly punctate nuclear pattern . This likely reflects stable co-localization between IE1 and ND10 due to viral protein levels insufficient to disrupt the nuclear structures . At 24 h following induction only 2 . 8% of cells were negative for IE1 expression and >97% stained positive for the viral protein . In almost all positive cells IE1 exhibited a largely diffuse nuclear staining indicating complete disruption of ND10 . Very similar results were obtained for IE1 expression and localization 72 h post induction . Importantly , the observed temporal and spatial pattern of IE1 subnuclear localization in TetR-IE1 cells closely resembles that observed during productive hCMV infection in fibroblasts where initial colocalization between IE1 and ND10 is succeeded by ND10 disruption and diffuse nuclear distribution of the viral protein [43] , [44] , [71] . To compare the relative levels of IE1 expressed during hCMV infection and after induction of TetR-IE1 cells , TetR cells were infected with the hCMV Towne strain , and samples collected before or 3 h , 6 h , 12 h , 24 h , 48 h and 72 h after infection were analyzed for IE1 steady-state protein levels in comparison with samples of TetR-IE1 cells that had been treated with doxycycline ( Figure 1 B ) . The timing of IE1 induction in TetR-IE1 cells was remarkably similar to the kinetics of IE1 accumulation in hCMV-infected cells . In addition , the IE1 levels detected at 24 to 72 h post induction were comparable to the protein amounts that had accumulated by 24 h post hCMV infection . To confirm that TetR-IE1 cells express fully active IE1 , replication of wild-type and IE1-deficient hCMV strains was compared by multi-step analyses conducted in doxycycline-treated TetR and TetR-IE1 cells ( Figure 1 C ) . To this end , we employed a bacterial artificial chromosome ( BAC ) -based recombination approach to generate a “markerless” mutant virus strain ( TNdlIE1 ) lacking the entire IE1-specific coding sequence . For details on the construction of TNdlIE1 and a revertant virus ( TNrvIE1 ) see Materials and Methods . As expected , the replication of two independent TNdlIE1 clones was strongly attenuated in TetR cells , with a ∼2 to >3 log difference in titers between mutant and revertant virus strains . It is important to note that our previous work has shown that TNrvIE1 and the parental wild-type strain ( TNwt ) exhibit identical replication kinetics [33] . However , induced TetR-IE1 cells were able to support wild-type-like replication of the TNdlIE1 viruses demonstrating that the viral protein provided in trans can fully compensate for the lack of IE1 expression from the hCMV genome during productive infection . Interestingly , even the titers of TNrvIE1 were reproducibly up to ∼20-fold higher in TetR-IE1 as compared to IE1-negative cells between 3 and 12 days post infection . Taken together , these results show that in TetR-IE1 cells expression of IE1 can be synchronously induced from the autologous hCMV major IE ( MIE ) promoter resulting in fully functional protein at levels present during the early stages of hCMV infection . Thus , TetR/TetR-IE1 cells present an ideal model to study the activities of the IE1 protein outside the complexity of infection , yet under physiological conditions . The capacity of hCMV IE1 to activate transcription from both viral and cellular promoters has long been appreciated ( [72]; reviewed in [2] , [40] , [41] ) . However , most reports on IE1-regulated host gene transcription have relied on transient transfections and promoter-reporter assays . To our knowledge , regulation of endogenous cellular transcription by IE1 has so far only been studied sporadically and at the level of single genes . To comprehensively assess the impact of IE1 on the human transcriptome , we performed a systematic gene expression analysis using our TetR/TetR-IE1 cell model and Affymetrix GeneChip Human Gene 1 . 0 ST Arrays covering 28 , 869 genes ( >99% of sequences currently present in the RefSeq database , National Center for Biotechnology Information ) . We compared the gene expression profiles at 24 h and 72 h post induction in induced versus non-induced TetR-IE1 cells and in induced TetR-IE1 versus induced TetR cells . Expression from the vast majority ( 99 . 9% ) of genes represented on the arrays was not significantly affected by IE1 . However , mRNA levels of 38 human genes differed by a factor of two or more ( p>0 . 01 ) in both the induced TetR-IE1/non-induced TetR-IE1 and the induced TetR-IE1/induced TetR comparisons . For 32 ( 84% ) of the 38 genes , changes in mRNA levels were only observed after 72 h ( but not 24 h ) of IE1 expression , and only six ( 16% ) were differentially expressed at both 24 h and 72 h . Moreover , 13 ( 34% ) of these genes were down-regulated by a factor between 2 . 0 and 5 . 5 ( data not shown ) and 25 ( 66% ) were up-regulated by a factor between 2 . 0 and 41 . 9 ( Table 1 ) . For the present work , we concentrated on the set of genes that was found to be up-regulated by expression of IE1 . We utilized the Gene Ontology ( GO ) classification system ( http://www . geneontology . org ) to identify attributes which predominate among IE1-activated gene products regarding the three GO domains “biological process” , “molecular function” , and “cellular component” . Furthermore , we employed a set of analysis tools to construct maps that visualize overrepresented attributes on the GO hierarchy ( Figure 2 ) . According to GO , the most significantly enriched “biological process” terms with respect to the 25 IE1-activated genes are: “immune system process” , “immune response” , “inflammatory response” , “response to wounding” , “response to stimulus” , “defense response” , “chemotaxis” , “taxis” , and “regulation of cell proliferation” ( Figure 2 A ) . In fact , virtually all IE1-induced genes with assigned functions have been implicated in adaptive or innate immune processes including inflammation . Moreover , 7 ( 28% ) of the 25 genes encode known cytokines or other soluble mediators , namely the chemokine ( C-X-C motif ) ligands CXCL9 , CXCL10 and CXCL11 , the chemokine ( C-C motif ) ligand CCL11 , endothelin 1 ( encoded by EDN1 ) , and the tumor necrosis factor ( TNF ) superfamily members 4 ( TNFSF4 , also known as OX40 ligand ) and 18 ( TNFSF18 , also known as GITR ligand ) . This observation is also illustrated by the fact that , according to GO , the most significantly enriched “molecular function” terms in the IE1-activated transcriptome are: “cytokine receptor binding” , “cytokine activity” , “chemokine activity” , “chemokine receptor binding” , and “G-protein-coupled receptor binding” ( Figure 2 B ) . Furthermore , the top “cellular component” category is “extracellular space” ( Figure 2 C ) . For a more thorough assessment of overrepresented GO terms among IE1-induced genes , see Supporting Tables S1 , S2 and S3 . Surprisingly , the genes induced by IE1 are generally associated with stimulatory rather than inhibitory effects on immune function including inflammation ( Figure 2 A and Supporting Table S1 ) . For example , some of the gene products are involved in the proteolysis ( cathepsin S encoded by CTSS ) , intracellular transport ( TAP1 transporter ) or cell surface presentation ( HLA-DRA ) of antigens ( reviewed in [73] ) . The chemokines CXCL9 , CXCL10 , and CXCL11 mediate leukocyte migration ( see Discussion; reviewed in [73] , [74] , [75] ) . CD274 ( also known as PDL1 ) , TNFSF4 , and TNFSF18 are co-stimulatory molecules which promote leukocyte ( including T and B lymphocyte ) activation , proliferation and/or survival ( reviewed in [73] , [76] , [77] , [78] , [79] ) . Indoleamine 2 , 3-dioxygenase 1 ( IDO1 ) and IRF1 have also been linked to T lymphocyte regulation , but they have additional functions in innate immune control of viral infection ( reviewed in [73] , [80] , [81] , [82] , [83] , [84] , [85] . Likewise , GBP1 and murine GBP2 exhibit antiviral activity [86] , [87] , [88] , [89] . Out of the 25 IE1-activated genes , 14 were selected for validation by qRT-PCR . The selected genes were representative of the entire range of expression kinetics and induction magnitudes measured by microarray analysis . The PCR approach confirmed expression of all tested genes typically reporting similar or larger fold increases compared to the array data ( Figure 3 A–B and Figure 4 A ) . For example , in induced ( 72 h ) versus non-induced TetR-IE1 cells the CXCL10 mRNA was found to be increased 24 . 6-fold by array analysis ( Table 1 ) and 68 . 0-fold by PCR ( Figure 3 A ) . Under the same conditions , the GBP4 transcript was induced 13 . 5-fold by array analysis ( Table 1 ) as compared to 19 . 1-fold by PCR ( Figure 3 A ) . The corresponding data for TAP1 were 2 . 1-fold ( array analysis; Table 1 ) and 2 . 3-fold ( PCR; Figure 3 A ) . Largely concordant results regarding induction magnitudes between array and PCR analyses were also obtained for CCDC3 , CCL11 , HES1 , SERTAD4 , TNFSF4 , and TNFSF18 ( Figure 3 B ) as well as for CXCL9 , CXCL11 , IDO1 , IFIT2 , and IRF1 ( Figure 4 A ) . In addition to the extent of gene activation , the precise timing of induction was exemplary investigated for CXCL10 , GBP4 and TAP1 ( Figure 3 A ) . A substantial increase in mRNA production from all three genes was evident at 72 h ( and to a lesser extent at 48 h ) but only minor effects were detected between 6 h and 24 h post IE1 induction consistent with the array data ( Table 1 ) . Tubulin-β ( TUBB ) gene expression , which is not affected by IE1 , served as a negative control for the PCR experiments . Finally , the chemokines CXCL9 and CXCL11 were exclusively detected in supernatants from TetR-IE1 but not TetR cells ( Figure 3 C ) . Moreover , the levels of CXCL10 protein were drastically increased in TetR-IE1 compared to TetR cells . This demonstrates that for these genes elevated mRNA levels also translate into enhanced protein synthesis and secretion . The fact that increased expression of all tested IE1-activated genes was detectable with two or three alternative approaches strongly suggests that essentially all genes identified within the given experimental framework and data analysis settings are truly differentially expressed upon induction of IE1 . Moreover , the activation of at least a subset of IE1-responsive genes appears to be temporally coupled . A plethora of past studies has established that immune regulatory genes are preferential targets of IFN-based regulation [28] , [29] , [30] . Intriguingly , at least 21 ( 84% ) of the 25 IE1-activated human genes identified by microarray analysis turned out to be bona fide ISGs ( Table 2 ) according to informations retrieved from the Interferome database ( http://www . interferome . org [90] ) and other sources including our own qRT-PCR analyses ( Figure 4 A and Supporting Table S4 ) . Several of these ISGs cluster in certain chromosomal locations ( e . g . , 1p22 , 4q21 , and 10q23-q25; Table 2 ) apparently reflective of their co-regulation . An initial assessment mainly based on the Interferome data revealed that IE1-activated ISGs are normally induced by either only IFN-γ or by both type II and type I IFNs ( Table 2 ) . To confirm this assignment and to further discriminate between type I and type II ISGs , we treated TetR and TetR-IE1 cells with exogenous IFN-α or IFN-γ and analyzed the effects on mRNA accumulation from a select subset of IE1-responsive ISGs . The transcript levels of all tested ISGs , namely CXCL9–11 , GBP4 , IDO1 , IFIT2 , IRF1 , and TAP1 ( Figure 4 A ) as well as CCL11 ( Supporting Table S4 ) were not only increased by IE1 expression ( TetR-IE1 relative to TetR cells ) but also by IFN-γ treatment of TetR cells , although to varying degrees ( ∼2 to >30 , 000-fold; Figure 4 A ) . Notably , there was a significant positive correlation ( Pearson's correlation coefficient = 0 . 81 ) between the magnitudes of IE1- and IFN-γ-mediated ISG induction . In contrast , the same genes were substantially less susceptible ( CXCL9–11 , GBP4 , IDO1 , and IFIT2 ) or entirely unresponsive ( CCL11 , IRF1 , and TAP1 ) to IFN-α ( Figure 4 A ) , and there was no correlation ( Pearson's correlation coefficient = −0 . 04 ) between IE1 and IFN-α responsiveness . For comparison , three typical type I ISGs , the genes encoding eukaryotic translation initiation factor 2α kinase 2 ( EIF2AK2 , also known as PKR ) , myxovirus ( influenza virus ) resistance 1 ( Mx1 , also known as MxA ) , and 2′ , 5′-oligoadenylate synthetase ( OAS1 ) , were strongly induced by IFN-α but barely by IFN-γ or IE1 ( Figure 4 B ) . Although no obvious synergistic or additive effects between IE1 expression and IFN-γ treatment were observed in these assays ( Figure 4 A–B ) , IFN-α induction of type I ISGs was severely compromised in TetR-IE1 as compared to TetR cells ( Figure 4 B ) . The latter observation is consistent with our previous work which has demonstrated that IE1 blocks STAT2-dependent signaling resulting in inhibition of type I ISG activation [31] , [33] . Hence , it appears that expression of IE1 selectively activates a subset of ISGs and ISG gene clusters which are primarily responsive to IFN-γ indicating that the viral protein elicits a type II IFN-like transcriptional response . ISG activation typically requires synthesis , secretion and receptor binding of IFNs ( reviewed in [26] , [27] , [29] , [30] ) . IFN-α is encoded by a multi-gene family and is mainly expressed in leukocytes although some members are stimulated by IFN-β in fibroblasts [91] . However , neither of 12 IFN-α ( IFNA ) and three alternative type I IFN coding genes ( IFNE , IFNK , and IFNW1 encoding IFN-ε , IFN-κ , and IFN-ω , respectively ) was noticeably induced by IE1 as judged by our microarray results ( Supporting Table S5 ) . In contrast to IFN-α , IFN-β is encoded by a single gene ( IFNB ) and is produced by most cell types , especially by fibroblasts ( IFN-β is also known as “fibroblast IFN” ) . However , previous work has shown that IE1 expression does not induce transcription from the IFN-β gene in fibroblasts [31] , [32] , [92] . Consistently , our microarray data did not reveal appreciable differences in IFNB1 mRNA levels between TetR and TetR-IE1 cells ( Supporting Table S5 ) . The single human IFN-γ gene ( IFNG ) is expressed upon stimulation of many immune cell types but not usually in fibroblasts , and our microarray results indicate that IE1 does not activate expression from this gene . Likewise , none of the known type III IFN genes ( IL28A , IL28B , and IL29 encoding IFN-λ2/IL-28A , IFN-λ3/IL-28B , and IFN-λ1/IL-29 , respectively ) was significantly responsive to IE1 expression in this system ( Supporting Table S5 ) . For the IFN-β and IFN-γ transcripts , these results were confirmed by highly sensitive qRT-PCR from doxycycline-treated TetR-IE1 and TetR cells . Levels of the two IFN mRNAs did not significantly differ between TetR-IE1 and TetR cells at any of ten post induction time points ( 0 h–96 h ) under investigation ( Supporting Figure S1 and Supporting Table S6 ) . Thus , IE1 does not seem to induce expression from the IFN-γ or any other human IFN gene . To further rule out the possibility that ISG activation is a result of low level IFN production or secretion of any other soluble mediator from IE1 expressing cells , culture supernatants from TetR-IE1 cells induced with doxycycline for 24 h or 72 h were transferred to MRC-5 cells . As expected , MRC-5 cells did not undergo ISG induction 3 h to 72 h following media transfer ( data not shown ) . Furthermore , we set up a transwell system with TetR cells in the top and TetR-IE1 cells in the bottom chamber ( Figure 5 ) . Following addition of IFN-γ to the lower chamber , we observed substantially increased mRNA levels of three IE1-responsive indicator ISGs ( CXCL9 , CXCL11 , and GBP4 ) in both TetR and TetR-IE1 cells ( Figure 5 A ) . In contrast , addition of doxycycline caused up-regulation of ISG mRNA levels in TetR-IE1 but not TetR cells ( Figure 5 B ) . These results indicate that ISG induction is restricted to IE1 expressing cells and that a diffusible factor is not sufficient to mediate gene activation by the viral protein . Finally , we performed experiments adding neutralizing antibodies directed against IFN-β and IFN-γ to the cell culture media ( Figure 6 ) . ISG-specific qRT-PCRs from TetR cells treated with a combination of antibodies and high doses of the respective exogenous IFN confirmed that cytokine neutralization was both highly effective and specific . At the same time , neither the IFN-β- nor the IFN-γ-specific neutralizing antibodies had any significant negative effect on IE1-mediated ISG induction . These results strongly support the view that ISG activation by IE1 is independent of IFN-β , IFN-γ , and likely other IFNs . Homodimeric STAT1 complexes are the central intracellular mediators of canonical IFN-γ signaling ( reviewed in [26] , [27] , [28] , [29] , [30] ) . Interestingly , previous work has shown that the IE1 protein interacts with both STAT1 and STAT2 , although STAT2 binding appeared to be more efficient [31] , [32] , [33] , [39] . STAT2 has also been implicated in certain IFN-γ responses ( [93] , [94]; reviewed in [95] ) , although some ( hCMV-mediated ) activation of ISG transcription appears to occur entirely independent of STAT proteins ( [96]; reviewed in [26] , [27] ) . To investigate whether ISG activation by IE1 requires the presence of STAT1 and/or STAT2 , we employed siRNA-based gene silencing individually targeting the two STAT transcripts . Following transfection of MRC-5 , TetR and/or TetR-IE1 cells with two different siRNA duplexes each for STAT1 and STAT2 , we monitored endogenous STAT expression by immunoblotting ( Figure 7 A ) and qRT-PCR ( Figure 7 B ) . An estimated ≥80% selective reduction in STAT1 and STAT2 protein accumulation was observed 2 days following siRNA transfection , and even after 5 days significantly lower protein levels were detected compared to cells transfected with a non-specific control siRNA ( Figure 7 A ) . The knock-down of STAT1 and STAT2 was also evident at the level of mRNA accumulation ( 86 to 95% for STAT1 and 51 to 95% for STAT2 at day 5 post transfection; Figure 7 B ) . The knock-down specificity was verified by confirming that STAT1 siRNAs do not significantly reduce STAT2 mRNA levels and vice versa . Moreover , none of the STAT-directed siRNAs had any appreciable effect on IE1 expression ( Figure 7 B ) . Again , expression from the CXCL10 and GBP4 genes was strongly up-regulated in doxycycline-treated TetR-IE1 versus TetR cells . However , STAT1 knock-down caused the CXCL10 and GBP4 genes to become almost entirely resistant to IE1-mediated activation in induced TetR-IE1 cells . In contrast , depletion of STAT2 had no negative effect on IE1-dependent ISG induction ( Figure 7 B ) although it diminished basal and IFN-α-induced type I ISG ( OAS1 ) expression ( Supporting Figure S2 ) . These results demonstrate that STAT1 , but not STAT2 , is an essential mediator of the cellular transcriptional response to IE1 expression and suggest that the viral protein might mediate ISG activation via activation of JAK-STAT signaling . The activation-inactivation cycle of STAT transcription factors entails their transition between different dimer conformations . Unphosphorylated STATs can dimerize in an anti-parallel conformation , whereas tyrosine ( Y701 ) phosphorylation triggers transition to a parallel dimer conformation resulting in increased DNA binding and nuclear retention of STAT1 ( reviewed in [29] , [30] , [97] ) . In addition , serine ( S727 ) phosphorylation is required for the full transcriptional and biological activity of STAT1 [98] . In order to investigate whether IE1 promotes STAT1 activation , we compared the levels of Y701- and S727-phosphorylated STAT1 in doxycyline-induced TetR and TetR-IE1 cells ( Figure 8 A ) . Total STAT1 steady-state protein levels were very similar in TetR and TetR-IE1 cells . In contrast , Y701-phosphorylated forms of STAT1 were only detectable in the presence of IE1 unless cells were treated with IFN-γ . In addition , IE1 was almost as efficient as IFN-γ in inducing STAT1 S727 phosphorylation . These results strongly suggest that IE1 expression triggers the formation of Y701- and S727-phosphorylated , transcriptionally fully active STAT1 dimers . To examine whether STAT1 Y701 and/or S727 phosphorylation is an essential step in IE1-mediated ISG activation , we set up a “knock-down/knock-in” system designed to study mutant STAT1 proteins in a context of diminished endogenous wild-type protein levels . We constructed an “siRNA-resistant” STAT1 coding sequence , termed STAT1* , containing two silent nucleotide exchanges in the sequence corresponding to siRNA STAT1 #146 ( Figure 7 A ) . The STAT1* sequence was used as a substrate for further mutagenesis to generate siRNA-resistant constructs encoding mutant STAT1 proteins with conservative amino acid substitutions that preclude tyrosine or serine phosphorylation ( Y701F or S727A , respectively; reviewed in [99] , [100] ) . A retroviral gene transfer system based on vector pLHCX was utilized to efficiently express the different STAT1 proteins in TetR-IE1 cells . All STAT1 variants ( STAT1* , STAT1*Y701F , and STAT1*S727A ) were overexpressed to levels undiscernible from the wild-type protein and mRNA ( Figure 8 B–C ) . In comparison to transfections with a non-specific control siRNA ( #149 ) , siRNA #146 severely reduced the levels of endogenous and overexpressed wild-type STAT1 without negatively affecting expression of the siRNA-resistant STAT1 variants or IE1 ( Figure 8 B–C ) . As expected , the Y701F and S727A mutant STAT1 proteins did not undergo tyrosine or serine phosphorylation , respectively , upon stimulation by IFN-γ . Interestingly , while the S727A protein could still be tyrosine-phosphorylated , the Y701F mutant was defective for both tyrosine and serine phosphorylation ( Figure 8 B ) . This observation is in agreement with previous findings showing that IFN-γ-dependent S727 phosphorylation occurs exclusively on Y701-phosphorylated STAT1 [101] . Ectopic expression of wild-type STAT1 , STAT1* , and STAT1*S727A but not STAT1*Y701F in addition to the endogenous protein enhanced IE1-mediated activation of CXCL10 and GBP4 transcription . Conversely , siRNA-mediated depletion of endogenous STAT1 strongly reduced this response . Importantly , expression of STAT1* in cells depleted of endogenous STAT1 rescued ISG induction by IE1 almost completely . STAT1*S727A expression also compensated for the lack of endogenous STAT1 , although slightly less efficiently compared to STAT1* , whereas STAT1*Y701F was unable to rescue IE1-mediated ISG activation ( Figure 8 C ) . Thus , although IE1 appears to trigger phosphorylation of STAT1 at both Y701 and S727 , only the former modification is required for ISG activation . Nonetheless , STAT1 S727 phosphorylation may augment IE1-dependent gene activation . Y701 phosphorylation usually causes a cytoplasmic to nuclear shift in steady-state localization and efficient sequence-specific DNA binding of STAT1 dimers ( reviewed in [29] , [30] , [97] ) . Accordingly , immunofluorescence microscopy revealed that the presence of IE1 strongly promotes nuclear accumulation of STAT1 , very similar to what was observed following addition of IFN-γ ( Figure 9 A ) . In contrast , significant amounts of nuclear STAT2 were only detected after treatment of cells with IFN-α but not upon IE1 expression . These results were confirmed by nucleo-cytoplasmic cell fractionation ( Figure 9 B ) . In these assays , IE1 induction for 72 h was as efficient in promoting STAT1 nuclear accumulation as treatment with type I or type II IFNs for 1 h . IFN treatment also strongly induced the nuclear accumulation of STAT2 . However , the levels of nuclear STAT2 increased only marginally upon expression of IE1 . Finally , we asked whether IE1 may direct STAT1 to promoters of type II ISGs . Chromatin immunoprecipitation ( ChIP ) analyses demonstrated that the viral protein potentiates the recruitment of STAT1 to certain IFN-γ- and IE1-responsive ISG promoters ( e . g . , TAP1 ) but not to promoters of several non-ISGs ( e . g . , GAPDH; Figure 10 A ) . Moreover , there was a positive correlation between the magnitude of STAT1 chromatin association induced by IE1 and IFN-γ . At the same time , IE1 had no effect on association of STAT2 with these promoters ( Figure 10 B ) . These results are in agreement with the fact that a previous global ChIP-sequencing study has experimentally demonstrated STAT1 association with 14 ( 56% ) out of the 25 IE1-responsive gene promoters identified in this study ( [102] and Supporting Table S7 ) . In addition , 22 ( 88% ) of these promoter sequences ( all except EDN1 , HBG1 , and HLA-DRA ) carry one or more ( up to six ) predicted STAT1β binding sites ( GAS elements ) according to the PROMO tool ( version 3 . 0 . 2 , default settings with 15% maximum matrix dissimilarity rate , http://alggen . lsi . upc . es ) , which predicts transcription factor binding sites as defined by position weight matrices derived from the TRANSFAC ( version 8 . 3 ) database [103] , [104] . Similar results were obtained with other in silico promoter analysis tools ( data not shown ) . Based on these findings we propose that IE1 activates a subset of ISGs at least in part through increasing the nuclear concentration and sequence-specific DNA binding of phosphorylated STAT1 thereby modulating host gene expression in an unanticipated fashion .
The transcriptional transactivation capacity of the hCMV MIE proteins has been recognized for decades ( [72]; reviewed in [2] , [40] , [41] ) . For example , it has long been established that the 72-kDa IE1 protein can stimulate transcription from its own promoter-enhancer [36] , [105] , [106] . IE1 also activates at least a subset of hCMV early promoters therein collaborating with the viral 86-kDa IE2 protein [34] , [35] , [53] , [71] , [72] , [107] , [108] , [109] . Furthermore , IE1 or combinations of IE1 and IE2 can stimulate expression from a variety of non-hCMV promoters . In fact , numerous heterologous viral and cellular promoters are responsive to IE1 or combinations of IE1 and IE2 [50] , [51] , [52] , [57] , [60] , [61] , [71] , [72] , [110] , [111] , [112] , [113] , [114] , [115] , [116] , [117] . IE1 may accomplish transcriptional activation via interactions with a diverse set of cellular transcription regulatory proteins thereby acting through multiple DNA elements [50] , [51] , [52] , [54] , [55] , [56] , [57] , [58] , [59] , [105] , [106] , [109] , [110] , [111] , [112] , [113] , [117] , [118] , [119] , [120] , [121] , [122] , [123] , [124] , [125] , [126] as well as epigenetic mechanisms including histone acetylation [53] , [59] , [127] . More recently , IE1 has also been implicated in transcriptional repression [31] , [32] , [33] , [57] , [62] , [63] , [64] . Our own work ( [31] and this study , Figure 4 B ) and a report by Huh et al . ( 2008 ) has demonstrated that IE1 can inhibit the hCMV- or IFN-α/β-dependent activation of human ISGs including ISG54 , MxA , PKR , and CXCL10 . The mechanism of inhibition appears to involve physical interactions of IE1 with the cellular STAT1 and STAT2 proteins that result in diminished DNA binding of the ternary ISGF3 complex to promoters of type I ISGs ultimately interfering with transcriptional activation [31] , [32] , [33] . Despite this plethora of studies , our understanding of the true transcriptional regulatory capacity of IE1 is still limited . This is mainly due to the fact that IE1-regulated transcription has almost exclusively been studied at the single gene level . Moreover , much of the past work has relied on transfection-based promoter-reporter assays , and IE1-dependent up- or down-regulation of only very few endogenous human genes has been demonstrated so far . The present work constitutes the first systematic analysis of IE1-specific changes to transcription from the human genome . Importantly , to minimize cellular compensatory effects and to closely mimic the situation during hCMV infection , all experiments were based on short-term ( up to 72 h ) induction of IE1 expression from its autologous promoter ( Figure 1 A–B ) . Just over 0 . 1% ( 25 out of 28 , 869 ) of all human transcripts under examination were found to be significantly up-regulated by IE1 under stringent analysis conditions ( Table 1 ) . This figure may be unexpected in the light of the reported interactions of IE1 with several ubiquitous transcription factors and its reputation as a “promiscuous” transactivator . However , rather than causing a broad transcriptional host response , IE1-specific gene activation was largely restricted to a subset of ISGs that are primarily responsive to IFN-γ ( Table 2 , Figure 4 and Supporting Table S4 ) . Thus , IE1 appears to activate certain ISGs ( typically type II ISGs ) while simultaneously inhibiting the activation of other ISGs ( typically type I ISGs ) . Importantly , more than half ( at least 14 out of the 25 ) IE1-activated genes identified in this study were previously shown to be induced during hCMV infection of fibroblasts and/or other human cell types ( Table 3 ) . This strongly suggests that many if not all IE1-specific transcriptional changes observed in our expression model may be relevant to viral infection . On the other hand , our preliminary results indicate that the conditional replication defect of IE1 knock-out viruses in human fibroblasts [35] , [36] may not result from an inability to initiate an IFN-γ-like response ( data not shown ) . In fact , additional viral gene products are known or expected to contribute to ISG activation during hCMV infection ( reviewed in [26] , [27] ) and may compensate for IE1 in this respect , at least during productive infection of fibroblasts . In addition to being distinctively responsive to IFN-γ , most IE1-activated genes appear to share similar kinetics of induction ( Table 1 and Figure 3 ) , and many cluster in certain genomic locations ( Table 2 ) suggesting a common underlying mechanism of activation . Specific siRNA-mediated STAT1 ( but not STAT2 ) knock-down inhibited IE1-dependent activation of several target ISGs almost completely ( Figure 7 A ) . Conversely , STAT1 overexpression proved to enhance ISG activation in IE1 expressing cells ( Figure 8 C ) . Moreover , defective IE1-activated ISG transcription in cells depleted of endogenous STAT1 was efficiently rescued by ectopic STAT1 expression ( Figure 8 C ) . These results demonstrate that the STAT1 protein is a critical mediator of the cellular transcriptional response to IE1 . Moreover , this response appears to strictly depend on the Y701-phosphorylated form of STAT1 which is induced by IE1 expression ( Figure 8 ) . Although recent work has shown that some STAT1 functions are executed by the non-phosphorylated protein ( reviewed in [97] , [99] , [100] ) , it is the Y701-phosphorylated form that preferentially accumulates in the nucleus and binds to DNA with high affinity ( reviewed in [29] , [30] ) providing a mechanism for IE1-dependent ISG activation . IE1 also induces S727 phosphorylation of STAT1 ( Figure 8 A ) , but this modification is dispensable merely serving an augmenting function in ISG activation triggered by the viral protein ( Figure 8 C ) . Phosphorylation of S727 is thought to be required for the full transcriptional activity of STAT1 by recruiting histone acetyltransferase activity [98] , [128] , [129] . Interestingly , the hCMV IE1 protein can promote histone acetylation [53] suggesting it might compensate for S727 phosphorylation by binding to DNA-associated STAT1 . Our prior work has shown that IE1 physically interacts with STAT1 during hCMV infection and in vitro , and the two proteins co-localize in the nuclei of transfected cells treated with IFN-α [31] . The results of Figure 9 extend these observations by demonstrating that the viral protein facilitates nuclear accumulation and DNA binding of STAT1 in the absence of IFNs . The STATs were initially described as cytoplasmic proteins that enter the nucleus only in the presence of cytokines . However , it has now been established that STATs constantly shuttle between nucleus and cytoplasm irrespective of cytokine stimulation ( reviewed in [97] , [130] , [131] ) . Thus , complex formation between nuclear resident IE1 and STAT1 passing through the nucleus may be sufficient to impair STAT1 export to the cytoplasm resulting in nuclear retention and increased DNA binding of the cellular protein . In this scenario , IE1 may increase the levels of Y701-phosphorylated STAT1 by interfering with nuclear dephosphorylation of the cellular protein . In fact , DNA binding was shown to protect STAT1 from dephosphorylation , which normally occurs at a step preceding export to the cytoplasm [132] , [133] . This one-step “nuclear shortcut” model assumes that small amounts of Y701-phosphorylated STAT1 enter the nucleus in the absence of IFNs and any potential IE1-induced mediators of STAT1 activation . Conceivably , human fibroblasts ( TetR cells ) may constitutively release small amounts of soluble inducers ( e . g . , certain growth factors; see below ) that maintain residual levels of activated STAT1 undetectable by immunoblotting ( Figure 8 A ) . Moreover , we cannot rule out that the fetal calf serum used for cell culture media may contain factors causing a limited number of STAT1 molecules to undergo Y701 phosphorylation . In contrast , increased S727 phosphorylation in the presence of IE1 may result from higher levels of DNA-targeted STAT1 , as this modification is preferentially or exclusively incorporated into the nuclear chromatin-associated cellular protein , at least during the normal IFN-γ response [101] . Alternatively , IE1 may actively induce STAT1 Y701 phosphorylation thereby promoting nuclear import of STAT1 dimers . This phosphorylation event is typically mediated by cytoplasmic JAK family kinases upon ligand-mediated activation of IFN receptors . However , our results demonstrate that IE1 does not induce the expression of human IFN genes , and we found no evidence for IFN-γ or IFN-β secretion from IE1 expressing cells ( Supporting Table S5 , Figure 6 and data not shown ) . Moreover , our transwell and media transfer experiments indicate that cytokines or other soluble mediators that may constitute a hypothetical IE1 “secretome” are not sufficient to stimulate ISG expression ( Figure 5 and data not shown ) . However , this does not rule out the possibility that IE1 may cooperate with one or more soluble factors to trigger the observed transcriptional response . In fact , 80% of all IE1 target genes were not found activated within the first 24 h after induction of IE1 expression despite the fact that the viral protein had reached almost peak levels by this time ( Figure 1 B and Table 1 ) . Instead , up-regulation typically started at 48 h and increased until at least 72 h following IE1 expression ( Table 1 and Figure 3 A ) . This timing of induction is compatible with a two-step model in which IE1 first initiates de novo synthesis and secretion of an unidentified cellular gene product required to trigger STAT1 Y701 phosphorylation ( step 1 ) . Besides IFNs , STAT1 signaling can be induced by several interleukins ( e . g . , IL-6 ) some of which are known to be up-regulated by IE1 [58] , [60] , [61] , [110] . However , STAT1 Y701 phosphorylation can also occur independently of cytokines ( reviewed in [134] ) . In fact , growth factors including the epidermal growth factor and certain hormones are also able to induce STAT1 Y701 phosphorylation [135] , [136] , [137] , [138] , [139] . In addition , tumor necrosis factor ( TNF ) has been shown to signal through activated STAT1 [140] raising the intriguing possibility that the soluble protein products of TNFSF4 and/or TNFSF18 , two TNF family members belonging to the few genes already activated by 24 h following IE1 induction ( Table 1 ) , may be involved in IE1-mediated Y701 phosphorylation of STAT1 . However , activation of one or more of these IFN-independent pathways may not produce enough activated nuclear STAT1 to trigger efficient ISG expression and may therefore be required but not sufficient for IE1-mediated gene induction . In accordance with this possibility , the levels of Y701-phosphorylated STAT1 were much higher in IFN-γ-treated as compared to IE1 expressing cells ( Figure 8 A ) . Thus , on top of low level Y701 phosphorylation , IE1-dependent nuclear retention of STAT1 through complex formation between the viral and cellular protein ( as outlined for the one-step model; see above ) may be necessary in order to elicit a significant transcriptional response ( step 2 ) . Although activated STAT1 is clearly a key mediator of IE1-dependent ISG induction , additional factors may be involved . In fact , not all known STAT1-activated human genes seem to be included in the IE1-specific transcriptome implying that additional gene products likely contribute to target specificity . One of the candidate co-factors that has been repeatedly linked to IE1 function is NFκB . In fact , IE1 was shown to activate the NFκB p65 ( RelA ) and RelB promoters [55] , [112] , [113] , [121] , to facilitate expression of the NFκB RelB subunit and/or NFκB post-translational activation [58] , [113] , [119] , [121] , and to activate transcription through NFκB binding sites [58] , [105] , [106] , [113] , [119] , [126] . At the same time , NFκB has been implicated in IFN-γ-induced activation of a subset of ISGs including CXCL10 and GBP2 ( [141] , [142] , [143] , [144] , [145]; reviewed in [146] , [147] ) . However , we did not observe nuclear translocation of NFκB following induction of IE1 in TetR-IE1 cells . Moreover , siRNA-mediated knock-down of NFκB p65 had no significant impact on IE1-activated CXCL10 and GBP4 expression in these cells ( data not shown ) . These observations indicate that the transcriptional response to IE1 is largely independent of NFκB , at least within our experimental setup . IRF1 is another transcription factor that contributes to the activation of certain ISGs including CTSS , GBP2 , and TAP1 ( [128] , [148] , [149] , [150]; reviewed in [80] , [81] , [82] ) . IRF1 might enhance IE1-mediated ISG activation , especially since its mRNA is up-regulated by expression of the viral protein ( Table 1 and Figure 4 A ) . A key feature of the IE1 protein appears to be its ability to target to and disrupt subnuclear multi-protein structures known as PML bodies or ND10 during the early phase of hCMV infection and upon ectopic expression [42] , [43] , [44] . The mechanism of IE1-dependent ND10 disruption most likely involves binding to the PML protein , a major constituent of ND10 [54] . We have not specifically investigated the role of PML in IE1-mediated gene induction . Nonetheless , our results are compatible with the possibility that ND10 disruption is required for the transcriptional response to IE1 since the nuclear structures were confirmed to be disintegrated at both post-induction time points ( 24 h and 72 h ) of our microarray analysis ( data not shown ) . Although the exact function of ND10 remains unclear , the structures have been implicated in a variety of processes including inflammation [151] and anti-viral defense ( reviewed in [45] , [46] , [47] , [48] ) . Besides a proposed role of ND10 in viral gene expression , they may also function in transcriptional regulation of certain cellular genes . Several examples of selective associations between ND10 and genes or chromosomal loci , especially regions of high transcription activity and/or gene density , have been reported ( reviewed in [152] ) . For example , immunofluorescent in situ hybridization analyses demonstrated that the major histocompatibility ( MHC ) class I gene cluster on chromosome 6 ( 6p21 ) is non-randomly associated with ND10 in human fibroblasts [153] . Transcriptional activation in the presence of IFN-γ correlates with the relocalization of this locus to the exterior of the chromosome 6 territory in a process that appears to involve DNA binding of Y701-phosphorylated STAT1 , changes in chromatin loop architecture , and histone hyperacetylation [154] , [155] , [156] . Interestingly , many IE1-activated genes cluster in certain genomic locations ( Table 2 ) . This includes the HLA-DRA and TAP1 genes located within the ND10-associated MHC locus at 6p21 . Together these observations raise the intriguing possibility that , through a combination of PML disruption and STAT1 activation , IE1 might cause higher order chromatin remodeling of entire chromosomal loci resulting in transcriptional activation . One of the most surprising findings of the present study concerns the fact that most IE1-induced cellular genes are generally associated with stimulatory rather than inhibitory effects on immune function and inflammation ( Table 1 , Figure 2 and Supporting Tables S1 , S2 ) . It has been proposed that certain inflammatory and innate defense mechanisms launched by the host to limit hCMV replication may actually facilitate viral dissemination , for example by increasing target cell availability and/or by creating an environment conducive to virus reactivation ( coined “no pain , no gain” by Mocarski [157] ) . Thus , it is plausible that hCMV not just attenuates host immunity through the numerous immune evasion mechanisms ascribed to this virus ( reviewed in [158] ) , but rather aims at counterbalancing the effects of the innate and inflammatory response in restricting and facilitating viral replication . This strategy may be crucial in allowing for what has been termed “mutually assured survival” of both virus and host [159] . The functional group of IE1-induced pro-inflammatory proteins potentially involved in viral target cell recruitment is best represented by the chemokines CXCL9 , CXCL10 , and CXCL11 . All three proteins are not only induced by IE1 ( Table 1 and Figures 3–7 ) but also during hCMV infection of various cell types , and they represent major constituents of the viral secretome ( [4] , [18] , [24] , [160] , [161] , [162] , [163] , [164] , [165] and Table 3 ) . By binding to a common receptor , termed CXCR3 , the three chemokines have the ability to attract subsets of circulating leukocytes to sites of infection and/or inflammation ( reviewed in [74] , [75] ) . Although CXCR3 is preferentially expressed on activated T helper 1 cells , the receptor protein is also present on many other cell types including CD34+ hematopoietic progenitors [166] which are preferential sites of hCMV latency [167] , [168] , [169] , [170] , [171] , [172] . CXCR3 and its ligands have been implicated in a large variety of inflammatory and immune disorders ( reviewed in [74] , [75] ) . For example , cells expressing CXCR3 are found at high numbers in biopsies taken from patients experiencing organ transplant dysfunction and/or rejection [173] , [174] , [175] , [176] , [177] , [178] , [179] , [180] , [181] . Moreover , CXCL9 [175] , [176] , [177] , [179] , [180] , CXCL10 [173] , [174] , [175] , [176] , [177] , [179] , [180] , and CXCL11 [175] , [176] , [177] , [178] , [179] , [180] , [181] mRNA and protein levels are increased in tissues of organs undergoing rejection . Importantly , the levels of CXCR3-positive cells and CXCR3 ligand mRNA in the biopsy samples frequently correlate with the grade of graft rejection [174] , [176] , [177] , [178] , [180] suggesting a causative role of this pathway . Up-regulation of CXCL10 and other chemokines also correlated with transplant vascular sclerosis and chronic rejection in an rCMV cardiac allograft infection model [4] , [182] , [183] . In addition to CXCL9 , CXCL10 , and CXCL11 , IE1 also up-regulates expression of CCL11 ( Table 1 ) , another CXCR3-interacting chemokine [184] . Through activation of the CXCR3 axis , IE1 might contribute to hCMV dissemination and pathogenesis in unexpected ways . The IE1 protein has long been suspected to be a key player in the events leading to reactivation from hCMV latency although this view has recently been challenged by functional analysis of the mCMV and rCMV IE1 orthologs in mouse and rat models of infection , respectively [37] , [185] . Nonetheless , inflammatory ( including allogeneic ) immune responses are believed to be efficient stimuli for hCMV reactivation . In fact , stimulation of latently infected monocytes or myeloid progenitor cells with pro-inflammatory cytokines including IFN-γ can reactivate viral replication ( [186] , [187] , [188] , [189]; reviewed in [190] , [191] , [192] ) . IFN-γ may aid hCMV reactivation by affecting cellular differentiation ( [193]; reviewed in [28] , [190] , [191] , [192] ) and/or by activating transcription through GAS-like elements present in the viral MIE promoter-enhancer [194] . These GAS-like elements were shown to be required for efficient hCMV transcription and replication , at least after low multiplicity infection , and IFNs enhanced MIE gene expression [194] . Conceivably , the IE1 protein may phenocopy the effect of IFN-γ in activating both cellular ISGs and the viral MIE promoter thereby facilitating viral reactivation . Conversely , along the lines of the “immune sensing hypothesis of latency control” proposed by Reddehase and colleagues [195] , episodes of IE1 expression may promote maintenance of viral latency not only through providing antigenic peptides ( reviewed in [196] ) but also by concomitantly activating critical immune effector functions including antigen transport ( TAP1 ) , processing ( CTSS ) and presentation ( HLA-DRA ) as well as immune cell recruitment ( CXCL9 , CXCL10 , CXCL11 , CCL11; see above ) and co-stimulation ( TNFSF4 , TNFSF18 and CD274 ) . Current anti-hCMV strategies are directed against viral DNA replication , but sometimes fail to halt disease . This may be due to virus-induced “side effects” that are not correlated to production of virus particles and lysis of host cells . In fact , in hCMV pneumonitis and retinitis , disease symptoms were repeatedly found in the absence of replicating virus or viral cytopathogenicity [197] , [198] . Similarly , in mouse models of viral pneumonitis mCMV replication per se was not sufficient to cause disease [197] , [199] , [200] . Conversely , mCMV disease could be triggered immunologically without inducing viral replication [201] . Here we have shown that out of >160 different hCMV gene products , a single protein ( IE1 ) is sufficient to alter the expression of human genes with strong pro-inflammatory and immune stimulatory potential without the requirement for virus replication . The present work supports the idea that the hCMV MIE gene and specifically the IE1 protein may play a direct and predominant role in viral immunopathogenesis and inflammatory disease [202] , [203] , [204] , [205] . Thus , the IE1 protein should be considered a prime target for the development of improved prevention and treatment options directed against hCMV .
The pMD2 . G and psPAX2 packaging vectors for recombinant lentivirus production were obtained from Addgene ( http://www . addgene . org; plasmids 12259 and 12260 , respectively ) . Plasmids pLKOneo . CMV . EGFPnlsTetR , pLKO . DCMV . TetO . cICP0 , and pCMV . TetO . cICP0 were kindly provided by Roger Everett ( Glasgow , UK ) . pLKOneo . CMV . EGFPnlsTetR contains the complete hCMV MIE promoter upstream of a sequence encoding EGFP fused to an NLS and TetR [68] , [69] , [70] . In the pLKO . 1puro derivative pLKO . DCMV . TetO . cICP0 , expression of the herpes simplex virus type 1 infected cell protein 0 cDNA ( cICP0 ) is under the control of a tandem TetO sequence located downstream of a truncated version of the hCMV MIE promoter ( DCMV ) [69] , [70] . To generate pLKO . DCMV . TetO . cIE1 , the IE1 cDNA of the hCMV Towne strain was PCR-amplified from pEGFP-IE1 [71] with upstream primer #483 containing a HindIII site and downstream primer #484 containing an EcoRI site ( the sequences of all primers used in this study are listed in Supporting Table S8 ) . The IE1 sequence was subcloned into the HindIII and EcoRI sites of pCMV . TetO . cICP0 . The NdeI-EcoRI fragment of the resulting plasmid pCMV . TetO . IE1 was verified by sequencing and used to replace the ICP0 cDNA in pLKO . DCMV . TetO . cICP0 thereby generating plasmid pLKO . DCMV . TetO . cIE1 . QuikChange site-directed mutagenesis of plasmid pRc/CMV-hSTAT1p91 ( kindly provided by Christian Schindler , New York , USA ) with oligonucleotides #660 and #661 resulted in pCMV-STAT1* encoding a STAT1 variant mRNA resistant to silencing by the STAT1-specific siRNA duplex #146 ( the sequences of all siRNAs used in this study are listed in Supporting Table S9 ) . The plasmids pCMV-STAT1*Y701F and pCMV-STAT1*S727A were generated by QuikChange mutagenesis of pCMV-STAT1* with primer pairs #662/#663 and #664/#665 , respectively . BamHI-EcoRV fragments of pRc/CMV-hSTAT1p91 , pCMV-STAT1* , pCMV-STAT1*Y701F , and pCMV-STAT1*S727A were treated with Klenow fragment and ligated to the HpaI-digested , dephosphorylated retroviral vector pLHCX ( Clontech , no . 631511 ) resulting in plasmids pLHCX-STAT1 , pLHCX-STAT1* , pLHCX-STAT1*Y701F , and pLHCX-STAT1*S727A , respectively . The correct orientations and nucleotide sequences of the inserted STAT1 cDNAs were verified by sequencing . Human MRC-5 embryonic lung fibroblasts ( Sigma-Aldrich , no . 05011802 ) , the human p53-negative non-small cell lung carcinoma cell line H1299 ( ATCC , no . CRL-5803 [206] ) , and Phoenix-Ampho retrovirus packaging cells ( from Garry Nolan , Stanford , USA [207] ) were maintained in Dulbecco's Modified Eagle's Medium supplemented with 10% fetal calf serum , 100 units/ml penicillin , and 100 µg/ml streptomycin . All cultures were regularly screened for mycoplasma contamination using the PCR Mycoplasma Test Kit II from PromoKine . Where applicable , cells were treated with 1 , 000 U/ml recombinant human IFN-α A/D ( R&D Systems , no . 11200 ) , 10 ng/ml recombinant human IFN-β 1a ( Biomol , no . 86421 ) , or 10 ng/ml recombinant human IFN-γ ( R&D Systems , no . 285-IF ) for various durations . Neutralizing goat antibodies to human IFN-β ( no . AF814 ) or IFN-γ ( no . AF-285-NA ) and normal goat IgG ( no . AB-108-C ) were purchased from R&D Systems and used at concentrations of 1 µg/ml ( anti-IFN-β ) or 2 µg/ml ( anti-IFN-γ , normal IgG ) . Transwell assays were performed in tissue-culture-treated 100-mm plates with polycarbonate membrane and 0 . 4 µm pore size ( Corning , no . 3419 ) . During the week prior to transfection , Phoenix-Ampho cells were grown in medium containing hygromycin ( 300 µg/ml ) and diphtheria toxin ( 1 µg/ml ) . Production of replication-deficient retroviral particles , retrovirus infections , and selection of stable cell lines were performed according to the pLKO . 1 protocol available on the Addgene website ( http://www . addgene . org/pgvec1 ? f=c&cmd=showcol&colid=170&page=2 ) with minor modifications . Retroviral particles were generated by transient transfection of H1299 cells ( pLKO-based vectors ) or Phoenix-Ampho cells ( pLHCX-based vectors ) using the calcium phosphate co-precipitation technique [208] . Recombinant viruses were collected 36 h and 60 h after transfection , and were used for transduction of target cells by two subsequent 16 h incubations . To generate TetR cells , MRC-5 fibroblasts at population doubling 19 were infected with pLKOneo . CMV . EGFPnlsTetR-derived lentiviruses and selected with G418 ( 0 . 2 mg/ml ) . To generate TetR-IE1 cells , TetR cells were transduced by pLKO . DCMV . TetO . cIE1-derived lentiviruses and selected with puromycin ( 1 µg/ml ) . Cells with high level EGFPnlsTetR expression ( and low IE1 background ) were enriched by fluorescence-activated cell sorting in a FACSCanto II flow cytometer ( BD Biosciences ) . TetR cells were maintained in medium containing G418 ( 0 . 1 mg/ml ) , while TetR-IE1 cells were cultured in the presence of both G418 ( 0 . 1 mg/ml ) and puromycin ( 0 . 5 µg/ml ) . To induce IE1 expression , cells were treated with doxycycline ( Clontech , no . 631311 ) at a final concentration of 1 µg/ml . To generate TetR-IE1 cells with stable expression of ectopic STAT1 proteins , uninduced TetR-IE1 cells were transduced with pLHCX-derived retroviruses encoding STAT1 , STAT1* , STAT1*Y701F , or STAT1*S727A . The EGFP-expressing wild-type Towne strain ( TNwt ) of hCMV was derived from an infectious BAC clone ( T-BACwt [209] ) of the viral genome . Allelic exchange to generate IE1-deficient viruses ( TNdlIE1 ) and corresponding “revertants” ( TNrvIE1 ) utilized the following derivatives of transfer plasmid pGS284 [210]: pGS284-TNIE1kanlacZ , pGS284-TNMIEdlIE1 , pGS248-TNMIE , and pGS284-TNMIErvIE1 . Plasmid pGS284-TNIE1kanlacZ contains the kanamycin resistance gene ( kan ) and the lacZ gene cloned between sequences flanking the IE1-specific exon four of the hCMV TN MIE transcription unit . The ∼1000-bp flanking sequences were obtained by PCR amplification using primers #136 and #137 ( downstream flanking sequence ) or #139 and #140 ( upstream flanking sequence; for PCR primer sequences , see Supporting Table S8 ) and T-BACwt as template . The amplified downstream flanking sequence was cloned into pGS284 via BglII and NotI sites present in both the PCR primers and target vector sequences . Following addition of adenosine nucleotide overhangs to the 3′-ends of the PCR product , the upstream flanking sequence was first subcloned into vector pCR4-TOPO ( Invitrogen ) and subsequently inserted via NotI sites into pGS284 carrying the downstream flanking sequence . The kanlacZ expression cassette was released from plasmid YD-C54 [211] and cloned into the PacI sites ( introduced through PCR primers #137 and #139 ) located between the hCMV flanking sequences in the pGS284 derivative described above . Plasmid pGS284-TNMIEdlIE1 contains an MIE fragment lacking 1 , 413 bp between the AccI sites upstream and downstream of exon four . The exon four-deleted MIE fragment was obtained from T-BACwt by overlap extension PCR as previously described [212] . The primer pairs used for PCR mutagenesis were #348/#349 ( upstream fragment ) , #350/#351 ( downstream fragment ) , and #348/#351 ( complete fragment ) . The final PCR product was cloned via BglII and NotI sites into pGS284 . For the construction of pGS248-TNMIE ( previously termed pGS248-MIE; [33] ) , a ∼3000-bp sequence of the MIE region was amplified by PCR using template T-BACwt and primers #155 and #156 . After phosphorylation , the PCR product was first inserted into the SmaI site of pUC18 and then excised from this vector via FseI and NotI sites . The FseI-NotI fragment was subsequently cloned into the same sites of pGS284-TNMIEdlIE1 thereby repairing the exon four deletion in this plasmid to generate pGS284-TNMIErvIE1 . DNA sequence analysis was completed on all hCMV-specific PCR amplification products to confirm their integrity . Allelic exchange was performed through homologous recombination in Escherichia coli strain GS500 as previously described [33] , [210] , [211] . First , the BAC pTNIE1kanlacZ was generated by recombination of T-BACwt with pGS284-TNIE1kanlacZ followed by selection for kanamycin resistance and LacZ expression . After that , the BACs pTNdlIE1 and pTNrvIE1 were made through recombination of pTNIE1kanlacZ with pGS284-TNMIEdlIE1 and pGS284-TNMIErvIE1 , respectively , followed by selection for the loss of kanamycin resistance and LacZ expression . The BAC constructs were analyzed by EcoRI digestion . The BACs pTNdlIE1 and pTNrvIE1 were used for electroporation of MRC-5 cells to reconstitute viruses TNdlIE1 and TNrvIE1 , respectively , as has been described previously [211] . Cell- and serum-free virus stocks were produced upon BAC transfection of MRC-5 fibroblasts ( TNwt and TNrvIE1 ) or TetR-IE1 cells ( TNdlIE1 ) , and the titers of the wild-type TN and revertant preparations were determined by standard plaque assay on MRC-5 cells . Titration of TNdlIE1 stocks was performed by quantification of intracellular genome equivalents [33] . Multistep replication analysis of recombinant viruses on TetR and TetR-IE1 cells has been described previously [33] . For global transcriptome analysis , 1 . 9×106 TetR or TetR-IE1 cells of the same passage number were seeded on 10-cm dishes . When cells reached confluency ( three days after plating ) , the medium was replaced , and cells were growth-arrested by maintaining them in the same medium for seven days before they were collected for transcriptome analysis . During the last 72 h or 24 h prior to collection , cultures were treated with doxycycline at a final concentration of 1 µg/ml or were left untreated . Total RNA was isolated using TRIzol reagent ( Invitrogen ) and Phase Lock Gel Heavy ( Eppendorf ) according to the manufacturers' instructions . A second purification step with on-column DNase digestion was performed on the isolated RNA using the RNeasy Mini Kit from Qiagen . All subsequent steps were performed at the Kompetenzzentrum für Fluoreszente Bioanalytik ( Regensburg , Germany ) . Total RNA ( 100 ng ) was labeled using reagents and protocols specified in the Affymetrix GeneChip Whole Transcript ( WT ) Sense Target Labeling Assay Manual ( P/N 701880 Rev . 4 ) . Quantity and quality of starting total RNA , cRNA , and single-stranded cDNA were assessed in a NanoDrop spectrophotometer ( Thermo Fisher Scientific ) and a 2100 Bioanalyzer ( Agilent Technologies ) , respectively . Samples were hybridized to Affymetrix Human Gene 1 . 0 ST Arrays which interrogate 28 , 869 well-annotated genes and cover >99% of sequences present in the RefSeq database ( National Center for Biotechnology Information ) . We probed a total of 18 microarrays , which allowed us to monitor three biological replicates for each experimental condition ( TetR and TetR-IE1 cells without and with 24 h and 72 h of doxycycline treatment ) . For creation of the summarized probe intensity signals , the Robust Multi-Array Average algorithm [213] was used . Files generated by the Affymetrix GeneChip Operating 1 . 4 and Expression Console 1 . 1 software have been deposited in Gene Expression Omnibus ( GEO , National Center for Biotechnology Information [214] ) and are accessible through GEO Series accession number GSE24434 ( http://www . ncbi . nlm . nih . gov/geo/query/acc . cgi ? acc=GSE24434 ) . In order to determine steady-state mRNA levels by qRT-PCR , total RNA was isolated from 3 to 4×105 fibroblasts using Qiagen's RNeasy Mini Kit and RNase-Free DNase Set according to the manufacturer's instructions . First-strand cDNA was synthesized using SuperScript III and Oligo ( dT ) 20 primers ( Invitrogen ) starting from 2 µg of total RNA . Unless otherwise noted , first-strand cDNA was diluted 10-fold with sterile ultrapure water , and 5 µl were used to template 20-µl real-time PCRs performed in a Roche LightCycler 1 . 5 [33] . The instrument was operated with a ramp rate of 20°C per sec using the following protocol: pre-incubation cycle ( 95°C for 10 min , analysis mode: none ) , 40 to 50 amplification cycles with single fluorescence measurement at the end of the extension step ( denaturation at 95°C for 10 sec , primer-dependent annealing at 66 to 56°C for 10 sec , primer-dependent extension at 72°C for 8 to 10 sec , analysis mode: quantification ) , melting curve cycle with continuous data acquisition during the melting step ( denaturation at 95°C for 0 sec , annealing at 65°C for 60 sec , melting at 95°C for 0 sec with a ramp rate of 0 . 1°C/sec , analysis mode: melting curves ) , cooling cycle ( 40°C for 30 sec , analysis mode: none ) . The PCR mix was composed of 9 µl PCR grade water , 1 µl forward primer solution ( 10 µM ) , 1 µl reverse primer solution ( 10 µM ) , and 4 µl 5× concentrated Master Mix from the LightCycler FastStart DNA MasterPLUS SYBR Green I kit . The sequences of the high pressure liquid chromatography-purified PCR primers are listed in Supporting Table S8 . All samples were quantified at least in duplicate , and each analysis included positive , minus-RT , and non-templated controls . The second derivate maximum method with arithmetic baseline adjustment ( LightCycler Software 3 . 5 ) was used to determine quantification cycle ( Cq ) values . Cq values were further validated by ensuring they meet the following criteria: ( i ) corresponding melting peaks of the generated PCR products , calculated using the polynomial method with digital filters enabled , had to match the single peak of the positive control sample , ( ii ) standard deviations of Cq values from technical replicates had to be below 0 . 33 , ( iii ) Cq values had to be significantly different from minus-RT controls ( CqCq-RT-1 ) , and ( iv ) Cq values had to be within the linear quantification range . The linear quantification range was individually determined for each primer pair by generating a standard curve with serial dilutions of first-strand cDNA from the sample with the highest expression level . PCR efficiency ( E ) was calculated from the slope of the standard curve according to equation ( 1 ) : ( 1 ) The relative expression ratio ( R ) of the target ( trgt ) and reference ( ref ) gene in an experimental ( eptl ) versus control ( ctrl ) sample was calculated using the efficiency-corrected model shown in equation ( 2 ) : ( 2 ) Control samples of all experiments had reference and target gene expression levels well above the limits of detection . The tubulin-β gene ( TUBB ) was chosen as a reference , because ( i ) expression levels did not change upon IE1 induction , IFN treatment , siRNA transfection , or hCMV infection , ( ii ) it allowed for RNA-specific detection with no spurious product generation in minus-RT controls , and ( iii ) it exhibited similar expression levels compared to the target genes under investigation , which were generally expressed at levels lower than TUBB in the absence and at similar or higher levels relative to TUBB in the presence of IE1 expression , IFN treatment , or hCMV infection . CXCL9 , CXCL10 , and CXCL11 chemokine concentrations in cell culture supernatants were determined using commercially available colorimetric sandwich enzyme immunoassay kits ( Quantikine Immunoassays no . DCX900 , DIP100 , and DCX110 from R&D Systems ) following the manufacturer's instructions . The sequences of siRNA duplexes used for mRNA knock-down experiments are listed in Supporting Table S9 . They were introduced into cells at 30 nM final concentration using the Lipofectamine RNAiMAX Reagent ( Invitrogen ) following the manufacturer's instructions . Briefly , exponentially growing cells were seeded either in 12-well dishes at 2 . 5×105 cells/well for RNA analyses or in 6-well dishes at 5×105 cells/well for protein analyses . Transfections were performed in Opti-MEM I Reduced Serum Medium ( Invitrogen ) with 2 µl or 5 µl of RNAiMAX Reagent for 12- or 6-wells , respectively . Cells ( 3 . 8×106 ) on 10-cm dishes were collected with trypsin/EDTA and then centrifuged for 5 min at 500× g and 4°C . Supernatants were removed and cells resuspended in 100 µl CSK buffer ( 10 mM PIPES [pH 6 . 8] , 300 mM sucrose , 100 mM NaCl , 3 mM MgCl2 , 1 mM EDTA , 0 . 1% ( v/v ) Igepal CA-630 ) with freshly added protease and phosphatase inhibitor cocktails . Lysates were centrifuged for 1 min at 1 , 300× g and 4°C , and the supernatants ( cytoplasmic extracts ) were transferred to clean pre-chilled tubes and combined with one volume of 2× protein sample buffer ( 100 mM Tris-HCl [pH 6 . 8] , 4% ( w/v ) SDS , 20% ( v/v ) glycerol , 200 mM β-mercaptoethanol , 0 . 1% ( w/v ) bromophenol blue ) . The insoluble ( pellet ) fractions containing nuclei were washed once with 500 µl CSK buffer before they were suspended in 200 µl 2× protein sample buffer and sonified in a Bioruptor ( Diagenode; “H” setting; 30 sec on-off interval ) for 15 min . Samples were centrifuged for 10 min at 20 , 000× g and 4°C , and the supernatants ( nuclear extracts ) were transferred to clean pre-chilled tubes . Cytosolic and nuclear extracts were heated to 95°C for 5 min before immunoblot analysis . Generation of whole cell extracts , sodium dodecyl sulfate-polyacrylamide gel electrophoresis , immunoblotting , and ( immuno ) fluorescence microscopy were performed according to previously published protocols [33] , [53] , [215] . Immunodetection employed primary mono- or polyclonal antibodies directed against hCMV IE1 ( 1B12; [216] ) or human GAPDH ( Abcam , no . ab9485 ) , histone H2A ( Abcam , no . ab13923 ) , STAT1 ( no . sc-464 for immunoblotting and no . sc-346 for immunofluorescence , both from Santa Cruz ) , STAT1α ( Santa Cruz , no . sc-345 ) , STAT2 ( Santa Cruz , no . sc-22816 ) , and phosphorylated STAT1 ( Y701-specific antibody no . 9171 and S727-specific antibody no . 9177 , both from Cell Signaling Technologies ) . The secondary antibodies used were peroxidase-conjugated goat anti-mouse ( no . 115-035-166 ) or goat anti-rabbit IgG ( no . 111-035-144 ) from Dianova for immunoblotting , and highly cross-adsorbed Alexa Fluor 594- or Alexa Fluor 633-conjugated goat anti-mouse ( no . A-11032 or no . A-21052 , respectively ) and Alexa Fluor 546-conjugated goat anti-rabbit IgG ( no . A-11035 ) from Invitrogen for immunofluorescence . ChIP was performed essentially as described by Nelson et al . [217] , [218] . Resting cells on a 15-cm dish were cross-linked by treatment with 1% ( v/v ) formaldehyde for 10 min at 37°C . Isolated chromatin was sonified for 15 min in a Bioruptor ( Diagenode; “H” setting , 30 sec on-off interval ) and cleared by centrifugation for 20 min at 20 , 000× g and 4°C . Sheared chromatin from 7×106 cells ( 0 . 7 ml ) was subjected to immunoprecipitation for 16 h at 4°C with gentle rotation using 10 µg of antibody . Two different polyclonal rabbit antibodies each against STAT1 ( no . sc-3454 and sc-346 from Santa Cruz ) and STAT2 ( no . sc-476 and sc-839 from Santa Cruz ) were used . After the antibody incubation step , insoluble material was removed by centrifugation ( 10 min at 20 , 000× g and 4°C ) and 0 . 63 ml ( 90% ) supernatant was transferred to a clean pre-chilled tube . Antibody-antigen complexes were isolated by sedimentation following incubation with 60 µl of Protein A Agarose/Salmon Sperm DNA slurry ( Millipore ) for 60 min at 4°C . PCR-ready DNA was prepared using Chelex-100 and duplicate samples of 5 µl ( 25% of the final reaction volume ) each were used for DNA quantification by qPCR as described above and in recent publications [33] , [215] . The PCR primer sequences are listed in Supporting Table S8 . | Human cytomegalovirus ( hCMV ) is a leading cause of birth defects and severe disease in people with compromised immunity . Disease caused by hCMV is frequently linked to inflammation , and the virus has been shown to induce numerous host genes many of which encode pro-inflammatory proteins . However , little is known about the contributions of individual viral proteins to these changes in cellular transcription . We systematically analyzed the effects of the hCMV immediate-early 1 ( IE1 ) protein , a major viral transcriptional activator , on expression of >28 , 000 human genes . Following expression under conditions mimicking the situation during hCMV infection , IE1 elicited a transcriptional response dominated by the up-regulation of pro-inflammatory and immune stimulatory genes normally induced by the secreted signaling protein interferon-γ . However , IE1-mediated gene expression was independent of interferon induction , yet required the activated form of signal transducer and activator of transcription 1 ( STAT1 ) , a central mediator of interferon signaling . Indeed , STAT1 moved to the nucleus and became associated with IE1 target genes upon expression of the viral protein . Our results demonstrate that a single hCMV protein can trigger a pro-inflammatory host cell response via an unexpected mechanism and suggest that IE1 may contribute to hCMV disease in more direct ways than previously thought . | [
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"fami... | 2011 | Human Cytomegalovirus IE1 Protein Elicits a Type II Interferon-Like
Host Cell Response That Depends on Activated STAT1 but Not
Interferon-γ |
Despite many years of study into inversions , very little is known about their functional consequences , especially in humans . A common hypothesis is that the selective value of inversions stems in part from their effects on nearby genes , although evidence of this in natural populations is almost nonexistent . Here we present a global analysis of a new 415-kb polymorphic inversion that is among the longest ones found in humans and is the first with clear position effects . This inversion is located in chromosome 19 and has been generated by non-homologous end joining between blocks of transposable elements with low identity . PCR genotyping in 541 individuals from eight different human populations allowed the detection of tag SNPs and inversion genotyping in multiple populations worldwide , showing that the inverted allele is mainly found in East Asia with an average frequency of 4 . 7% . Interestingly , one of the breakpoints disrupts the transcription factor gene ZNF257 , causing a significant reduction in the total expression level of this gene in lymphoblastoid cell lines . RNA-Seq analysis of the effects of this expression change in standard homozygotes and inversion heterozygotes revealed distinct expression patterns that were validated by quantitative RT-PCR . Moreover , we have found a new fusion transcript that is generated exclusively from inverted chromosomes around one of the breakpoints . Finally , by the analysis of the associated nucleotide variation , we have estimated that the inversion was generated ~40 , 000–50 , 000 years ago and , while a neutral evolution cannot be ruled out , its current frequencies are more consistent with those expected for a deleterious variant , although no significant association with phenotypic traits has been found so far .
Polymorphic inversions have been known for a long time to segregate in the genomes of multiple species , ranging from insects to plants and animals , and constitute one of the most studied paradigms in evolutionary biology [1–3] . Given that they just change the orientation of a chromosomal segment and often do not result in gain or loss of DNA , inversions could easily be considered neutral variants , but far from this , their adaptive value and phenotypic effects are becoming increasingly clear . For example , in several species of Drosophila inversions affect characters like body size or developmental time [2] , and some of them exhibit latitudinal or altitudinal clines that strongly suggest adaptation to different environmental conditions [1 , 4] . Inversions have also been attributed roles in flowering time and reproductive isolation between two ecotypes of monkeyflower [5] , wing-pattern morphs in mimetic butterflies [6] , stickleback fish freshwater adaptation [7] , or in the social behavior and plumage color in sparrows [8] , and even a human 900-kb inversion in chromosome 17 is thought to affect fertility and be positively selected in European populations [9] . However , the molecular mechanisms by which inversions are able to affect phenotype are not yet clear . Two main mechanisms have been proposed [10] . One is based on the effective suppression of recombination within the inverted sequence between standard and inverted chromosomes . This suppression can occur both through the reduced pairing and crossing over due to the formation of inversion loops in heterozygotes , and by selection against the unbalanced gametes resulting from unique crossovers within the inverted segment . In this case , the advantage of an inversion could be caused by the capture of a favorable combination of alleles maintained together in strong linkage disequilibrium ( LD ) due to the reduction of recombination [2 , 11 , 12] . Another option is that the phenotypic consequences of inversions depend on the mutational effect of their breakpoints on adjacent genes . Breakpoints can disrupt genes as happens in several disease-causing mutations in humans [13–15] or modify gene expression by separating coding regions from their regulatory elements or by providing new regulatory regions [16 , 17] . One striking example is the Rose-comb mutation in chickens , in which ectopic expression of a gene relocated by a 7 . 4-Mb inversion causes altered comb morphology and a gene disrupted by the same inversion has been associated to poor sperm motility [18] . Also , in humans , certain inversions mediated by repeats of complex structure seem to predispose to microdeletions that cause genetic disorders in the offspring [10 , 19 , 20] , although in these cases , the disease-causing mutation is the deletion rather than the inversion . Nevertheless , very few cases of position effects have been identified for polymorphic inversions in natural populations [18 , 21] . Inversions represent a special challenge in complex genomes such as that of humans , not only due to their balanced nature , but also because their breakpoints are usually located within highly identical inverted repeated sequences that can reach large sizes ( >100 kb ) . For these reasons , inversions have often been set aside in favor of other structural variants that are easier to detect , like copy number variants ( CNVs ) . In recent years , the use of high-throughput techniques like paired-end mapping [22–24] has allowed the detection of multiple candidate regions to contain inversions in the human genome , but it is necessary to validate them since many represent different types of errors rather than real polymorphic variants [25] . Besides , large projects that try to characterize all human variation like the 1000 Genomes Project ( 1000GP ) [26] might miss many inversions , either because short next-generation sequencing reads and paired-ends are not able to cross long repeats causing inversions [27] , or due to the low coverage and difficulty of mapping reads containing simple breakpoint sequences . So far , only a few polymorphic inversions not directly related to pathological processes have been studied in detail in humans [9 , 28–30] . Some of them have been associated to different expression levels of genes contained within the inverted sequence , such as the polymorphic inversion in chromosome 17q21 that is associated to a decreased MAPT expression , among other expression changes [31] , or the 4 . 5-Mb inversion at 8p23 [29] and the 0 . 45-Mb inversion at chromosome 16p11 [32] , where computationally-predicted inversion alleles correlate with expression levels of several genes . However , we do not know if these expression changes are consequence of position effects caused by the inversion breakpoints or of specific nucleotide changes captured by the inversion . These inversions have also been associated with certain phenotypes , such as recombination , fertility and several neurodegenerative diseases for the 17q21 inversion [9 , 33 , 34] , or asthma and obesity for the 16p11 inversion [32] , but the mechanisms linking the differentially expressed genes in the inverted region to their phenotypic consequences have not been completely elucidated . Other inversions have breakpoints located in positions where effects on adjacent genes would be expected . This is the case of a recently-described 16 . 5-kb polymorphic inversion that disrupts chymotrypsinogen precursor genes CTRB1 and CTRB2 by exchanging their respective first exons [30] , although as both genes belong to the same family , complete copies are reconstructed in the inverted arrangement . In this work , we describe a new polymorphic inversion found at a 4 . 7% frequency in East Asians , which represents one of the few inversions genotyped in several worldwide populations that show a limited geographical distribution . In addition , the inversion disrupts and inactivates a transcription factor gene and generates a new transcript in inverted chromosomes , thus providing mechanisms by which it may be directly affecting phenotype . Finally , we show that these changes are able to generate distinct genome-wide expression patterns and investigate the inversion’s functional and evolutionary impact .
Using available fosmid paired-end mapping data in humans [22] , HsInv0379 inversion was predicted in chromosomal band 19p12 in a region close to the centromere [25] . This inversion was supported by five discordant fosmid clones belonging to a Japanese individual , NA18956 , who also has concordant clones in the same genomic region . The analysis of available partial sequences from fosmid ABC9-45236600J18 insert obtained by 454 shotgun sequencing confirmed the presence of an inversion breakpoint , since these sequences map in two different regions separated by more than 400 kb on the GRCh37 ( HG19 ) reference genome ( Fig 1 ) . Therefore , a fragment of 7 kb including the inversion breakpoint 1 ( BP1 ) was amplified by PCR from the fosmid DNA and analyzed by restriction mapping with several enzymes ( S1 Fig ) , which allowed us to locate the breakpoint within a 1 . 5-kb segment . Primers flanking this region were then used to amplify and sequence a 1 , 894-bp band containing the breakpoint directly from individual NA18956 genomic DNA . The alignment of this sequence in the inverted chromosome ( Inv ) with the reference genome ( Std ) revealed BP1 exact position , defining regions A ( outside the inversion ) and B and C ( inside the inversion ) ( Fig 1 ) . The mapping in the reference genome of sequence C allowed us to locate breakpoint 2 ( BP2 ) and an 850-bp BD PCR product was amplified and sequenced from NA18956 genomic DNA . The analysis of BP1 and BP2 sequences revealed clean breaks with no insertions or deletions that were located at HG19 chr19 positions 21830133–21830134 ( BP1 ) and 22245260–22245261 ( BP2 ) , resulting in a 415-kb inversion ( Fig 1 ) . BP1 falls within the first copy ( 42 . 9-kb long ) of a pair of inverted segmental duplications located 24 . 5 kb apart , although they show only a 91 . 6% identity and present multiple indels that make the mapping of BP1 unequivocal . Both inversion breakpoints are located within blocks of transposable elements ( TEs ) of 14 . 3 kb in BP1 and 4 . 9 kb in BP2 formed by a LINE element with several Alu sequences inserted inside at different positions ( S1 Fig ) . Even though the composition of both blocks is similar , the nucleotide identity between them is very low and the inversion breakpoints occurred within L1 elements of different subfamilies in a direct orientation with respect to each other , which suggests that the inversion was not generated by non-allelic homologous recombination ( NAHR ) . No microhomology was detected at the breakpoints either . Therefore , the most plausible generation mechanism for this inversion is non-homologous end joining ( NHEJ ) . These TE blocks also indicate that the Std chromosome corresponds to the ancestral arrangement because the L1 copies are abruptly interrupted at the breakpoint in the derived Inv sequence ( S1 Fig ) . In addition , the Std arrangement is found in the chimpanzee genome sequence ( PanTro4 assembly ) . To find out its distribution and frequency in different human populations , inversion HsInv0379 has been genotyped using three different strategies ( Table 1 ) . First , 534 individuals from seven human HapMap populations ( CEU and TSI of European origin , YRI and LWK of African origin , and GIH , CHB and JPT of Asian origin; see Table 1 for details ) were genotyped by multiplex PCR across the breakpoints ( Fig 1 and S1 Fig ) . Only five individuals carrying the inversion in heterozygosis were found , all in East Asian populations ( ASN ) , two CHB ( 2 . 2% Inv frequency ) and three JPT ( 3 . 3% Inv frequency ) , and inversion genotypes fit perfectly Hardy-Weinberg equilibrium ( P = 0 . 4636 ) . Second , taking advantage of the fact that many individuals genotyped by PCR had been sequenced in the 1000GP Phase 1 [26] , we searched for SNPs in LD with the inversion . The comparison of the SNP genotypes in the inverted segment plus 20 kb of flanking sequence revealed three tag SNPs ( rs150182828 , rs142395395 and rs148316037 ) with alleles that segregate in complete LD with the inversion ( r2 = 1 ) . For these three SNPs , which span 400 . 8 kb , all Std chromosomes carry the ancestral reference alleles ( Fig 1 ) while the five heterozygote individuals are the only ones with the alternative alleles , also in heterozygosis . Two tag SNPs are located within the inverted sequence in intergenic regions and the third one right outside , in an intron of gene ZNF257 ( Fig 1 ) . The analysis of the recently released SNP calls for 2 , 535 genomes included in 1000GP Phase 3 ( ftp://ftp . 1000genomes . ebi . ac . uk/vol1/ftp/release/20130502/ ) together with the already published 1 , 092 genomes in Phase 1 [26] , and 96 Malay genomes from the Singapore Sequencing Malay Project ( SSMP ) [35] allowed us to identify 56 additional candidate individuals to carry the inversion based on the tag SNPs ( Table 1 and S1 Table ) . All these individuals carry the alternative alleles for the three SNPs except five individuals , which have only two of the alleles , and HG02152 ( CDX ) , that is homozygous for two alternative SNP alleles . The predicted inversion genotypes were confirmed by PCR in six of the new heterozygotes and the Inv homozygote . Interestingly , almost all the potential inversion carriers belong to East Asian populations ( CHB , JPT , CHS , CDX , KHV and Malays ) , but we also identified a Bengali ( BEB ) and a Mexican ( MXL ) individual that are clearly heterozygous for the three tag SNPs ( S1 Table ) . Finally , we performed similarity searches against the reads of 1 , 892 individuals from 19 populations available at the 1000GP ftp site on summer 2013 ( including both mapped and unmapped reads ) using 100-bp sequences spanning the two breakpoints in each arrangement as queries ( S2 Table ) . Reads containing at least one of the inversion breakpoints ( from either Std or Inv orientation ) were retrieved for 482 individuals , with an average of just 3 . 6 reads/individual due to the low coverage of many of these genomes . Of those , Inv chromosomes were detected in 19 of 20 candidate Std/Inv heterozygotes according to the tag SNPs ( the remaining individual having one Std read ) , whereas only reads corresponding to the Std arrangement were recovered from the 462 predicted Std/Std individuals ( S1 Table ) . Std alleles were also detected in nine of the inversion carriers , validating their heterozygote status . In total , we have independent PCR and/or breakpoint-sequence confirmation of the Inv allele for 25 of the 61 individuals ( 41% ) predicted by the tag SNPs to carry the inversion ( 59 unrelated; S1 Table ) . Therefore , we can confidently use these SNPs as proxies to detect Inv chromosomes . Overall , inversion genotypes were determined for 2 , 771 individuals ( 2 , 667 excluding related individuals; Table 1 and S1 Table ) , of which 197 individuals from different populations have been genotyped by the three methods and results are in complete agreement . These genotypes reveal an inversion frequency of 1 . 12% worldwide and of 4 . 73% in East Asia , which ranges from ~2 . 5% in the Northern populations to ~7% in the Southern populations ( being Malays an exception with a frequency of 3 . 65% ) ( Table 1 and Fig 2 ) . The HsInv0379 inverted segment contains three protein-coding genes: ZNF100 , ZNF43 and ZNF208 and at least one long intergenic non-coding RNA ( reported in GENCODE v19 gene annotation ) . A fourth protein-coding gene , ZNF257 , appears to be disrupted by BP2 ( Fig 1 ) . ZNF257 encodes a transcription factor with a Krüppel-associated box ( KRAB ) repressor domain and 13 zinc fingers . This gene has two main transcripts of 3 , 520 and 3 , 641 nucleotides , which are transcribed from the same promoter but differ in the presence of an extra non-coding second exon ( Fig 3 ) . The inversion removes the first two exons as well as the promoter of this gene , which are relocated 415 kb away in the Inv chromosomes . Thus , total ZNF257 expression ( both isoforms included ) was quantified by quantitative PCR ( qPCR ) in lymphoblastoid cell lines ( LCLs ) of 15 Std/Std and 11 Std/Inv individuals from the CHB and JPT populations , plus the Inv/Inv homozygote ( CDX ) . A 2 . 9-fold decrease ( P = 0 . 0047 ) was found in the inversion carriers compared to the homozygote Std individuals and no expression was detected in the Inv/Inv individual ( Fig 3 and S2 Fig ) , indicating that , as expected , this gene is not expressed from the Inv chromosomes . However , five Std/Std individuals showed an extremely low ZNF257 expression , comparable to the levels in inversion carriers ( S2 Fig ) . These individuals are all from the CHB population and most likely carry some regulatory variant in cis or trans that causes a lower expression of ZNF257 not related to the presence of the inversion . In fact , an analysis of Geuvadis RNA-Seq data [36] in LCLs from European and YRI populations ( which include only Std/Std homozygotes ) indicates that ZNF257 is among the top 10% genes with highest variation in expression among those with similar low expression levels ( S3 Fig ) . In addition , several studies including the recent results from the GTEx project [36 , 37] suggest the existence of eQTLs for the gene , with 13 SNPs significantly associated to ZNF257 expression in different tissues , although due to the transformation of the data during the analysis the biological interpretation of the observed effects is not easy . In our data set , each of these SNPs explains 9 . 8–19 . 8% of the variation of ZNF257 expression in Std/Std homozygotes , which contrasts with the 27 . 6% explained by the inversion across all the samples assuming an additive model ( S3 Table ) . Since ZNF257 is a transcription factor that may be controlling the expression of other genes , we searched for genome-wide expression changes associated to the inversion by analyzing the RNA-Seq profiles of LCLs in eight of the previous Std/Std and Std/Inv individuals showing discrepant levels of ZNF257 expression ( see S4 Table for RNA-Seq summary results ) . We detected 56 differentially expressed protein-coding genes and 27 non-coding RNAs ( False Discovery Rate , FDR < 0 . 1 ) , of which 49 were down-regulated and 34 up-regulated , although 60 of them ( 72 . 3% ) have an FDR < 0 . 05 . These genes exhibit moderate to high fold changes ( 1 . 2–8 . 7 ) with the greater variation corresponding to non-coding RNAs ( S5 Table ) , and none of them are located within or close to the inverted sequence . Because only four individuals of each genotype were compared , the results could be confounded by differences between the two groups other than the presence of the inversion . Thus , we repeated the analysis for the 18 possible permutations exchanging two individuals from each genotype class ( S4 Fig ) . The median proportion of genes differentially expressed between the two groups in the permutations was 0 . 17% , which is ~3 times less than those identified between Std/Std and Std/Inv individuals using the same criteria ( 0 . 47% , at a nominal FDR < 0 . 1 ) . Besides , none of the genes identified in the permutations were in the differentially expressed list from the inversion genotype comparison . We also performed 400 simulations of read counts with the mean and dispersion of the real data and searched for differentially expressed genes with FDR < 0 . 1 in each case . Only 5 . 5% of the simulations had a higher number of differentially expressed genes than the comparison of individuals with different inversion genotypes . Next , several enrichment analysis tools ( see Methods ) were used to try to detect functional relationships among the differentially expressed genes , but no statistically significant functional categories have been uncovered based on current knowledge . However , immune response was the most significant biological process gene-ontology category in the DAVID Functional Annotation Tool ( P = 0 . 00091 ) , although significance was lost after correcting for multiple testing . Thus , we selected 11 genes involved in the immune system with different fold-change values and FDRs to validate their expression in the whole set of available LCL RNAs ( 15 Std/Std , 11 Std/Inv and 1 Inv/Inv ) using qPCR . All the genes except one showed good validation when considering only the eight individuals used in the RNA-Seq analysis ( Table 2 ) . In the large sample set , the expression difference was always in the expected direction ( up or down regulated ) except for one gene ( NFATC1 ) , but qPCR validation depended on the gene’s FDR . For FDR < 0 . 05 , significant differences between Std/Std and Std/Inv were obtained for three genes , while the other three were marginally significant ( Table 2 and Fig 3 ) . Of the three genes with FDR = 0 . 05–0 . 10 , only the expression difference of the CACNB2 gene ( FDR = 0 . 077 ) could be validated , while none of the two genes tested with higher FDR showed significant differences . As for ZNF257 , we also see a significant or marginally-significant correlation between the expression levels and inversion genotype ( Std/Std or Std/Inv ) for five genes ( Table 2 ) , in which inversion genotype explains between 10% and 19% of the variation in gene expression . Therefore , there is a clear association between inversion genotypes and gene expression of several genes in trans . In the case of the Inv/Inv sample , it behaves as expected from the expression change observed in heterozygotes in 7 of the 11 genes tested , although since expression levels for any given gene can be affected by many variables , it is difficult to draw reliable conclusions with a single individual . Since we found five Std/Std individuals with low expression levels of ZNF257 mRNA , we have an opportunity to test the relationship between this gene and the detected expression changes . A marginally significant correlation between the ZNF257 expression values and that of the other genes tested by qPCR in the 26 Std/Std or Std/Inv individuals was found for two genes , SNHG5 and BCL11A ( Table 2 ) , which indicates that a low ZNF257 expression level is associated to an increase in the two genes . Accordingly , for these genes the significance of the expression change between Std/Std and Std/Inv is higher when the five Std/Std with low ZNF257 expression are removed from the homozygous Std group ( P = 0 . 0140 and P = 0 . 0096 , respectively ) . Conversely , this does not happen for other genes like CACNB2 , which shows no clear association with ZNF257 , suggesting that these expression changes depend more on inversion genotype than on ZNF257 level . Another important effect of the inversion is that it brings the ZNF257 promoter and first exons to a completely different part of the genome , where they might induce the transcription of new chimeric transcripts . Therefore , we specifically searched for transcripts generated by the ZNF257 promoter around BP1 in Inv chromosomes . By mapping RNA-Seq reads to a construct with the inverted sequence , we detected a spliced fusion transcript formed by the first exon of gene ZNF257 and a completely new 296-bp exon made up of fragments of LINE and Alu elements ( Fig 4 ) . We confirmed the existence of this RNA by amplifying most of it by RT-PCR and by sequencing the exon-exon junction in individual NA18956 . Indeed , both by RT-PCR and qPCR the fusion transcript was found in the 11 inversion carriers analyzed , with 1 . 7-fold higher expression levels in the Inv/Inv individual , while it is not expressed in any of the Std/Std individuals tested ( including three non-East Asian individuals ) ( Fig 4 and S2 Fig ) . The complete new transcript is short , with only 468 bases , and its longest ORF contains only 75 aa . It does not show homology to any other known transcript either . However , according to the RNA-Seq reads mapping to the ZNF257 exon 1 ( common to the two genes ) in inversion heterozygotes that express both transcripts and in Std homozygotes ( Fig 4 ) , the level of expression of the fusion transcript is at least 7 . 4 times higher than that of ZNF257 . Because the inversion tag SNPs are not included in SNP genotyping arrays , the potential functional effects of the inversion have been missed by typical genome-wide association studies . Therefore , based on the lymphoblast transcriptomic results , we made an attempt to associate the inversion allele with general blood-related phenotypic traits by genotyping the inversion tag SNP rs148316037 in 3 , 787 Japanese individuals of the Nagahama cohort [39–41] . The inversion showed a frequency of 1 . 95% in this population with a single homozygote and 146 heterozygotes , which fits perfectly the Hardy-Weinberg equilibrium ( P = 0 . 71 ) . A regression analysis was performed to assess the effects of the inversion on immunological , hematological and metabolic measures from blood samples available for this cohort ( S6 Table ) . However , no significant associations have been detected between HsInv0379 inversion alleles and the phenotypical traits analyzed , including disease indicators for diabetes and cardiovascular or liver disease , as well as alterations in blood cell counts or presence of certain antibodies ( S6 Table ) . Only red blood cell count shows a decrease in inversion carriers ( P = 0 . 036 ) , but this association is lost after multiple testing correction . The presence of tag SNPs and identical breakpoints in the reads of all Inv chromosomes indicate that the inversion was generated only once from the ancestral Std orientation . Thus , to investigate the evolutionary history of the inversion , we first estimated the age of the derived Inv allele . We used in this analysis the unphased Malay population SNP data set from the SSMP [35] because it provides accurate SNP genotypes for 96 individuals based on >30x coverage sequencing . In 381 , 827 bp of the inverted region we identified 30 SNPs that are polymorphic exclusively in the seven Std/Inv heterozygotes ( out of 2 , 005 SNPs without missing values ) . Of these , one corresponds to the tag SNP rs142395395 and four SNPs are found only in three heterozygotes , so they most likely represent variants specific of the Inv chromosomes ( the probability that one such variant belongs to Std chromosomes is P = 0 . 0001 ) . The remaining 25 variants are singletons , and 22 were attributed to the seven Std chromosomes in heterozygotes ( on average there are 3 . 12 singletons/chromosome ) , leaving 3 singletons in Inv chromosomes . Based on this variation , we determined a nucleotide diversity ( π ) of 8 . 86 × 10−4 for Std and 9 . 73 × 10−6 for Inv chromosomes . We used the divergence between the human and chimpanzee genomes ( dH-C = 0 . 0134 ) to establish a local substitution rate for this region . Taking into account this substitution rate and the pairwise divergence between Std and Inv chromosomes ( dS-I = 9 . 95 × 10−4 ) , after subtracting the variation among ancestral Std haplotypes [42] , we estimated the age of the inversion in 43 , 450 years ( 95% confidence interval ( CI ) : 14 , 934–93 , 438 ) or 52 , 140 years ( 95% CI: 17 , 921–112 , 126 ) , assuming a divergence time between human and chimpanzee of 5 or 6 mya , respectively . Next , to understand better the effects of the inversion on the nucleotide variation patterns , we phased the SNPs for a 4-Mb region around the inverted segment in the 286 1000GP Phase 1 East Asian individuals ( 97 CHB , 100 CHS and 89 JPT ) [26] to infer Std and Inv haplotypes . In this case , there are two main challenges for SNP phasing . First , the inversion has a low frequency and there are no Inv/Inv homozygotes in the 1000GP Phase 1 dataset from where to recognize SNP variants present exclusively in the derived arrangement ( which are always found in Std/Inv individuals and are difficult to place in one of the chromosomes unequivocally ) . Second , inversion length increases the possibility of phasing errors [43] . To minimize these effects , we used the BEAGLE software [44] to filter and call the SNP genotypes based on their likelihoods in each individual , and then to phase the different variants ( see Methods for details ) . A total of 15 , 799 high-quality SNPs in 570 phased haplotypes ( excluding the two chromosomes of one heterozygote individual , in which a phasing error between inversion breakpoints was detected ) were finally included in posterior analyses . These haplotypes were used to estimate the proportion of each chromosome that belongs to a number K of hypothetical ancestral populations with the software STRUCTURE [45] . Notably , the Inv arrangement shows a single component even when a high number of ancestry components ( K = 10 ) is considered ( S5 Fig ) . At the well-supported value of K = 5 , the proportion of the Inv component in Std chromosomes is 12 . 9% in JPT , 6 . 3% in CHB and 10 . 5% in CHS , which suggests that Inv haplotypes are similarly related to any group of Std chromosomes and probably appeared before the establishment of the different East Asian populations , as the estimated age suggests . In addition , this highlights the highly homogeneous composition of Inv haplotypes due to its relatively recent and unique origin as well as the lack of gene flow between arrangements . Similar results were obtained by building an haplotype network , in which all the haplotypes with the inversion form a closely related and monophyletic group ( S5 Fig ) . Although phasing and SNP imputation errors might affect nucleotide variation estimates , we have also examined the global variation patterns of π and Tajima's D statistic [46] along and beyond the inverted region in the 1000GP Phase 1 dataset ( Fig 5 ) . Consistent with the age estimates , there are low levels of nucleotide diversity and negative values of Tajima's D within the inverted haplotypes , which extend outside the breakpoints . We then tried to determine the effects of the inversion on recombination by inferring population-scaled recombination rates ( 4Ner/kb ) between each pair of consecutive SNPs in the 24 Inv and 24 randomly sampled Std phased chromosomes from the three East Asian populations . As expected since most Inv chromosomes are found in heterozygotes , there is a marked reduction in recombination within the inverted segment ( Fig 5 ) , which shows a genetic length of 83 4Ner units in Std East Asian chromosomes and only 5 in Inv . Accordingly , the distribution of Fst values between SNPs in Std and Inv chromosomes shows increased differentiation within the inverted region , which is maximal at the breakpoints ( Fig 5 ) . This reduction of recombination in heterozygotes is apparent even taking into account that the phased chromosomes used in this analysis can include a higher proportion of shared variants due to the phasing problems explained above . In fact , in the high-coverage SSMP data only two SNPs with enough read support were found to be shared between arrangements and were likely generated by gene conversion . Finally , we looked for evidences of natural selection acting on this inversion with two approaches . First , we searched for recent partial selective sweeps in this region by applying the integrated haplotype score ( iHS ) test [47] to the 5 , 890 SNPs with available ancestral state information ( 37 . 3% of the phased SNPs ) . Although this test may be affected by recombination inhibition , no significant signals of recent positive selection were detected for the proximal ( P = 0 . 67 ) or distal ( P = 0 . 83 ) breakpoints or any SNPs in high LD with the inversion . Second , we used forward-in-time simulations to compare the observed frequency of the inversion with that expected under a human demographic model [48 , 49] and different evolutionary scenarios ( Fig 6 ) . Population-scaled selection coefficient ( Nes ) values corresponding to positive ( +10 and +5 ) and purifying selection ( -5 , -10 , -15 , -20 , -25 and -30 ) acting on a mutation of ~43 , 450 years were considered , together with a neutral change ( Nes = 0 ) . The results show that the probabilities to observe the actual frequencies ( 2 . 4–8% ) in positive selection simulations are lower than those from a neutral mutation ( Fig 6 ) . On the other hand , these probabilities are higher with increasingly negative selection coefficients ( Fig 6 ) , which suggests that the inversion could be evolving under purifying selection and therefore that it may have negative consequences for its carriers . However , the likelihoods of negative selection coefficients are not significantly different from that of a neutral allele according to the log-likelihood ratio test , and the possibility that the inversion is neutral cannot be ruled out .
Procedures that involved the use of human samples were approved by the Animal and Human Experimentation Ethics Committee ( CEEAH ) of the Universitat Autònoma de Barcelona ( Ref . 821H ) . Protocols for the Nagahama cohort project were approved by the Kyoto University Graduate School and Faculty of Medicine Ethics Committee ( Ref . G278 ) and written informed consent was obtained from all of the participants .
A total of 547 samples from eight populations of HapMap and 1000GP [26 , 73] projects have been used ( see Table 1 for details ) . Ninety unrelated individuals were analyzed in each of these populations except for CHB ( 49 ) and JPT ( 47 ) plus a single CDX individual , and the CEU and YRI populations , which are organized in 30 parent-children trios . Genomic DNAs were obtained from Coriell Cell Repository ( Camden , NJ , USA ) , except most of those from the CEU population and those of the samples used for the expression analysis , which were isolated from LCLs ( Coriell Cell Repository , Camden , NJ , USA ) as previously described [74] or using the PrepFiler Forensic DNA Extraction kit ( Life Technologies ) . Fosmid ABC9-45236600J18 was obtained from Evan E . Eichler ( University of Washington , WA , Seattle ) and DNA was isolated from 1 . 5 ml of overnight bacterial TB culture following a typical alkaline lysis plasmid DNA extraction protocol [75] . For inversion genotyping , one primer in region C within the inverted segment was used in combination with primers in regions A and D outside the inversion ( S7 Table ) to generate products AC ( Inv ) and/or CD ( Std ) . PCR amplifications were performed in a reaction volume of 25 μl including 1x buffer , 1 . 5 mM MgCl2 , 200 μM each dNTP , 0 . 4 μM each primer , 1 . 5 U Taq DNA polymerase ( Roche ) and 50–100 ng genomic DNA . Typical cycling conditions were 2 min at 94°C of denaturation followed by 35 cycles of 30 sec at 94°C , 30 sec at 60–65°C and 30–60 sec at 72°C , and a final step of 7 min at 72°C . In long-range PCRs , the same reaction conditions were used except for 240 μM each dNTP , 2 . 5 U Pfu Turbo DNA Polymerase ( Stratagene ) and 1–10 ng of fosmid DNA , together with cycling steps of denaturation at 95°C and extension at 68°C for 9 min . For RT-PCR , total RNA from 27 East Asian LCLs ( Coriell Cell Repository , Camden , NJ , USA ) was isolated using Trizol ( Life Technologies ) and cDNA synthesis was carried out after DNase treatment ( DNA-free , Ambion ) using SuperScript First Strand Synthesis System for RT-PCR ( Invitrogen ) from 1 μg total RNA with a combination of oligodT and random primers . Controls without retrotranscriptase were performed for all samples to exclude DNA contamination . RT-PCR reactions were carried out in the same conditions described above with 1 μl of cDNA as template . When needed , PCR products were sequenced by the Sanger method at Macrogen ( Seoul , Korea ) . Total RNA was isolated from 15-ml cell cultures of eight East Asian LCLs collected before reaching saturation ( 4 . 5–8 . 6 × 106 cells ) , using miRNeasy Mini kit with on-column DNase digestion ( Qiagen ) . RNA quality and quantity were measured by absorbance with Nanodrop ( Thermo Scientific ) , fluorescence on a Qubit instrument ( Life Technologies ) and 2100 Bioanalyzer ( Agilent Technologies ) . TruSeq cDNA libraries ( Illumina ) were prepared from 500 ng total RNA with polyA capture , and 2 × 100 bp paired-end sequencing was performed on the Illumina HiSeq 2000 platform at Beckman Coulter Genomics ( Danvers , MA , USA ) . A total of 413 million single reads were produced ( 51 . 7 million per sample on average; S4 Table ) . We mapped fastq files of each sample against the GRCh37 ( H19 ) human genome with TopHat2 ( default parameters ) , adding the Ensembl release 73 ( Gencode v18 ) gene annotation to guide the alignments , and HTSeq [76] was ran to count the number of reads for each gene based on the same gene annotation . To detect differentially expressed genes , we applied DESeq2 [77] and selected genes with FDR < 0 . 1 . Protein coding genes and non-coding genes were analyzed separately . Permutations and simulations were carried out as detailed in S4 Fig . Functional relationships among differentially expressed genes ( FDR < 0 . 05 ) were analyzed with the DAVID Functional Annotation tool [78] . Chimeric transcripts originated across the inversion breakpoints were detected with the IdeGen pipeline [79] using the gene annotation file ( Ensembl 73 , Gencode v18 ) , inverted region sequence in GenBank format , human genome sequence ( HG19 ) and the DESeq2 normalized fastq files for each sample . The sequence of the inverted region was created in silico by inverting the segment between breakpoints and adding 1 Mb of flanking region at each side . In quantitative real-time RT-PCR , 20-μl reactions were carried out in an ABI Prism 7500 Real-Time PCR System ( Applied Biosystems ) with iTaq SYBR Green Supermix with Rox ( Bio-Rad ) , 75–125 nM of each primer ( S7 Table ) and 1 μl of a 1/10 dilution of the cDNA sample ( except for gene ZNF257 that was amplified from 0 . 5 μl of undiluted cDNA due to its low expression levels ) . An independent RNA sample isolated from a different cell culture was used for those individuals previously analyzed by RNA-Seq . All samples were measured in triplicate by relative quantification with a standard curve and a final dissociation curve stage . Genes POLR2F and ACTB were amplified as reference genes to control for differences in cDNA concentration . Mean expression values for each genotype group ( Std/Std vs . Std/Inv ) were compared with a Student’s t-test . To search the Std and Inv sequences at inversion HsInv0379 breakpoints among the individuals sequenced by the 1000GP [26] , we prepared a fasta file with the 100 bases surrounding the two breakpoints ( S2 Table ) . If the 1000GP reads had already been aligned to the reference genome , only unmapped reads and reads mapped to the breakpoint regions were downloaded from the ftp server in SAM format with SAMtools [80] , and then converted to fastq . Otherwise , the raw fastq files were downloaded , avoiding color-space sequences and exome reads . The reads were processed with a slightly modified version of BreakSeq [52] as described previously [81] . Reads overlapping at least 10 bases of either side of a breakpoint were retained ( regardless of their length ) , and only those mapping uniquely to an Inv or Std breakpoint with no other hits in the reference genome were counted as allele observations . A total of 1 , 892 individuals from the 1000GP [26] were analyzed sequentially between January and August 2013 . For inversion genotyping with the three tag SNPs , SNP calls were obtained from the 1000GP Phase 3 vcf files ( 20130502 release ) . For those individuals with alternative alleles , allele count was checked using mpileup function of SAMtools v 0 . 1 . 19 [80] with default parameters ( minimum base quality Q = 13 ) . LD between the inversion and SNPs in the inverted region plus 20 kb of flanking sequence at each side from the 1000GP Phase 1 SNP data [26] was calculated with Haploview v4 . 1 [82] ( both for each population separately and the seven HapMap populations together ) , using unrelated individuals for which the inversion had been genotyped by PCR . Only SNPs in perfect LD with the inversion ( r2 = 1 ) were considered tag SNPs . Next , haplotypes were inferred using BEAGLE package v3 . 3 . 2 [44] from 1000GP Phase 1 SNP data [26] in the inverted region and 1 . 8 Mb of flanking sequence at each side for 286 East Asian individuals . Both inversion breakpoints were included in their corresponding genomic positions as extra variants with two alleles ( Std and Inv ) to assess the presence of switch errors in phasing . Two different phasing strategies were used . The first phasing run was carried out with default ( fast ) parameters including all 1000GP SNPs but using genotype likelihoods to call SNP genotypes . The second one was aimed to increase accuracy by excluding all markers with allelic R2 < 0 . 9 in the first run ( larger values of allelic R2 indicate more accurate genotype imputation ) , and increasing to 20 both the number of iterations of the phasing algorithm and the number of sampled haplotype pairs for each individual during each iteration . In the accurate phasing , a switch error between breakpoints was detected in only one inversion carrier ( compared to only two inverted chromosomes correctly retrieved using the first phasing run ) . To determine the genetic substructure within the inverted region and the likely number of ancestral population groups ( K ) of the 570 phased East Asian chromosomes , we used a Bayesian genetic clustering algorithm ( STRUCTURE v2 . 3 ) [45] . We assumed the admixture model and ran 100 , 000 Markov chain Monte Carlo iterations with a burn-in period of 100 , 000 . We also ran STRUCTURE assuming the linkage model , and we obtained equivalent results . We did not use prior population information and K values between 1 and 10 were tested to estimate their posterior probability . Estimates of recombination rate were obtained using the rhomap program distributed within the LDHat package v2 . 2 [83] and the same strategy used in Alves et al . 2014 [84] . For each pair of adjacent SNPs we obtained five estimates of the population recombination rate ( p = 4Ner/kb ) and the median was used in the analysis . Recombination was estimated separately in a random sample of 24 Std phased chromosomes and the 24 phased Inv chromosomes . π [85] and Tajima's D [46] statistics were estimated at non-overlapping windows of 80 SNPs . The alteration of the site frequency spectrum produced by the phasing algorithm has a minor effect on recombination rate estimates or population structure inference , but it could have a big effect on polymorphism level estimates . Thus , the Tajima's D distribution was Z-transformed and centered at 0 to try to correct for the systematic overestimation caused by the preferential filtering of low frequency variants during the phasing procedure . A divergence-based estimate of the inversion age [42] was calculated using high-coverage SNP data from the SSMP [35] . Nucleotide variation was analyzed in the inverted region ( chr19: 22245260–21863433 ) , excluding the segmental duplication copy at BP1 ( chr19:22245260–21863433 ) , which shows an increased nucleotide diversity that may alter final results ( Fig 5 ) , and 2 . 3% of SNPs with missing values for some individuals . We assumed that variants in heterozygotes found also in Std homozygotes belonged to the Std chromosome , while those variants found exclusively in more than one heterozygote had appeared in Inv chromosomes . A proportion of the singletons found in heterozygotes were assigned to Std chromosomes based on the observed singleton frequency in Std homozygotes , and the rest were attributed to Inv chromosomes . We calculated the net pairwise nucleotide differences between orientations ( dA ) by subtracting nucleotide diversity observed in Std sequences ( πS ) to the total nucleotide differences between Std and Inv sequences ( dS-I ) ( equations 10 . 20 , 10 . 21 and 10 . 22 in Nei 1987 [85] ) . The divergence time between Std and Inv chromosomes was estimated with the formula T = dA/2s ( where T is time and s is the local substitution rate ) . The 95% confidence intervals for age estimates were obtained with 1 , 000 bootstrap resamplings of 96 individuals . The local substitution rate was estimated with the same formulas as before using chimpanzee as outgroup and assuming a divergence time with humans of 5–6 Mya . Alignment between human ( HG19 ) and chimpanzee reference genomes ( panTro4/CHIMP2 . 1 . 4 ) was retrieved from Ensembl database . The integrated haplotype score ( iHS ) test [47] was performed on those SNPs located within the inverted region ± 1 . 8 Mb with known ancestral state ( 5 , 890 SNPs ) . To determine if the inversion itself is undergoing positive selection we compared the standardized iHS value for the breakpoints to the overall iHS distribution . To further check the role of linked selection on inversion current frequency , LD with the inversion was calculated for the list of SNPs with significant iHS values ( P < 0 . 05 ) . The expected frequency distribution of hypothetical mutations with different selective effects that appeared ~43 , 450 ya under the human demographic history inferred by Gravel et al . 2011 [48] was estimated by forward-in-time simulations . The demographic history included an ancient African expansion ( ~177 , 000 ya ) , an out-of-Africa bottleneck ( ~62 , 000 ya ) , a founding of Asia bottleneck ( ~28 , 000 ya ) , an initial phase of exponential growth within Asia , and a recent explosive growth phase ( starting ~5 , 000 ya ) . All simulations were performed using SFS_CODE [86] and the same parameters as in Maher et al . 2012 [87] were used except for the founding-of-Asia bottleneck which is more severe . Simulations consisted in 106 iterations of a gene with length 1 bp , initial population of 2 , 000 diploid individuals , random mating between males and females , without mutation in each generation , and sampling at the end 96 diploid individuals ( from the terminal population size of 150 , 408 individuals ) to calculate allele frequency . All extinct or fixed iterations were discarded and only the first 1 , 000 iterations still segregating were kept for analysis . Years were converted to generations by rescaling to the ancestral population size of 7 , 310 [48] and assuming 30 years per generation . The command line for SFS_CODE used here is "sfs_code 1 1000000-A-n 96-N 2000-P 2-t 0-L 1 2-I-r 0-W 0-Td 0 1 . 9800273598-Td 0 . 2211582307 0 . 1285753765-Tg 0 . 28499772 44 . 75089-Td 0 . 28499772 0 . 2976894143-Tg 0 . 3260373917 282 . 7192-TE 0 . 3374373005—mutation 0 . 238372093 S 0 G <selection coefficient>" . Parameter likelihood was estimated as the probability to find the 2 . 4–8% observed frequency values in East Asian populations in each simulated scenario and selection coefficients were compared to the neutral model ( Nes = 0 ) using a likelihood ratio test . Inversion tag SNP rs148316037 was genotyped by TaqMan assay ( Applied Biosystems ) ( S7 Table ) from 5–10 ng of DNA of 3 , 824 Japanese subjects from the Nagahama Prospective Genome Cohort for Comprehensive Human Bioscience ( The Nagahama Study ) , a community-based prospective multi-omics cohort study conducted by Kyoto University in Japan [39] . Complete linkage between the inversion and rs148316037 in this cohort was confirmed by genotyping the inversion by PCR in a total of 56 individuals ( 33 Std/Std , 22 Std/Inv and 1 Inv/Inv ) . We performed quantitative linear regression and logistic linear regression to analyze the associations between genotypes of rs148316037 tag SNP as a proxy for the inversion and clinical phenotypes ( S6 Table ) . The quantitative traits were transformed by rank-based inverse normalization method to fit normality and used as dependent variables in the linear regression analyses . Age and sex were used as covariates . All the data described here have been deposited at the InvFEST Human Polymorphic Inversion Database ( http://invfestdb . uab . cat/report . php ? n=HsInv0379 ) . DNA sequences have been deposited at GenBank ( accession numbers KT592300-KT592304 ) . RNA-Seq data are available at the Sequence Read Archive ( SRA290330 ) . | Since the discovery of chromosomal inversions almost 100 years ago , how they are maintained in natural populations has been a highly debated issue . One of the hypotheses is that inversion breakpoints could affect genes and modify gene expression levels , although evidence of this came only from laboratory mutants . In humans , a few inversions have been shown to associate with expression differences , but in all cases the molecular causes have remained elusive . Here , we have carried out a complete characterization of a new human polymorphic inversion and determined that it is specific to East Asian populations . In addition , we demonstrate that it disrupts the ZNF257 gene and , through the translocation of the first exon and regulatory sequences , creates a previously nonexistent fusion transcript , which together are associated to expression changes in several other genes . Finally , we investigate the potential evolutionary and phenotypic consequences of the inversion , and suggest that it is probably deleterious . This is therefore the first example of a natural polymorphic inversion that has position effects and creates a new chimeric gene , contributing to answer an old question in evolutionary biology . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2015 | Functional Impact and Evolution of a Novel Human Polymorphic Inversion That Disrupts a Gene and Creates a Fusion Transcript |
Thermotolerance is an essential attribute for pathogenesis of Cryptococcus as exemplified by the fact that only two species in the genus , which can grow at 37°C , are human pathogens . Species which have other virulence factors including capsule formation and melanisation , but lack the ability to propagate at 37°C are not pathogenic . In another related fungal pathogen , Candida albicans , heat shock protein 90 has been implicated to be a central player in commanding pathogenicity by governing yeast to hyphal transition and drug resistance . Exploring Hsp90 biology in Cryptococcus in context of thermotolerance may thus highlight important regulatory principles of virulence and open new therapeutic avenues . Hsp90 is involved in regulating thermotolerance in Cryptococcus as indicated by growth hypersensitivity at 37°C upon mild compromise of Hsp90 function relative to 25°C . Biochemical studies revealed a more potent inhibition of ATPase activity by pharmacological inhibitor 17-AAG at 37°C as compared to 25°C . Catalytic efficiency of the protein at 37°C was found to be 6 . 39×10−5μM-1 . Furthermore , indirect immunofluorescence analysis using a specific antibody revealed cell surface localization of Hsp90 via ER Golgi classical secretory pathway . Hsp90 was found to be induced under capsule inducing conditions and Hsp90 inhibition led to decrease in capsular volume . Finally compromising Hsp90 function improved anidulafungin tolerance in Cryptococcus . Our findings highlight that Hsp90 regulates pathogenicity of the fungus by myriad ways . Firstly , it is involved in mediating thermotolerance which implies targeting Hsp90 can abrogate thermotolerance and hence growth of the fungus . Secondly , this study provides the first report of biochemical properties of Hsp90 of a pathogenic fungus . Finally , since Hsp90 is localised at the cell wall , targeting cell surface Hsp90 can represent a novel strategy to combat this lethal infection .
All living cells are endowed with a heat shock response machinery which plays a protective role against stress . This machinery is inducible under heat shock and it provides cells the capacity to effectively withstand sub lethal temperatures and tolerance to many other stresses . This phenomenon has been shown to be exploited by pathogens wherein quick adaptation to divergent host environment is essential to establish a successful infection . Various classes of heat shock proteins such as Hsp60 , Hsp70 and Hsp90 have been implicated to be involved in propagation of parasitic virulence . For instance , Hsp90 acts as a thermosensor in the malaria parasite wherein temperature stress is perceived as a cue for transition from one development stage to another [1] . In Entamoeba and Giardia , Hsp90 regulates the process of encystation [2 , 3] . Numerous observations have linked heat shock response with the pathogenic potential of fungi [4] . Hsp90 , an essential molecular chaperone [1 , 3 , 5 , 6] , has been shown to govern various aspects of C . albicans pathogenicity determinants including morphological yeast to hyphal transition [7] , emergence of drug resistance [8–10] and biofilm formation [11] . Using genetic screens , it was shown that Hsp90 regulates thermal adaptation in C . albicans by downregulating Hsf1 [12] . Interestingly , in C . albicans , a 47kDa C terminal fragment of Hsp90 was shown to be present on the cell wall [13 , 14] and antibodies targeting the exposed Hsp90 were shown to inhibit infection [15] . In Aspergillus fumigatus , the role of Hsp90 in drug resistance [16] , conidiation and maintenance of cell wall integrity has been well established [17] . In Cryptococcus , Hsp90 has been recently shown to be crucial for growth of the fungi and Hsp90 inhibitor radicicol has synergistic action with azoles [18] . The fungal kingdom comprises over 1 . 5 million known species present ubiquitously in the environment , most of which are either free living saprobes or commensals . In contrast to the large number of protozoa and viruses capable of infecting humans , there are only a few fungi which are human pathogens . Common leading systemic fungal pathogens include Candida , Pneumocystis , Histoplasma , Aspergillus , Cryptococcus , Mucor , Rhizopus and Coccidioidomyces [19 , 20] . This is intriguing owing to the enormous diversity and the ubiquitous nature of the fungal kingdom . It is also noteworthy to highlight that most of the fungal infections are either restricted to the immunocompromised state of the host or may result from an accidental breach of the anatomical barriers . Furthermore , the advent of antibiotic therapies in the 1960s have also paved the way for fungal infections . Nonetheless upon summarizing the lessons learned from pathogenic and non-pathogenic fungi , we arrive at the conclusion that high body temperature in mammals and birds provide an innate physical barrier to the vast inoculum of ubiquitous fungal spores . Therefore , the ability to successfully survive at the physiological temperature of 37°C seems to be the utmost requirement in order to be pathogenic to humans . The best example which underpins the importance of thermotolerance for virulence is seen in the genus Cryptococcus which comprises over 37 species , most of which are environmental and non-pathogenic to humans . Only two are human pathogens by virtue of their abilities to grow at 37°C implicating the importance of thermotolerance for pathogenesis [21 , 22] . Non-pathogenic species of Cryptococcus such as C . podzolicus are equipped with the other critical pathogenicity armours including capsule formation and melanisation , however they lack the ability to propagate at 37°C [23] , indicating thermotolerance is the fundamental requirement for pathogenicity . However , the mechanism of growth at elevated temperature with respect to heat shock response has long been enigmatic . In this study , we have tried to investigate the role of Hsp90 in thermotolerance of the fungus C . neoformans . We find that C . neoformans critically depends on Hsp90 machinery for survival at 37°C as indicated by hypersensitivity to Hsp90 inhibition at 37°C ( human body temperature ) as compared to 25°C ( environmental temperature ) . Also , we have investigated Hsp90 mediated thermotolerance at the biochemical level by characterization of ATPase activity and its inhibition by pharmacological inhibitor . Hsp90 was found to be upregulated under capsule inducing conditions , and immunofluorescence analysis showed that Hsp90 is localized on the fungal cell surface . We also find that Hsp90 governs critical aspects of capsule regulation including capsule formation and maintenance around the cell wall . Furthermore , Hsp90 inhibition compromises intrinsic resistance of Cryptococcus to echinocandins–the only class of antifungals which targets the fungal cell wall . In all , our study establishes the involvement of Hsp90 in thermotolerance , cell wall integrity and capsulation processes in C . neoformans which are the most essential virulence determinants of the pathogenic fungus .
C . neoformans strain MTCC 1353 and clinical isolate was a kind gift from Dr . R Ravikumar , NIMHANS , Bangalore , India . All isolates were maintained at −80°C in 25% glycerol . Isolates were grown in either YPD ( 1% yeast extract , 2% bactopeptone , 2% glucose ) or Sabouraud Dextrose broth unless otherwise stated . 2% agar was added for solid media . Susceptibility to drugs was determined in flat bottom , 96-well microtiter plates using broth microdilution protocol . Minimum inhibitory concentration ( MIC ) tests were set up in a total volume of 0 . 2 ml/well with 2-fold dilutions of radicicol ( RAD ) and anidulafungin ( AF ) . RAD gradients were typically from 5nM to 50μM with the following concentration steps in nM: 5 , 50 , 500 , 1000 , 5000 , 10000 , 20000 , 30000 and 50000 . AF gradients were used in the following concentration steps in μg/ml were: 32 , 16 , 8 , 4 , 2 , 1 , 0 . 5 , 0 . 25 . Cell densities of overnight cultures were determined by haemocytometer and dilutions were prepared such that ∼103 cells were inoculated into each well . Plates were inoculated at the indicated temperatures . MIC50 was defined as the concentration of drug reducing growth by 50% relative to the wells containing no drug . Dimethyl sulfoxide ( DMSO ) was the vehicle control for radicicol ( RAD ) and Anidulafungin ( AF ) . Absorbance was determined spectrophotometrically at 600 nm and was corrected for background from the corresponding medium . All drugs were purchased from Sigma Aldrich . To determine nature of interaction between Hsp90 inhibitor RAD and AF , we calculated the fractional inhibitory concentration by the following formula: ∑FICs = ( MIC50 of AF in combination/ MIC50 of AF alone ) + ( MIC50 of RAD in combination/ MIC50 of RAD alone ) . ∑FIC values <0 . 5 indicates substantial synergism and 0 . 5–1 . 25 indicates an additive interaction . Five-fold dilutions of cells ( from ∼1×106 cells/ml ) were spotted onto SD agar media after growth assays as indicated and incubated at the indicated temperatures . Plates were photographed after 2–3 days . C . neoformans cells grown till mid log phase were collected by centrifugation and the pellet was washed three times with ice cold PBS . The cells were lysed using ice cold lysis buffer containing 50 mM Tris ( pH 7 . 4 ) , 1% Triton X 100 containing 1 mM EDTA with an equal volume of 1-mm-diameter glass beads by multiple rounds of vortexing ( BioSpecProducts , Inc . , Bartlesville , OK ) . After disruption , the samples were centrifuged at 20 , 000 g for 15 min at 4°C to remove the glass beads , unbroken cells , and particulate debris from the homogenate . After centrifugation , the soluble protein fraction was collected , the protein content was measured by the Bradford assay . The proteins were stored at—80 . 0°C for further analysis . Protein samples were mixed with one-fifth volume of 6× Laemelii buffer , boiled for 5 minutes , and resolved on a 10% SDS-PAGE gel . Protein was blotted onto PVDF membrane and blocked with 5% skim milk in tris buffered saline with 0 . 1% tween . Antibodies were used in the following dilutions: Anti CnHsp90 antibody ( 1:5000 ) , Anti PGK antibody ( 1:5000 ) , Anti tubulin antibody ( 1:2000 ) . Exponential phase cells were harvested and washed thrice with sterile PBS and resuspended in 10 mM phosphate buffer ( PBS ) ( pH 7 . 4 containing 1% ( v/v ) , βME at 25°C and 37°C . After 1h treatment , the cells were spun and the supernatant fluid was concentrated and suspended in Laemelli buffer followed by immunoblot analysis as described above . Total RNA was isolated from yeast culture using the standard Trizol method and cDNA was prepared by RT PCR . Cn Hsp90 was amplified from C . neoformans cDNA using the following primers: 5’ CCCCCGGATCCATGTCCACCGAGACCTTTGG ( forward primer ) and 5’ CCCCCCGAATTCTTAGTCAACCTCCTCCATGGAG ( reverse primer ) . Amplified product of 2157 bp was cloned in pRSET-A vector as a 6x-His tag fusion protein and transformed into competent E . coli DH5α cells . Confirmation of positive clones was done upon insert release by restriction digestion . For purification , His-tagged Cn Hsp90 was expressed in E . coli p LysS strain . Cells were grown at 37 °C till the optical density at 600 nm reached 0 . 6 . Induction was done with 0 . 5mM IPTG at 16 °C . Ni-NTA column was used to purify CnHsp90 to homogeneity . Fluorescence measurements were carried out in a Perkin Elmer fluorescence spectrophotometer as reported previously [6] . 20 μg of CnHsp90 was incubated with varying concentrations of ATP ( 100μM-3000μM ) in binding buffer ( 40 mM HEPES-KOH buffer pH 7 . 4 , 5 mM MgCl2 and 100 mM KCl ) and tryptophan fluorescence was measured by scanning the emission spectrum in the wavelength range of 300–400 nm at excitation at 280 nm . The intensity at λmax 340 nm was selected for calculations . Difference in intrinsic fluorescence of protein alone and in presence of ligand was plotted against ligand concentration . Binding curve was analyzed using GraphPad Prism 5 . 0 software using non-linear regression analysis with single site-specific binding . Similarly , determination of 17-AAG binding was performed by incubating 20 μg protein in binding buffer ( 50 mM Tris and 1 mM EDTA ) with varying concentrations of 17-AAG ( 500 nM– 70 μM ) . The final concentration of DMSO in the assay was 1% . 1 . 5 μM of CnHsp90 was incubated with varying concentrations of ATP ( 50 to 4000 μM ) as previously described [24] . The assay buffer contained 40 mM Tris Cl buffer , pH 7 . 4 , 100 mM KCl , 5 mM MgCl2 . [γ32P] ATP of specific activity of 0 . 55 Ci/mmole was used as a tracer . The reaction mixture was incubated at 25°C and 37°C for 1 hour . Thin layer chromatography was performed on polyethyleneimine-cellulose sheets ( Merck ) wherein the mobile phase contained 0 . 5M LiCl , 0 . 5mM EDTA and 2N formic acid . To rule out nonspecific ATPase activity due to copurifying proteins , 300 μM of Hsp90 inhibitor 17-AAG was used as control . The TLC sheets were dried and analyzed by phosphor imaging . The spots corresponding to phosphate and ATP were quantitated using Image Quant software ( Fujifilm ) . Final Hsp90 ATPase activity was calculated by subtracting the activity in the presence of 17-AAG from the total ATPase activity . Data was analyzed using GraphPad Prism 5 . 0 software using Michaelis-Menten kinetics . For ATPase inhibition assay , purified CnHsp90 was incubated with a saturating concentration of ATP ( 2 mM ) and 17-AAG concentration was varied from 2 . 5 μM to 150 μM . 300 μM 17-AAG was used in control reaction . Percentage residual ATPase activity was plotted against log of concentration of inhibitor and the result was analyzed using GraphPad Prism 5 . 0 as described above . ELISA was performed with intact yeast cells to confirm surface association of Hsp90 in C . neoformans as described previously [25] . Briefly , 5×105 live yeast cells/well were incubated in 96-well polystyrene plates ( Costar 9018; Corning Inc . , New York , USA ) for 2 h at 25°C and 37°C in PBS . Unattached yeast cells were removed by washing with PBS . Blocking was done for 1 h using 2% BSA ( Sigma–Aldrich ) in PBS supplemented with 0 . 05% Tween-20 . The plates were washed three times with 0 . 1% Tween-20 in PBS and incubated with anti-CnHsp90 antibody that was serially diluted as indicated in the blocking solution . After 1 h incubation , the plates were washed and incubated with peroxidase-labeled anti-rabbit IgG ( Sigma–Aldrich ) and incubated for 1 h . Serologic reactions were measured by the addition of TMB ( Invitrogen ) and determined by OD measurements at 450 nm . Polyclonal antiserum against PGK raised in rabbit was used as a negative control . No antibody and no antigen controls were also used as negative controls . Yeast cells were grown to log phase and washed with PBS . Vesicle trafficking inhibitors included BFA and NEM at concentrations previously used in similar studies [26] . A single colony on solid YPD medium was cultured overnight in liquid YPD medium . Cells were washed with PBS and 106 cells were added into 3 ml of liquid YPD containing vesicle trafficking inhibitors BFA ( 25μg/ml ) and NEM ( 500μM ) and further cultured in a shaking incubator at 25 °C and 37°C . Cells were then fixed with paraformaldehyde for 30 mins . Blocking was done with 3% BSA in phosphate-buffered saline for 1 h . Primary antibodies against CnHsp90 was diluted in phosphate-buffered saline and incubated for 2 h . Following three washes with PBS , sample was incubated with fluorescein isothiocyanate-conjugated anti-rabbit secondary antibody . Three washes were given to the coverslips maintaining gentle agitation . The coverslips were mounted on glass slides with 90% glycerol containing 2% DABCO and Calcaflour white and visualized under a confocal laser scanning microscope ( Leica TCS SP8 ) . For cell surface association studies , it should be noted that permeabilization step was not carried out . A single colony from solid YPD medium for each strain was cultured overnight at 37 °C in liquid YPD medium . For capsule induction , 106 cells were added into 3 ml of capsule inducing medium ( 10% fetal bovine serum in PBS ) and further incubated at 37 °C for 12 hours with shaking . Capsular staining was done by India ink and examined by Zeiss microscope . Hsp90 inhibitors RAD ( 0 . 5μM ) was added either initially in the capsule inducing medium or after 12 hours of induction . Cell viability was examined by Trypan blue dye exclusion method to rule out cell death due to RAD treatment . To calculate the capsule volume , the diameters of the whole cell ( Dw ) and the cell body ( Dc ) were measured with Zeiss Zenlite software . Capsule volume was defined as the difference between the volume of the whole cell ( yeast cell plus capsule ) and the volume of the cell body ( no capsule ) as previously described [27] . Following equation was used: volume of a sphere as 4/3 × π × ( D/2 ) 3 . 40 cells were measured for each experiment on at least three separate occasions . All results were reported as Mean ± S . E . M . Grouped data was statistically analyzed using one-way ANOVA . Two-tailed P-test was used for paired comparisons . All analysis was done using GraphPad Prism 5 . 0 .
The first and foremost criterion for a pathogen to establish infection in any host is its ability to survive and propagate successfully at the physiological temperature of the host . To probe the role of Hsp90 in regulating growth at different temperatures , we tested the effect of Hsp90 inhibitor Radicicol ( RAD ) on the growth of C . neoformans at both 25°C and 37°C . MIC50 ( minimum inhibitory concentration ) for RAD treatment was observed to be 15 . 67 μM when cells were grown at 25°C . However , at 37°C , there was almost a tenfold reduction in MIC50 ( Fig 1A ) . At 37°C , MIC50 was found to be 1 . 78 μM . This indicates that C . neoformans critically depends on Hsp90 for survival at 37°C as the dose which causes no inhibition at 25°C is more potent at 37°C . To test whether compromise of Hsp90 function can exert a fungistatic or fungicidal effect at 37°C , RAD susceptibility testing was followed by spotting on agar plates without any inhibitor . Cells grown at 37°C for 72 hours in presence of RAD were spotted and incubated both at 25°C and 37°C . We found that C . neoformans grown at 37°C for 72 hr in the presence of RAD were inviable after transferring to 37°C as well as 25°C indicating that the Hsp90 inhibition is fungicidal ( Fig 1B ) . To rule out enhanced drug uptake at higher temperature , we determined the effect of Amphotericin B ( AmB ) on growth at 25°C and 37°C ( Fig 1C ) . MIC50 values for AmB was 0 . 27μg/ml and 0 . 52 μg/ml at 25°C and 37°C respectively indicating that hypersensitivity to Hsp90 inhibitor observed at 37°C is not a general phenomenon . A more pronounced effect was seen for a Cryptococcus clinical isolate wherein MIC 50 value was found to be 18 . 63 μM and 1 . 51 μM at 25°C and 37°C respectively ( Fig 1D ) . AmB MIC50 values remained the same at both temperatures ( Fig 1E ) . At higher concentrations of drug , there was no growth at both temperatures tested , indicating Hsp90 function is essential in C . neoformans . Next , we wanted to address whether high temperature hypersensitivity is specific to C . neoformans . We did the same growth inhibition assay in presence of RAD with C . albicans as an organismal control wherein we found that MIC values remain the same at both temperatures tested ( Fig 1F ) . We speculate that the chaperone machinery which includes cochaperones and clients may be different in thermotolerant and non-thermotolerant Cryptococcus species . Thus , the increased sensitivity of C . neoformans to Hsp90 inhibition at physiological temperature clearly suggests that it is critically dependent on the Hsp90 machinery for thermotolerance in its host which is the first step for infection . To further delineate the role of Hsp90 in governing thermotolerance , we investigated whether temperature can enhance the function of C . neoformans Hsp90 ( CnHsp90 ) at the biochemical level . Hsp90 function depends on its ATPase activity and N-terminus has a unique Bergerat-type ATP-binding fold that is involved in ATP binding . A critical arginine residue positioned in the middle domain of the protein occupies the centre stage in catalysis [28] . At the level of primary structure , C . neoformans Hsp90 shows 69% and 68% identity with C . albicans and human Hsp90 respectively . However , it is a well-established fact that Hsp90s from different organisms differ in their biochemical activities . Furthermore , it has been previously shown that protozoan parasites have higher ATPase activity than their human counterpart . [3 , 6 , 24 , 29] . The biochemical parameters of Hsp90 from fungal pathogens have not been characterized previously . Therefore , to determine the biochemical properties of CnHsp90 , it was cloned from C . neoformans genomic DNA in pRSET-A vector ( Fig 2A ) . CnHsp90- 6×-His tagged fusion protein was expressed in Escherichia coli BL21 pLysS and was purified to homogeneity using Ni-NTA chromatography ( Fig 2B ) . Intrinsic fluorescence quenching was employed to analyse CnHsp90 binding to its ligand ATP . Briefly , increasing concentration of ATP was incubated with a constant amount of protein and the decrease in the intrinsic fluorescence of protein upon binding to ligand was monitored as described under “experimental procedures” . Difference in intrinsic fluorescence was plotted against molar concentration of the ligand and the saturation curve thus obtained was further analysed by Graphpad Prism 5 software using non-linear regression analysis . CnHsp90 was found to display measurable differences in fluorescence intensity induced by varying concentrations of ATP ( Fig 2C ) . The dissociation constant ( Kd ) for ATP binding was determined to be 497 . 05 μM . Next , we wanted to determine the ATPase activity of CnHsp90 at 25°C and 37°C . Hydrolysis reaction was performed by incubating CnHsp90 with ATP ( 100–4000 μM ) at 25°C and 37°C . γ-32P-ATP was used as a tracer . Fractional cleavage of ATP by CnHsp90 was plotted against corresponding ATP concentrations in order to calculate the ATPase activity . CnHsp90 obeys Michaelis Menten kinetics and Km for ATP hydrolysis for CnHsp90 were found to be 324 . 95 μM and 526 . 85 μM respectively at 25°C and 37°C ( Fig 2D ) . The catalytic efficiency of CnHsp90 was found to be 5 . 07 × 10−5 min−1 μM−1 at 25°C and 6 . 39 × 10−5 min−1 μM−1 at 37°C ( Fig 2E ) . The catalytic efficiency of CnHsp90 was found to be higher than human Hsp90 . Higher in vitro catalytic efficiency indicates that the rate of client cycling through the chaperone cycle will be higher , however , in vivo it may also be regulated by cochaperones and cofactors . Inhibition of Hsp90 ATPase activity compromises Hsp90 function and hence cell growth . So , we wanted to address whether the observed hypersensitivity to Hsp90 inhibitor at the physiological temperature is also reflected at the level of protein activity . First , we characterized the in vitro binding of C . neoformans Hsp90 to 17-N-allylamino-17-demethoxygeldanamycin ( 17-AAG ) which is a derivative of Geldanamycin . 17-AAG and geldanamycin both binds to the nucleotide binding pocket and competitively inhibit the ATPase activity . Geldanamycin is hepatotoxic for clinical use and 17-AAG is known to be a better tolerated derivative . We took the approach of intrinsic fluorescence quenching as described above to determine the binding strength of 17-AAG to Hsp90 in vitro . Significant quenching of intrinsic fluorescence of CnHsp90 was seen upon increasing concentrations of the inhibitor . The saturation curve of CnHsp90-17-AAG binding was used to calculate the dissociation constant , Kd , for 17-AAG binding , which was found to be 12 . 92 μM ( Fig 3A ) . Further we determined the effect of 17-AAG on the ATPase activity of CnHsp90 . Pure protein was incubated at both temperatures with fixed saturating concentrations of ATP , and 17-AAG concentration was varied , ranging from 5 μM to 300 μM . Percent remaining activity for each 17-AAG concentration was calculated and was plotted against log10 17-AAG concentration ( Fig 3B ) . IC50 for 17-AAG-mediated inhibition of CnHsp90 ATPase activity was observed to be 117 . 15 μM and 26 . 89 μM at 25°C and 37°C respectively ( Fig 3C ) . Thus at 37°C , 17-AAG inhibits CnHsp90 protein more potently . However , since in vivo ATPase activity of Hsp90 is known to be regulated by many cochaperones which either stimulate or bring down Hsp90 ATPase activity , the difference in ATPase IC50 observed in vitro is not sufficient alone to explain the observation at the cellular level . For example , Sba1p is a cochaperone which stabilizes the ATP bound conformation of Hsp90 by interfering with ATP hydrolysis , thereby prolonging the association of clients with Hsp90 [30] . Aha1 has a ATPase stimulatory activity [31] . Our study is the first to report the kinetic parameters of Hsp90 from a pathogenic fungus . The biochemical properties of CnHsp90 have been tabulated and compared to Hsp90 from host human and protozoan parasites in Table 1 . Presence of a melanised cell wall and polysaccharide capsule are the other two well established pathogenicity armours of Cryptococcus [32] . Armoured intricately around the cell wall , capsule defends phagocytic action of macrophages [33–35] . While Hsp90 is primarily a cytosolic chaperone , in many pathogenic organisms , it has been shown to be present on the cell surface as well . Most notable among these examples and closely related to our system is C . albicans wherein a 47kDa , C terminal fragment of Hsp90 was detected on the cell surface [13] . Interestingly , the surface exposed Hsp90 could also be targeted by a monoclonal antibody called Mycograb which was shown to neutralize Candida infections [15] . Also , cell surface Hsp90 has been detected in cancer cells [36] . With this background , we therefore examined whether Hsp90 is localised at the cell surface . Cryptococcal cells grown at 25°C and 37°C were subjected to indirect immunofluorescence analysis without permeabilization and the association of Hsp90 at the cell surface was probed using specific antibody against CnHsp90 , anti CnHsp90 Ab . Hsp90 was observed to be localised on the fungal cell surface at both 25°C and 37°C . Also , a high degree of co-localization between Hsp90 and calcofluor staining was observed implicating that Hsp90 is also enriched in the cell wall ( Fig 4A ) . In order to rule out nonspecific binding of antibody to the fungal cell surface and as a negative control to rule out accidental permeabilization during the experimental steps , we used antibody to a cytosolic protein phosphoglycerate kinase . Immunofluorescence using Anti-PGK Ab was performed as above and signal corresponding to cell surface was not observed in this case . Signal at the cell wall was also not seen in case of cells probed with pre-immune serum thereby ruling out nonspecific antibody binding . To further reconfirm our results , we examined the surface distribution of Hsp90 by whole cell based ELISA . In brief , polystyrene plates were incubated with intact yeast cells and the cell surface association of Hsp90 was probed with different dilutions of Anti CnHsp90 Ab . As a control to rule out nonspecific binding due to cell lysis , we used an antibody to PGK as above . We saw significant binding of cell surface Hsp90 to the specific antibody as can be seen in the ELISA curve ( Fig 4B ) . Binding was not observed in control fungal cells using polyclonal antiserum against PGK . To further probe into the nature of this association , we resorted to previously described method of fungal cell “shaving” . β-mercaptoethanol extraction of cell surface associated proteins were performed as described in the experimental procedures . Briefly log phase cells were incubated in 1% βME- PBS for 60 mins and the extract thus obtained ( culture supernatant ) was subjected to immunoblot analysis using Anti CnHsp90 Ab . A band at the correct molecular size of Hsp90 was detected in the βME extract at both temperatures , further strengthening our observation ( Fig 4C ) . Capsule and cell wall are intricately linked and assembly of capsule involves the trafficking of a large number of polysaccharides along with the proteins necessary for assembly onto the cell surface . Role of classical secretion pathway has been implicated in capsular monomer assembly by using conditionally defective secretory mutants wherein cargo from accumulated vesicles was found to react with anti GXM mAbs [37] . Interestingly , it was also shown that colloidal gold labelled mAbs against GXM binds with linear fibres present both on cell surface and cytosolic secretory vesicles [38] . In order to address how Hsp90 is trafficked to the cell surface , we tried to interfere with the process of capsular assembly by using Brefeldin A ( BFA ) , a well-studied vesicle trafficking inhibitor . BFA interferes with the action of ARF and blocks the anterograde transport of proteins between the ER and Golgi apparatus . Cells were grown in presence of BFA at 25°C and 37°C and then immunofluorescence was carried out as described above . Signal for Hsp90 at cell surface was completely abolished in BFA treated cells ( Fig 5A and 5B ) indicating ER to Golgi transport is important for Hsp90 localization to the cell surface . We also used N-ethylmaleimide ( NEM ) which is a cysteine alkylating agent that interferes with disulphide bond formation . A faint and diffused signal is seen in case of NEM treated cells which indicates NEM is also able to abolish the cell surface trafficking process of Hsp90 ( Fig 5C ) . This result clearly establishes that cell surface association of Hsp90 depends on the classical secretory pathway . We hypothesized that Hsp90 may be chaperoning client proteins which are important in this process and hence gets piggybacked along with its client to the surface . This means Hsp90 inhibition will abrogate its association with these client proteins and hence would interfere with the process of its trafficking to the cell wall . To test this possibility , we also grew the cells in the presence of 0 . 5 μMRAD for 48 hours and probed Hsp90 surface localisation as above . We examined the cell viability by Trypan blue dye exclusion method and found 90–95% viability thus ruling out cell death during RAD treatment . Signal at the cell surface for Hsp90 was not observed at both temperatures ( Fig 5D ) . This indicates that pharmacological inhibition of Hsp90 also leads to derailment of the pathways necessary for its localization on the cell wall . Cells respond to stress by regulating the abundance of proteins in myriad ways . Therefore , to get a cellular picture of Hsp90 under thermal stress , we first quantified the protein level expression of Hsp90 at different temperatures . Cells were grown at 25°C and 37°C till exponential phase and the lysate was probed with Anti CnHsp90 antibody . Upon checking the expression of CnHsp90 under steady state , we found similar protein levels under conditions of prolonged growth in YPD at 25°C and 37°C ( Fig 6A ) . When cells were grown at 25°C and then shifted to 37°C , we found transient increase in Hsp90 levels after 20 mins ( S1A Fig ) . However , since in vitro culture conditions are drastically different than the host environment , we tried to mimic the host environment by growing cells in the presence of 10% serum , which also is known to induce the process of capsulation . We probed protein levels under capsule inducing conditions and found a marked upregulation of Hsp90 under these conditions ( Fig 6B ) . We also observed significant upregulation of Hsp90 under another well-established capsule inducing condition i . e . 37°C and 5% CO2 which mimics lung environment ( S1B Fig ) . Capsule regulation is dynamic , it’s size changes in context of infection and polysaccharide shedding is also reported . Since Hsp90 is cell surfaced localised and is also upregulated under capsule inducing conditions , therefore we hypothesized that compromise in Hsp90 function may affect capsular assembly . To test this hypothesis , we examined the effect of Hsp90 inhibition on capsule formation . First cells were incubated in capsule inducing medium in presence of RAD and capsule formation was observed microscopically with respect to no drug control . Significant reduction in capsule size was observed when RAD was added in the capsule inducing media as compared to no drug ( Fig 6C ) . This indicates that Hsp90 function is important for induction of capsule formation as treatment with RAD during capsule induction led to approximately 60% reduction in capsular volume ( Fig 6D ) . Next , we asked if Hsp90 is also required for maintenance of capsule around the cell . Cells were first grown in capsule inducing medium and RAD treatment was done post capsulation . Similar reduction was seen in capsular volume in case of post capsulation treatment also indicating that Hsp90 is required for maintenance of capsules around the cell wall . Taken together , these observations clearly suggest that Hsp90 trafficking to the cell wall and capsular assembly are related processes and hence it assigns an important role of regulating capsule dynamics to Hsp90 in C . neoformans . Cryptococcus has been shown to be intrinsically resistant to echinocandins which target the fungal cell wall . In Candida albicans and Aspergillus fumigatus , role of Hsp90 in echinocandin resistance has been well established [10] . Previous studies in Cryptococcus have shown synergy of Hsp90 inhibitors Mycograb [15] and RAD [18] with azoles . Given that Hsp90 is present at the surface of C . neoformans , we set out to examine if Hsp90 has a role in potentiating echinocandin resistance in Cryptococcus . To address this , first we evaluated the susceptibility of C . neoformans to the widely used echinocandin–anidulafungin ( AF ) by performing antifungal broth microdilution assays as described previously . This assay was done both at 25°C and 37°C to examine whether temperature influences AF tolerance . We observed robust resistance to AF as indicated by normal growth of cells even at high doses of AF ( 16μg/ml ) . Also , higher temperature had no impact on AF tolerance as resistance was seen at both temperatures tested ( Fig 7A ) . Therefore , C . neoformans is resistant to AF and the resistance profile is similar at 25°C and 37°C . Next , we wanted to evaluate the impact of pharmacological inhibition of Hsp90 on AF resistance in Cryptococcus . A similar approach was followed wherein cells were grown in presence of AF and RAD at the concentrations indicated ( Fig 7B ) . Compromising Hsp90 function with RAD ( 0 . 25μM and 0 . 5 μM ) in presence of AF ( 4μg/ml ) ) had no impact on growth of the isolate as compared to the drug free controls at 25°C . Notably , at 37°C there was approximately a 42% decrease in growth at a lower dose of AF ( 4μg/ml ) upon RAD treatment at a concentration of 0 . 25μM . At 0 . 5μM RAD , AF had enhanced sensitivity with almost 47% lower growth ( Fig 7C ) . Surprisingly this effect was not seen at 25°C at the same concentrations tested as mentioned above . To determine the nature of drug interaction , we further analyzed the fractional inhibitory concentrations of the two drugs at 37°C by calculating ∑FIC for the combination treatment as described in the methods section . ∑FIC value for RAD and AF combination was calculated to be 0 . 56 thus indicating an additive effect . This strengthens the fact that Hsp90 mediated thermotolerance regulates pathogenicity of the fungus in myriad ways . Our study therefore also reinforces the potential of Hsp90 inhibitors as a promising and powerful antifungal combination therapy along with echinocandins against Cryptococcal infections .
Fungal pathogens first need to cross the formidable barrier of high physiological temperature in order to live and colonize within mammals . One such example of thermotolerance manoeuvring fungal pathogenesis has been seen in the genus Cryptococcus wherein only species capable of growth at 37°C are human pathogens . Cryptococcus species which lack this ability despite having other virulence factors , for example , C . podzolicus are non-pathogenic [39] . Temperature is known to act as a cue for dimorphism in C . albicans wherein it undergoes yeast to hyphal transition at 37°C which is implicated in its virulence . Interestingly Hsp90 has been shown to be the regulator of this switch by repressing the Ras1-PKA signaling pathway [7] . In C . neoformans , serial analysis of gene expression and microarray studies have revealed the upregulation of Hsp90 at 37°C [22 , 40] , under reduced iron conditions [41] and under fluconazole stress [42] . However detailed understanding about the role of Hsp90 in C . neoformans is lacking . In this context , we have investigated the role of Hsp90 in governing thermotolerance in C . neoformans . We find that growth at physiological temperature critically depends on Hsp90 function as mild compromise in function at 37°C but not at 25°C is lethal for C . neoformans . We further investigated biochemical profile of the protein by characterization of its ATPase activity and inhibition by 17-AAG . This is the first report of the kinetic parameters of Hsp90 of a pathogenic fungus . We found that CnHsp90 binds to its ligand with an affinity constant 497 . 05 μM . ATPase activity was found to be higher at 37°C . This strengthens the fact that being a pathogen which experiences stressful and highly demanding environment , higher rate of client cycling through the chaperone cycle is a must as reflected by higher catalytic efficiency . Interestingly we observe that ATPase activity is 4 . 5-fold more sensitive to inhibition by 17-AAG at 37°C which indicates different conformational dynamics of the protein at higher temperature . Nonetheless , this agrees with higher cellular growth inhibition indicating at 37°C , ATPase activity of Hsp90 is more crucial for its survival . Alterations in ambient temperature may lead to a change in concentration of free Hsp90 as global burden of protein folding increases and hence may influence the interaction of Hsp90 with those clients which are required for growth at high temperature . This prompted us to investigate the localization of Hsp90 . Hsp90 was found to be cell surface associated and this association was perturbed by interfering with the ER Golgi classical secretory pathway . Since cell wall is also intricately associated with capsule , another important and unique virulence attribute of the pathogen , we probed Hsp90 levels under capsule inducing conditions and found it to be upregulated . Capsular assembly is a complicated process as it involves synthesis of nucleotide sugar donors in the cytoplasm , however , assembly takes place near the cell wall . Active transport of capsular polymers takes place and it has been shown that inhibitors of vesicular transport or secretory pathway mutants lead to decreased capsule . Additionally , the cell wall is the interface of capsule attachment and it provides a scaffold for proteins that mediate the process . Upon compromise of Hsp90 function during the process of capsulation as well as post capsulation , significant reduction in capsule size was seen thereby confirming that Hsp90 is involved both in assembly and maintenance of capsule . In this light , presence of Hsp90 on the cell wall indicates that it chaperones important clients which are involved in the above processes , hence , compromising Hsp90 function compromises cell wall organisation which in turn affects capsule assembly . Pharmacological inhibition of Hsp90 may titrate it away from the client which gets degraded and hence we see a decrease in capsule formation . Signalling pathways mediated by kinases like Hog1 , PKC and protein kinase A have been shown to be involved in capsule regulation in Cryptococcus . These kinases are well established clients of Hsp90 in other organisms such as C . albicans . We speculate that under capsule inducing conditions , Hsp90 chaperones the dephosphorylated form of Hog1 and keeps it poised for signal transduction to regulate capsule size . In yeast , a dedicated cochaperone called Cdc37 which presents kinase clients to Hsp90 was found to be upregulated at the transcript level in capsular mutants under capsule inducing conditions . It would be interesting to experimentally validate the interaction of Hsp90 and Cdc37 with these kinases in Cryptococcus . Transcript data analysis ( available in FungiDB ) also revealed upregulation of another co-chaperone Aha1 . Nonetheless , different line of evidences such as cell surface localisation of Hsp90 , upregulation of Hsp90 and cochaperones under different capsule inducing conditions , reduction in capsule volume upon Hsp90 inhibition and transcript data analysis suggests a crucial role of Hsp90 machinery in governing critical aspects of cell wall and capsule regulation in the pathogen . Echinocandins are the only class of antifungals whose target is located on the fungal cell wall and coincidentally we found Hsp90 to be also localised on the cell wall . Echinocandins are the most recent class of antifungals with a broad inhibitory spectrum against most pathogenic fungi such as Candida and Aspergillus [43 , 44] . However , it seems that Cryptococcus is intrinsically resistant to Echinocandins . Surprisingly , studies have pointed out that the target of the drug , ( 1 , 3 ) beta-glucan synthase is essential for the organism [45] and also the enzyme is inhibited in vitro by echinocandins [46] . Mutations in the target genes FKS1 and FKS2 are also not responsible for the resistant phenotype . Our work reveals Hsp90 inhibitor RAD and anidulafungin are effective in combination against Cryptococcus thereby extending the current antifungal armoury . Interestingly this effect is also seen at 37°C and not at 25°C , thus again reconfirming the fact that virulence and thermotolerance are linked in this fungus . This implies that either Hsp90 directly regulates cell wall stress response exerted by echinocandins such that impairing Hsp90 function abrogates intrinsic resistance to echinocandins or Hsp90 is essential for cell wall integrity and inhibition of Hsp90 makes anidulafungin more accessible to its target . We postulate Hsp90 commands the thermotolerant ability by chaperoning crucial clients directly involved in the process . For example , calcineurin , a bona fide client of Hsp90 , has been implicated in growth at high temperature as well as virulence of the pathogen [47–49] . As such , compromising Hsp90 function may cause destabilization of proteins involved in growth at high temperature , which in turn leads to derailment of the pathways enabling thermotolerance . Kinases like Hog1 , Mkc1 and Cek1 , which are crucial for cell wall integrity [50] , are also well- established clients of Hsp90 [12 , 51] . Taken together , our study establishes a critical role of Hsp90 in mediating three essential virulence determinants in C . neoformans i . e . thermotolerance , capsule formation and echinocandin resistance . Compromising Hsp90 function may lead to rewiring of fundamental pathways implicated in virulence and hence our study corroborates with numerous other studies highlighting the potential of targeting Hsp90 in fungal pathogens . Understanding the basis of thermotolerance and virulence will thus not only highlight acquisition of pathogenicity determinants , but may also open new therapeutic avenues to cripple a lethal infection . | Thermotolerance is a pre-requisite for microbes to propagate successfully as human pathogens . In this study , we have investigated the role of Heat shock protein 90 in the pathogenesis and thermotolerance of C . neoformans , an environmental fungus that causes meningoencephalitis in humans . We show that thermotolerance of Cryptococcus critically depends on Hsp90 function as modest inhibition of Hsp90 function , robustly compromised growth of the fungus at 37°C with little effect at 25°C . This observation correlated with the fact that pharmacological inhibitor , 17-AAG also showed a more potent inhibition of ATPase activity of the protein at 37°C as indicated by a lower IC50 as compared to 25°C . Indirect immunofluorescence analysis using an antibody specific to CnHsp90 revealed cell surface localization of Hsp90 . BFA sensitivity of such surface localization indicated involvement of ER-Golgi classical secretory pathway for this localization . Furthermore , inhibition of Hsp90 function not only abrogated the natural resistance of C . neoformans to cell wall targeting inhibitors echinocandins but also led to decrease in capsular assembly which is one of the classical virulence determinants of the pathogen . In all , this study provides the first detailed biochemical as well as functional insights into the role of Hsp90 in governing thermotolerance and augmenting virulence factors in C . neoformans . | [
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"pha... | 2017 | Heat shock protein 90 localizes to the surface and augments virulence factors of Cryptococcus neoformans |
The Sri Lankan Anti-Filariasis Campaign conducted 5 rounds of mass drug administration ( MDA ) with diethycarbamazine plus albendazole between 2002 and 2006 . We now report results of a comprehensive surveillance program that assessed the lymphatic filariasis ( LF ) situation in Sri Lanka 6 years after cessation of MDA . Transmission assessment surveys ( TAS ) were performed per WHO guidelines in primary school children in 11 evaluation units ( EUs ) in all 8 formerly endemic districts . All EUs easily satisfied WHO criteria for stopping MDA . Comprehensive surveillance was performed in 19 Public Health Inspector ( PHI ) areas ( subdistrict health administrative units ) . The surveillance package included cross-sectional community surveys for microfilaremia ( Mf ) and circulating filarial antigenemia ( CFA ) , school surveys for CFA and anti-filarial antibodies , and collection of Culex mosquitoes with gravid traps for detection of filarial DNA ( molecular xenomonitoring , MX ) . Provisional target rates for interruption of LF transmission were community CFA <2% , antibody in school children <2% , and filarial DNA in mosquitoes <0 . 25% . Community Mf and CFA prevalence rates ranged from 0–0 . 9% and 0–3 . 4% , respectively . Infection rates were significantly higher in males and lower in people who denied prior treatment . Antibody rates in school children exceeded 2% in 10 study sites; the area that had the highest community and school CFA rates also had the highest school antibody rate ( 6 . 9% ) . Filarial DNA rates in mosquitoes exceeded 0 . 25% in 10 PHI areas . Comprehensive surveillance is feasible for some national filariasis elimination programs . Low-level persistence of LF was present in all study sites; several sites failed to meet provisional endpoint criteria for LF elimination , and follow-up testing will be needed in these areas . TAS was not sensitive for detecting low-level persistence of filariasis in Sri Lanka . We recommend use of antibody and MX testing as tools to complement TAS for post-MDA surveillance .
Lymphatic filariasis ( LF , caused by the mosquito borne filarial nematodes Wuchereria bancrofti , Brugia malayi , and B . timori ) , is a major public-health problem in many tropical and subtropical countries . The latest summary from the World Health Organization ( WHO ) reported that 56 of 73 endemic countries have implemented mass drug administration ( MDA ) with a combination of two drugs ( albendazole with either ivermectin or diethycarbamazine ) , and 33 countries have completed 5 or more rounds of MDA in some implementation units [1] . With more than 4 . 4 billion doses of treatment distributed between 2000 and 2012 , the Global Programme to Eliminate Lymphatic Filariasis ( GPELF ) is easily the largest public health intervention to date based on MDA . Bancroftian filariasis was highly endemic in Sri Lanka in the past [2]–[4] . The Sri Lankan Ministry of Health' Anti Filariasis Campaign ( AFC ) used a variety of methods to reduce filarial infection rates to low levels by 1999 [5] , [6] . Sri Lanka was one of the first countries to initiate a LF elimination program based on GPELF guidelines [7] . The AFC provided annual MDA with diethylcarbamazine alone for three years starting in 1999 . This was followed by five annual rounds of MDA with albendazole plus diethylcarbamazine in all 8 endemic districts ( implementation units , IU ) between 2002 and 2006 . Various types of surveillance have been conducted by AFC and other groups since the MDA program ended in 2006 [8]–[12] . Post-MDA surveillance results ( based on detection of microfilariae or Mf in human blood by microscopy ) have consistently shown Mf rates much lower than the target value of 1% in all endemic areas [13] . The AFC also conducted school-based surveys for filarial antigenemia in 2008 according to WHO guidelines active at that time . Approximately 600 children were tested for circulating filarial antigenemia ( CFA ) in 30 schools in each of the 8 endemic districts , and no positive tests were observed ( unpublished data , Sri Lanka Ministry of Health ) . WHO guidelines emphasize that LF elimination programs should provide care for people with acute and chronic clinical manifestations of filariasis [7] , and the AFC has an excellent network of clinics that is devoted to this activity [13] . The present study represents a significant expansion of earlier post-MDA surveillance activities in Sri Lanka . Transmission assessment surveys ( TAS ) were performed according to current WHO guidelines [14] , [15] for sampling primary school children to detect filarial antigenemia in each district . While TAS results may be useful for deciding whether MDA can be stopped , TAS cannot guarantee that LF transmission has been interrupted in evaluation units ( EUs ) , which are typically districts with populations that may exceed 1 million . Therefore we conducted more intensive surveillance activities in smaller areas ( Public Health Inspector “PHI” areas ) that were considered to be at high risk for persistent filariasis to complement the TAS program . Provisional targets have been proposed for documenting the interruption of filariasis transmission based on studies of the effects of MDA in Egypt , which also has LF transmitted by Culex mosquitoes [16] . Targets proposed for treated populations after at least five years of effective MDA were <2% for filarial antigenemia in communities ( which corresponds to a MF prevalence rate of <0 . 5% ) , <2% for antibody to the recombinant filarial antigen Bm14 in first grade primary school children , and <0 . 25% for parasite DNA rates in mosquitoes as assessed by molecular xenodiagnosis ( MX ) . The present study provided an opportunity to gain further experience with these parameters in the post-MDA setting . Thus , the first aim of this study was to test the hypothesis that LF has been eliminated in Sri Lanka some 6 years after the completion of its national MDA program . The second aim was to assess the relative value of different methods for detecting low level persistence of filariasis after MDA .
Comprehensive surveillance activities in this project used Public Health Inspector ( PHI ) areas as sentinel sites . PHIs are sub-district health administration units that are comprised of smaller Public Health Midwife ( PHM ) areas . PHI's typically have populations in the range of 10 , 000–30 , 000 people , but they are larger in the country's capital city of Colombo which does not belong to a district . Post-MDA comprehensive surveillance studies were performed in at least two PHIs in each of the 8 LF-endemic districts in Sri Lanka plus two sites in Colombo town . The mean area of these PHIs was 6 . 3 km2 ( range 0 . 6 km2–24 . 5 km2 ) . Most PHIs selected for this study were considered to be at increased risk for persistent filariasis based on high infection rates prior to MDA or based on results of microfilaremia surveys conducted after 2006 . Field teams for collection of demographic information and blood specimens consisted of a medical officer , a Public Health Inspector , a phlebotomist , and one or two assistants . Blood samples were collected during the day . Sterile , single use , contact activated BD-microtainer lancets ( Fisher Scientific , Pittsburgh , PA ) were used for blood collection in community and school surveys . Approximately 300 to 400 µl of blood was collected by finger prick from each study subject into an EDTA coated blood collection vial ( Fisher Scientific ) . Barcode stickers were used to link specimens to data records . Samples were transported to the AFC headquarters laboratory in Colombo in coolers . Plasma was separated from blood samples from school children and stored at −80 C for later antibody testing . A pilot study was performed in Peliyagodawatta in Gampaha district in 2008 as a training exercise and to test the feasibility of comprehensive LF surveillance in Sri Lanka using methods pioneered in Egypt . This semi-urban area ( with a population of about 10 , 560 in an area of 1 . 59 km2 ) was resurveyed in 2011 . All other PHIs were only studied once . The community surveys used a systematic sampling scheme to sample all areas in each PHM within the PHI being studied . The AFC obtained census lists with the numbers of houses in each PHM and PHI along with maps showing the PHMs within PHIs . The number of houses/households needed for each community survey ( 125 ) was divided by the number of PHMs in the PHI to get the number of houses to be sampled in each PHM . That number was divided by 4 to get the number of houses to be sampled per quadrant in each PHM . The central house in the quadrant was sampled , and other houses were selected by moving in the 4 cardinal directions from the central house . The sampling interval for houses was calculated by dividing the total number of houses in the PHM quadrant by the number of houses that were to be sampled in that quadrant . For instance , if there were 60 houses in a quadrant and 10 houses were to be sampled , the sampling interval was 6 . If a selected house could not be sampled because of absence or refusal , field teams sampled the next house . Community surveys sampled people who were at least 10 years of age , and a maximum of 4 subjects were enrolled per house . Finger prick blood was collected from children in grades 1 and 2 in primary schools that served children in the study PHIs; approximately 350 school blood samples were collected per PHI . Blood was tested for filarial antigenemia by card test , and plasma was stored for later antibody testing . Mosquitoes were collected with gravid traps ( Model 1712 , John W . Hock Company , Gainesville , FL ) using liquid bait . The liquid bait was prepared 5–6 days prior to use containing yeast , milk powder and dry straw in water [17] . In some PHI areas cow dung was added to the liquid bait to attract mosquitoes . Gravid traps were placed adjacent to houses for one to four days; mosquitoes were collected in the morning and traps were replaced in the evening . Traps were placed in shaded , quiet areas near natural breeding sites . Traps were placed in all 4 quadrants of each PHM to ensure sampling from all areas in each PHI . In the Peliyagodawatta pilot study in 2008 , 4835 mosquitoes were collected from 20 trap sites , and the number of pools collected from each trap ranged from 1–10 pools of mosquitoes ( range 5–20 mosquitoes per pool ) . In all subsequent surveys , 4 pools of twenty mosquitoes were collected from each of 50 trapping sites per PHI . Trapped mosquitoes were collected , sorted , dried at 95°C for 1 hr . and placed in tubes for later testing ( 20 mosquitoes/pool ) . The tubes were labeled with barcode stickers and transferred to the AFC headquarters laboratory for DNA isolation and qPCR testing . Washington University personnel trained staff in the central AFC laboratories on standard operating procedures for Mf detection by microscopy , antibody and antigen testing , DNA isolation from mosquitoes , and detection of filarial DNA by qPCR . All samples were tested in AFC laboratories in Colombo . Circulating filarial antigenemia ( CFA ) was detected with a simple card test ( BinaxNOW Filariasis , Alere Inc . , Scarborough , ME ) [16] , [18] . IgG4 antibodies to recombinant filarial antigen Bm-14 in human plasma were detected by microplate ELISA ( Filariasis CELISA , Cellabs Pty Ltd , Brookvale , NSW , Australia ) as previously described [19] . Previous studies have shown that this kit is sensitive and specific for infection and/or heavy exposure to filarial parasites . Plasma ELISAs were performed with a single well per sample , and all positive and borderline tests were retested on a different day . Samples that produced an OD value >0 . 35 in two assays performed on different days were considered to be positive for antibody to Bm14 . Microfilaria ( Mf ) testing was performed for people with positive filarial antigen tests ( in community household surveys , school surveys , and TAS ) with three-line blood smears ( 60 µl total volume of night blood tested ) . Mosquitoes were sorted by experienced technicians . Blood fed , gravid , and semi-gravid Culex quinquefaciatus mosquitoes were identified by morphology and sorted into 4 pools of 20 mosquitoes per collection site . Two hundred and seventy-seven pools of mosquitoes ( mean pool size of 17 ) were collected and tested from Peliyagodawatta in the pilot study that was performed in 2008 . Approximately 200 pools were tested from each PHI area in later surveys . W . bancrofti DNA was detected in mosquito pools by qPCR as previously described [16] , [20] . DNA isolation and PCR analysis for samples from the 2008 pilot study were performed by AFC personnel together with Washington University technicians in St . Louis . All subsequent PCR work was conducted by AFC personnel in the AFC laboratory in Colombo . Demographic information including age , gender , documentation of informed consent , and a history of compliance with the previously administered MDA program was collected and entered into personal digital assistants ( PDA ) ( Dell Axim ×51 , Dell Inc . Round Rock , TX or HP iPAQ 211 , Hewlett Packard , Palo Alto , CA ) using a preloaded survey questionnaire . Participant data , specimen ID , and test results were linked using preprinted barcode labels as described by Gass et al [21] . AFC deployed 2 or 3 teams for blood collection and 2 or 3 teams for mosquito collection in each PHI , and teams were comprised of a mixture of personnel from the district and from AFC headquarters . Data collected by multiple teams were synchronized at AFC headquarters , and data were transferred to a laptop computer using LF field office data manager software designed by the Lymphatic Filariasis Support Center , Taskforce for Global Health , Decatur , GA . Transferred files were merged to create a master database , which was backed up using an external hard drive . Specimens and laboratory test results were linked to study subject numbers ( or to trap site and pool number for mosquito data ) using barcodes . Deidentified , cleaned data were transferred into Excel files ( Microsoft Corp . , Redmond , WA ) for analysis at AFC and at Washington University . GPS coordinates for human and mosquito sampling sites were plotted using ArcGIS 10 . 2 . 1 ( ESRI , Redlands , CA ) to show the location of households surveyed and mosquito trapping sites for each PHI . Waypoints were color coded to show the infection status of household residents and mosquitoes from these collection sites . TAS were performed in all 8 endemic districts in late 2012 or early 2013 according to WHO guidelines . The TAS program used districts as evaluation units ( EUs ) in 5 cases . However , 3 districts or areas with large populations ( Colombo district plus Colombo town , Gampaha , and Galle ) were each divided into two EUs for TAS . All EUs met criteria for conducting TAS by having completed 5 rounds of MDA in 2006 with high MDA compliance rates ( >80% ) . All sentinel and spot check sites in each district had Mf prevalence rates well below 1% for several years prior to TAS . Since Sri Lanka has high primary school attendance rates ( >95% ) , TAS surveys used the cluster method to sample students in 30–35 randomly selected schools per EU[15] . Systematic selection of school children was performed with Survey Sample Builder software , SSB . V . 2 . 1 ( http://www . ntdsupport . org/resources/transmission-assessment-survey-sample-builder ) . The TAS sampling strategy required filarial antigen testing of approximately 1500 primary grade children in each EU . Blood samples were collected with One Touch Ultra Soft lancet holders with disposable lancets ( LifeScan , Inc . , Milpitas , CA ) . Finger prick blood was collected into capillary tubes provided with the BinaxNow Filariasis cards , and 100 µl of blood was added directly to sample application pads of the cards according to the manufacturer's instructions . Tests were performed in the school auditorium , library , or health screening station immediately after blood collection , and read at 10 minutes . Antigen test results ( positive or negative ) were recorded manually using preprinted data collection forms . Children with positive filarial antigen tests were tested for microfilaremia with night blood smears as described above . We used the software program PASW Statistics 18 ( SPSS , now IBM Corporation , Armonk , NY ) and JMP ( SAS , Cary , NC ) . The Chi-square test was used to assess the significance of differences in categorical variables such as antigenemia rates . The correlation between human and mosquito infection parameters was analyzed by the Spearman rank test . Logistic regression was used to assess the independence of risk factors for filarial antigenemia . Graphs were produced with GraphPad Prism V . software ( La Jolla , CA ) . Filarial DNA rates ( maximum likelihood estimates with 95% confidence intervals ) were calculated with PoolScreen 2 . 02 [22] , [23] . To sharpen the analysis of risk factors for filarial infection , we limited the analysis to 14 PHI areas where one or more people had positive filarial antigen tests . All analyses were performed assuming simple random sampling for simplicity of exposition . A generalized linear mixed model was used to estimate design effects of household-based cluster sampling used in community surveys . This analysis was performed with data from the two PHIs with the highest surveyed CFA rates . The study protocol for comprehensive surveillance in PHIs was reviewed and approved by institutional review boards at Washington University School of Medicine and at the University of Kelaniya in Sri Lanka ( FWA 00013225 ) . Prior to school surveys ( both PHI surveys and TAS ) , study personnel held preliminary meetings with school principals and officials from the Sri Lankan Ministry of Education about the goals and procedures for the study . They also met with parents or guardians to discuss the study design and the significance of the study . Printed participant information sheets and written consent forms were provided to participants ( or to parents/guardians ) in Sinhalese , Tamil and English . Written consent was obtained from adults . Participation of minors required written consent from at least one parent or guardian plus assent by the child/minor . Consent was also documented electronically into PDAs by study personnel prior to collection of health information or blood samples . TAS surveys used preprinted paper forms for parental consent and other forms for data collection ( school name , child name , age , sex , and CFA result ) .
Nineteen PHI surveys were conducted in 8 districts and in Colombo town between March 2011 and July 2013 . Demographic information for survey participants is provided in Table 1 , and results are summarized in Table 2 and Figure 1 . Community CFA rates were <2% in 17 of 19 PHIs , but upper confidence limits for CFA were >2% in 5 of 19 PHIs . Microfilaremia rates were <1% in all PHI areas studied . Sixteen of 65 CFA-positive subjects ( age range 23–70 yr ) were positive for Mf ( mean count 14 per 60 µl range 1–51 ) , and 68% of Mf carriers were males . The Unawatuna PHI area in Galle district had the highest rates for several filariasis parameters ( Table 2 and Figure 1 ) . CFA rates were higher in males than females when data from all community surveys were considered ( 1 . 01% vs . 0 . 42% , P<0 . 001 ) and when localities with no positive CFA tests were excluded from the analysis ( 1 . 39% vs . 0 . 57% , P<0 . 001 ) ( Table 3 ) . CFA rates were also higher in adults than in children , and this was especially true for people older than 30 years ( Table 3 ) . CFA rates were lower in people who reported having used a bed net the night before their interview ( all localities ) , but the difference was not statistically significant ( 0 . 57% vs . 0 . 92% , P = 0 . 06 ) . However , the reduced CFA rate in bed net users was significant when localities with no positive CFA tests were excluded from the analysis ( 0 . 76% vs . 1 . 29% , P = 0 . 04 ) . Bed net users also had lower rates of microfilaremia in these localities ( 0 . 17% vs . 0 . 52% , P = 0 . 012 ) . Reported compliance rates for ingestion of antifilarial medications during the national MDA program were high in most PHIs surveyed , but very low rates were reported in PHIs in Galle district and in Colombo town ( Table 2 ) . These results are consistent with low surveyed compliance rates previously reported for these areas [10] . CFA rates in community surveys were significantly lower in people who reported that they had ingested antifilarial medication during the national MDA program ( 0 . 45% vs . 1 . 15% , P = 0 . 001 ) . Logistic regression was used to assess the independence of different risk factors for CFA for all surveyed communities and for the subset of communities with one or more subjects positive for CFA ( Table 4 ) . Gender , age , and prior MDA treatment were significant independent indicators of risk , but reported bed net use was not . Intraclass correlations by household in the two locations with the highest filarial infection rates were 0 . 16 and 0 . 08 , and these values correspond to design effects of 1 . 6 and 1 . 3 . CFA rates were very low in children tested in school surveys , and this was consistent with TAS results presented below . Anti-filarial antibodies were detected in primary school children in 17 of 19 PHIs . Antibody rates exceeded the target rate of 2% in 10 of 19 PHIs; five PHIs had borderline elevated antibody rates , and 5 others had higher rates with upper confidence limits >5% . Only three of 137 children with positive antibody tests ( out of 6198 children tested for antibody from all 19 PHI areas ) had positive CFA tests , and all three of these children were Mf negative . Community antibody testing was performed in a subset of PHIs that were surveyed in the comprehensive surveillance study ( Table S1 ) . Although CFA and Mf rates in these communities were below provisional target levels , community antibody rates were high in all of these PHIs , and this probably reflects high infection rates that were present in these areas prior to implementation of the national MDA program . Human filariasis parameters tended to be significantly correlated with each other [e . g . , community Mf rate vs . community CFA rate ( r = 0 . 63 , P = 0 . 0018 ) , school CFA rate vs . school antibody rate ( r = 0 . 5 , P = 0 . 0142 ) , and community CFA rate vs . school CFA rate ( r = 0 . 69; P = 0 . 0006 ) ] . More than 17 , 000 primary grade school children were tested in TAS in 337 schools located in 11 EUs in 8 districts and in Colombo town ( Table 5 ) . The numbers of positive CFA tests were well below the TAS threshold level of 18 ( critical cut-off value ) in all EUs . Thus all EUs “passed” TAS including the coastal Galle District EU , where high rates for filariasis markers were noted in two PHI study areas . None of the 16 children with positive CFA tests in TAS surveys had microfilaremia . All CFA-positive children were treated with anti-filarial medications and follow-up surveys are in progress or planned to further assess people in areas with positive children . Almost 3 , 900 pools ( 20 mosquitoes per pool ) of blood fed , gravid or semi-gravid mosquitoes collected in 19 PHI areas were tested for filarial DNA by qPCR ( Table 6 ) . Filarial DNA rates exceeded the target of 0 . 25% in 10 of 19 PHIs . Mosquitoes from both PHIs surveyed in Galle district and one in Matara district had parasite DNA rates of more than 1% , and these rates were comparable to those seen in some filariasis endemic areas in Egypt with continued filariasis transmission following one or two rounds of MDA [24] . Upper confidence limits for filarial DNA rates were ≥1% in 5 of 19 PHIs surveyed . On the other hand , three of 19 PHIs surveyed had no positive mosquito pools . Most of the other filariasis parameters were also low in these PHIs . Mosquito DNA samples from Wattala were retested by qPCR at Washington University and confirmed to be negative . The percentages of positive mosquito trap sites were highly variable in different PHIs , and these rates were strongly correlated with percentages of pools positive for filarial DNA ( r = 0 . 99 , P<0 . 0001 ) , community CFA rates ( r = 0 . 72 , P = 0 . 0003 ) , and school CFA rates ( r = 0 . 77; P<0 . 0001 ) . Percentages of mosquito pools positive for filarial DNA were highly correlated with community CFA rates ( r = 0 . 71 , P = 0 . 0001 ) and school CFA rates ( r = 0 . 79 , P<0 . 0001 ) . In addition , percentages of houses with at least one CFA positive resident were highly correlated with percentages of mosquito trap sites with filarial DNA in mosquitoes ( r = 0 . 75 , P = 0 . 0001 ) ( Table S2 ) and with percentages of mosquito pools that contained filarial DNA ( r = 0 . 73; P = 0 . 0002 ) . GPS data for PHI areas with high and low rates of persistent LF are shown in Figures 2 and S1 . These maps show that sampled households and mosquito collection sites were nicely dispersed to cover the study areas . Infections in human and parasite DNA in mosquitoes tended to be dispersed in most study areas . A pilot LF surveillance study was performed in 2008 in Peliyagodawatta , which is located in Gampaha district just outside of the city of Colombo . The area was resurveyed in 2011 , approximately 2 . 5 years after the baseline study . This is a low income , peri-urban area with high mosquito densities , and no intervention for LF control was undertaken in this area between 2008 and 2011 . Results from the two surveys are summarized in Table 7 . Several filariasis parameters were lower in 2011 than in 2008 . While only the reduction in community CFA was statistically significant , the trend toward reduction was present for all of these parameters apart from Mf rate , which was already very low in 2008 . The first survey in Peliyagodawatta identified 37 amicrofilaremic subjects with positive filarial antigen tests . These people were not treated for LF at that time . Twenty-five of these people were retested in 2010 , approximately 18 months after the first survey; others had moved or were otherwise not available for follow-up . Only 12 of 25 subjects were still CFA-positive ( 48% ) , and only 1 of 25 was microfilaremic by 60 µl night blood smear . None of the subjects reported symptoms or signs of clinical filariasis during the 18 month interval . All subjects with filarial antigenemia were treated in 2011 .
The term “LF elimination” has been interpreted in different ways , but WHO documents clearly state that one goal of LF elimination programs is interruption of transmission [15] . WHO is also responsible for deciding when countries have eliminated LF . Pending their review , we think it is important to recognize the achievements of Sri Lanka's Anti-Filariasis Campaign , which is one of the finest LF elimination programs in the world . The program has reduced Mf rates to less than 1% in all sentinel and spot check sites , all EUs easily passed TAS criteria for stopping MDA , and the AFC has a network of clinics that provide care to thousands of lymphedema patients in all endemic districts . By these criteria , Sri Lanka has achieved several WHO targets and the country is on track to achieve elimination . If WHO determines that Sri Lanka has not met criteria for LF elimination , we believe that the organization should develop criteria and a recognition program for countries that can document this level of superb control , because this pre-elimination status is a significant achievement in public health and an important step on the road to LF elimination . External recognition of “superb control” or “near elimination” may help national programs obtain political support and resources needed for the difficult last mile required for true elimination . While protocols for transmission assessment surveys are based on solid sampling principles , the sensitivity of TAS for detecting ongoing transmission of LF has not been adequately tested in field studies [15] . Our results clearly show that TAS performed according to WHO guidelines were not sensitive for detecting ongoing LF transmission in Sri Lanka . There are a number of reasons for this . First , we believe that EUs of 1 to 2 million are too much too large , because risk factors that affect LF transmission often vary widely across such large populations/areas . This problem could be mitigated by reducing the size of EUs ( for example , to areas with populations of 100 , 000 or less ) , but that would significantly increase the cost of TAS . A second problem with TAS is that filarial antigenemia rates in young children are sometimes very low in areas with ongoing LF transmission . Our study showed that CFA rates in school aged children were much lower than those in adults . Therefore , the sensitivity of TAS might be improved by using a similar cluster sampling method to test adults ( for example , those attending primary health clinics ) instead of children in schools . A recent report from Togo described the use of other types of passive surveillance for assessing LF following MDA [25] . Since anti-filarial antibody rates are uniformly higher than antigenemia rates in LF-endemic populations , another potential solution for the problem of low TAS sensitivity would be to substitute antibody testing for antigen testing in TAS for samples of school-aged children . Antibody results from the present study using a commercially available ELISA kit provide a proof of principle for this approach . However , ELISA testing may not be feasible for all LF programs , and available rapid-format antibody tests have not yet been validated for this purpose . Results from this study strongly support the use of molecular xenodiagnosis for post-MDA surveillance in areas where LF is transmitted by Culex mosquitoes . MX does not require collection of blood samples or active participation by large numbers of people in endemic areas . However , MX does require cadres of skilled personnel , specialized laboratory facilities , and funds for consumables . While MX was performed by MOH personnel in this study , this required significant external inputs including equipment , supplies , training of personnel , and funds for mosquito collection . Also , additional work is needed to develop and validate sampling methods for assessment of mosquito DNA rates in areas larger than PHIs . To summarize this section of the Discussion , while TAS surveys may be useful for decisions regarding stopping MDA , they are not sufficient to show that LF transmission has been interrupted . The sensitivity of TAS might be improved by reducing the size of EUs or by sampling adults instead of school-aged children . We recommend antibody testing of children using TAS sampling methods and/or MX ( especially in areas believed to be at high risk ) to complement antigen-test based TAS , because these methods appear to be more sensitive than TAS for detecting ongoing LF transmission . This study has provided new insight regarding provisional targets for MDA programs that were suggested in 2007 based on data from Egypt [16] . Since there is uncertainty surrounding all point estimates , we now recommend using confidence intervals to express targets as illustrated in Figure 1 . The new suggested target for the antifilarial antibody rate in first and second grade school children is to have an upper confidence limit of <5% . The new target for MX ( Culex mosquitoes ) is to have an upper confidence limit of the maximum likelihood estimate of <1% . The new target for the community CFA rate ( age >9 ) is to have an upper confidence limit of <2% . This target provides a very high level of confidence that the Mf rate will be less than 0 . 5% in the community with a much smaller sample size than what would be required for Mf testing . Additional studies will be needed to test the new proposed targets in different regions . We believe that these targets will be helpful for identifying areas that require continued surveillance . Existing guidelines do not adequately address this issue . Four options to consider are resumption of MDA , implementation of test and treat programs , vector control , and watchful waiting . It may be difficult to justify resumption of MDA when Mf rates are well below 1% when one considers that many of those with persistent infections may have been noncompliant with MDA in the past . Test and treat campaigns may be more efficient for finding and treating those with persistent infections than MDA , and the Sri Lanka AFC has started to do this in Galle district . Our results suggest that adult males and people who do not recall having taken MDA in the past should be considered to be high priority target groups for test and treat programs . WHO has recommended vector control as a post MDA strategy [26] . Although vector control can be difficult to implement at the scale needed for LF elimination , surveillance results may identify hot spot areas where focused vector control may be feasible . Our finding that CFA rates were lower in people who reported using bed nets is interesting , although the logistic regression analysis suggested that lack of bed net use was not an independent risk factor for filarial infection . Bed nets are popular in Sri Lanka because of the mosquito nuisance factor and the risk of dengue . Beneficial effects of bed nets for LF have been reported from areas with Anopheles transmission [27] , [28] . The Sri Lanka government should consider implementing a health education campaign to reinforce the popularity of bed nets and increase usage rates in areas with persistent LF . The longitudinal data from Peliyagodawatta are intriguing , because they suggest that some areas with filariasis parameters that do not meet our provisional criteria for interruption of transmission may spontaneously improve over time . Thus the strategy of watching , waiting , and retesting may be the best course of action for some areas with persistent LF . Other data from Peliyagodawatta on the natural history of filarial antigenemia in amicrofilaremic individuals in the post-MDA setting are reassuring . These results suggest that there is no pressing need to actively identify and treat asymptomatic and amicrofilaremic persons with positive filarial antigen tests following MDA . This is because the risk of such people developing microfilaremia is low , and antigenemia often clears over time without treatment . We believe that this study has contributed significant new information regarding post-MDA surveillance and low level persistence of filariasis following MDA . LF elimination is a dynamic process [29] , and point estimates of persistent infection may be less important than trends over time . For this reason , we plan to restudy Peliyagodawatta and several other PHIs with elevated LF parameters three years after the evaluations described in this publication . | Lymphatic Filariasis ( LF , also known as “elephantiasis” ) is a disabling and deforming disease that is caused by parasitic worms that are transmitted by mosquitoes . The Sri Lankan Anti-Filariasis Campaign provided five annual rounds of mass drug administration ( MDA ) with diethylcarbamazine and albendazole between 2002 and 2006 in all endemic areas ( districts or implementation units ) , and this reduced infection rates to very low levels in all sentinel and spot check sites . Transmission Assessment Surveys ( TAS , surveys for filarial antigenemia in primary school children ) performed in 2012–2013 ( about 6 years after the last round of MDA ) showed that all 11 evaluation units in formerly endemic areas easily satisfied a key World Health Organization target for LF elimination programs . More comprehensive surveillance was performed with other tests to assess LF parameters in 19 study sites in the same eight districts . We detected evidence of persistent LF in all districts and evidence of ongoing transmission in several areas . Exposure monitoring ( screening for anti-filarial antibodies in primary school children ) and molecular xenomonitoring ( detecting filarial DNA in mosquito vectors ) were much more sensitive than TAS for detecting low level persistence of filariasis in Sri Lanka . These methods are complementary to TAS , and they are feasible for use by some national filariasis elimination programs . Results from this study suggest that TAS alone may not be sufficient for assessing the success of filariasis elimination programs . | [
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] | 2014 | A Comprehensive Assessment of Lymphatic Filariasis in Sri Lanka Six Years after Cessation of Mass Drug Administration |
Dengue and malaria are two major public health concerns in tropical settings . Although the pathogeneses of these two arthropod-borne diseases differ , their clinical and biological presentations are unspecific . During dengue epidemics , several hundred patients with fever and diffuse pain are weekly admitted at the emergency room . It is difficult to discriminate them from patients presenting malaria attacks . Furthermore , it may be impossible to provide a parasitological microscopic examination for all patients . This study aimed to establish a diagnostic algorithm for communities where dengue fever and malaria occur at some frequency in adults . A sub-study using the control groups of a case-control study in French Guiana – originally designed to compare dengue and malaria co-infected cases to single infected cases – was performed between 2004 and 2010 . In brief , 208 patients with malaria matched to 208 patients with dengue fever were compared in the present study . A predictive score of malaria versus dengue was established using . 632 bootstrap procedures . Multivariate analysis showed that male gender , age , tachycardia , anemia , thrombocytopenia , and CRP>5 mg/l were independently associated with malaria . The predictive score using those variables had an AUC of 0 . 86 ( 95%CI: 0 . 82–0 . 89 ) , and the CRP was the preponderant predictive factor . The sensitivity and specificity of CRP>5 mg/L to discriminate malaria from dengue were of 0 . 995 ( 95%CI: 0 . 991–1 ) and 0 . 35 ( 95%CI 0 . 32–0 . 39 ) , respectively . The clinical and biological score performed relatively well for discriminating cases of dengue versus malaria . Moreover , using only the CRP level turned to be a useful biomarker to discriminate feverish patients at low risk of malaria in an area where both infections exist . It would avoid more than 33% of unnecessary parasitological examinations with a very low risk of missing a malaria attack .
Dengue fever and malaria - the two most common arthropod-borne diseases - are major public health concerns in tropical settings [1] , [2] . The dengue viruses ( family Flaviridae , genus Flavivirus ) and the Plasmodium parasites are widespread in American and Asian intertropical regions , where their endemic areas greatly overlap . Although their pathogeneses differ , their clinical and biological presentations are unspecific and it is difficult to distinguish the two infections . French Guiana is a French Overseas territory located on the northeastern coast of South America . About 90% of its 84 , 000 km2 surface is Amazonian rain forest . The remaining 10% in the north is a coastal plain where 90% of the 215 , 000 inhabitants live . Cayenne is the capital and represented almost half of the population in 2009 [3] . In French Guiana , dengue fever ( DF ) and malaria coexist , and are both frequent . Malaria is endemic with an annual number of cases ranging from 3 , 200 to 4 , 700 [4] ( Figure 1 ) . Until 2006 , P . vivax represented half of the total cases , but currently , the proportion of P . vivax malaria is 75% , similarly to other observations in Latin America [2] , [4] , [5] . Dengue fever is endemo-epidemic and the 4 serotypes ( DENV-1 , DENV-2 , DENV-3 and DENV-4 ) circulate . If the first cases of DF were reported in French Guiana in 1943 , an increase in the number of DF cases and outbreaks has been observed recently [6] . The two last main epidemics occurred in 2006 and 2009 , reaching a total of 14 . 000 estimated cases . During dengue epidemics , hundreds of consultations are held in the emergency department , and it is a real challenge for physicians to identify patients with a high risk of malaria among all those with dengue fever . Demographic criteria - that have never been evaluated - are commonly used to target those patients who should get a parasitological examination . The main objective of the study was to identify clinical and biological criteria to discriminate malaria from dengue fever in endemic areas . The secondary objective was to build a predictive score of malaria to guide the indication of parasitological examinations in case of a dengue epidemic . Thus , this study aimed to establish a diagnostic algorithm for communities where dengue fever and malaria occur at some frequency in adults .
A sub-study of a matched retrospective case-control study – designed to compare dengue and malaria co-infections to single infections – was performed between June 2004 and February 2010 at the Emergency Room ( ER ) of Cayenne Hospital in French Guiana [7] . In brief , the patients co-infected with dengue and malaria were exhaustively identified during the study period ( n = 104 ) and matched to 4 controls −2 with malaria only and 2 with dengue only – based on the date of the microbiological diagnosis . For the present study , we included the two groups of n = 208 mono-infected patients to compare those with malaria to those with dengue fever . Case definitions were based on compatible clinical history and positive biological diagnosis for one infection and negative for the other . The diagnosis of malaria relied on the identification of hematozoa on a thin blood film and/or on a thick blood film stained with Giemsa and a negative dengue test . During the study period , the diagnosis method for malaria diagnosis ( microscopic examination by an expert microscopist ) and parasitaemia evaluation remained unchanged . Thick and thin blood films were prepared within an hour of blood collection ( 4 ml of venous blood collected in an EDTA tube ) . They were stained with diluted Giemsa ( 1∶10 ) . Two hundred oil immersion fields of the thin blood film and 1000 white blood cells ( WBC ) on the thick smear were examined before classifying a slide as negative . The screening sensitivity was ∼6 plasmodia/µl ( assuming 8 , 000 WBC/µl of blood ) . At the time of the study period , malaria rapid diagnosis tests ( RDT ) were not routinely performed . Due to the evolution of the techniques between 2004 and 2010 , the laboratory diagnosis of dengue relied on different methods . Before 2006 , the diagnosis was based on direct virus isolation and genome detection by RT-PCR ( Reverse Transcriptase-Polymerase Chain Reaction ) . From 2006 , the hospital protocol was modified in accordance with evidence presented by Dussart et al . [8] , [9] and confirmed by a multinational prospective clinical study carried in South-East Asia and Latin America , in which the protocol was found to have good sensitivity [10] . NS1 antigen detection was thus performed from day 0 to day 5 , and indirect diagnosis based on detection of specific anti-dengue IgM antibodies in patients' sera was performed after day 3 [11] . On days 4 and 5 , both tests were made and associated to dengue RT-PCR . Eventually , 56 ( 26 . 9% ) patients were diagnosed using cell-culture virus isolation and/or RT-PCR , 84 ( 40 . 4% ) using NS1 antigen +/− IgM , 58 ( 27 . 8% ) using IgM , 9 using IgM+IgA , and one had IgM seroconversion . The proportion of dengue hemorrhagic fever ( DHF ) among all DF was not assessed , given the difficulties to establish the diagnosis of DHF retrospectively following the WHO 1997 definition ( positive tourniquet test , rising hematocrit , and elevated thrombocytopenia ) [12] . Individual data ( including socio-epidemiologic data , previous medical history , clinical symptoms , and biological results ) were retrieved anonymously from the computerized medical charts . Data were analyzed using R version 2 . 13 . 0 , the Epicalc package , and Stata 11 . 0 software ( Stata Corporation , College Station , USA ) . Continuous variables were categorized following laboratory or usual cut-off values . Because of the small sample size , they were generally dichotomized in order to preserve statistical power . A C-reactive protein ( CRP ) level ≤5 mg/L was considered as negative . Continuous variables were compared using matched Student t-test . Categorical variables were analyzed using the Wald test in matched bivariate analysis . Statistical significance was set at p<0 . 05 . Because of the unreliability of the data obtained retrospectively , variables obtained from anamnesis and clinical examination , and variables with >5% missing data were a priori excluded from the multivariate model . Remaining variables with p<0 . 20 in bivariate analyses were entered into a conditional multivariate logistic regression model . Conditional multivariate backward stepwise logistic regression was then performed to estimate the adjusted odds ratios ( OR ) and 95% confidence intervals ( 95%CI ) . All significant variables of the logistic model were used to determine a preliminary predictive score of malaria versus dengue . To improve model stability , a semi-external validation was performed using a . 632 bootstrap procedure [13] . Briefly , 1000 training and testing samples were generated . Medians and interquartile ranges of each β coefficient obtained from regression over the training samples were then reported . To assess the goodness-of-fit model , the AUC ( area under the receiver operating characteristic curve ) and its 95%CI were computed . Median β coefficients from the bootstrap procedure were then rounded to construct integer weights for each variable . The assigned weights were then summed to compute that patient's score . The intrinsic qualities of the score ( sensibility and specificity ) were then assessed using a classic bootstrap procedure . All analyses were performed using R software , version 2 . 13 . 0 , and Stata 11 . 0 software ( StataCorp ) . The retrospective use of anonymous patient files on the site of patient care is authorized by the French National Commission on Informatics and Liberties . All the data collected retrospectively were anonymized in a standardized case report form and in the database .
The 416 patients were mostly men ( 67 . 6% , sex ratio = 2 ) and had a median age of 30 . 7 years ( interquartile range ( IQR ) : 20 . 6–42 . 3; range: 0 . 4–86 years ) . Sixty-seven patients ( 16 . 1% ) were younger than 15 . Among the 208 malaria patients , 141 ( 68% ) were infected with P . vivax , 58 ( 28% ) with P . falciparum , and 8 ( 4% ) with both species . In the DF group , 140 ( 67% ) cases were early diagnosis ( NS1 antigen , RT-PCR or IgM seroconversion ) and 68 ( 33% ) were delayed diagnosis ( IgM ) . The results of serotyping were available for 91 patients , among whom 25 were infected by the DENV-1 ( 27 . 5% ) , 25 by the DENV-2 ( 27 . 5% ) , 28 by the DENV-3 ( 30 . 8% ) , and 13 by the DENV-4 ( 14 . 2% ) . Patients with malaria were significantly older than those with dengue ( 35 . 3 years ( ±15 . 4 ) vs . 28 . 0 years ( ±17 . 85 ) respectively; p<0 . 001 ) . Variables significantly associated with malaria were age ≥15 years , male gender , recent journey in the forest , and previous history of malaria . Residency on the coast was associated with dengue . Eventually , the clinical outcomes were favorable in both groups , as no deaths were reported . The malaria patients arrived in the ER later than those with dengue ( duration of the symptoms 5 . 1 days ( ±3 . 9 ) vs . 3 . 7 days ( ±2 . 4 ) , respectively; p<0 . 001 ) and were more often hospitalized . Tachycardia >90 bpm , fever ≥40°C , chills , malaise and/or dizziness , and splenomegaly were more frequent in malaria patients . Conversely , retro-orbital pain , ENT symptoms ( such as associated pharyngitis , otitis or sinusitis ) , and rash were associated with DF . However , there were no differences between the two groups in terms of blood pressure , signs of shock , fatigue , headaches , arthromyalgia , digestive disorders , dehydration , pallor , or jaundice . The mean platelet count was higher in patients with DF ( 198 . 109/L ( ±93 ) ) than in those with malaria ( 110 . 109/L ( ±55 ) ) respectively; p<0 . 001 ) . Thrombocytopenia <100 . 109/L , kidney failure , electrolyte abnormalities ( eg , hyponatremia , hypokaliemia , and acidosis ) and hyperbilirubinemia were significantly more frequent in malaria patients than in those with DF . An elevated CRP ( >5 mg/L ) was significantly associated with malaria ( p<0 . 001 ) . The proportion of patients with CRP>50 mg/L was 69 . 0% in P . falciparum infections , 58 . 7% in P . vivax infections , and 65 . 5% in patients infected with both species . There was no significant difference between the Plasmodia association and P . falciparum alone nor or between P . vivax and P . falciparum ( p = 0 . 420 and 0 . 170 respectively with Fisher's exact test ) for the proportion of high CRP level . Biological variables significantly associated with dengue fever were prolonged activated partial thromboplastin time ( aPTT ) , and elevated ALT levels . Finally , anemia , neutropenia , or lymphopenia did not differ between dengue and malaria patients . In matched multivariate analysis , male gender , age>15 years , tachycardia , anemia , thrombocytopenia and CRP>5 mg/l remained independently associated with malaria as compared to DF ( Table 3 ) . After 1000 resampling using a . 632 bootstrap procedure , the median β coefficients matching these prognostic factors were estimated . The median AUC was 0 . 86 ( 95% CI , 0 . 82; 0 . 89 ) , which indicates good model discrimination . The construction of the score is detailed in Table 3 . The median β coefficient of each prognostic factor was rounded to a weight of +1 , except for platelet count ( +2 ) and CRP level ( +9 ) ( Figure 2 ) . For each patient , the score was then obtained by summing the corresponding weights , and ranged from 0 to 15 . The sensitivity and specificity of the different cut-offs are presented in figure 3 . Placing the highest cost on failing to diagnose malaria , the cut-off of 10 was chosen to increase the sensitivity and design a screening test . Patients with a score <10 were at very low risk of malaria ( Figure 3 ) , with a sensitivity of 0 . 997 ( 95% CI , 0 . 995–1 ) and a specificity of 0 . 41 ( 95% CI , 0 . 32–0 . 50 ) . Negative and predictive values could not be estimated because the sample size had been pre-determined . Considering the large weight of the CRP>5 mg/L , sensitivity and specificity for this coefficient alone were estimated ( Table 4 ) . The sensitivity and specificity of CRP alone was of 0 . 995 ( 95%CI 0 . 991–1 ) and 0 . 35 ( 95%CI 0 . 32–0 . 39 ) , respectively .
In many tropical areas malaria and DF coexist . Due to the challenge posed by their similar clinical pictures in case of massive influx of patients with “dengue-like” syndrome during an epidemic of DF , a predictive score was built to target the patients with a high risk of malaria and who needed parasitological examination . To our knowledge the present study is the first to propose a simple and sensitive tool , the CRP level , to discriminate malaria from dengue fever . If it does not replace the microscopic examination , it helps to avoid one third of the unnecessary parasitological tests for patients at very low risk of malaria . In case of documented dengue , an elevated CRP level may lead to seek an associated diagnosis such as malaria or bacterial infection . | The authors present a retrospective matched-pair study on dengue and malaria performed in French Guiana . These two infections are major public health concerns in tropical regions , especially in South America and Southeast Asia , where they affect neglected populations which makes them interesting to be published in a journal aiming to publish about neglected tropical diseases . Although the pathogeneses of these two arthropod-borne differ , their clinical and biological presentations are unspecific . During dengue epidemics , hundreds of patients are admitted weekly with diffuse pains and fever at the emergency room . Among them , it is difficult to accurately distinguish malaria attacks , which are far less frequent than dengue fever cases . Moreover , it may be impossible to provide a parasitological microscopic examination for all patients . We believe the results of the present study , based on a sample of n = 416 individual are worthwhile as they support evidence that biological factors can help to discriminate between the two , in areas where they co-exist in endemic areas . A simple prognostic score based on clinical and biological criteria was built , interesting and easy-to-use for physicians in tropical areas . | [
"Abstract",
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"fa... | 2013 | Discriminating Malaria from Dengue Fever in Endemic Areas: Clinical and Biological Criteria, Prognostic Score and Utility of the C-Reactive Protein: A Retrospective Matched-Pair Study in French Guiana |
As the interface between a microbe and its environment , the bacterial cell envelope has broad biological and clinical significance . While numerous biosynthesis genes and pathways have been identified and studied in isolation , how these intersect functionally to ensure envelope integrity during adaptive responses to environmental challenge remains unclear . To this end , we performed high-density synthetic genetic screens to generate quantitative functional association maps encompassing virtually the entire cell envelope biosynthetic machinery of Escherichia coli under both auxotrophic ( rich medium ) and prototrophic ( minimal medium ) culture conditions . The differential patterns of genetic interactions detected among >235 , 000 digenic mutant combinations tested reveal unexpected condition-specific functional crosstalk and genetic backup mechanisms that ensure stress-resistant envelope assembly and maintenance . These networks also provide insights into the global systems connectivity and dynamic functional reorganization of a universal bacterial structure that is both broadly conserved among eubacteria ( including pathogens ) and an important target .
The bacterial cell envelope serves as a resilient macrostructure and permeability barrier that protects microbes from osmotic stress , xenobiotics and environmental insults while supporting cell morphology and transport of essential nutrients and waste . For Gram-negative species like Escherichia coli , the cell envelope consists sequentially of a phospholipidic inner membrane ( IM ) , a peptidoglycan ( PG ) cell wall embedded in aqueous periplasm , and an outer membrane ( OM ) composed of phospholipids and lipopolysaccharide ( LPS ) . Unique sets of proteins determine the functional identity of each of these compartments under physiological demand [1] , [2] . These include diverse outer membrane proteins ( OMP ) such as β-barrel porins that mediate cell adhesion and passage of small molecules , inner membrane proteins ( IMP ) involved in active transport and adaptation to changing growth conditions , and soluble periplasmic enzymes and membrane-tethered lipoproteins that process metabolic precursors required for envelope assembly . Proper expression , transport and activity of these envelope-associated proteins is critical to bacterial cell viability , morphology and stress-resistance [3] . The cell envelope also plays a crucial role in bacterial pathogenesis [3] . One-quarter of prescription antimicrobials are currently directed against proteins involved in envelope biogenesis [4] , including classical antibiotics such as the β-lactams ( e . g . penicillin ) and modern ‘last resort’ glycopeptide drugs like vancomycin . Yet despite the emergence of widespread clinical resistance , few new therapeutics targeting the bacterial cell envelope have been developed over the past two decades due in part to the extraordinary functional robustness of this structure [5] . The utility of combination therapies targeting redundant pathways as an alternate clinical strategy [2] underscores the need to identify functional dependencies among essential envelope bioprocesses that contribute to envelope formation , stability and drug tolerance . Cell envelope biogenesis has been studied extensively in E . coli [3] , including investigations of individual genes and pathways involved in the biogenesis of fatty acids [6] , cell wall [7] , LPS [8] and OMP [9] . Yet important gaps still exist in the understanding of the global mechanisms that ensure faithful envelope assembly and integrity under different growth conditions or in response to antibiotic challenges [3] . New components of envelope assembly pathways continue to be discovered [10] , [11] , [12] , [13] , yet nearly one-third of the membrane proteins of E . coli are currently functionally unannotated likely in part due to incomplete or biased historical experimental analyses [1] , [2] , [14] . Moreover , most ( >90% ) of the annotated biosynthetic genes of E . coli are dispensable for viability under standard laboratory culture conditions [15] . This redundancy , which presumably reflects in part a robust modular systems level organization [16] , has hindered both functional annotation [2] and antibiotic development using traditional single gene/target-centric approaches [17] . Unbiased genetic screens can reveal unexpected functional dependencies between genetic loci ( i . e . epistasis , wherein the phenotypic effects of mutation of one gene are modified by one or more other genes ) . For example , aggravating ( negative ) genetic interactions , manifesting as synthetic sickness or lethality , often result from loss-of-function mutations in pairs of genes in parallel or compensatory pathways that impinge on a common essential process [18] . Conversely , alleviating ( positive ) interactions can occur between genes in the same pathway if the loss of one gene alone inactivates the pathway such that loss of a second gene confers no additional defect [18] . Large-scale genetic screens in yeast have outlined the tightly integrated functional organization of essential biological systems [19] , [20] , and global network rewiring in response to environmental stress causing DNA damage [21] . No analogous systematic surveys have yet been reported for bacteria , and only ad hoc genetic studies on a few select components of the E . coli cell envelope have been reported to date [22] . As a result , the degree of functional redundancy , connectivity and modularity among the biosynthetic pathways supporting envelope assembly and maintenance remains unclear . Such knowledge is paramount for targeting envelope systems resistant to existing antibiotics . To this end , we applied our high-throughput synthetic genetic array ( eSGA ) screening technology [23] in a comprehensive manner to identify and quantify epistatic relationships between all known and predicted components of the cell envelope biosynthetic machinery of E . coli during growth in both auxotrophic and prototrophic culture conditions . Unbiased scoring and filtering of the resulting genetic data revealed condition-specific genetic interaction networks required for the proper formation and integrity of the OM , cell wall , and LPS , and functional dependencies mediating membrane protein secretion and cell division , which were verified independently . These functional association maps provide a unique perspective into the global functional architecture and dynamic rewiring of widely-conserved envelope bioprocesses critical to bacterial morphology , fitness and environmental adaptation . All of the data are publicly-accessible as a community resource via a dedicated web portal .
Using a quantitative screening format originally developed to investigate pathway crosstalk in yeast [20] , we performed 821 high-density eSGA screens to examine the fitness of all possible digenic mutant combinations of hypomorphic alleles ( i . e . partial loss of gene function ) of 128 essential biosynthetic genes and single-gene deletions of 683 non-essential protein-coding envelope genes and 10 small non-coding regulatory RNAs ( sRNA ) linked to post-transcriptional regulation of cell surface protein expression ( Figure 1A , see Protocol S1 ) . Target inclusion was based on an exhaustive survey of the literature and databases of envelope-related biosynthetic pathways and gene annotations [1] ( Table S1 ) . Targets came from 20 representative bioprocesses ( Figure 1B ) , including 363 integral membrane proteins ( 66 OMPs , 297 IMPs ) , and consisted of three basic types: Group 1 ( Annotated ) , comprising 357 core biosynthetic genes ( ‘building block’ enzymes ) with experimental evidence supporting direct involvement in a specific step of an annotated envelope biogenesis pathway or bioprocess; Group 2 ( Uncertain Function ) , encompassing 286 genes , where existing experimental evidence indicates a role in envelope biogenesis but without certainty as to a particular pathway or bioprocess; Group 3 ( Predicted ) , comprising 178 unannotated genes predicted to participate in envelope biogenesis based on protein-protein interactions , genomic context inferences [14] , or tentative EcoCyc , Gene Ontology ( GO ) or GenProtEC assignments . Despite significant differences in bacterial morphology and envelope composition ( e . g . Gram-positives versus Gram-negatives ) , many of these genes are broadly evolutionary conserved consistent with fundamental roles in cell envelope biology beyond E . coli ( Figure S1 and Table S2 ) . Following the conjugation of single mutant strains and genetic transfer ( Figure 1C ) , double mutants were first plated as replicate arrays onto solid agar containing rich ( Luria Broth ) medium . After outgrowth for 24 hrs at 32°C , viable stationary phase colonies were then replica pinned onto minimal ( M9 ) medium to identify additional genetic interactions under limiting nitrogen and carbon levels ( Figure 1C ) . Both sets of plates were digitally imaged , and colony sizes measured and normalized to account for experimental variation ( see Protocol S2 and S3 ) . Screen reproducibility was uniformly high ( r typically >0 . 8; Figure S2A ) and comparable to high-quality quantitative genetic interaction screens reported previously for yeast [19] , [20] . Although the Hfr donor strain is not isogenic with the BW25113 KEIO deletion mutant strain background , a pilot test set of 30×30 conjugations showed that the growth rates of double mutants produced by crossing 30 diverse F- ‘recipient’ strains from the Keio collection [15] with the corresponding set of 30 ‘donor’ mutants in either an Hfr C or an isogenic strain background were comparable ( r = 0 . 7; Figure S2B ) . Digenic mutant fitness was estimated using an established multiplicative model [19] which reports both the strength and confidence of genetic interactions between any two genes ( see Protocol S4 ) . Briefly , if two genes are functionally unrelated , the growth rates of the respective single mutations are predicted to combine in a simple multiplicative manner in the double mutant; significant deviations from this expected fitness imply a functional association [18] . The resulting E-scores of the double mutants on both rich medium and minimal medium ( Table S3 ) showed a bimodal distribution ( Figure S2C ) , with the major peak approximating a normal distribution centered on neutrality , confirming the expectation that genetic interactions are relatively uncommon ( i . e . limited to only certain gene pairs ) . Positive E-scores suggestive of alleviating interactions ( double mutants grew more rapidly than expected ) were found in the right tail of the distributions , reflecting factors operating in the same pathway [24] , while aggravating interactions ( double mutants grew more slowly than expected ) occurred in the heavy left tail , with a prominent peak of highly negative E-scores representing gene pairs exhibiting synthetic lethality [19] . Genetic interactions by a given biogenesis gene reflect its functional associations with other envelope components and thus serve as a high-resolution phenotype . We applied a statistical framework to define suitable E-score cutoffs to derive biologically-relevant interactions by minimizing the false discovery rate . Specifically , we evaluated the extent to which pairs of envelope genes involved in different biogenesis bioprocesses showed significant ( p-value≤0 . 05 ) enrichment at various E-score values . Enrichment increased progressively as the E-score threshold was raised ( Figure S2D ) , reaching a maximum at −2 ( aggravating interactions ) and +2 ( alleviating interactions ) . We used these apex values ( E≤−2 , E≥2 ) as cutoffs , and assigned p-values using a null distribution background ( see Methods ) . Strikingly , the patterns of genetic interactions found in rich and minimal ( Table S3 ) medium were markedly different , reflecting a profound reorganization in the envelope biogenesis machinery . For example , although more highly connected on average than non-essential genes ( Figure S2E and S2F ) , essential genes exhibited a higher ratio of alleviating interactions ( p-value = 1 . 22×10−50 ) in rich medium ( Figure 2A , Figure S3A , Protocol S5 ) . Conversely , aggravating interactions were far more common ( p-value = 3 . 70×10−57 ) for essential genes in minimal medium ( Figure 2A ) , suggesting compensatory relationships emerge under environmental constraint ( i . e . nutrient limitation ) . The likelihood of a genetic interaction by any one particular envelope biogenesis gene in either condition was correlated both with gene essentiality and mRNA expression levels in culture ( Figure S3B ) . As with yeast [19] , [25] , essential genes producing abundant transcripts had significantly more aggravating interactions , while envelope factors with multiple annotated functions suggestive of pleiotropy were more likely to display synthetic lethality ( Table S4 ) . To independently gauge the accuracy of these networks , we examined the screen results obtained for 62 gene pairs reported previously to exhibit aggravating ( 53 pairs ) or alleviating ( 9 pairs ) phenotypes . In total , we correctly captured two-thirds ( 63% ) of the published GI ( Figure 2B and Table S5 ) , which is statistically significant ( p-value<0 . 05 by random sampling; Figure 2C ) . For example , the rich medium network recapitulated aggravating interactions between the periplasmic chaperone surA and the β-barrel protein assembly machinery ( BAM ) [26] and a functionally redundant chaperone skp [27] . Conversely , the minimal medium network captured the conditional synthetic lethality reported between cell division proteins zapB and ftsZ [28] . Half ( 10 of 23 ) of the discordant gene pairs were found using different growth conditions in the literature ( Table S5 ) , reinforcing the notion of conditional-dependency . Many components of the cell envelope biosynthetic machinery are predicted to be functionally-associated based on physical association ( Figure S4A ) , transcriptional co-expression ( Figure S4B ) , and/or genomic context ( Figure S4C ) . Consistent with this , cell envelope genes with positively correlated genetic profiles were more likely to be present within the same operon in E . coli compared to random pairs of genes ( Figure 2D ) , consistent with the natural chromosomal clustering of functionally-related genes in bacteria [29] . For example , components of the fec Fe-enterobactin uptake system were correlated in rich medium ( Figure 2D ) , consistent with joint participation in the import of cellular iron [30] . Similarly , the genetic interaction patterns of the LPS 1 , 2-glucosyltransferase components of waa operon ( formerly rfa ) were correlated in minimal medium ( Figure 2D ) , consistent with the coordinated role in LPS core biosynthesis [31] . Likewise , pairs of co-expressed envelope genes also tended to show more positively correlated genetic interaction profiles ( Figure 2E ) . For example , the genetic interaction profiles of the co-expressed cytochrome bo terminal oxidase subunits ( cyoC , cyoD ) were correlated in rich medium ( r = 0 . 53; Figure 2E ) , reflecting elevated aerobic respiration . In contrast , the genetic interaction patterns of the co-expressed cell division components ( minD , minE ) were closely correlated in minimal medium ( r = 0 . 51; Figure 2E ) , consistent with the cooperative role in modulating the division potential of cellular sites located at mid cell and at the cell poles [32] . As in yeast [19] , [20] , envelope biogenesis factors with highly correlated genetic profiles were also significantly more likely to be connected by protein-protein interaction ( PPI ) ( Figure 2F ) . For example , the genetic profiles of two transporters ( mdtI , mdtJ ) that form a heterodimeric complex required for spermidine excretion [33] were highly correlated in rich medium ( r = 0 . 65; Figure 2F ) . The profiles of mdtJ/mdtI were also similar to other translocases linked to multidrug resistance such as resistance-nodulation-cell division , major facilitator , and ATP-binding cassette proteins ( Figure S5 ) . Conversely , the genetic profiles of ftsE and its interacting partner ftsZ , which are required for assembly of the cytokinetic Z-ring [34] , were closely correlated in minimal medium ( r = 0 . 60; Figure 2F ) . We concluded that the filtered networks reliably captured functional dependencies , and hence could be used to infer biologically-relevant relationships . For example , the genetic profile of the recently characterized OM lipoprotein ycfM/lpoB was similar to that of the penicillin binding protein mrcA under both rich and minimal conditions ( Table S6 ) , consistent with a recently proposed role as joint regulators of PG synthesis [12] . Having established that the genetic maps were informative about biological relationships at the level of individual envelope components , multiprotein complexes and biosynthetic pathways , we explored the global functional connections linking envelope bioprocesses in the two networks ( Table S7 and S8 ) . Using functional enrichment analysis ( see Materials and Methods ) , we identified significant ( p-value≤0 . 05 ) crosstalk ( elevated patterns of aggravating or alleviating interactions ) between bioprocesses ( Figure 3A ) . We found that certain patterns were prevalent in both culture conditions ( Figure 3A ) . For example , aggravating interactions were prominent ( p-value≤0 . 05 ) between the oligopeptide transport , cell wall , cell shape and cell division machineries , consistent with the tight integration of these bioprocesses . As bacteria proliferate , the murein sacculus elongates in such a way that the distinctive rod shape of E . coli is maintained [7] . Murein peptides liberated by dynamic degradative recycling of the cell wall are actively imported for reuse by multiple reuptake systems [7] . Defective oligopeptide transport exacerbates slow growth and morphological deficiencies [7] , which is reflected in our genetic networks . In some cases , this crosstalk was unexpected . For example , Figure 3B shows a sub-network of aggravating interactions between the pathways generating colanic acid ( CA ) , an exopolysaccharide ( also known as M-antigen ) produced by E . coli K-12 in response to hypotonic conditions or membrane perturbations [35] , and the pathways responsible for producing the cell wall , LPS and enterobacterial common antigen ( ECA ) , another surface glycophospholipid [36] . This crosstalk presumably reflects use of shared metabolic intermediates . For example , UDP-N acetylglucosamine is required for biosynthesis of ECA , LPS ( lipid A ) and PG in E . coli [36] . While disturbances in envelope integrity can lead to increased CA synthesis via activation of the Rcs regulon [37] , defects in LPS formation do not affect CA expression under standard laboratory growth conditions [38] , and dependencies between these systems have not been reported before [37] . To verify our results , we challenged CA mutants with amoxicillin and phosphomycin , antibiotics , which block cell wall/PG biogenesis , or with polymyxin B , which targets the lipid A component of LPS [2] . Consistent with our genetic data , CA strains were nearly as hypersensitive to the compounds as mutants deficient in cell wall and LPS formation ( Figure 3C ) . A synergistic inhibitory effect was also observed when CA/LPS double ( wcaB lpxA ) mutants were challenged with amoxicillin and polymyxin B simultaneously ( Figure 3D ) . Collectively , these data indicate that an underlying functional coordination ( direct or indirect ) of envelope glycoconjugate production is essential to sustain envelope integrity . Comparison of the two networks revealed differential physiological demands placed by the two culture conditions . For instance , alleviating interactions were preferentially detected in rich medium ( p-value = 1 . 42×10−3; Figure 3A ) between the pathways producing fatty acids and chorismate , the last branch point of the shikimate pathway that produces aromatic amino acid precursors . When amino acid pools exceed the requirements for protein synthesis , surplus aromatic precursors are directed towards fatty acid biosynthesis [39] . Hence , the lipid composition of the bacterial cell envelope reflects the combined output of both the shikimate and fatty acid pathways , which is mirrored as an alleviating phenotype during double mutant growth in abundant nutrient conditions . Conversely , alternate selective pressures were placed on envelope biosynthetic pathways in minimal medium , where aggravating interactions became more pronounced ( p-value = 9 . 4×10−4 ) between the cell division ( Fts ) and protein secretion ( Sec ) systems ( Figure 4A ) . For example , SecY and Ftsk mutants showed alleviating interactions on rich medium , but synthetic lethality on minimal medium . This differential dependency was confirmed by liquid culture growth curve assays ( Figure 4B ) . The genetic interaction profiles of cell division and secretion mutants were also more highly correlated on minimal medium than rich medium ( Figure 4C ) . Genes exhibiting alleviating interactions are more likely to encode proteins that are physically associated [40] . Consistent with this , we found that affinity purified endogenous Fts interacts physically with the Sec export apparatus ( Figure 4D , see Methods ) , implicating the Sec translocon directly in targeting of critical cell division determinants . Protein secretion is an important determinant of nutrient import , and is known to be slowed along with cell division when bacteria are grown with limiting nutrients , favoring cell elongation [41] . Moreover , the cell surface localization of several Fts septation proteins including the essential ftsI protein ( penicillin-binding protein 3 ) with a membrane spanning segment is one such process that requires sec translocon gene functions for correct membrane integration [41] , [42] . Consistent with this , cell division/secretion double mutants formed exaggerated filamentous cell aggregates in minimal medium , whereas this phenotype was rescued by growth in rich medium ( Figure 4E and 4F ) , suggesting transport of essential cleavage factors is limiting in nutrient-poor conditions . Using a variant of differential interaction network strategy [21] , slightly over 1 , 400 gene pairs showed contrasting genetic interactions in rich versus minimal medium ( Table S9 , Protocol S6 ) . These differential interactions were enriched significantly ( p-value≤0 . 05 ) for genes functioning in cell division , chromosome segregation and protein secretion pathways ( Figure S6A ) . For example , annotated murein amidases ( e . g . amiABC ) involved in septum splitting , and cell division proteins localized to the membrane-associated ring structure ( e . g . ftsAEKHLQXYZ ) showed differential interactions ( i . e . aggravating in minimal and alleviating in rich medium ) ( Figure S6B ) . Conversely , we observed significantly fewer differential interactions ( p-value≤0 . 05 ) among genes annotated to fatty acid degradation , stress response and chaperone pathways ( Figure S6A ) , suggesting that functional connections between these genes remains to a larger extent unchanged . Since functionally-related genes often have similar genetic profiles [19] , [20] , [40] , the biological roles of incompletely characterized components can potentially be inferred based on correlation to annotated components . An illustrative example is a sub-network of strong alleviating interactions found in rich medium between the unannotated genes yceG and yebA and with several well-known cell division PG hydrolases ( Figure 5A ) , each with distinct domain-architectures ( Figure 5B ) . Binary fission in E . coli and other Gram-negatives depends on localized cell wall assembly at the division site by PG synthases e . g . , penicillin-binding proteins [43]; subsequent splitting of these septa by PG hydrolases is required for cell division [44] , [45] . Consistent with our genetic data , ultrastructure analysis revealed impaired membrane invagination and cytokinesis in yebA and yceG mutants ( Figure 5C ) , with chains of daughter cells connected by uncleaved septa ( Figure 5D and Figure S7A ) . Over-expression of either factor in trans fully rescued the phenotype ( Figure 5D ) . Single yebA and yceG mutants also showed reduced sensitivity to ampicillin ( Figure 5E ) , which blocks PG assembly , whereas wild-type E . coli rapidly lyse due to imbalanced PG hydrolase activity [44] . Consistent with joint promotion of septal PG splitting , growth curve assays confirmed an alleviating interaction between yebA and yceG in rich medium ( Figure 5F ) . A sub-network of strong aggravating interactions was also found in rich medium ( Figure 6A and 6B ) , linking 3 unannotated genes ( one encoding a putative β-barrel protein , ytfN and the other two lipoproteins , yfgH , yceK ) to the lptDE complex involved in the final stages of LPS assembly at the OM outer leaflet [46] . Since impaired LPS destabilizes the envelope integrity [10] , we challenged the mutant strains with vancomycin , an inhibitor of PG formation normally excluded by the intact OM of Gram-negatives [47] . Unlike drug-resistant wild-type E . coli , vancomycin induced morphological defects manifested by prominent mid-cell membranous bulges in single mutants and cell wall failure/lysis in double mutants ( Figure 6C ) . Impaired OM integrity was also evident by drug hypersensitivity ( Figure 6D ) , lowered OMP abundance ( Figure 6E ) , and elevated levels of the σE-stress response DegP protease [10] . Taken together , these data point to the tight participation of yfgH , yceK , ytfN in LPS/OM formation and OM integrity Another envelope gene of uncertain function , yhjD , which encodes a putative IMP with ( 5–6 TMH ) previously implicated in Lipid A precursor IVA transport [48] , showed a similar genetic profile ( Table S6 ) and alleviating interactions ( Figure 7A and 7B ) with components of the lptBCFG complex that extracts LPS intermediates from the IM for passage to the OM [49] , and aggravating interactions with other LPS transport factors ( Figure S7B and S7C ) . Mutant lptBCFG strains have morphologically perturbed envelopes [10] , [50] . Transmission electron microscopy ( TEM ) likewise revealed a defective ultrastructure , membranous projections and periplasmic bodies characteristic of compromised LPS transport in strains lacking yhjD ( Figure 7C ) . Like lptBCFG mutants [10] , [50] , strains lacking yhjD also showed an activated DegP stress response and accumulated intracellular lipid A precursors whereas OMP abundance was not affected ( Figure 7D ) . Consistent with the alleviating epistasis , these defects were not exacerbated in yhjD lptBCFG double mutants . Since alleviating interactions arise with in pathways or physical complexes [40] , we affinity purified endogenous YhjD from detergent solubilized E . coli cell extracts to identify stably associated proteins ( see Methods ) . As shown in Figure 7E , YhjD co-purified specifically with LptB , consistent with association as a multiprotein complex . Moreover , recombinant YhjD also bound selectively to core-lipid A ( rough LPS ) in vitro ( Figure 7F ) . Since site-specific suppressor mutation in YhjD has been shown to reduce the toxic-side effects of lipid IVA accumulation by rendering the LPS transporter MsbA critical for lipid IVA trafficking [48] , it is conceivable that the deletion of YhjD eliminates the buildup of toxic lipid A intermediates in lptBCFG mutants , resulting in alleviating phenotype . Antisense sRNAs regulate gene expression by base-pairing to mRNAs via imperfect complementarity [51] , often in response to environmental contingency such as stationary phase cells in nutrient rich medium or in minimal medium challenge [52] , [53] . We therefore examined the genetic interactions of the 10 sRNAs in our networks ( cyaR , dicF , gcvB , micA , micC , micF , omrA , oxyS , rybB , sgrS ) with both verified and computationally-predicted targets ( Table S10 ) . Cognate target-regulator pairs showed predominantly alleviating phenotypes under both culture conditions ( Figure 8A ) . For example , oxyS with both the OM lipoprotein ybaY [54] and cls , which encodes cardiolipin synthase , whose levels are both significantly elevated in E . coli mutants lacking oxyS in rich and minimal medium ( Figure 8B ) . However , condition-specific regulator-target relationships were also observed consistent with differential sRNA activity ( Figure 8B ) . For instance , alleviating interactions were preferentially observed in rich medium between gcvB and mtr stationary phase culture cells , which encodes a tryptophan-specific permease feedback inhibited via the Trp repressor [55] , and oppA , which encodes a periplasmic oligopeptide transporter . Deletion of gcvB causes constitutive expression of oppA [56] , which is normally repressed in nutrient-rich conditions . Similarly , omrA displayed an alleviating phenotype in rich medium with iron transporters ( fecCDE ) . Although essential for growth , iron is toxic and its import is tightly control [57] . Conversely , the regulators micC and oxyS displayed alleviating interactions with certain targets preferentially in minimal medium ( Figure 8A ) , implying repression is lost in nutrient-limiting conditions . We confirmed that the mRNA levels of ompW and entB increase substantively in minimal medium in micC and oxyS , mutants , respectively ( Figure 8B ) . Collectively , these results demonstrate how quantitative genetic interaction maps can be used to probe regulatory relationships orchestrating cell envelope homeostasis .
The cell envelope forms an essential interface between a microbe and its environment , or host in the case of pathogens . While E . coli has clearly evolved well-developed adaptive mechanisms to withstand diverse perturbations [2] , our genetic results show that the K-12 laboratory isolate is unable to compensate for the loss of different combinations of individual cell envelope components and bioprocesses in culture . We have provided diverse lines of evidence supporting the unexpected biological participation of multiple novel factors in disparate core envelope processes . While additional follow-up mechanistic studies are warranted , the genetic interaction networks serve as a valuable resource for gleaning mechanistic and cell biological insights into E . coli envelope bioprocesses at the gene , pathway and physiological level . These genetic interactions networks also inform on the global modular biological architecture of the bacterial cell envelope biosynthetic machinery , and its pronounced re-organization as an adaptive environmental response . Although our screens missed additional cases of epistasis emergent under alternate growth or stress conditions , the size and scope of the genetic map provides a fresh perspective into the functional interplay between convergent and compensatory systems that collectively ensure cell envelope assembly and integrity under two commonly studied culture conditions . The functional relationships we detected extend beyond established biochemical pathways and metabolic fluxes , and are consistent with the recently introduced notions of conditional and induced essentiality [58] and the substantive rewiring of genetic interaction networks in yeast following genotoxic stress [21] . Although the evolutionary basis for these emergent systems properties is unclear , it suggests a ubiquity of dynamic bioprocess crosstalk among microbes [3] . E . coli has an envelope architecture that is very similar to that of infectious species like Salmonella enterica ( serovar Typhimurium ) , Pseudomonas aeruginosa and Neisseria meningitidis . Just as genetic screens in model eukaryotes have facilitated the characterization of conserved disease-related biological systems in humans [18] , the generation of genetic interaction maps for E . coli suggests functional vulnerabilities that could potentially be exploited to combat these and other pathogens . For example , the coupling of cell wall and LPS glycoconjugate production we observed implies that a new family of peptidomimetic antibiotics ( e . g . protegrin ) targeting LPS assembly in P . aeruginosa [59] might be potentiated by inhibitors of either PG assembly or exopolysaccharide virulence factors analogous to CA in E . coli . To facilitate exploration of these connectivity maps , our datasets are publicly accessible via a dedicated web portal ( http://ecoli . med . utoronto . ca/eMap/CE/ ) . The fact that a wide breadth of biological information could be derived from a defined collection of double mutants using a simple measure of colony growth provides strong motivation for future efforts aimed at examining other bacterial traits of broad biological , clinical and pharmacological significance .
E . coli cell envelope gene targets suitable for screening were compiled based on published functional studies and database surveys [1] , pathway annotations in EcoCyc , and relevant GO and GenProtEC annotations . Literature curated genetic interactions were manually compiled from low-throughput experimental studies . To generate functional association networks ( see Protocol S7 and S8 ) , high-quality E . coli PPI curated in the eNET , BIND , DIP , IntAct and MPI_LIT databases were compiled; microarray based mRNA transcript profiles were downloaded from the M3D database to derive a network of co-expressed genes based on correlation; and functional connections inferred by genomic context methods were computed as reported before [14] . Metabolic networks were reconstructed using Ecocyc annotations . Bacterial strains and plasmids used in this study are listed in Table S11 . The F- ‘recipient’ single gene deletion mutants were from the Keio knock-out strain collection [15] , marked with kanamycin resistance ( KanR ) , and from the recently developed ASKA single-gene deletion mutant library ( Yamamoto et al . , unpublished data ) marked with chloramphenicol-resistance ( CmR ) . Donor mutant strain construction , conjugation and imaging was performed essentially as described [23] . Briefly , to construct Hfr Cavalli ( Hfr C ) donor knockout mutants , λ-Red recombination was used to replace the entire coding sequence of each open reading frame of non-essential genes with a drug selection marker , whereas the selection cassette was integrated into 3′-UTR of essential genes to perturb transcript abundance [23] . In total , 505 ‘query’ gene mutations in Hfr C were systematically transferred via conjugation to an arrayed collection of 714 F- ‘recipient’ knockout and hypomorphic mutant strains [23] . Robotic colony pinning and drug selection procedures are detailed in Protocol S2 . An “Hfr” donor ( marked with KanR ) isogenic with the E . coli single-gene deletion knock libraries was constructed for testing essentially as described [60] . Plate image processing and colony size quantization were adapted from an automated image processing system originally devised for yeast [61] . Epistasis scores were calculated based on a multiplicative model [61] where a GI between a pair of genes ( i , j ) is identified if the fitness phenotype of the double mutant ( Wij ) deviates significantly from that predicted for non-interacting gene pairs ( Wi×Wj ) . Enrichment was determined by contrasting the frequency of observed genetic interactions between or within functional modules against the expected frequencies according to the hypergeometric distribution using the Fisher's exact test [62] with correction for multiple hypothesis testing [63] . This enrichment approach was used to determine the optimal E-score cutoff values for selecting aggravating and alleviating genetic interactions . Additional details are provided in Protocols S2 , S3 , S4 , S5 , S6 , S7 . Computational prediction of regulatory sRNA targets was performed using RNAup [64] from the Vienna RNA package ( -Xp-w20-b parameters ) to measure sequence complementarity between each sncRNA and the 5′ regions ( −50 and +50 nt relative to translation start site ) of all protein coding genes in E . coli . Genes were ranked according to free energy , with the lowest scoring predicted as targets . Known mRNA targets were compiled from published functional studies and the NPInter and sRNAMap databases . Immunoblots were probed with polyclonal ( LptD , OmpA , LamB , DegP ) or monoclonal ( MBP , LPS , His epitopes ) antisera . Hexahistidine ( His6 ) -tagged E . coli LptB or LolE fusion protein were expressed using an IPTG inducible promoter from a high copy pCA24N plasmid [65] . Sequential peptide affinity ( SPA ) tagging and purification of Fts , Sec and YhjD was performed essentially as previously described [66] . The affinity-purified proteins were subjected to gel-free liquid chromatography-electrospray-linear ion trap tandem mass spectrometry ( LC-MS ) to identify the stably and weakly associated interacting proteins with high sensitivity . Spectral searches were performed against a database containing complete set of E . coli protein-coding sequences and filtered for high-confidence matches essentially as described [66] . Details of the immunoprecipitation are provided in Protocol S9 . For growth curve analyses , overnight cultures were inoculated into 100-well microtitre plates containing 100 µl of liquid medium , incubated with shaking at 32°C for over 24 hrs with optical density ( 600 nm ) measured every 15 min using an automated Bioscreen-C ( Thermolabsystems , Helsinki , Finland ) . For drug assays , overnight E . coli cultures in liquid LB medium were serially diluted and pinned onto solid LB agar plates in the absence or presence of drug ( see Protocol S10 ) . To examine cell morphology , strains were grown to log-phase ( A600∼0 . 5 ) in LB medium at 32°C; 30 min prior to imaging , cultures were treated with vancomycin hydrochloride ( 1 . 5 µg/ml ) . Cell structures were stained using membrane dye FM4-64 ( Molecular Probes; 1 µg/ml ) or of DAPI/ml ( 250 ng/ml ) , and 1 . 5 µl of cell suspension was spotted onto a glass slide for microscopy . Digital images were captured using a Quorum WaveFX Spinning Disc Confocal System . Cell length was measured using the Volocity program ( Improvision Ltd . ) . For drug interaction assays , drugs were tested over varying concentration ranges . The minimum inhibitory drug concentration was deemed to substantially reduce the growth rate by at least 20–50% relative to a no-drug control . Drug combinations were compared to single drugs using an isobologram on an arithmetic scale . For further details , see Protocol S11 . The in vitro LPS purification and binding assay was based on an approach reported previously [67] . Total soluble LPS was separated by SDS-PAGE and examined by silver staining ( see Protocol S12 ) . Defects in OM protein biogenesis were assayed as previously described [26] . To assess ampicillin sensitivity , overnight cultures were diluted in fresh LB and grown at 32°C to an OD600 of ∼0 . 6 . The cells were then diluted 1∶3 in fresh LB medium with or without 5 µg of ampicillin/ml and growth continued at 32°C , with OD600 measured every 20 min . Cells were fixed with 2% glutaraldehyde in 0 . 1 M sodium cacodylate buffer overnight , post-fixed with 1% osmium tetroxide , dehydrated in a graded ethanol series followed by absolute propylene oxide , and embedded in Quetol-Spurr resin . Sections ( 90 nm thick ) were cut on a RMC MT6000 ultramicrotome , stained with uranyl acetate and lead citrate , and viewed on a FEI CM100 TEM . To measure mRNA levels , target RNA was isolated from stationary phase mutant cultures grown in rich or minimal medium using standard hot phenol extraction procedure , followed by DNase I treatment . cDNA was synthesized from ∼0 . 5 µg total RNA using iScript™ cDNA synthesis kit with SYBR green supermix ( Bio-Rad ) following the manufacture's protocol . Primer sequences used for qRT-PCR were as follows: forward primer of cls gene , 5′ GATTATATTTCGCGTTCACGTCTG-3′ , reverse primer of cls gene , 5′-TCCGACTAACGGCAGAATGTAA-3′; forward primer of ybaY gene , 5′ATTACCGTGAATGACAAACTGGTA-3′ , reverse primer of ybaY gene , 5′- CAGGTTGTTGTGTTGCTGAAATAG-3′; forward primer of mtr gene , 5′- TCTGCATCACACCTTCGCAGAGAT-3′ , reverse primer of mtr gene , 5′-TTACGCCAAGGAACGAACTCGCTA -3′; forward primer of ompW gene , 5′-GCGGCTTTGGCAGTAACAACTCTT-3′ , reverse primer of ompW gene , 5′-TGATGAACGGTTGCAATATCGCCG-3′; forward primer of entB gene , CGCGACTACTGCAAACAGCACAAT-3′ and reverse primer of entB gene , 5′-ATCAGGTTGTCGTCATCGAACGGT-3′ . A primer set specific to glutathione S- transferase ( gst ) ( forward primer of gst gene , 5′- CTTTGCCGTTAA CCCTAAGGG -3′; reverse primer of gst gene , 5′- GCTGCAATGTGCTCTAACCC -3′ ) was used as an internal control for normalization . mRNA quantification was performed on a Rotor-Gene RG-300 qRT-PCR system ( Corbett Research ) under standard reaction conditions . Relative mRNA expression level were quantified by comparing the cycle threshold ( Ct ) values of each deletion mutant strain in rich medium or minimal medium to the Ct value of WT strain RNA , normalizing the sample value to gst expression . All reactions were performed independently from three biological replicates . | Proper assembly of the cell envelope is essential for bacterial growth , environmental adaptation , and drug resistance . Yet , while the biological roles of the many genes and pathways involved in biosynthesis of the cell envelope have been studied extensively in isolation , how the myriad components intersect functionally to maintain envelope integrity under different growth conditions has not been explored systematically . Genome-scale genetic interaction screens have increasingly been performed to great impact in yeast; no analogous comprehensive studies have yet been reported for bacteria despite their prominence in human health and disease . We addressed this by using a synthetic genetic array technology to generate quantitative maps of genetic interactions encompassing virtually all the components of the cell envelope biosynthetic machinery of the classic model bacterium E . coli in two common laboratory growth conditions ( rich and minimal medium ) . From the resulting networks of high-confidence genetic interactions , we identify condition-specific functional dependencies underlying envelope assembly and global remodeling of genetic backup mechanisms that ensure envelope integrity under environmental challenge . | [
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"p... | 2011 | Genetic Interaction Maps in Escherichia coli Reveal Functional Crosstalk among Cell Envelope Biogenesis Pathways |
Mapping expression Quantitative Trait Loci ( eQTLs ) represents a powerful and widely adopted approach to identifying putative regulatory variants and linking them to specific genes . Up to now eQTL studies have been conducted in a relatively narrow range of tissues or cell types . However , understanding the biology of organismal phenotypes will involve understanding regulation in multiple tissues , and ongoing studies are collecting eQTL data in dozens of cell types . Here we present a statistical framework for powerfully detecting eQTLs in multiple tissues or cell types ( or , more generally , multiple subgroups ) . The framework explicitly models the potential for each eQTL to be active in some tissues and inactive in others . By modeling the sharing of active eQTLs among tissues , this framework increases power to detect eQTLs that are present in more than one tissue compared with “tissue-by-tissue” analyses that examine each tissue separately . Conversely , by modeling the inactivity of eQTLs in some tissues , the framework allows the proportion of eQTLs shared across different tissues to be formally estimated as parameters of a model , addressing the difficulties of accounting for incomplete power when comparing overlaps of eQTLs identified by tissue-by-tissue analyses . Applying our framework to re-analyze data from transformed B cells , T cells , and fibroblasts , we find that it substantially increases power compared with tissue-by-tissue analysis , identifying 63% more genes with eQTLs ( at FDR = 0 . 05 ) . Further , the results suggest that , in contrast to previous analyses of the same data , the majority of eQTLs detectable in these data are shared among all three tissues .
Regulatory variation plays an essential role in the genetics of disease and other phenotypes as well as in evolutionary change [1]–[3] . However , in sharp contrast to nonsynonymous variants in the human genome , which can now be identified with great accuracy , it remains extremely difficult to know which variants in the genome may impact gene regulation in any given tissue or cell type . [Henceforth we use “tissue” for brevity , but everything applies equally to cell types . ] Expression QTL mapping ( e . g . [4]–[6] represents a powerful approach for bridging this gap , by allowing regulatory variants to be identified , and linked to specific genes . Indeed , numerous studies ( e . g . [7] , [8] ) have shown highly significant overlaps between eQTLs and SNPs associated with organismal-level phenotypes in genome-wide association studies ( GWAS ) , suggesting that a large fraction of GWAS associations may be due to variants that affect gene expression . Ultimately , understanding the biology of organismal phenotypes , such as diseases , is likely to require understanding regulatory variation in many different tissues ( [9] , [10] ) . For example , if regulatory variants differ across tissues , then , in understanding GWAS hits , and using them to understand the biology of disease , we would like to know which variants are affecting which tissues . At a more fundamental level , identifying differential genetic regulation in different tissues could yield insights into the basic biological processes that influence tissue differentiation . To date , eQTL studies have been performed in a relatively narrow range of tissue types . However , this is changing quickly: for example , the NIH “Genotype-Tissue Expression” ( GTEx ) project aims to collect expression and genotype data in 30 tissues across 900 individuals . Motivated by this , here we describe and illustrate a statistical framework for mapping eQTLs in expression data on multiple tissues . While statistical methods for identifying eQTLs in a single tissue or cell type are now relatively mature ( e . g . [11] ) current analytic tools are limited in their ability to fully exploit the richness of data across multiple tissues . In particular , available methods fall short in their ability to jointly analyze data on all tissues to maximize power , while simultaneously allowing for differences among eQTLs present in each tissue . Indeed relatively few papers have considered the problem . The simplest approach ( e . g . [12] , [13] ) is to analyze data on each tissue separately ( “tissue-by-tissue” analysis ) , and then to examine overlap of results among tissues . However , this fails to leverage commonalities among tissues to improve power to detect shared eQTLs . Furthermore , although examining overlap of eQTLs among tissues may appear a natural approach to examining heterogeneity , in practice interpretation of results is complicated by the difficulty of accounting for incomplete power . Both [13] and [14] provide approaches to address this , but only for pairwise comparisons of tissues . Compared with tissue-by-tissue analysis , joint analysis of multiple tissues has the potential to increase power to identify eQTLs that have similar effects across tissues . Both [15] and [16] conduct such joint analyses – the first using ANOVA , and the second using a weighted -score meta-analysis – and [16] confirm that their joint analysis has greater power than tissue-by-tissue analysis . The ANOVA and -score methods each have different advantages . The ANOVA framework has the advantage that , by including interaction terms , it can be used to investigate heterogeneity in eQTL effects among tissues . Gerrits et al . ( [15] ) use this to identify eQTLs that show significant heterogeneity , and then classify these eQTLs , post-hoc , into different types based on estimated effect sizes . The weighted -score method has the advantage that , unlike ANOVA , it allows for different variances of expression levels in different tissues ( which are likely to occur in practice ) . However , it does not so easily allow for investigation of heterogeneity; Fu et al . ( [16] ) hence assess heterogeneity for pairs of tissues by using a resampling-based procedure to assess the significance of observed differences in scores . Other papers , including [17] and [18] , also show that joint analyses provide more power . Our work goes beyond these papers in its modeling of heterogeneity , and in its use of a hierarchical model to borrow information across genes to estimate weights associated with different types of heterogeneity . Here we introduce a statistical framework for the joint analysis of eQTLs among multiple tissue types , that combines advantages of some of the methods above , as well as introducing some new ones . In brief , our framework integrates recently-developed GWAS meta-analysis methods that allow for heterogeneity of effects among groups [19]–[23] , into a hierarchical model ( e . g . [24] , [25] ) that combines information across genes to estimate the relative frequency of patterns of eQTL sharing among tissues . Like ANOVA , our approach allows investigation of heterogeneity among several tissues , not just pairs of tissues . However , in contrast to ANOVA , our framework allows for different variances in different tissues . Moreover , unlike any of the methods described above , our framework explicitly models the fact that some tissues may share eQTLs more than others , and estimates these patterns of sharing from the data ( a similar idea was applied to ChIP-Seq data by [26] ) . Our methods also allow for intra-individual correlations when samples are obtained from a common set of individuals . While we focus here on comparing and combining information across different tissue types , our framework could be applied equally to comparing and combining across other units , e . g . different experimental platforms , multiple datasets on the same tissue types , or data on individuals from different populations . The remainder of the paper is as follows . After providing a brief overview of our framework , we use simulations to illustrate its power compared to other methods , and then apply it to map eQTLs , and assess heterogeneity among tissues , using data from Fibroblasts , LCLs and T-cells ( [12] ) . Consistent with results from [16] , we show that our joint analysis framework provides a large gain in power compared with a tissue-by-tissue analysis . Furthermore , compared with previous analyses of these data , we find a much higher rate of tissue-consistent eQTLs .
Consider mapping eQTLs in tissues . In our applications here the expression data are from micro-arrays , and so we assume a normal model for the expression levels , suitably-transformed . ( These methods can also be applied to RNA-seq data after suitable transformation; see Discussion ) . That is , in each tissue , , we model the potential association between a candidate SNP and a target gene by a linear regression: ( 1 ) where denotes the observed expression level of the target gene in tissue for the individual , the mean expression level of this gene in tissue , the effect of a candidate SNP on this gene expression in tissue , the genotype of the individual at the SNP ( coded as 0 , 1 or 2 copies of a reference allele ) and the residual error for tissue and individual . Note that the subscript on residual variance indicates that we allow the residual variance to be different in each tissue . In addition , when tissues are sampled from the same set of individuals , we allow that the residual errors may be correlated ( with the correlation matrix to be estimated from the data ) . The primary questions of interest are whether the SNP is an eQTL in any tissue , and , if so , in which tissues . To address these questions we use the idea of a “configuration” from [21] , [23] . A configuration is a binary vector where indicates whether the SNP is an eQTL in tissue . If then we say the eQTL is “active” in tissue . The “global null hypothesis” , , that the SNP is not an eQTL in any tissue , is therefore . Every other possible value of can be thought of as representing a particular alternative hypothesis . For example , represents the alternative hypothesis that the SNP is an eQTL in all tissues , and represents the alternative hypothesis that the SNP is an eQTL in just the first tissue . Our aim is to perform inference for . A natural approach is to specify a probability model , , being the probability of obtaining the observed data if the true configuration were , and then perform likelihood-based inference for . The support in the data for each possible value of , relative to the null , is quantified by the likelihood ratio , or Bayes Factor ( BF , [27] ) : ( 2 ) Specifying these likelihoods requires assumptions about , the distribution of the effect sizes for each possible configuration ( as well as less crucial assumptions about nuisance parameters such as and ) . Of course , if then by definition , but for the tissues where various assumptions are possible – for example , one could assume that the effect is the same in all these tissues , or allow it to vary among tissues . Here we use a flexible family of distributions , ( see Methods ) , where the hyper-parameters can be varied to control both the typical effect size , and the heterogeneity of effects across tissues ( see below ) . The value of measures the support in the data for one specific alternative configuration , compared against the null hypothesis . To account for the fact that there are many possible alternatives , the overall strength of evidence against at the candidate SNP is obtained by “Bayesian Model Averaging” ( BMA ) , which involves averaging over the possible alternative configurations , weighting each by its prior probability , : ( 3 ) Further , under an assumption of at most one eQTL per gene , the overall evidence against for the entire gene ( i . e . that the gene contains no eQTL in any tissue ) is given by averaging across all candidate SNPs [28] . In either case , at either the SNP or gene level , large values of constitute strong evidence against . has a direct Bayesian interpretation as the strength of the evidence against , but here we also use it as a frequentist test statistic ( [28] , [29] ) , assessing significance by permutation or simulation . The latter has the advantage that and obtained in this way are “valid” even if not all the prior assumptions are exactly correct . Note that depends on the choice of , and the power of as a test statistic is expected to depend on how well this choice of these hyper-parameters captures the range of alternative scenarios present in the data . Here we make use of three different choices: Each of these choices has something to recommend it . The first , being data driven , is the most attractive in principle , but also the most complex to implement . The default choice is simpler to implement , and is included partly to demonstrate that one does not have to get the hyper-parameter values exactly “right” for to be a powerful test statistic . Finally , has the advantage that it is easily applied to large numbers of tissues; neither of the other methods scales well , either computationally or statistically , with the number of tissues , because the number of terms in the sum in equation ( 3 ) is . When there is strong evidence against , the Bayes Factors can also be used to assess which alternative configurations are consistent with the data . Specifically the posterior probability on each configuration is: ( 4 ) and the posterior probability that the SNP is an eQTL in tissue is obtained by summing the probabilities over configurations in which : ( 5 ) The second of these is particularly helpful when the data are informative for an eQTL in tissue , but ambiguous in other tissues: in such a case the probability will be close to 1 , even though the “true” configuration will be uncertain ( so none of the probabilities ( 4 ) will be close to 1 ) . Because both ( 4 ) and ( 5 ) are sensitive to choice of hyper-parameters , we compute them using ( where the hyper-parameters are estimated from the data ) . Further details of methods used are provided in the Methods section . We now analyze data from [12] , consisting of gene expression levels measured in fibroblasts , LCLs and T-cells from 75 unrelated individuals genotyped at approximately 400 , 000 SNPs . The data were pre-processed similarly to the original publication , as described in the Methods section . Throughout we focus on testing SNPs that lie within 1 Mb of the transcription start site of each gene ( the “cis candidate region” ) , and on a subset of 5012 genes robustly expressed in all three cell-types .
In this work , we have presented a statistical framework for analyzing and identifying eQTLs , combining data from multiple tissues . Our approach considers a range of alternative models , one for each possible configuration of eQTL sharing among tissues . We compute Bayes Factors that quantify the support in the data for each possible configuration , and these are used both to develop powerful test statistics for detecting genes that have an eQTL in at least one tissue ( by Bayesian model averaging across configurations ) , and to identify the tissue ( s ) in which these eQTLs are active ( by comparing the Bayes factors for different configurations against one another ) . Our framework allows for heterogeneity of eQTL effects among tissues in which the eQTL is active , for different variances of gene expression measurements in each tissue , and for intra-individual correlations that may exist due to samples being obtained from the same individuals . For eQTL detection , our framework provides consistent , and sometimes substantial , gains in power compared to a tissue-by-tissue analysis and ANOVA or simple linear regression . Concerning the tissue specificity of eQTLs , our framework efficiently borrows information across genes to estimate configuration proportions , and then uses these estimates to assess the evidence for each possible configuration . When re-analyzing the gene expression levels in three cell types from 75 individuals ( [12] ) , we found that there appears to be a substantial amount of sharing of eQTLs among tissues , substantially more than suggested by the original analysis . In the next few years , we expect that expression data will be available on large numbers of diverse tissue types in sufficient sample sizes to allow eQTLs to be mapped effectively ( for example , the NIH GTEx project aims to collect such data ) . The methods presented here represent a substantive step towards improved analyses that fully exploit the richness of these kinds of data . However , we also see several directions for potential extensions and improvements . First , our current framework can only partially deal with the challenges of large numbers of tissues . Specifically , because with tissues , there are possible configurations of eQTL sharing among tissues , some of our current methods , which consider all possible configurations , will become impractical for moderate ( speculatively , above about 10 , perhaps ) . Our test statistic partially addresses this problem , by allowing for heterogeneity while averaging over only configurations , which is practical for very large . Our simulation results suggest that is a powerful test statistic for identifying SNPs that are an eQTL in at least one tissue . However our preferred approach for identifying which tissues such SNPs are active in involves a hierarchical model that estimates the frequency of different patterns of sharing from the data , and this hierarchical model scales poorly with . In particular , having a separate parameter for each possible configuration is unattractive ( both statistically and computationally ) for large , and alternative approaches will likely be required . There are several possible ways forward here: for example , one would be to reduce the number of distinct configurations by clustering “similar” configurations together; another would be to focus less on the discrete configurations , and instead to focus on modeling heterogeneity in effect sizes in a continuous way - perhaps using a mixtures of multivariate normal distributions with more complex covariance structures than we allow here . We expect this to remain an area of active research in the coming years , especially since these types of issues will likely arise in many genomics applications involving multiple cell types , and not only in eQTL mapping . Another important issue to address is that most future expression data sets will likely be collected by RNA-seq , which provides count data that are not normally distributed . Previous eQTL analyses of RNA-seq ( e . g . [32] ) have nonetheless performed eQTL mapping using a normal model , by first transforming ( normalized ) count data at each gene to the quantiles of a standard normal distribution . Although this approach would not be attractive in experiments with small sample sizes , with the moderate to large sample sizes typically used in eQTL mapping experiments this approach works well . As a first step , this approach could also be used to apply our methods to count data . However , ultimately it would seem preferable to replace the normal model with a model that is better adapted to count-based data , perhaps a quasi-Poisson generalized linear model ( [33] ) ; Bayes Factors under these models could be approximated using Laplace approximations , similar to the approximations used here for the normal model [21] . The quasi-Poisson model has the advantage over the normal transformation approach that it preserves the fact that there is more information about eQTL effects in tissues where a gene is high expressed than in tissues where it is low expressed . This information is lost by normal transformation . In our primary analyses here we addressed this by analyzing only genes that were robustly expressed in all tissues , but this is sub-optimal , and will become increasingly unattractive as the number of tissues grows . Our analyses here assess ( cis ) eQTL sharing among tissues by performing association testing at the level of individual SNPs . A different approach to investigating eQTL sharing among tissues is to study the “cross-heritability” of expression levels among tissues ( e . g . [34] , [35] ) . These methods are based on polygenic models , and attempt to estimate the combined influence of all shared eQTLs; this contrasts with our analysis , where the focus is on sharing of individually-identifiable eQTLs of moderate-to-large effect . Both [34] and [35] estimate cross-tissue heritability to be low . [34] , studying expression in Blood and Adipose tissues from Icelanders , estimated cross-tissue heritability as 3%; [35] obtained an estimate of mean genetic correlation close to zero for Blood and LCLs in monozygotic twins ( ) . These results may appear to conflict with our results ( both from our model-based approach , and the less-model-based pairwise analysis approach from [13] ) , which suggest that most large-effect cis eQTLs are shared among fibroblasts , LCLs and T cells . However , these low estimates of cross-tissue heritability reflect not only the extent of sharing of eQTLs , but also the absolute size of the eQTL effects . If eQTL effects are small , explaining only a small proportion of the total variance in gene expression , then cross-tissue heritability will be also small , even if all eQTLs have exactly the same effect in all tissues . Thus , to assess eQTL sharing in the heritability-based approaches , it is helpful to contrast cross-tissue heritability , , with within-tissue heritability , , ( which is also affected by eQTL effect size , but not by sharing ) . Specifically , within the polygenic model it can be shown that the correlation coefficient of the eQTL effects in two tissues and is: . Applying this to the cis estimates of and from [34] , for adipose and blood , yields . Although this estimate of effect correlation within a polygenic model , is not directly comparable with our estimate of sharing of eQTLs in a decidedly non-polygenic model ( and for different cell types ! ) , this result suggests that the two analyses may be less in conflict than they initially appear .
For we use a hierarchical model , similar to [24] , [25] , which combines information across genes , to estimate the grid weights 's and configuration weights 's . Following both [25] , [26] we make the simplifying assumption that each gene has at most one eQTL ( which may be active in multiple tissues ) , and that each SNP is equally likely to be the eQTL . Let be the number of SNPs in the cis-region for gene . Then , if denotes the Bayes Factor ( 12 ) computed for SNP in gene , the “overall Bayes Factor” measuring the evidence for an eQTL in gene , , is obtained by averaging over the possible eQTL SNPs , the possible configurations , and the grid of values for , weighting by their probabilities: ( 13 ) Furthermore , if we let denote the probability that each gene follows the null ( i . e . contains no eQTL ) then the likelihood for gene , as a function of , is given by ( 14 ) ( 15 ) The overall likelihood for our hierarchical model is obtained by multiplying these likelihoods across genes: ( 16 ) Note that although the expression levels for different genes are not independent , because the SNPs being tested in different genes are mostly independent this independence assumption for the likelihoods across genes is a reasonable starting point . We have developed an EM algorithm to estimate the parameters by maximum likelihood ( see Supplementary information ) . For our simulations , when simulating SNP-gene pairs , the genotypes at each SNP in each individual were simulated as Binomial ( 2 , 0 . 3 ) : that is , with minor allele frequency 30% and assuming Hardy-Weinberg equilibrium . Phenotypes with eQTLs were simulated , with effect size based on an expected proportion of variance explained ( PVE ) of 20%; ( see Text S1 ) . For Figure 1A and 1B the error variances ( one per tissue ) were all equal to 1 . For Figure 1C the error variances were randomly drawn from , all equally likely . The ANOVA/LR method uses the same linear model as our Bayesian methods ( 1 ) , except that the residual errors are assumed to be equal across tissues . Within this model we tested the global null hypothesis ( for all ) using an test comparing the null model with the unconstrained alternative ( unconstrained ) . See Text S1 . The phenotypes from Dimas et al . ( [12] ) were retrieved from the Gene Expression Omnibus ( GSE17080 ) . We mapped the 22 , 651 non-redundant probes to the hg19 human genome reference sequence ( only the autosomes ) using BWA ( [37] ) , kept 19 , 965 probes mapping uniquely with at most one mismatch , and removed the probes overlapping several genes from Ensembl . This gave us 12 , 046 genes overlapped by 16 , 453 probes . For genes overlapped by multiple probes , we chose a single probe at random . In our analyses we considered only genes that were robustly expressed in all tissues . A gene was considered robustly expressed in a given tissue if its mean expression level across individuals in this tissue was larger than or equal to the median expression level of all genes across all individuals in this tissue . As a result , we focused on 5012 genes . Genotypes were obtained from the European Genome-phenome Archive ( EGAD00000000027 ) . We extracted the genotypes corresponding to the 85 individuals for which we had phenotypes and converted the SNP coordinates to the hg19 reference using liftOver ( [38] ) . To detect outliers , we performed a PCA of these genotypes using individuals from the CEU , CHB , JPT and YRI populations of the HapMap project using EIGENSOFT ( [39] ) . As in the original study , we identified 10 outliers and removed them from all further analyses , which were therefore performed on 75 individuals . Gene expression measurements suffer from various confounders , many of which may be unmeasured ( [40] ) , but which can be corrected for using methods such as principal components analysis ( PCA ) . Following [32] , we applied PCA in each tissue separately on the 501275 matrix of expression levels of each gene in each individual . We sorted principal components ( PCs ) according to the proportion of variation in the original matrix they explain , and selected PCs so that adding another PC would explain less than 0 . 0025% of the variation . As a result , this procedure identified 16 PCs in Fibroblasts , 7 in LCLs and 15 in T-cells . We then regressed out these PCs from the original matrix of gene expression levels , and used the residuals as phenotypes for all analyses . All methods we compared assume that the errors are distributed according to a Normal distribution . Before analysis we therefore rank-transformed the expression levels at each gene to the quantiles of a standard Normal distribution ( [28] ) . On the data set from Dimas et al . , we assessed the performance of two methods , the tissue-by-tissue analysis and the BMA joint analysis , by comparing the number of genes identified as having at least one eQTL in any tissue , at a given FDR . For each method , we defined a test statistic , which was computed for each gene . For the tissue-by-tissue analysis , the test statistic is the minimum of the linear regressions between the given gene and each cis SNP in each tissue ( so the minimum is taken across all SNPs and all tissues ) . For the BMA joint analysis , the test statistic is the average of the Bayes Factors for the given gene and each cis SNP . ( When applying the tissue-by-tissue analysis to test for eQTLs in a single tissue , the test statistic is the minimum of the linear regressions between the given gene and each cis SNP in that tissue . ) In each case we converted the test statistic to a for each gene , testing the null hypothesis that the gene contains no eQTL in any tissue , by comparing the observed test statistic with the value of the test statistic obtained on permuted data obtained by permuting the individuals labels ( using the same permutations in each tissue to preserve any intra-individual correlations between gene expression in different tissues ) . Specifically , let denote the total number of permutations ( we used ) , the value of the test statistic for gene on the non-permuted data , and the value of the test statistic on the -permuted data . The for gene from the tissue-by-tissue analysis is: . For the BMA joint analysis , the is: . Note that permutations were performed for each gene , since the null distribution of the test statistic will vary across genes ( not least because the genes have different numbers of SNPs in their cis candidate region; see Figure S3 ) . From the calculated for each gene we estimate using the qvalue package ( [31] ) , and determine the number of genes having at least one eQTL in any tissue at an FDR of by computing the number of genes with . When performing the tissue-by-tissue analysis on a single tissue , we performed the permutations in each tissue separately . | Genetic variants that are associated with gene expression are known as expression Quantitative Trait Loci , or eQTLs . Many studies have been conducted to identify eQTLs , and they have proven an effective tool for identifying putative regulatory variants and linking them to specific genes . Up to now most studies have been conducted in a single tissue or cell type , but moving forward this is changing , and ongoing studies are collecting data aimed at mapping eQTLs in dozens of tissues . Current statistical methods are not able to fully exploit the richness of these kinds of data , taking account of both the sharing and differences in eQTLs among tissues . In this paper we develop a statistical framework to address this problem , to improve power to detect eQTLs when they are shared among multiple tissues , and to allow for differences among tissues to be estimated . Applying these methods to data from three tissues suggests that sharing of eQTLs among tissues may be substantially more common than it appeared in previous analyses of the same data . | [
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"mo... | 2013 | A Statistical Framework for Joint eQTL Analysis in Multiple Tissues |
Nucleoside-based cofactors are presumed to have preceded proteins . The Rossmann fold is one of the most ancient and functionally diverse protein folds , and most Rossmann enzymes utilize nucleoside-based cofactors . We analyzed an omnipresent Rossmann ribose-binding interaction: a carboxylate side chain at the tip of the second β-strand ( β2-Asp/Glu ) . We identified a canonical motif , defined by the β2-topology and unique geometry . The latter relates to the interaction being bidentate ( both ribose hydroxyls interacting with the carboxylate oxygens ) , to the angle between the carboxylate and the ribose , and to the ribose’s ring configuration . We found that this canonical motif exhibits hallmarks of divergence rather than convergence . It is uniquely found in Rossmann enzymes that use different cofactors , primarily SAM ( S-adenosyl methionine ) , NAD ( nicotinamide adenine dinucleotide ) , and FAD ( flavin adenine dinucleotide ) . Ribose-carboxylate bidentate interactions in other folds are not only rare but also have a different topology and geometry . We further show that the canonical geometry is not dictated by a physical constraint—geometries found in noncanonical interactions have similar calculated bond energies . Overall , these data indicate the divergence of several major Rossmann-fold enzyme classes , with different cofactors and catalytic chemistries , from a common pre-LUCA ( last universal common ancestor ) ancestor that possessed the β2-Asp/Glu motif .
Nucleoside-based cofactors are widely abundant and are likely to have appeared well before proteins [1–3] . The early protein forms may have therefore evolved to bind and function with nucleoside-based cofactors [4] . However , tracing motifs that relate to the earliest stages of protein-cofactor evolution is a challenge [5] . Omnipresent cofactor-binding motifs , such as the P-loop ( phosphate-binding loop or Walker A motif ) , are considered fingerprints of the earliest precursors of modern proteins [5] . However , in general , abundance of a trait per se ( in terms of number of species and their distribution in the tree of life ) is not sufficient to indicate common ancestry , as convergence of sequence and structure is a feasible alternative . The more minimal a motif is in terms of the number of amino acids , the more likely it is to be the outcome of convergent evolution—namely , to have evolved independently , along separate lineages , yet ended up with the same molecular solution [6] . In fact , there is ample evidence for convergence , both of structural architectures ( folds ) and of binding and catalytic motifs . Folds such as β-propellers , for example , have emerged in parallel many times [7–10] . Artificial proteins belonging to the most ancient folds are computationally designed with sequences that bear no relation to natural proteins [8 , 9] . Omnipresent catalytic motifs such as the Asp/Glu dyads of glycosyl hydrolase and transferases are seen in >50 different folds [11] and with no significant sequence homology beyond the dyad itself . Such motifs have probably emerged independently , and their conserved geometry is due to physicochemical constraints dictated by a shared function . In fact , when it comes to binding and catalytic motifs , convergence is probably as dominant as divergence [12] . Overall , differentiating divergent from convergent evolution remains a crucial , largely unresolved dilemma in evolutionary biology in general and in protein evolution in particular [13–16] . Our study focuses on the Rossmann fold . By virtue of catalyzing >300 different enzymatic reactions [17] , the Rossmann fold is one of the most widely occurring protein folds [18–21] and is accordingly well represented in the presumed set of proteins that existed in the last universal common ancestor ( LUCA ) [20 , 22 , 23] . Belonging to the general class of β/α proteins , the Rossmann fold comprises two tandem repeats . Each repeat comprises three consecutive strands forming a parallel pleated sheet and two connecting α-helices [24–26] . The strand order along the core β-sheet is 3-2-1–4-5-6 , although modifications of the last strand are often seen ( Fig 1 ) . Rossmann-fold enzyme families are also characterized by their use of cofactors [20 , 27 , 28] and in particular of nucleoside-containing cofactors that were present in the presumed “RNA world , ” prior to the emergence of proteins [1 , 2] . Rossmann-fold enzymes therefore comprise a clear example of the evolutionary link between cofactors and their utilizing enzymes . Indications for pre-LUCA evolutionary links in the Rossmann fold have been noted that relate to nucleoside binding and the shared fold [19 , 29] . Shared nucleoside binding motifs have also been described upon the identification of the Rossmann fold and at later stages ( e . g . , [6 , 30–39] ) . Specifically , nicotinamide adenine dinucleotide ( NAD ) - and flavin adenine dinucleotide ( FAD ) -utilizing enzymes share a Gly-rich loop that resides between H1 and β1 and interacts with the cofactors’ phosphate moieties [19 , 40 , 41] , and the hydroxyls of the cofactors’ ribose moiety typically interact with a Glu/Asp at the tip of β2 ( β2-Asp/Glu; Fig 1 ) [42 , 43] . Sequence homology can obviously be detected between NAD and nicotinamide adenine dinucleotide phosphate ( NADP ) enzymes and may span over to FAD enzymes , specifically in relation to the above two motifs [44 , 45] . However , the sequence homology with other Rossmann classes such as S-adenosyl methionine ( SAM ) -dependent methyltransferases is much less clear [36 , 44] . The ribose-binding Glu/Asp at the tip of β2 has also been detected in methyltransferases [42 , 43] . However , the Gly-rich motif is not apparent in SAM-utilizing Rossmann enzymes , possibly because SAM does not contain phosphate groups . Consequently , some sequence-based classifiers , including those using sensitive homology detectors such as CATH ( Class Architecture Topology Homologous superfamilies ) , define these classes as separate superfamilies [46] . However , based amongst other considerations on the shared β2-Asp/Glu motif , other classifiers such as ECOD ( Evolutionary Classification of Protein Domains ) [30] or Interpro [47] classify all three classes ( NAD ( P ) , FAD , and SAM-dependent Rossmann enzymes ) in the same homology group [31 , 32 , 35 , 38 , 39] . Overall , a common fold [20] and the shared binding motif ( the ribose β2-Asp/Glu interaction ) are highly suggestive of a common Rossmann ancestor and specifically of common ancestry of NAD- , FAD- , and SAM-utilizing enzymes [30 , 34 , 38] . Indeed , these three classes ( and a few additional ones addressed below ) are all present in the presumed LUCA [48 , 49] . However , so far , there has been no attempt , to our knowledge , to examine whether these shared features are indeed a hallmark of common descent [39] . Such a systematic analysis is crucial in view of convergence being common and especially because the shared binding motif comprises a single residue .
We were initially interested in engineering the SAM-binding site of DNA methyltransferases—a Rossmann-fold enzyme superfamily . Our attention was focused on the adenosine group that appears in nearly all of the key enzymatic cofactors . In this context , we were searching for a highly conserved interaction that is critical to adenosine binding and could be modified . However , our analysis indicated that none of the residues that interact with the adenine ring are conserved in all DNA methyltransferases . In contrast , we observed that a Glu residue that interacts with the ribose is entirely conserved . We first observed that the carboxylate-ribose interaction is completely conserved in SAM-dependent methyltransferases , including DNA , RNA , protein , and small molecule methyltransferases . We realized that conservation does not simply concern an active-site Asp/Glu that interacts with SAM [42 , 43] but primarily relates to a bidentate interaction with the ribose’s 2ʹ and 3ʹ hydroxyls with an unusually narrow distribution of H-bond distances and angles . Distinctly , the interacting Asp/Glu is at the tip of the Rossmann’s second beta strand ( β2 ) ( Fig 2A; S1 Fig and S2 Fig ) . Further , although the β2-Asp/Glu was described as a characteristic of Rossmann NAD dehydrogenases [44] , its bidentate nature has not been described as such . A wider examination that further included NAD- and FAD-dependent oxidreductases was performed ( see Methods and S3 Fig ) . This analysis confirmed that , as suggested earlier [40 , 41 , 50] , the ribose-interacting Asp/Glu is also widely spread in these two enzyme classes . However , to our knowledge , the prevalence of this Asp/Glu interaction across NAD/FAD oxidoreductases , as well as SAM-dependent methyltransferases , and the geometrical conservation of the bidentate interaction with the bound ribose have not been previously noted . We therefore defined a new canonical Rossmann motif based on four criteria: ( i ) a tight , bidentate interaction exists between a carboxylate side chain and the ribose’s 2ʹ and 3ʹ-hydroxyls; ( ii ) the ribose’s furanose ring conformation is in an envelope form , mainly the E1 and 2E conformations ( S4 Fig: see also S1 Text ) ; ( iii ) the angle the ribose and the interacting carboxylate ( hereafter the ribose–carboxylate angle α; defined in Fig 2B ) is 90°–140°; and ( iv ) the interacting Glu/Asp is located at the tip of the β2 strand of the Rossmann fold ( Fig 2A ) . A systematic analysis identified the above motif features as being unique to the Rossmann fold . All nonredundant PDB structures containing ribose ligands were downloaded ( Table 1; n = 2 , 949; S5 Fig ) . Of these , ~30% were found to have a carboxylate side chain that is within interacting distance ( ≤3 . 4 Å ) of both the 2ʹ and 3ʹ hydroxyls of the ribose ( n = 811 ) . These structures were then categorized by the angle α ( Fig 2B ) . The secondary structural element to which the interacting Glu/Asp residue belongs was also classified , as well as the fold ( using Structural Classification of Proteins [SCOP] and/or CATH annotations ) . This analysis indicated that the canonical bidentate interaction underlies enzyme families and superfamilies that possess a Rossmann fold . Specifically , the canonical interaction was found in 54% of the structures classified as a Rossmann fold ( Table 1 ) . These structures were manually examined , and the order of their β-strands was found to fit the Rossmann-fold topology . Further , ≥96% of the examined Rossmann enzymes have their ribose rings in the 2E or E1 configuration ( discussed below ) . Only 8% of the structures belonging to the Rossmann fold possessed noncanonical interactions—namely , bidentate interactions with α < 90° or > 140° and/or with the interacting Glu/Asp not being located at the tip of a β strand . Conversely , in enzymes belonging to non-Rossmann folds , monodentate or no Asp/Glu interactions are the rule ( 91% ) . Further , when bidentate interactions are present in non-Rossmann proteins , they almost never meet the canonical criteria , namely the canonical angle and the interacting Glu/Asp being at the tip of a β-strand . Indeed , amongst non-Rossmann enzymes , only 1 . 7% exhibit bidentate interactions that meet the canonical criteria versus 6% that exhibit bidentate interactions that do not meet the canonical criteria; Fig 2A–2C , S6 Fig ) . One notable example showing how unique the canonical motif is to the Rossmann fold is the P-loop nucleoside-triphosphatase ( NTPase ) fold ( CATH annotation 3 . 40 . 50 . 300; SCOP superfamily c . 37 . 1 , P-loop containing nucleoside triphosphate hydrolase ) . This fold also belongs to the class of β/α proteins . Overall , its topology is highly similar to the Rossmann fold , except that the order of strands within its core β-sheet is 2-3-1–4-5-6 . Thus , the location of β2 , where the canonical Rossmann Asp/Glu ribose-binding residue appears ( Fig 1 ) , is shifted relative to the Rossmann topology . We found that none of the structures belonging to the P-loop NTPases superfamily ( CATH Family 3 . 40 . 50 . 300; n = 210 ) contains the canonical carboxylate-ribose interaction . Further , as discussed below , the mode of nucleoside binding in P-loop NTPases differs fundamentally from the one observed in the Rossmann fold . Nearly half of the structures ( 279/578 ) in our original dataset were found to have the canonical carboxylate-ribose interaction but had no SCOP or CATH category ( Table 1 ) . We manually examined all 279 structures and found that 271 of these structures have a Rossmann , or Rossmann-like , topology , as defined above , and with the interacting Glu/Asp located at the tip of β2 ( S5 and S6 Tables , S7 Fig ) . In fact , 108 out of the 279 structures that were not annotated in the CATH version v3 . 5 . 0 used to make our dataset are annotated in the current version ( v . 4 . 0 . 0; in which the number of annotated domains is larger by 36% ) . This “blind test” indicates that the applied criteria are sufficient not only to identify the canonical motif in Rossmann enzymes but also to rigorously identify a Rossmann enzyme merely by the existence of this canonical motif . NAD-utilizing enzymes provide another indication for divergence from a common adenosine-binding ancestor . The cofactor NAD contains two riboses , one attached to adenosine and the other to nicotinamide . However , in the 259 available structures of NAD-dependent enzymes , only bidentate carboxylate-ribose interaction was found with the ribose . Among the NAD enzymes annotated as Rossmann , 145 structures out of 155 fit the canonical criteria with respect to the interaction with the adenosine’s ribose ( S7 Table ) . Only four structures possess an additional bidentate interaction with NAD’s nicotinamide ribose . Of these four , two are annotated as Rossmann folds . Both these structures have one canonical interaction at the tip of β2 binding the adenosine ribose , as do the 145 other NAD Rossmann-fold enzymes . The nicotinamide riboses , however , interact with Glu residues located not at the tip of β2 , and these bidentate interactions exhibit noncanonical geometries ( Fig 3A and S8 Fig ) . The variability of the ribose-carboxylate angles and topology ( Asp/Glu locations other than β2 ) and the sporadic presence ( 4/155 indicating appearance in recently evolved lineages ) are all consistent with emergence by convergence . In contrast , the prevalence ( 145/155 ) and conservation of both geometry and topology of the interaction with the adenosine’s ribose most likely indicates divergence from a primordial ancestor of the Rossmann fold . A motif that has been retained for ≥3 . 7 billion y of evolution is likely to be functionally important . Indeed , the contribution of the Glu/Asp interaction in NAD- and FAD-utilizing enzymes is widely recorded ( published data listed in S8 Table ) [51 , 52] . However , we could not find reports describing the experimental examination of its role in SAM-utilizing enzymes . To this end , we examined a typical bacterial mC5 DNA methyltransferase , M . HaeIII , in which Glu29 interacts with the SAM cofactor with the canonical motif geometry ( Fig 4 ) , as do nearly all other Rossmann methyltransferases ( Table 1 ) . Methylation activity was completely lost upon replacement of Glu29 , including conservative replacements such as Gln , or Asp , and dropped by up to 450-fold in terms of kcat/KM in the Glu29Thr and Ala mutants ( Fig 4 , S8 Table ) . Overall , it appears that the canonical bidentate interaction have an important contribution to cofactor binding in the three classes of Rossmann enzymes in which it prevails , namely in NAD- , FAD- , and SAM-utilizing enzymes . However , the effects of mutations seemed to differ; for example , in glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) ( NAD dependent ) and sarcosine oxidase ( FAD dependent ) , the conservative D to E mutations reduced kcat/KM by ≤10-fold , whereas in M . HaeIII ( SAM dependent ) , activity was completely lost . Thus , in all three enzymes , relatively conservative exchanges such as D to A or D to N resulted in up to 90-fold losses , yet the loss of activity observed for the SAM-dependent M . HaeIII was generally higher . The contribution of the bidentate interaction to SAM binding is probably higher than in the case of NAD and FAD because in the latter two , the Asp/Glu bidentate interaction is further away from the reaction center . Is the highly conserved geometry of the Rossmann bidentate motif the outcome of chance or of necessity [54] ? Namely , does the canonical geometry comprise the most optimal mode of ribose binding , or is it just one out of several options ? Evolution of the Rossmann fold and cofactor binding implies that a single solution was selected at the ancestral stage , presumably owing at least in part to its favorable binding energy , and has been conserved ever since . Indeed , a scenario of divergence typically follows from the existence of several possible solutions; in particular , divergence of the bidentate carboxylate interaction geometries would seem to imply that there are multiple such geometries of similar energy . Convergence , on the other hand , is compatible with a scenario whereby the bidentate interaction geometry seen in existing proteins is the only optimal one or even the only possible one . We can illustrate the above line of reasoning by considering the dihedral angles ( ω ) of the peptide bonds in proteins . The distribution of ω along >200 , 000 peptide bonds in known protein structures is narrow , with a clear maximum at planarity ( >97% of bonds within ω = 180 ± 10° ) . This distribution corresponds to a single optimum value of 180° [55] . The planarity of the peptide bond therefore relates to a physical constraint that dictates all protein structures , rather than to a trait that diverged from the very first peptide . Another example mentioned in the introduction is the Asp/Glu dyads seen in glycosydases of many different folds , whereby the intercarboxylate distances are highly conserved within two categories of retaining glycosidases ( 5 . 5 Å ) and inverting ones ( 10 Å ) [11] . The favorable contribution of the bidentate carboxylate interaction to binding of vicinal-diols ( as are the 2ʹ , 3ʹ hydroxyls of ribose ) was indicated in small-molecule structures ( S9 Fig ) and by quantum mechanical calculations [56] . In the present work , we carried out new calculations to examine how energetically favorable is the geometry of the canonical interaction , and specifically how the energy of this interaction changes with the ribose-carboxylate angle ( α ) and ribose ring configuration . We performed quantum mechanical calculations designed to produce energy profiles of the different furanose configurations of ribose and of the ribose-carboxylate interaction angle ( α ) [57] . For this purpose , density functional theory electronic structure calculations with the Solvation Model based on Density ( SMD ) solvation model were used to study the ribose-carboxylate interaction in model systems in which the structures were energy minimized as a function of the ribose-carboxylate angle α ( Fig 5; the energy calculations are described in detail in the S1 Text ) . The quantum mechanical calculations were performed on two models systems , M1 and M2 , defined in Fig 5 . After conformational searches , we identified the lowest-energy structures of model M2 ( dubbed g-a , g-t , and t-t ) and those for M1 ( dubbed 2E-endo and 3E-exo ) . The lowest-energy structure obtained for M1 is 2E-endo , and for M2 , it is t-t . Both 2E-endo and t-t exhibit a similar endo conformation , with respective α values of 132° and 129° and a similar envelope form for the ribose ring ( 2E for 2E-endo and E1 for t-t ) . The relative energy was accordingly plotted against the angle α ( Fig 5A for model M1 and Fig 5B for model M2 ) , indicating the lowest-energy structure for each value of α . These plots show that the bidentate interaction presents an angle optimum of ~130° . This optimum clearly overlaps the canonical Rossmann angle ( Fig 2B ) . Further , the vast majority of Rossmann enzymes possess a ribose ring in a 2E or E1 configuration ( 96% of 263 PDB structures analyzed; see S1 Text ) and an endo conformation ( 100% of 263 structures; see S1 Text ) , thus matching their modeled counterparts , 2E-endo and t-t . However , beyond the canonical optimum , the potential energy surface for the carboxylate-bidentate interaction is relatively flat , with several minima . The only angles that appear to be highly disfavored are the edges , i . e . , close to 0° and 180° , and these regions are also unoccupied in natural proteins ( Fig 2B ) . Energy minima corresponding to the 3E-exo configuration for M1 , and the g-a configuration for M2 , are seen in α range of 10°–37° ( Fig 5 ) . According to our calculations , the endo configuration is more stable than the exo , by about 1 kcal/mol for model M1 and by only 0 . 1 kcal/mol for model M2 . These differences are relatively small—an energy difference of 0 . 55 kcal/mol ( the average difference for M1 and M2 ) corresponds to ~2 . 5-fold difference in affinity . For comparison , as indicated by the effects of mutations of the canonical Asp/Glu , the contribution of this interaction in Rossmann enzymes of different classes differs by well over 10-fold ( see the above section and S8 Table ) . The model structures that correspond to the alternative energy minima are seen in typical noncanonical interactions ( Fig 2C , carboxyl side chains in variable greens ) . One characteristic example can be seen in Fig 3A , with the angles of the noncanonical interactions being 16° , far off the canonical range ( 90°–140° ) and within the second predicted minimum ( Fig 5 ) . This alternative minimum corresponds to an exo disposition and has the ribose ring in the 3E for 3E-exo and in 2E for g-t . This mode is clearly seen in enzyme structures with the interaction angle in the range of 14° to 43° ( Fig 2B and Fig 3 ) , whereby the interaction corresponds to an exo configuration and the furanose conformation of the ribose is scattered among several possibilities ( see S1 Text ) . Another example is human phosphoglyceraldehyde kinase where Glu344 , located at the tip of β4 , not β2 , interacts with the ADP ribose in a bidentate manner , with the angle being 57° ( S10 Fig ) . Overall , the computations indicate that the canonical interaction is an intrinsically favorable mode for binding of ribose . It also corresponds to a furanose ring configuration that is the most energetically favored irrespective of the protein binding pocket and additional interactions , e . g . , with the nucleoside’s base . However , the canonical interaction is only one out of at least two , if not more , favorable modes of bonding . Indeed , a wide distribution of interaction angles ( Fig 2B ) is seen in non-Rossmann ribose-binding proteins and predominantly in noncanonical interactions in Rossmann enzymes .
The utility of the carboxylate-ribose bidentate interaction , and its appearance in numerous protein families belonging to different folds and binding different cofactors , suggest that it arose independently , i . e . , by convergent evolution . This is not surprising in view of the simplicity of this motif—a single carboxylate side chain aligned against the ribose hydroxyls . However , the statistics of occurrence clearly support the hypothesis of divergence . The canonical interaction is >30 times more frequent in Rossmann enzymes ( 54% ) compared to non-Rossmann ones ( 1 . 7% ) . In contrast , the occurrence of noncanonical bidentate interactions in Rossmann and non-Rossmann proteins is nearly identical ( 8% and 6% , respectively; Table 1 ) . Thus , whilst convergence to the canonical geometry and/or topology did occur , as exemplified in Fig 3B , its frequency of occurrence is not only lower but is also independent of the fold . The distinct features of convergence are apparent , including within Rossmann enzymes . The distinct geometry of this motif in Rossmann enzymes may also provide a new means for automated classifications , as indicated by our manual examination of the structures with no CATH or SCOP annotations . The presence of an Asp/Glu at the loop connecting the second β-strand and the following helix is insufficient to distinguish between Rossmann from non-Rossmann enzymes ( as previously noted [37 , 39] and also indicated by our data ) . However , when the carboxylate-ribose angle criterion is added , prediction accuracy increases to 97% ( the false positive rate is 8/279 ) . The ancient origins of the ribose– ( Asp/Glu-β2 ) motif and the claim for divergent evolution are also supported by the role of this motif in the switch of cofactor specificity of dehydrogenases . NADP-dependent dehydrogenases seem to have diverged from NAD-dependent enzymes [58] , probably along multiple lineages . NADP differs from NAD in the 3ʹ-hydroxyl of the adenosine ribose being phosphorylated . Thus , binding of NADP is a priori excluded because of the negatively charged Glu/Asp that interacts with the unmodified ribose hydroxyls in NAD dehydrogenases . Indeed , the replacement of the β2-Asp/Glu is a prerequisite for the switch in specificity to NADP ( S11 Fig ) [59 , 60] . Thus , loss of the canonical Glu/Asp underlines the evolution of orthogonal , NADP-dependent dehydrogenases . The existence of alternative ribose-binding modes with binding energies that are similar to that of the canonical Rossmann mode ( Fig 5 ) and the accordingly wide distribution of binding modes of the noncanonical interactions ( as reflected by the interaction angle α; Fig 2B ) also support the hypothesis that the canonical Rossmann motif is the outcome of common ancestry and not of convergent evolution . Many structural features are the outcome of strict biophysical constraints , namely of one geometry being highly favored ( a deep-well potential energy surface ) . The negative constraints ( steric clashes , loss of resonance energy , etc . ) are most dominant in dictating deep-well potentials . This is , for example , the case with the planarity of amide bonds [55] . In contrast , the multiminima potential energy surface for the carboxylate-ribose interaction indicates strong constraints acting only at the edges ( around 0° and 180°; Fig 5 ) . This suggests that the conservation of the interaction angle in Rossmann enzymes relates to their divergence from a common ancestor in which this angle was dictated by various factors , including but not limited to the favorable ribose-carboxylate interaction . Common ancestry is the hallmark of Darwinian evolution . Our data support the notion of a primordial Rossmann ancestor in which binding of an adenosine-based cofactor was mediated by the ribose-β2-Asp/Glu interaction , alongside the Gly-loop that resides at the tip of the first strand ( β1 ) ( Fig 6 , S13 Fig ) [24 , 30 , 36 , 39] . The Gly-rich motif binds the phosphate groups of NAD/FAD/adenosine-5ʹ-triphosphate ( ATP ) ( typically , GxGxxG ) [5 , 61] . This motif is also recognizable in methyltransferases , although with low sequence identity because , unlike NAD- and FAD-dependent enzymes , their cofactor , SAM , does not contain a phosphate group ( Fig 6 ) . The minimal postulated ancestor therefore spans the Rossmann fold's first two strands and the connecting helix ( β1-H1-β2 ) and includes the Gly-rich and ribose-β2-Asp/Glu interaction ( Fig 7A ) [40 , 62] . Our analysis supports a postulated pre-LUCA ancestor that underlined the divergence of at least three major enzyme classes: methyltransferases , NAD ( P ) and FAD oxireductases [29] , and the many superfamilies belonging to these two classes , as well as the divergence of other enzyme families using other adenosine-based cofactors such as ATP ( Fig 6 ) . The Gly-rich loop and the ribose-β2-Asp/Glu motif was the keystone of this primordial ancestor [40 , 62] . Such keystone elements may relate to earlier precursors , possibly shorter polypeptides that contained these binding motifs [5 , 40 , 41 , 43 , 45] and from which the Rossmann ancestor evolved via a series of duplications , recombination , and fusions [63 , 64] .
For the study of the individual enzyme classes , all structures belonging to SAM-dependent methyltransferases ( SCOP category c . 66 . 1 ) , NAD ( P ) -binding Rossmann-fold domains ( c . 2 . 1 ) , and FAD/NAD-linked oxidoreductases ( c . 3 . 1 . 5 ) were downloaded from SCOP ( v . 1 . 75 ) . Redundant structures of the same protein in which the PDB code was the same for the first three letters/digits and the Glu/Asp residue number was identical were removed . Structures with <2 . 5 Å resolution were further considered , resulting in 55 methyltransferase ( c . 66 . 1 ) and 315 oxidoreductase ( c . 2 . 1 and c . 3 . 15 ) enzyme domains that were assigned as Rossmann by SCOP ( a flowchart describing this analysis is available as S3 Fig ) . For the systematic analysis of all ribose-binding proteins , we first identified 66 ribose-containing ligands ( S2 Table ) for which ≥10 nonredundant structures are available in the PDB . We excluded ligands that are part of polynucleotides such as RNA or DNA . All PDB structures that have ribose-containing ligands and <2 . 5 Å resolution were downloaded , and 80% sequence redundancy was removed with cd-hit [71] . The final dataset comprised 2 , 949 structures ( Table 1 ) comprising 210 P-loop NTPase structures , 2 , 313 structures containing ligands with one ribose ring , and 426 structures with ligands such as NAD or FAD that contain two riboses ( a flowchart describing this analysis is available as S5 Fig ) . The four structures with NAD ligands and two bidentate interactions were analyzed separately . We calculated the distances , angles , and dihedral angles of atoms of interest using the PDB coordinates and custom Perl-scripts . For all retrieved PDB structures , the first chain in the asymmetric unit containing the cofactor was extracted . A random sample indicated that the variability in the distances and angles between different molecules in the asymmetric unit is low , and hence , an arbitrary choice of the first chain containing the cofactor is representative ( S1 Text; average standard deviation for the distance is 0 . 074 Å , and for α is 2 . 2° ) . First , all residues that bind the ribose ligands were determined using CSU , and based on whether there is an Asp/Glu residue in the vicinity of the 2’ , and 3’-OH of the ribose ( ≤4 Å ) . Then , we further characterized the ribose-Asp/Glu interaction and defined four binding modes: canonical bidentate , noncanonical bidentate , monodentate , or “no Asp/Glu interaction . ” The canonical bidentate interaction was defined by four criteria: Noncanonical bidentate interaction was assigned to structures meeting criterion ( i ) , namely structures with a bidentate interaction yet with the plane angle being <90° or >140° and the interacting Asp/Glu not located at the tip of a β-strand . Monodentate interactions were assigned to structures with a single putative H-bond interaction between an Asp/Glu carboxylate and either the 2ʹ or the 3ʹ-hydroxyl groups . A more generous cutoff distance of ≤4 Å was taken here than for the bidentate interactions ( ≤3 . 4 Å ) because the latter , and especially the canonical bidentate interactions , tend to be much tighter ( average distance = 2 . 7 Å; S2B Fig ) . Finally , no Glu/Asp interaction was ascribed to structures where no carboxylate was found within 4 Å of either the 2ʹ or the 3ʹ-hydroxyl groups of the bound ribose . When available , we retrieved the CATH and SCOP classification for the PDB structures in our dataset . Assignments of Rossmann fold were derived from CATH topology 3 . 40 . 50 ( CATH_v3 . 5 . 0 , version date: 20 . 09 . 2013 , was used for this analysis ) . However , as explained in the main text , we separately analyzed superfamily 3 . 40 . 50 . 300 , the P-loop containing nucleotide triphosphate hydrolases that are usually not considered as Rossmann . For SCOP , categories c . 66 . 1 , c . 2 . 1 , c . 3 . 1 , and c . 4 . 1 were assigned as Rossmann . Including both CATH and SCOP databases significantly increased the fraction of structures with annotated fold ( e . g . , for structures containing one ribose ligands , the CATH database assigns 207 proteins as Rossmann , and addition of SCOP added another 85 ) . About 46% of structures had neither a CATH nor a SCOP annotation ( 1 , 354/2 , 949 ) . We therefore manually inspected a randomly chosen subset of the structures that possess the canonical interaction . We confirmed these as belonging to the Rossmann fold by identifying the canonical 3-2-1-4-5-6 topology of β-strands , or as Rossmann-like by identifying structures in which the last β strand ( β6 ) is missing ( S5 Table ) . A variant of M . HaeIII containing four stabilizing mutations and with wild-type-like activity was the starting point for generating the Glu29 mutants [72] . The pASK-IBA3+vector ( IBA , ampicillin resistance ) plasmid containing the gene for the stabilized M . HaeIII was used as a template for PCR amplification . Mutants in position 29 were constructed by site-directed mutagenesis . The Glu codon was replaced with the Gln codon ( CAA ) , Thr codon ( ACC ) , Leu codon ( CTG ) , Asp codon ( GAT ) , Trp codon ( TGG ) , Ala codon ( GCG ) , Val codon ( GTG ) , or Ser codon ( AGC ) . The mutant encoding plasmids were transformed into E . coli MC1061 , [mcrA0 relA1mcrB1 hsdR2 ( r-m+; in which DNA methylation is not toxic ) bearing the GroEL/ES encoding plasmid pGro7 ( chloramphenicol resistance; Takara ) to assist the folding of compromised mutants [72] . Transformants were selected by growth in the presence of ampicillin and chloramphenicol . The methyltransferase activity was tested by treatment of the extracted plasmid with the cognate restriction enzyme , HaeIII . The level of plasmid protection by virtue of methylation by M . HaeIII was determined by gel analysis . Bacteria were grown with no inducer or under induction ( 0 . 2 μg/ml anhydrotetracycline ) and with 0 . 05% arabinose for induction of GroEL/ES expression . Wild-type M . HaeIII gave full protection even when basally expressed ( no inducer ) . Time-dependent in vitro methylation assays were performed with purified enzyme variants ( 0 . 1–8 μM ) essentially as described [73] , using H3-labeled SAM ( 0 . 1–8 μM ) and DNA substrate carrying nine methylation GGCC sites per molecule at 2 . 5 nM . We carried out quantum mechanical electronic structure calculations on models M1 and M2 ( S1 Text ) by using the M06-2X/6-31+G ( d , p ) [74 , 75] model chemistry including the effect of aqueous solvent by using the SMD solvation model [76] . All electronic structure calculations were performed with Gaussian09 [77] . We performed an exhaustive conformational search for model M1 ( Fig 4A ) . Starting from the lowest-energy optimized structures obtained with model M1 , namely 2E-endo and 3E-exo , we carried out a relaxed potential energy surface scan along the coordinate defined by α ( see Fig 5A ) . In the scan , all degrees of freedom were optimized with the exception of the angle α . This was accomplished by interfacing the Gaussian 09 program49 with a utility program we wrote that allows a constraint on the angle between two vectors . For model M2 ( Fig 5B ) , after carrying out a conformational analysis of the molecule of adenosine and an analysis to find the best conformations that lead to a double hydrogen bond with a molecule of acetate , three fully optimized structures of model M2 , denoted as g-t , g-a , and t-t , were found . These structures were taken as initial geometries to explore the potential energy surface ( PES ) . The PES was explored by a combination of successive relaxed energy minimization scans along two angles and a dihedral angle that equals to perform a scan along the angle α ( see S1 Text ) . | Common descent is the hallmark of Darwinian evolution . Homology of biological traits , and particularly of protein sequences and structures , serves as an indication for divergence from a common ancestor and a means of assigning phylogenetic relationships . However , because of shared functional demands and chemical-physical constraints , proteins that evolved independently of one another often converge on very similar molecular traits , including structure and sequence . We tested the widely accepted hypothesis of common ancestry of several major enzyme classes , comprising hundreds of different families and using different cofactors and catalytic chemistries . Although they share the same overall architecture—the Rossmann fold—these enzymes show no significant sequence homology across different classes . We describe an analysis based on the omnipresence of a single residue across these classes: an acidic aspartate or glutamate residue that binds ribose , the common denominator of the different cofactors used by these enzymes . We show that Rossmann enzymes possess a unique interaction geometry that represents a fingerprint of common ancestry rather than an outcome of molecular constraint . We thus provide the first systematic test of divergence versus convergence of a highly abundant protein motif and assign common descent in one of the most ancient and functionally diverse protein folds . | [
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... | 2016 | An Ancient Fingerprint Indicates the Common Ancestry of Rossmann-Fold Enzymes Utilizing Different Ribose-Based Cofactors |
Kaposi’s sarcoma-associated herpesvirus ( KSHV ) binding to the endothelial cell surface heparan sulfate is followed by sequential interactions with α3β1 , αVβ3 and αVβ5 integrins and Ephrin A2 receptor tyrosine kinase ( EphA2R ) . These interactions activate host cell pre-existing FAK , Src , PI3-K and RhoGTPase signaling cascades , c-Cbl mediated ubiquitination of receptors , recruitment of CIB1 , p130Cas and Crk adaptor molecules , and membrane bleb formation leading to lipid raft dependent macropinocytosis of KSHV into human microvascular dermal endothelial ( HMVEC-d ) cells . The Endosomal Sorting Complexes Required for Transport ( ESCRT ) proteins , ESCRT-0 , -I , -II , and–III , play a central role in clathrin-mediated internalized ubiquitinated receptor endosomal trafficking and sorting . ESCRT proteins have also been shown to play roles in viral egress . We have recently shown that ESCRT-0 component Hrs protein associates with the plasma membrane during macropinocytosis and mediates KSHV entry via ROCK1 mediated phosphorylation of NHE1 and local membrane pH change . Here , we demonstrate that the ESCRT-I complex Tsg101 protein also participates in the macropinocytosis of KSHV and plays a role in KSHV trafficking . Knockdown of Tsg101 did not affect virus entry in HMVEC-d and human umbilical vein endothelial ( HUVEC ) cells but significantly inhibited the KSHV genome entry into the nucleus and consequently viral gene expression in these cells . Double and triple immunofluorescence , proximity ligation immunofluorescence and co-immuoprecipitation studies revealed the association of Tsg101 with the KSHV containing macropinosomes , and increased levels of Tsg101 association/interactions with EphA2R , c-Cbl , p130Cas and Crk signal molecules , as well as with upstream and downstream ESCRT components such as Hrs ( ESCRT-0 ) , EAP45 ( ESCRT-II ) , CHMP6 ( ESCRT-III ) and CHMP5 ( ESCRT-III ) in the KSHV infected cells . Tsg101 was also associated with early ( Rab5 ) and late endosomal ( Rab7 ) stages of KSHV intracellular trafficking , and CHMP5 ( ESCRT-III ) was also associated with Rab 5 and Rab 7 . Knockdown of Tsg101 significantly inhibited the transition of virus from early to late endosomes . Collectively , our studies reveal that Tsg101 plays a role in the trafficking of macropinocytosed KSHV in the endothelial cells which is essential for the successful viral genome delivery into the nucleus , viral gene expression and infection . Thus , ESCRT molecules could serve as therapeutic targets to combat KSHV infection .
Kaposi’s sarcoma-associated herpesvirus ( KSHV ) is implicated in the etiology of Kaposi’s sarcoma ( KS ) [1 , 2] , primary effusion B-cell lymphoma ( PEL ) or body-cavity B-cell lymphoma ( BCBL ) , and B-cell proliferative multicentric Castleman’s disease ( MCD ) [3 , 4] . KSHV infects a variety of in vitro and in vivo target cells such as endothelial cells , B cells , monocytes , epithelial cells and keratinocytes , and establishes latency . KSHV entry into the cell is the initial crucial step in its replication cycle and KSHV utilizes a complex multistep process involving interactions of its multiple envelope glycoproteins with several host cell surface receptors . Infection of adherent human microvascular dermal endothelial cells ( HMVEC-d ) and fibroblast cells ( HFF ) is initiated by the binding of viral envelope glycoproteins gB , gpK8 . 1A , gH and ORF4 with the cell surface heparan sulfate ( HS ) molecule . This is followed by sequential interactions with integrin α3β1 , αVβ3 , and αVβ5 , the integrin associated CD98/xCT molecule and the entry receptor EphA2R molecule [5–9] . KSHV enters the human endothelial , fibroblast , epithelial , and B cells by endocytosis [10–13] . KSHV is detected inside the endocytic vesicles as early as 5 min post-infection ( p . i . ) in HMVEC-d , human umbilical vein endothelial cells [HUVEC] and HFF cells [11–13] . KSHV capsid is released from the endosome into the cytoplasm in an acid pH-dependent manner and the capsid rapidly reaches the nuclear periphery within 15 min p . i . via the microtubules [10 , 11 , 14] . Macropinocytosis , a particular form of endocytosis for cargo internalization , is used as the major route of productive KSHV infection in HMVEC-d and HUVEC cells [11] . KSHV co-endocytosed with the macropinocytosis marker dextran , colocalized with the early endosome marker Rab5 and late endosome marker Rab 7 during entry into the endothelial cell [8 , 15] , and viral entry was blocked by macropinocytosis inhibitors EIPA and Rottlerin [11] . Our studies have shown that KSHV interaction with cell surface integrins results in a rapid autophosphorylation of focal adhesion kinase ( FAK ) , a non-receptor tyrosine kinase , which in turn activates a cascade of signal molecules such as Src , phosphatidylinositol 3-kinase ( PI3-K ) , Rho-GTPases ( RhoA , Rac , and Cdc-42 ) , and ROS [5–9] . Simultaneous PI3-K mediated tyrosine phosphorylation of the adaptor E3 ubiquitin ligase c-Cbl protein results in the monoubiquitination of α3β1 and αVβ3 integrins and rapid lateral translocation of virus-bound α3β1 and αVβ3 integrins into the lipid raft ( LR ) regions of the plasma membrane of HMVEC-d cells . LR translocated KSHV interacts with and activates LR-associated Ephrin A2 receptor tyrosine kinase ( EphA2R ) , which results in recruitment of the c-Cbl-integrin-myosin IIA light chain ( MLC ) complex to the LR region and amplification of Src , PI3-K and c-Cbl activation that are crucial for macropinocytosis [16 , 17] . Virus particles bound to polyubiquitinated αVβ5 in the non-LR regions of the membranes enter the cells by clathrin-mediated endocytosis which localizes with lysosomes [17] . KSHV infection of HMVEC-d cells also simultaneously induces the LR translocation of calcium and integrin-binding protein 1 ( CIB1 ) which associates with EphA2R , Src , c-Cbl , PI3-K , alpha-actinin-4 , and myosin IIA , as well as scaffold p130Cas and downstream adaptor Crk molecules to form a macropinosome complex [15 , 18] . This enhances the EphA2R cross talk with the cytoskeleton and actin-MLC mediated bleb formation , and c-Cbl mediated ubiquitination of actin and MLC results in the macropinocytosis of KSHV particles [16] . However , post-entry trafficking of viral particles is not fully understood . The main organelles in the classical clathrin endocytic pathway are early endosome , maturing endosome , late endosome and endolysosome . Endosomal Sorting Complexes Required for Transport ( ESCRT ) proteins , ESCRT-0 , -I , -II , -III and VPS4 complexes [19] , play critical roles in sorting ubiquitinated membrane proteins into early endosomes followed by maturing endosomes , and delivery into lysosomes [20] . Studies have revealed the hierarchical assembly of these complexes on endosomal membranes with ESCRT-0 as the most upstream molecules to be recruited . ESCRT-0 recruits ESCRT-I which then recruits the ESCRT-II complex that subsequently recruits the ESCRT-III complex proteins on the endosomal membrane . The ESCRT-0 , -I , -II and -III complex proteins ubiquitinate the cargo while the VPS4 complex proteins have been shown to play a vital role in recycling the ESCRT-III complex proteins [21] . In our recent study , we have shown that ESCRT-0 Hrs protein plays a role during KSHV entry in HMVEC-d cells [22] . The Hrs protein was shown for the first time to be associated with the plasma membrane during macropinocytosis and aids the entry of KSHV via ROCK1 facilitated phosphorylation of the intracellular pH-regulating protein , NHE1 , and a local membrane pH change required for macropinocytosis [22] . The tumor susceptibility gene 101 ( Tsg101 ) , which is a crucial member of the ESCRT-I complex , has been documented to be essential for the recruitment of subsequent ESCRT complexes . Tsg101 is an important component of the ESCRT machinery mediating the biogenesis of multi-vesicular bodies , and thus plays an essential role in cargo degradation and recycling of membrane receptors [23] . The Tsg101 protein also plays vital functions during the abscission stage of cytokinesis , thereby ensuring that the two daughter cells separate completely [24] . In recent years , the Tsg101 protein has been shown to support the efficient budding of several enveloped viruses and thus facilitating viral egress [25–29] . It also plays a key role in facilitating the interaction of viral matrix proteins and ESCRT components [30 , 31] . A recent study reported that Tsg101 plays an important role during Crimean-Congo hemorrhagic fever virus ( CCHFV ) entry via the multi-vesicular body ( MVB ) pathway into host cells , and silencing Tsg101 and other ESCRT components prevented CCHFV infection [32] . Tsg101 has also been reported to play key roles in human papillomavirus and Echovirus 1 infection [33 , 34] and mediates the receptor sorting into multivesicular endosomes during vesicular stomatitis virus infection [35] . In the present study , we evaluated the role of Tsg101 in the macropinocytic entry of KSHV and infection . We demonstrate that although Tsg101 did not affect the entry of KSHV in HMVEC-d and HUVEC cells , it is important for the nuclear entry of KSHV genome and gene expression . The Tsg101 protein interacts with the signal complex proteins induced by KSHV binding and entry of HMVEC-d cells , as well as with other upstream and downstream ESCRT proteins . We also demonstrate that Tsg101 is important for the KSHV transition from early to late endosomes which suggest that Tsg101 plays a role in KSHV trafficking in endothelial cells .
Primary human dermal microvascular endothelial cells ( HMVEC-d CC-2543; Clonetics-Lonza , Walkersville , MD ) and human umbilical vein endothelial cells ( HUVEC CC-2517; Clonetics-Lonza ) were purchased at the lowest possible passage number ( 3–4 ) , and cultured in endothelial cell basal medium 2 ( EBM2 ) supplemented with growth factors ( Cambrex , Walkersville , MD ) and endothelial cell growth medium , respectively . KSHV positive primary effusion lymphoma ( PEL ) cell line BCBL-1 carrying >80 copies of latent viral genome was cultured in RPMI 1640 GlutaMax ( Gibco Life Technologies , Grand Island , NY ) supplemented with 10% ( v/v ) fetal bovine serum ( FBS , HyClone , Logan , UT ) , and 1% penicillin-streptomycin ( Gibco ) [5] . All cells were regularly tested and confirmed to be mycoplasma negative using Mycoalert kit ( Lonza ) . The KSHV lytic cycle in BCBL-1 cells was induced by TPA ( 12-O-Tetradecanoyl-phorbol-13-acetate; from Millipore Sigma , Billerica , MA ) followed by supernatant collection and virus purification as per the procedures described previously [5] . Briefly , about 1 , 500 ml of BCBL-1 cells were cultured to a density of 5 x 106/ml and induced with a 20 ng/ml concentration of TPA . On the sixth day , the culture supernatant was collected and centrifuged at 5 , 000 rpm for 10 minutes at 4°C in a Beckman JLA rotor to remove the cells and cell debris . The supernatant was centrifuged again at 15 , 000 rpm for 2 h at 4°C to pellet the virus . The pellets were resuspended in 1/100 starting volume of DMEM without phenol red indicator and without serum . The suspension was clarified by three centrifugations at 1 , 000 rpm for 10 min to remove any residual cell debris and filtered through 0 . 45-μm membrane filter ( GE healthcare , Buckinghamshire , UK ) . The suspension was centrifuged at 30 , 000 rpm at 4°C for 2 h in a Beckman 90Ti rotor to pellet the virus and resuspended in serum free DMEM without phenol red . The aliquots of purified ( concentrated ) KSHV were stored at -80°C till further use . Viral DNA was extracted and copy number estimated by real-time DNA-PCR using primers for the KSHV ORF73 gene as described previously [36] . Unless stated otherwise , all de novo infections were carried out with 30 KSHV DNA copies/cell ( multiplicity of infection-MOI ) , and the same batch of KSHV was used for all sets of experiments . The thymidine analog 5-bromo-2-deoxyuridine ( BrdU ) labeling reagent ( Life Technologies , Thermo-Fisher Scientific , Carlsbad , CA ) at a ratio of 1:100 ( v/v ) was used to metabolically label the KSHV DNA by adding it to the culture medium of BCBL-1 cells on day 1 and day 3 of TPA induction . The labeled virus from the day 5 culture supernatant was purified and quantitated as described above [5] , and infection was done with 30 KSHV DNA copies/cell . Texas Red conjugated dextran , Alexa 594 conjugated Phalloidin , Protein A-Sepharose 6 MB and Protein G–Sepharose CL-4B Fast Flow beads were from Amersham Pharmacia Biotech , Piscataway , NJ . Mouse monoclonal anti-KSHV gpK8 . 1A ( 4A4 ) , LANA-1 , and rabbit anti-gB antibodies were generated in our laboratory [37 , 38] . All the other antibodies used for this study were obtained from commercial vendors and details are given below ( Table 1 ) . The siRNA oligonucleotides against Tsg101 ( pool of 3 target specific siRNAs ) were purchased from Santa Cruz Biotechnology , Inc . , Santa Cruz , CA . HMVEC-d cells were transfected with target specific siRNA using the Neon Transfection System ( Invitrogen , Carlsbad , CA ) according to the manufacturer's instructions . Briefly , sub-confluent cells were harvested from the culture flasks , washed once with 1x phosphate-buffered saline ( PBS ) and resuspended at a density of 1x107 cells/ml in resuspension buffer R ( Invitrogen ) . 10 μl of this cell suspension was gently mixed with 100 pmol of control or target specific siRNA and then microporated at RT using a single pulse of 1 , 350 V for 30 ms . After microporation , cells were distributed into pre-warmed complete medium and placed at 37°C in a humidified 5% CO2 incubator . 48 h post-transfection , the cells were analyzed for knockdown efficiency by Western blotting . Cells were lysed in radioimmunoprecipitation assay ( RIPA ) lysis buffer ( 15 mM NaCl , 1 mM MgCl2 , 1 mM MnCl2 , 2 mM phenylmethylsulfonyl fluoride and protease inhibitor mixture [Sigma] ) . The lysates were sonicated and centrifuged at 12 , 000 rpm for 10 min at 4°C followed by estimation of protein concentrations by BCA protein assay reagent ( Pierce , Rockford , IL ) . Equal concentrations of proteins were separated on SDS-PAGE , transferred to a nitrocellulose membrane and probed with the indicated specific primary antibodies followed by incubation with species-specific HRP-conjugated secondary antibody . The chemiluminescence based detection of immunoreactive protein bands ( Pierce ) was performed as per the manufacturer's protocol . The bands were scanned using the FluorChem FC2 and Alpha-Imager Systems ( Alpha Innotech Corporation , San Leonardo , CA ) . HMVEC-d and HUVEC cells were either mock or KSHV infected ( 30 DNA copies/cell ) at 37°C . After 2 h of incubation , the cells were washed twice with Hank’s balanced salt solution ( HBSS ) to remove the unbound virus , treated with 0 . 25% trypsin-EDTA for 5 min at 37°C to remove the bound but noninternalized virus , and washed [14 , 36] . The cells were also treated with DNAse I for 10 min at 37°C ( amplification grade; Invitrogen , Carlsbad , CA ) according to the manufacturer's protocol to remove any contaminating DNA and assess only the viral DNA that remained internalized and associated with the cell [36] . The total DNA was extracted from both uninfected and infected cells using a DNeasy kit ( Qiagen , Valencia , CA ) followed by amplification of the KSHV ORF73 gene by real-time DNA PCR using primers and probes described previously [14 , 36] . The KSHV ORF73 gene cloned in the pGEM-T vector ( Promega , Madison , WI ) was used as the external standard . A standard curve was generated and the relative viral copy numbers were calculated as a measure of KSHV entry . A pure nuclear fraction was obtained from cells using the Nuclei EZ Prep nuclear isolation kit ( Sigma ) as per the manufacturer’s instructions . Briefly , HMVEC-d and HUVEC cells were infected with KSHV ( 30 DNA copies/cell ) for 2 h at 37°C , washed twice with HBSS , treated with 0 . 25% trypsin-EDTA for 5 min at 37°C to remove the bound but noninternalized virus , washed and treated with DNAse I for 10 min at 37°C . Cells were subsequently washed , lysed on ice for 5 min with a mild lysis buffer ( Sigma ) followed by centrifugation at 500xg for 5 min to obtain the concentrated nuclear pellet . The cytoskeletal components loosely bound to the nuclei were removed by subjecting the nuclear pellet to a second cycle of lysis and centrifugation steps as described previously [14] . The pure nuclear fraction was then used for DNA isolation followed by amplification of the KSHV ORF73 gene by real-time DNA PCR as described previously [14 , 36] to measure the nuclear entry of KSHV genome . HMVEC-d and HUVEC cells were infected with KSHV ( 30 DNA copies/cell ) for 2 h at 37°C , washed twice with HBSS , treated with 0 . 25% trypsin-EDTA for 5 min at 37°C to remove the bound but noninternalized virus . After 48h , cells were washed , treated with DNAse I for 10 min at 37°C , washed , total RNA was extracted from cell lysates using an RNeasy kit ( QIAGEN ) , quantified and subjected to one step real-time RT-PCR ( EZ RT-PCR core reagents , Applied Biosystems , Branchburg , NJ ) for the ORF73 gene using gene specific primers and TaqMan probes as described previously [36] . A standard curve was derived using the Ct values for different dilutions of in vitro transcribed transcripts to obtain the relative copy numbers of the transcripts [36] . The expression levels of ORF73 were normalized to GAPDH ( glyceraldehyde-3-phosphate dehydrogenase ) gene expression . HMVEC-d cells grown on 8 chambered slides either left uninfected or infected with KSHV ( 30 DNA copies/cell ) were washed with HBSS , treated with trypsin-EDTA for 2 min at 37°C , fixed with 4% paraformaldehyde solution for 20 min , permeabilized using 0 . 2% Triton X-100 in PBS for 5 min followed by washing with PBS . The cells were then blocked using Image-iT FX signal enhancer ( Invitrogen ) for 20 min at room temperature , and incubated with target specific primary antibodies followed by staining with secondary antibodies conjugated to Alexa 488 or 594 . The stained cells were mounted in mounting medium with DAPI ( 4′ , 6′-diamidino-2-phenylindole ) ( Invitrogen ) and visualized with a Nikon 80i fluorescent microscope equipped with Metamorph digital imaging software . The colocalizations of mean pixel intensities were analyzed with the NIS-Elements AR imaging software ( Nikon ) . Mean colocalization pixel intensities were measured in arbitrary units ( a . u . ) and are presented as the percent colocalization . Control siRNA or Tsg101 siRNA transfected cells were infected with BrdU labeled KSHV ( 30 DNA copies/cell ) at 37°C for 30 min . Cells were then washed with HBSS , treated with trypsin-EDTA for 2 min at 37°C , fixed and permeabilized using 0 . 2% Triton X-100 in PBS for 5 min , washed and followed by a denaturation step with 4N hydrochloric acid ( HCl ) for 10 min at RT to expose incorporated BrdU residues [39] . Cells were blocked with Image-iT FX signal enhancer ( Invitrogen ) for 20 min and stained with mouse monoclonal anti-BrdU primary antibody followed by Alexa 488 conjugated secondary antibody staining . Entry of KSHV was analyzed by fluorescence microscopy . At least five independent fields , each containing at least 10 cells , were observed and analyzed as a proportion of DAPI-stained cells . A paired t test was used between control and siRNA treated cells to obtain the P values for the percentage inhibition in entry . Proximity ligation assays were performed using the Duolink PLA kit ( Sigma ) as per manufacturer’s instructions [40 , 41] . Briefly , HMVEC-d cells either left uninfected or infected with KSHV ( 30 DNA copies/cell ) were washed with HBSS , treated with trypsin-EDTA for 2 min at 37°C , fixed with 4% paraformaldehyde for 15 min , permeabilized by 0 . 2% Triton X-100 for 5 min and washed with PBS . The cells were then blocked with Duolink blocking buffer for 30 min at 37°C , washed and incubated with target specific primary antibodies diluted in Duolink antibody diluent and incubated for 1 h at 37°C . The cells were subsequently incubated with specific PLA probes ( PLUS and MINUS ) , followed by hybridization , ligation and amplification . The signal was detected as a distinct fluorescent dot ( Red or Green ) by using a Nikon Eclipse 80i microscope equipped with Metamorph digital imaging software . For controls , cells were also treated as described but reacted only with primary or secondary antibodies to check specificity of the PLA reactions . HMVEC-d cells were lysed in lysis buffer containing 25 mM Tris-HCl , pH 7 . 5 , 150 mM NaCl , 1% NP40 , 2 mM EDTA , 10% Glycerol , and protease inhibitor mixture . For immunoprecipitation , 300–500 μg of clarified and precleared cell lysate proteins were incubated overnight with appropriate primary antibody at 4°C , and the immune complexes were captured by protein A or G-Sepharose . The immune complexes were then eluted in SDS-PAGE sample buffer and analyzed by Western blotting with specific primary and secondary antibodies [42] . The results are expressed as means ± SD of at least three independent experiments ( n≥3 ) to ensure reproducibility . The p value was calculated using a two tailed Student’s T test . In all tests , p<0 . 05 was considered statistically significant .
To determine the potential role of ESCRT-I Tsg101 protein during KSHV entry in HMVEC-d and HUVEC cells , we knocked down ( KD ) the Tsg101 protein by specific siRNA and checked the knockdown efficiency . We observed more than 90% reduction in Tsg101 levels in HMVEC-d and HUVEC cells by western blot analysis and results for HMVEC-d cells are shown in Fig 1A , lanes 1 and 2 . To determine whether Tsg101 plays any roles in the KSHV entry and/or nuclear delivery of viral genome stages of infection [15] , siControl and siTsg101 transfected HMVEC-d and HUVEC cells were infected with KSHV for 2 h , washed , treated with 0 . 25% trypsin-EDTA for 5 min at 37°C to remove the bound but noninternalized virus , washed , treated with DNAse I for 10 min at 37°C , and real-time DNA PCR carried out with extracted DNA . The results showed almost similar levels of KSHV entry in both control ( 2802 ± 140 DNA copy numbers ) and siTsg101 ( 2612 ± 112 DNA copy numbers; ~10% inhibition ) treated HMVEC-d cells ( Fig 1B ) and HUVEC cells ( 3686 ± 294 vs . 3424 ± 332 DNA copy numbers; 7% inhibition ) ( Fig 1C ) . This demonstrated that Tsg101 had no significant role in KSHV entry in HMVEC-d and HUVEC endothelial cells . To determine whether Tsg101 plays a role in nuclear delivery of KSHV genome , control and Tsg101 siRNA transfected HMVEC-d cells were cultured in 8 chambered glass slides , infected with BrdU genome labeled KSHV for 30 min followed by immunofluorescence assay ( IFA ) to track the viral particles . We have shown before that BrdU labeling had no effect on virus infectivity [18 , 39] . In siControl cells , at 30 min post-infection ( p . i . ) , most of the BrdU-labeled KSHV genome was associated with the nuclei of the infected cells ( Fig 1D , white arrows ) with few viral particles in the cytoplasm . In contrast , in siTsg101 cells we observed a significant decrease ( ~60% ) in the nuclei associated BrdU-KSHV genome with the majority of the viral particles still in the cytoplasm of the infected cells ( Fig 1D , red arrows and 1E ) . To further validate the IFA findings , we infected the control and siTsg101 transfected HMVEC-d and HUVEC cells with KSHV ( 30 DNA copies/cell ) , isolated the nuclear fractions , extracted the DNA and determined the nuclei associated viral genomes by real-time DNA-PCR for the KSHV ORF73 gene . In contrast to the control siRNA transfected HMVEC-d cells with KSHV DNA copy numbers of about 2441 ± 92 , in Tsg101 siRNA transfected cells , we observed a significant decrease ( ~ 54% ) in the nuclei associated KSHV genome copy numbers ( 1123 ± 115 ) ( Fig 1F ) . A similar result was obtained for HUVEC cells transfected with siControl ( 2503 ± 150 ) compared to siTsg101 ( 1061 ± 89 ) cells with a decrease of ~ 58% in the nuclei associated KSHV genome copy numbers ( Fig 1G ) . To determine the effect of Tsg101 KD on KSHV gene expression during de novo infection , real-time reverse transcriptase-PCR ( RT-PCR ) was performed . For this , control and siTsg101 transfected HMVEC-d and HUVEC cells were infected with KSHV ( 30 DNA copies/cell ) for 48 h followed by real-time RT-PCR for the KSHV ORF73 gene expression . The siTsg101 cells showed ~70% downregulation of viral gene expression compared to siControl cells for both HMVEC-d ( Fig 2A ) and HUVEC ( Fig 2B ) cells . An IFA was performed to validate the PCR data . We examined the expression of KSHV latency associated LANA-1 protein ( ORF 73 ) in the control and siTsg101 transfected HMVEC-d cells infected with KSHV for 48 h . The IFA results were also consistent with real-time RT-PCR findings as we observed ~ 60% reduction in the characteristic nuclear punctate LANA-1 staining in the siTsg101 cells ( Fig 2C and 2D ) . These studies collectively demonstrated that Tsg101 is dispensable for KSHV entry but important for KSHV nuclear delivery in primary HMVEC-d and HUVEC endothelial cells . To determine whether Tsg101 colocalizes with KSHV particles and plays a role in viral trafficking through the cytoplasm , we performed IFA by infecting HMVEC-d cells with KSHV for 5 , 10 and 30 min followed by staining for Tsg101 and KSHV envelope glycoprotein gB . A significant colocalization was observed between Tsg101 and KSHV gB within 5 min p . i . which was sustained till the observed 30 min p . i . ( Fig 3A , yellow spots , white arrows ) . KSHV colocalized with Tsg101 at the cell periphery within 5 min p . i . and reached the nuclear periphery by 30 min p . i . ( Fig 3A ) . To validate the colocalization of Tsg101 with KSHV , HMVEC-d cells were infected with KSHV for 10 min , lysed and immunoprecipitated with anti-Tsg101 antibody and western blotted for KSHV glycoprotein gB . The IP results showed a faint band of gB which suggest a direct or indirect association of Tsg101 with KSHV particles during de novo infection ( Fig 3B , i , lane 2 ) . The whole cell lysate proteins analyzed by western blot did not show significant change in the total protein levels of these molecules ( Fig 3B , ii-iv ) . Since we observed that Tsg101 KD did not hamper virus entry but drastically reduced nuclear delivery of viral genome , we next sought to define the importance of Tsg101 in KSHV trafficking . siTsg101 and siControl transfected HMVEC-d cells were infected with KSHV for 30 min , and stained for KSHV-envelope glycoprotein gpK8 . 1A and rhodamine-phalloidin for filamentous actin . KSHV particles were observed near the cell periphery in siTsg101 cells while in control siRNA cells , KSHV particles reached the nuclear periphery within 30 min p . i . ( Fig 3C , white arrows ) . These results demonstrated that the traffic of KSHV particles towards the nucleus requires Tsg101 and suggested that Tsg101 is playing a role in KSHV trafficking towards a productive infection . We have previously shown that macropinocytosis is the major pathway of KSHV entry in HMVEC-d and HUVEC cells [11 , 15–18] and the schematic model in Fig 4C shows the gradual process of bleb formation that subsequently leads to KSHV macropinocytosis . To determine whether Tsg101 assists in macropinocytosis of KSHV , we performed a triple colocalization IFA by staining for Tsg101 in the HMVEC-d cells incubated with the macropinocytic marker dextran ( Texas Red labeled ) in the presence or absence of virus infection for 5 , 10 and 30 min . Compared to the uninfected cells , KSHV infected cells showed a substantial increase in triple colocalization of KSHV-gB , Tsg101 and dextran molecules that gradually increase during the course of infection ( Fig 4A , yellow arrows ) . The mean pixel intensities of colocalizations were analyzed which are shown in Fig 4B . As an important component of the ESCRT machinery mediating the biogenesis of multi-vesicular bodies during clathrin mediated endocytosis , Tsg101 is associated with early and late endosomes as well as recycling vesicles and lysosomes . As our choices were very limited for negative controls , we used antibodies against the GM130 protein , a cis-Golgi marker protein , as a negative control for the triple IFA experiments with anti-Tsg101 and anti-BrdU ( KSHV genome ) antibodies . We observed the colocalization of Tsg101 only with KSHV ( S1 Fig , cyan color , yellow arrows ) . In contrast , Tsg101 did not colocalize with GM130 as shown by the absence of magenta color spots while GM130 and virus did not colocalize as shown by the absence of yellow color spots ( S1 Fig ) . These results demonstrated the specificity of Tsg101 colocalization with KSHV containing macropinosomes and suggested that Tsg101 is associated with KSHV containing macropinosomes formed during entry [15–18] and productive trafficking in the endothelial cells ( Fig 4C ) . KSHV interacts with HMVEC-d cell surface HS molecules , followed by sequential interaction with various integrins and the entry receptor Ephrin A2 receptor tyrosine kinase ( EphA2R ) [8 , 18] . This interaction also simultaneously activates the adaptor c-Cbl early during infection and recruits a signaling complex comprised of HMVEC-d cells scaffold protein p130Cas and adaptor Crk molecule [15] ( Fig 4C ) . To determine whether Tsg101 interacts with any of the signal complex molecules , serum starved HMVEC-d cells were uninfected or KSHV infected for 5 , 10 and 30 min , lysed and immunoprecipitated with anti-Tsg101 antibody and Western blotted for EphA2R , c-Cbl , p130Cas and Crk molecules . The IP results clearly demonstrated an increase in interaction of Tsg101 with all these signal molecules during KSHV infection with a maximum interaction at 10 min p . i . and detectable over the observed 30 min p . i . ( Fig 5Ai , i-iv , lanes 2–4 ) . In contrast , no appreciable association of Tsg101 was observed with these signal molecules in the uninfected cells ( Fig 5Ai , i-iv , lane 1 ) . These results corroborate our previous findings that EphA2R , c-Cbl , p130Cas , and Crk association is significantly enhanced by KSHV infection [15] . Whole-cell lysate ( WCL ) proteins analyzed by Western blot demonstrated that KSHV infection did not significantly change the total protein levels of these molecules ( Fig 5Aii , vi-x , lanes 1–4 ) . Fig 5Aiii shows the schematic model of these interactions during KSHV infection . We also utilized PLA to validate the IP results as PLA can detect an endogenous individual protein or interaction between two proteins . PLA is based on the principle that if two epitopes or proteins are within the proximity of 40 nm or less , the PLA oligo probes linked to two secondary antibodies bound to primary antibody-antigen complexes will be amplified to give a PLA signal visualized as a fluorescent dot . HMVEC-d cells were either uninfected or KSHV infected for 10 min and PLA was performed to observe the difference in association levels of Tsg101 with all the signal molecules activated during KSHV entry ( Fig 5B , 5D , 5F and 5H ) . The PLA results corroborated with the IP results and clearly demonstrated a significant increase in the association levels of Tsg101 with EphA2R ( Fig 5B ) , c-Cbl ( Fig 5D ) , p130Cas ( Fig 5F ) and Crk ( Fig 5H ) at 10 min p . i . in infected cells compared to control cells . Fig 5C , 5E , 5G and 5I show the corresponding graphical representation of the average of PLA interaction ( colocalization ) dots per cell . Collectively , these results demonstrated that increased levels of Tsg101 interaction with the EphA2R and other signal molecules induced by KSHV during entry in HMVEC-d cells . KSHV enters the endothelial cells by macropinocytosis , and a cargo internalized by this process of endocytosis is generally directed from early to late endosomal stages [43] . To decipher the role of Tsg101 in KSHV trafficking in endothelial cells , we performed IFA to observe the localization of Tsg101 in various stages of endosomal maturation . HMVEC-d cells were either left uninfected or infected with KSHV for 5 , 10 and 30 min . IFA was performed by staining for Tsg101 and Rab 5 , an early endosomal marker ( Fig 6A ) . KSHV infection increased the association of Tsg101 with the early endosomes ( Fig 6A and 6B ) , and the infection did not increase the total level of Rab5 protein ( Fig 6E ) . We next inspected the role of Tsg101 in KSHV trafficking by tracking its association with Rab7 , a late endosomal marker ( Fig 7A ) . IFA analysis revealed a substantial increase in Tsg101 localization in Rab7 positive endosomes of HMVEC-d cells during KSHV infection in a time dependent manner ( Fig 7A and 7B ) , and the levels of Rab7 protein remained the same during infection ( Fig 7E ) . To validate the findings observed in IFA , we next carried out PLA . As can be seen in Fig 6C and Fig 7C , PLA reactions also confirmed the close association of Tsg101 with both Rab5 ( Fig 6C and 6D ) and Rab7 ( Fig 7C and 7D ) proteins which increased significantly over the course of KSHV infection compared to uninfected HMVEC-d cells ( Figs 6D and 7D ) . These results clearly demonstrated that the ESCRT-I Tsg101 associated with macropinosomic early and late endosomes during KSHV infection . We have recently shown that Hrs , an ESCRT-0 component , associates with the plasma membranes during KSHV macropinocytosis and plays an important role in virus entry [22] . Hrs also recruits the next ESCRT-I complex followed by subsequent recruitment of other ESCRT complexes ( Fig 8A ) . Since Hrs is an important protein in the ESCRT-0 complex that interacts with Tsg101 to recruit the ESCRT-I complex proteins , we determined whether Tsg101 interacts with other vital proteins of the ESCRT-II and III complexes . Serum starved HMVEC-d cells were mock or KSHV infected for 5 , 10 and 30 min , lysed , immunoprecipitated with anti-Tsg101 antibody and subjected to Western blotting for ESCRT complex proteins , Hrs ( ESCRT-0 ) , EAP45 ( ESCRT-II ) , CHMP5 ( ESCRT-III ) , and CHMP6 ( ESCRT-III ) . A basal level of association of Tsg101 was observed with all the complexes in uninfected HMVEC-d cells ( Fig 8B , i-iv , lane 1 ) . The results demonstrated an increase in interaction of Tsg101 with neighboring ESCRT complex proteins during KSHV infection which was at its maximum at 5 and 10 min p . i . and was detectable over the observed 30 min p . i . ( Fig 8B , i-iv , Lanes 2–4 ) . Western blots of total protein levels demonstrated that viral infection did not alter the expression of these proteins ( Fig 8B , vi-x ) . When PLA was performed , the results corroborated the IP results and clearly demonstrated a significant increase in the association of Tsg101 with ESCRT-0 Hrs ( Fig 8C ) , ESCRT-II EAP45 ( Fig 8E ) , ESCRT-III CHMP6 ( Fig 8G ) , and ESCRT-III CHMP5 ( Fig 8I ) at 10 min p . i . compared to the control cells . Fig 8D , 8F , 8H and 8J show the corresponding graphical representation of the average interacting ( colocalization ) PLA dots per cell . Taken together , these results demonstrated that ESCRT-I Tsg101 protein interacts closely with upstream and downstream ESCRT complex proteins during KSHV entry and trafficking in the HMVEC-d cells . Since Tsg101 interacted with other ESCRT complex proteins during KSHV infection , we next evaluated the association of downstream ESCRT III protein CHMP5 during virus entry . PLA reactions for CHMP5 with Rab5 ( Fig 9A and 9B ) and CHMP5 with Rab7 ( Fig 9C and 9D ) demonstrated the close association of CHMP5 with early and late endosomes , and suggested the involvement of Tsg101 downstream ESCRT complex proteins in KSHV trafficking via Rab5 and Rab7 dependent pathways . Tsg101 has been shown to play an important role in cargo trafficking [44 , 45] . Our results also show that Tsg101 exploits the same endosomal route during macropinocytic entry in HMVEC-d cells ( Figs 4 , 6 , 7 and 9 ) , and studies in Figs 1 , 2 and 3 demonstrated that KSHV particle trafficking towards the nucleus is hampered in the absence of Tsg101 . To determine how Tsg101 knockdown affects KSHV trafficking , IFA was carried out with KSHV infected siControl and siTsg101 RNA transfected HMVEC-d ( Fig 10A and 10E ) and HUVEC cells ( Fig 10B and 10F ) . The percent colocalization based on the mean pixel intensities of the respective IFA are shown in Fig 10C , 10D , 10G and 10H . KSHV association with Rab5 positive early endosomes ( trafficking ) was not significantly affected by Tsg101 knockdown ( Fig 10A–10D ) . In contrast , viral trafficking to the Rab7 positive late endosomes was significantly affected in the Tsg101 knockdown HMVEC-d and HUVEC cells ( Fig 10E and 10F , lower panels , and Fig 10G and 10H ) compared to the control cells ( Fig 10E and 10F , upper panels and Fig 10G and 10H ) . These results suggested that Tsg101 plays a critical role in KSHV trafficking in HMVEC-d and HUVEC cells by probably facilitating the transition from early endosome to late endosome during infection .
Entry into a target host cell is the most important step in any viral infection as the host cells impose restrictions on every step of the virus life cycle , including entry , trafficking , replication and release . KSHV utilizes the macropinocytosis pathway to enter the human primary dermal endothelial cells ( HMVEC-d ) , which is the natural in vivo target of KSHV , leading to the development of Kaposi’s sarcoma . All the steps of macropinocytosis such as the actin modulation , macropinosome assembly , closure , and trafficking are tightly governed by multi-step signal assemblies and amplifications [46–56] . We have shown that KSHV manipulates the host cell's pre-existing signal pathways via its interactions with cell surface receptors such as integrins and the entry receptor Ephrin A2 receptor tyrosine kinase ( EphA2R ) early during infection as one of the best strategies to overcome the obstacles imposed by the host cells and to create an environment that is conducive to infection . Our studies conducted here , as a continuation of our earlier findings , demonstrate the trafficking of KSHV after internalization from the plasma membrane of infected HMVEC-d and HUVEC cells . The highlights of our comprehensive studies are: ( a ) ESCRT-I complex protein Tsg101 plays a role in KSHV trafficking and its absence severely impacts the nuclear delivery of KSHV genome; ( b ) Tsg101 is associated with several KSHV infection-induced host cell signal molecules that are essential for the macropinocytic entry of virus; ( c ) during KSHV infection , Tsg101 interacts substantially with its upstream ( ESCRT-0 ) and downstream ( ESCRT-II and III ) complexes; ( d ) Tsg101 is important for the transition of KSHV containing early endosomes to late endosomes , and ( e ) this is the first report demonstrating that the ESCRT-I complex protein Tsg101 , known to contribute to clathrin-mediated endocytosis , participates in the macropinocytic mode of endocytosis and plays a role in a post-macropinocytic step . Our studies have shown that KSHV interacts with EphA2R in the lipid raft region of HMVEC-d cells along with integrins resulting in the activation of EphA2R and amplification of the FAK , Src , PI3-K and RhoGTPase signaling cascade [57] . The adaptor c-Cbl protein mediated ubiquitination of receptors aids in the amplification of signal cascades , and the adaptor CIB1 protein plays a role in scaffolding EphA2R with cytoskeletal myosin IIA and alpha-actinin-4 during KSHV macropinocytic entry . The CIB1 molecule promotes EphA2R associated signal events and its depletion by shRNA was shown to reduce the KSHV induced bleb formation and activation of EphA2R , Src , Erk1/2 , virus entry , trafficking and productive infection [18] . We further demonstrated the role of scaffold protein p130Cas and adaptor Crk molecule early during KSHV infection of HMVEC-d cells . These molecules were found to be associated with KSHV , EphA2R and CIB1 early during viral infection . The p130Cas knockdown did not affect KSHV entry but considerably reduced nuclear trafficking of viral DNA with KSHV accumulating in the lysosomes [15] . Several studies have shown the association of ESCRT complex proteins with traditional clathrin-mediated endocytosis [21 , 32 , 58] , and there are no reports of the association of any ESCRT proteins with macropinocytosis . Our recent study was the first report to show the association of cytoplasmic ESCRT-0 Hrs protein with the HMVEC-d cell plasma membranes at the site of KSHV infection and macropinosomes , and Hrs is an essential component for KSHV entry in target cells [22] . Hrs translocates to the plasma membrane of KSHV infected cells , associates with α-actinin-4 , mediates recruitment of the ROCK1 molecule which in turn induces the phosphorylation of NHE1 ( Na+/H+ exchanger 1 ) involved in the regulation of local pH changes associated with macropinocytosis of KSHV . Tsg101 has been shown to play important roles during viral egress including the release of influenza virus from infected cells [44] . Although Tsg101’s role in human papillomavirus and Echovirus 1 infection has been studied recently [33 , 34] , its role in macropinocytosis , KSHV entry and trafficking was not known . Results presented here , for the first time , show that ESCRT-I protein Tsg101 associates with the internalized macropinosomes and plays a role in KSHV infection of primary endothelial cells . Tsg101 in the ESCRT-I complex functions mainly as the vacuolar sorting machinery and helps in segregating cargos into typical small vesicles that finally bud into MVB [59] . Impaired MVB sorting has been linked to plasma membrane recycling of endocytosed cargos and major signaling defects . Mutations in several ESCRT proteins have also been linked to a variety of diseases including cancer [60 , 61] . Studies have shown the role of Tsg101 in the delivery of cargo proteins to the late endosomal compartments . In the absence of Tsg101 , the endocytosed EGF receptors did not route to lysosomes , but instead , recycled back to the cell surface; this delayed degradation of receptors resulted in prolonged cell signaling [44] . The lack of Tsg101 also resulted in a massive defect in the cellular secretory pathway [62] . Similarly , Tsg101 knockdown resulted in the absence of the macropinocytosed KSHV particles transiting from the early endosome to late endosomes , and consequently , localization of KSHV particles at the cell periphery and reduction of their traffic towards the nucleus . This observation demonstrates that Tsg101 plays a role in trafficking of KSHV after its entry into the cell . A study on Ebola virus showed that the matrix protein VP40 interacts with Tsg101 in vitro . The study focused on the role of Tsg101 in the late stage of the assembly process at the site of budding at the plasma membrane [27] . Other recent studies also showed that the nucleoprotein NP of the Marburg virus interacts with Tsg101 for efficient budding of virus [28 , 29] . Similarly the influenza virus HA and Nipah virus C protein has been shown to interact with Tsg101 for efficient release of live virus [62 , 63] . Budding and entry of viruses are two separate events and require interactions of several host proteins with viral counterparts . KSHV , however , remains compartmentalized in the macropinosomes / endosomes during its entry and trafficking through the cytoplasm of the endothelial cells . The endosome enclosed virion envelope glycoproteins are associated with the internalized receptors ( integrins and EphA2R ) on the inner side of the endosomes ( Fig 5Aiii ) , and therefore , the viral envelope glycoproteins are probably not directly interacting with the cytoplasmic Tsg101 . We did attempt PLA for KSHV and Tsg 101 but did not observe any PLA dots which suggested that they are not in close proximity and thus there is probably no direct interaction . Hence , the faint band of KSHV glycoprotein gB immunoprecipitated with Tsg101 ( Fig 3B and 3I , lane 2 ) , may not be due to the direct interaction of viral envelope gps within the macropinosome with Tsg101 . Nevertheless , as ESCRT proteins function as the recognizers ( ZIP code readers ) of the ubiquitinated receptors ( ZIP code ) , there is a greater possibility of Tsg101 recognizing the ubiquitinated EphA2R and integrins along with ESCRT-0 Hrs protein on the cytoplasmic side of the macropinosome . Our IP studies demonstrating the co-immunoprecipitation of Tsg101 with EphA2R during KSHV de novo infection with a little such interaction in the uninfected cells , together with the increased PLA Tsg101 and EphA2R dots denoting the close proximity and increased interactions of Tsg101 and EphA2R are suggestive of interactions on the cytoplasmic side of the macropinosome . Our studies have shown that KSHV infection of HMVEC-d cells induced the activation of a signal complex comprised of integrins ( α3β1 and αVβ3 ) , EphA2R , c-Cbl , CIB1 , p130Cas , and Crk which are recruited to the macropinosomes and subsequently in the early endosome to facilitate KSHV entry and trafficking in host cells [15] . Our IP data demonstrating the association of Tsg101 with EphA2R , c-Cbl , p130Cas and Crk signal molecules , which increase significantly at 5 min and sustained til 30 min p . i . ( Fig 5A ) , substantiate our earlier studies on the role of these signal molecules in the macropinocytic entry of KSHV . We have shown that KSHV infection induced c-Cbl mediates the ubiquitination of the KSHV receptors integrin and EphA2R , which are recognized by Hrs which then associates with the KSHV macropinosome . We extended these findings and show that Hrs associates with Tsg101 which in turn associates with its downstream ESCRT-II and -III proteins in the macropinosome ( Fig 11 ) . The ESCRT complexes are recruited sequentially with Hrs being upstream to initiate the recruitment during clathrin mediated endocytosis [64] . Our analysis demonstrates that Tsg101 interacts with both upstream complex Hrs and with downstream complex proteins , EAP45 ( ESCRT-II ) , CHMP6 ( ESCRT-III ) and CHMP5 ( ESCRT-III ) , and CHMP5 and CHMP6 proteins associate with KSHV ( glycoprotein gB ) particles early during infection ( S2 and S3 Figs ) . Our finding of the association of ESCRT-III complex CHMP5 protein with Rab5 and Rab7 positive endosomes demonstrate that other ESCRT complexes could also be playing important roles during macropinosome dependent sorting of internalized cargos . A similar observation was made in a study that showed that CHMP5 regulates the late endosomal function and its loss inhibits lysosomal degradation of activated receptors during mouse embryogenesis [65] . This could be either due to a failure in the recruitment of components required for mediating the fusion event or a failure in the disassociation of the ESCRT-III lattice [65] . The Crimean-Congo hemorrhagic fever virus ( CCHFV ) traffics through the early endosomes in a Rab5-dependent manner to be delivered to the MVB which was not affected by blocking Rab7 [32] . In contrast , our findings confirm the previous results and show that KSHV traffics through the endosomal pathway in a Rab5 and Rab7 dependent manner . During KSHV infection there is also a possibility of recruitment of Rab5 and Rab7 which was also evident from the immunofluorescence analysis . An increase in fluorescence signal for Tsg101-Rab5 and Tsg101-Rab7 was observed upon KSHV infection as compared to the respective uninfected cells ( Figs 6A and 7A ) . New reports have shown that Tsg101 plays a vital role in cargo sorting as its downregulation or inability to interact with neighboring ESCRT proteins prevents the delivery of epidermal growth factor receptor ( EGFR ) to late endosomes thus causing cellular accumulation of ubiquitinated EGFR in early endosomes [58 , 59] . We also observed that KSHV trafficking was severely affected in the absence of Tsg101 . Although KSHV traffics easily through the early endosome in both Tsg101 knockdown as well as control endothelial cells , transition of KSHV from the early to late endosome was significantly blocked in the Tsg101 knockdown cells . These results of blockage in viral transition may not be KSHV specific but definitely suggest that Tsg101 plays an important role during the intracellular trafficking of KSHV and is critical for the transition from early to late endosomes . However , how Tsg101 mediates this transition and the fate of KSHV particles that are stuck in the early endosomes in the absence of Tsg101 are not known . Further extensive studies are required to answer these questions which are beyond the scope of the present study . Overall , our studies reinforced the notion that a ) KSHV has evolved to utilize host cell components efficiently to enter the primary endothelial cell , b ) Tsg101 protein associates with macropinocytosis of KSHV following the traditional endosomal trafficking towards a productive infection , and c ) acts as a key player in regulating KSHV trafficking . Tsg101 knockdown blocking the viral transition from early to late endosomal stages adds a new dimension to the current understanding of host cellular transport proteins involved in KSHV entry and infection , and suggest that Tsg101 can serve as a potential target to control KSHV infection . | KSHV is etiologically associated with human endothelial Kaposi’s sarcoma , and understanding of endothelial infection is essential to design methods to block infection . KSHV infection of endothelial cells is initiated by its interaction with cell surface heparan sulfate , various integrins and the Ephrin A2 receptor tyrosine kinase ( EphA2R ) molecule which results in the induction of integrin-c-Cbl mediated signaling , leading to KSHV entry by the macropinocytic mode of endocytosis . Host ESCRT complex proteins are involved in the cargo trafficking and play roles in viral egress . We have shown that ESCRT-0 Hrs protein facilitates the assembly of signaling molecules in KSHV macropinocytosis . Studies here demonstrate for the first time that the ESCRT-I Tsg101 protein , known to contribute to clathrin-mediated endocytosis , participates in macropinocytosis and plays a role in a post-macropinocytic step of KSHV infection . Tsg101 associates with macropinosomes containing KSHV , receptor ( EphA2R ) , signal molecules ( c-Cbl , p130Cas and Crk ) , and with upstream and downstream ESCRT proteins . Tsg101 is important for the virus to transition from early to late endosomes . These studies reveal that ESCRT proteins can be an important target for therapeutic interventions against KSHV infection . | [
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"viruses",... | 2016 | ESCRT-I Protein Tsg101 Plays a Role in the Post-macropinocytic Trafficking and Infection of Endothelial Cells by Kaposi’s Sarcoma-Associated Herpesvirus |
Human African trypanosomiasis ( HAT ) , also known as sleeping sickness , is a fatal parasitic disease caused by trypanosomes . Current treatment options for HAT are scarce , toxic , no longer effective , or very difficult to administer , in particular for the advanced , fatal stage of the disease ( stage 2 , chronic HAT ) . New safe , effective and easy-to-use treatments are urgently needed . Here it is shown that fexinidazole , a 2-substituted 5-nitroimidazole rediscovered by the Drugs for Neglected Diseases initiative ( DNDi ) after extensive compound mining efforts of more than 700 new and existing nitroheterocycles , could be a short-course , safe and effective oral treatment curing both acute and chronic HAT and that could be implemented at the primary health care level . To complete the preclinical development and meet the regulatory requirements before initiating human trials , the anti-parasitic properties and the pharmacokinetic , metabolic and toxicological profile of fexinidazole have been assessed . Standard in vitro and in vivo anti-parasitic activity assays were conducted to assess drug efficacy in experimental models for HAT . In parallel , a full range of preclinical pharmacology and safety studies , as required by international regulatory guidelines before initiating human studies , have been conducted . Fexinidazole is moderately active in vitro against African trypanosomes ( IC50 against laboratory strains and recent clinical isolates ranged between 0 . 16 and 0 . 93 µg/mL ) and oral administration of fexinidazole at doses of 100 mg/kg/day for 4 days or 200 mg/kg/day for 5 days cured mice with acute and chronic infection respectively , the latter being a model for the advanced and fatal stage of the disease when parasites have disseminated into the brain . In laboratory animals , fexinidazole is well absorbed after oral administration and readily distributes throughout the body , including the brain . The absolute bioavailability of oral fexinidazole was 41% in mice , 30% in rats , and 10% in dogs . Furthermore , fexinidazole is rapidly metabolised in vivo to at least two biologically active metabolites ( a sulfoxide and a sulfone derivative ) that likely account for a significant portion of the therapeutic effect . Key pharmacokinetic parameter after oral absorption in mice for fexinidazole and its sulfoxide and sulfone metabolites are a Cmax of 500 , 14171 and 13651 ng/mL respectively , and an AUC0–24 of 424 , 45031 and 96286 h . ng/mL respectively . Essentially similar PK profiles were observed in rats and dogs . Toxicology studies ( including safety pharmacology and 4-weeks repeated-dose toxicokinetics in rat and dog ) have shown that fexinidazole is well tolerated . The No Observed Adverse Event Levels in the 4-weeks repeated dose toxicity studies in rats and dogs was 200 mg/kg/day in both species , with no issues of concern identified for doses up to 800 mg/kg/day . While fexinidazole , like many nitroheterocycles , is mutagenic in the Ames test due to bacterial specific metabolism , it is not genotoxic to mammalian cells in vitro or in vivo as assessed in an in vitro micronucleus test on human lymphocytes , an in vivo mouse bone marrow micronucleus test , and an ex vivo unscheduled DNA synthesis test in rats . The results of the preclinical pharmacological and safety studies indicate that fexinidazole is a safe and effective oral drug candidate with no untoward effects that would preclude evaluation in man . The drug has entered first-in-human phase I studies in September 2009 . Fexinidazole is the first new clinical drug candidate with the potential for treating advanced-stage sleeping sickness in thirty years .
A major challenge for new drug development is the identification of pharmacologically active compounds with a favourable activity and toxicity profile that can be turned into new drug candidates . The contemporary approach to identifying such compounds is high-throughput screening of large and chemically diverse compound libraries to identify novel pharmacophores , followed by lead optimisation [1] , [2] . Sometimes , this screening effort is narrowed down by using more targeted libraries that are thought to be enriched in compounds with a desired type of activity ( e . g . kinase inhibitors [3] ) . However , promising candidates can also be found by revisiting the wealth of past drug discovery research , during which promising lines of research were sometimes not pursued for commercial or other strategic reasons . In this paper , we report the successful result of a proactive compound mining approach into a well-known class of anti-infectives , the nitroimidazoles , to rediscover fexinidazole , a long forgotten antiparasitic drug candidate . Fexinidazole turned out to be an excellent candidate to cure human African trypanosomiasis ( HAT ) , including the advanced and fatal stage of the disease . An estimated sixty million people in 36 sub-Saharan African countries are at risk for HAT , especially poor and neglected populations living in remote rural areas [4] , [5] . While the number of reported HAT cases has decreased in recent years due to intensified control activities , 50 , 000 to 70 , 000 people are estimated to be infected [6] . In west and central Africa , Trypanosoma brucei gambiense causes a chronic form of sleeping sickness , whereas in eastern and southern Africa T . b . rhodesiense causes an acute form of the disease [7] , [8] . Both forms of HAT occur in two stages: stage 1 ( early , hemolymphatic ) is characterized by non-specific clinical symptoms such as malaise , headache , fever , and peripheral oedema , whereas stage 2 ( late , meningoencephalic ) is characterized by neurological symptoms including behavioural changes , severe sleeping disturbances , and convulsions , which , if left untreated , lead to coma and death [9] , [10] . Available treatments for HAT [8] ( Table 1 ) are few , old , and limited due to toxicity , diminishing efficacy in several geographical regions [11] , [12] , and complexity of use [13] . Treatment is stage-specific , with the more toxic and difficult-to-use treatments being used for stage 2 HAT . NECT , a combination treatment of a simplified course of intravenous eflornithine and oral nifurtimox , has been the only advance in the past 25 years [14] , [15] , and has been recently accepted into the WHO's Essential Medicines List as treatment for stage 2 HAT [16] . Despite being a clear improvement with reduced toxicity and treatment duration , the requirement for intravenous administration is still a limitation . It is estimated that less than 20% of currently infected people have access to treatment or are under any HAT surveillance , due to a combination of lack of effective and field-adapted diagnostics and treatments , combined with extreme poverty and remoteness of the affected populations , including in conflict zones [4] , [17] . To change the dynamics of HAT control and access more patients while improving their case-management , a safe , effective , affordable , and easy-to-use ( short course , preferably oral ) treatment is urgently needed . Nitroimidazoles are a well-known class of pharmacologically active compounds , among which several have shown good activity against trypanosomes [18] . The best-known anti-trypanosomal drug candidate in this class was megazol [19] , [20]; its development was abandoned because of toxicity , in particular mutagenicity [21] , [22] , a known possibility in this chemical family [23] , [24] . However , other members of this family including metronidazole [25] , are widely used as antibiotics , indicating that it is possible to select compounds with an acceptable activity/toxicity profile in this class . A systematic review and profiling of more than 700 nitroheterocyclic compounds ( mostly nitroimidazoles ) from diverse sources was undertaken and included an assessment of antiparasitic activity and mutagenic potential using state-of-the-art scientific methods . From these efforts , fexinidazole , a 2-substituted 5-nitroimidazole , was identified as a promising drug candidate for the treatment of HAT . Fexinidazole ( 1-methyl-2- ( ( p- ( methylthio ) phenoxy ) methyl ) -5-nitroimidazole , CAS registry number 59729-37-2 ) had been in preclinical development in the 1970s and early 1980s as a broad-spectrum antimicrobial agent by Hoechst AG ( now sanofi-aventis ) , selected within a broader series because of its wider range of action , lower toxicity and comparative ease of chemical synthesis [26] , [27] . In 1983 , the in vivo activity of fexinidazole against African trypanosomes was further substantiated [28] . However , fexinidazole's development was not pursued at the time . This paper describes the trypanocidal efficacy and preclinical profile of fexinidazole as a novel clinical drug candidate for HAT , devoid of genotoxic risks for patients . The results show fexinidazole's potential to become a safe , efficacious , affordable , short-course ( less than 14 days ) , oral treatment with a suitable shelf life in tropical conditions . Ideally the treatment will be safe and effective in both stages 1 and 2 HAT caused by T . b . gambiense and T . b . rhodesiense , allowing for significantly simplified diagnosis , treatment and patient-management and ultimately a better control of the disease .
All work was conducted in accredited laboratories and according to international guidelines . Specific references to the relevant authorities are provided below as appropriate . Where not stated , details of specific license holders can be obtained from the appropriate laboratories if required . Fexinidazole and metabolites were prepared for in vitro studies as a stock solution in DMSO further diluted with water or 0 . 5% methylcellulose in water to appropriate concentration required for the assay . For in vivo studies , fexinidazole was prepared as an optimized suspension comprising 5% w/v Tween 80/0 . 5% w/v Methocel in water , unless stated otherwise . A range of pharmacokinetic studies have been performed in different species ( mouse , rat , dog ) in the context of this paper , either as pharmacokinetic studies to establish the PK profile of fexinidazole and its metabolites , or as part of other studies ( safety pharmacology and toxicity ) to demonstrate the systemic exposure of fexinidazole and its metabolites in the conditions of that particular study . In the rat repeated-dose toxicokinetic study , fexinidazole was administered orally by gavage once a day for 28 consecutive days to ten or fifteen Crl:CD ( SD ) IGS BR rats/sex/group at doses of 50 , 200 , or 800 mg/kg/day . A control group received the vehicle alone ( 5% Tween 80/0 . 5% methocel ) . Ten animals/sex/group were sacrificed at the end of the treatment period on day 29 or 30 of study . The remaining 5 animals/sex/group in the control and high-dose groups were sacrificed on day 43 at the end of a 2-weeks observation period . Systemic exposure to fexinidazole and its sulfoxide and sulfone metabolites was evaluated in three additional animals/sex/group . Samples were taken at predose , and 30 min , 1 , 2 , 4 , 8 and 24 h after dosing on days 1 , 14 , and 28 , and in addition at 48 and 72 h after treatment on day 28 . In the dog repeated-dose toxicokinetic study , fexinidazole was given orally by gavage once a day for 28 days to five ( control and high dose ) or three ( low and mid dose ) beagle dogs/sex/dose at the doses of 0 ( control group ) , 50 , 200 , or 800 mg/kg/day . The control group received the vehicle alone ( same as above ) . Systemic exposure to fexinidazole and of its sulfoxide and sulfone metabolites was evaluated on days 1 , 14 and 28 in the same animals used for the toxicological study . Samples were taken at predose , and 30 min , 1 , 2 , 4 , 8 and 24 h after dosing on days 1 , 14 , and 28 , and in addition at 48 and 72 h after treatment on day 28 . For both species , the standard package of toxicological analyses was carried out . Both rat and dog studies were carried out by Accelera , Nerviano Medical Sciences , Italy , according to their internal Standard Operating Procedures , were GLP regulated and were conducted in compliance with the DECRETO LEGISLATIVO 2 Marzo 2007 , No . 50 and OECD Principles of GLP ( January 1998 ) ENV/MC/CHEM ( 98 ) 17 and the ICH regulatory guidelines for repeated-dose toxicokinetics studies ( ICH M3 and S3A ) . Preliminary studies in rat and rabbit have been performed to have an early idea of reproductive and developmental toxicity risks , and to determine dose levels to be used in further pivotal studies . In the rat study , fexinidazole was administered orally by gavage once a day from day 6 to day 17 of gestation or from day 6 of gestation to day 7 of lactation to 10 mated rat Crl:CD ( SD ) IGS BR rats/sex/group at doses of 50 , 200 , or 800 mg/kg/day . A control group received the vehicle alone ( 5% Tween 80/0 . 5% methocel ) . In the rabbit study , fexinidazole was administered orally by gavage once a day from day 6 to day 20 of gestation to 6 inseminated New Zealand White Rabbit KBL females at the dose of 20 , 40 and 80 mg/kg/day . A control group received the vehicle alone ( 5% Tween 80/0 . 5% methocel ) . Both rat and rabbit studies were carried out by Accelera , Nerviano Medical Sciences , Italy , according to their internal Standard Operating Procedures , were GLP regulated and were conducted in compliance with the DECRETO LEGISLATIVO 2 Marzo 2007 , No . 50 and OECD Principles of GLP ( January 1998 ) ENV/MC/CHEM ( 98 ) 17 and the appropriate ICH regulatory guidelines for reproductive toxicology ( ICH S5A ) .
The antiparasitic activity of fexinidazole was assessed in experimental models of HAT . In vitro fexinidazole and its two main metabolites showed trypanocidal activity against the STIB900 laboratory strain of T . b . rhodesiense with very steep dose-response relations when assessed after 72 h of culture ( Figure 1 ) . With an IC50 of 0 . 48–0 . 82 µg/mL , fexinidazole's in vitro potency is weaker than that of the reference drug melarsoprol ( IC50 = 0 . 003 µg/mL ) and other trypanocidal drugs ( Table 2 ) or the abandoned drug candidate megazol ( IC50 = 0 . 02 µg/mL ) , although the two drugs currently used as first line to treat stage 2 HAT have a similarly modest in vitro potency ( eflornithine: 0 . 9 µg/mL; nifurtimox: 0 . 4 µg/mL ) . Importantly , in contrast to melarsoprol and other drugs , fexinidazole has little or no non-specific cytotoxicity . Fexinidazole has a comparable IC50 of 0 . 16–0 . 36 µg/mL against a laboratory T . b . gambiense strain ( STIB930 ) and against six recent T . b . gambiense clinical isolates ( IC50 values from 0 . 30 to 0 . 93 µg/mL ) ( data not shown ) . In vivo , fexinidazole is effective in curing both T . b . rhodesiense and T . b . gambiense acute models of infection at an oral dose of 100 mg/kg/day ( or 50 mg/kg twice a day ) for 4 days ( Table 3A ) . Most significantly , in a T . b . brucei GVR35 infected mouse model of stage 2 HAT involving brain infection , fexinidazole given orally showed a dose-related increase in efficacy , with a dose of 200 mg/kg/day for 5 days being highly effective ( Table 3B ) . In two other independent experiments , 100% cure was obtained in groups of 5 mice receiving an oral dose of 100 mg/kg , twice per day for 5 days ( in these experiments , five daily intraperitoneal injections of 15 mg/kg melarsoprol also cured 100% ) . Of the drugs currently in clinical use ( Table 1 ) , only melarsoprol is effective in this experimental stage 2 HAT model . Fexinidazole is rapidly metabolised in vivo , with the main metabolites being the sulfoxide and sulfone derivatives ( Figure 2 ) [26] . This principle metabolic conversion was confirmed in vitro using rat S9 fractions and hepatocytes from the mouse , rat , dog , monkey and human [Dataset S1] . In this comparative hepatocyte metabolism assay , fexinidazole was rapidly metabolised by all species , with in vitro intrinsic clearance rates highest in monkey ( 6500 mL/min/kg ) > dog ( 5000 mL/min/kg ) > mouse ( 4300 mL/min/kg ) > rat ( 2900 mL/min/kg ) > human ( 125 mL/min/kg ) . No meaningful differences were observed when comparing the in vitro metabolism of fexinidazole by hepatocytes from African-American or Caucasian donors [Dataset S2] . The main metabolic pathways of oxidation to the sulfoxide and sulfone derivatives were also confirmed to be the major route of metabolism in vivo in mice , rats and dogs ( see below ) . As shown above , both metabolites have in vitro anti-trypanosomal activity similar to the parent compound ( IC50 in µg/mL: 0 . 41–0 . 49 for the sulfoxide and 0 . 35–0 . 40 for the sulfone versus 0 . 48–0 . 82 for the parent compound ) ( Table 2 ) . The potential hepatic oxidative pathways involved in fexinidazole metabolism were assessed by testing the clearance of the fexinidazole and its two primary metabolites by a range of cytochrome P450 ( CYP450 ) enzymes [Dataset S3] . The data show that fexinidazole is extensively metabolised by a range of CYP450 enzymes , including 1A2 , 2B6 , 2C19 , 3A4 , and 3A5 and , to a lesser extent , 2D6 . The 2C8 and 2C9 enzymes were inactive . Interestingly , none of the enzymes tested metabolised either the sulfoxide or the sulfone to any significant degree ( their metabolic pathways remain to be established ) . These data are in agreement with in vivo data showing the long systemic half-lives of the sulfoxide and sulfone metabolites in animal studies ( see below ) . Since fexinidazole is metabolised extensively by multiple CYP450 isoforms , its metabolism is unlikely to be significantly affected by other drugs . The oral absorption potential of fexinidazole was assessed in the well-known Caco-2 cell model for intestinal epithelial permeability [[36] , Dataset S4] . In this assay , fexinidazole showed high absorption potential ( apparent permeability Papp = 57 . 2 10−6 cm/s and no significant efflux ) . Intestinal permeability of fexinidazole is therefore not expected to be a limiting factor for absorption in humans . The PK profile of fexinidazole was assessed in single-dose and multiple-dose studies in mice , rats and dogs . The absolute bioavailability of oral fexinidazole was 41% in mice , 30% in rats , and 10% in dogs . In all species tested , fexinidazole was rapidly and extensively metabolised to the sulfoxide and subsequently sulfone derivatives . Key pharmacokinetic parameters after oral absorption in mice for fexinidazole and its sulfoxide and sulfone metabolites are shown in Table 4 [Dataset S5] . Essentially similar PK profiles were observed in rats and dogs [Datasets S6 , S7] , even if the exact values varied among species ( see also below ) . The ability to cross the blood-brain barrier is crucial for drugs intended to treat stage 2 HAT . The ability of fexinidazole to do so was initially assessed in vitro in a MDR1-MDCK model [37 , Dataset S8] . Fexinidazole showed high predicted brain permeation ( apparent permeability Papp = 60 . 6 10−6 cm/s and no significant efflux ) . In mice , the presence of fexinidazole and both metabolites in the brain was confirmed after oral dosing ( Table 5 , Dataset S5 ) , and is consistent with the data showing efficacy in the murine model of chronic HAT ( Table 3B ) . The PK profile of fexinidazole was further characterised in mice that were administered the same treatment schedule that was curative in the chronic disease model ( Table 3B ) . The plasma profile in mice of fexinidazole and its sulfoxide and sulfone metabolites after 5 days of fexinidazole treatment at the effective dose ( 200 mg/kg/day ) is illustrated in Figure 3 . The data show that a high and prolonged systemic bioavailability of biologically active compounds is achieved a few hours after drug administration , seemingly without drug accumulation and associated potential toxicity [Dataset S9] . This pattern of parent and metabolite plasma profiles without significant drug accumulation is further illustrated in Tables 6 and 7 , which show plasma PK parameters in Sprague-Dawley rats and beagle dogs after 1 and 14 days of daily oral dosing with fexinidazole ( data taken from the 28-day toxicokinetics studies , see below ) . In both species , it is interesting to note that there is no apparent accumulation in the plasma of either parent drug or metabolites , irrespective of dose , at least during the treatment period of 1–14 days . In the dog , and to some extent in the rat , the only difference seen between the data from day 1 versus day 14 is that the Tmax for the sulfone metabolite occurs some hours earlier on day 14 compared to day 1 , although the overall amount of the metabolite in plasma is similar on both days . Whole-body autoradiography in rats using [14C]-radiolabelled fexinidazole ( see figure 2 for labelling site ) showed that the parent drug and/or its metabolites are broadly distributed to all organs and tissues ( the assay did not distinguish between fexinidazole and its metabolites ) , with peak concentrations in most tissues 2 h after oral dosing . After 48 h , most radioactivity was eliminated from the body and no tissue specific accumulation was noted [Dataset S10] . Furthermore , radioactivity was detected at all times in the brain , with a brain-to-blood concentration ratio of 0 . 4–0 . 6 . Excretion balance studies in rats showed that 30% and 59% of fexinidazole-related material was excreted via urine and faeces , respectively , within 96 h [Dataset S11] . Elimination of the radioactivity after oral dosing was rapid , with 84% eliminated within 48 h . About 1 . 4% of the dose was recovered from the carcass with an overall recovery of the total radioactivity of approximately 93% . In regulatory safety pharmacology assessments , in vitro exposure of hERG-transfected HEK 293 cells to fexinidazole sulfone , but not fexinidazole or the sulfoxide , showed a statistically significant decrease of 33% on hERG peak tail current at the highest of the three doses tested ( 30 µM , 9 . 34 µg/mL; no effect at 1 or 5 µM ) [Dataset S12] . However , assessment of cardiovascular parameters in beagle dogs after single oral doses up to 1000 mg/kg showed no meaningful effects on blood pressure , heart rate , and ECG intervals , including the Q-T interval [Dataset S13] . Similarly , no meaningful effects were observed after single oral doses in rats of up to 1000 mg/kg on general behaviour and body temperature ( modified Irwin's test ) or on respiratory parameters [Dataset S14 , S15] . Because fexinidazole treatment for HAT is expected to be a single regimen of 14 days or less , 28-day regulatory toxicokinetic studies were carried out in rats and dogs . Once daily oral fexinidazole doses of 50 , 200 and 800 mg/kg/day were well tolerated in rats at all doses tested [Dataset S16] . Only a minimal-to-slight decrease in food consumption and in the expected body weight increases ( due to normal growth ) was observed at 200 and 800 mg/kg , in male animals only . Minimal-to-moderate changes were observed in the liver of all fexinidazole-treated animals ( increased liver weight and/or hypertrophy of the centrilobular hepatocytes ) . However , there was no increase in liver enzymes including AST and ALT , and all other clinical pathology parameters were also normal . Taken together with the observation that these changes were restricted to the dosing period , these were considered of adaptive origin ( metabolism ) and not indicative for liver toxicity . The No Observed Adverse Event Level ( NOAEL ) in the rat was set at 200 mg/kg/day . In Beagle dogs , daily oral fexinidazole doses of 50 , 200 and 800 mg/kg/day were also well tolerated [Dataset S17] . Slight-to-moderate body weight loss and reduction in food intake were observed at 800 mg/kg/day during treatment . A minimal-to-slight decrease in the number of lymphocytes was seen at the highest dose . The No Observed Adverse Event Level ( NOAEL ) in the dog was also set at 200 mg/kg/day . In both rat and dog studies , plasma levels of fexinidazole and both metabolites were measured and showed that fexinidazole was adequately absorbed , resulting in a significant and prolonged exposure of especially fexinidazole sulfoxide and sulfone ( data up to 14 days of treatment in rats and dogs is shown in Tables 6 and 7 ) . Preliminary studies on the potential effects of fexinidazole on embryo-foetal and early postnatal development were carried out in pregnant rats and no adverse effects on embryos/foetuses , parturition , and neonates were identified in dams . Further standard development and reproductive toxicology ( DART ) studies are currently ongoing to confirm and extend the preliminary results . Fexinidazole and its primary metabolites are nitroimidazoles and , like many other nitroheterocyclic compounds , are potentially mutagenic [48] . To evaluate bacterial mutagenicity , a standard full Ames test was carried out on four strains of Salmonella typhimurium , with and without rat liver microsomes [Dataset S18] . Fexinidazole elicited both frameshift and base substitution mutations . However , this activity was significantly reduced or abolished when nitroreductase-deficient Salmonella strains were used for the assay ( representative example shown in Figure 4 ) . Rat liver microsomes metabolise fexinidazole efficiently to the sulfoxide metabolite under these experimental conditions ( data not shown ) , so mutagenicity of this metabolite is covered by the above data . A separate Ames test of the sulfone metabolite gave similar results to fexinidazole ( data not shown ) . These data suggest that the observed mutagenic activity is due to bacterial activation of fexinidazole and its metabolites by nitroreductases , and is not an inherent property of the compounds . A detailed analysis of fexinidazole's genotoxic potential on mammalian systems was undertaken subsequently . First , genotoxicity in mammalian cells was evaluated in an in vitro micronucleus test using human peripheral lymphocytes [Dataset S19] . Fexinidazole did not induce the formation of micronuclei , and thus no clastogenic damage , either in the presence or absence of rat liver microsomal enzymes ( Table 8A ) . A separate in vitro micronucleus assay of the sulfone metabolite was also negative ( data not shown ) . An in vivo bone-marrow micronucleus test in mice administered high oral doses of fexinidazole ( up to 2 g/kg ) confirmed the lack of clastogenicity ( Table 8B , Dataset S20 ) , while plasma analysis of these mice confirmed the exposure to fexinidazole and its two major metabolites ( data not shown ) . Finally , an ex vivo rat liver unscheduled DNA synthesis study ( Table 8C ) confirmed the lack of mammalian genotoxic activity for fexinidazole and its metabolites [Dataset S21] . Taken together , these data support the conclusion that fexinidazole does not pose a genotoxic risk to patients . No direct studies have been done on the mode of action of fexinidazole . However , fexinidazole might act as a prodrug like other 5-nitroimidazoles that are toxic to the parasites only after bioreductive activation [54] . From studies of trypanosomes resistant to the action of nitroimidazoles , it appears that these parasites have bacterial-like nitroreductases , which can activate nitroimidazole drugs into reactive intermediates that in turn cause cellular damage [55] . Fexinidazole and the sulfoxide and sulfone metabolites were shown to have a low single electron redox potentials being −511 mV , −493 mV , and −488 mV , respectively . In the same study , the single electron redox potential of metronidazole was −516 mV , and of megazole was −422 mV .
This paper provides data showing that fexinidazole , a 2-substituted 5-nitroimidazole identified among a series of existing but long forgotten compounds , is a promising drug candidate for HAT . A full set of preclinical studies have been conducted in accordance with the regulatory requirements for pharmaceuticals for human use , and fexinidazole has now successfully entered phase I clinical trials . Fexinidazole is the first new drug candidate in 30 years that is in clinical development for the advanced and fatal stage of the disease ( stage 2 ) . In addition , being an oral drug with the potential to be effective against both stage 1 and stage 2 HAT caused by T . b . gambiense and T . b . rhodesiense , it could become the much needed breakthrough for HAT control by drastically simplifying case management . Fexinidazole has been shown to be selectively trypanocidal in vitro on T . b . rhodesiense and T . b . gambiense parasites , both on established laboratory strains and recent clinical isolates . Whilst in vitro potency is modest , with IC50 values between 0 . 1 and 0 . 8 µg/mL , a short course ( 4 or 5 days ) of oral fexinidazole treatment is curative in experimental mouse models of acute and chronic ( stage 2 ) HAT at doses of 100–200 mg/kg/day . This would correspond to a daily human equivalent dose ( HED ) for adults of 16 mg/kg calculated based on body surface area [56]; however , more detailed mouse pharmacodynamics studies are required together with human PK data to be able to propose an effective therapeutic dose , including duration . The experimental curative capacity of fexinidazole is significant , as among the currently used drugs in the clinic , only the highly toxic drug melarsoprol is curative in the chronic mouse model which involves an established brain infection that mimics stage 2 HAT . The observation that a single high dose of fexinidazole was also partially curative in the acute model ( data not shown ) underscores the potential for a short course treatment which will be crucial to achieve an easy-to-use treatment for remote and rural areas . While the predictive value of these murine models in terms of the potential for curing stage 2 patients is not fully established ( only melarsoprol cures both ) , the demonstration that a drug candidate can clear systemic trypanosome infections in both the acute and chronic model , as well as clearing the brain infection ( no relapse in the chronic model ) , is widely considered as the critical feature for a stage 2 HAT drug candidate . It has been argued by some that obtaining data from other animal models ( rat , monkey ) before moving into clinical development is desirable . However , the urgency to find new drugs for HAT combined with the lack of clinical candidates in the pipeline warrants a bolder strategy . Moreover , as fexinidazole's in vivo efficacy is likely to depend on the combined exposure profile of the parent drug and its two major metabolites , and knowing that metabolism can vary between species , it is uncertain what can be learned from additional animal disease models . Clearly , the critical studies ahead to determine the curative potential of fexinidazole in humans will be the human safety and PK studies in phase I , and subsequently a proof-of-concept phase II study in patients . Upon oral administration , fexinidazole is well absorbed and rapidly metabolised into the sulfoxide and sulfone derivatives , both of which have similar in vitro trypanocidal activity to the parent compound . The excellent in vivo activity of fexinidazole when administered orally is likely to be due to the cumulative exposure to not one but three active compounds which distribute throughout the body with different but overlapping kinetics , thus ensuring effective exposure in both the systemic circulation and the brain . In mice , rats and dogs , the half-life of fexinidazole after oral treatment ranges from 1 h to 3 h , whilst the half-life of the sulfoxide ranges from 2 h to 7 h and that of the sulfone can be up to 24 h after dosing . As the in vitro intrinsic clearance rate by human hepatocytes was lower than that of all other species tested , it can be expected that the half-lives in humans will be even longer , which further supports fexinidazole's potential for a once per day short-duration treatment schedule . On the other hand , a non-linear dose-related absorption and consequent exposure was observed in both rats and dogs ( not done in mice ) . It will thus be important to carefully analyse the dose-related PK of fexinidazole and both metabolites after oral dosing in humans to better predict the dose-response relationship . While fexinidazole and the sulfoxide are metabolised by multiple liver microsomal enzymes , suggesting a low risk for drug-drug interactions , the metabolic route of the sulfone remains to be established . No accumulation of either fexinidazole or the primary metabolites was found in rats , and almost all drug-related material was eliminated from the body within 48 h of oral dosing , excreted mainly through faeces ( 59% ) and urine ( 30% ) . The distribution of fexinidazole and metabolites to the brain was confirmed in mice and rats , and considering the lipophilicity of the molecules ( logDpH 7 . 4 2 . 83 [fexinidazole] , 0 . 74 [sulfone] , 0 . 52 [sulfoxide] ) , there is no reason to assume that the brain penetration potential , critical for the efficacy in stage 2 HAT , would be different in humans . A full regulatory toxicology package has been conducted , including safety pharmacology ( respiratory , cardiovascular , and general behaviour ) and 4-weeks repeated-dose toxicokinetics studies in the rat and the dog . Overall , fexinidazole was well tolerated , with no specific issues of concern or target organs for toxicity identified . Fexinidazole is positive in the classical in vitro Ames test , but this effect is highly dependent on the presence of bacterial nitroreductases . A carefully designed set of in vitro and in vivo assays to detect possible signals of mammalian genotoxicity remained negative . While a clearly positive Ames test result has long been considered a no-go for drug development ( except for terminal diseases ) as it would indicate a possible risk for ( human ) carcinogenicity , bacterial mutagenicity is not necessarily a relevant indication for mammalian genotoxicity , when bacterial specific metabolism is involved , especially with certain compound classes such as nitroimidazoles [57] . In fact several examples exist of nitroaromatic drug candidates currently in development for diseases requiring a much longer treatment than HAT , for instance epilepsy and tuberculosis , in which either the positive Ames test was not considered decisional to indicate a hazard to patients or no bacterial mutagenicity was detected [58] , [59] , [60] . Instead , a carefully designed series of in vitro and in vivo mammalian genotoxicity assays can be used to rule out the different possible mechanisms of mutagenicity that would indicate a risk for genotoxic-related carcinogenicity . The observation by us and others that it is possible to select non-mammalian mutagenic compounds within the nitroheterocycles family reopens the potential for the further use of this family of compounds with well-known anti-infective properties . It is important to emphasize that the observed positive Ames results in nitroreductase-containing tester strains in no way point to a residual risk for carcinogenicity not captured by the detailed in vitro and in vivo mammalian genotoxicity studies as performed with fexinidazole . In contrast to what is often assumed , the in vitro micronucleus test measuring chromosome damage is no less sensitive as a screening test than the Ames test , even if it involves larger scale genetic damage than bacterial point mutations [61] . Although there are a few documented examples of genotoxic carcinogens that can induce chromosome damage but not bacterial point mutations ( e . g . arsenic ) , there are , to our knowledge , no examples of genotoxic carcinogens that induce bacterial point mutation but not chromosome damage . It has also been argued that gut flora contains bacterial nitroreductases , which could convert nitroaomatics into mutagenic species , much like what is observed in the in vitro Ames test and thus still present a genotoxic risk in vivo . A recent study of AMP397 , a nitroaromatic compound previously in clinical development for epilepsy has attempted to address the issue of potential generation of gut-bacteria derived mutagens [58] . This compound has a similar profile to fexinidazole , with positive Ames test results in standard strains and lack of activity in nitroreductase-deficient bacterial strains and in mammalian cell assays . Suter et al . carried out a mutagenicity study of AMP397 in vivo in the transgenic MutaMouse model using five daily doses at the maximum tolerated dose and sampling at 3 , 7 and 31 days after treatment . No evidence of mutagenicity was seen in the colon or liver . Likewise , a comet assay ( measuring DNA strand breakage ) did not detect any genetic damage in the jejunum or liver of treated rats after dosing the animals at a dose six times higher than that possible in the mouse study . A radioactive DNA binding study also failed to show any DNA binding in rat liver . Thus , if a mutagenic metabolite was formed by intestinal bacteria , it is unable to exert any genotoxic activity in adjacent intestinal tissue . As the genetic toxicology profile of fexinidazole is the same as AMP397 and the mechanism behind the bacterial specific mutation seen is the same , there is no reason to expect a different assessment regarding gut flora activation . The mechanism of action of fexinidazole is not yet elucidated , but likely involves bioreductive activation . Fexinidazole and the sulfoxide and sulfone metabolites were shown to have a low single electron redox potentials ( ranging between −511 and −488 mV ) . The nitroreductive enzymes present in mammalian cells can only reduce compounds with relatively high redox potentials under aerobic conditions . In contrast , bacterial nitroreductases such as those in the Salmonella assay can act at much lower redox potentials than equivalent mammalian systems . This gives a plausible explanation for the positive results in the standard Ames test and the reduced or abolished activity in nitroreductase-deficient strains . In line with these observations , it is of interest to note that the single electron redox potential of metronidazole was −516 mV , while megazole's is significantly higher at −422 mV . The rediscovery of fexinidazole as a drug candidate also shows the success of the compound mining approach , during which a careful investigation of existing compounds within a family of known pharmacologically active compounds using state-of-the-art science , has yielded a new drug candidate for clinical development in a relatively short time . Starting the experimental work within this limited set of existing compounds in 2005 ( around 700 compounds tested , mainly parasitology and genotoxicity assays ) , a preclinical candidate could be selected early 2007 , and clinical trials initiated in the second half of 2009 . Compared to drug discovery “from scratch” , this represents a significant shortcut . It also shows that it is worthwhile to dig into past research efforts to find those potential drug candidates which are lingering in drawers or on shelves . In particular in the context of non-profit drug development such as for neglected diseases where the existence of patents is not considered a prerequisite for development , this compound mining strategy may be worthwhile to pursue more vigorously . Based on the data presented in this paper , fexinidazole has entered clinical development , and a phase I trial is currently ongoing to establish its PK and tolerability in healthy volunteers from African origin ( in a combined single ascending dose and multiple ascending dose study ) [62] . If well tolerated , fexinidazole is expected to progress to phase II trials in patients with stage 2 HAT by the end of 2010 . If fexinidazole successfully completes clinical development , it will represent a real breakthrough for the control of HAT in rural Africa for several reasons . Fexinidazole would be the first oral drug for stage 2 HAT , well tolerated and effective upon a short-course treatment . Compared to the current options of either 10 days of daily intravenous melarsoprol with its dreadful toxicity and waning efficacy , the very complicated eflornithine monotherapy ( 56 infusions over 14 days ) , or even the recent improvement of NECT ( a combination therapy of 10 days oral nifurtimox and 7 days of 12 hourly eflornithine infusions ) , this would be ground-breaking . Moreover , based on its simple chemistry and short synthesis , fexinidazole is expected to be relatively cheap ( certainly not more than US$ 50 per treatment , likely significantly less ) . Furthermore , stability data to date show that fexinidazole is very stable , which is a good starting point for the development of a stable solid dosage formulation for use in tropical climates . Finally and most significantly , it could be the first treatment to be used for both stage 1 and stage 2 HAT , thereby overturning the long-standing but complicated diagnosis and treatment paradigm which includes systematic lumbar punctures of every diagnosed patient to determine which stage of the disease they are in before deciding which treatment to prescribe ( to avoid exposing a stage 1 patient to the risks and burden of the stage 2 treatments ) . A safe , effective , cheap and easy to use treatment for both stage 1 and 2 HAT , ideally in combination with an easy field diagnostic , would make HAT control a realistic option for the future . In contrast to the current diagnosis and treatments options which are largely dependent on vertical HAT control approaches , this safe , effective , easy to use stage 1+2 treatment could be integrated into more horizontal approaches which are more likely to reach the extremely poor and remote populations most affected by HAT . Clearly , there are many hurdles to overcome before fexinidazole can reach this target , but it surely is the most promising candidate in many years . A concerted effort to progress fexinidazole efficiently through clinical development and registration is warranted . | This article describes the preclinical profile of fexinidazole , a new drug candidate with the potential to become a novel , oral , safe and effective short-course treatment for curing both stage 1 and 2 human African trypanosomiasis and replace the old and highly problematic treatment modalities available today . Fexinidazole is orally available and rapidly metabolized in two metabolites having equivalent biological activity to the parent and contributing significantly to the in vivo efficacy in animal models of both stage 1 and 2 HAT . Animal toxicology studies indicate that fexinidazole has an excellent safety profile , with no particular issues identified . Fexinidazole is a 5-nitroimidazole and , whilst it is Ames-positive , it is devoid of any genetic toxicity in mammalian cells and therefore does not pose a genotoxic risk for use in man . Fexinidazole , which was rediscovered through a process of compound mining , is the first new drug candidate for stage 2 HAT having entered clinical trials in thirty years , and has the potential to revolutionize therapy of this fatal disease at a cost that is acceptable in the endemic regions . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"infectious",
"diseases/neglected",
"tropical",
"diseases",
"pharmacology/drug",
"development"
] | 2010 | Fexinidazole – A New Oral Nitroimidazole Drug Candidate Entering Clinical Development for the Treatment of Sleeping Sickness |
Key innovations are disruptive evolutionary events that enable a species to escape constraints and rapidly diversify . After 15 years of the Lenski long-term evolution experiment with Escherichia coli , cells in one of the twelve populations evolved the ability to utilize citrate , an abundant but previously untapped carbon source in the environment . Descendants of these cells became dominant in the population and subsequently diversified as a consequence of invading this vacant niche . Mutations responsible for the appearance of rudimentary citrate utilization and for refining this ability have been characterized . However , the complete nature of the genetic and/or ecological events that set the stage for this key innovation is unknown . In particular , it is unclear why it took so long for citrate utilization to evolve and why it still has evolved in only one of the twelve E . coli populations after 30 years of the Lenski experiment . In this study , we recapitulated the initial mutation needed to evolve citrate utilization in strains isolated from throughout the first 31 , 500 generations of the history of this population . We found that there was already a slight fitness benefit for this mutation in the original ancestor of the evolution experiment and in other early isolates . However , evolution of citrate utilization was blocked at this point due to competition with other mutations that improved fitness in the original niche . Subsequently , an anti-potentiated genetic background evolved in which it was deleterious to evolve rudimentary citrate utilization . Only later , after further mutations accumulated that restored the benefit of this first-step mutation and the overall rate of adaptation in the population slowed , was citrate utilization likely to evolve . Thus , intense competition and the types of mutations that it favors can lead to short-sighted evolutionary trajectories that hide a stepping stone needed to access a key innovation from many future generations .
Escherichia coli can more effectively uptake iron when a small amount of citrate , about 10 μM , is added to chemically defined media [1] . In 1950 , when DM ( Davis-Mingioli ) medium was initially designed , the recipe used 1700 μM citrate . DM medium was formulated to isolate auxotrophic mutants by the penicillin method . It was shown that the addition of citrate improved the lethality of penicillin , thereby reducing the number of false-positives when selecting for auxotrophs . The penicillin method was widely used , and DM was adopted as a chemically defined medium for other types of experiments as a consequence [2] . The elevated concentration of citrate was typically unnecessary in these new circumstances , but it remained unaltered as new labs and generations of scientists inherited the same DM recipe . The Lenski long-term evolution experiment ( LTEE ) consists of twelve E . coli B populations that have been propagated daily in glucose-limited DM medium for over 60 , 000 generations [3 , 4] . A relatively low concentration of glucose ( 139 μM ) was used in the LTEE to restrict the cell density and thereby reduce the chances that stable ecology reinforced by cross-feeding interactions would evolve , which has largely been the case except for in one population [5 , 6] . The low-glucose formulation of DM used in the LTEE means that the standard amount of citrate present ( 1700 μM ) represents a substantial nutrient pool that could be exploited , but the ancestral strain of E . coli is unable to utilize citrate under the conditions of the LTEE . Citrate is an untapped niche . After 31 , 500 generations , a mutant in one of the LTEE populations , designated Ara−3 , evolved the ability to utilize citrate as a carbon source . Descendants of this mutant that were able to fully exploit this additional carbon source evolved by 33 , 000 generations and dominated thereafter [7] . Previous work has demonstrated that the evolution of citrate utilization in the LTEE proceeded through three stages typical of any key innovation: potentiation , actualization , and refinement [7–10] . The principal mutations involved in the latter two steps have been characterized . Actualization refers to the first manifestation of a rudimentary Cit+ phenotype . The actualizing mutation is a tandem duplication of the rnk-citG region of the E . coli chromosome that includes the citrate:succinate antiporter gene , citT . This duplication results in an arrangement in which one of the two copies of citT is now downstream of the aerobically-active rnk promoter ( Prnk ) . Thus , the actualization step results in CitT production under the LTEE conditions [8] . However , early Cit+ cells with the citT duplication are able to uptake and metabolize only a small fraction of the citrate present during one 24-hour growth cycle of the LTEE [7 , 11] . Subsequently , refinement mutations improved the rudimentary Cit+ trait in their descendants such that they became capable of utilizing all of the citrate in DM during each growth cycle ( Cit++ phenotype ) . One critical mutation for refinement activated expression of dctA , a C4-dicarboxylate:H+ symporter gene . DctA allows active transport of C4-dicarboxylates , including succinate , into the cell . Because CitT is an antiporter that couples export of these compounds to citrate import , expression of DctA creates a sustainable cycle for importing citrate that is powered by the proton gradient [9] . The dctA mutation refines the rudimentary Cit+ trait into the Cit++ phenotype that was responsible for the population expansion observed at ~33 , 000 generations in the LTEE [7] . While the actualization and refinement stages of Cit+ evolution in the LTEE are understood , the mechanistic basis of potentiation has remained elusive . The critical diagnostic characteristic of a potentiated strain is that is has an increased chance of giving rise to a Cit+ descendant after further evolution [8] . Blount et al . identified potentiated strains by performing ‘replay’ experiments [7] . In these experiments , pre-Cit+ clones isolated from the LTEE population at various time points were tested to determine whether they were capable of evolving citrate utilization . Cit+ cells rarely arose in these replay experiments . When they did , the Cit+ trait re-evolved more often in clones selected from later time points that were closer to when the citT duplication first arose in the LTEE population . The phylogenetic distribution of the LTEE strains giving rise to Cit+ variants in the replay experiments suggests the existence of at least two critical junctures at which the potential for evolving Cit+ increased [8] . By 20 , 000 generations , the LTEE population had diversified into three long-lived clades that co-existed at least until full citrate utilization ( Cit++ ) evolved at ~33 , 000 generations . E . coli isolates from all of these groups evolved Cit+ in the replay experiments , whereas no strains from earlier than 20 , 000 generations did , suggesting that all three clades share some determinant of potentiation . A significantly higher proportion of clones from the clade that gave rise to citrate utilization in the LTEE were able to evolve Cit+ in the replays , suggesting that they share a second determinant for increased potentiation not present in the other clades . Due to the extreme rarity of Cit+ arising in these replay experiments even after months of evolution [7] , it is not realistic to use this approach to further narrow down the genetic basis of potentiation . In this study , we tested the viability of the critical actualizing mutation for Cit+ evolution in a series of pre-Cit+ isolates from the LTEE by measuring the effect of activating citT expression on competitive fitness . We found that activating citT expression slightly increased the fitness of the ancestral strain and some later pre-Cit+ clones . Unexpectedly , activating citT expression was highly deleterious in certain strains from intermediate time points , and we did not find any strains that benefitted significantly more from this mutation than the ancestral strain did . We conclude that potentiation for the evolution of citrate utilization in the LTEE is due to the interplay of genetic factors in specific strains and the population at large . First , adaptation had to occur via a genetic trajectory that maintained the potential for evolving Cit+ by a beneficial mutational step in order for the innovation to remain accessible . Second , the rate of adaptation in the overall population needed to slow to a pace at which early variants with the weakly beneficial Cit+ trait could avoid being driven extinct by competitors before refining mutations arose .
By definition , the first E . coli cell that evolved the citT-activating mutation that was ultimately successful in the LTEE was fully potentiated when this mutation arose . The earliest Cit+ descendant of this cell that has been identified is strain ZDB564 from 31 , 500 generations . At this time Cit+ cells were still extremely rare in the population [10] , which means that it is likely that the suite of mutations in ZDB564 is identical to those in the first Cit+ cell , or nearly so . Previously , strain ZDB706 , a Cit− revertant of ZDB564 , was isolated by passaging ZDB564 on DM medium lacking citrate to allow for the spontaneous collapse of the rnk-citG duplication to the ancestral single-copy state that lacks a copy of the rnk promoter upstream of citT ( Fig 1A ) [10] . We co-cultured ZDB564 and ZDB706 in DM medium to estimate the effect that the citT duplication had on competitive fitness when it originally arose . These experiments involved reverting an arabinose-utilization allele in one of the two strains to be competed from the inactivated state present in all strains from this LTEE population ( Ara– ) to the active state ( Ara+ ) so that cells of each type can be distinguished by the colors of the colonies that they form on indicator plates ( S1 Fig and Methods ) [4] . These Ara+ strain variants were assayed to establish that the genetic marker was neutral with respect to fitness and that no secondary mutations affecting fitness had accumulated during strain construction prior to further competition experiments ( S2 Fig ) . When competing ZDB564 and ZDB706 , we found a slight fitness advantage of 2 . 2% for the presence of the citT-activating duplication in ZDB564 ( Fig 1B ) . This result that was consistent between the competitions utilizing Ara+ ZDB706 or Ara+ ZDB564 marked variants ( two-tailed t-test , P = 0 . 33 , n = 12 and 18 , respectively ) . We next wanted to add the citT-activating mutation to pre-Cit+ strains in order to test our hypothesis that there was a transition in the lineage leading to Cit+ such that this mutation became more beneficial once a potentiated genetic background evolved . The effect of adding a plasmid containing the evolved Prnk-citT unit has been tested in previous studies , [8 , 9] but this approach is problematic because these plasmids are multicopy , whereas only a single activated copy of the citT gene was present in the initial Cit+ strains . However , engineering the authentic rnk-citG duplication into the chromosome of a strain is difficult because this configuration is genetically unstable . It readily collapses via homologous recombination if there is not selection to maintain citrate utilization , as was utilized in reverting ZDB564 to the Cit− variant ZDB706 . To address these shortcomings , we developed a Prnk-citT knock-in assay , in which a mimic of the evolved configuration is integrated into the chromosome of a pre-Cit+ LTEE clone ( Fig 1C ) . Briefly , we created an activated citT module linked to an antibiotic selection marker in which the rnk promoter is upstream of the truncated rnk-citG fusion ORF formed by the duplication followed by the complete citT reading frame . To control for any fitness cost imposed by the selection marker , we also made a null module containing only the antibiotic resistance gene . Both of these cassettes are targeted to integrate into the E . coli chromosome such that they replace the lac operon , which is unrelated to citrate or glucose metabolism . We validated this approach by adding the Prnk-citT module to the fully potentiated Cit− revertant , ZDB706 , and adding the null module to its neutral Ara+ variant . Addition of the Prnk-citT cassette to the fully potentiated Cit− strain ZDB706 resulted in increased citT mRNA levels equivalent to those seen in ZDB564 , the original Cit+ isolate with the actual rnk-citG duplication that evolved in the LTEE ( two-tailed t-test , P = 0 . 65 , n = 3 ) ( Fig 1D ) . The resulting Cit+ variant of ZDB706 had a fitness advantage of 2 . 4% over the corresponding Cit− variant with the null knock-in cassette ( Fig 1B ) , which was not statistically different from the fitness advantage found for the authentic citT-activating mutation in the pooled ZDB564 versus ZDB706 competitions ( two-tailed t-test , P = 0 . 71 , n = 6 and 30 , respectively ) . Therefore , applying the Prnk-citT knock-in assay to additional strains allows us to ask: if the citT-activating mutation had evolved in a genetic background that existed earlier in the LTEE , would it have been as beneficial ? As a first step in further elucidating the fitness consequences of evolving rudimentary Cit+ on other strains from the LTEE , we performed the Prnk-citT knock-in assay on the ancestral LTEE strain , REL606 . We found a slight fitness benefit of 1 . 0% for the Cit+ mutation ( Fig 1B ) . This effect size is near the limit for the smallest differences that can be distinguished in these types of competitive fitness assays , resulting in relatively weak support for the hypothesis that there was any fitness advantage at all for the REL606 variant with the Prnk-citT module relative to the one with the null module ( one-tailed t-test , P = 0 . 033 , n = 12 ) . There was evidence , though also not very strong , that the benefit of the Prnk-citT module in the fully potentiated strain ZDB706 was greater than it was in REL606 ( one-tailed t-test , P = 0 . 018 , n = 12 and 6 , respectively ) . Expression of citT was not quite as high in the REL606 strain with the Prnk-citT module as it was in ZDB706 with the same module ( two-tailed t-test , P = 0 . 00016 , n = 3 ) ( Fig 1D ) , suggesting that mutations during the LTEE on the lineage leading to Cit+ may have altered the strength of the rnk promoter . Overall , the REL606 measurements indicated , surprisingly , that there was likely a modest benefit for a mutation activating expression of citT at the very beginning of the LTEE , and that this benefit may have only slightly improved after further mutations that occurred during the potentiation stage in the evolution of this metabolic innovation . Why did the appearance of citrate utilization take so long and why has it not evolved in other LTEE populations ? One hypothesis for its rarity is that the evolution of a particular ecology in the population was important for enabling the evolution of Cit+ . This type of situation is known to occur , for example , when nutrient cross-feeding between genetically diverged subpopulations yields negative frequency dependence , such that the competitive advantage for a newly evolved strain or a certain subpopulation is greater when it is rare within the population than when it is common [12] . The pre-Cit+ clade was rare during the time period when the rnk-citG duplication evolved . It constituted <1–5% of the population from 30 , 000 to 32 , 500 generations [10] . To test whether this kind of ‘ecological potentiation’ was important for the evolution of Cit+ in the LTEE , we repeated the Prnk-citT knock-in assay competition for strain ZDB706 in the context of the full diversity that existed in the population at 31 , 000 generations ( Fig 1B ) . The Cit+ and Cit− variants were mixed together equally and added such that they comprised ~1% of the cells in a mixture with the evolved population sample . In this context , the Cit+ strain had a 0 . 9% fitness advantage over the Cit− strain , which was less than and only marginally different from the result when the two strains were competed versus one another normally ( two-tailed t-test , P = 0 . 053 ) . Thus , we find no support for the ecological potentiation hypothesis . If anything , the more diverse mixed population context may slightly reduce the benefit of Cit+ evolution . We next performed the Prnk-citT knock-in assay on 23 additional clones isolated from the LTEE population ( Fig 2A ) . Our goal was to determine whether activating citT expression was similarly beneficial in other evolved genetic backgrounds . We measured citT mRNA levels in five of the constructed strains with the Prnk-citT cassette and found them to be similar in all of these strains ( S5 Fig ) , indicating that the strength of the rnk promoter was largely unchanged by the specific suites of evolved mutations present in each of these strains . For four of the evolved strains we found strong evidence that the citT cassette significantly increased fitness versus the control with the null cassette , as it had in the fully potentiated strain ZDB706 ( one-tailed bootstrap test incorporating Ara+/Ara− marker and Cit+/Cit− competitions described in Methods , P < 0 . 05 ) . In nine strains , citT activation had no significant effect on fitness ( two-tailed bootstrap test , P < 0 . 05 ) , though our measurements did not achieve sufficient precision to rule out that there was a fitness benefit of 1% or greater in seven of these cases ( one-tailed bootstrap test , P < 0 . 05 ) . Unexpectedly , the Cit− variant outcompeted the Cit+ variant for the 11 remaining strains of the 23 we tested ( one-tailed bootstrap test , P < 0 . 05 ) . The actualizing step needed for subsequently evolving full citrate utilization ( Cit++ ) would have been effectively blocked if it occurred in these strain backgrounds; they are ‘anti-potentiated’ . For five of these strains , activating citT expression was extremely detrimental , decreasing competitive fitness by >20% ( one-tailed bootstrap test , P < 0 . 05 ) . For ZDB483 and ZDB14 , two of the severely anti-potentiated strains , we investigated the nature of this defect by comparing growth curves of the Cit+ and Cit− variants . There was very little difference in the growth curve for the LTEE ancestor REL606 whether the activated citT cassette or null control cassette was added to its genome , which is in keeping with its almost imperceptible effect on the competitive fitness of this strain . In contrast , we found that activating citT expression drastically increased the lag phase of growth in the severely anti-potentiated strains ( Fig 2B ) . This additional lag time can explain the sizable competitive disadvantage versus the Cit− strain , even though the Cit+ variants are able to reach a higher final cell density if cultured alone . Identifying specific mutations that contributed to potentiation and anti-potentiation requires interpreting the fitness data from the Prnk-citT knock-in assays in a phylogenetic context . To improve the resolution of a previously published whole-genome phylogenetic tree of 29 clonal isolates from this LTEE population [8] , we sequenced the genomes of 20 new clones ( S1 Table ) and also incorporated 12 other clones sequenced in another recent study of the rate of genome evolution through 50 , 000 generations in all LTEE populations [13] . The 20 newly sequenced isolates were selected to improve our ability to temporally order mutations that occurred near when citrate utilization evolved: they were minimally diverged from the line of descent to the Cit+ progenitor and were mostly sampled at later time points . The updated phylogenetic tree ( Fig 3 ) includes all 25 clones we tested with the Prnk-citT knock-in assay . We used these strains to identify branches in the tree within which the adaptive potential of activating citT expression changed due to one or more mutations . Specifically , we clustered phylogenetically-adjacent strains into groups within which all pairwise comparisons of the fitness effect of the Prnk-citT module were not significantly different ( Bonferroni-corrected two-tailed bootstrap tests , P > 0 . 05 ) . Overall , this analysis suggests that there were at least three major step-like changes in the potential for evolving the rudimentary Cit+ trait along the pre-Cit− lineage that eventually evolved citrate utilization ( Fig 4 ) . Proceeding backward in the tree from the earliest known Cit+ isolate ( ZDB564 ) , two earlier clones ( ZDB19 and ZDB13 ) from as early as 29 , 000 generations are as fully potentiated as the key Cit− revertant ( ZDB706 ) . The overall fitness effect of evolving Cit+ in this group was +2 . 4% [+1 . 4% , +3 . 4%] ( 95% confidence interval ) . The next-earliest group comprises three clones isolated at time points from 25 , 000 to 27 , 000 generations ( ZDB478 , ZDB486 , and ZDB309 ) . Activation of citT had little to no impact on this set of strains , with an estimated group-wise effect on fitness of +0 . 4% [–1 . 3% , 2 . 0%] . One intermediate strain , ZDB310 from 27 , 000 generations , was not significantly different from either of these two groups immediately before and afterward , although the two groups were significantly different from one another . It was deleterious to evolve Cit+ in an earlier , intermediate set of isolates composed of ZDB425 , ZDB458 , and ZDB464 with an estimated fitness effect of –5 . 4% [–7 . 2% , –3 . 6%] . These clones appear to be genetically typical of the pre-Cit+ lineage . ZDB425 at 10 , 000 generations and ZDB458 at 20 , 000 generations have only one and two ‘private’ mutations not shared with the main pre-Cit+ lineage , respectively , though we cannot rule out that other changes in the impact of citT activation may have occurred on the main line of descent within this interval . Before these anti-potentiated clones , there is an initial cluster that groups ZDB409 and ZDB429 with the REL606 ancestor . In these three isolates , evolution of Cit+ would have been slightly beneficial with a fitness impact of +1 . 7% [+0 . 0% , +3 . 3%] . Other strains are not classified into these major groups . It is less likely that they are representative of how potentiation evolved in the lineage leading to Cit+ . For example , the four most highly anti-potentiated clones ( ZDB467 , ZDB483 , ZDB14 , ZDB18 ) appear to have evolved this property independently and due to ‘private’ mutations not shared with the main pre-Cit+ lineage ( Fig 3 ) , at least this is the most parsimonious explanation . Similarly , the fitness effects measured in the Prnk-citT knock-in assay for two three-member subclades ( ZDB334 , ZDB339 , ZDB317; and ZDB23 , ZDB27 , ZDB25 ) indicate that each likely shared one or more mutations that altered Cit+ potentiation only within that subclade , though the effects are much smaller in these cases . Finally , we excluded ZDB446 from this analysis because it was so deeply branched: removed by >5 , 000 generations from the pre-Cit+ lineage . It would have been clustered with the earliest group containing REL606 according to our criteria . During the time period when the pre-Cit+ lineage was anti-potentiated , from approximately 10 , 000 to 20 , 000 generations , invasion of a new Cit+ subpopulation would have been nearly impossible . Lineages that lost fitness by evolving the rudimentary version of this new trait would be rapidly purged by selection before refining mutations ( e . g . , activating dctA ) could accumulate to give the decisive benefit of full citrate utilization ( the Cit++ phenotype ) . What about the earlier and later time periods when the evolution of Cit+ was neutral or slightly beneficial ? During these epochs , a newly evolved Cit+ lineage would still have had to outcompete not only its own ancestor , but also other lineages that were evolving at the same time , many of which would have accumulated alternative beneficial mutations related to improving fitness on glucose . It is possible that a citT-activating mutation could have appeared in the same genome as one or more other highly beneficial mutations and hitchhiked along with them to a high frequency in the LTEE population by chance , even when it was neutral or had a very small fitness benefit compared to these other ‘driver’ mutations . However , genomic signatures of evolution and models of clonal interference both suggest that it is rare for mutations in the LTEE , particularly very early in the experiment , to succeed by getting lucky in this way [13 , 14] . It would have been far more probable for a new citT mutation to survive if it was one of the most beneficial mutations appearing in the population when it evolved and thus itself a driver mutation . In order to understand when the fitness effects we measured for evolving Cit+ by citT activation would have made this metabolic innovation a likely evolutionary pathway in the context of competition within the LTEE population , we compared the group-wise fitness effects determined from the Prnk-citT knock-in assays to two models of the fitness effects of beneficial mutations that were successful at different generations in this LTEE population ( Fig 4 ) . The Wiser et al . approach fits the fitness trajectory of this LTEE population to a model that incorporates a uniform type of diminishing returns epistasis between beneficial mutations and assumes consecutive sweeps [15] . The Tenaillon et al . model fits the number of beneficial mutations accumulating over time from genome sequencing data [13] . We combined this information with the Wiser et al . fitness trajectory to infer the representative fitness change for each subsequent beneficial mutation . The larger fitness effects in the Wiser et al . model reflect that it estimates the advantages of sweeping cohorts that may include more than one beneficial mutation . Overall , both models give very similar results that reflect the well-known deceleration in fitness gains during the Lenski long-term experiment [3 , 4 , 14 , 16] . Comparing these models to the results of the Prnk-citT knock-in assays demonstrates that even if Cit+ evolution was marginally beneficial in the REL606 ancestor and other early isolates , it was initially less beneficial than would have been needed to reliably succeed on its own merits at this point . Even by 5 , 000 generations , citT activation appears to have been average , at best , in terms of its fitness effect among all possible beneficial mutations . It would have been unlikely for the Cit+ trait to appear and persist at this point because there were so many alternative mutations , such as those that required only single-base substitutions or IS insertions that knocked out gene function , which would have occurred at a higher rate than the specific duplications or IS element insertions needed to activate citT expression [7] . After anti-potentiation appeared and receded in this lineage , competition would have continued to suppress Cit+ evolution when the citT mutation was again neutral . In striking contrast , evolving Cit+ was superior to a typical successful beneficial mutation in the final group of strains that first evolved by 29 , 000 generations . This timing is consistent with when Cit+ cells finally did evolve and reach a detectable frequency in this LTEE population by beating their competitors .
Our work reframes and further elucidates why the emergence of citrate utilization is so rare in the Lenski long-term evolution experiment ( LTEE ) . Rudimentary citrate utilization ( the Cit+ phenotype ) can apparently evolve at any time when a mutation switches on expression of the CitT transporter under the aerobic conditions of the experiment . However , the success of a new Cit+ variant is far from guaranteed . It is contingent on whether its descendants can survive long enough to incorporate a second mutation , such as one activating expression of the DctA transporter , that enables full citrate utilization ( the Cit++ phenotype ) . The chance that Cit++ will be realized by this evolutionary pathway is dependent on two major factors . First , the initial mutational step conferring the weak Cit+ phenotype must be beneficial to fitness . Whether it is advantageous or not depends on the context of other mutations present in an evolved genome in which citT activation occurs . Second , the benefit of the mutation conferring weak Cit+ must be great enough that it can survive in competition with other adaptive mutations . Whether it is sufficiently beneficial depends on the population context in which it arises . We found that both genetic and population factors limited Cit++ evolution at different times in the LTEE ( Fig 4 ) . Unexpectedly , evolution of Cit+ by activating citT expression appears to have already been slightly beneficial to fitness in the ancestral strain used to found this E . coli population on the first day of the LTEE and to have remained so in other early evolved isolates . Even though Cit+ strains that evolved in the LTEE population at this point would have been capable of displacing their own Cit− ancestors , this first step on the pathway to the full Cit++ innovation was unlikely to be successful due to competition with mutations on adaptive pathways that improve fitness in the original glucose niche . New cells with highly beneficial mutations related to this primary component of the LTEE environment were essentially guaranteed to arise in the population and outcompete any cells with mutations activating citT expression . By 10 , 000 generations , the lineage in which Cit+ eventually evolved became ‘anti-potentiated’ after it accumulated additional mutations . Now , the pathway to innovation was blocked because it was deleterious to evolve rudimentary Cit+ in this genetic background . There was a fitness valley separating the evolved Cit- strains from the full Cit++ phenotype . Finally , further mutations appeared in the focal LTEE lineage by 29 , 000 generations that altered the fitness impact of activating citT expression such that it was again beneficial to evolve the Cit+ phenotype , and perhaps even more so than it had been in the ancestor . At this point , the rate of adaptation of the population had slowed enough that evolving rudimentary Cit+ was now among the most beneficial mutational steps remaining . This key stepping stone on the mutational pathway to robust citrate utilization was no longer suppressed by genetic or population factors , and the Cit++ innovation evolved . Cit++ mutants of E . coli capable of growth on citrate as a sole carbon source under aerobic conditions have been isolated in other studies [7 , 8 , 17 , 18] . In all of these cases , multiple mutations have been required to achieve the Cit++ phenotype . When they have been identified , the mutations that yield Cit++ activate expression of the CitT and DctA transporters , as is observed in the LTEE . These studies have isolated Cit++ mutants in much shorter periods of time ( <1–8 weeks ) than it took to evolve in the LTEE ( ~15 years ) because they involve starving E . coli cells for days to weeks under conditions in which citrate was present as a potential carbon source . In the context of our results and as previously noted by others [19] , this difference in environmental conditions relative to the glucose-limited transfer regime of the LTEE , in which cells are in stationary phase for only ~16–18 hours each day , dramatically increases the fitness benefit of evolving the rudimentary Cit+ phenotype . Therefore , these stark conditions are expected to completely mask and overwhelm the dependency on potentiating genetic and population factors found in the LTEE . Activating citT expression would be universally beneficial in any genetic background in these types of experiments . Any increase in lag phase or other trade-off with respect to growth rate that might accompany this intermediate step in the pathway to Cit++ is irrelevant when cells without the mutation simply cannot replicate at all . The citrate-only starvation conditions also eliminate any interference from alternative mutations with benefits related to glucose utilization that suppress Cit++ evolution in the LTEE . Why is evolution of Cit+ beneficial in some evolved genetic backgrounds and deleterious in others under the conditions of the LTEE ? Activation of CitT expression under these aerobic conditions via the rnk-citG duplication leads to coupled import of citrate ( a C6-tricarboxyate ) and export of C4-dicarboxylates ( e . g . , succinate ) [20] . In wild-type E . coli strains , CitT is normally expressed only under anaerobic conditions , and the imported citrate can only be assimilated when a fermentable co-substrate , such as glucose , is also present [21] . Under these conditions , citrate is cleaved to acetate and oxaloacetate by citrate lyase . The structural proteins and accessory factors necessary for producing this enzyme complex are encoded in the same operon as citT . When glucose is co-utilized with citrate , the resulting oxaloacetate is reduced to succinate by reverse tricarboxylic acid ( TCA ) cycle reactions . This process consumes reduced cofactors produced by breakdown of the sugar to balance redox metabolism without the need for O2 . The succinate or other C4-dicarboxylates produced can be exchanged for more citrate import via CitT to continue this mixed fermentation mode of growth , or these TCA cycle intermediates can be siphoned off into biosynthetic pathways as necessary for cellular replication . Under the aerobic conditions of the LTEE , citrate lyase is not expressed and succinate to balance citrate import by CitT must be produced in a different manner , from citrate or glucose using reactions of central metabolism . The availability of O2 makes it possible to maintain redox balance while synthesizing succinate via the TCA cycle , the glyoxylate bypass , or anaplerotic reactions ( e . g . , phosphoenolpyruvate carboxylase ) . E . coli growing under aerobic conditions ferments glucose to acetate , and mutations in genes related to the ability to re-uptake and utilize acetate are widespread in the LTEE [13 , 22 , 23] . These mutations affect acetate transporters and also pathways for assimilating acetate as acetyl-CoA through citrate synthase , the TCA cycle , and the glyoxylate bypass . Therefore , how these pathways are altered by adaptation to better utilize glucose and acetate is likely an important determinant of the genetic background that affects the ability to evolve citrate utilization . If introduction of the CitT transport reaction misbalances the redox state of the cell or the distribution of carbon compound intermediates between anabolism and catabolism , then it would be deleterious to fitness . Therefore , mutations altering central metabolism are candidates for explaining the changes in the fitness effect of citT activation along the LTEE lineage that ultimately evolved citrate utilization ( Fig 4 ) . Starting with the ancestor and examining when changes in the potential for evolving Cit+ were observed in the LTEE , a mutation in nadR , a repressor of NAD coenzyme biosynthesis [24] , occurs along the branch in the phylogenetic tree when anti-potentiation first evolved , before 10 , 000 generations . Mutations in nadR have appeared and swept to fixation in all twelve LTEE populations . These mutations include frameshift mutations and IS element insertions [13] , indicating that they are loss-of-function mutations , and deleting this gene from the genome of the LTEE ancestor has been shown to be beneficial [14] . Reducing or eliminating NadR activity is predicted to increase the NAD/NADH pool in the cell and could enable increased rates of glucose fermentation . Since NADH is a potent allosteric regulator of enzymes in central metabolism , including citrate synthase ( gltA ) for entry into the TCA cycle , this mutation may also reconfigure other cellular fluxes in ways that make CitT transport deleterious to fitness . Between 10 , 000 and 25 , 000 generations mutations occurred in this LTEE population in three key genes that affected the activities of enzymes in central metabolism: iclR , arcB , and gltA1 . These mutations have all been shown to improve growth on acetate [10] . Two of these mutations are in negative regulators; they are expected to derepress enzymes of the glyoxylate bypass ( iclR ) [25] and TCA cycle ( arcB ) [26] , leading to increased metabolic flux through these pathways . Mutations in both of these genes are found in nearly all LTEE populations [13] . The citrate synthase mutation ( gltA1 ) reduces allosteric inhibition of this enzyme by NADH [10] , which increases flux of acetyl-CoA into the TCA cycle . Evolved strains with mutations in gltA have only persisted in one other LTEE population that maintained the low ancestral mutation rate through 50 , 000 generations [13] . Both the arcB and gltA1 mutations occurred on a branch in the phylogenetic tree for the citrate LTEE population when the effect of citT activation reverted to being neutral with respect to competitive fitness , so they are candidates for reversing anti-potentiation . The iclR mutation does not seem to have had an effect on genetic potentiation on its own , but it may have interacted with the arcB and/or gltA1 mutations in a way that contributes to this anti-potentiation effect . Only one mutation in a gene known to be involved in central metabolism occurred around 27 , 000 to 29 , 000 generations , at the point in the phylogenetic tree when adding the citT mutation seems to have again become beneficial to fitness . This mutation is upstream of the ilv operon for branched chain amino acid biosynthesis in the yifB/ilvL intergenic region . This pathway consumes pyruvate and acetyl-CoA , and its products can be used to synthesize the pantothenate moiety of coenzyme A ( CoA ) [27] . If this mutation affects gene expression of the ilv operon , then it could impact the balance of citric acid cycle intermediates flowing into or out of the TCA cycle to sustain cellular growth directly or indirectly via changing CoA/acetyl-CoA availability . While the functions of the genes that we have highlighted in central metabolism suggest that they may be especially important for altering the potential for Cit+ evolution , other mutations also accumulated on the branches in the phylogenetic tree where the effects of citT activation on E . coli fitness changed ( Fig 3 ) . In future work , the Prnk-citT knock-in assay can be used to further dissect this adaptive pathway by testing strains in which various evolved alleles have been removed or added . As an example of this type of approach , we have previously shown that removing the gltA1 mutation from the earliest Cit+ isolate ( ZDB564 ) makes the citT-activating duplication highly deleterious because it introduces a growth lag like that observed in the strongly anti-potentiated LTEE isolates in this study [10] . Similar studies could be conducted on strains that represent as closely as possible the genotypes present at critical junctures in the phylogenetic tree to determine which mutations altered the chances of achieving this innovation . Another remaining question is whether the Cit+ innovation will ever evolve in the other eleven LTEE populations . It has not as of more than 60 , 000 generations [23] , nearly twice the amount of time that was required for it to evolve in the population analyzed here [7] . The ‘innovation interference’ of other highly beneficial mutations within a population suppressing Cit+ evolution has undoubtedly faded in all eleven of these populations as the pace of fitness increase has slowed similarly in all of them [15 , 28] . However , the ubiquity of nadR mutations in the LTEE may indicate that other populations similarly descended into a genetically anti-potentiated state . Our results suggest that Cit++ may still appear in the future if mutations suitably adjust fluxes in central metabolism to make evolving rudimentary Cit+ by activating citT expression a beneficial step on the pathway to innovation , as long as no critical components have been irrecoverably lost from the genome . Through 50 , 000 generations , no population has deleted either citT or dctA , and these genes have not accumulated any mutations in most populations [13] , so the latent genetic potential to evolve Cit+ seems to have remained intact so far . The LTEE is an open-ended evolution experiment [29]; it did not begin with the aim of isolating E . coli that utilize citrate . There was never strong selection for this novel capability . Because evolving citrate utilization allowed the new Cit++ clade to colonize an untapped nutrient niche and rapidly diversify , this new metabolic capacity is an example of a key evolutionary innovation [30] . The evolution of Cit++ initiated a new round of rapid evolutionary optimization that included mutations that reduced the activity of citrate synthase ( gltA2 ) and eliminated flux through the glyoxylate shunt ( aceA ) , both of which reversed the effects of pre-Cit+ adaptive mutations [10] . The many new possibilities for improving fitness in this alternative niche also likely contributed to the evolution of hypermutation within the Cit++ clade by 36 , 000 generations [8] . Lastly , new ecological interactions arose in this population such that Cit− and Cit++ types co-existed via negative-frequency dependent interactions for at least 10 , 000 generations after Cit++ evolved [7 , 8] . Continuing evolution of interactions between these and other E . coli lineages led to the emergence of an ecology that is unique to this flask in the LTEE [11] . We found that a metabolic innovation in a laboratory population of E . coli was contingent on both a history of genetic adaptation and ongoing population dynamics . Evolution of metabolic capabilities has been found to be crucial to the emergence and continued success of bacterial pathogens in several instances [31 , 32] . For example , Salmonella acquired the ability to use tetrathionate as an electron acceptor , giving it a growth advantage relative to other bacteria in the environment that it creates in the gut during infection by inducing inflammation [33] . On a shorter timescale , mutations in the opportunistic pathogen Pseudomonas aeruginosa that accumulate during chronic infections in the cystic fibrosis lung lead to an increased ability to acquire iron from hemoglobin [34] . Even in the simple environment of the LTEE , both genetic and population factors suppress the evolution of an innovation that allows a new niche to be exploited by a new bacterial species . It may be useful in the treatment of disease to understand when these and other factors , including competition for specific nutrients by commensal species in a microbiome , can be used to suppress evolutionary outcomes that are harmful to human health [35] .
E . coli were cultured in Davis-Mingioli ( DM ) medium and Lysogeny Broth ( LB ) [10] . As necessary , media were supplemented with 50 μg/mL kanamycin and 80 μg/mL 5-bromo-4-chloro-3-indolyl β-d-galactopyranoside ( X-gal ) . Evolved clones characterized in this study from archived LTEE populations and strain ZDB706 ( the spontaneous Cit− revertant of ZDB564 ) were isolated in previous studies [7 , 8 , 10] . New strains constructed in this study are listed in S3 Table . The activated Prnk-citT module was constructed by amplifying the evolved rnk-citG duplication junction from the pCit plasmid along with a linked kanamycin resistance gene ( Kanr ) [9] . The Prnk-citT construct in pCit is originally from evolved strain CZB154 [9] . As a control , another module was created which only contains the Kanr marker . These modules were integrated into the genomes of several Cit− strains ( REL607 , REL1166A , ZDB429 , ZDB467 , and ZDB483 ) via lambda Red recombination [36] such that they replaced the lac locus ( lacA to lacZ ) , spanning positions 333 , 862–337 , 485 in the REL606 genome ( GenBank:NC_012967 . 1 ) [37] . We transferred the cassettes to other strains using P1 bacteriophage transduction [38] . Successful transductants were scored based on blue/white screening in the presence of X-gal and kanamycin . All Cit+ strains were made by transduction of the Prnk-citT module into an Ara− LTEE clone . Isogenic Cit− strains were constructed by insertion of the control Kanr module into an Ara+ version of the same clone generated as described in the next section . To determine whether any other mutations present in the evolved strains from the LTEE were altered during transduction , we screened for mutations identified by whole-genome sequencing in the recipient strain that were within 100 kb upstream or downstream of the Prnk-citT insertion site . Strains from three Cit+/Cit− pairs were found to have gained or lost evolved alleles in this process ( S2 Table ) . All Ara− strains inherited a point mutation in araA present in the REL606 LTEE ancestor that prevents arabinose utilization [14] . To isolate spontaneous Ara+ mutants , Ara− strains were revived overnight at 37°C in DM containing 1 mg/mL glucose ( DM1000 ) . For each strain , three separate flasks containing 10 ml of DM1000 were each inoculated with ~500 cells from the first DM1000 culture to reduce the chance that they might share any secondary mutations affecting fitness . After incubating overnight at 37°C , cells were harvested by centrifugation at 4 , 000 rpm for 15 min and the entire volume was plated on minimal arabinose ( MA ) plates . Plates were incubated for 36–48 h and colonies were streaked and grown on new MA plates before picking single-colonies as candidate Ara+ revertants . The presence of secondary mutations affecting fitness was assessed by competing the original Ara− and selected Ara+ strains , as described below . In most cases , we identified an Ara+ revertant with a fitness that was not significantly different from its Ara− progenitor ( S3 Fig ) . Relative fitness was measured using co-culture competition assays [4 , 39] . Two strains to be competed are differentiated based on their ability to ferment arabinose . Ara− strains form red colonies on tetrazolium arabinose ( TA ) media , and Ara+ strains form pink colonies . Strains were revived overnight in LB then were diluted 10 , 000-fold into separate cultures for each replicate competition assay in DM containing 25 μg/mL glucose ( DM25 ) . These cultures were preconditioned and competed under the same conditions as used in the LTEE [4 , 40] , in 10 mL of DM25 in 50 mL Erlenmeyer flasks shaken at 120 rpm over a diameter of 1 inch with incubation at 37°C . After 24 h of growth separately to precondition strains to these conditions , two replicate cultures for each Ara− and Ara+ pair were mixed at equal volumes in fresh DM25 media such that there was an overall 1:100 dilution . Dilutions of these initial mixtures were plated on TA plates to determine the initial representation of each strain in each replicate flask . Then , the competition was carried out over three days of transferring 1:100 dilutions into fresh medium each day . A dilution of each culture after growth on day three was again plated to determine the final representation of each strain . Relative fitness was calculated as the ratio of the realized growth rates of each strain between the final and initial platings [4 , 39] ( S1 Dataset ) . For comparisons of the effect of the authentic rnk-citG duplication versus the addition of the Prnk-citT module to REL606 and ZDB706 ( Fig 1 ) we first established neutrality of an Ara+ revertant and then judged whether there was significant difference between the fitnesses of the Cit− and Cit+ strains pairs . For comparing the fitness impact of evolving Cit+ in other strains ( Fig 2 ) , we measured the relative fitness of the Ara− Cit+ variant of the strain with the Prnk-citT module added versus the Ara+ Cit− revertant of its Cit− progenitor ( Cit competition ) and multiplied this by the relative fitness of the Ara+ Cit− revertant versus the Ara− Cit− clone with the null module added ( Ara competition ) ( S2 Fig ) . To account for how error in each of these two competitions impacts confidence in the overall fitness change inferred for evolving Cit+ , we performed 10 , 000 bootstrap resamplings of the Ara and Cit competition replicates to estimate 95% fitness intervals and significance on the combined measurements . The same bootstrapping procedure was used for comparing the fitnesses of different strains in the population phylogeny in the procedure that combined them into equivalence groups along the lineage to Cit+ ( Fig 4 ) . Cells were cultured according to the method described in Blount et al . [8] . Briefly , cells were initially grown to saturation in a 5 ml LB culture and transferred into 10 ml of DM25 media ( 1:10 , 000 dilution ) followed by two 24-hour preconditioning cycles in DM25 with 1:100 dilutions . For each preconditioning cycle , cells were diluted by 1:100 into fresh DM25 media . At this point , we performed a final dilution of 1:100 into DM25 . Cells were grown until they reached ~50% of the final OD420 and the entire culture ( 10 ml ) was harvested for extracting RNA . RNA was extracted from frozen cell pellets using the RNASnap protocol [41] . The resulting supernatant was column purified , incorporating on-column DNase treatment ( RNA Clean & Concentrator-25 , Zymo Research ) . TapeStation analysis ( Agilent ) was used to verify RNA integrity ( all RIN scores ≥ 8 . 0 ) . Samples were then reverse transcribed in parallel using random primers , with 200ng of RNA as template ( High Capacity Reverse Transcription Kit , Applied Biosystems ) . qPCR was run in 384 well plates on an Applied Biosystems ViiA 7 , using SYBR Green ( Thermo Fisher ) as fluorophore in a 5 μl reaction . QuantStudio was used to determine quantification cycle ( Cq ) values ( S2 Dataset ) . All samples were run in technical triplicates . We selected two reference genes ( refs ) , 16S RNA and idnT , from an initial pool of candidates based on primer efficiency , primer specificity ( as judged by melt curve ) and stability of expression in a subset of our strains of interest . Primer efficiency was calculated from the slope of a plot of log ( dilution ) versus Cq , using a 5-fold or 10-fold dilution series of a pool of cDNA from every sample . Final primer sequences and efficiencies were as follows: citT ( forward = GTTATAGCGGGTAATGTCTTTC , reverse = CACTGATTGGCCTTGTATTG , efficiency = 99 . 25% ) ; idnT ( forward = CCCGACACCGCTATCTACTAATAC , reverse = CGCACCATCGAGCAAATCAT , efficiency = 100 . 5% ) ; 16S ( forward = CCCGAAGGTTAAGCTACCTACT , reverse = CATGAAGTCGGAATCGCTAGTAATC , efficiency = 97 . 6% ) . In our final analysis comparing citT expression across strains , we used three biological replicates per strain , and 2 μl of a 1:100 dilution of cDNA as template . Relative expression ( R ) of citT in the strain of interest relative to ancestral REL606 was calculated as follows . First , ΔCq was calculated for individual biological replicates according to ΔCq=CqcitT−x¯ ( Cqrefs ) , where x¯ ( X ) represents the mean of the values for quantity X . Then , ΔΔCq and R were calculated from the mean ΔCq of three biological replicates for each strain tested as ΔΔCq=x¯ ( ΔCqstrain ) −x¯ ( ΔCqREL606 ) and R = 2–ΔΔCq . Genome sequences were analyzed for 61 evolved strains from the LTEE population in this study ( S1 Table ) . For the 20 newly sequenced strains , genomic DNA was purified using the GenElute Bacterial Genomic DNA kit ( Sigma ) and then sequenced using standard procedures on an Illumina HiSeq 2500 instrument to generate 101-base paired-end reads by the University of Texas at Austin Genome Sequencing and Analysis Facility . Data files for these 20 genomes have been deposited in the NCBI Sequence Read Archive ( SRP120037 ) . Raw sequencing reads for all 61 genomes are available via links from the main LTEE NCBI BioProject page ( PRJNA414462 ) . We initially predicted mutations in each re-sequenced genome by comparing Illumina reads to the REL606 reference genome [37] using breseq ( v0 . 31 . 1 ) [42 , 43] . Then , we further curated the lists of predicted mutations as previously described [13] . Briefly , a maximum-parsimony phylogenetic tree for all 61 strains from the LTEE population was constructed using the DNAPARS program from the PHYLIP package ( v3 . 69 ) [44] . Where necessary , we manually corrected mutation predictions , including adding mutations that were hidden by later deletions or splitting sequence differences into multiple mutational events to construct the most parsimonious phylogeny possible . In the current study , we did not discard mutations in repetitive regions before analysis , except we did ignore changes in the hypervariable 7×CCAG repeat at reference coordinates 2103891–2103918 in the final lists of mutations predicted in all clones ( S3 Dataset ) . To construct the curve for the Wiser et al . model [15] in Fig 4 we calculated the expected time in generations ( t ) and fitness increase ( s ) for each subsequent sweep of a cohort of beneficial mutations using equations S3 , S4 , and S7 from the supplement of that study using parameter values ( α0 = 58 . 4 , μ = 10−7 , and N = 3 . 3×107 ) that they found to be compatible with the fitness trajectories of the non-mutator LTEE populations . For the Tenaillon et al . model [13] , we first calculated a curve describing the number of beneficial mutations expected in an evolved isolate ( n ) according to the term , n=ct , with the best-fit coefficient value ( c = 0 . 135 ) found in that study for all non-mutator LTEE populations considered together . Next , we combined this model with the fitness ( W ) model from Wiser et al . , W ( t ) = ( at + 1 ) b , with best-fit parameters ( a = 0 . 0842 and b = 0 . 00611 ) found specifically for the citrate population ( Ara–3 ) [15] . Finally , the Tenaillon et al . [13] curve in Fig 4 was graphed by calculating each generation ( tn ) at which the number of beneficial mutations ( n ) was an integral value , tn = ( n/c ) 2 . The graphed selection coefficient was estimated as the fitness at that time W ( tn ) minus the fitness at the time of the previous beneficial mutation W ( tn-1 ) . | Key innovations are rare , game-changing moments in evolution when a species or population achieves new success by escaping its normal constraints . We examined a case in which bacteria that had been maintained in the laboratory for fifteen years evolved to exploit a previously untapped nutrient in their environment . Why didn’t this highly beneficial innovation evolve earlier ? We found that two distinct mechanisms suppressed this innovation at different times in the history of the population . Early on , competition drove any new cells that started on the path to evolving the innovation extinct . Later , genetic changes accumulated in the population that shut down the potential to benefit from the new nutrient . After competition abated somewhat and further genetic changes restored a beneficial path to the innovation , it evolved . This example illustrates how stiff competition can force evolving populations to adopt short-sighted , incremental solutions that block or significantly delay achieving innovative breakthroughs . | [
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... | 2018 | Innovation in an E. coli evolution experiment is contingent on maintaining adaptive potential until competition subsides |
Despite having caused one of the greatest medical catastrophies of the last century through its teratogenic side-effects , thalidomide continues to be an important agent in the treatment of leprosy and cancer . The protein cereblon , which forms an E3 ubiquitin ligase compex together with damaged DNA-binding protein 1 ( DDB1 ) and cullin 4A , has been recently indentified as a primary target of thalidomide and its C-terminal part as responsible for binding thalidomide within a domain carrying several invariant cysteine and tryptophan residues . This domain , which we name CULT ( cereblon domain of unknown activity , binding cellular ligands and thalidomide ) , is also found in a family of secreted proteins from animals and in a family of bacterial proteins occurring primarily in δ-proteobacteria . Its nearest relatives are yippee , a highly conserved eukaryotic protein of unknown function , and Mis18 , a protein involved in the priming of centromeres for recruitment of CENP-A . Searches for distant homologs point to an evolutionary relationship of CULT , yippee , and Mis18 to proteins sharing a common fold , which consists of two four-stranded β-meanders packing at a roughly right angle and coordinating a zinc ion at their apex . A β-hairpin inserted into the first β-meander extends across the bottom of the structure towards the C-terminal edge of the second β-meander , with which it forms a cradle-shaped binding site that is topologically conserved in all members of this fold . We name this the β-tent fold for the striking arrangement of its constituent β-sheets . The fold has internal pseudosymmetry , raising the possibility that it arose by duplication of a subdomain-sized fragment .
Thalidomide was provided to pregnant women as an anti-nausea and sedative drug from 1957 to 1962 , and was available over the counter in many countries . It was withdrawn after it became apparent that it had caused a range of birth defects in many newborns , with over 10 , 000 cases reported from more than 46 countries [1] , [2] . Soon after its ban , however , it was reintroduced as an agent against a complication of leprosy [2]–[4] , due to its anti-inflammatory and immunomodulatory activity , and has since then also been evaluated for treatment of , among others , AIDS and Crohn's Disease [5] . In 1994 , evidence of its antiangiogenic activity led to its consideration for cancer therapy [6] and it is one of the main drugs available today against multiple myeloma [7] , [8] . Despite strict controls on its use , its value in the treatment of leprosy leads to the ongoing birth of babies with thalidomide-induced malformations in developing countries [2] , [9] . Because of its antiangiogenic and immunomodulatory activities , pharmacological interest in thalidomide continues to be very high [5] , but until recently , its molecular mechanism of action – both with respect to its positive and its negative effects – remained unclear due to a lack of known targets . In 2010 , Handa and co-workers showed in a landmark study that cereblon , a protein originally identified in a screen for mutations causing mild mental retardation [10] , is a major target of thalidomide and is responsible for the teratogenic effects of the drug [11] . Cereblon owes its name to its involvment in brain development and to its central LON domain , which led to its initial annotation as an ATP-dependent Lon protease [10] . In the 2010 study , Handa and co-workers showed that cereblon is a cofactor of damaged DNA-binding protein 1 ( DDB1 ) , which acts as the central component of an E3 ubiquitin ligase complex and regulates the selective degradation of key proteins in DNA repair , replication and transcription [12] . Binding of thalidomide to a C-terminal region in cereblon inhibits the E3 ubiquitin ligase activity of the complex and leads to developmental limb defects in chicks and zebrafish [11] . Point mutations in this region , which abolish thalidomide binding , but allow the continued formation of the E3 complex , restore ubiquitination and prevent the teratogenic activities of thalidomide . Despite these advances , there has been little progress in understanding the mechanism of thalidomide binding and teratogenicity , due to the difficulties in preparing cereblon protein for biochemical and biophysical studies . Such progress would however be important for further pharmacological development , given that current thalidomide derivatives , such as pomalidomide and lenalidomide , appear to have inherited its teratogenicity ( see e . g . [13] ) . In search of a better understanding of cereblon , we decided to subject the protein to a detailed bioinformatic analysis , with a particular focus on its thalidomide-binding domain . Here we show that this domain is present in several protein families of eukaryotes and bacteria , is related to the highly conserved yippee and Mis18 proteins of eukaryotes , and has a homologous origin with methionine sulfoxide reductase B , the regulatory domain of RIG-I helicase , and glutathione-dependent formaldehyde-activating enzyme . Our findings place the domain into a broad evolutionary context and show that the development of model systems is possible in order to study specific aspects of cereblon activity .
Cereblon proteins occur throughout eukaryotes , however not in fungi . They are typically 400–600 residues long ( 442 in the case of human cereblon ) and their genes occur in single copy per genome . Their most salient feature is the presence of a central LON domain ( residues 80–317 in human cereblon , Fig . 1 ) . As defined in the Pfam and SMART databases , the LON domain actually comprises two domains , an N-terminal pseudo-barrel of six β-strands , closed off on one side by a helix , ( LON-N ) and a helical bundle of four to five helices – four in the case of cereblon , to judge by secondary structure prediction and length of the domain ( LON-C ) . The two LON domains are connected by an unstructured loop of typically around 10 residues , which however is much longer in cereblon , at about 60 residues . Handa and co-workers identified this region by deletion analysis as responsible for DDB1 binding ( Fig . 1 ) [11] . Since an α-helical motif – the H-box – has been found to be a crucial structural element used by both viral and cellular substrate receptors to bind to DDB1 [14] , we surmised that an H-box exists in cereblon as well , in the segment connecting LON-N with LON-C . H-box sequences are however very divergent and the H-box is thus primarily defined by its helical propensity and a general pattern of hydrophilic and hydrophobic residues [14] . We tried to identify an H-box in cereblon , and particularly in the connector between the two LON domains , by searching against a profile HMM generated from the H-box sequences listed by Li et al . [14] , but did not obtain statistically significant matches . The connector is poorly conserved across phyla , but contains a highly conserved motif WPxWxYxxYD immediately prior to the start of the LON-C domain ( Fig . 1 ) . Since this motif coincides with a region of elevated helical potential , we considered this the best guess for the site of DDB1 interaction . After submission of this manuscript , two studies presented the structure of cereblon in complex with DDB1 [15] , [16] , which showed that the interaction between the two proteins is topologically novel and not mediated by an H-box . All three regions with elevated helical propensity in the connector ( Fig . 1 ) are indeed helical , albeit the first one as a 310 helix . The main interactions are formed between the first region and DDB1 β-propeller A , and between the third region ( containing the conserved motif ) and DDB1 β-propeller C . N-terminally to the LON domain , cereblon proteins have an extension of typically 50–100 residues ( 79 in the case of human cereblon ) , of which the front part is not conserved across phyla and generally predicted as intrinsically unstructured ( Fig . 1 ) . Starting about 35 residues prior to the beginning of the LON domain , the extension becomes well-conserved and particularly a motif FDxxLPxxHxYLG is recognizable in most cereblon homologs , from humans and plants to basal eukaryotes . Since the extension is adjacent to the connector between LON-N and LON-C in the LON domain model ( Fig . 1 ) and experimental evidence suggested the binding interactions with DDB1 to be bipartite [14] , we considered that this motif could contribute to DDB1 binding . The cereblon-DDB1 complex structures however show that the extension interacts with the C-terminal region of cereblon via the conserved motif [15] , [16] . Indeed , since it runs alongside the thalidomide-binding site , it may relay information on the occupancy of the site to the LON-N domain . We therefore conjecture that deletion of the extension could uncouple the C-terminal region from the rest of the E3 ligase complex , alleviating or even entirely abolishing the effects of thalidomide binding . The C-terminal region of cereblon , comprising about 100–130 residues ( 125 in the case of human cereblon ) , represents the best-conserved part . It has multiple invariant residues and encompasses completely the part of the protein identified through deletion analysis as responsible for thalidomide binding [11] . Sequence similarity searches show that this region also occurs in much shorter proteins than cereblon , where it essentially covers the entire length of the protein , identifying it as a domain . We name this domain CULT , for cereblon domain of unknown activity , binding cellular ligands and thalidomide . With the CULT domain of human cereblon as a starting point , PSI-Blast searches of the non-redundant protein database at NCBI converge in three iterations . Analysis of the results , for example using clustering by pairwise sequence similarity in CLANS ( Fig . 2 ) , shows that most of the search space consists of cereblon sequences , recognizable by their LON domain , but that several other groups of CULT domain-containing proteins are identifiable . The two main groups are: ( I ) prokaryotic proteins , mainly from δ-proteobacteria , but with a few representatives from α- and γ-proteobacteria and one sequence from a spirochete; these proteins consist entirely of the CULT domain; and ( II ) animal proteins from placozoans to vertebrates , but not occurring beyond fishes; these proteins also consist of the CULT domain , but carry an N-terminal secretion signal sequence . Indeed , the homolog from the sand fly Phlebotomus arabicus has been identified experimentally as a salivary protein [17] . Two further , more divergent groups are also apparent: one from oomycetes , with an N-terminal signal sequence followed by a CULT domain and ending with a carbohydrate-binding domain ( SCOP: b . 64 ) ; and the second from kinetoplastids , with an N-terminal CULT domain followed by a C-terminal region that cannot be assigned to a known domain family at present . The remaining few sequences from the PSI-Blast search do not recognizably belong to any of these groups; they are mainly from green algae and can all be confirmed by reverse PSI-Blast searches to contain a CULT domain . Multiple alignment of the sequences identified in the search ( Fig . 3A ) show that several residues are highly conserved in the CULT domain . Conservation of these residues is highest in the CULT core group ( cereblon , secreted eukaryotic sequences , bacterial sequences ) and declines towards the periphery . Particularly conspicuous are three tryptophan residues , marked by arrows in Fig . 3A , which are seen to form the binding site for thalidomide and cellular ligands in the crystal structure of the bacterial CULT protein MGR_0879 from Magnetospirillum gryphiswaldense ( [18]; PDB ID:4V2Y; Figs . 3B , C ) . The crystal structure , which we determined after this bioinformatic study , shows that the other highly conserved residues group around this binding site ( S1 Fig . ) , their conservation being rationalized by an influence on substrate recognition and discrimination . The one exception to this are two CxxC cysteine motifs , which we took from the beginning of this project to be indicative of a zinc binding site and thus present for structural reasons . We developed the bacterial model system to study the CULT domain because we found eukaryotic cereblon proteins very difficult to express in useful amounts and even more difficult to purify in a soluble state . In contrast , the bacterial protein could be produced and purified in a straight-forward way [18] . We reasoned that , at 36% sequence identity and with almost all well-conserved positions similar or the same between the CULT domains of humans and Magnetospirillum , the bacterial system should represent an accurate model for the eukaryotic domain . The structures of eukaryotic CULT domains from human , mouse and chicken [15] , [16] now show that the expectation is true to an astonishing extent , with a root-mean-square deviation ( r . m . s . d . ) of around 0 . 9 Å over 100 Cα positions between the bacterial and human proteins ( Fig . 3B ) . The bacterial domain is thus structurally almost as similar to the eukaryotic domains as these are to each other ( Table . S1 ) . We searched for remote homologs of the CULT domain using profile Hidden Markov Model ( HMM ) comparisons in HHpred and obtained matches at probabilities better than 90% ( E values <1e-6 ) for multiple protein families , several of which have members of known structure ( Fig . 4 ) . The best matches were to a protein family found throughout eukaryotes , yippee [19] . Two of the five yippee paralogs in mammals have been implicated in signal transduction [20] and tumor suppression [21] , respectively , but the actual mechanism of these proteins remains unknown . In searching against Pfam we noticed that , in this database , the profile for yippee ( PF03226 ) was generated jointly with another protein , Mis18 , which in our analyses is not particularly close to yippee and indeed seems about as remote from yippee as cereblon is ( Fig . 5 ) . Mis18 proteins are broadly represented in eukaryotes , except plants , and appear to be involved in centromere assembly [22] , [23] , although their actual mechanism remains unknown . The reason for merging Mis18 with yippee in Pfam is unclear to us . Two protein families of known structure related at a similar level to the CULT domain as yippee and Mis18 are methionine sulfoxide reductase B ( MsrB or SelR ) and the regulatory domain of retinoic acid-induced gene-1 ( RIG-I ) . MsrB is the most widely distributed protein in this study and is universal to all cellular life . It protects cells from oxidative stress by reducing methionine-R-sulfoxide residues ( for a review see e . g . [24] ) . RIG-I has a more limited phylogenetic spectrum , being detectable only in animals . It is an RNA helicase that , upon binding viral RNA , activates the host innate immune system ( for a review see e . g . [25] ) . The regulatory domain is the RNA 5′-triphosphate sensor of RIG-I , activating the ATPase activity of the protein by RNA-dependent dimerization [26] . These four proteins , yippee , Mis18 , MsrB , and RIG-I , are sufficiently close to the CULT domain in sequence space that they usually show up in the non-significant part of sequence similarity searches , between E values of 0 . 005 and 10 , and are occasionally included in the significant part as well . Thus , for example , PSI-Blast searches of the nr database with our bacterial model protein , Magnetospirillum MGR_0879 , include the first yippee and RIG-I sequences in the second iteration and the first Mis18 and MsrB sequences in the fifth . These proteins appear roughly equidistant from cereblon in sequence space ( Fig . 5 ) . More distantly related , but showing up with fair regularity in our searches is glutathione-dependent formaldehyde-activating enzyme ( GFA ) , a protein found in bacteria and most eukaryotes , except plants . GFA catalyzes the first step in the detoxification of formaldehyde [27] . All these proteins share a common fold , formed by two four-stranded , antiparallel β-sheets that are oriented at approximately a right angle and pinned together at their tip by a zinc ion ( Fig . 6 ) . The two sheets are connected covalently across the top on both sides by loops , due to circular permutation . Thus , the last strand of the domain is topologically the first strand of the first sheet , yielding the strand order β8-β1-β2- ( β3 ) for the first sheet and ( β4 ) -β5-β6-β7 for the second ( β3 and β4 are shown in brackets as , in some structures , they have lost their β-strand character ) . Because of the striking arrangement of these β-sheets we have named this fold the β-tent . A conserved feature of all proteins with a β-tent fold is an insertion between strands β2 and β3 , which usually has a β-hairpin stem and reaches across the bottom of the tent to extend the second β-sheet at its C-terminal edge . Due to the curvature of the β-sheet and the sizable nature of the loops connecting β4 to β5 on one side and the strands of the insertion on the other , all β-tent proteins contain a cradle-shaped groove at this location , which hosts the binding site ( Fig . 7 ) . The residues giving the binding site its specificity in the individual proteins are frequently found in equivalent positions . This is particularly conspicuous when comparing the binding sites of CULT and MsrB ( Fig . 8 ) . Of the four residues forming the thalidomide-binding site in Magnetospirillum CULT ( 4V2Y: W79 , W85 , W99 , and Y101 ) , the last three have equivalents in homologous positions in the methionine sulfoxide-binding site of MsrB ( 3HCI: R97 , H111 , F113 ) ; the first , W79 , is also a tryptophan in the MsrB binding site , but from an analogous position in the insert loop ( W73 ) , due to a shift in the position of the site caused by the shape difference between W85 of CULT and R97 of MsrB . This shift places the ligand above β7 in MsrB , rather than above β6 , allowing the positioning of a further residue into the active site , which is the catalytic cysteine; conversely , there appears to be no need for a catalytic residue in CULT . We note that the homology of the conserved aromatic residues in CULT to the residues of the binding site in MsrB can be readily seen from the HHpred alignment . Extending these observations to yippee , which has a similar distribution of conserved residues as CULT ( S1 Fig . ) , we predict that the binding site of this protein is also an aromatic cage , comprising the highly conserved Y43 , F45 , W82 , and Y84 , as numbered in D . melanogaster yippee isoform B , ABC67182 . 1 ( Fig . 7 ) . Of these , W82 and Y84 are in homologous positions to W99 and Y101 of CULT and H111 and F113 of MsrB , whereas Y43 and F45 are at the same position as W73 in MsrB , but not recognizably homologous . A striking property of the β-tent fold is that , in several of the proteins , the two sheets have considerable structural symmetry , such as for example in the MsrB structure 3HCJ , where superposition of the two 43-residue halves yields an r . m . s . d . of 1 Å over the Cα positions of the core 30 residues ( Fig . 6 ) . This raises the possibility that the fold originated by duplication of a subdomain-sized fragment , but we note that no similarity is detectable between the two halves by sequence comparisons . Searches in structure space for other proteins with the β-tent fold yielded three more proteins of known structure ( Figs . 6 , S2 ) , which share the fold with the same topology of secondary structure elements , including the β-hairpin extension between strands β2 and β3 , but have no significant sequence similarity to the other proteins in this study , or to each other ( Fig . 4 ) . These are MSS4 , a guanine exchange factor and nucleotide-free chaperone for the Rab GTPase [28] , [29] , TCTP , a pleiotropic protein involved in malignant transformation and regulation of apoptosis [30]–[32] , and DUF427 , a domain of unknown function . Whereas MSS4 and TCTP are eukaryotic proteins , TCTP being present universally and MSS4 broadly , but not in plants , DUF427 is seen mainly in bacteria and fungi , with a small number of archaea presumably having acquired this domain by lateral transfer . Of these proteins , only MSS4 has the zinc binding site ( Fig . 6 ) . In the SCOP database , MSS4 and TCTP are grouped together with MsrB and GFA as families within the MSS4-like superfamily , which is the sole representative of the MSS4-like fold ( b . 88 ) . A fundamental issue in understanding the biological role of CULT domains , not directly illuminated by their homology to other proteins , is the identification of their physiological ligand ( s ) . The only ligands known today , thalidomide and its derivatives , are clearly non-physiological . Given that the clustering of the invariant tryptophans into a cage-like arrangement was already suggested at the modeling stage ( see above ) , we searched PDB for ligands bound in aromatic cages , loosely defined . For this we allowed the aromatic residues to be Phe and Tyr , as well as Trp , and provided only a very general requirement for cage-like geometry , in order to gain as broad a view as possible ( see Methods ) . We obtained 1098 distinct ligands , which could be grouped approximately into five classes , corresponding to heterocyclic rings , hydrocarbon rings , hydrocarbon chains with and without heteroatoms , and ammonium-based cations ( Fig . 9 , Table S2 ) . Upon inspection , many of the “cages” identified indeed turned out to be only approximately cage-like and for 46 ligands , all binding sites turned out to be geometrically too divergent to be considered further . Half of the identified ligands belonged to the largest class , comprising heterocyclic rings . Many of these were enzyme inhibitors , both of natural and synthetic origin , such as indole-2 , 3-diones ( 4KWG ) , aryl hydrazines ( 4MQQ ) , or non-nucleoside reverse transcriptase inhibitors ( 1S9G ) . Thalidomide , which is bound in the aromatic cage of CULT domains via its glutarimide ring , belongs to this class . Among the natural compounds , we found pyrimidines and their nucleosides of particular interest , as these resemble the glutarimide ring of thalidomide [18] and are bound in similar cages . For example , the transcription factor RutR ( 3LOC; Fig . 9B ) can bind both uracil and thymine in its aromatic cage and acts as the master regulator of genes involved in the synthesis and degradation of pyrimidines [33] . An experimental screen against Magnetospirillum MGR_0879 found that , of the nucleobases , uracil and its nucleoside ( uridine ) were indeed bound and their relevance for eukaryotic cereblon could be established in vivo in zebrafish . It is attractive to consider that they might also be the physiologically relevant ligand , given that DDB1 is an integrator of cellular information on DNA damage and incorporation of uracil into DNA represents a mutagenic lesion [18] . Another type of ligand that we found to be of particular interest in this analysis comprises amino acid sidechains , modified and unmodified . These include the heterocyclic rings of His , Pro , and Trp , the hydrocarbon rings of Phe ( Fig . 9C ) and Tyr , the hydrocarbon chains of Ile , Leu ( Fig . 9D ) , Met , and Val , and the cationic sidechains of metylated and unmethylated Lys ( Fig . 9G ) and Arg ( Figs . 9H , S3 ) . Particularly the latter occur prominently in the tails of histones and are recognized by aromatic cages in a range of different domains , including bromodomains , chromodomains ( Fig . 9G ) , and Tudor domains ( Fig . 9H ) . Given that the DDB1-Cul4A E3 ubiquitin ligase complex is known to bind and ubiquitinate histones ( see e . g . [34] ) , an activity of cereblon in recognizing histone tail modifications within a linear sequence motif and providing the target specificity for the ligase complex appears fully plausible [18] . Other sidechain interactions , particularly in the context of linear sequence motifs , also appear entirely possible . Thus , the homeobox transcription factor MEIS2 , which is implicated in various aspects of human development , was recently identified as a cereblon interactor [15] . Its binding was exclusive with thalidomide and its derivatives , suggesting that it is recognized via the same binding site . We note that MEIS2 and its paralogs contain two folded domains , one being the homeobox domain and the other uncharacterized at present , flanked by extended regions predicted to be unstructured and with low sequence conservation . The N-terminal approximately 10 residues are however very highly conserved and contain sidechains ( Arg , Tyr , His ) that could easily be envisaged as the ligands of an aromatic cage . We therefore consider this region to be the most attractive first candidate for exploring the MEIS2-cereblon interaction . This said , the very high similarity between the bacterial and eukaryotic CULT domains , particularly in the area of the aromatic cage , points to a wide-spread ligand , present also outside the cell , rather than to a linear sequence motif . By similarity to metyllysine , one might envisage choline , carnitine , betaine , and related compounds , but none of these could so far be seen to interact with the CULT domain in our model system .
In this article we have presented evidence that the thalidomide-binding region of cereblon is a conserved domain , CULT , present in several other proteins of eukaryotes and bacteria . The CULT domain is recognizably homologous to at least five other domain families , which share - where known - a common fold and a shared mechanism of ligand binding . The fold is also recognizable in three further domain families , which however do not have detectable sequence similarity to any of the other proteins , or to each other , and whose evolutionary relationship thus remains unclear ( the SCOP database , however , clearly considers them homologous , as it groups them into the same superfamily ) . We have named the common fold of these proteins the β-tent , due to the orientation of its two constituent β-sheets . The widely differing activities of proteins with a β-tent fold , as well as the absence of invariant residues across the domains , suggest that the β-tent is a structural scaffold , which mounts a binding site at a specific location . The binding site is formed by a cradle-shaped groove , whose sides are provided by loops connecting strands β4 to β5 , and βI1 to βI2 of the common fold; the bottom is formed by strands β5 , β6 , and β7 . The elaboration of this site in the individual families is tailored to their specific function , but appears to follow common principles , particularly in families binding small-molecule ligands . Here , binding residues are mainly located on the two loops and strand β6 , while catalytic residues appear to be located on strand β7 . For families whose binding site is at present unknown , this can therefore be reasonably predicted by mapping their conservation pattern onto homology models of the relevant region . Members of the β-tent fold show , to varying degrees , a twofold rotational symmetry around a central axis passing through the apical zinc ion ( where present ) . The symmetry is most pronounced in MsrB and this domain also has the broadest phylogenetic spectrum , being the only one with a universal representation in all cellular life forms . It therefore seems attractive to surmise that it is the ancestral representative of this fold , from which the others evolved by duplication and differentiation , and that it itself originated by duplication of a four-stranded β-meander . We have previously argued for an origin of folded proteins from subdomain-sized peptides [35] , [36] . But for the apparent lack of internal sequence symmetry to support this inference , the β-tent would seem an attractive candidate for such a scenario . The absence of statistically significant sequence similarity between MSS4 , TCTP , DUF427 and the other proteins of this fold raises the possibility of a convergent origin . We note however that MsrB and RIG-I also do not share statistically significant sequence similarity between each other ( Fig . 4 ) and are only connected conclusively in sequence space via CULT and yippee ( Fig . 5 ) . The homology of all proteins with a β-tent fold thus remains a clear possibility , which may become substantiated by new domain families found in hitherto poorly explored parts of the tree of life .
Sequence similarity searches were carried out at the National Institute for Biotechnology Information ( NCBI; http://blast . ncbi . nlm . nih . gov/ ) and in the MPI Bioinformatics Toolkit ( http://toolkit . tuebingen . mpg . de; [37] ) . PSI-Blast [38] at NCBI was run on the non-redundant protein sequence database ( nr ) with an E-value threshold of 0 . 005 . CS-Blast [39] in the MPI Toolkit was run on a version of nr clustered at 70% sequence identity ( nr70 ) , also with a threshold of E = 0 . 005 . The sequence relationships of proteins identified in these searches were explored by clustering them according their pairwise Blast P-values [40] in CLANS [41] . Clustering was done in default settings ( attract = 10 , repulse = 5 , exponents = 1 ) , with other settings as given in the figure legends . Searches for more distant homologs were made with HHpred [42] and HHsenser [43] on the databases pdb70 ( sequences of protein databank structures , as available in April 2014 , clustered at 70% sequence identity ) , CDD ( conserved domain database from NCBI , as of February 2014 ) , pfamA release 27 . 0 , SCOP release 1 . 75 , and profile HMM databases of all human and all Drosophila proteins built locally and available through the MPI Toolkit . Secondary structure was predicted in the MPI Toolkit , using the meta-tool Quick2D . Structure similarity searches were carried out on the Dali server ( ekhidna . biocenter . helsinki . fi/dali_server; [44] ) . Molecular models were built using Modeller [45] , and manipulated in Swiss PDB Viewer [46] and PyMol ( Schrödinger , LLC ) . Sequence conservation patterns were visualized with ProtSkin ( http://www . mcgnmr . mcgill . ca/ProtSkin/; [47] ) . Aromatic cage-like conformations containing ligands in PDB structures were detected by applying a set of geometric criteria ( see Figure 9A ) . First , in each PDB structure , all non-water molecules in the HETATM record were identified and regarded as ligands . Only aromatic residues ( phenylalaline , tryptophan and tyrosine ) within 6 . 0 Å distance to these ligands were considered in further analysis . Then , we defined a set of at least three aromatic residues from the same polypeptide chain to form a cage-like conformation interacting with a ligand if: a ) all pairwise distances between their side chain mass centers ( MCSC ) were less than 10 . 0 Å; b ) the angle between and was less than 60° for at least three of the aromatic residues , where is the normal vector of the aromatic ring , is the vector connecting MCSC and the mass center of all side chain heavy atoms ( MCALL ) ; and c ) at least two ligand atoms were within 3 . 0 Å distance to MCALL . The program was implemented in Python using BioPython [48] , SciPy [49] and NetworkX [50] libraries . We applied these geometric rules to scan 102 , 886 PDB files downloaded from the PDB ( 24 Aug 2014 ) . In total , 6 , 144 putative aromatic cage-like conformations were detected with 1 , 098 different ligands binding to them . We grouped the cages according to the ligands they interact with . In each group , redundant cage-like conformations were removed ( two cage-like conformations were considered identical if the composite residue names and numbers were the same ) . Subsequently , we manually examined at least one cage-like conformation in each of the 1 , 098 groups . Based on the ligand moiety within the aromatic cage , we further classified the 1 , 098 groups into different categories ( S2 Table ) . | In the public perception , thalidomide mainly evokes children with stunted limbs . Less known is that thalidomide continues to be a very useful drug , licensed in most countries for the treatment of multiple myelomas and leprosy . Aside from its catastrophic effect on human embryonal development , it has a manageable spectrum of side-effects and a broad range of potential indications . Interest in its further pharmacological development thus remains high , but is hindered by our limited knowledge of the reasons for its worst side-effect – teratogenicity . For half a century , even the main protein target of thalidomide in the human body remained unknown , until a seminal study showed in 2010 that this was cereblon . Further progress towards a mechanistic understanding has however been limited by the difficulties in using cereblon for biochemical studies . Here we show that the thalidomide-binding region of cereblon is contained within a domain also present in other protein families , and that this domain is related to several domains with known functions . Where established experimentally , all these domains are seen to form their main substrate-binding sites at the same location in the common fold , often using residues in equivalent positions . Our findings offer the possibility to develop model systems for the study of specific aspects of cereblon activity . | [
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"research",... | 2015 | The Thalidomide-Binding Domain of Cereblon Defines the CULT Domain Family and Is a New Member of the β-Tent Fold |
Despite widespread interest in social dominance , little is known of its neural correlates in primates . We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals . To examine this possibility we used magnetic resonance imaging ( MRI ) , which affords the taking of quantitative measurements noninvasively , both of brain structure and of brain function , across many regions simultaneously . We carried out a series of tests of structural and functional MRI ( fMRI ) data in 25 group-living macaques . First , a deformation-based morphometric ( DBM ) approach was used to show that gray matter in the amygdala , brainstem in the vicinity of the raphe nucleus , and reticular formation , hypothalamus , and septum/striatum of the left hemisphere was correlated with social status . Second , similar correlations were found in the same areas in the other hemisphere . Third , similar correlations were found in a second data set acquired several months later from a subset of the same animals . Fourth , the strength of coupling between fMRI-measured activity in the same areas was correlated with social status . The network of subcortical areas , however , had no relationship with the sizes of individuals' social networks , suggesting the areas had a simple and direct relationship with social status . By contrast a second circuit in cortex , comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex , covaried with both individuals' social statuses and the social network sizes they experienced . This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status .
Social status is a salient feature of group life in many primates including humans and macaques [1] . Position in the dominance hierarchy influences access to food and mates and is a predictor of health and reproductive success [2] . It is also associated with individual differences in behavior; for instance , more dominant macaques make more prosocial choices and are more likely to make a choice that leads to reward for both themselves and another as opposed to a choice that leads just to reward for themselves [3] , [4] . Although subordinate animals pay attention to social cues provided by animals from any social rank , dominant animals follow information provided by other dominant animals [5] . Despite widespread interest [6] , [7] the neural correlates of social status in primates are largely unknown . Identifying brain areas in which structure and function are related to social status is an important first step for understanding the neural mechanisms that might drive social status and mediate its consequences . Serotonin has been linked to dominance status; pharmacological manipulations that increase or decrease serotonergic activity lead , respectively , to increases and decreases in dominance status in monkeys [8] . However , the wider neural system in which serotonin operates in relation to dominance in primates has proved difficult to investigate . An alternative approach to studying the neural correlates of primate dominance has been to induce relative differences in social status during the playing of interactive games in human subjects . The amygdala was recently implicated in tracking social hierarchy during performance of such a game in human subjects [9] , but the degree to which playing brief and artificial games induces or simulates the often protracted differences in dominance status experienced by primates , including humans , in the real world remains unclear . Here , we investigate the neural correlates of social status by relating spontaneously occurring social dominance status in 25 captive macaques to differences in their brains' gray matter ( GM ) , measured with structural MRI , and the spontaneous coupling of activity between brain regions , measured with functional MRI ( fMRI ) . Quite distinct aspects of macaque behavior have been related to neural structure and function in this way in the past [10] . MRI has the advantage of furnishing quantitative measurements of neural data across the whole brain . However , some of the neural structures implicated in other fundamental aspects of emotional and motivational behavior are subcortical and small in size and so they are difficult to investigate with non-invasive approaches . Questions remain , however , over the best methods to ensure the reliability and robustness of whole brain GM differences . The originators of MRI voxel-based GM analyses emphasized that taking into account the spatial extent , across adjacent MRI voxels , of any statistical effect may not be appropriate in GM analyses [11] . Instead they suggested an alternative approach for testing whether or not relationships between GM and behavioral or disease variables are robust; they suggested examining whether effects are bilaterally symmetrical [12] . The approach of finding similar effects in bilaterally symmetrical structures was used in some of the earliest human GM analyses by some of these investigators [13] and has continued to be used [14] . It rests on the assumption that if a statistical effect noted had a chance of occurrence of p<0 . 001 in one brain area under the null hypothesis , then it has the chance of occurring in the same area in both hemispheres with the square of this probability ( i . e . , p<0 . 00001 ) [12] , [14] . The convention adopted in these studies in recent years has been to focus on effects that extend over 10 voxels [14] and so we have adopted the same approach in our study . In addition to the whole brain approach , we also adopted a hypothesis-driven region of interest ( ROI ) approach widely used in human neuroimaging . We examine effects in predefined ROIs using a threshold of p<0 . 05 and correction for multiple comparisons across all voxels in the ROI . As noted above , there are a priori reasons for thinking that dominance may be associated with the amygdala and the serotonergic system . We cannot , with a non-invasive approach such as MRI , selectively examine neurons identified as serotonergic , but we can examine whether the brainstem nuclei containing many serotonergic nuclei have any association with dominance . As explained below , the two analysis approaches , the ROI-led and the more exploratory search for bilaterally symmetric effects , suggest similar conclusions . In addition to social status , another major aspect of social life is overall size of the social network that an animal experiences . Previously we reported that structure and activity in a specific network of cortical areas in the macaque , centered on the mid-superior temporal sulcus ( mSTS ) , anterior cingulate cortex ( ACC ) , and dorsal and rostral prefrontal cortex ( PFC ) reflects each macaque's social group size [15] . In an additional analysis , we contrasted the relationship between brain structure and these two social variables: social status and social network size . We identified subcortical regions that were solely related to social status and cortical regions linked to social status and social network size . The pattern of results suggested the existence of two distinct networks related to different aspects of social status .
We obtained structural and fMRI scans of 25 macaques living in groups of five , four , three , and two individuals ( five , twelve , one , and seven animals in each case ) after assigning each animal a cardinal index of dominance on the basis of its behavioral interactions ( based on [16] ) . Deformation-based morphometric ( DBM ) analysis was used to identify regions in the left hemisphere where GM covaried with social status . This analysis specifies the expansion/contraction required at each voxel in the group average templates scan to deform the brain to an individuals' brain . A discussion of these types of methods can be seen in [17] . First , we report the results of tests examining the relationship between dominance and GM , after controlling for age , weight , sex , and number of structural scans included in the DBM ( see Methods ) [15] , in a 2752 . 5 mm3 ( 22 , 020 voxels ) ROI ( Figure 1 ) centered over bilateral medial temporal lobe so as to include the whole amygdala . After correcting for multiple comparisons across all voxels in the ROI , we were able to identify voxels extending from the central AMY to the border with the hippocampus in both left and right hemispheres that showed a relationship with dominance ( p<0 . 05 corrected for multiple comparison; Figure 1 ) . Next we examined a 2 , 574 . 5 mm3 ( 20 , 596 voxels ) bilateral ROI ( Figure 2 ) in the brainstem between the medulla and the midbrain so as to include the location of the serotonergic nuclei . Using the same approach in the amydala investigation , we identified voxels both to the left and right of the midline with a significant association with dominance ( p<0 . 05 corrected for multiple comparisons; Figure 2 ) . The region included parts of the RN and the adjacent reticular formation such as the gigantocellular reticular nuclei . Next we employed the approach of looking for bilaterally symmetrical brain regions in which GM exhibited similar relationships with dominance [12]–[14] . We used the same threshold as in other recent human GM investigations [14]: p<0 . 001; volume>1 . 25 mm3 , equivalent to 10 adjacent voxels . The chance that bilaterally symmetrical effects would be found in the two hemispheres under the null hypothesis is , of course , even lower ( p<0 . 00001 ) . In order to explain the approach , we first report how we sought regions of GM in the left hemisphere where the deformation was significantly related to social status after controlling for age , weight , sex , and number of structural scans included in the DBM ( see Methods ) [15] and identified ( 1 ) the AMY , ( 2 ) a region centered on the posterior hypothalamus ( PH ) but extending into adjacent lateral hypothalamus , and ( 3 ) a brainstem region that again included parts of the RN and the adjacent reticular formation such as the gigantocellular reticular nucleus ( Figure 3 and Table S1 ) . In other words , this alternative approach identifies the same two areas that were identified in the ROI approach and a third region—the PH . We also sought regions of GM that significantly correlated with decreased dominance , or subordinance scores . We identified several regions within the striatum and the adjacent septum . These comprised the posterior putamen ( PPUT ) , and the tail of the caudate ( CAUD ) ( Figure 4 and Table S1 ) . Using a slightly more liberal statistical threshold of p<0 . 005 ( volume>5 mm3 ) , however , we were also able to identify a relatively extensive region in the anterior dorsal striatum , in the caudate nucleus , that extended into dorsal parts of the septum ( DS ) ( Figure 4 ) . We note the existence of this region here because we again found evidence for a negative relationship between all three of these brain structures and dominance even at the more stringent statistical criterion level of p<0 . 001 in the right hemisphere ( see below ) . To examine the reliability of the effects we had found in the left hemisphere , we next examined whether effects could be found in the other hemisphere . A similar approach has been used in human neuroimaging experiments [12]–[14] . We sought regions of GM in the right hemisphere where the deformation was significantly related to social status ( positive and negative correlations are shown in Figures 5 and 6 , respectively ) . Notably all regions survived at our strigent criterion ( p<0 . 001 , volume>1 . 25 mm3 ) , with the exception of the RN , which survived at p<0 . 005 ( cluster volume , 6 . 5 mm3 ) . Importantly , at this threshold , the effect was spatially extensive and included many voxels at which the effect was significant at p<0 . 001 ( Figure 5 , righthand panel ) . Again in the right hemisphere , as in the left hemisphere , we also found evidence of a negative relationship between GM and social status in PPUT , CAUD , and DS . Notably the DS region that had been tentatively idenfied in the left hemisphere was the largest cluster to survive within the analysis at p<0 . 001 of right hemisphere effects ( cluster volume , 5 . 375 mm3 ) . On reviewing the illustrations of the partial correlations between GM and dominance in each ROI , we noted that it might be argued that the animal with the lowest dominance score was an outlier . Although this animal's dominance score was within two standard deviations of the mean , we nevertheless checked whether the relationship between dominance and GM in each ROI still held after excluding this individual . We found that this was indeed the case , with the exception of the right CAUD ROI , where the correlation remained only marginally significant ( p = 0 . 065 ) . In order to further corroborate the link between GM in the ROIs , we collected a second set of dominance scores and carried out a second set of MRI scans of the animals . We turn to the results of this follow-up investigation next . After an interval of 4 to 5 months we were able to collect a second structural scan as well as a second independent measure of dominance for a homogeneous subgroup of 15 monkeys drawn from the original group of 25 . We focused on male macaques because nearly all the macaques in the initial investigation had been male macaques and living in groups of four or five individuals ( see Table S3 ) , but otherwise we attempted to include as many of the original animals as possible . Because the animals were assigned to other neuroscientific experiments , it was only possible to reinvestigate 15 monkeys at this second time point . This second measure of dominance confirmed that , despite some changes in group membership ( two of the monkeys previously housed in a group of four were now housed in a group of two ) , social hierarchies were relatively stable across the time spanned by the two assessment periods; there was a correlation between the social statuses assigned to the 15 monkeys measured on the two different occasions ( r = 0 . 681 , p = 0 . 005 ) . We therefore examined whether the same relationship between brain structure and dominance could be detected in this new data set . Instead of running whole brain analyses in what was now a smaller group of animals , we focused on the six bilateral ROIs identified from the first experiment . Twelve 166 . 375 mm3 ( equivalent to 11 voxels3 at a resolution of 0 . 5 mm ) ROI masks were positioned over the coordinates calculated as the centers of gravity of the clusters identified in the previous analyses . Within these ROIs , even after controlling for age and weight , we once again found positive correlations between GM and dominance in AMY , RN , and PH in both left and right hemispheres and negative correlations in CAUD and PPUT in both left and right hemispheres and in right DS . The only effect of the original 12 that was not observed on the second occasion was the negative one between left DS and social status ( Figure 7 and Table S2 ) . The first three analyses examined relationships between social status and brain structure . In the next analysis , we sought to determine whether dominance was associated with differences in functional activity . We looked at activity measured in the resting state and indexed by the blood oxygen level–dependent ( BOLD ) signal measured with fMRI . It has previously been shown that the strength of BOLD coupling between certain cortical regions is correlated with the social network size that an individual animal experiences [15] and so , by analogy , here we measured whether the strength of activity coupling between pairs of regions identified in the first three analyses was correlated with social status . In order to avoid making multiple comparisons of the many possible pairs of areas , we focused our analysis in two ways . First , we again focused on just the left hemisphere—the hemisphere in which we had begun our analysis and in which , on average , effects were perhaps slightly stronger . Second , we examined the correlations in resting state activity in a network of areas with a positive relationship with dominance and a network of areas with a negative relationship to dominance . Therefore , we focused on coupling between the largest area identified as having a positive relationship with dominance ( AMY ) and each of the other two areas that also had a positive relationship with dominance ( PH and RN ) and then on the largest area identified as having a negative relationship with dominance ( PPUT ) and the other two areas that also had a negative relationship with dominance ( DS and CAUD ) . Note , however , that we are not testing alternative hypotheses about the coupling between just particular pairs of areas , rather than others , being related to dominance . We are testing the more general hypothesis that coupling within this network of areas is related to dominance . If such a relationship exists , then we might observe evidence for it in the coupling strengths between more than one pair of areas ( i . e . , that both interregional AMY–PH and AMY–RN coupling correlate with dominance ) . To carry out the analysis , we first extracted the raw BOLD time series for every 3 . 375 mm3 ROI mask registered individually in each of the 25 animals . We did this after controlling for fluctuations in BOLD signal across the whole brain GM , white matter , and cerebral spinal fluid . Next , for each animal , the partial correlation coefficient between the resulting BOLD time series in each pair of areas ( AMY and RN , AMY and PH , PPUT and CAUD , PPUT and DS ) was calculated after controlling for all other ROI time series in both hemispheres ( the 10 other areas identified in Figures 1–7—in other words , after controlling for the BOLD time series in the other left hemisphere areas and all the right hemisphere areas ) . This first stage of the analysis establishes the relationship between the activity levels in each pair of areas , after controlling for the effects of other areas , in each individual animal . The next stage of the analysis is then to test whether variations in the strength of these interareal coupling relationships across individuals were related to dominance . In order to examine how variations in the strength of interareal coupling across individuals are related to dominance , the next analysis was conducted at the “group level”—on data from all individuals . At the group level , the resulting partial correlation values were Fisher-transformed and entered into a correlation with the residual variance of individual social status values after controlling for age , weight , and sex . This analysis indexes interareal BOLD coupling between areas in individuals and the individuals' dominance statuses . Significant negative relationships were found between dominance and the activity coupling between left AMY and PH ( r = −0 . 423 , p = 0 . 035; Figure 8A ) , the activity coupling between left AMY and left RN ( r = −0 . 477 , p = 0 . 016; Figure 8B ) , and the activity coupling between left PPUT and CAUD ( r = −0 . 466 , p = 0 . 019; Figure 8C ) . The relationship between dominance and PPUT–DS activity coupling , however , was not significant ( r = −0 . 039 , p = 0 . 853; Figure 8D ) . Statistically , under the null hypothesis that there is no real relationship of BOLD coupling between each pair of areas and dominance at p>0 . 05 , the chance of our finding evidence of coupling being correlated with dominance in three of the pairs of areas is actually p<0 . 0025 . In general , a subordinate social status was associated with positive coupling between activity levels in pairs of the areas , but as social status rose , there was more likely to be negative coupling between areas . We are unable yet to explain the directions of the relationships between coupling strength and social status; however , we note that this is generally the case in human neuroimaging experiments too . Although a negative coupling between BOLD signals might indicate that one area is exerting an influence , via inhibitory interneurons , on the other area , what is important is that there is a relationship between a behavioral or cognitive variable and BOLD coupling as opposed to the specific sign of the coupling . For example , in one of the brain systems in which activity coupling changes have been most extensively investigated , the premotor–motor system , it is known that coupling between two areas changes between negative and positive within a matter of milliseconds as an individual transitions from being at rest to engaging in a behavior [18]–[24] . Whether the same is true for the subcortical brain regions we investigated here can only be determined in further experiments with awake behaving animals . The BOLD coupling relationships are relatively strong . This is illustrated by the fact that several subdominant individual animals ( animals in which dominance scores were less than the median score of 31 . 25 ) had activity coupling that was significantly positive at the individual time series level ( p<0 . 01; blue crosses in Figure 8 ) , whereas several dominant animals ( animals in which dominance scores exceeded the median score of 31 . 25 ) had activity coupling that was significantly negative at the individual time series level ( p<0 . 01; red crosses in Figure 8 ) . Chi-squared tests confirmed the existence of a significant relationship between the presence of a positive coupling pattern and subdominant status and a negative coupling pattern and dominant status for the AMY–PH and AMY–RN pairs ( p = 0 . 041 and p = 0 . 050 , respectively ) . We have previously reported that GM in the mSTS and rostral and dorsal PFC correlates with the sizes of macaques' social networks [15] . Animals experienced extensive contact with social networks of different sizes ( of between one and seven individuals ) in which they lived for most of each day . The group sizes were artificially determined; they were set by the needs of various neuroscientific experiments that would be carried out . Such group sizes are smaller than the group sizes that occur in the wild , but nevertheless they are larger than the pairwise interactions typically studied in neuroscientific investigations of social behavior in macaques [25]–[31] . In addition , an attractive feature of such group sizes is that it ensures all animals within a given group come into proximity with one another on a daily basis . More GM was found in mSTS and rostral and dorsal PFC when animals experienced larger social networks . The next question , therefore , is whether the six subcortical areas ( Figures 1–6 ) identified in the present analysis of social status also have any relationship with social network size . The two factors , social network size and social status , should not be correlated with one another , and this was the case in the present sample ( Pearson's r = −0 . 31 , p = 0 . 126 , Spearman's r = −0 . 24 , p = 0 . 256 ) . The lack of correlation between the two factors means that it is possible to identify variance in GM that is related to either social network size or dominance , or both . The most stringent and sensitive test for any impact of social network size on the brain areas reported in Figures 1–7 is to examine the largest number of animals for which data are available . Because we now have MRI and social network size measurements for 36 animals , we used this large group when testing whether social network size was associated with GM in the six subcortical ROIs . Note , however , that because we had not obtained dominance status measures from all of these animals , we had only been able to analyze data from 25 animals in our investigation of dominance . Despite the sensitivity of a social network size test involving 36 individuals and an ROI-based approach , no significant correlation with social network size was found even after controlling for age , weight , sex , and number of scans [left ROIs , AMY ( r = −0 . 015 , p = 0 . 932 ) , CAUD ( r = −0 . 021 , p = 0 . 905 ) , DS ( r = 0 . 003 , p = 0 . 987 ) , PH ( r = −0 . 100 , p = 0 . 983 ) , PPUT ( r = −0 . 004 , p = 0 . 983 ) , and RN ( r = 0 . 001 , p = 0 . 997 ) ; right ROIs , AMY ( r = 0 . 103 , p = 0 . 548 ) , CAUD ( r = 0 . 019 , p = 0 . 911 ) , DS ( r = −0 . 099 , p = 0 . 567 ) , PH ( r = −0 . 072 , p = 0 . 675 ) , PPUT ( r = −0 . 023 , p = 0 . 896 ) , and RN ( r = −0 . 026 , p = 0 . 880 ) ; Figure 9] . Further direct comparisons confirmed no differences between sexes . This suggests that individual variation in dominance status in the six subcortical regions we have identified in the present report is specific to this aspect of social behavior and unrelated to other aspects of social behavior associated with experience of social networks of different sizes . This was confirmed by showing that all of the relationships between social dominance and GM in these six regions remained significant even when social network size was partialled out from the residual GM effects ( all r<−0 . 525 or >0 . 573 and all p<0 . 01 ) . Moreover , the resting state fMRI coupling analyses that reported a link between BOLD coupling and dominance in Figure 8 remained significant even after the effect of social network size was similarly partialled out ( all r<−0 . 385 , all p<0 . 05 ) . Neural networks associated with effects of social network size and social status did , however , overlap at two points in the cortex that we have previously linked to social network size—the mSTS and rostral and dorsal PFC [15] . ROI examination based on areas identified in our previous study revealed the effects of both social status and social network size overlapped within voxels in both left and right mSTS ( p<0 . 05 corrected for multiple comparisons; cluster volumes , 3 . 875 mm3 and 1 . 375 mm3 right and left , respectively; Figure 10A ) ; even after taking into account age , weight , and sex , increased mSTS size correlated with higher social rank . In the rostral and dorsal PFC , effects of social network size and dominance were found in adjacent voxels in close proximity in the anterior part of the principal sulcus . When we tested for overlap of social network size and dominance in a small ROI between these voxels , we again found positive results ( p<0 . 05 corrected for multiple comparisons; cluster volume , 1 . 75 mm3; Figure 10B ) . It has been suggested that some hormone levels correlate with dominance in monkeys , but the relationship is complex and influenced by numerous factors and perhaps is only clear when very large group sizes are investigated [32] , [33] . We measured two hormone-related metabolites in 13 of the male macaques participating in the second study of dominance ( see Table S3 ) . We assessed fecal levels of a metabolite of cortisol , associated with stress , by measuring the 3α , 11ß-dihydroxy structure cortisol metabolite ( 3α , 11ß-dihydroxy-CM ) , and we assessed fecal androgen metabolite levels by measuring epiandrosterone , which reflects testicular function . Naturally , a logical step would be to test correlations between individual hormone levels and differences in structure or functional couples; however , statistical power in our sample would be too low to infer meaningful relationships . We were unable to find a relationship between dominance and cortisol metabolite regardless of whether or not effects of social network size , age , and weight were partialled out . We did , however , find evidence for a significant relationship between epiandrosterone and dominance after partialling out effects of age , weight , and social network size ( r = −0 . 703 , p = 0 . 023 ) . This pattern of results suggests that stress , at least as indexed by cortisol metabolite levels , is unlikely to mediate the relationship between the brain areas in Figures 1–8 and social status .
We identified two types of social-status–related brain regions . The evidence is particularly clear regarding the association between these areas and dominance in male macaques; all but three of the macaques in the first sample investigated were males , and all the macaques studied in the second sample were males . The first type ( Figures 1–6 ) , which have been identified , to our knowledge , for the first time in the present study comprised a network centered on ( 1 ) the amygdala ( AMY ) and closely interconnected structures including ( 2 ) posterior hypothalamus ( PH ) , ( 3 ) brainstem regions including the raphe nucleus ( RN ) and adjacent reticular formation areas such as the gigantocellular reticular nucleus . We also identified regions of the basal ganglia— ( 4 ) the posterior putamen ( PPUT ) , ( 5 ) caudate tail ( CAUD ) and ( 6 ) dorsal striatum/lateral septum ( DS ) . It is composed of two parts in which GM was either positively ( AMY , RN , PH ) or negatively ( PPUT , CAUD , DS ) correlated with social status . In each case , the relationship with social status was a simple , direct , and strong one and spatially extensive , bilateral , and found in a series of analyses of both GM and BOLD coupling ( Figures 1–8 ) . Relationships between GM and activity coupling and social status in these subcortical areas were observed , but there was no evidence of relationship with other variables such as social network size . The second network involved cortical regions , such as mSTS and rostral PFC , where GM covaried both with social status and with social network size . We discuss this second network at the end of the Discussion section . It is perhaps worth drawing attention to the fact that an assumption behind our analysis is that there is something about the experience of being subordinate ( or conversely dominant ) in a small group that is shared with the experience of being subordinate ( or conversely dominant ) in a larger group even if all aspects of the experience are not identical . By including a factor of dominance as well as a factor of social group size in our analyses , we identify variance in GM and brain activity that is related to the experience of being subdominant or dominant independent of the impact of group size . As explained in the Introduction , we focused only on brain areas that exhibited a consistent relationship with social status in a series of four distinct tests . A relationship between GM in the six subcortical structures was found in both left and right hemispheres . In a further test , when structural MRI and social status measurements were repeated after a 4- to 5-month interval , we again observed similar relationships between GM in these six regions and social status . The only exception was that although the social status effect in DS was found once again in the right hemisphere , it was not found again in the left hemisphere . Furthermore , an additional test showed that the strength of coupling between fMRI-measured activity in different parts of the subcortical network changed as a function of social status . Whether neural activity in these brain regions determines or is determined by dominance is still to be ascertained . In theory , to address this question , animals could be repeatedly assigned and reassigned from one social group to another , and an attempt could be made to carry out a longitudinal analysis of dominance effects . Although such a manipulation is theoretically possible , it would be disruptive to the animals' welfare . In our colony , in line with national guidelines , emphasis is placed on the welfare benefits of stable group housing . Another potentially interesting approach is to test whether incidental changes in dominance that occur spontaneously can be ascribed to prior neural changes . For such an approach to work , however , it is necessary for dominance changes over time to be sufficiently substantial that successive dominance measures are uncorrelated with one another . If such a change occurs , then it would be possible to test if neural measures are more predictive of later dominance than current dominance . However , sufficiently large incidental changes in dominance did not occur during our study period; dominance scores at the two time periods we studied were highly correlated ( r = 0 . 681 , p = 0 . 005 ) . Such an approach might also require more frequent neural measurements and dominance measurements to be taken so that putative predictive neural changes were not missed . It has been suggested that humans and monkeys assign values to themselves , “self-values , ” just as they assign values to environmental stimuli [34] . Social rank is likely to be an important determinant of such self-values . Activity in some of the regions we identified , such as parts of the striatum , is known to encode many parameters that determine the values of choices [35] , and our results suggest the same regions may also encode longer term valuation signals reflecting each individual's status . Recently neurons have been reported in the caudate that track a monkey's own social status during an interactive food-grab game with a competitor . These cells showed decreased activity when an individual was in a submissive state and the competitor was performing successfully and was actively taking most food items in the task [27] . It is also now clear that caudate cells encode not just the actions that an individual macaque makes but the actions made by other macaques present [26] , [36] . The amygdala is also known to be important for tracking some aspects of reward value [37] and lesions to the amygdala affect socioemotional behaviors such as defense and approach tendencies [38] . The prevalence of such behaviors covaries with social status . Amygdala activity in humans has been linked to the tracking of social hierarchies during an investment game [9] . The degree to which such brief games provide insights into dominance hierarchies has been questioned , but the present results , which included particularly extensive regions of amygdala GM associated with social status , confirm the importance of the amygdala as a neural correlate of dominance . Serotonin levels have been related to social status . Raleigh and colleagues [39] examined the consequences of removing the dominant individual from groups of vervet monkeys when serotonin levels were either increased or decreased in one of the remaining group members . Animals in which serotonin levels had been increased were more likely to accede to the dominant position than animals in which serotonin levels had been decreased . Although we did not measure serotonin directly in the current study , the brainstem regions we identified in the present study have been associated with serotonin; in the rodent , not only is the raphe nucleus a source of serotonin , but serotonergic neurons are found in other areas such as the gigantocellular raphe nucleus [40] . Such serotonergic neurons may influence spinal circuits for coordinating emotionally related motor behaviors [40] , but they may also influence other areas such as the amygdala . Allelic differences in serotonin transporter [5-hydroxytryptamine transporter ( 5-HTT ) ] are associated with some of the same socioemotional behaviors that have been linked to the amygdala [41] , and social reward in rodents has been shown to be related to the interaction of serotonin with oxytocin in the ventral striatum [42] . Whether such interactions also occur in primates is unknown , although there is evidence that social reward is also related to oxytocin levels in macaques [30] . Such brainstem regions are not often reported in human neuroimaging experiments . The locations of effects were identified with reference to monkey brain atlases [43] , [44] . Methodologically , it may be important to note that this region was consistently within our field of view and that our subjects have smaller brains than the humans typically studied in neuroimaging investigations . Second , there is very little head movement in our subjects because they were anaesthetized and held in a stereotaxic frame . Third , we note that because respiration , which disproportionately affects brainstem regions , was artificially maintained at a fixed rate in our anaesethetized subjects , respiratory artefacts could be , and were , removed with 0 . 1 Hz low-pass filtering . Not only did the series of analyses confirm the relationship between the six regions and social status , but it was also noticeable that there was not similarly strong or consistent evidence for GM correlations with social status in other brain areas . Only one additional region deserves to be mentioned—the hippocampus and immediately adjacent cortex . We found evidence of a reasonably extensive region of hippocampus in which GM was significantly positively correlated with higher social status in our initial analysis of the left hemisphere , which survived small volume correction for multiple comparisons in the medial temporal ROI . We were able to find evidence of a similar relationship in the right hemisphere . However , we were not able to find evidence for the relationship in our third analysis , which focused on a smaller group of exclusively male subjects at a later date . This region may be especially deserving of attention in future investigations of the neural correlates of dominance . Although neonatal lesions of the hippocampus do not appear to affect social status in macaques [45] , the region is smaller in human individuals that have suffered stressful events particularly when they occurred in childhood [46] . Stress has been related to hippocampal degeneration [47] , but the relationship between stress and social status is a complex one that may be related to the stability of the social group [48] . There is also evidence that stress decreases as social status increases but that being at the very top of a hierarchy is stressful [33] . Differences in the individuals sampled in the second test or undetected variation in group stability might therefore account for changes in the relationship between hippocampus and dominance in our two measurement periods . However , the relationship between stress and social status was not strong in the present sample ( Figures 1–8 ) ; metabolites of the stress-related hormone cortisol were not correlated with social status in the current study . Another social variable , social network size , has previously been shown to be related to brain structure and function in macaques [15] , [49] . However , GM in all six of these subcortical regions bore no relationship with the social network size in which animals lived ( Figure 9 ) . We were , however , able to identify a second set of regions , the mSTS and the dorsal and rostral PFC , in which GM was related to both social status and social network size ( Figure 10 ) . A complex set of factors determine an individual monkey's social status [50] . Social status in male macaques is not simply the consequence of successful engagement in agonistic behavior but a consequence of success in forming social bonds that promote coalitions between individuals [2] . We suggest that the second set of regions—mSTS and rostral PFC—in which GM was related to both social status and social network size may mediate the way in which dominance is dependent on social bond formation , which is in turn dependent on social cognition . The interactions that mSTS and rostral PFC have with other brain areas while macaques are at rest resemble the interregional interactions of the human temporal parietal junction ( TPJ ) and rostral medial frontal cortex brain areas , suggesting some relationships between these regions of the macaque and human brain [51]–[54] . In humans , TPJ and rostral medial frontal cortex are associated with the making of inferences about other individuals' actions and intentions [55] , [56] and the use of memories of social networks [57] . The PFC region identified in the present investigation of macaques included parts of the principal sulcus just anterior to where neurons have been recorded that are active during the performance of competitive games [25] , [58] , [59] . Unlike in some other cortical regions , these neurons' activity encoded both choices that the monkey and the competitor made and activity depended on whether the monkey was engaged in a genuinely social situation , playing against another monkey , or against an inanimate computer . Being able to track another individual's behavior as well as one's own would obviously be an advantage in a social setting , and this may be why these areas increase as an individual experiences larger social network sizes; as an individual's social network expands , so too does the number of individuals , and combinations and alliances of individuals , whose behavior must be followed in relation to one's own . A better ability to track others' actions in relation to one's own may , however , also assist an individual in becoming more dominant . There is some evidence that GM of the macaque amygdala is correlated with an individual's social network size [15] . The relatively restricted region in which such effects have been found was in a more dorsal part of the amygdala than that linked with social status in the current study . However , as explained above , there was no evidence that the amygdala region identified in the current study had any association with social network size ( Figure 9 ) . The amygdala is composed of many anatomically dissociable nuclei , each with distinct connectivity , and so it is entirely possible that potentially neighboring nuclei have distinct functions related to different aspects of social life . In summary , in a series of analyses we have identified brain areas with a consistent relationship with two aspects of dominance . The fact that the association was much stronger in these brain areas than in other brain areas underlines the importance of particular neural processes and argues against all neural processes being equally predictive of dominance . Nevertheless there are a number of other factors that are likely to influence dominance that we were not able to examine in this study . For example , personality types varying in extraversion have been identified in female baboons and have been related to position in the social hierarchy [60] . In humans social hierarchies govern life experiences . Individual social status is correlated with both general and mental health [61] . It is possible that the subcortical areas identified in this study mediate some of these effects . These areas appear to have a relatively simple and direct relationship with social status . By contrast , other cortical regions , mSTS and rostral and dorsal PFC , are associated not just with social status but with other social cognitive processes that are taxed as social network size increases but which are also prerequisites for success in competitive social interactions .
MRI scans of 25 ( 3 females ) rhesus macaques were used in a DBM analysis of the effect of social status on GM . Data from individuals were used if at least two isotropic 0 . 5 mm resolution scans were available . Animals were drawn from social groups comprised of five , four , three , and two individuals and five , twelve , one , and seven animals lived in groups of each of these sizes ( see Table S3 ) . The same animals were subsequently also used in a DBM analysis of the effect of social network size on GM , but additional data from other animals were added to this analysis so that the total data set for this second analysis comprised 36 macaques ( 10 females; see Table S4 ) . The additional animals in this second analysis were ones that could not be included in the dominance status analysis because their dominance status had not been determined . In addition , animals in the second analysis were sometimes drawn from large social groups ( groups containing six and seven individuals ) that could not be effectively counterbalanced within the dominance status analysis , but of course such larger social group sizes are essential for parametric analysis of social network size . The relative social status indices used in the first , second , and fourth analyses shown in Figures 1–8 and 10 were adapted from Zumpe and Michael [16] determined by one investigator ( J . S . ) during a series of 5-minute observations ( 11 or 12 sessions ) . Each observation period was preceded by 5 minutes of habituation to the presence of the investigator . The directions of agonistic behaviors ( aggressive or submissive ) were recorded . Each individual exhibited at least seven single agonistic behaviors during the allotted time period . Behaviors recorded included chasing , escaping , aggressive , and nonspecific social behaviors ( for example , resting together ) . The percentage of dominant interactions out of the total social interactions was calculated to determine cardinal dominance indices . Grooming and mounting are thought to have no necessary relationships with dominance [62] ( p100 ) ; therefore , these behaviors were classified as nonspecific social behaviors . Both structural MRI and resting-state fMRI data were available for all of 25 animals from this first period of data collection . For 15 monkeys from the original 25 , we were able to collect , after a 4- to 5-month interval , a second structural scan ( again composed of at least two isotropic 0 . 5 mm resolution scans as discussed below; see Table S3 ) as well as a second independent set of measures of dominance ( 7 to 10 observation sessions ) . Measurements were made in the same way as those carried out previously in the first assessment period . This smaller group of animals were all male and came from similar sized social groups . At the time of the first measurement , all animals were living in groups of five or four individuals ( 5 and 10 animals , respectively ) . At the time point of the second measurement , 13 of the animals were still living in the same sized social group . Two animals had moved from a group of four to a pair . Although dominance status again appeared stable within the second measurement period , there were some differences between the dominance statuses of individuals recorded at the first and second time periods . Fecal samples were collected from a subset of the male animals included in the second social status analysis ( 13/15 ) . Animals were included when three fecal samples were available ( see Table S3 ) . We measured two hormone related metabolites: ( 1 ) fecal cortisol metabolite levels [we measured levels of the 3α , 11ß-dihydroxy structure cortisol metabolite ( 3α , 11ß-dihydroxy-CM ) ] and ( 2 ) fecal androgen metabolite levels ( we also measured epiandrosterone , which reflects testicular function ) . The samples were analyzed at the German Primate Centre , Leibniz Institute for Primate Research , Goettingen . Analyses were carried out using parametric bivariate analysis in SPSS . Protocols for animal care , MRI , and anesthesia were carried out under authority of personal and project licenses in accordance with the UK Animals ( Scientific Procedures ) Act ( 1986 ) using similar procedures to those that we have previously described [15] , [63] . During scanning , under veterinary advice , animals were kept under minimum anaesthetic using Isoflurane . A four-channel phased-array coil was used ( Windmiller Kolster Scientific , Fresno , CA ) . Structural scans were acquired using a T1-weighted MP-RAGE sequence ( no slice gap , 0 . 5×0 . 5×0 . 5 mm , TR = 2 , 500 ms , TE = 4 . 01 ms , 128 slices ) . Whole-brain BOLD fMRI data were collected for 53 min , 26 s from each animal , using the following parameters: 36 axial slices , in-plane resolution 2×2 mm , slice thickness 2 mm , no slice gap , TR = 2 , 000 ms , TE = 19 ms , 1 , 600 volumes . Only structural MRI scans were available from the second data collection period . Structural MRI data were submitted to a DBM analysis using the Oxford Centre for Functional Magnetic Resonance Imaging ( FMRIB ) Software Library ( FSL ) tools FNIRT and Randomise [11] , [64] . The logic of the approach is that if a group of brain images can be warped to an identical image , then volumetric changes involved in that warping process give measures of the local differences in brain structure between individuals . Related analyses have previously been described [15] . All the brains were first aligned to the MNI rhesus macaque atlas template [65] , [66] using the affine registration tool FLIRT [67] , [68] , followed by nonlinear registration using FNIRT [69] , [70] , which uses a b-spline representation of the registration warp field [71] . The resulting images were averaged to create a study-specific template , to which the native GM images were then nonlinearly reregistered . The determinant of the Jacobian of the warp field used on registered partial volumes to correct for local expansion or contraction was extracted—the Jacobian is a matrix of the directional stretches required to register one image to another , and the determinant of this matrix gives a scalar value for the volumetric change implied . The Jacobian values were then used as the dependent variable in the statistical analyses of the effects of social status . The GLM analysis included factors of demeaned social status , age , weight , sex , and the number of structural scans from which each individual's mean structural MRI scan was derived and it was implemented using permutation-based nonparametric testing in the Randomise procedure . We examined both positive and negative contrasts to identify GM regions that were larger in more dominant animals as well as GM structures larger in subordinate animals . We examine the relationship between dominance and GM , after controlling for age , weight , sex , and number of structural scans included in the DBM [15] , in a 2 , 752 . 5 mm3 ( 22 , 020 voxels ) ROI ( ROI mask depicted in Figure 1 in translucent pink ) centered over bilateral medial temporal lobe so as to include amygdala . Statistics produced from the FSL Randomise procedure were small volume corrected for multiple comparisons using the threshold free cluster enhancement approach at p<0 . 05 [72] . Next we created a 2 , 574 . 5 mm3 ( 20 , 596 voxels ) bilateral ROI ( ROI mask depicted in Figure 2 in translucent pink ) in the brainstem between the medulla and the midbrain so as to include the location of the serotonergic nuclei . Using the same approach , we performed the FSL Randomise procedure and corrected for small volume multiple comparisons with threshold free cluster enhancement at p<0 . 05 . In another set of analyses we looked throughout all subcortical regions in the left hemisphere for areas in which effect significance was p<0 . 001 and extended over 10 voxels ( corresponding to 1 . 25 mm3 ) . The results of this analysis are shown in Figures 3 and 4 . For illustrative purposes we show the relationships between dominance and the mean Jacobian value extracted from 3 . 375 mm3 mask ROIs placed at the centers of gravity of the regions identified as having a significant relationship with dominance ( at p<0 . 005 ) . The Matlab Regstats function was used to calculate the residual DBM effect size and dominance after controlling for confounding effects of age , weight , sex , and number of structural scans that had contributed to the average MRI scan used for each individual . We carried out the same analysis in the right hemisphere , again seeking subcortical regions in which effect significance was p<0 . 001 and extended over 10 voxels ( corresponding to 1 . 25 mm3 ) . The results of this analysis are shown in Figures 5 and 6 . In examining the bilaterality of our effects , we adopt an approach advocated by the originators of MRI voxel-based GM analyses who emphasized that taking into account the spatial extent , across adjacent MRI voxels , of any statistical effect is not necessarily appropriate for GM analyses [11] . The alternative test of robustness involves examining whether effects are bilaterally symmetrical [12] . The premise rests on the assumption that if a statistical effect noted had a chance of occurrence of p<0 . 001 in one brain area under the null hypothesis , then it has the chance of occurring in the same area in both hemispheres with the square of this probability ( i . e . , p<0 . 00001 ) [12] , [14] . For 15 monkeys from the original 25 , we were able to collect a second structural scan as well as a second independent set of measures of dominance . We therefore conducted the same DBM analyses for these 15 animals in both hemispheres . Instead of running whole brain analyses , we now focused on the 12 ROIs ( six in each hemisphere ) identified in the analysis of data from the first time period . These were AMY ( left hemisphere , −10 . 62 , −1 . 47 , −9 . 85; right hemisphere , 11 . 21 , 0 . 35 , −9 . 39 ) , PH ( left hemisphere , −1 . 43 , −10 . 02 , −5 . 83; right hemisphere , 2 . 06 , −10 . 08 , −5 . 49 ) , RN ( left hemisphere , −2 . 763 , −22 . 65 , −10 . 80; right hemisphere , 4 . 79 , −24 . 46 , −12 . 15 ) , PPUT ( left hemisphere , −13 . 36 , −9 . 87 , 1 . 60; right hemisphere , 13 . 98 , −8 . 82 , 1 . 06 ) , DS ( left hemisphere , −1 . 99 , 2 . 67 , 6 . 40; right hemisphere , 2 . 31 , 4 . 27 , 5 . 72 ) , CAUD ( left hemisphere , −7 . 19 , −9 . 03 , 9 . 20; right hemisphere , 7 . 08 , −7 . 39 , 9 . 22 ) . Note the coordinates refer to the macaque MNI atlas [65] . Each mask was first registered to F99 space and then individually registered from F99 space to each monkey structural scan . The ROI masks were 166 . 375 mm3 in size . We also restricted our analyses to contrasts that reflect the expected direction of effect—that is , positive correlation for AMY , PH , and RN and negative for CAUD , DS , and PPUT . The results of this analysis are shown in Figure 7 . Again as in Figures 3–6 , for illustrative purposes , we show the relationships between dominance and the mean Jacobian value extracted from 3 . 375 mm3 ROI masks centered over the peak voxel of the significant cluster within the larger volume of interest . We carried out additional analyses to determine whether the regions identified as having a relationship with social status in the first series of analyses were exclusively concerned with social status or whether GM in these regions was also correlated with social network size . To examine whether GM or functional coupling in the regions shown in Figures 1–6 was also significantly correlated with social network size , Jacobian values were extracted from 3 . 375 mm3 ROIs placed on the AMY , PH , RN , PPUT , DS , and CAUD ( the same coordinates were used as in the follow-up investigation of dominance using the data collected at the second time point ) . The residual GM effect size ( after age , weight , sex , and number of scans included was controlled ) was calculated and correlated with social group size with nonparametric bivariate analyses in SPSS . A previous report suggested mSTS and rostral and dorsal prefrontal GM correlates with social network size [15] . We therefore overlaid the two statistical images: one showing GM regions with a significant relationship with dominance and one showing GM regions with a significant relationship with social network size after cluster correction using a small ROI mask ( p<0 . 05 ) . Specifically , we created anatomically corrected cuboids based on coordinates from [15] where GM correlated with both social status and social network size in the left mSTS and PFC ( −25 . 75 , −13 . 75 , −3 . 25 and 7 . 25 , 21 . 25 , 5 . 75 , respectively ) . The PFC cuboid in the current analysis was 49 mm3 , whereas the mSTS was 63 mm3 . We also replicated the mSTS in the opposite hemisphere by flipping the ROI mask into the other hemisphere . As confirmation we performed a conjunction analysis across the two 3D statistical images by first merging the two images and then determining the lowest p value in the overlap cluster . For illustrative purposes , we again show the relationships between dominance and now also for social group size and the mean Jacobian value extracted from 3 . 375 mm3 ROIs placed at the centers of gravity of the clusters identified by this overlap analysis . The residual DBM effect size of social group size is shown ( green ) after controlling for confounding effects of social status , age , weight , sex , and number of structural scans that had contributed to the average MRI scan used for each individual . The residual DBM effect size of social status ( red ) is shown after controlling for confounding effects of social group size , age , weight , sex , and number of structural scans that had contributed to the average MRI scan used for each individual . Prior to fMRI analysis , the following preprocessing was applied [63]: removal of non-brain voxels , discarding of the first six volumes of each fMRI dataset , 0 . 1 Hz low-pass filtering to remove respiratory artifacts , motion correction , spatial smoothing ( Gaussian 3 mm FWHM kernel ) , grand-mean intensity normalization of the entire 4D dataset by a single multiplicative factor , high-pass temporal filtering ( Gaussian-weighted least-squares straight line fitting , with sigma = 50 . 0 s ) . Registration of functional images to the skull-stripped structural MRI scan and to the MNI macaque template [65] , [66] was achieved with nonlinear registration using FLIRT [67] . To establish increases in functional connectivity between brain areas as a function of social status , we conducted partial correlation analyses . A 3 . 375 mm3 mask was drawn over the coordinates identified as the centers of gravity of the 12 areas ( six in each hemisphere ) in which significant DBM effects of social status had been found ( AMY , PH , RN , PPUT , DS , and CAUD ) . This meant that the same coordinates were used both in this analysis and in the follow-up DBM analysis of data collected at a second time point . The masks were then registered to each individual animal's MRI scan and corrected to ensure that they accurately covered the same region in each individual . The individual animal masks were then registered into each individual's fMRI scan space , and the BOLD time series were extracted from each mask in each monkey . We partialled out the confounding influence of the whole brain GM , white matter , and cerebrospinal fluid BOLD time courses by using the FSL general linear model ( GLM ) tool . To avoid multiple comparisons , we focused on just the left hemisphere—the hemisphere in which we had begun our analysis . Second , in order to further focus our analysis , we examined the correlations in resting state activity in a network of areas with a positive relationship with dominance and a network of areas with a negative relationship to dominance . Therefore , we focused on coupling between the largest area identified as having a positive relationship with dominance ( AMY ) and each of the other two areas that also had a positive relationship with dominance ( PH and RN ) and then on the largest area identified as having a negative relationship with dominance ( PPUT ) and the other two areas that also had a negative relationship with dominance ( DS and CAUD ) . The time series for four pairs of left hemisphere masks ( AMY–RN , AMY–PH , PPUT–CAUD , and PPUT–DS ) were then entered into four partial correlation analyses that each controlled for the correlation with the BOLD time series in all 10 other ROIs . So , for example , when examining the partial correlation between left AMY and left RN BOLD times series , we controlled for the correlation with the BOLD time series in left PH , PPUT , CAUD , and DS and right AMY , RN , PH , PPUT , CAUD , and DS . The resulting partial correlation values were then Fisher-transformed and entered into a correlation with individual social status values . This group-level correlation was performed after the variance explained by age , weight , and sex was partialled out using Matlab's Regstats tool . Effectively , at this point we are examining the correlation between each individual's Fisher-transformed value and its social status after controlling for age , weight , and sex . For illustration we plot the residuals of dominance against the residuals of the partial correlations . We also distinguish which animals had significant regional partial correlation coupling at each end of the dominance spectrum . Those animals where ROI×ROI correlation coefficients were significant at p<0 . 01 and whose dominance scores were less than the group median ( 31 . 25 ) are indicated in blue . In contrast , those animals where ROI×ROI correlation coefficients were significant at p<0 . 01 and whose dominance scores were more than the group median are indicated in red . There is a rough clustering of animals along this dimension suggesting that subordinance is associated with slight but significant positive coupling that becomes a more , slight , but significant anticorrelation the more dominant an animal is . Chi-squared tests in SPSS were used to examine this relationship . | Social status is an important feature of group life in many primates . Position in the dominance hierarchy influences access to food and mates and is correlated with both general and mental health . Discovering how the brain is organized with respect to individual social status is an important first step for understanding the neural mechanisms that might drive social status and mediate its consequences . We performed a neuroimaging study in non-human primates and our findings suggest that brain organization reflects at least two aspects of dominance . First , we identified neural circuits in brain regions that appear to have a relatively simple and direct relationship with social status—one circuit in which gray matter volume tended to be greater in socially dominant individuals and another in which gray matter volume was greater in those with a more subordinate social position . We also showed that the degree of connectivity within each circuit was associated with experiences at each end of the social hierarchy . Second , given that social status in male macaques depends not only on successful engagement in agonistic behavior but also on success in forming social bonds that promote coalitions , we explored regions where gray matter relates to both social status and social network size . This second neural circuit may mediate the way in which dominance is dependent on social bond formation , which is in turn dependent on social cognition . | [
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"cognitive"... | 2014 | A Neural Circuit Covarying with Social Hierarchy in Macaques |
Blood vessels form either when dispersed endothelial cells ( the cells lining the inner walls of fully formed blood vessels ) organize into a vessel network ( vasculogenesis ) , or by sprouting or splitting of existing blood vessels ( angiogenesis ) . Although they are closely related biologically , no current model explains both phenomena with a single biophysical mechanism . Most computational models describe sprouting at the level of the blood vessel , ignoring how cell behavior drives branch splitting during sprouting . We present a cell-based , Glazier–Graner–Hogeweg model ( also called Cellular Potts Model ) simulation of the initial patterning before the vascular cords form lumens , based on plausible behaviors of endothelial cells . The endothelial cells secrete a chemoattractant , which attracts other endothelial cells . As in the classic Keller–Segel model , chemotaxis by itself causes cells to aggregate into isolated clusters . However , including experimentally observed VE-cadherin–mediated contact inhibition of chemotaxis in the simulation causes randomly distributed cells to organize into networks and cell aggregates to sprout , reproducing aspects of both de novo and sprouting blood-vessel growth . We discuss two branching instabilities responsible for our results . Cells at the surfaces of cell clusters attempting to migrate to the centers of the clusters produce a buckling instability . In a model variant that eliminates the surface–normal force , a dissipative mechanism drives sprouting , with the secreted chemical acting both as a chemoattractant and as an inhibitor of pseudopod extension . Both mechanisms would also apply if force transmission through the extracellular matrix rather than chemical signaling mediated cell–cell interactions . The branching instabilities responsible for our results , which result from contact inhibition of chemotaxis , are both generic developmental mechanisms and interesting examples of unusual patterning instabilities .
Despite the biomedical importance of angiogenesis and vasculogenesis , existing experiments are sufficiently ambiguous that even the fundamental mechanisms guiding patterning are uncertain . Experiments suggest a central role for chemotaxis in both de novo and sprouting blood-vessel growth [4]–[6] . ECs respond to , and often produce , a wide range of chemoattractants and chemorepellants , including the many isoforms of vascular-endothelial growth factor A ( VEGF-A ) [6] , the chemokine SDF-1 [7] , [8] , which ECs secrete [7] , fibroblast growth factor 2 ( FGF-2 ) , which induces ECs in developing vessels to secrete VEGF [9] , Slit-2 , which can act either as a chemoattractant or a chemorepellant depending on the receptor to which it binds [10] , and the chemorepelling semaphorins [10] . Which of these molecules ( if any ) govern vascular patterning is still unclear . The Torino Group ( e . g . , [11] , [12] ) argued that a VEGF-A was the short-range autocrine chemoattractant that their chemotaxis-based blood-vessel-growth model required , since ECs express receptors for VEGF ( VEGFR-2 ) , chemotax towards sources of VEGF under favorable conditions , and secrete VEGFs . However , experiments suggest that cell-autonomous secretion of VEGF is essential only for vascular maintenance , not for angiogenesis per se: mice genetically-engineered to lack the VEGF gene only in their ECs have normal vascular density and patterning , but impaired vascular homeostasis and EC survival [13] . A plausible , alternative cell-autonomous chemoattractant to guide EC aggregation is the chemokine SDF-1/CXCL12 , which ECs both secrete and respond to [8] . However , based on experiments that suggest that ECs can follow stresses in the ECM ( see , e . g . , [14] for review ) , Manoussaki and Murray [15] , and Namy et al . [16] proposed that mechanical interactions rather than , or in addition to , chemical interactions govern vasculogenesis . Further complicating this picture , Szabo and coworkers [17] showed that non-vascular , glia or muscle cells cultured on rigid , plastic culture dishes in continuously-shaken medium can form linear structures . Such culture conditions should reduce both the formation of chemoattractant gradients or migration along stress lines in the ECM . In the absence of ECM , they hypothesized that cells preferentially move towards elongated structures . Szabo and coworkers [17] proposed two mechanisms for such cell behavior: cells would align to surrounding cells , or they would mechanotactically follow stress fields in the cytoskeleton of neighboring cells . The molecular mechanisms of such cell behavior remains unclear as is the relevance of these results to ECs . Angiogenesis and vasculogenesis also require a number of local , contact-dependent ( juxtracrine ) signals: Tip-cell selection during angiogenic sprouting depends on Delta-notch signaling [3] , while Eph receptor-ephrin ligand binding amplifies ECs' response to SDF-1 [8] . All ECs express vascular-endothelial-cadherin ( VE-cadherin ) , a homophilic , trans-membrane cell-adhesion molecule , which appears to play a crucial role in vascular patterning [18] , [19] . Besides its role in cell-cell adhesion , VE-cadherin has a signaling function that determines how ECs respond to VEGF-A . When ECs bind to other ECs through their VE-cadherin , VEGF-A reduces their motility and proliferation . In the absence of VE-cadherin binding , VEGF-A activates pathways related to actin polymerization and the cell cycle , enhancing cell motility and proliferation in sub-confluent monolayers , and causes preferential extension of pseudopods in directions with higher VEGF-A concentrations [20] . We hypothesize that VE-cadherin-binding acts locally to prevent extension of pseudopods in the direction of cell-cell contacts for all critical chemoattractants , not only to VEGF-A . VE-cadherin −/− double-knock-out mice develop abnormal vascular networks in the yolk sac [18] , with ECs forming isolated vascular islands instead of wild-type polygonal vascular networks . These mice also have defective angiogenic sprouting , suggesting that both vasculogenesis and angiogenesis require VE-cadherin . VE cadherin −/− ECs still form strong adhesive junctions , so loss of VE-cadherin-mediated signaling rather than loss of intercellular adhesion seems to be responsible for the knock-out phenotype [18] . A number of models and simulations replicate features of in vitro vascular patterning and can help partially reconstruct minimal sets of behaviors ECs require to self-organize into polygonal , vascular patterns [11] , [12] , [15]–[17] , [21]–[23] . Because of the experiments we discussed above , and others which have demonstrated that sprouting angiogenesis and vasculogenesis both require chemotaxis ( see , e . g . , [7] , [8] , [24] ) , most models of vasculogenesis assume that intercellular signaling occurs via a diffusible chemoattractant . Using continuum models deriving from the fluid-dynamic Burgers' equation , Preziosi and coworkers ( called the Torino Group in this paper ) showed that simulated ECs secreting a chemoattractant that attracts surrounding ECs , could self-organize into polygonal patterns similar to the patterns in EC cultures and in vivo [11] , [12] , [25] , [26] . However , their work assumed that endothelial cells accelerate in chemical gradients , which is not plausible in the highly viscous , non-inertial environment of the ECM . Microfluidic evidence indicates that mammalian cells ( HL60 ) rapidly reach a flow-dependent , constant velocity [27] in chemoattractant gradients rather than continuously accelerating . We have previously suggested that [22] a linear force-velocity relation is the most appropriate model of ECs' experimental response , with the velocity of ECs proportional to the strength of the gradient of the chemoattractant . However , in simulations of this simple model , isotropic ECs form well-separated rounded clusters instead of networks . We have shown that adding one of a number of mechanisms ( including cell adhesion [21] and cell elongation [22] ) to chemotactic aggregation suffices to produce quasi-polygonal networks . Section “Results” discusses these mechanisms in more detail . In the mechanical models of Manoussaki and Murray [15] , and Namy et al . [16] ECs pull on the elastic ECM and aggregate by haptotactically migrating along the resulting ECM stress lines . Surprisingly , the mathematical form of the chemical and mechanical models is practically identical . Because these mechanical models assume that ECs exert radially-symmetric stresses on the ECM , modeling stress fields and EC haptotaxis or EC secretion and response to a chemoattractant , results in the same cell movement . Since simulations of the two mechanisms are identical , distinguishing between the effects of chemical and mechanical mechanisms will require additional experiments ( such experiments are currently underway in the Glazier laboratory ( Shirinifard , Alileche and Glazier , preprint , 2008 ) ) . A separate set of simulations addresses angiogenesis . Many models of sprouting blood-vessel growth introduce blood-vessel-level phenomenology by hand through high-level rules for branching [28]–[30] . Attempts to derive blood-vessel sprouting and splitting from the underlying behavior of ECs include Levine and coworkers' [31] model of the onset of angiogenic sprouting as a reinforced random walk , where the ECs degrade the ECM , which locally enhances EC motility and produces paths of degraded ECM , and Bauer and Jiang's [32] cell-based model of blood-vessel sprouting along externally generated morphogen gradients , which assumed that branch splitting results from ECM inhomogeneities . Neither model can explain both EC assembly and blood-vessel sprouting . Could the behavior of the individual ECs also explain aspects of blood-vessel sprouting ? Because the same genetic machinery regulates both angiogenesis and vasculogenesis [4] , a common set of mechanisms is plausible . Manoussaki [33] extended her mechanical model of vasculogenesis to describe angiogenesis by adding long-range , chemotactic guidance cues . In her simulations , ECs migrated from an aggregate towards a chemoattractant source and cell-traction-driven migration contracted the sprout into a narrow , vessel-like cord . In this paper we present an alternative chemotaxis-based mechanism that can produce networks both from dispersed ECs and EC clusters without requiring long-range guidance cues . Instead , in our model long-range signals would only steer the self-organized vessels , a more biologically-realistic mechanism . Extending simulations that we have briefly introduced elsewhere [23] , we show that VE-cadherin-mediated contact inhibition of chemotactic pseudopod projections , in combination with secretion of a diffusing , rapidly decaying chemoattractant by ECs , suffices to reproduce aspects of both de novo and sprouting blood-vessel growth . In our simulations ECs: a ) secrete a chemoattractant and b ) preferentially extend pseudopods up gradients of the chemoattractant , unless , c ) contact inhibition locally prevents chemotactic pseudopod extension . Thus , cell-cell binding suppresses the extension of chemotactic pseudopods , while unbound cell surfaces in contact with the ECM continue to extend pseudopods towards sources of chemoattractant [24] . We compare two biologically-plausible scenarios for chemotaxis , one in which ECs actively extend and retract pseudopods along chemoattractant gradients , and one in which the pseudopods' retractions are chemotactically neutral . The second scenario suggests a sprouting mechanism where a secreted autocrine factor acts both as a long-range chemoattractant and a local inhibitor of pseudopod sprouting .
In in vitro cultures of mouse allantois explants , ECs ( fluorescently labeled in red ) organized into polygonal patterns ( Figure 1A–1C ) . When we blocked VE-cadherin receptors with anti-VE-cadherin antibodies , thus preventing VE-cadherin receptors from binding to those on apposing cells , the mouse ECs formed isolated vascular islands ( Figure 1D–1F ) . We hypothesize that anti-VE-cadherin's antibody blockage of VE-cadherin signaling prevents contact inhibition of chemotactic motility , sensitizing the endothelial cells to the chemoattractant at cell–cell interfaces . In our corresponding simulations ( Figure 2A–2C and Video S1 ) , we randomly distributed 1 , 000 ECs , each with an area of ∼200 µm2 over an area of ≈700 µm×700 µm ( 333×333 lattice sites , or pixels , of 2 µm×2 µm each ) , which we positioned inside a larger lattice of 1 , 00 µm×1 , 00 µm to minimize boundary effects . In this cell-based simulation of the Torino Group's continuum model [11] , [12] , without endothelial-cell acceleration in chemoattractant gradients our cells form disconnected , vascular islands rather than a vascular network . We would expect this result , because with the more realistic chemotactic response we employ , the Torino Group's model reduces to the classic Keller-Segel equations [40] of chemotactic aggregation [25] , which , like our simulations , form isolated vascular islands . Apparently , the basic Torino-Group model of chemotactic cell aggregation misses a biological mechanism essential for vasculogenesis . We have previously suggested a number of additional mechanisms , any one of which , together with cell aggregation , suffices to induce vasculogenesis-like patterning . For example , when we gave the ECs the elongated shapes observed in later stages of experiments , neighboring cells aligned with each other , causing cell clusters to elongate and interconnect , creating a vascular network , in a mechanism similar to Szabo's [17] . These vascular networks remodel gradually , with dynamics resembling those of in vitro vascular networks . The causes of cell elongation in experiments are not clear . ECs could elongate either cell-autonomously ( e . g . , by remodeling their cytoskeletons ) , or non-cell-autonomously , by maximizing their contact areas with surrounding cells or by aligning to morphogen gradients in the ECM [22] . Unless we state otherwise , in this paper we neglect cell-autonomous elongation . Even without strong cell-cell adhesion the ECs can form vascular-like structures in simulations of vasculogenesis if the diffusion length of the chemoattractant ( the length L over which the concentration drops to half its value at the EC membrane ) is short enough , because the ECs align with the chemical gradients [23] . This length scale L depends on the diffusion coefficient D and the chemoattractant decay rate ε as [12] . To investigate whether the Torino-Group Model could reproduce sprouting angiogenesis , we started our simulations with rounded clusters of simulated ECs representing a blood vessel's surface after degradation of the ECM , keeping the simulation parameters unchanged from Figure 2 . As in vasculogenesis , cell-elongation sufficed to drive angiogenesis-like sprouting ( see Figure 3A–3C ) , where we used a length constraint , see [22] ) . EC clusters also produced sprouts for strong cell-cell adhesion ( i . e . , for values of J ( c , c ) <10 ) ; Figure 3D–3F ) , via a mechanism similar to the cell-elongation-dependent mechanism for vasculogenesis [22] . Adhesion-independent sprouting occurred only for a narrow range of very small diffusion constants of the chemoattractant , between D<2·10−14 m2 s−1 and D>2·10−14 m2 s− ( see Figure 3G–3I ) . The allowable range of D increased for bigger cells [23] . We also systematically screened for sprouting in the absence of contact-inhibited chemotaxis . We present the results of these screens in the section Sensitivity analysis and in Figure S1 , but we defer an in-depth study of these phenomena to our future work . In this paper , we focus on the role of contact-inhibited chemotaxis in sprouting blood-vessel growth . We hypothesize that VE-cadherin's local inhibition of chemotaxis-induced pseudopod extensions at EC-EC boundaries , may be responsible for ECs' self-organization into vascular-like networks . We modeled contact inhibition of chemotaxis in our simulations by suppressing chemotaxis at cell-cell interfaces . Thus , only interfaces between cells and ECM respond to the chemoattractant . Figure 2D and Video S2 and Video S3 show typical simulations of de novo blood-vessel growth with contact inhibition . The ECs assemble into a structure resembling a capillary plexus: cords of cells enclose lacunae , which grow slowly . Smaller lacunae shrink and disappear , while larger lacunae subdivide via vessel sprouting as , for example , in the quail yolk sac [41] . To investigate the role of contact-inhibited chemotaxis in blood vessel sprouting , we ran a set of simulations with a large cluster of endothelial cells representing a blood vessel's surface after degradation of the ECM , keeping all simulation parameters the same as those in Figure 2D . The surface of the cluster first roughens , with some cells protruding from the surface , then digitates into a structure reminiscent of a primary vascular plexus ( Figure 4A–4C and Video S4 and Video S5 ) , the first type of structure to develop in both de novo and sprouting blood-vessel growth [41] . The sprouting instability requires contact inhibition of chemotaxis . Without it , the clusters remained rounded and compact ( Figure 4D ) . Thus our simulations suggest that a process operating at the level of individual cells—chemotaxis with contact inhibition—may drive in vitro blood-vessel growth both sprouting and de novo . What drives blood vessel sprouting in our model ? At equilibrium , the chemoattractant has a quasi-Gaussian profile across the cluster . It levels off towards the cluster's center , while its inflection point is at the cluster boundary . Chemotaxis produces a continuous , inward , normal force at the cluster boundary , creating a buckling instability ( see , e . g . , [42] ) ; chemotactic forces also compress small initial bumps laterally , producing sprouts . Since contact inhibition of chemotaxis leaves the interior cells insensitive to the chemoattractant , ingressing surface cells easily push them aside . When we omit contact inhibition of motility to mimic anti-VE-cadherin-antibody-treated allantois cultures , the interior cells also feel the inward-directed chemotactic forces and resist displacement ( Figure 4D and Video S6 ) . To explore this idea , we varied the ratio of the chemotactic response at cell–cell interfaces relative to the chemotactic response at cell-ECM interfaces ( Χ ( c , c ) /Χ ( c , M ) ) , where Χ ( c , c ) is the ECs' sensitivity to the chemoattractant at cell-cell interfaces and Χ ( c , M ) the sensitivity at cell-ECM interfaces ( see the section Materials and Methods for details ) . We looked for sprouting in clusters of 128 cells , each of area ∼200 µm2 , placed in a 400 µm×400 µm lattice , keeping all other parameters unchanged from their values in Figure 4 . We defined the clusters' compactness after 10 , 000 Monte Carlo Steps ( the time unit of the simulation , see the section Materials and Methods , with 1 MCS equivalent to about 30 s ) to be C = Acluster/Ahull , the ratio between the cluster's area , Acluster , and the area of its convex hull ( that is the tightest possible “gift wrapping” around the cluster ) , Ahull . The compactness C = 1 for a perfectly circular cluster , whereas C → 0 for highly branched or dispersed clusters of cells . We found a phase transition at ( Χ ( c , c ) /Χ ( c , M ) ) ≈0 . 5 separating sprouting from non-sprouting clusters ( Figure 5 ) , suggesting that the sprouting instability only occurs when the core of the cluster behaves as a fluid: because each cell's volume is nearly conserved ( apart from small fluctuations around its target volume ) , the core cells can only release the pressure the ingressing cells exert on them by moving outwards as sprouts . Our ongoing work characterizes this instability mathematically , proving that the cluster self-organizes into a network structure with fixed cord width ( A . Shirinifard and J . A . Glazier , preprint 2008 ) . To validate our model against published EC tracking experiments [19] , we compared the trajectories of cells in sprouting and non-sprouting clusters . Figure 6A–6D shows the trajectories of ten cells in a sprouting cluster ( with contact-inhibition; Figure 6A–6B ) , and ten cells in a non-sprouting cluster ( without contact-inhibition; Figure 6C–6D ) . In non-sprouting clusters , cells followed random-walk trajectories , while in sprouting clusters , they followed biased random-walk trajectories . To further characterize cell motility , we measured cells' average displacements and velocities over 10 independent simulations of 128 cells each . In sprouting clusters , the cells moved further during a given interval than in non-sprouting clusters . Thus , the cell velocity [19] is larger during sprouting if the interval Δt between subsequent cell positions is sufficiently large ( here we use Δt = 2 . 5 h as in Perryn et al . [19] ) ; for shorter intervals ( e . g . , 30 s ) the cell velocity is highest in non-sprouting clusters ( not shown ) , indicating that ECs in sprouting clusters moved faster , but had a somewhat slower random motility . Our simulations agree with recent experiments tracking ECs in embryonic mouse allantoides [19] that measured the cell-autonomous motility of ECs cells in allantoides relative to the motility of the surrounding mesothelium in which the ECs reside . Administration of anti-VE-cadherin antibodies reduced both cell-autonomous motion and net displacement of ECs . Thus , our simulations suggest that VE-cadherin's role as a contact-dependent inhibitor of cell motility suffices to explain the reduced cell motility observed in anti-VE-cadherin-treated allantoides cultures . Contact-inhibited sprouting occurs for a wide range of parameter values . In most of our simulations we set the EC-EC adhesion equal to the EC-ECM adhesion ( i . e . , J ( c , c ) = 2J ( c , M ) ; the factor of 2 arises because we model the ECM as a single large generalized cell ) , which is equivalent to setting the surface tension of the cluster to zero [35] . Zero surface tension clarifies the role of contact inhibition in sprouting , but real ECs adhere strongly to each other via adherens junctions [18] . In Figure 7 and in Video S7 , S8 , S9 , S10 , S11 , S12 , S13 , S14 , S15 , S16 , S17 , S18 , S19 , S20 , S21 , S22 , we studied the effect of cell-cell adhesion on sprouting in clusters of 128 cells ( 256 cells in the Videos ) . For stronger EC-EC adhesion , equivalent to positive surface tension , J ( c , c ) <2J ( c , M ) , the sprouts are longer and thinner and the network less compact than for zero surface tension . For very weak EC-EC adhesion J ( c , c ) ≫2J ( c , M ) , equivalent to strong negative surface tension , the ECs separate from each other , so contact-inhibition no longer occurs , and the clusters do not sprout . For small negative surface tensions , with values of J ( c , c ) >2J ( c , M ) , chemotaxis overcomes the negative surface tension , so ECs still touch each other and sprouting occurs as for zero surface tension , producing thickened sprouts and elongated clusters . The insets to Figure 7 and Video S20 , S21 , S22 show the results for 50≤J ( c , c ) ≤70 . We also investigated how sprouting depends on the chemotactic strength Χ ( c , M ) ( Figure 8 and Video S23 , S24 , S25 , S26 , S27 S28 , S29 , S30 , S31 , S32 , S33 ) . For Χ ( c , M ) = 500 , most vascular cords are two cells wide ( Video S24 ) , while for For Χ ( c , M ) >500 the cords become thinner and longer , with cords only one cell wide ( Videos S25 , S26 , S27 , S28 , S29 , S30 , S31 , S32 , S33 ) . For higher chemotactic forces , the cells intercalate , moving to the chemical gradients' peak . We have derived the conditions for this folding instability in our ongoing work ( A . Shirinifard and J . A . Glazier , preprint , 2008 ) . Higher chemotactic strengths increase ruffling of the cluster boundary , reducing the cluster's compactness in the absence of contact inhibition ( Figure 8 ) . We assumed that ECs extend or retract pseudopods depending on the difference in chemoattractant concentration between the retracted and extended positions , independent of the absolute chemoattractant concentrations . However , at higher chemoattractant concentrations , most chemoattractant receptors will saturate with chemoattractant and become insensitive to chemoattractant levels . To study the effect of saturated chemotactic response [21] on angiogenic sprouting , we varied the saturation parameter s ( see Eq . 3 in Materials and Methods ) leaving all other parameters unchanged . For s = 0 , the chemotactic response is linear; for s>0 , the response to the chemoattractant gradient vanishes at high concentrations ( see Materials and Methods ) . For small positive s , the clusters sprout normally ( see Figure 9 and Videos S34 , S35 , S36 ) ; however , for large s , the chemotactic response weakens at the chemoattractant levels present at the edge of the cell cluster; thus cells no longer chemotact towards the cluster's interior and the sprouting instability disappears ( Videos S37 , S38 , S39 ) . We could test this prediction experimentally by partially inactivating the ECs' chemoattractant receptors . We observed the same effect when we increased the chemoattractant secretion rate for moderate response saturation ( s = 0 . 05; see Figure S2 , bottom panel ) leading to higher overall chemoattractant concentrations . We could test this situation experimentally by overexpressing the chemoattractant in ECs . Since for unsaturated chemotactic response ( s = 0 ) , multiplying the chemoattractant concentrations is equivalent to multiplying the chemotactic strength ( Χ ( c , M ) ) by the same factor , increasing the secretion rate first thins and lengthens the cords by increasing the chemotactic strength , then eventually prevents sprouting as the chemotactic response saturates . This effect is most apparent for s = 0 . 01 ( Figure S2 , top panel ) . In the Torino Group's continuum model , the separation between the cords increases with the diffusion length L of the chemoattractant , Figure 10 and Videos S40 , S41 , S42 , S43 , S44 , S45 , S46 show sprouting clusters for a range of diffusion lengths . In agreement with the Torino Group's model , longer diffusion lengths produce thicker cords with larger intercord spaces . The clusters do not sprout well when L approaches the EC-cluster diameter . Clusters consisting of 1 , 024 cells sprout for D>3·10−13 m2 s−1 ( L>17 . 3 µm ) , while 128-cell clusters do not ( Figure 10 and Video S47 , S48 , S49 , S50 , S51 , S52 , S53 ) . If the diffusion length is shorter than the ECs' diameter , the clusters dissociate: the ECs perform random walks with long persistence lengths , moving up the chemoattractant gradients they leave behind themselves ( Video S40 and S47 ) . In our simulations , the trailing edges of the ECs retract actively in response to the chemoattractant and exert an inward-normal , compressive force on the EC cluster . To check if sprouting requires this compressive force , we also simulated a situation in which only extending pseudopods at cell-ECM interfaces respond to the chemoattractant , while retraction is chemotactically neutral . Both sprouting-angiogenesis and vasculogenesis occurred , but required higher intrinsic cell motilities ( larger values of the parameter T ) . Figure 11 shows the motilities required under both assumptions . We looked for sprouting after 5000 MCS ( ∼40 h ) in clusters of 128 cells , each of area ≈200 µm2 , placed in a 400 µm×400 µm lattice , with all other parameters the same as in Figure 4 . For T<100 , our original chemotaxis assumptions produced sprouts , while no sprouting occurred if pseudopods responded to the chemoattractant only during extension . For 100<T>400 , both mechanisms produced sprouts . For T>400 , the ECs broke up into small pieces , a well-characterized , non-biological artifact of the GGH [35] . With extension-only chemotaxis , sprouting was slightly slower than for standard , extension-retraction Savill-Hogeweg [36] chemotaxis , as a plot of the time evolution of the clusters' compactness shows ( Figure 12 and Video S54 , S55 , S56 ) . However , at long times ( t>2500 MCS ) the compactness of clusters decreased at identical rates for both methods . These results suggest an additional mechanism for blood-vessel sprouting: at the cluster surface , all pseudopod extensions increase the effective energy slightly , so the chemoattractant inhibits pseudopod extension . A recent experimental study [43] found that autocrine secretion of the sprouting inhibitor TGF-β1 enhances branching in mammary epithelial tubes . Our model suggests a mechanism by which an autocrine , secreted chemical can act both as a chemoattractant and as an inhibitor . The rates of pseudopod extensions and retractions are critical to pattern evolution ( Figure 11 ) . Cells in growing tips see a shallower gradient than do those in valleys between the tips ( see , e . g . , Figure 4B ) , so pseudopod extensions at growing tips are more frequent than in the valleys between tips because they have a lower effective-energy cost . During sprouting , conservation of cell area requires that the cells in the valleys must retract , while those in the tips protrude . In the Savill-Hogeweg algorithm , retraction is energetically favorable , while it is energetically neutral in our pseudopod-extension-only chemotaxis algorithm , making the net change in effective energy positive with a rate depending on the cell motility . The effective-energy change is negative in the Savill-Hogeweg algorithm and thus nearly independent of T ( Figure 13 , where H0 is the initial effective energy ) .
We have shown that a single set of cell behaviors , i . e . , contact-inhibited chemotaxis to an autocrine , secreted chemoattractant can explain aspects of both de novo and sprouting blood-vessel growth . Our results suggest that branching in aggregates of chemotacting ECs could result from two separate effects of the same mechanism . For low cell motilities T , i . e . , a low probability for active , dissipative cellular protrusion , the branching resembles a buckling instability ( see , e . g . , [42] ) , in which the surface cells exert a surface-normal force on the cluster's inner core . For larger cell motilities , the shallower chemoattractant gradients at protrusions make the ECs there more likely to extend outward-directed pseudopods than cells in the valleys between the protrusions . While we have adopted the Torino Group's assumption that ECs chemotax in response to gradients of a diffusible , autocrine , secreted chemoattractant [12] , [25] , our simulation also reproduces continuum models that assume that ECs stress the ECM [15] , which either pulls on the surrounding ECs , provides haptotactic cues for active EC migration [16] , or both [26] . Because these models assume that ECs exert radially-symmetric stresses on the ECM , the underlying mathematical descriptions of the chemotactic and haptotactic mechanisms are equivalent . In both cases , contact inhibition should still operate and the patterning mechanism we have proposed should still apply , with traction or haptotaxis replacing chemotaxis and the mechanical screening length replacing the diffusion length . Our simulation may also apply to the formation of linear structures by non-vascular , glia or muscle cells cultured on rigid , plastic culture dishes in continuously-shaken medium [17] in which cells explore their environment using long filopodia , then move towards their neighbors by pulling themselves along bound filopodia . Thus , the combination of cell aggregation and contact-inhibition that drives patterning in our model , could also occur without chemical gradients and even without ECM . Our simulations also allow us to clarify a number of subtleties concerning the interpretation of our own and others' experiments in which blocking VE-cadherin interfered with normal vascular patterning . In our in vitro experiments , anti-VE-cadherin treatment caused ECs to round , in addition to its hypothesized effect on contact inhibition , so our experiments cannot rule out the possibility that the anti-VE-cadherin treatment inhibited vascular patterning because of its effect on EC shape . A further complication is that anti-VE-cadherin treatment could conceivably reduce the adhesion between ECs . As we noted above , In VE-cadherin −/− knock-out mice , ECs still form strong adhesive junctions [18] , suggesting that VE-cadherin is not required for EC-EC binding . Our simulations show that the contact-inhibition patterning mechanism operates over a wide range of cell-cell adhesions , suggesting that changes in adhesivity are not significant provided that contact-inhibition persists , and independent of cell shape [23] , suggesting that the shape change is not significant . However , we have also shown that strong cell-cell adhesion plus chemotaxis can produce vascular-like patterns in simulations [21] . Fortunately , the three vascular patterning mechanisms ( contact-inhibition , cell-elongation and cell-cell adhesion ) have vastly different kinetics [22] . Thus time-lapse microscopy experiments [19] , [44] quantifying the kinetics of capillary-plexus development ( see , e . g . , [22] ) , will allow us to definitively distinguissh among these three patterning mechanisms . Already , we can say that adhesion-driven patterning is so slow and requires such strong adhesion that it appears incompatible with the available qualitative data from experiments . To further test if VE-cadherin-mediated , contact-dependent signaling to VEGF-R2 [20] , rather than VE-cadherin's function as a cell-adhesion molecule is responsible for the effects of anti-VE-cadherin treatment in mouse yolk sacs , we could experimentally block signal transduction from VE-cadherin to VEGFR-2 , specifically interfering with VE-cadherin's signaling function , while leaving its role as an adhesion molecule intact . A possible target would be CD148 , which phosphorylates VEGFR-2 after VE-cadherin binding [20] , [45] . Embryonic vascularization and angiogenic sprouting are severely deficient in CD148 −/− knock-out mice [45] , further supporting our hypothesis that VE-cadherin's contact-dependent intercellular signaling is crucial to vasculogenesis and angiogenesis . Perryn et al . [19] showed that anti-VE-cadherin treatment reduced sprout extension in murine allantois cultures by 70% , while it reduced cell-autonomous motility along sprout segments by 50% . Based on these results , they postulated that VE-cadherin is required for the motility of ECs along sprouts towards the tip . However , our simulations show that the observed cell slow-down after anti-VE-cadherin administration may be an indirect effect of a reduction of sprouting . Furthermore , our simulations suggest that even substantially reduced cell motility may not prevent patterning , though it does slow it down . In our simulations , branching and pattern formation require only experimentally-observed cell-level mechanisms , instead of the blood-vessel-level phenomenology in some other angiogenesis models [28]–[30] . However , by starting with a cluster of endothelial cells , our simulations ignore many events preceding sprout formation , including the release of plasma proteins by the vessel , the breakdown of the basal lamina , the detachment of the ECs from surrounding ECs and smooth muscle cells , and cell proliferation . They also ignore subsequent processes consolidating outgrowth of the sprout , including tip-cell selection , any long-range chemoattractants and chemorepellants that guide the vessel to its target , the formation of new basal lamina , the sprout's association with stabilizing cells including pericytes , lumen formation within the sprout , and flow-induced remodeling of the developed vasculature . The mechanism for sprouting and network formation we have proposed forms a firm basis for future , more complete models of angiogenesis which include basal lamina and pericytes . We are currently studying the formation of directed sprouts with proliferating ECs in response to additional chemoattractants or chemorepellants and analyzing the role of cell elongation during sprouting . We are also studying the effect of additional , cell-cell contact-dependent signaling mechanisms , including delta-notch tip-cell selection [3] and chemoattractant-response amplifying Eph receptor-ephrin ligand interactions [8] .
The GGH represents biological cells as patches of identical lattice indices on a square or triangular lattice , where each index uniquely identifies , or labels a single biological cell . Connections ( links ) between neighboring lattice sites of unlike index represent bonds between apposing cell membranes , where the bond energy is , assuming that the types and numbers of adhesive cell-surface proteins determine J . A penalty increasing with the cell's deviation from a designated target volume Atarget ( σ ) imposes a volume constraint on the simulated ECs . We define the pattern's effective energy: ( 2 ) where and are neighboring lattice sites ( up to fourth-order neighbors ) , a is the current area of cell σ , Atarget ( σ ) is its target area , λ represents a cell's resistance to compression , and the Kronecker delta is δ ( x , y ) = {1 , x = y; 0 , x≠y . Each lattice site represents an area of 2 µm×2 µm . Since we assume that ECs do not divide or grow during patterning , we set Atarget ( σ ) = 50 lattice sites , corresponding to a cell diameter of about 16 µm , and λ = 25 for all cells . The ECs reside in a very thin layer of extracellular fluid , which is a generalized cell without a volume constraint and with σ = 0 . We assume that the ECs and fluid sit on top of a rigid ECM through which the chemoattractant diffuses , but we do not represent this ECM in the GGH lattice . We also assume that the presence of the fluid does not disturb the chemoattractant distribution in the ECM . Unless we specify otherwise , we use a bond energy J ( c , c ) = 40 between the ECs , and J ( c , M ) = 20 between the ECs and the ECM . For these settings the ECs do not adhere without chemotaxis . We define a special , high cell-border energy J ( c , B ) = 100 to prevent ECs from adhering to the lattice boundaries . We use fixed boundary conditions . To mimic cytoskeletally-driven pseudopod extensions and retractions , we randomly choose a source lattice site , and attempt to copy its index into a randomly-chosen neighboring lattice site . For better isotropy we select the source site from the twenty , first- to fourth-nearest neighbors [46] . During a Monte Carlo Step ( MCS ) we carry out N copy attempts , with N the number of sites in the lattice . We set the experimental time per MCS to 30 s; for this setting the simulated ECs move with nearly their experimental velocity [22] . We calculate how much the effective energy would change if we performed the copy , and accept the attempt with probability , where T defines the intrinsic cell motility . All our simulations , except those in Figures 11–13 , use T = 50 . In experiments , cells respond to chemoattractant gradients by executing a more-or-less-strongly biased random walk up or down the gradient , where , over times short enough to allow us to neglect adaptation , the velocity of the drift depends on the gradient strength and the absolute concentration . We therefore define a set of extensions to the basic GGH model which reproduce these empirical behaviors due to preferential extension and retraction of pseudopods up chemoattractant gradients [24] by including a chemical effective-energy change at each copy attempt [21] , [36] , ( 3 ) where c is the concentration of the chemoattractant , which we assume is present everywhere in a layer of ECM under the ECs , is the target site , the source site , and s regulates the saturation of the chemotactic response . Unless we specify otherwise , we set s = 0 , in which case chemotaxis depends linearly on the chemoattractant gradient only , independent of the chemoattractant concentration . ΔHchemotaxis → 0 for large values of s and , for s≠0 , for high chemical concentrations . The chemotaxis coefficient is μ = Χ ( c , M ) at cell-ECM interfaces and μ = Χ ( c , c ) at cell-cell interfaces respectively . Setting Χ ( c , c ) = 0 Χ ( c , M ) = 500 ensures that chemotactic extensions occur only at cell-ECM interfaces , reflecting VE-cadherin's suppression of pseudopods . Both extending and retracting pseudopods contribute to the chemical effective-energy change . To implement pseudopod-extension-only chemotaxis ( see Figures 11–13 ) , where only extending pseudopods at the cell-ECM interface respond to the chemoattractant , cells experience a chemical effective-energy change only if the source lattice site belongs to an EC , i . e . , ( 4 ) For a more detailed discussion of chemotaxis in the GGH model see [47] . We solve the partial-differential equation for chemoattractant diffusion and degradation ( Eq . 1 ) numerically using a finite-difference scheme on a lattice matching the GGH lattice . We use 15 diffusion steps per MCS , with Δt = 2 s . For these parameters , the chemoattractant diffuses more rapidly than the ECs , enabling us to ignore advection in the medium as the cells push the fluid . Source code and parameters for the simulations in this paper are available online in Protocol S1 from the supporting material , and from http://sourceforge . net/projects/tst . Parameter files for the simulations in this paper are included in Dataset S1 . We dissected allantoides from mouse embryos at embryonic stages 7 . 5–8 . 0 . We washed the explants in fresh , cold ePBS and pipetted them into fibronectin-coated ( 5 mg/ml ) Delta-T culture dishes ( Bioptechs , Butler , PA ) containing high-glucose , phenol-red-free Dulbecco's modified Eagles' medium ( DMEM ) supplemented with 10% fetal bovine serum ( FBS ) , 1% penicillin-streptomycin , and 1% L-glutamine ( GibcoBRL , Grand Island , NY ) . We maintained the allantoic explants using standard culture conditions ( 37°C and 5% CO2/95% air atmosphere ) in a custom-designed culture chamber for 12–24 hours in the presence of an endothelial-specific marker , CD34 monoclonal antibody ( BD PharMingen , San Diego , CA ) directly conjugated to Cy3 ( Amersham Biosciences ) . We fixed the allantoides in 3% paraformaldehyde for 20 minutes at room temperature , followed by an ePBS wash . For VE-cadherin antibody perturbations , we added anti-VE-cadherin monoclonal antibody ( BD PharMingen , San Diego , CA ) at 25 µg/ml to the culture medium . We observed the cultures with a 10× objective ( 0 . 30 N . A . ) on an inverted , automated , wide-field , epifluorescence/differential-interference-contrast ( DIC ) microscope ( Leica DMIRE2 , Leica Microsystems , Germany ) . We recorded images ( 608×512 pixel spatial and 12-bit intensity resolution ) with a cooled Retiga 1300 camera ( QImaging , Burnaby , British Columbia ) in 2×2 binned acquisition mode , using 100–300 ms exposures . Image acquisition and microscope settings used software described in [44] . | A better understanding of the mechanisms by which endothelial cells ( the cells lining the inner walls of blood vessels ) organize into blood vessels is crucial if we need to enhance or suppress blood vessel growth under pathological conditions , including diabetes , wound healing , and tumor growth . During embryonic development , endothelial cells initially self-organize into a network of solid cords via blood vessel growth . The vascular network expands by splitting of existing blood vessels and by sprouting . Using computer simulations , we have captured a small set of biologically plausible cell behaviors that can reproduce the initial self-organization of endothelial cells , the sprouting of existing vessels , and the immediately subsequent remodeling of the resulting networks . In this model , endothelial cells both secrete diffusible chemoattractants and move up gradients of those chemicals by extending and retracting small pseudopods . By itself , this behavior causes simulated cells to accumulate to aggregate into large , round clusters . We propose that endothelial cells stop extending pseudopods along a given section of cell membrane as soon as the membrane touches the membrane of another endothelial cell ( contact inhibition ) . Adding such contact-inhibition to our simulations allows vascular cords to form sprouts under a wide range of conditions . | [
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"physics/... | 2008 | Contact-Inhibited Chemotaxis in De Novo and Sprouting Blood-Vessel Growth |
Formin is one of the two major classes of actin binding proteins ( ABPs ) with nucleation and polymerization activity . However , despite advances in our understanding of its biochemical activity , whether and how formins generate specific architecture of the actin cytoskeleton and function in a physiological context in vivo remain largely obscure . It is also unknown how actin filaments generated by formins interact with other ABPs in the cell . Here , we combine genetic manipulation of formins mammalian diaphanous homolog1 ( mDia1 ) and 3 ( mDia3 ) with superresolution microscopy and single-molecule imaging , and show that the formins mDia1 and mDia3 are dominantly expressed in Sertoli cells of mouse seminiferous tubule and together generate a highly dynamic cortical filamentous actin ( F-actin ) meshwork that is continuous with the contractile actomyosin bundles . Loss of mDia1/3 impaired these F-actin architectures , induced ectopic noncontractile espin1-containing F-actin bundles , and disrupted Sertoli cell–germ cell interaction , resulting in impaired spermatogenesis . These results together demonstrate the previously unsuspected mDia-dependent regulatory mechanism of cortical F-actin that is indispensable for mammalian sperm development and male fertility .
Filamentous actin ( F-actin ) nucleation and polymerization are controlled by actin nucleators , including actin-related protein2/3 ( Arp2/3 ) and formin , in mammalian cells . Previous studies in typical cultured cell lines showed that Arp2/3 generates branched actin filaments , while formin generates straight actin filaments [1] . However , F-actin structure and dynamics regulated by formin in a variety of mammalian cell types and their physiological roles in vivo remain largely unknown . Mammalian diaphanous homolog ( mDia ) proteins , mammalian homologues of Drosophila diaphanous , belong to the formin family of proteins and consist of three isoforms in mammals , namely mDia1 , mDia2 , and mDia3 [2] . To unravel mDia-dependent F-actin structures in the mammalian body and explore their physiological functions in vivo , we generated mice deficient in each isoform and analyzed their phenotypes [3–5] . These studies showed the functional redundancy between mDia1 and mDia3 isoforms and demonstrated that mDia1/3-mediated F-actin is critical for neuroblast migration [5] and neuroepithelium integrity [6] in the developing brain , and mediates presynaptic plasticity of mature neurons in the adult brain [7] . However , the contribution and function of mDia-mediated F-actin in other systems remain an open question . Spermatogenesis is a process by which spermatogonial stem cells give rise to spermatozoa through spermatocytes , round spermatids , and elongated spermatids in seminiferous tubules . Besides these germ cells , the seminiferous tubule contains a somatic constituent of the seminiferous epithelium , the Sertoli cells . Sertoli cells make adhesion with developing germ cells and provide them with structural and functional supports [8] , which are indispensable for normal spermatogenesis . Adhesion between Sertoli cells and round spermatids is mediated by the adherens junction ( AJ ) [9] . In addition , a special form of cell–cell adhesion , the apical ectoplasmic specialization ( ES ) junction , is formed between Sertoli cells and spermatids in association with the elongation of the round spermatid [10 , 11] . In contrast to the AJ , which is a structure associated with contractile actomyosin bundles [12] , the apical ES junction is typified by a layer of densely packed noncontractile F-actin bundles [13] concentrated immediately beneath the Sertoli cell plasma membrane . It is known that these noncontractile F-actin bundles are associated with actin bundling protein espin1 [14] and support elongated spermatid adhesion and orientation through the regulation of the apical ES junction [15 , 16] . Although the structure and function of AJ and ES junctions have been extensively investigated , how F-actin structures associated with these junctions in Sertoli cell are formed , interact with each other , and are maintained during spermatogenesis are largely obscure . F-actin makes several different forms of architectures beneath the cell membrane , which are collectively termed cortical F-actin [17] and are determined by the environment surrounding the cell . For example , in cells cultured in suspension under steady state , F-actin in the cortex makes a highly dense and fine mesh structure with a homogeneous pore size of approximately 30 nm [18] . It was previously shown that the Arp2/3 complex dominantly nucleate these meshlike cortical actin filaments [18 , 19] , although about 10% of the cortical F-actin of these cells was shown to be formin dependent [19] . On the other hand , cortical F-actin structures in adherent cells are more complicated because dynamic remodeling of cortical network results in additional F-actin architectures , such as the contractile stress fibers [20] . Stress fibers are mostly localized at the basal plane of the cell and are more visible than those finely organized filaments , making conventional imaging of cortical F-actin very challenging . Indeed , the structure and dynamics of cortical F-actin of the adherent cell remain largely unexplored to date , and how and which actin nucleators regulate them are unknown . In this study , we show that both mDia1 and mDia3 are dominantly expressed in the Sertoli cells of mouse testes and are indispensable for sperm development and male fertility . Utilizing superresolution microscopy , we resolved the nanoscale F-actin architecture of Sertoli cells attached to the substrate and observed a previously unsuspected F-actin meshwork with a large mesh size of about 100 nm . Live imaging of F-actin has further revealed the highly dynamic nature of this cortical F-actin meshwork of the Sertoli cell . Moreover , genetic and pharmacological experiments have shown that this Sertoli cell cortical F-actin meshwork depends on actin nucleation and polymerization activity of formins , including mDia1/3 , but not Arp2/3 . Intriguingly , these mDia1/3-dependent actin filaments are required for the generation of contractile actomyosin bundles in Sertoli cells . Consequently , loss of mDia1/3 in Sertoli cells results in severe reduction of cortical F-actin meshwork and actomyosin bundles and , instead , unexpectedly causes ectopic formation of espin1-associated noncontractile F-actin bundles in the cell . Finally , we demonstrate that mDia-dependent cortical F-actin meshwork and contractile actomyosin in Sertoli cells are together critical for interaction with germ cells , which is required for their competency to support spermatogenesis .
When breeding mice in our colony , we found that , while mDia1 knockout ( KO ) male mice [3] and mDia3 KO male mice [5] were fully fertile , the mating of mDia1/3 double knockout ( DKO ) male mice [10] yielded no offspring upon mating . The fertilization rate upon in vitro fertilization ( IVF ) of wild-type ( WT ) oocytes with mDia1/3 DKO sperms was also greatly reduced , suggesting abnormality in the sperm ( S1A and S1B Fig ) . Analysis of the epididymis of 8-wk-old male mDia1/3 DKO mice further revealed reduced number , abnormal morphology , and impaired motility of mDia1/3 DKO sperm compared with the control WT mice ( S2A–S2I Fig ) . These results together suggest that the male infertility phenotype of mDia1/3 DKO mice is likely due to impaired sperm development . To investigate how mDia1/3 double deficiency causes sperm abnormalities , we next performed histological analysis on spermatogenesis in the testes of adult WT and mDia1/3 DKO mice . Paraffin sections of testis with Periodic acid-Schiff ( PAS ) staining revealed that , while numerous elongated spermatids aligned at the adluminal compartment of the seminiferous tubule in WT testes , the number of elongated spermatids in mDia1/3 DKO testes is extremely low compared with WT testes ( Fig 1A , red boxes ) . Notably , the heads of mDia1/3 DKO sperm were not properly oriented toward the basal lamina of the seminiferous tubule ( Fig 1A , black arrows in the lower red box ) . In addition , a fraction of mDia1/3 DKO elongated spermatids exhibited ectopic localization in seminiferous tubules , as evidenced by their presence at the proximity of basal lamina ( Fig 1A , black boxes ) . Moreover , we found a significant increase in apoptotic cell number in the mDia1/3 DKO seminiferous tubule by TUNEL staining ( S3A and S3B Fig ) . These results together suggest that mDia1/3 is indispensable for spermatogenesis . We next attempted to figure out whether the mDia1/3 deficiency in germ cells or Sertoli cells is responsible for the above abnormal spermatogenesis phenotype observed in mDia1/3 DKO mice . We first examined the expression of mDia1 and mDia3 in the seminiferous tubule by immunofluorescence staining . We found positive signals for mDia1 and mDia3 in vimentin-positive Sertoli cells [21] in the seminiferous tubule from adult WT mice ( Fig 1B ) . These mDia1 and mDia3 signals were absent in testis sections from mDia1 or mDia3 knockout ( KO ) mice ( S4A and S4B Fig ) , confirming the specificity of these signals . We also examined the expression of mDia3 in the WT seminiferous tubule during the spermatogenic cycle [22] and compared its localization with F-actin ( S5A Fig ) . We found that mDia3 is expressed in Sertoli cells throughout the spermatogenic cycle , though its staining intensity and localization varies in different stages . For example , in stages IV–V , although the majority of mDia3 staining localizes in the cell body , a fraction of mDia3 staining with relatively low intensity ( white arrows ) colocalizes with F-actin bundles associated with apical ES . Similarly , in stages VI–VII , a fraction of mDia3 staining localizes close to F-actin bundles associated with basal ESs ( white arrowheads ) , and the mDia3 staining becomes weak in stages X–XI . Specificity of these mDia3 signals was confirmed as they were mostly absent in testis sections from mDia3 KO mice ( S5B Fig ) . We then examined the functional requirement of mDia1 and mDia3 expressed in Sertoli cells for spermatogenesis by germ cell transplantation ( Fig 1C–1H ) , according to our previously established protocol [23] . We first transplanted testicular germ cell suspensions from WT or mDia1/3 DKO mice to germ cell–free and Sertoli cell–only testes of W/Wv mice ( Fig 1C ) , and examined spermatogenesis by hematoxylin–eosin ( HE ) staining of histological sections of the recipients ( Fig 1D ) . We found that W/Wv mouse testes transplanted with mDia1/3 DKO testicular cell suspensions had normal spermatogenesis , as did W/Wv mouse testes transplanted with WT testicular cell suspensions ( Fig 1D ) . Quantification results revealed no significant difference of the spermatozoa number per seminiferous tubule in these transplanted mice ( Fig 1E ) . Thus , mDia1/3 expression in germ cells is dispensable for spermatogenesis . As the reciprocal approach , we depleted germ cells of WT or mDia1/3 DKO mice with busulfan treatment and transplanted testicular germ cell suspensions from acrosin/actin-enhanced green fluorescent protein ( acro/act-EGFP ) transgenic mice to each Sertoli cell–only testis ( Fig 1F ) . We found that acro/act-EGFP testicular germ cells transplanted to busulfan-treated mDia1/3 DKO testes mimicked abnormal sperm phenotypes seen in mDia1/3 DKO testes , including a reduced number of elongated spermatid ( Fig 1G , red box ) , ectopic localization near the basal lamina of the seminiferous tubule ( Fig 1G , black box ) , and abnormal shape of the head ( Fig 1G , black box , yellow arrowhead ) . Quantification revealed a significant decrease in the spermatozoa number per seminiferous tubule of busulfan-treated Sertoli-only mDia1/3 DKO testes compared with WT testes ( Fig 1H ) . Therefore , mDia1/3 function in Sertoli cells is required for normal spermatogenesis . Given the critical function of mDia1/3 expression in Sertoli cells , we then used confocal microscopy and examined F-actin structure in primary Sertoli cells cultured on gelatin-coated cover glass . We found that actin filaments in control WT Sertoli cells are composed of thick F-actin bundles and faintly stained actin filaments between these bundles ( S6A Fig , left , and magenta line scanning ) . On the other hand , in mDia1/3 DKO Sertoli cells , F-actin bundles were apparently retained , but the staining intensity of faintly stained actin filaments between these bundles was greatly reduced ( S6A Fig , right , and green line scanning ) . To further resolve the architecture of faintly stained actin filaments in Sertoli cells at the nanoscale level , we next examined phalloidin-stained control WT cells with total internal reflection ( TIRF ) three dimensional-N-stochastic optical reconstruction microscopy ( 3D-N-STORM ) superresolution microscopy [24] . We found that the faintly stained actin filaments between thick F-actin bundles observed in the cortices of WT cells by confocal microscope are actually a meshwork of actin filaments with a relatively large pore size of about 100 nm ( Fig 2A , upper , white box ) . We then next examined the actin cytoskeleton organization of mDia1/3 DKO Sertoli cells and found that the above cortical F-actin meshwork was markedly sparser , and there were areas devoid of actin filaments in these cells ( Fig 2A , below , white box ) . Quantitative analysis of STORM images revealed that the occupancy of F-actin meshwork was significantly reduced in mDia1/3 DKO Sertoli cells ( Fig 2B ) . These results suggest that mDia1/3 contribute to the formation and maintenance of cortical F-actin meshwork in Sertoli cells . We next sought to analyze the relative contribution between formins and Arp2/3 on cortical F-actin meshwork in Sertoli cells . To this end , we utilized pharmacological inhibitors for formins and Arp2/3 . We found that treatment of WT cells with small molecule inhibitor of formin homology 2 domain ( SMIFH2 ) , a formin inhibitor [25] , reduced cortical F-actin meshwork similarly as was observed in mDia1/3 DKO cells ( Fig 2C , third row ) . Notably , a fraction of SMIFH2-treated Sertoli cells showed total suppression of cortical F-actin meshwork with concomitant decrease in F-actin bundles ( Fig 2C , fourth row ) . On the other hand , treatment of WT cells with CK-666 , an Arp2/3 inhibitor [26] , did not suppress the cortical F-actin meshwork ( Fig 2C , second row ) . Quantitative analysis ( Fig 2D ) confirmed that treatment with SMIFH2 significantly suppressed cortical F-actin meshwork in Sertoli cells and additionally revealed that treatment of CK-666 resulted in a slight but significant increase of cortical F-actin meshwork . We speculate that the latter might be due to the increased availability of actin monomers for formins when Arp2/3-mediated actin polymerization is suppressed . These results together therefore suggest that the cortical F-actin meshwork in Sertoli cells is a structure dependent on the actin polymerization activity of formins , including mDia1 and mDia3 , but not Arp2/3 . We next examined the dynamics of actin filaments in living primary cultured Sertoli cells . To this end , we introduced LifeAct-EGFP , a probe for F-actin [27] , into primary cultured Sertoli cells . Utilizing spinning disk superresolution microscopy ( SDSRM ) [28] , which allows fast image acquisition at the spatial xy-axis resolution of approximately 120 nm , we found that , while thick F-actin bundles are a relatively static structure , the cortical F-actin meshwork is an extremely dynamic structure , in which actin continually polymerizes and depolymerizes underneath the cortex of WT control cells ( S1 Movie ) . Quantification of the dynamics of cortical meshwork actin filaments of WT Sertoli cells revealed that the F-actin elongated for a distance of several micrometers , and their extension rate was very fast , with a mean of 0 . 81 ± 0 . 06 μm/s ( about 300 globular actin ( G-actin ) subunits incorporated per second ) ( Fig 3A and 3B , S2 Movie ) . The speed distribution further revealed at least two subpopulations of cortical meshwork actin filaments with different polymerization rates; the first subpopulation has a peak polymerization rate around 0 . 4 μm/s and the other subpopulation around 1 . 3 μm/s ( Fig 3B ) . It should also be noted that F-actin elongation was highly straight ( Fig 3C ) . On the other hand , in mDia1/3 DKO cells , although the straightness of elongated F-actin was not affected ( Fig 3C ) , the subpopulation of nascent actin filament with polymerization rate peak around 1 . 3 μm/s was absent ( Fig 3B ) , and the number of elongation events was significantly reduced ( Fig 3D ) . These results together suggested that cortical F-actin meshwork is a highly dynamic structure and its formation is dependent on mDia1 and mDia3 . Given the extremely rapid rate of actin polymerization observed in the cortical F-actin meshwork area and its impairment in mDia1/3 DKO Sertoli cells , we hypothesized that actin filament polymerization in the meshwork is driven by mDia1 and mDia3 . To test this hypothesis , we carried out single-molecule speckle imaging [29] of EGFP-mDia3 in living primary cultured WT Sertoli cells . The EGFP-mDia3 used in the experiment rescued the reduced cortical actin filament meshwork phenotype of mDia1/3 DKO Sertoli cells ( S7A–S7C Fig ) . Single-molecule speckle imaging with TIRF microscopy revealed fast and directional molecular movement of EGFP-mDia3 in the cortex of Sertoli cells ( Fig 3E , S3 Movie and S4 Movie ) . Kymograph ( Fig 3F ) and quantification analyses of EGFP-mDia3 single-molecule speckles further indicated that the average speed of EGFP-mDia3 was extremely fast , with an average rate of 1 . 38 ± 0 . 06 μm/s ( Fig 3G ) . In addition , the EGFP-mDia3 molecular movement was highly linear , similar to cortical meshwork actin filament ( Fig 3H ) . Moreover , a single molecule of EGFP-mDia3 traveled for long distance—on average , 4 . 46 ± 0 . 40 μm ( Fig 3I ) . Given that the spatial localization of a single molecule of EGFP-mDia3 in the cell cortex was similar to the cortical F-actin meshwork and the linear directional movement , long travel distance and fast movement speed of an EGFP-mDia3 single molecule were correlated with LifeAct-EGFP dynamics , and that the latter was diminished in the absence of mDia1 and mDia3 , we concluded that cortical F-actin meshwork is an actin filament structure directly generated by mDia1/3 in primary cultured Sertoli cells . These data further substantiated that cortical F-actin meshwork is a mDia1/3-dependent structure . In addition to the actin meshwork , thick actin bundles were seen in WT Sertoli cells and apparently similar actin bundles were observed also in mDia1/3 DKO Sertoli cells ( Fig 2A ) . We therefore examined the origin and composition of these actin bundles . Higher magnification of TIRF-N-STORM images revealed that thick F-actin bundles of Sertoli cells are structurally continuous with the cortical F-actin meshwork both in WT and mDia1/3 DKO Sertoli cells ( Fig 4A , left and middle ) . However , we noted that whereas these thick F-actin bundles were mostly intact in WT cells ( Fig 4A , left ) , those in mDia1/3 DKO cells were occasionally bent ( Fig 4A , right ) . Utilizing confocal microscopy , we found that most of F-actin bundles in primary cultured WT Sertoli cells were co-stained for phosphorylated myosin light chain ( pMLC ) ( Fig 4B , top ) and thus represent contractile actomyosin bundles [30] . On the other hand , the pMLC staining intensity in F-actin bundles was greatly reduced in mDia1/3 DKO Sertoli cells ( Fig 4B , bottom ) . Quantification of pMLC staining showed a significant decrease in mDia1/3 DKO cells ( Fig 4C ) . To identify actin bundles observed in mDia1/3 DKO seminiferous tubules , we next performed immunostaining for espin1 , an actin bundling protein associated with noncontractile F-actin bundles [31] . We found that most of F-actin bundles in primary cultured Sertoli cells from mDia1/3 DKO mice were associated with espin1 ( Fig 4D ) . Quantification further revealed that F-actin bundles associated with espin1 comprised about 50% of total F-actin bundles in mDia1/3 DKO Sertoli cells but were rarely observed in WT Sertoli cells ( Fig 4E ) . These results together indicate that mDia1/3 are indispensable not only for the formation and maintenance of the cortical F-actin meshwork but also for the generation of contractile actomyosin bundles in Sertoli cells . To examine how our findings on F-actin structures in Sertoli cells cultured in vitro may reflect those in vivo , we next investigated the F-actin structures in Sertoli cells in intact seminiferous tubules . To this end , we selectively fluorescently labeled Sertoli cells in vivo by microinjection of lentivirus-expressing LifeAct-EGFP to seminiferous tubules , according to our method reported previously [32] . We then dissected and untangled the lentivirus-injected seminiferous tubules , fixed and prepared them for imaging ex vivo [33] . Deconvoluted Z-stack images with spinning disk confocal microscopy showed that , although the morphology of intact Sertoli cells was different from that of cultured Sertoli cells , their F-actin structures imaged with LifeAct-EGFP consisted of at least two different F-actin structures , the thick F-actin bundles and thin F-actin meshwork ( S8 Fig , S5 Movie ) . These results suggest that the overall F-actin architectures of Sertoli cells in intact seminiferous tubules are largely similar to those found in cultured Sertoli cells . Recent studies suggested an important role of contractile actomyosin bundles in the regulation of cell–cell AJ [34 , 35] . Given that actomyosin bundles were impaired in primary cultured mDia1/3 DKO Sertoli cells , we next utilized an in vitro reconstitution experiment and investigated the impact of the loss of mDia1/3 on the formation of the AJ between a Sertoli cell and a round spermatid cell ( Fig 4F ) . In this system , germ cells isolated from the approximately 3-wk-old EGFP transgenic mice testes containing mostly round spermatids were added onto the primary cultured Sertoli cells and further cocultured for 24 h to allow the formation of Sertoli cell–round spermatid AJ . Immunocytochemistry of an AJ protein , N-cadherin , revealed that while approximately 50% of the round spermatids on WT primary Sertoli cells formed N-cadherin positive cell–cell adhesion , less than 20% of germ cells formed N-cadherin positive cell–cell adhesion with mDia1/3 DKO primary Sertoli cells ( Fig 4G and 4H ) . In addition , we found that the continuity of F-actin on the round spermatid–Sertoli cell interface was often disrupted in the mDia1/3 DKO Sertoli cell ( Fig 4I and 4J ) . Quantitative analysis further revealed that the density of the cortical F-actin meshwork beneath the germ cell in WT Sertoli cells was compromised in mDia1/3 DKO Sertoli cells ( Fig 4I and 4K ) . These results together suggest that mDia1/3-mediated F-actin is critical for formation of the AJ between Sertoli cells and round spermatids . Because the above findings showed the role of mDia1/3 in the formation of AJ between Sertoli cells and germ cells in vitro , we next examined if the mDia1/3 deficiency in Sertoli cells affects these cell–cell interactions in the seminiferous tubule in vivo . To this end , we performed immunostaining for nectin-2 , an adhesion molecule exclusively expressed in Sertoli cells [36 , 37] . Composite Z-stack images of nectin-2 in WT seminiferous tubules showed nectin-2 signals at the AJ between a Sertoli cell and a round spermatid ( see the area shown by the white two-way arrow in Fig 5A , WT ) and concentration of nectin-2 at the apical ES junction between Sertoli cells and elongated spermatids and basal ES between Sertoli–Sertoli cells ( Fig 5A ) . On the contrary , nectin-2 signal at the boundary between Sertoli cells and round spermatids was significantly reduced in mDia1/3 DKO seminiferous tubules ( Fig 5A , below ) . We also stained for nectin-2 in WT and mDia1/3 DKO seminiferous tubules throughout the spermatogenic cycles and observed consistent results ( S9 Fig ) . Moreover , high magnification images ( Fig 5B ) revealed that the accumulation ( Fig 5C ) and the continuity ( Fig 5D ) of concentrated nectin-2 signals at the apical ES junction were severely impaired in the mDia1/3 DKO seminiferous tubule . These results indicate that mDia1/3 are indispensable for both AJ and apical ES junction in the seminiferous tubule . It is known that while conventional AJs are associated with contractile actomyosin bundles [34 , 35] , ES junctions are typified by the presence of highly dense noncontractile F-actin bundles in the Sertoli cell [13 , 14] . To further resolve the F-actin architecture of WT and mDia1/3 DKO seminiferous tubules , we next conducted phalloidin staining and examined F-actin structures by confocal imaging ( Fig 5E ) . Composite Z-stack images of F-actin in WT seminiferous tubules show that , while thick F-actin bundles specifically localize to the apical ES junction along the elongated spermatid head ( Fig 5E , above , red box ) and basal ES at this stage ( Fig 5E , above , yellow box ) , thick F-actin bundles were intriguingly increased in number and intensity and aberrantly distributed over the whole region of the mDia1/3 DKO seminiferous tubule ( Fig 5E , below ) . Moreover , whereas the background F-actin staining in the area where round spermatids are located as shown by the white two-way arrow , is relatively high in WT seminiferous tubules ( Fig 5E , above ) , they were strongly reduced between the ectopic thick F-actin bundles in mDia1/3 DKO seminiferous tubules ( Fig 5E , blue box ) . Line scanning of the F-actin intensity in the round spermatid area ( Fig 5E , blue box , magenta and green lines ) clearly showed the stark difference between the faintly stained F-actin density in WT and mDia1/3 DKO Sertoli cells ( Fig 5F ) . Based on these observations , we summarized our results in a simplified diagram ( Fig 5G ) . Quantification revealed that the total F-actin intensity per seminiferous tubule was significantly reduced in mDia1/3 DKO seminiferous tubules compared with that of WT seminiferous tubules ( Fig 5H ) . To further clarify the identity of abnormal thick actin bundles specifically observed in mDia1/3 DKO seminiferous tubules , we next performed immunostaining of espin1 . We found that whereas espin1 staining is relatively weak and confined to the area around the head of elongated sperm in control WT seminiferous tubules at stages X–V of the spermatogenic cycle , it showed persistent and abnormally strong signals in mDia1/3 DKO seminiferous tubules , which are mostly colocalized with ectopic F-actin bundles ( Fig 5I and S10 Fig ) . Quantification showed that F-actin bundles associated with espin1 comprised about 60% of total F-actin bundles in mDia1/3 DKO seminiferous tubules but were rarely observed in WT seminiferous tubules ( Fig 5J ) . These findings together suggested that the loss of mDia1/3 impaired normal F-actin structures in both AJs and apical ES junctions and induced the formation of ectopic aberrant espin1-containing F-actin bundles in seminiferous tubules .
Despite advances in our understanding of formins’ biochemical activity , how and where formins generate F-actin and what forms of F-actin structures they make in a variety of cell types and tissues remain largely unknown . Technically , the presence of abundant F-actin bundles in adherent cells makes the observation of the fine cortical actin network challenging . In this work , we found that although mDia1 KO male mice and mDia3 KO male mice were fully fertile , mDia1/3 DKO male mice were infertile , suggesting the functional redundancy between the two mDia isoforms . Starting with the Sertoli cell–intrinsic defects in spermatogenesis in mDia1/3 DKO mice , we examined how the formins mDia 1 and mDia3 contribute to actin cytoskeleton structure and dynamics in Sertoli cells and spermatogenesis . We employed superresolution microscopy , 3D-N-STORM , to unravel the nanoscale F-actin architecture in Sertoli cells and found that the actin cytoskeleton in these cells is strongly dependent on formins . We observed at least two types of actin cytoskeleton structure coexisting in primary cultured WT Sertoli cells , the thin cortical F-actin meshwork and the thick actomyosin bundles . Notably , two types of actin filaments were also seen in Sertoli cells in situ in testis tubules . High magnification superresolution images further revealed that these two types of F-actin are of continuous structure . In contrast to the previous findings on cortical F-actin meshwork in cells cultured in suspension [18 , 19] , we found that the cortical meshwork of Sertoli cells on the substrate has a larger pore size and is largely dependent on formin activity , including mDia1/3 , but not on Arp2/3 . Utilizing spinning disk superresolution live imaging [28] , we further found that the cortical F-actin meshwork is a highly dynamic structure . Quantitative analysis of the cortical F-actin network in cultured Sertoli cells revealed two subpopulations in the cortical F-actin meshwork , the first subpopulation with the polymerization rate peak at about 0 . 4 μm/s and the second subpopulation with polymerization rate peak at about 1 . 3 μm/s . In mDia1/3 DKO Sertoli cells , the latter subpopulation was totally absent . Therefore , the subpopulation of newly polymerized actin with faster speed is dependent on mDia1/3 activity . Moreover , we found that the dynamic of a single mDia3 molecule in living Sertoli cells on a substrate is similar to that of the second subpopulation of cortical F-actin meshwork , with polymerization rate of about 1 . 3 μm/s . Given this correlation , it is likely that mDia1 and mDia3 generate a particular fraction of cortical F-actin meshwork with fast dynamics in Sertoli cells . We speculate that the other fraction of cortical F-actin meshwork is mediated by other formins expressed in Sertoli cells , such as formin1 [38] , because cortical F-actin meshwork was strongly suppressed by treatment with the formin inhibitor , SMIFH2 [25] . Intriguingly , we also found that actomyosin bundles are impaired in mDia1/3 DKO Sertoli cells . In the absence of mDia1 and mDia3 , noncontractile actin bundles containing espin1 replaced contractile actomyosin bundles in Sertoli cells . The mechanism by which mDia1/3-generated actin filaments are preferentially incorporated to actomyosin bundles and not to espin1-containing actin bundles remains unclear . We previously demonstrated that mDia1 helically rotates at the barbed end of the actin filament [39] and proposed that it might cause the twist of F-actin [40] . Because it was reported that the twisting of an actin filament affects its conformation and influences subsequent binding of actin binding proteins ( ABPs ) , including myosin II [41] , we speculate that mDia1 might affect the conformation of an actin filament that allows efficient binding of myosin II . It should also be noted that filament spacing in actin bundles is an architectural feature dependent on the actin bundling proteins . It was reported that the incorporation of small-sized ( about 8 nm ) espin1 molecules into F-actin results in compact F-actin bundling , which is segregated from F-actin containing contractile myosin of the larger size [42] . We speculate that long and straight actin filaments generated by mDia1/3 in the cortical meshwork may not be favorable for espin1 binding and instead may allow larger protein cross-linking to the formation of actomyosin bundles . A previous study reported that espin-associated F-actin bundles assemble into highly ordered , densely packed bundles [13] . On the other hand , the actomyosin bundle is a structure of parallel filaments of opposite polarity spaced apart by myosin [43 , 44] . Therefore , it is possible that espin-based actin bundles contain a larger number of actin filaments per bundle than actomyosin in mDia1/3 DKO Sertoli cells . Nevertheless , they are apparently more fragile than actomyosin bundles as they are occasionally bent , as observed in mDia1/3 DKO Sertoli cells in this study . Actomyosin is a contractile structure generating force in various cellular contexts , and its importance in maintaining the cell–cell AJ has been recently reported [34 , 35] . Consistently , we found that formation of the AJ was impaired in the mDia1/3 DKO seminiferous tubule , as evidenced by suppressed cell adhesion between round spermatids and Sertoli cells in vitro and reduced nectin-2 staining in Sertoli cell–germ cell junction in vivo . It is plausible that mDia1/3 supply cortical actomyosin bundles to encircle spermatids that may limit the diffusion of AJ proteins and promote their clustering in Sertoli cells , as reported as a prerequisite event for cell–cell junction formation in other systems [17 , 45] . Notably , a small fraction of germ cells that could form cell–cell junctions with mDia1/3 DKO Sertoli cells in vitro showed impaired continuity of F-actin in the proximity of cell–cell junctions . Therefore , mDia1/3-mediated actomyosin bundles in Sertoli cells also play a role in stabilization and maintenance of cell–cell junctions . It should also be noted that in addition to AJs , apical ES junctions were also severely impaired in mDia1/3 DKO mice . As the ES junction is formed subsequent to the AJ during sperm development , we speculate that proper AJ is a prerequisite for ES junction formation . One intriguing question is how the actomyosin bundles generated by mDia1/3 localize specifically to the AJ and exert their function there . Several models were previously proposed for the generation of actomyosin bundles at the AJ [34 , 46] . Because we observed mDia1/3-dependent actin polymerization throughout the Sertoli cell cortex , our results support a model that mDia1/3-depedent actomyosin bundles are generated in the cortex but the localization to the AJ is mediated by other side-binding ABPs , such as α-catenin [47] . Sertoli cells make adhesion with developing germ cells and contribute to spermatogenesis by providing structural and functional support [8] . Thus , proper adhesions between Sertoli cells and germ cells are indispensable for normal spermatogenesis . Involvement of F-actin in sperm development was also previously reported [48] . However , the detailed molecular mechanism of F-actin action in spermatogenesis , especially in the supporting Sertoli cells , was largely unknown . In this work , we demonstrated that mDia1/3-dependent cortical F-actin meshwork and contractile actomyosin in Sertoli cells are critical for spermatogenesis through the regulation of Sertoli cell–germ cell adhesion . In summary , here we have combined genetic and pharmacological manipulation of formins with superresolution and single-molecule imaging , and revealed a previously unsuspected requirement for the two formins , mDia1 and mDia3 , in sperm morphogenesis and male fertility . Importantly , mDia1/3 catalyze the formation of cortical F-actin meshwork and actomyosin bundles indispensable for the formation and function of AJs and apical ES junctions essential for proper spermatogenesis ( S11 Fig ) . The function of mDia unraveled here thus sheds a light on the importance of the F-actin structure and dynamics in Sertoli cells for spermatogenesis and paves a way for molecular dissection of its regulatory mechanisms .
Primary antibodies used were rabbit anti-mDia1 polyclonal ( LifeSpan BioSciences , Seattle , WA ) , rabbit anti-mDia3 polyclonal ( SIGMA-Aldrich , St . Louis , MO ) , chicken anti-vimentin polyclonal ( Millipore , Burlington , MA ) , rabbit anti-GFP polyclonal ( MBL , Nagoya , Japan ) , goat anti-nectin-2 polyclonal ( Santa Cruz Biotechnology , Dallas , TX ) , rabbit anti-espin1 polyclonal ( #PB538 , a gift from Dr . Bechara Kachar , NIH ) [49] , mouse anti-espin1 monoclonal , mouse anti-N-cadherin monoclonal ( BD Bioscience , San Jose , CA ) , and mouse anti-phospho-myosin light chain2 ( Ser19 ) monoclonal ( Cell Signaling , Danvers , MA ) . Inhibitors used were SMIFH2 ( Tocris , Bristol , United Kingdom ) and CK-666 ( Tocris , Bristol , UK ) . mDia1 KO mice were generated and backcrossed to C57BL/6N mice for more than 10 generations , as previously described [3] . mDia3 KO mice and mDia1/mDia3 DKO were generated and backcrossed to C57BL/6N mice for more than 10 generations , as previously described [5] . C57BL/6-Tg ( CAG-EGFP ) mice were purchased from the local supplier ( Japanese SLC , Hamamatsu , Japan ) and acro/act-EGFP [TgN ( acro/act-EGFP ) OsbC3-N01-FJ002] mice were kindly provided by Dr . Masaru Okabe ( Osaka University ) . All animal care and use were in accordance with the United States National Institutes of Health Guide for the Care and Use of Laboratory Animals and were approved by the Institutional Animal Care and Use Committee of Kyoto University Graduate School of Medicine . Testes from 12-wk-old WT or mDia1/3 DKO mice were collected in cold Hanks’ balanced salt solution ( HBSS; Invitrogen , Carlsbad , CA ) and placed on ice . After removal of the tunica albuginea , seminiferous tubules were dissociated from the testis and transferred immediately into 1 mL of 1 mg/mL collagenase in HBSS . Tubules were incubated for 15 min at 37°C in a water bath , then washed with HBSS three times . Collagenase-treated tubules were then dissociated in a mixture of 0 . 8 mL of 0 . 25% trypsin and 0 . 2 mL of 7 mg/mL DNase in HBSS for 10 min at 37°C in a water bath . A total of 5 mL of 10% FBS-contained Iscove’s modified Dulbecco’s medium ( IMDM; Invitrogen , Carlsbad , CA ) were subsequently added to the trypsinized cells and mixed by gently pipetting . The mixture was then centrifuged at 400g for 5 min . Cells were resuspended in 10% FBS-contained IMDM , counted , and then plated at a concentration of 8 × 105 cells/mL per well on a 0 . 2% gelatin-coated cover glass . Cells were allowed to settle for 24 h in 5% CO2 at 37°C . Nonattached cells were washed out with serum-free IMDM four times . Finally , 1 mL/well of IMDM containing 10% FBS was added the culture and cells were cultured for an additional 48 h in a CO2 incubator , as above . In vitro fertilization was performed as described previously [50] . In brief , female B6D2F1 mice were superovulated by intraperitoneal injections of equine chorionic gonadotropin ( eCG; Teikoku Zoki , Tokyo , Japan ) and human chorionic gonadotropin ( hCG; Teikoku Zoki , Tokyo , Japan ) at 48-h intervals . Ovulated eggs were recovered 13 h after the hCG injection and placed in a 200-μL drop of modified Krebs–Ringer bicarbonate solution ( TYH medium ) [51] containing glucose , sodium pyruvate , bovine serum albumin , and antibiotics ( 0 . 05 mg/mL penicillin , 100 IU/mL streptomycin ) . Fresh spermatozoa from the cauda epididymis were dispersed in a 200-μL drop of TYH medium , diluted to 1×106 spermatozoa/mL , and incubated for 1 . 5 h to induce capacitation . An aliquot of capacitated spermatozoa from control WT mice and mDia1/3 DKO mice were then added to the eggs at 2×105 spermatozoa/ml for IVF . The mixture was incubated for 8 h at 37°C under 5% CO2 in air . Fertilization was confirmed by pronuclear formation . For observation of sperm–zona binding , egg masses were treated with bovine testicular hyaluronidase ( 175 U/mL; Sigma-Aldrich , St . Louis , MO ) for 5 min to remove the cumulus cells . The cumulus-free eggs were placed in a 200-μL droplet of TYH medium and inseminated as described . After 30 min of incubation , sperm binding to the zona pellucida of the eggs was observed under an IX-70 microscope ( Olympus , Tokyo , Japan ) . The cauda epididymis was collected and minced with a razor blade in 1 mL PBS . The suspension was filtered through 70-μm-nylon mesh ( Corning , Corning , NY ) . The number of spermatozoa was counted using a hemocytometer . Cauda epididymal spermatozoa were suspended and incubated in TYH medium . Sperm motility was then measured using the CEROS sperm analysis system ( software version 12 . 3; Hamilton Thorne Biosciences , Beverly , MA ) . Analysis settings were as described previously [52] . The percentage of hyperactivated spermatozoa was analyzed as described previously [53] . Mature sperm were collected from cauda epididymis by pricking with a fine needle and rinsed twice with PBS . Sperms were then plated on slide glasses , air-dried , and fixed with 4% PFA/PBS for 15 min at room temperature . Sperm morphology was observed on a laser scanning confocal imaging system ( Leica SP5 ) with an oil immersion objective lens ( 100×1 . 4 numerical aperture ) . To enrich spermatogonial stem cells in donor testicular cell suspension , experimental cryptorchidism was surgically induced in donor mice [54] . Three to six weeks after the surgery , testis cells were dissociated into single-cell suspensions by two-step enzymatic digestion using collagenase type IV and trypsin ( SIGMA-Aldrich , St . Louis , MO ) , as described previously [23] . The dissociated WT or mDia1/3 DKO cells were then transplanted into W/Wv recipient mice ( Japan SLC , Hamamatsu , Japan ) through the efferent duct . For reciprocal transplantation , testis cells from cryptorchid acro/act-EGFP transgenic mice were transplanted into busulfan-treated control WT or mDia1/3 DKO mice through the efferent duct . Approximately 5 or 10 μL was introduced into the testes , respectively . Each injection filled 75%–85% of the seminiferous tubules . Testes or epididymides were fixed with 4% PFA at 4°C overnight . For paraffin sections , the testes or epididymides were embedded in paraffin and cut into sections at 4-μm thickness . For frozen sections , the testes were cryoprotected in 0 . 1 M PB containing 30% sucrose , frozen in Tissue-Tek OCT compound ( Sakura-finetek , Tokyo , Japan ) in dry ice , and then were cut into sections at 12-μm thickness using cryostat . HE and PAS staining were performed according to standard protocol . For immunohistochemistry , cryosections were washed with PBS three times for 5 min each . Antigen retrieval for mDia1 , nectin-2 , espin1 , and vimentin staining was carried out by boiling the sections in 10 mM citrate buffer , pH 6 . 0 , with a pressure cooker . Sections were incubated with the blocking buffer ( PBS containing 1% normal donkey serum ( Jackson laboratory , Bar Harbor , ME ) or 1% normal goat serum ( Jackson laboratory , Bar Harbor , ME ) and 0 . 3% TritronX-100 ) for 1 h at room temperature . Sections were then incubated with the primary antibody diluted in blocking buffer . After three washes with 0 . 3% Triton X-100 in PBS , sections were incubated with appropriate secondary antibodies conjugated to Alexa Fluor 488 , Alexa Fluor 555 , Alexa Fluor 594 , or Alexa Fluor 633 ( Invitrogen , Carlsbad , CA ) . Hoechst 33342 ( Invitrogen , Carlsbad , CA ) or DAPI ( Molecular Probes , Eugene , OR ) was used for nuclear staining . Phalloidin conjugated with Alexa 488 , 546 , 555 , or 647 ( Invitrogen , Carlsbad , CA ) was used for the staining of F-actin . Peanut agglutinin ( PNA ) conjugated with TRITC ( SIGMA-Aldrich , St . Louis , MO ) was used for the staining of round and early elongated spermatids acrosome . TUNEL staining was performed according to the manufacturer’s instructions using ApopTag Fluorescein Direct In Situ Apoptosis Detection Kit ( Millipore , Burlington , MA ) . Fluorescent images were acquired with a laser scanning confocal imaging system ( Leica SP5 ) equipped with 100× NA 1 . 4 HCX PL APO CS oil immersion objective lens ( Leica , Wetzlar , Germany ) . Images were processed using Adobe Photoshop CS5 software ( Adobe , San Jose , CA ) . For quantification of nectin-2 intensity , nectin-2 staining signals associated with the apical ectoplasmic specialization junction were selectively visualized by setting a threshold , and then the average intensity per pixel was analyzed by ImageJ software ( http://rsbweb . nih . gov/ij ) . For coefficient of variation of nectin-2 , a line scan of the nectin-2 staining signal along the apical ectoplasmic junction was performed using ImageJ software by drawing a line , and the intensity values along the line were obtained using the Plot Profile . Coefficient of variation of nectin-2 staining intensity along the apical ectoplasmic junction were then calculated as the ratio of the standard deviation and average staining intensity . Line scan for measurement of F-actin intensity was performed using ImageJ software by drawing a line on the seminiferous tubule , and the intensity values along the line were obtained using the Plot Profile . Plots were generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . For quantification of seminiferous tubule F-actin intensity , region of interest ( ROI ) was defined to specifically include the seminiferous tubule but not the myoid cell layer , and average F-actin intensity per pixel was then analyzed by ImageJ software . Averages of F-actin intensity per pixel of WT and mDia1/3 DKO seminiferous tubules were then generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . For quantification of the proportion of espin1-positive actin bundles , a binary image of F-actin bundles and espin1 were generated by setting a threshold . The two images were then merged and the pixel number of total F-actin bundles and espin1 signals that are colocalized with F-actin bundles was analyzed . The proportion of espin1-positive F-actin bundles were then calculated as a ratio of the pixel number of espin1-associated F-actin bundles and total F-actin bundles for seminiferous tubules . Averages of the proportion of espin1-positive actin bundles of WT and mDia1/3 DKO seminiferous tubules were then generated using Prism software ( GraphPad Software , San Diego , CA ) . Sertoli cells were cultured for 72 h on 25 mm round , No . 1 . 5 fiducialated cover glass ( Hestzig , Leesburg , VA; #600-100AuF ) for TIRF 3D-N-STORM superresolution imaging . For the fixation , the cells were briefly washed with 2 . 5 mL of prewarmed ( 37°C ) PBS and fixed and permeabilized with 0 . 3% glutaraldehyde ( EM Grade; Electron Microscopy Sciences , Hatfield , PA ) and 0 . 25% Triton X-100 in 1 mL of cytoskeleton buffer ( 10 mM MES , pH 6 . 1 , 150 mM NaCl , 5 mM EGTA , 5 mM glucose , and 5 mM MgCl2 ) for 1 . 5 min . The second fixation step was performed with 2% glutaraldehyde in 1 mL of cytoskeleton buffer for 10 min . Samples were quenched with 0 . 1% NaBH4 ( SIGMA-Aldrich , St . Louis , MO ) in 2 . 5 mL of freshly prepared PBS for 7 min on ice to reduce autofluorescence . Finally , fixed cells were washed with PBS twice , each time for a 10-min incubation , and then kept in PBS overnight at 4°C . Before imaging , F-actin was probed using 0 . 33 μM of Alexa Flour 647-conjugated phalloidin ( Life Technologies , Waltham , MA ) and incubated for 30 min at room temperature . The samples were imaged on a Nikon N-STORM microscope ( Nikon , Tokyo , Japan ) in TIRF mode . The microscope is equipped with a 100× NA 1 . 49 Apo TIRF objective lens , a back-illuminated EMCCD camera ( Andor Ixon3 , Belfast , UK ) , a Cy5 ( excitation , 620/60; emission , 700/75 ) filter set ( Chroma , Bellows Falls , VT ) , and a cylindrical lens for 3D imaging . During imaging , a 100-mW 641-nm laser ( Coherent , Santa Clara , CA ) and a 100-mW 405-nm laser ( Coherent , Santa Clara , CA ) were used to excite and photoswitch Alexa Fluor 647 , respectively . In each image acquisition , a 5–10-min period of full-powered illumination by 641-nm laser was first performed to turn most Alexa Fluor 647 fluorophores into dark state to achieve a sparse distribution of single molecules . Image frames were acquired when single-molecule blinking could be observed . The intensity of 405-nm laser was periodically tuned during imaging to reactivate fluorophores to maintain sufficient fluorophore density . For each image , 40 , 000 raw frames were acquired in the frame-transfer mode , with an exposure time of 50 ms , EM gain of 200 , and a readout speed of 10 MHz . Fluorophore detection and localization were carried out by PeakSelector ( courtesy of Harald Hess , Howard Hughes Medical Institute ) , a customized software developed in IDL ( Exelis Vis , Boulder , CO ) . The centroid position of each detected fluorophore was calculated via 2D-Gaussian nonlinear least-square fitting , as described earlier [55] . The localization precision of each centroid coordinate was computed using the Thompson-Webb formula depicted earlier [56] . Fluorophore peaks with localization precisions smaller than 20 nm were rejected from subsequent analysis . The fiducials pre-embedded on the glass coverslips were used to correct drift . The N-STORM images were then reconstructed by representing each localization coordinate as a normalized Gaussian function whose widths depend on the localization precision [57] . Three-dimensional data were rendered with colors encoding the z positions of fluorophores . The N-STORM image of F-actin in Sertoli cells contains a mixture of fine meshwork and high-density bundles . To separate these two structures and analyze the density of the fine F-actin meshwork , the image was first reconstructed with a pixel size of 160 nm ( an image size of 256 × 256 pixels ) to blur regions of F-actin meshwork , leaving F-actin bundles as more prominent structures . The cell region was then anisotropically enhanced [58 , 59] to highlight F-actin bundles , and then segmented using Otsu's method [60] . Next , another image was reconstructed with a pixel size of 10 nm , which is sufficiently high for the F-actin network , generating an image size of 4 , 096×4 , 096 pixels . The previously segmented regions of F-actin bundles were scaled up by 16 times and used as masks to isolate regions between thick F-actin bundles from the high-resolution image . The F-actin network was segmented from the isolated areas using Otsu's method . F-actin occupancy was then computed as the ratio between the number of F-actin pixels and the total number of pixels in the binarized regions of the F-actin network . For immunocytochemistry , cells were fixed with 4% PFA in PBS for 15 min at room temperature . The fixed cells were permeabilized with 0 . 1% Triton X-100 in PBS for 15 min at room temperature and then blocked with 5% skim milk in PBS for 1 h at room temperature . The cells were then stained with anti-pMLC antibodies ( CST , Danvers , MA ) and anti-espin1 antibodies ( BD Biosciences , San Jose , CA ) . Secondary antibodies were Alexa Fluor 488-conjugated goat anti-mouse IgG ( Molecular Probes , Eugene , OR ) and Alexa Fluor 488-conjugated goat anti-rabbit IgG ( Molecular Probes , Eugene , OR ) . F-actin was stained with Alexa Fluor 555-conjugated phalloidin ( 1:100; Molecular Probes , Eugene , OR ) . DAPI ( Molecular Probes , Eugene , OR ) was used for nuclear staining . Fluorescent images were acquired on a laser scanning confocal imaging system ( Leica SP5 ) equipped with 100× NA 1 . 4 HCX PL APO CS oil immersion objective lens ( Leica , Wetzlar , Germany ) . Images were processed using Adobe Photoshop CS5 software ( Adobe , San Jose , CA ) . ROI including a cell was defined , and average pMLC intensity per pixel was then analyzed by ImageJ software . Averages of pMLC intensity per pixel of WT and mDia1/3 DKO cells were generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . For quantification of the proportion of espin1-positive actin bundles , binary images of F-actin bundles and espin1 were generated by setting a threshold . The two images were then merged and the pixel number of total F-actin bundles and espin1 signals that are colocalized with F-actin bundles were analyzed . The proportion of espin1-positive F-actin bundles were then calculated as a ratio of the pixel number of espin1-associated F-actin bundles and total F-actin bundles for each cell . Averages of the proportion of espin1-positive actin bundles of WT and mDia1/3 DKO cells were then generated using Prism software ( GraphPad Software , San Diego , CA ) . Primary cultured Sertoli cells were transfected with pCAG-LifeAct-EGFP [5] or pCAG-EGFP-mDia3 [5] by electroporation using Neon Transfection System ( Invitrogen , Carlsbad , CA ) according to the manufacturer’s protocol . Briefly , 2×105 cells were transfected with 1 . 5 μg of plasmid DNA . Electroporation was performed at a single pulse of 1 , 350 V for 30 ms . After electroporation , cells were plated in IMDM medium containing 10% FBS for 24 h in 5% CO2 at 37°C . For observation of LifeAct-EGFP , primary cultured Sertoli cells were maintained in IMDM without phenol red containing 2% FBS . Time-lapse imaging of LifeAct-EGFP was carried out at 37°C using a SD-OSR IX83 inverted microscope ( Olympus , Tokyo , Japan ) equipped with a 100× NA 1 . 4 , UPLS APO oil immersion objective ( Olympus , Tokyo , Japan ) and Yokogawa W1 spinning disk unit ( Yokogawa , Musashino , Japan ) and controlled by MetaMorph software ( Universal Imaging , San Jose , CA ) . An area near the cell periphery was selectively illuminated . Images were recorded at a rate of 2 s/frame . Speed , straightness , and frequency measurements were performed by tracking individual actin filaments manually using ImageJ software . Graphs were generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . Single-molecule speckle imaging of EGFP-mDia3 was acquired using a microscope ( IX81 , Olympus , Tokyo , Japan ) equipped with 100-W mercury illumination , a Plan-Apo 100× , 1 . 4 NA oil-immersion objective ( Olympus , Tokyo , Japan ) , and a cooled EMCCD camera ( Evolve 512; Photometrics , Tucson , AZ ) . Cells expressing a low level of EGFP-mDia3 were observed . An area near the cell periphery was selectively illuminated . Images were recorded at a rate of 200 ms/frame . Measurements of speed , straightness , and travel distance of single-molecule movement were performed by tracking individual single molecules manually using ImageJ software . Graphs were generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . Kymograph analysis was performed using MetaMorph software ( Universal Imaging , San Jose , CA ) . Testes were isolated from the 3-wk-old C57BL/6-Tg ( CAG-EGFP ) mice , and the tunica and blood vessels were dissected and removed by fine forceps . Isolated testes were minced in PBS using scalpel blades . The minced tissue was then transferred into 50-mL plastic tubes and centrifuged at 100g for 1 min . Supernatant was discarded and the pellet was washed twice in PBS and centrifuged at 100g for 1 min to recover germ cells . Cells were then resuspended in PBS and filtered through the 40-μm nylon mesh to remove tissue debris and cell clumps . Germ cells were then centrifuged at 500g for 10 min . The resultant cell pellet was finally resuspended in Ham's F12/DMEM containing 10% FBS [61] . To remove residual germ cells contaminated in the primary culture of Sertoli cells prepared as described above , the primary cultures , after 3 d of incubation , were subjected to hypotonic treatment for 2 h at room temperature with 20 mM Tris-HCl buffer , pH 7 . 4 , for 2 min [62] . Purified Sertoli cells were then incubated with 10% FBS in IMDM for 2 h in 5% CO2 at 37°C to recover from the hypotonic treatment . Germ cells ( 5×105 cells/well ) isolated from testes of 3-wk-old C57BL/6-Tg ( CAG-EGFP ) mice were then plated onto the Sertoli cells . These cells were cocultured for 1 d , fixed with 4% PFA/PBS for 15 min at room temperature , and subjected to immunocytochemistry . Fluorescent images were acquired on a SD-OSR IX83 inverted microscope ( Olympus , Tokyo , Japan ) equipped with a 100× NA 1 . 4 , UPLS APO oil immersion objective ( Olympus , Tokyo , Japan ) and Yokogawa W1 spinning disk unit ( Yokogawa , Musashino , Japan ) controlled by MetaMorph software ( Universal Imaging , San Jose , CA ) . Living GFP-positive germ cells with round nuclear shape , as determined by DAPI staining and continuous N-cadherin signal around the germ cells , were defined as adhesive cells . Living GFP-positive germ cells with round nuclear shape , as determined by DAPI staining and continuous phalloidin staining surrounding the germ cells , were defined as germ cells with continuous F-actin cup . Cortical F-actin meshwork density and the continuity of the F-actin cup were quantified manually using ImageJ software . Graphs , including the plot of correlation , were generated based on the data obtained by ImageJ using Prism software ( GraphPad Software , San Diego , CA ) . Sperms prepared from the cauda epididymis and suspended as above were fixed with an equal volume of 2% PFA and 2% GA in 0 . 1 M cacodylate buffer . Thereafter , they were fixed with 1% GA in 0 . 1 M cacodylate buffer , pH 7 . 4 , at 4°C overnight . The samples were further fixed with 1% tannic acid in 0 . 1 M cacodylate buffer , pH 7 . 4 , at 4°C for 1 h . After the fixation , the samples were washed four times with 0 . 1 M cacodylate buffer for 30 min each , followed by postfixation with 2% OsO4 in 0 . 1 M cacodylate buffer at 4°C for 2 h . The samples were dehydrated through a series of graded ethanol ( 50% , 70% , 90% , 100% ) . The samples were substituted into tert-butyl alcohol at room temperature and then frozen . The frozen samples were vacuum dried . After drying , the samples were coated with a thin layer ( 30 nm ) of osmium by using an osmium plasma coater ( NL-OPC80NS , Nippon Laser & Electronics Laboratory , Nagoya , Japan ) . The samples were observed by a JSM-6340F scanning electron microscope ( JEOL , Akishima , Japan ) at an acceleration voltage of 5 . 0 kV . We constructed the pLV-LifeAct-EGFP ( LV , lentivirus ) by inserting a LifeAct-EGFP fragment amplified by PCR from pCAG- LifeAct-EGFP [5] with primers LifeAct-EGFP forward ( 5′-GCTCTAGAATGGGCGTGGCCGACCTGAT-3′ ) and LifeAct-EGFP reverse ( 5′-CTCTCGAGTTACTTGTACAGCTCGTCCATGCC-3′ ) into pLV-CAG1 . 1 ( a gift from Dr . Inder Verma , Salk Institute ) . Lentivirus were generated as previously reported [32] . We injected recombinant lentivirus vectors into male C57BL6/N adult mice at 6 wk of age . Mice were anesthetized by i . p . injection of Avertin before the operation . Approximately 10 μL of lentivirus vector solution containing 0 . 04% trypan blue was injected into the right seminiferous tubules via the efferent ductules , according to the method described , and Sertoli cells were selectively labeled [32] . After 1 wk , mice were humanely killed and the injected right testis was dissected and the tunica albuginea were removed . Preparation of seminiferous tubules for imaging was then performed according the previous report [33] , with slight modifications . Seminiferous tubules were disentangled and then fixed with 4% PFA for 1 h at room temperature . Fixed seminiferous tubules were then cut into small pieces and attached to MAS-coated slide glass ( Matsunami , Kishiwada , Japan ) by half-drying . Specimens were mounted in antifade prolong diamond ( Thermo Fisher Scientific , Waltham , MA ) . Samples were observed under SD-OSR IX83 inverted microscope ( Olympus , Tokyo , Japan ) equipped with a 100× NA 1 . 4 , UPLS APO silicone immersion objective ( Olympus , Tokyo , Japan ) , and Yokogawa W1 spinning disk unit ( Yokogawa , Musashino , Japan ) and controlled by MetaMorph software ( Universal Imaging , San Jose , CA ) . Deconvolution processing of stacked images was performed by cellSens Dimension software ( Olympus , Tokyo , Japan ) . Three-dimensional reconstruction of stacked images was generated by Volocity software ( PerkinElmer , Waltham , MA ) . Prism ( GraphPad Software , San Diego , CA ) and Excel ( Microsoft , Redmond , WA ) were used for statistical analyses . Data are presented as mean ± SEM , and were analyzed by one-way factorial ANOVA or unpaired Student t test . P < 0 . 05 was considered statistically significant . | Paternal genetic information is transmitted to the offspring via sperm . The unique cell morphology of the sperm plays essential roles in sperm transport through the female reproductive tract and in fertilization with oocytes . Sertoli cells are somatic cells located in the seminiferous tubules of the testis and are known to contribute to the development of sperm . While many studies have analyzed sperm development , the mechanisms underlying its morphogenesis remain obscure . In this work , we showed that the interaction between developing sperm and Sertoli cells is critical for sperm morphogenesis . We further unraveled that this interaction is strongly dependent on the cortical F-actin meshwork and contractile actomyosin bundles of Sertoli cells , and that two actin polymerization and nucleation factors of the formin family , mDia1 and mDia3 , are involved in the generation of both actin-based structures . Loss of these formins in mice result in disrupted Sertoli cell actin structures , abnormal sperm morphology , and male infertility . We conclude that mDia1 and mDia3 play a role in sperm development through the regulation of the actin cytoskeletal architecture of Sertoli cells and that defects in these proteins might contribute to male infertility . | [
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"preparat... | 2018 | mDia1/3 generate cortical F-actin meshwork in Sertoli cells that is continuous with contractile F-actin bundles and indispensable for spermatogenesis and male fertility |
Metabolic Syndrome ( MetS ) is highly prevalent and has considerable public health impact , but its underlying genetic factors remain elusive . To identify gene networks involved in MetS , we conducted whole-genome expression and genotype profiling on abdominal ( ABD ) and gluteal ( GLU ) adipose tissue , and whole blood ( WB ) , from 29 MetS cases and 44 controls . Co-expression network analysis for each tissue independently identified nine , six , and zero MetS–associated modules of coexpressed genes in ABD , GLU , and WB , respectively . Of 8 , 992 probesets expressed in ABD or GLU , 685 ( 7 . 6% ) were expressed in ABD and 51 ( 0 . 6% ) in GLU only . Differential eigengene network analysis of 8 , 256 shared probesets detected 22 shared modules with high preservation across adipose depots ( DABD-GLU = 0 . 89 ) , seven of which were associated with MetS ( FDR P<0 . 01 ) . The strongest associated module , significantly enriched for immune response–related processes , contained 94/620 ( 15% ) genes with inter-depot differences . In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data , median variability in ABD due to familiality was greater for MetS–associated versus un-associated modules ( ABD: 0 . 48 versus 0 . 18 , P = 0 . 08; GLU: 0 . 54 versus 0 . 20 , P = 7 . 8×10−4 ) . Cis-eQTL analysis of probesets associated with MetS ( FDR P<0 . 01 ) and/or inter-depot differences ( FDR P<0 . 01 ) provided evidence for 32 eQTLs . Corresponding eSNPs were tested for association with MetS–related phenotypes in two GWAS of >100 , 000 individuals; rs10282458 , affecting expression of RARRES2 ( encoding chemerin ) , was associated with body mass index ( BMI ) ( P = 6 . 0×10−4 ) ; and rs2395185 , affecting inter-depot differences of HLA-DRB1 expression , was associated with high-density lipoprotein ( P = 8 . 7×10−4 ) and BMI–adjusted waist-to-hip ratio ( P = 2 . 4×10−4 ) . Since many genes and their interactions influence complex traits such as MetS , integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations .
Genome-wide association ( GWA ) studies are routinely employed to identify common genetic variants contributing to complex diseases . Many replicated GWA signals have been found for metabolic traits including high-density lipoprotein ( HDL ) , low-density lipoprotein , body mass index ( BMI ) , triglycerides ( TG ) and blood pressure , greatly enhancing the understanding of the genetic basis of these traits [1]–[6] . However , statistically significant signals resulting from GWA studies do not necessarily lead directly to the identification of genes associated with disease or provide limited insights into the molecular mechanisms of the disease phenotype . In addition , the associated SNPs explain a very small proportion of the heritability estimated for the complex trait [7] . For example , a GWA study for BMI in up to ∼250 , 000 individuals identified 32 loci that , together , explain only 4 . 5% of the phenotypic variation or ∼6–11% of the genetic variation in BMI [3] . The 1000 Genomes Project Consortium tested ∼95% of common variation using low-coverage sequencing of 167 individuals and showed that only one-third of complex trait associations are likely to be caused by common coding variation , indicating that most contributions of common variation to complex traits are regulatory in nature [8] . eQTL ( expression Quantitative Trait Loci ) studies could help in understanding how known genetic variants identified by GWA studies influence clinical traits through gene expression , or suggest potential biological pathways . eQTLs have already been associated to several complex traits including Type I diabetes [9] , asthma [10] and obesity [11] . In addition , eQTL studies have shown that top hits from GWA studies are more likely to be eQTLs [12] , [13] and eSNPs are enriched for association to Type 2 diabetes ( T2D ) [14] . Focusing on SNPs that have been associated with an expression trait in the relevant tissue and testing whether such eSNPs are associated with disease could highlight novel genetic loci that fail to meet the stringent genome-wide significance level of GWA studies . Metabolic syndrome ( MetS ) is highly prevalent , occuring in up to 22% of US individuals , and is a serious public-health problem world wide [15] . Defined by The International Diabetes Federation ( IDF ) , it is characterized by central obesity plus the presence of two of four heritable metabolic abnormalities: raised TG; reduced HDL; hypertension; and hyperglycaemia . It is considered a serious risk factor of both T2D and cardiovascular disease [16] . Traditional approaches have highlighted insulin resistance , obesity , inflammation , and glucose and/or lipid metabolism to be important to the pathophysiology of the MetS [17] , [18] . Body fat distribution plays an important role due to its association with metabolic disorders . Individuals with increased intra-abdominal/visceral fat ( high waist-to-hip ratio ( WHR ) ) are at high risk of MetS , whereas those with increased subcutaneous fat in the gluteofemoral region ( low WHR ) are at little or no risk of MetS [19] , [20] . The adverse metabolic risk of visceral fat has been attributed to distinct metabolic properties of adipocytes in this fat depot compared with those in other sites , including differences in metabolic responses , gene expression , adipokine secretion and insulin action [21]–[23] . In addition , GWA studies have identified multiple loci that modulate body fat distribution independent of overall adiposity [24] . The estimated heritability of MetS ranges from 0 . 10 to 0 . 51 , whilst that of the individual traits that constitute MetS range from 0 . 13 to 0 . 72 [25]–[27] . The clinical clustering of individual MetS traits may be explained by shared genetic and environmental factors contributing to their origin [25] . GWA studies on the individual metabolic traits have identified many genetic loci , however , a much smaller number of genetic factors that influence MetS as a clinical entity have been identified ( www . genome . gov/gwastudies , accessed 02-03-2011 [28] ) . It is likely that for a clinical entity such as MetS comprising multiple complex trait components , there is considerable genetic heterogeneity in causal pathways . Therefore examining many genes simultaneously using a systems-based approach , such as weighted gene co-expression network analysis [29] , may be more powerful than analysing single-gene effects . A previous eQTL study in adipose tissue has led to the identification of a macrophage-enriched metabolic network which was enriched for eQTL signals and associated with obesity-related traits [11] . However , the focus of most eQTL studies so far has been on single tissue networks ignoring the fact that complex clinical entities such as MetS are the result of interactions of multiple molecular networks operating within and between tissues . In addition , it is not often recognised that molecular phenotypes such as gene expression traits are influenced by biological and technical variation , affecting power of association detection . To uncover eQTLs in tissues relevant to MetS , we analysed gene expression profiles in abdominal ( ABD ) and gluteal ( GLU ) adipose tissue , and whole blood ( WB ) , from 73 individuals , allowing the investigation of differential regulation between different adipose depots applying both single-gene and a network approaches . Using a second independent cohort comprising 145 and 141 twins with ABD and WB expression data collected longitudinally across two visits , we demonstrate the relative contribution of familial , environmental , and experimental variability to the MetS-associated expression phenotypes . Lastly , we identify a set of SNPs associated with the expression of genes in selected MetS-associated modules showing differential expression between the adipose depots , and test these eSNPs for association with MetS-related phenotypes in two large GWA cohorts .
Figure S1 shows the study design . Using Affymetrix hgu133plus2 arrays , we analysed ABD , GLU and WB samples from 29 MetS cases and 44 controls from the MolOBB study . For each subject , we collected six quantitative traits used to define MetS including waist circumference , systolic and diastolic blood pressure , TG , HDL and fasting glucose levels . We defined MetS according to IDF Criteria [16]: central obesity , as assessed by waist circumference plus any two of the following four components ( raised TG , reduced HDL cholesterol , raised blood pressure , raised fasting plasma glucose ) ( Table 1 ) . After filtering for high-quality array data , we limited further analyses to 54 , 65 , and 68 individuals and those probesets that showed a mean intensity above 4 arbitrary units of log2 ( intensity ) in at least 10% of individuals resulting in 8941 ( ABD ) , 8307 ( GLU ) and 6909 ( WB ) gene expression profiles ( probesets were mapped to Entrez Genes ) , respectively ( see Methods ) . We identified 893 and 335 genes showing significant expression changes with MetS in ABD and GLU applying a 1% False Discovery Rate ( FDR ) correction [30] with 210 genes overlapping ( ‘single-gene analysis’ ) ( Figure 1 , Table S1 , Table S2 ) . Hierarchical clustering of the differentially expressed genes showed distinct clustering of the majority of MetS cases . Clustering was independent of gender or the presence of specific subsets of the two MetS components as defined in the IDF criteria ( waist circumference plus any two of the four MetS components ) ( Figure 1 ) . The large overlap between the two fat depots supports the robustness of the data and consistency across fat depots . Among the top 10 genes that were associated with MetS was KCTD10; SNPs at this locus were previously associated with HDL [31] ( Figure 1C ) . To validate these findings further , we compared previously implicated MetS-associated loci [32] and obesity-related gene expression differences [11] with the MetS-associated expression differences in our study . This comparison revealed consistency for MetS-associated expression differences including LPL , C3AR1 , HSD11B1 , and FAT3 in ABD and APOE , FAT3 and FNDC4 in GLU ( Table S3 , Table S4 ) . None of the genes was differentially expressed between MetS cases and controls in WB although for the individual MetS components ( 122 genes for waist circumference , nine genes for TG and one gene for HDL ) significant gene expression differences were identified ( not shown ) . Only two of these genes , ATP5E and BLVRB showed significant expression changes with multiple MetS components ( waist circumference ( FDR P = 9 . 0 *10−3 ) and TG ( FDR P = 0 . 01 ) ; waist ( FDR P = 5 . 7 *10−3 ) and HDL ( FDR P = 4 . 3 *10−3 ) indicating that MetS gene expression differences were more pronounced in the fat depots , which became the main focus of further analysis . The distribution of adipose tissue between ABD and GLU depots varies between individuals and this variation is associated with MetS and some of the WHR-associated loci have shown depot-specific differences in expression patterns and/or an enrichment of associations with metabolic phenotypes [24] . This led us to test the hypothesis that MetS-associated expression differences found for genes expressed in both depots might reflect depot-specific expression differences . Whereas 8 . 9% and 13% of the genes associated with MetS in ABD or GLU only exhibited depot-specific differential expression , 44 of the 210 overlapping MetS-associated genes ( 21% ) including KCTD10 and C3AR1 showed evidence for depot-specific expression changes . These findings support the hypothesis that , at least for some genes , the associations with MetS reflect depot-specific differences . A Pearson correlation matrix ( containing an estimate of each pairwise correlation between gene expression levels , irrespective of MetS status ) was calculated and transformed into a matrix of connection strengths using a power function resulting in a weighted network ( see Methods and [33] ) . Using these connection strengths , genes were clustered in distinct groups of highly connected genes ( modules ) . For each gene in a module , we calculated the Module Membership ( MM ) by correlating its gene expression profile with the module eigengene ( the first principal component of the gene expression profiles in each module ) . Genes with high MM values to the respective module are considered hubgenes ( see Methods and [30] ) . We constructed gene networks separately for each of the three MolOBB tissue datasets and identified 20 , 26 and 18 modules in ABD , GLU and WB , respectively . To distinguish between modules , each module was assigned an arbitrary color . Figure S2 depicts a hierarchically clustered connectivity matrix of the ABD dataset and the 20 identified modules . We examined the biological significance of the identified modules by testing for 1 ) association with MetS 2 ) enrichment of Gene Ontology ( GO ) terms 3 ) hubgenes and 4 ) previous implicated genes . For the former , we extracted the first principal component of the gene expression profiles in each module ( module ‘eigengene’ ) and tested its association with MetS ( see Methods ) . From the 20 , 26 and 18 modules found in ABD , GLU and WB , nine , six and zero modules , respectively , were associated with MetS ( FDR P<0 . 01 , Table 2 ) . Four of the nine ABD MetS-associated modules and two of the six GLU MetS-associated modules showed a significant ( FDR P<0 . 01 ) enrichment of GO terms ( Table 3 ) . In the ABD brown module , the eigengene was downregulated for MetS cases compared to MetS controls indicating that genes positively correlated with the eigengene ( MM>0 ) were downregulated in MetS cases . This module was enriched for GO Biological Processes related to oxidative phosphorylation pathways ( GO: 0006082 organic acid metabolic process ( FDR P = 7 . 9*10−7 ) and GO:0006091 generation of precursor metabolites and energy ( FDR P = 7 . 5*10−7 ) . For these GO categories , the majority of the genes ( more than 84% of genes with MM>0 ) were downregulated in MetS cases . The genes in these GO categories had a higher median MM ( MM>0 . 74 ) than the 877 genes in the module ( MM = 0 . 51 ) showing functional relevance of these genes in the module . Furthermore , among the top 10 genes with the highest rank of membership ( hubgenes ) , eight were previously implicated in mitochondrial processes including generation of metabolites and energy ( ATP5B , ACO2 , SUCLG1 and UQCRC ) , oxidation reduction ( MOSC1 , MOSC2 , LDHD ) and fatty acid oxidation ( ECHS1 ) ( Table S5 , Figure 2A ) . This module contained the genes LPL , FAT3 and PPMG1 for which SNPs were previously associated with MetS ( Table S4 ) [32] . The eigengene of the ABD cyan module was upregulated for MetS cases compared to MetS controls and genes in this module were enriched for immune response related GO categories . CD163 , C1QB , C1QC and C3AR1 , which are involved in the inflammatory response and/or complement cascade were among the strongest hubgenes ( Table S5 ) . This module contained three of seven reported genes ( C3AR1 , HSD11B1 and CD68 ) with a highly significant MM ( MM>0 . 75 ) from a previously identified macrophage-enriched metabolic network in subcutaneous adipose tissue in humans and mice that was associated with obesity-related traits and enriched for inflammatory response and macrophage activation pathway [11] ( Table S3 ) . In addition , CD163 encodes a monocyte/macrophage specific receptor whose soluble form ( sCD163 ) is elevated in T2D and obesity [34] . Although , gene identity and connectivity strength of the previously published module was not available , which is required for a comprehensive comparison between studies , the modules might represent similar immune-response related processes in ABD . For the GLU samples , the brown module showed an enrichment for glucose metabolic processes ( GO:0045913 positive regulation of carbohydrate metabolic process ( FDR P = 3 . 8*10−3 ) ) . For the darkgreen GLU module eigengene , the strongest MetS-associated module in GLU and associated with all MetS components ( FDR P<0 . 01 ) , an upregulation among MetS cases was observed as compared to controls . No significant enrichment of GO terms was observed among the genes in the module ( Table 3 ) . Among the top 10 of hubgenes in the darkgreen GLU module , were GLUL ( MM = −0 . 89 ) and PHLDA2 ( MM = 0 . 84 ) ( Table S5 , Figure 2B ) . Both these genes are highly differentially expressed between depots ( FDR P<0 . 01 ) . GLUL , encoding glutamate synthase , showed lower expression levels in GLU , as compared to ABD but the relation of this gene to MetS is unknown . PHLDA2 encoding pleckstrin homology-like domain , family A , member 2 was upregulated in GLU as compared to ABD and is known to be involved in fetal growth with elevated placental expression associated with low birth weight [35] . To investigate to what extent gene expression probesets identified in the single-gene analyses as associated with MetS were included in the MetS-associated modules , and signified hubgenes , the correlation between MM and gene significance ( direct association between gene expression probeset and MetS from single-gene analyses ) was calculated for each gene expression probeset ( see Methods and [33] ) . For 862/893 ( 97% ) and 238/335 ( 71% ) of the MetS-associated probesets in ABD ( p<0 . 01 , MM>0 . 36 ) and GLU ( p<0 . 01 , MM>0 . 41 ) , a significant association with a MetS-associated module eigengene was found ( 147 probesets were overlapping ) . For the ABD brown ( Pearson ρ>0 . 41 , p<10−36 ) and the GLU darkgreen modules ( Pearson ρ>0 . 57 , p<10−9 ) most significantly associated with MetS ( Table 2 ) , the correlations between gene significance for MetS and the individual MetS components and MM were highly significant ( Figure 3 , Figure S3 ) . These results imply substantial concordance in results between the two approaches and support the increased power of the network-based approach by reducing the number of tests significantly . A further advantage of the network approach is the identification of distinct functional modules within single-tissue networks that associated with MetS . Genes that fall into these modules were more highly connected than with genes in other modules ( Figure S2 ) and their relevance can be inferred based on the correlation with the eigengene . The MetS-associated modules were enriched for immune response and oxidative phosphorylation pathways consistent with studies showing that adipose tissue secretes factors that regulate energy homeostasis and the immune response and the activation of inflammatory signalling pathways that emerges in the presence of obesity , insulin resistance and T2D [11] , [36] . MetS is a complex trait that is manifested in multiple tissues and where regulatory processes may act specific to a tissue as well as across tissues . The regulatory processes that play a role within a tissue may differ from those processes across tissues . It is likely that if modules of coexpressed genes are preserved among tissues , these modules may highlight communication between tissues and elucidate biological pathways that are shared among the tissues . Studying differential expression of individual genes in the module may reveal differences in pathway regulation across tissues . To examine to what extent biological processes underlying MetS are shared and differentially regulated among the different adipose depots , we first examined the overlap of expressed genes between ABD and GLU ( Figure S4 ) . Of 8992 probesets expressed in ABD or GLU , 685 ( 7 . 6% ) were expressed in ABD; 51 ( 0 . 6% ) in GLU and 8256 ( 92% ) in both adipose depots . For 679 of the 8256 probesets ( 8 . 2% ) , differential expression between depots was found ( FDR P<0 . 01 ) . GO analysis of the 685 ABD-only probesets showed enrichment for common GO terms ( GO:0051171∼regulation of nitrogen compound metabolic process ( FDR P = 7 . 5*10−3 ) ) and other gene transcription terms whilst analysis of the 51 GLU-only probesets showed no enrichment . The enrichment of gene transcription categories among genes expressed in ABD only might suggest regulatory processes specific for ABD rather than genes that are able to induce gene activity changes in other tissues . The large overlap of expressed genes among ABD and GLU , however , suggest the existence of shared processes or at least communication between tissues . To examine whether the eigengene networks are similar across fat depots , we calculated spearman correlations for the median expression ( ρ = 0 . 98 , p<1*10−10 and whole-network connectivities ( ρ = 0 . 66 , p<1*10−10 ) between ABD and GLU ( Figure S5 ) . These significant correlations suggest that the ABD and GLU networks are comparable . Next , we applied differential eigengene network analysis on 8256 genes that were expressed in both the ABD and GLU datasets [29] . In this analysis , we detected 22 consensus modules , i . e . , modules that are shared by the ABD and GLU datasets . To identify differences in pathway regulation between ABD and GLU depots , we examined the relationship between all pairs of the consensus module eigengenes represented by consensus networks ( see Methods and [29] ) . For each individual eigengene within an adipose depot , we found that its relationship with the other eigengenes was highly preserved across the adipose depots , with an overall preservation network density D ( PreservABD , GLU ) of 0 . 89 ( see Methods; Figure S6 ) . To assess the relevance of the consensus modules for MetS , we tested the consensus module eigengenes for association with MetS ( Table S6 ) . Eigengenes of seven consensus modules ( six in ABD and six in GLU ) were associated with MetS of which five modules were overlapping ( FDR P<0 . 01 ) ( Table S6 ) , suggesting that , in general , the effect of consensus modules on MetS was not characterized by different patterns of coexpressed genes between different adipose depots . The yellow module eigengene showed the strongest association with MetS in both the ABD ( FDR P = 1 . 4*10−5 ) and the GLU dataset ( FDR P = 4 . 6*10−6 ) and was upregulated in MetS cases as compared to controls in both fat depots . The genes in this yellow module were enriched for immune response related processes ( Table S7 ) . Among the hubgenes of the yellow module , that is , the genes with the highest rank of module membership in both networks , were C3AR1 , CD163 and c22orf9 and NPC2 ( Figure 2C and 2D and Table S8 ) . Consistent with the overlap of hubgenes between the cyan ABD module and the consensus module , the module eigengenes of ABD cyan and the yellow consensus module were highly correlated ( ρ = 0 . 97 , p<1*10−10 ) and contained many common genes ( 310 genes ) . The yellow module eigengenes in ABD and GLU were highly correlated ( ρ = 0 . 81 ) and not differentially expressed ( p = 0 . 64 ) . However , 94 genes of the 620 genes ( 15% ) were differentially expressed between depots ( FDR P<0 . 01 ) which were enriched for the GO-term: GO:0009611 response to wounding ( FDR P = 2 . 3*10−3 ) ( see Methods ) . Among these differentially expressed genes , were the hubgenes C3AR1 , C1QC , CD163 involved in the complement cascade suggesting that the inflammatory response overlapping in the fat depots are regulated through common genes . . Thus , the results suggested the presence of a specific , highly preserved Mets-associated module enriched for immune response pathways containing a significant number of inter-depot differentially expressed genes which may indicate differential regulation between adipose depots . Variation of gene expression traits may be driven by biological as well as experimental factors . Characterizing and quantifying sources of variation of gene expression traits or module eigengenes is important for the identification of regulatory genetic variants . In a separate dataset ( MolTWIN ) of 154 healthy twins , we retained gene expression of 202 ABD and 191 WB samples from 145 and 141 twins after quality control , respectively ( 202/191 visits , with 29/26 duplicate measurements ( see Methods ) ) . To examine whether the two independent ABD datasets were comparable , spearman correlations for the median expression ( ρ = 0 . 96 , p<1*10−10 ) , whole-network connectivities ( ρ = 0 . 51 , p<1*10−10 ) and the intramodular connectivities for the brown module ( ρ = 0 . 71 , p<1*10−10 ) were calculated using the module assignments from MolOBB to calculate the connectivities ( Figure S7 ) . The significant correlations suggested that the ABD networks were comparable . The MolTWIN dataset allowed us to decompose the biological and experimental variation underlying an expression trait into five components: familiality ( genetic and common environment effects shared by twin pairs ) ; individual environment ( unique for twin individual ) ; common visit and individual visit effects , which respectively measure the amount of shared ( by twins within a pair ) and non-shared variation occurring in the phenotype over the sampling period . The residual component of variation comprised experimental effects ( two technical replicates of the same sample ) . Familiality and individual environment variation assess longitudinally stable , and common and individual visit variation , short-term biological components . Although , our main focus –given the size of the MolTWIN datasets– was on estimating familiality , we also included heritablity estimates for contrast and completeness ( Table S9 ) . We assessed the relative proportions of the five sources of variances using a twin mixed-effects modelling approach ( see Methods ) retaining 6787 probesets expressed in MolTWIN ABD and WB , and for four groups of probesets selected for association with MetS in MolOBB identified in single-gene analysis and expressed in MolTWIN and in MolOBB 1 ) 626/893 ABD probesets; 2 ) 205/335 GLU probesets; 3 ) 121/210 probesets with expression in both tissues and 4 ) 22/121 differentially expressed probesets ( see Methods ) . Familiality was the largest source of variation that contributed to the variance of the gene expression traits in ABD and WB ( Figure 4 , Text S2 ) . The four groups of MetS-associated probesets showed similar familiality patterns , and their median familiality estimates were significantly higher compared to the probesets not associated with MetS , in both MolTWIN ABD and in WB ( Table S9 ) . Also , the groups of MetS-associated probesets showed a greater median familiality in ABD than in WB ( Table S9 ) . The highest median estimates were found for the 121 probesets associated with MetS in ABD+GLU ( 0 . 43 , IQR: 0 . 18 ) , and the 22 associated with MetS and differentially expressed between ABD and GLU ( 0 . 41 , IQR: 0 . 15; Table S9 ) . In addition to familiality , we estimated heritabilities for the groups of MetS-associated probesets , and the heritability patterns were similar as the familiality patterns in ABD but not in WB which might suggest an enrichment of genetic signals in ABD but not in WB . We also used the MolTWIN data to characterize the sources of variation underlying the eigengenes of the MetS-associated modules from the MolOBB data . Rather than constructing networks in MolOBB and MolTWIN separately , we calculated module eigengenes in the MolTWIN study using the module assignments from MolOBB and decomposed the module eigengenes into the five variance sources as described above ( Figure 5 , Text S2 ) . The variability patterns of the eigengenes were consistent with the results for probesets identified using the single-gene approach . Median familiality estimates from MolTWIN ABD ( Figure 5A ) were greater for MetS-associated module eigengenes than those not associated with MetS in MolOBB ABD ( median = 0 . 48 , IQR = 0 . 30 vs median = 0 . 18 , IQR = 0 . 28 , p = 0 . 08 ) and GLU ( median = 0 . 54 , IQR = 0 . 10 vs median 0 . 20 , IQR = 0 . 28 , p = 7 . 8*10−4 ) . This pattern was not observed for familiality estimates derived from MolTWIN WB ( Figure 5B ) . For the MetS-associated modules , median heritability estimates were significantly greater than for modules not associated with MetS in ABD ( median = 0 . 41 , IQR = 0 . 27 vs median = 6 . 9*10−5 , IQR = 0 . 25 , p = 0 . 03 ) and GLU ( median = 0 . 65 , IQR = 0 . 32 vs median = 0 . 14 , IQR = 0 . 28 , p = 0 . 007 ) . To assess whether specific genetic loci were associated with MetS-associated gene expression in ABD and GLU , we performed cis eQTL analyses ( cis defined as SNP location within 500 kb of the gene start or stop position; eQTLs are defined as genomic loci that regulate expression levels of mRNAs or proteins ) . For the ABD eQTL analysis , we used both ABD datasets ( MolOBB and MolTWIN ) comprising 189 individuals whilst for the GLU dataset we used 62 individuals from the MolOBB dataset . Out of the 8242 ABD genes tested , we found 1287 cis eQTL genes ( FDR P<0 . 01 ) using a fixed-effects meta-analysis [37] . We found evidence for an eQTL in cis for 77 of the 893 probesets associated with MetS in the single-gene meta-analysis . Six of these eQTL genes showed significant inter-depot differences ( Table 4 ) . For the GLU eQTL analysis , 628 of the 8307 tested genes had an eQTL in cis ( empirical p<0 . 01 , see Methods ) . We found a cis eQTL for 6/335 genes associated with MetS . Two of these genes ATP8B4 and LTBP2 , exhibited differential expression between ABD and GLU ( Table 4 ) . Only one of these MetS eSNPs ( an eSNP has been defined as a SNP associated with an expression trait ) , rs8207 , affecting PHOSPHO2 expression levels , was found in both ABD and GLU analyses but none of the corresponding expression probesets showed significant differences between adipose depots ( Table 4 ) . We similarly calculated cis eQTL associations for probesets in the ABD brown and GLU darkgreen modules most significantly associated with MetS in MolOBB . For 124/877 genes in the ABD brown module ( 877 tests ) , we found evidence for an eQTL in cis . For 14/124 genes , a high MM ( p<0 . 01 ) and a significant association with MetS was found ( Table 4; Figure 3 ) . For the GLU darkgreen module comprising 107 genes , we found two eQTL genes that were significantly associated with MetS and high MM ( p<0 . 01 ) ( Table 4; Figure S3 ) . For the yellow consensus module ( 620 genes ) , shared between ABD and GLU datasets , we found 69 and 26 genes with evidence for an eQTL in cis in ABD and GLU respectively; five eQTLs in ABD and four eQTLs in GLU , had corresponding genes exhibiting interdepot expression differences ( Table 4 ) . To validate the eQTL analysis , we evaluated 29 SNPs and their proxies ( r2>0 . 5 ) that were associated with MetS in a GWA of 22 , 161 participants [32] . In both ABD and GLU , an eQTL for HERPUD1 ( rs3764261 ) was found ( Table S4 ) . Modules are groups of highly correlated genes and could be the result of transcriptional co-regulation . We examined whether we could find genomic hotspots i . e . genetic loci that regulate multiple genes that are coexpressed within the module . We tested the module eigengenes of the ABD brown , GLU darkgreen and yellow consensus modules for association with 296 , 017 SNPs . After multiple testing correction ( FDR P<0 . 05 ) , we found the 21q22 . 13 locus ( rs2835630 , p = 1 . 4*10−7 , FDR P = 0 . 04 ) significantly associated with the ABD brown module eigengene and the 6p21 locus ( rs909982 , p = 8 . 3*10−8 , FDR P = 0 . 02 ) associated with the GLU darkgreen module . The SNP at the 21q22 . 13 locus was within the Down Syndrome Critical Region in a high LD region containing the TTC3 and DSCR9 genes . Of the two genes , only TTC3 was expressed in ABD . This gene was not differentially expressed between MetS cases and controls ( p = 0 . 01 , FDR P = 0 . 06 ) and assigned to the turquoise module ( MM = −0 . 62 , P = 3 . 4*10−7 ) . Remarkably , TTC3 is an E3 ligase facilitating ubiquitination and degradation of phosphorylated Akt [38] whereas Akt has a key role in metabolic regulation . The SNP at the 6p21 locus was in the intronic region of LRFN2 . This gene was however not expressed in GLU and plays a role in neuronal development . These loci may act as a master regulator of the genes in the module mediating a gene expression regulatory mechanism . To validate our results , we tested our prioritised eSNPs for association with MetS-related phenotypes using data from two large GWA cohorts . Based on the eQTL analyses , we prioritised a set of 32 eSNPs that were associated with MetS-associated probesets/modules ( Table 4 ) : 15 eSNPs associated with probesets in the most significant ABD ( brown ) module , three eSNPs in the most significant GLU ( darkgreen ) module , and 14 eSNPs associated with genes exhibiting inter-depot differences in the consensus ( yellow ) module and/or with the single-gene models ( nine of which were also significantly associated with MetS ) . The 32 eSNPs were tested for association with individual phenotypic components of MetS and the fourteen eSNPs exhibiting ABD-GLU inter-depot differences were tested for association with WHR-adjBMI ( Table 4 ) : Association with BMI and WHR-adjBMI was assessed using data from the GIANT consortium comprising ∼120 , 000 individuals and with HDL and TG in >100 , 000 individuals from a large-scale publicly available lipid study [4] . For each of the four clinical phenotypes , a Bonferroni-adjusted significance threshold of 1 . 6*10−3 was chosen such that Pr ( Number of False Positives >0 ) <0 . 05 by correcting for 32 SNP-clinical phenotype associations . This threshold was corresponding to a FDR of 0 . 03 across 110 tests . Adopting a much simplified scenario given the complex correlation structure of the MetS-related traits , we found three significant associations which was more than expected by chance; assuming independence between the 110 tests , the binomial probability was 7 . 3*10−4 . SNP rs10282458 , was significantly associated with gene expression levels of the adipokine RARRES2 encoding chemerin , and was significantly associated with BMI ( genomic control corrected p = 6 . 0*10−4 ) . RARRES2 gene expression levels showed a familiality of 0 . 53 in the MolTWIN ABD dataset and were highly connected with the brown module eigengene ( MM = 0 . 83 ) . In MolOBB , expression levels of RARRES2 were strongly associated with MetS ( p = 1 . 9*10−5 ) and with the individual components of MetS: waist ( p = 1 . 6*10−8 ) , HDL ( p = 2 . 0*10−5 ) and diastolic blood pressure ( p = 1 . 5*10−4 ) . SNP rs2395185 , which affected expression levels of HLA-DRB1 , was significantly associated with HDL ( genomic-control corrected p = 8 . 7*10−4 ) . Expression levels of HLA-DRB1 showed a familiality of 0 . 59 in MolTWIN ABD and were correlated with waist circumference ( p = 2 . 9*10−5 ) and HDL ( p = 5 . 3*10−5 ) in MolOBB . Next , we tested the 14 eSNPs that were associated with ABD-GLU inter-depot differences and rs10282458 for association with WHR-adjBMI in the GIANT consortium . By focusing on WHR after adjustment for BMI , we anticipated to detect associations with body fat distribution independent of those influencing overall adiposity . SNP rs10282458 was indeed associated with BMI but not with WHR-adjBMI ( Table 4 ) . We found one significant association ( genomic-control corrected ) between eSNP rs2395185 , influencing HLA-DRB1 expression levels in ABD and GLU , and WHR-adjBMI ( p = 2 . 4*10−4 ) . These results may suggest that differential regulation of the HLA-DRB1 region is associated with WHR-adjBMI .
Given that many molecular processes in multiple tissues could be involved in the onset of MetS , we genotyped and profiled gene expression in WB and two different adipose depots , ABD and GLU , from 73 individuals . After constructing coexpression networks for each tissue independently and between tissues , we identified MetS-associated modules of coexpressed genes enriched for immune response and oxidative phosphorylation pathways in adipose depots but not in WB . By testing eSNPs , that were associated with expression of the genes in the MetS-associated modules , for association with MetS-related phenotypes in large scale GWA datasets , we found associations with RARRES2 and HLA-DRB1 . Thus , by constructing networks across and within different adipose depots combined with single-gene analysis , two signals which had not reached genome-wide significance in GWA datasets of more than 100 , 000 individuals were identified . Adipose tissue is a dynamic endocrine organ that secretes proteins such as cytokines and hormones , collectively named adipokines . Adipokines may regulate energy and vascular homeostasis , as well as inflammatory processes , and are involved in glucose and lipid metabolism . Chemerin , encoded by RARRES2 , is an adipokine known to play an important role in adipogenesis and metabolic homeostasis and modulating chemotaxis and activation of dendritic cells and macrophages [39] , [40] . In humans , chemerin levels are associated with multiple components of MetS including BMI , plasma TG , hypertension , and HDL [41]–[43] . In a study of Caucasian individuals , a serum chemerin concentration of 240 ug/L was selected to diagnose MetS with a sensitivity of 75% and specificity of 67% [44] . Chemerin expression and secretion from adipose tissue increases with adipocyte differentiation and obesity [39] , [41] . Despite the evidence linking circulating chemerin levels with metabolic phenotypes , to our knowledge , this is the first study that identified loci near genes encoding chemerin for MetS-related phenotypes . A GWA study reported that serum chemerin levels were heritable and found a genetic association between the EIDL3 gene and serum chemerin levels supporting a potential role for chemerin in angiogenesis [45] . Given the convergence of adipocyte and macrophage function , chemerin may provide an interesting link between chronic inflammation , often associated with obesity-related diseases , and obesity and metabolic function in human adipose tissue with MetS . In humans , variations in adipose tissue distribution is associated to different metabolic consequences , with abdominal increase of fat producing a much greater risk for metabolic traits than gluteofemoral fat , suggesting differential regulation between the two adipose depots [20] . We identified a MetS-associated module highly preserved across the two adipose depots and enriched for immune response pathways , with 15% of the probesets differentially expressed between tissues . A modest association between eSNP rs2395185 , influencing HLA-DRB1 expression levels in ABD and GLU , and WHR-adjBMI was found . The HLA-associated SNP found in our study has also been linked to ulcerative colitis [46] , [47] . Cis eQTLs of the HLA-DRB1 locus with other SNPs have previously been associated with Type 1 diabetes in liver tissue [9] and with cholesterol levels in omental and subcutaneous fat [4] suggesting differential regulation of this locus across different tissues . The specific identified genetic associations were found with a network approach rather than with single-gene association between expression and clinical traits , even though there was substantial concordance in results between the two strategies . Investigating coexpression networks may be a more powerful approach than a single-gene association analysis since most cellular components are connected to each other through regulatory , metabolic and protein-protein interactions and summarising coexpressed genes in a single eigengene reduces the number of tests significantly . In our study , we tested a set of SNPs , associated with expression of genes in MetS-associated expression modules in relevant tissues , with the hypothesis that these eSNPs are enriched for SNP-MetS associations . Testing this small SNP set for disease association in large GWAS cohorts revealed two SNP-disease associations , the signals of which would have been relatively weak in a genome-wide multiple-testing context . An additional motivation for utilising a network-based approach is that it is unlikely that MetS is a consequence of an abnormality in a single gene product , but reflects the perturbations of a particular functional module in the gene network by a complex interaction of genetic and environmental interactions [48] , [49] . The existence of distinct disease-specific functional modules is consistent with: findings from GWA studies observing that many genetic loci identified with GWAs for traits such as height , lipids and BMI may be not randomly distributed with respect to biological function [50] , genes associated with similar disorders show higher expression profiling similarity for their transcripts , and proteins involved in the same disease have an increased tendency to interact with each other [51] . We found an enrichment of oxidative phosphorylation genes in the most significant ABD gene network module , which is consistent with previous studies showing compelling evidence for mitochondrial dysfunction in association with insulin resistance and obesity [52] , [53] . Reduced mitochondrial biogenesis has been demonstrated in humans with MetS , coinciding with reduced ATP level and dysfunctional mitochondrial electron transport [54] , [55] . Mitochondrial dysfunction may lead to an increased production of Reactive Oxygen Species and consequently oxidative stress which is coupled to activation of inflammatory pathways and insulin resistance in adipocytes [36] , [56] . The network topology-based approach helps to uncover potential mechanisms that contribute to the shared pathophysiology of the multiple components of MetS . Defects in gene products that are part of the same pathway , may also affect other cellular functions , resulting in potential comorbidity effects . Consistent with this view , our results and those of other studies support the idea that the chronic low-grade inflammatory condition that is associated with obesity plays a role in the etiology of MetS [36] . Specifically , cells of the innate immune system , particularly macrophages , are crucially involved in adipose inflammation and systemic metabolic abnormalities [36] . CD163 , one of the hubgenes found this study , encodes a monocyte/macrophage specific receptor whose soluble form ( sCD163 ) is elevated in T2D and obesity [34] . It is however not clear whether obesity is the origin or whether inflammation is proximal to metabolic dysfunction [36]; a chronic excess of nutrients can trigger metabolic dysfunction and inflammatory responses simultaneously leading to metabolic excess which also leads to inflammatory responses . In any expression study , many expression traits associated with the disease will not necessarily be causative , but instead be mostly reactive to disease . In addition , expression levels represent measurements from a heterogeneous mixtures of cells . It is important to distinguish the effect of genetic variation on gene expression from other factors that are reactive to the disease or confounding factors that also correlate with expression variability . Both our single-gene and network-based results showed that the expression probesets and modules filtered by association with MetS had increasing familiality and heritability levels , which may suggest an enrichment of genetically relevant signals . Our results arose principally from the analysis of gene expression in ABD and GLU adipose depots , and not WB . In addition , the heritability of the genes associated with MetS in both ABD and GLU was high in ABD tissue of the twins but not in WB . Moreover , the proportion of variance that was explained by the fact that the twins attended the hospital together ( common visit effect ) was high in WB , indicating stronger short-term environmental effects on WB than ABD expression levels . These observations suggest that WB is not necessarily the tissue of choice to detect eQTLs that are of direct relevance to MetS . In conclusion , we performed an eQTL study in WB , ABD and GLU and highlighted two genetic loci associated with MetS mediated by gene expression variation . Considering many genes and their interactions influence complex traits such as MetS , the integrated analysis of genotype data and expression networks across multiple tissues relevant to the clinical traits under study is an efficient strategy to identify novel genetic associations , and may offer better targets for drug development .
The MolTWIN study was approved by St . Thomas' Hospital Research Ethics Committee ( EC04/015 Twins UK ) . The MolOBB study received ethical approval from Oxfordshire REC C ( 08/H0606/107 ) . All participants gave informed consent . The MolOBB study consists of 44 healthy controls ( 27 men , 17 women ) and 29 cases with MetS ( 16 men , 13 women ) between 39 and 56 years old that were collected from the Oxford Biobank as part of the MolPAGE consortium [57] . Based upon the IDF Criteria ( www . idf . org ) , MetS was assigned as central obesity ( waist circumference ( or BMI>30 kg/m2 ) plus any two of the following four factors: raised triglycerides , reduced HDL cholesterol , raised blood pressure or raised fasting plasma glucose [16] . Control subjects were selected to be discordant from the MetS cases ( Table 1 ) . From these individuals , ABD and GLU adipose and WB samples were taken . A total of 143 samples were obtained , with 71 subjects successfully donating both tissue types , and one individual donating only GLU . Subcutaneous adipose tissue from the abdominal wall is taken at the level of the umbilicus; subcutaneous gluteal tissue is taken from the upper outer quadrant of the buttock and WB samples were taken using EDTA and PAXgene tubes . Gene expression data is available at ArrayExpress ( E-TABM-54 ) . A total of 154 twins ( 56 monozygotic ( MZ ) pairs and 21 dizygotic ( DZ ) pairs ) , were ascertained from the UK Adult Twin registry at St . Thomas' Hospital [58] and recruited to participate in this study . Gene expression data is available at ArrayExpress ( E-TABM-325 ) . Eligible volunteers were healthy , Caucasian , post-menopausal females of Northern European descent , aged between 45–76 years old . Twins were checked for zygosity using a panel of 47 SNPs [59] . Each participant donated subcutaneous adipose tissue from the abdominal wall and WB; 34 MZ twin pairs donated samples during two visits whereas 21 DZ pairs and 22 MZ pairs donated samples during one visit . Both twins in a pair visited on the same day . For the WB samples , PAXgene tubes were used and RNA was extracted according to the manufacturer's protocol ( PAXgene , QIAGEN ) . Total RNA was extracted with TRIreagent ( SIGMA-ALDRICH , Gillingham , UK ) from the fat biopsies and quantified using a NanoDrop . For six of the MolOBB subjects and 30 of the MolTWIN subjects from the first visit ( 15 MZ pairs ) , RNA was split into two aliquots before labelling ( technical replicates ) . RNA was labelled using the MessageAmp II 96-well amplification kit ( Applied Biosystems , CA , USA ) . Labelled RNA was hybridized onto Affymetrix hgu133plus2 arrays washed , stained , and scanned for fluorescence intensity according to manufacturers protocols ( Affymetrix , Inc . , USA ) . For each tissue , RNA samples were randomised and extracted in batches of 12 samples , rerandomised before labelling in 96-well plates and hybridised in batches of 12 samples on a plate-row by plate-row basis . Quality control checks involved signal intensities , background intensity , expression of control genes and spike-ins , as well as a spatial representation of the intensities . To identify outliers further , principal components analysis was performed on the normalised gene expression dataset using the NIPALS algorithm . The majority of the probes on the hgu133plus2 arrays were collected into 17 , 726 non-overlapping probesets according to Entrez Gene annotations provided by Dai et al . [60] . After outlying arrays had been removed , there remained data in the MolOBB study from 54 ABD samples ( four in technical duplicate ) , 65 GLU samples ( five in technical duplicate ) and 68 WB samples . During 202 visits , 231 MolTWIN samples from ABD ( 29 technical replicates ) were successfully profiled from 145 individuals . From the WB samples , 217 MolTWIN gene expression profiles for 141 individuals were generated during 191 visits ( 26 technical replicates ) . All arrays were normalised concurrently across datasets for comparisons between tissues and separately for comparisons within a single tissue using GC robust multi-array analysis [61] . Gene-specific expression summaries were averaged across technical replicates of a sample . We then filtered the data , retaining only those probesets that were annotated to an autosomal location , and also showed a mean intensity above 4 arbitrary units of log2 ( intensity ) in at least 10% of individuals . After this filtering stage in the MolOBB , there remained 8619 probesets in the ABD-GLU dataset , 8941 in the ABD dataset , 8307 in the GLU and 6909 probesets in the WB dataset . In the MolTWIN study , 8928 probesets in the ABD dataset and 9071 probesets in the WB dataset remained . DNA was successfully extracted from WB samples using GeneCatcher ( Invitrogen Life Technologies , Carlsbad , USA ) according to manufacturer's protocol . 166 samples ( 70 MolOBB , 96 twins ( one MZ individual per MZ pair and two DZ individuals per DZ pair ) ) are genotyped with Illumina 317K BeadChip SNP arrays ( Illumina , San Diego , USA ) . Genotype data ( EGAS00000000102 ) is available at EGA . Quality control on the genotyped subjects was performed applying slightly changed quality control filters as described previously by the Wellcome Trust Case Control Consortium [62] . Two twin samples are removed due to sample success rate <95% and three samples ( two twins , one MolOBB ) were removed due to non European ancestry . SNPs are removed when minor allele frequency ( MAF ) <1% or showed a success rate <95% and MAF>5% , and when <99% and MAF<5% . Hardy-Weinberg equilibrium was calculated by combining all unrelateds of the MolOBB and MolTWIN dataset ( e . g . one twin per twinpair ) and SNPs were removed if P value<10−4 . After QC , genotypes of the ungenotyped MZ twin were copied from genotyped MZ twin . Finally , we included 69 MolOBB individuals and 144 twins genotyped for 296 , 017 autosomal SNPs . All code is available at http://www . well . ox . ac . uk/ggeu/PLoSGenet_Minetal_MolPAGE/ . | Metabolic Syndrome ( MetS ) is a highly prevalent disorder with considerable public health concern , but its underlying genetic factors remain elusive . Given that most cellular components exert their functions through interactions with other cellular components , even the largest of genome-wide association ( GWA ) studies may often not detect their effects , nor necessarily provide insight into the complex molecular mechanisms of the disease . Rather than focusing on individual genes , the analysis of coexpression networks can be used for finding clusters ( modules ) of correlated expression levels across samples . In this study , we used a gene network–based approach for integrating clinical MetS , genotypic , and gene expression data from abdominal and gluteal adipose tissue and whole blood . We identified modules of genes related to MetS significantly enriched for immune response and oxidative phosphorylation pathways . We tested SNPs for association with MetS–associated expression ( eSNPs ) , and tested prioritised eSNPs for association with MetS–related phenotypes in two large-scale GWA datasets . We identified two loci , neither of which had reached genome-wide significance levels in GWAs , associated with expression levels of RARRES2 and HLA-DRB1 and with MetS–related phenotypes , demonstrating that the integrated analysis of genotype and expression data from relevant multiple tissues can identify novel associations with complex traits such as MetS . | [
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] | 2012 | Coexpression Network Analysis in Abdominal and Gluteal Adipose Tissue Reveals Regulatory Genetic Loci for Metabolic Syndrome and Related Phenotypes |
Mutation screening of the breast cancer genes BRCA1 and BRCA2 identifies a large fraction of variants of uncertain clinical significance ( VUS ) whose functional and clinical interpretations pose a challenge for genomic medicine . Likewise , an increasing amount of evidence indicates that genetic variants can have deleterious effects on pre-mRNA splicing . Our goal was to investigate the impact on splicing of a set of reported variants of BRCA2 exons 17 and 18 to assess their role in hereditary breast cancer and to identify critical regulatory elements that may constitute hotspots for spliceogenic variants . A splicing reporter minigene with BRCA2 exons 14 to-20 ( MGBR2_ex14-20 ) was constructed in the pSAD vector . Fifty-two candidate variants were selected with splicing prediction programs , introduced in MGBR2_ex14-20 by site-directed mutagenesis and assayed in triplicate in MCF-7 cells . Wild type MGBR2_ex14-20 produced a stable transcript of the expected size ( 1 , 806 nucleotides ) and structure ( V1-[BRCA2_exons_14–20]–V2 ) . Functional mapping by microdeletions revealed essential sequences for exon recognition on the 3’ end of exon 17 ( c . 7944-7973 ) and the 5’ end of exon 18 ( c . 7979-7988 , c . 7999-8013 ) . Thirty out of the 52 selected variants induced anomalous splicing in minigene assays with >16 different aberrant transcripts , where exon skipping was the most common event . A wide range of splicing motifs were affected including the canonical splice sites ( 15 variants ) , novel alternative sites ( 3 variants ) , the polypyrimidine tract ( 3 variants ) and enhancers/silencers ( 9 variants ) . According to the guidelines of the American College of Medical Genetics and Genomics ( ACMG ) , 20 variants could be classified as pathogenic ( c . 7806-2A>G , c . 7806-1G>A , c . 7806-1G>T , c . 7806-1_7806-2dup , c . 7976+1G>A , c . 7977-3_7978del , c . 7977-2A>T , c . 7977-1G>T , c . 7977-1G>C , c . 8009C>A , c . 8331+1G>T and c . 8331+2T>C ) or likely pathogenic ( c . 7806-9T>G , c . 7976G>C , c . 7976G>A , c . 7977-7C>G , c . 7985C>G , c . 8023A>G , c . 8035G>T and c . 8331G>A ) , accounting for 30 . 8% of all pathogenic/likely pathogenic variants of exons 17–18 at the BRCA Share database . The remaining 8 variants ( c . 7975A>G , c . 7977-6T>G , c . 7988A>T , c . 7992T>A , c . 8007A>G , c . 8009C>T , c . 8009C>G , and c . 8072C>T ) induced partial splicing anomalies with important ratios of the full-length transcript ( ≥70% ) , so that they remained classified as VUS . Aberrant splicing is therefore especially prevalent in BRCA2 exons 17 and 18 due to the presence of active ESEs involved in exon recognition . Splicing functional assays with minigenes are a valuable strategy for the initial characterization of the splicing outcomes and the subsequent clinical interpretation of variants of any disease-gene , although these results should be checked , whenever possible , against patient RNA .
Germline pathogenic variants in the tumor suppressor genes BRCA1 ( MIM# 113705 ) and BRCA2 ( MIM# 600185 ) are associated with increased risk of breast and ovarian cancer [1 , 2] , and account for about 16% of the familial risk for breast cancer [3] . More than 25 breast cancer susceptibility genes have been identified so far , most of which play a role in the DNA repair pathway linked to BRCA1 and BRCA2 [4] . Additionally , a vast number of SNPs have been associated with breast cancer risk [5 , 6] , increasing the complexity of the genetic landscape of Hereditary Breast/Ovarian Cancer ( HBOC ) . Moreover , according to the BRCA Share Database ( http://www . umd . be/BRCA2/; last accessed date , April 2016 ) , more than 2700 different sequence variations have been reported at the BRCA2 gene , ~30% of which are causal . A large proportion of the recorded pathogenic variants truncate the BRCA2 protein ( nonsense and frameshift ) . However , up to 20% of BRCA1/2 tests report variants of uncertain clinical significance ( VUS ) [7] . These pose a challenge in genetic counselling as VUS-carrier families are usually considered as negative ( undetermined ) so they cannot benefit from prevention protocols [8] . In fact , other factors must be involved in the pathogenesis of genetic disorders since gene expression is regulated by a wide range of cis-regulatory sequences that control it , as for example , transcription initiation ( promoter ) [9] , pre-mRNA splicing [10] or post-transcriptional regulation and mRNA stability ( 3’UTR ) [11] . It is therefore expected that point mutations in those motifs can be correlated with gene expression alterations and disease . Interestingly , nearly 90% of disease-associated SNPs are placed outside protein-coding regions ( 45% intronic , 43% intergenic ) , suggesting a relevant role of the non-coding sequence variations [12] . Splicing is a central process of gene expression whereby introns are excised and exons are joined sequentially . It has been calculated that >90% of mammalian genes undergo alternative splicing which is controlled by a dense array of diverse cis-acting elements and splicing factors [10 , 13] . According to GENCODE ( V . 24 , http://www . gencodegenes . org/stats/current . html ) , the average number of protein coding transcripts per gene is ~4 . In this regard , it has been recently reported the existence of 24 naturally occurring alternative splicing events of the BRCA2 gene [14] . Alternative splicing not only allows transcriptome and proteome diversity , but it also regulates important processes such as embryonic development or cell differentiation . Exon recognition requires specific signals at the 5’ and 3’ splice sites , the polypyrimidine tract , the branch point , and supplementary sequences referred to as Exonic Splicing Enhancers ( ESE ) and Silencers ( ESS ) [15] . Interestingly , an unexpectedly large fraction of variants can actually disrupt pre-mRNA processing [16 , 17] . Remarkably , aberrant splicing is common in cancer so that it can be considered a hallmark of this disease [18] . We previously estimated that a significant proportion of likely pathogenic BRCA1/2 variants ( 33 . 9% ) from 14 exons would impair splicing [19] . The most suitable method to identify splicing aberrations is based on the study of patient RNA of the affected tissue although this sort of sample is not always available [20 , 21] . Nevertheless , direct RNA analysis of several disease genes , including NF1 ( MIM# 613113 ) and BRCA1/2 , has proven to be a highly sensitive method to identify splicing anomalies [22 , 23] . Minigene-based technologies have become alternative approaches to primarily test whether a specific DNA variant affects splicing , especially when patient samples cannot be collected . In a recent report we presented the new splicing reporter plasmid pSAD ( Patent P201231427-CSIC ) that constituted the backbone of the largest BRCA2 minigene ever reported with 9 exons ( 19 to 27 ) [24] . This construct allowed the analysis of 40 variants spread throughout these exons and flanking introns , demonstrating its capability for the successful identification and characterization of spliceogenic variants . Moreover , up to date , we have examined the impact on splicing of 112 different DNA variants by minigene assays , 51 of which induced aberrant splicing patterns [19 , 24 , 25] . The intronic GT dinucleotide in positions +1 and +2 is the most conserved element of the donor splice signal . However , in a small fraction of the donor sites ( <1% ) , GT is replaced by GC that are rather located in alternatively spliced introns [26 , 27] . Recognition of a GC donor site at the BTK gene was associated with splicing enhancers for SR proteins 9G8 , Tra2β and SC35 [27] . The BRCA2 intron 17 has also a 5’ GC motif and there have been identified minor natural alternative splicing isoforms Δ18 ( exon 18 skipping ) and Δ17 , 18 ( exons 17+18 skipping ) [14 , 28] . To study the regulatory mechanisms of both exons and how DNA variants affect this process we constructed a large minigene with exons 14 to 20 in the pSAD plasmid ( MGBR2_ex14-20 ) to keep the genomic context . Splicing regulatory elements were searched by functional microdeletion mapping . Finally , 52 variants detected in HBOC patients were selected and assayed in the minigene MGBR2_ex14-20 .
The efficient inclusion of the exons in the mature mRNA may require the presence of enhancer sequences and the binding to SR-proteins [29] . The highest density of active ESEs is near splice sites ( ~50 nt at both exon ends ) with a maximum between 10 and 20 nucleotides from the canonical 5’ and 3’ splice sites of each exon [30]; so DNA variants at these regions have a higher likelihood of disrupting ESEs . Furthermore , previous studies suggested a specific regulation of the donor GC-sites by ESEs [27] . We therefore proceeded to map regulatory sequences involved in exons 17 and 18 processing by functional tests of four exonic 30-nt deletions of each exon . These deletions covered the 5’ and 3’ 55 nucleotides of each exon excluding the first two and last three nucleotides . Three 30-nt microdeletions , c . 7944_7973del ( exon 17 ) , c . 7979_8008del ( exon 18 ) and c . 8004_8033del ( exon 18 ) , had impacts on splicing ( exon 17 or 18 skipping ) ( Fig 2A ) , indicating that these sequences probably contain regulatory motifs guiding exon recognition . According to the ESEfinder algorithm [31] , these sequences contain several putative enhancer sequences ( see Fig 2C ) , but only SF2/ASF and SRp40 motifs were present in the three deletions suggesting that these SR proteins might be required for competent exon identification . We then carried out the fine mapping of ESEs with additional internal 10-nt deletions of exons 17 [c . 7944_7953del ( del1 ) , c . 7954_7963del ( del2 ) and c . 7964_7973del ( del3 ) ] and 18 [c . 7979_7988del ( del4 ) , c7989_7998del ( del5 ) , c . 7999_8008del ( del6 ) , c . 8004_8013del ( del7; 5-nt overlap between del6 and del7 ) , c . 8014_8023del ( del8 ) and c . 8024_8033del ( del9 ) ] ( S2 Table; Fig 2B ) . The del2 and del3 deletions of exon 17 only disrupted splicing weakly ( 2 . 2% and 4 . 6% of aberrant transcripts , respectively; S3 Table ) whereas del1 did not at all . Exon 18 skipping was found at del4 , del6 and del7 . These segments must therefore contain splicing enhancer sequences . Deletions 5 , 8 and 9 of exon 18 did not affect splicing and produced the expected transcripts . According to the bioinformatics predictions of ESEs ( Fig 2C ) , the common feature of the three positive exon 18 deletions was the presence of two putative ESEs for SF2/ASF ( one in the overlapping segment of del6-7 ) at nucleotides c . 7981_7987 ( GATACGG ) and c . 8001_c . 8007 ( CAGAAGA ) . We then proceeded to disrupt both motifs by mutagenesis with the following sequence variations: c . 7984A>T , c . 8001C>T and c . 8003G>A , which target conserved nucleotides of the two SF2 motifs ( Fig 2C , S2 Table ) [31] . We carried out the assays with the triple mutant , a double mutant c . [8001C>T;8003G>A] , which targeted the SF2-II site , and the three independent variants ( Fig 2B and 2C ) . Intriguingly , only the triple and the double mutants remarkably impaired splicing with 59 . 7% and 44 . 2% of aberrant transcripts ( Fig 2B ) , respectively , but these effects were not observed either with c . 7984A>T or c . 8001C>T , which did not apparently affect splicing , whereas c . 8003G>A only induced weak exon 18 skipping ( 8 . 8% ) , suggesting a synergistic effect of these variants on splicing . We can conclude that these sequences are required for exon 18 recognition so that any variation in these nucleotides may affect splicing and confer breast cancer risk . In order to investigate the participation of SF2/ASF in this process , we initially performed inhibition experiments with siRNAs of splicing factors SF2/ASF , SC35 and Tra2β . Preliminary data unexpectedly suggested a role for SC35 in exons 17 and 18 definitions as well as small contributions of Tra2β and SF2/ASF ( S2 Fig ) . In fact , a putative SC35 motif ( GGCTATAA , c . 8010-8017 ) was located at the spliceogenic del7 deletion ( Fig 2C ) . We also searched for ESE sequences within intron 17 . Firstly , we selected a region of 115 nucleotides ( c . 7976+231_7977-141del ) where Human Splicing Finder ( HSF ) had predicted the presence of a notable concentration of high-scored Tra2β sites ( S2 Table ) , being Tra2β one of the SR-proteins involved in GC recognition in the BTK gene [27] . The presence of SREs was also checked in the rest of the intron 17 with another three deletions , c . 7976+21_7976+140del , c . 7976+136_7976+240del and c . 7977-150_7977-21del . However , none of them had an impact on splicing suggesting that regulatory elements of the GC site are not located within intron 17 . A total of 221 reported DNA variants ( BRCA Share , BIC and 1000 Genomes databases , last accessed date: April 2016 ) were analyzed with NNSPLICE and HSF . We selected fifty-four out of them ( 24 . 4% ) on basis of these criteria: splice site disruption or modification , creation of alternative splice sites , disruption of an ESE within positive 30-nt microdeletions , creation of silencers ( specifically hnRNPA1 sites ) ( S2 Table ) . Remarkably , 36 variants had previously been classified as VUS by the BRCA Share and BIC databases . All the selected DNA changes were introduced into the wild type MGBR2_ex14-20 construct by site-directed mutagenesis except for two ( c . 7829dup—exon17- and c . 8169_8172dup—exon18- ) that were disregarded because of the recurrent failure of the mutagenesis experiments . Fifty-two variants ( 17 of exon 17 and 35 of exon 18 ) were functionally tested in the splicing reporter minigene MGBR2_ex14-20 . All the transcripts were quantified to evaluate their possible implication in disease pathogenesis ( S3 Table ) . Only variants with ≥5% of anomalous transcripts were considered as positive . Thirty DNA variants ( 57 . 7% ) impaired splicing ( Table 1 , S3 Table , Figs 3 and 4 , S3 Fig ) , whilst another three variants ( c . 7875A>G , c . 7985C>T and c . 8042C>G ) had weak impacts on splicing ( 4 . 7% , 3 . 3% and 2 . 3% , respectively; S3 Table ) . All the splicing outcomes were highly reproducible with low intra-variability ( standard deviations <1 . 8% for 27 variants; S3 Table ) . Spliceogenic variants consisted of 14 intronic and 16 exonic variants that had previously been predicted as 11 missense , 1 nonsense , 1 frameshift and 3 synonymous variants , confirming that any type of genetic variant can potentially disrupt pre-mRNA processing . According to the prediction software and their location , 15 variants disrupted the canonical 3’ and 5’ splice sites ( c . 7806-2A>G , c . 7806-1G>A , c . 7806-1G>T , c . 7806-1_7806-2dup—previously reported as c . 7806insAG- , c . 7975A>G , c . 7976G>C , c . 7976G>A , c . 7976+1G>A , c . 7977-3_7978del , c . 7977-2A>T , c . 7977-1G>T , c . 7977-1G>C , c . 8331G>A , c . 8331+1G>T and c . 8331+2T>C ) , three disrupted the polypyrimidine tract ( c . 7806-9T>G , c . 7977-7C>G and c . 7977-6T>G ) , three created novel active splice sites ( c . 8023A>G , c . 8035G>T and c . 8168A>G , but also c . 7977-7C>G and c . 7806-1_7806-2dup—see above- ) , seven affected enhancer or silencer motifs ( c . 7992T>A , c . 8007A>G , c . 8009C>A , c . 8009C>T , c . 8009C>G , c . 8072C>T and c . 8249_8250del , all of them in exon 18 ) and two were presumed to alter ESE/ESS motifs and generate alternative sites ( c . 7985C>G—weak 3’ss- and c . 7988A>T—strong 5’ss- ) that actually were not used , so they should be considered as ESE/ESS-variants . Seven of the ESE/ESS variants were placed into the positive ESE-containing microdeletions c . 7979_8008del30 and c . 8004_8033del30 , spanning a 25-nt interval of exon 18 ( c . 7985-8009 ) . Variants of exon 17 and flanking intronic sequences rendered 6 different abnormal transcripts ( Fig 5 ) : ex17 skipping , ex17-ins8 ( alternative intronic acceptor 8 nt upstream ) , ex17-del1 ( novel acceptor 1 nt downstream ) , ex17-del20 ( alternative acceptor 20 nt downstream ) , ex17-del69 ( alternative acceptor 69 nt downstream ) and ex17-insAG ( novel acceptor 2 nt upstream ) , where exon 17 skipping was the most abundant event . Mutations at exon 18 and contiguous sequences induced more than 10 different aberrant transcripts ( Fig 5 ) : ex18 skipping , ex18-ins6 ( novel intronic acceptor 6 nt upstream ) , ex18-del191 ( alternative acceptor 191 nt downstream ) , ex18-del309 ( new donor 309 nt upstream ) , ex18-del298 ( new donor 298 nt upstream ) , ex18-del164 ( new donor 164 nt upstream ) , ex18-del157 ( use of cryptic donor 157 nt upstream ) , and rare phenomena such as ex17-del20+ex18 skipping ( cryptic acceptor plus skipping ) , ivs17_58 nt retention+ex18 skipping ( intronic cryptic donor plus skipping ) , one 878-nt transcript as well as other uncharacterized aberrant transcripts . Exon 18 skipping was the most frequent outcome ( 19 out of 21 variants induced it ) . Twelve transcripts would introduce premature termination codons ( PTC ) .
Splicing is specifically regulated by a dense array of motifs and splicing factors so that an important message of our study is that any nucleotide change has the potential of disrupting this process . In fact , the 30 positive changes comprised 14 intronic and 16 exonic variants including 11 missense , 1 frameshift , 1 nonsense and 3 synonymous predicted changes [43] . Synonymous variations are particularly interesting since they have traditionally been considered as neutral . Many sequence variations affect disease risk , including synonymous variants that , actually , may have unexpected deleterious effects over the splicing and protein translation mechanisms [44 , 45] . It has been shown that these variants account for 6–8% of all driver mutations in oncogenes , where about half of them impair splicing [46] . Conversely , protein truncating variants ( nonsense ) are directly classified as deleterious though we have herein shown that the associated-nucleotide changes can affect splicing regulatory elements , so we could observe a “dangerous” unclassifiable splicing effect whenever they induced in-frame deletions of an exon . With regard to the affected splicing motifs of positive variants ( Table 1 , S2 Table ) and taking into account the bioinformatics and splicing outcomes , we can conclude that 15 variants affected the natural 5’ and 3’ splice sites , three the polypyrimidine tract , three created novel alternative splice sites and 9 affected ESE/ESS motifs . The NNSplice , MaxEnt and HSF algorithms accurately anticipated the splice site disruptions and the generation of novel active sites , but the splicing outcomes were absolutely unpredictable reinforcing the current need of functional assays . The characterization of the physiological alternative splicing events of BRCA1 and BRCA2 [14 , 47] and improved computer tools will help to estimate the aberrant transcripts that a particular DNA variant may generate . It is also worthy to mention that three variants of the polypyrimidine tract , c . 7806-9T>G , c . 7977-7C>G and c . 7977-6T>G , produced defective splicing . Pyrimidine to Purine changes at this element are critical for exon recognition as we had previously described [25] . However , these modifications are barely identified by the splicing software with slight reductions of the splice site score ( S2 Table ) . For example , NNSplice of c . 7806-9T>G calculated a weak decrease of the 3’ splice site score of exon 17 from 0 . 95 to 0 . 83 , yet it was associated with a total splicing disruption . In silico predictions of ESE/ESS motifs , which are constituted by short-degenerate sequences , showed low sensitivity . Nevertheless , there have been recently postulated two in silico approaches , ΔtESRseq and ΔHZEI , that accurately detect potential ESE-variants [43] . We have found that 9 out of 28 pre-selected ESE/ESS variants affected splicing , so we have even improved its accuracy with respect to former studies by virtue of the functional mapping by microdeletions that has proven to be an exceptional method to refine ESE-variant selection . This strategy revealed the presence of operating ESEs in intervals c . 7944-7973 ( exon 17 ) and c . 7979-8008 and c . 8004-8033 ( exon 18 ) . Remarkably , 7 out of 9 ESE/ESS variants are placed within these intervals of exon 18 confirming the value of preliminary ESE-mapping to choose candidate variants and to fine map regulatory sequences . Interestingly , only the triple ( c . 7984 , c . 8001 and c . 8003 ) and double ( c . 8001 and c . 8003 ) mutants of SF2 sites significantly affected splicing whereas single mutants did not or did only weakly , suggesting a precise and compound control of exon 18 processing , where ESE sequences might act cooperatively . In this regard , while two possible SF2/ASF sites were bioinformatically predicted ( c . 7981_7987 , GATACGG , and c . 8001_c . 8007 , CAGAAGA ) ( Fig 2C ) , preliminary siRNAs experiments suggested the participation of the splicing factor SC35 in the regulation of exons 17 and 18 ( S2 Fig ) , which is also involved in the regulation of a pathological GC site of the BTK gene [27] . Nevertheless , the definite identification of the splicing factors involved in exons 17 and 18 processing should be carried out by further siRNA and pulldown assays [48] . Independently of the factors involved , these data allowed us to underline three small DNA segments ( c . 7944-7973 , c . 7979-7988 and c . 7999-8013 ) where spliceogenic ESE-variants may occur . Given the poor precision of ESE/ESS-prediction software ( 12 . 2% of selected variants ) [19 , 24] , these data will provide a very valuable information for genetic counselors with a view to selecting specific exonic mutations within those intervals for splicing assays . Donor-GC sites , such as that of exon 17 , have been linked to alternative splicing [26] so that they require the control by factors that promote their efficient selection [27] . Certainly , exons 17 and 18 undergo naturally-occurring alternative splicing producing minor transcripts Δ18 and Δ17+18 [28] , although in our study Δ18 was only detected at even lower levels in the wild type minigene ( <1%; S3 Table ) , together with the full-length transcript ( ≥99% ) . This may probably be due to: i ) the genomic context that influences exon recognition [15]; ii ) tissue-dependent alternative splicing as we used different host cells ( MCF-7 vs . HeLa ) ; and iii ) RNA preparation and storage conditions , primer design , PCR conditions , and PCR product detection methodology can introduce small variations in splicing isoform ratios as previously reported [14 , 42] . Identification of pathogenic variants with impact on splicing will aid in breast cancer prediction , prevention and surveillance , but the clinical interpretation of the splicing outcomes of candidate variants is a particularly complex task . It is accepted that a variant would be considered likely pathogenic when it causes a majority of aberrant RNA isoforms and generates a stop codon or loss of a known functional domain . The identification of numerous anomalous transcripts of exons 17 and 18 and the production of ≥2 transcripts by many variants are proofs of this arduous undertaking . Twelve transcripts introduced a frameshift in the open reading frame and a PTC so they inactivated BRCA2: ex17-del1 , ex17del20 , ex17ins8 , ex17insAG , ex18 skipping , ex18-del191 , ex18-del298 , ex18-del164 , ex18-del157 , ex18-del236 , ex17-del151+ex18 skipping and ivs17_58-nt retention+ex18 skipping . Conversely , exon 17 skipping , ex17-del69 , ex18-ins6 and ex18-del309 kept the reading frame with a priori unknown impact on BRCA2 function . Exon 17 skipping and ex17-del69 led to deletions of 57 and 23 amino acids , respectively , at the essential α-helical domain of the BRCA2 protein ( amino acids 2479 to 2667 ) . This domain facilitates BRCA2 binding to single-stranded and double-stranded DNA [49] . Moreover , 30 out of the 57 residues encoded by exon 17 are strictly conserved from sea urchin to human revealing its importance for BRCA2 activity ( IARC BRCA2 alignment; http://agvgd . iarc . fr/BRCA2_Align . htm ) . Likewise , it has been shown that the loss of exon 17 inactivates BRCA2 function [37] . Furthermore , exon 17 variant c . 7976G>A , which is associated with total exon 17 skipping , reached odds of causality of >3 , 000:1 [38] . Consequently , we can infer that the rest of the variants with ex17 skipping as the unique transcript , such as c . 7976G>C and c . 7976+1G>A , are also likely pathogenic . Moreover , variants c . 7806-9T>G and c . 7806-2A>G with at least 3 abnormal transcripts , including ex17 skipping , could also be considered as likely pathogenic , given that the other transcripts disrupt the reading frame ( Ivs16ins8 or ex17-del20 ) or leads to in-frame loss of 23 aminoacids ( ex17-del69 ) , 13 of which are strictly conserved . The RNA isoform ex18-ins6 would insert new amino acids Ser-Phe between Tyr2658 and Arg2659 . Precisely , amino acids from Val2652 to Asp2661 are conserved from sea urchin , and two missense changes at this protein segment , p . Leu2653Pro and p . Arg2659Lys were formerly classified as deleterious [38 , 50] . Consequently , transcript ex18-ins6 might have a deleterious impact on BRCA2 function but it is required further protein function studies . Finally , abnormal transcript ex18-del309 was predicted to cause an in-frame deletion of 103 amino acids between codons Ile2675 and Lys2777 of the OB1 ( oligonucleotide ssDNA-binding fold ) motif at the DNA binding domain of BRCA2 , 24 of which are strictly conserved from sea urchin . Variant c . 8023A>G , which induced ex18del309 , had previously been classified as pathogenic [21] ( BIC and UMD databases ) , so this transcript disrupts BRCA2 function . Also , c . 8331G>A might be an important risk allele as abnormal transcripts almost reach 60% , which is the suggested threshold for severe splicing aberrations [51] . According to the guidelines of the American College of Medical Genetics and Genomics ( ACMG ) , [52] 12 spliceogenic variants were classified as pathogenic ( c . 7806-2A>G , c . 7806-1G>A , c . 7806-1G>T , c . 7806-1_7806-2dup , c . 7976+1G>A , c . 7977-3_7978del , c . 7977-2A>T , c . 7977-1G>T , c . 7977-1G>C , c . 8009C>A , c . 8331+1G>T and c . 8331+2T>C ) and 8 as likely pathogenic ( c . 7806-9T>G , c . 7976G>C , c . 7976G>A , c . 7977-7C>G , c . 7985C>G , c . 8023A>G , c . 8035G>T and c . 8331G>A ) , under the splicing viewpoint ( S4 Table ) . Remarkably , all of them account for 72 independent records at the mutation databases ( S4 Table ) and nine of them had been classified as VUS . Reclassification of VUS as deleterious will notably increase the number of HBOC families who may benefit from tailored preventive and prophylactic measures as well as new targeted therapies , such as Poly ( ADP-ribose ) polymerase ( PARP ) -inhibitors , for patients with BRCA1/2 associated cancers [53] . It is also worthy to mention that causal and likely causal splicing variants account for a remarkable 30 . 8% ( 20/65 ) of all predicted pathological variants of exons 17 and 18 at the BRCA2 Share database ( S5 Table ) , representing the second more frequent type of causal variants after frameshift mutations ( 44 . 6% ) . On the other hand , two variants with weaker splicing alterations , c . 8168A>G/ p . Asp2723Gly ( 30% ) and c . 8249_8250del ( 7% ) , were previously classified as likely pathogenic ( protein function and truncation , respectively ) [38] , so their pathogenicity may probably be due to a double mechanism: protein inactivation and splicing disruption , like BRCA1 c . 5123C>A ( p . A1708E ) [25 , 54] . Likewise , c . 8009C>A was previously classified as causal because of its predicted nonsense change ( p . Ser2670X ) , but it actually induces 96% of aberrant transcripts so it should be reclassified as a spliceogenic variant . Reclassification of missense and protein truncation variants as splicing alterations might also have an effect in their penetrance and expressivity . Taken together , 8 spliceogenic variants remain classified as VUS since relevant proportions of the full-length transcript were detected ( c . 7975A>G , c . 7977-6T>G , c . 7988A>T , c . 7992T>A , c . 8007A>G , c . 8009C>T , c . 8009C>G and c . 8072C>T ) ( Table 1; S3 and S4 Tables ) . It is complex to interpret the role of variants with partial splicing anomalies in HBOC under the clinical perspective as they will require more studies to elucidate it . Nevertheless , we can speculate that they represent low BC risk alleles that might interact with other susceptibility and protector alleles to modify the overall BC risk . The incorporation of all these data into a single integrated model of BC risk would improve disease prediction and prevention . In conclusion , dysregulation of splicing should be considered as a primary mechanism of gene inactivation to be investigated in human disease genes . Spliceogenic variants are comparatively abundant in BRCA2 exons 17 and 18 because recognition of both exons additionally requires the regulation of specific ESE motifs in exons 17 and 18 , whose abolitions drive splicing aberrations . Furthermore , the pSAD-based minigenes are useful tools for molecular diagnostics and genetic counseling of hereditary breast/ovarian cancer or other genetic disorders as well as for the basic research on the splicing process . Hence , RNA assays supply essential information for the clinical interpretation of variants that should be incorporated in the genetic counselling of human hereditary diseases .
BRCA2 variants of breast/ovarian cancer patients were available from the BIC ( https://research . nhgri . nih . gov/projects/bic/Member/index . shtml ) and the BRCA Share databases ( last accessed date 2016/04/01; http://www . umd . be/BRCA2/ ) [55] . Variants of intron 17 were collected from the 1000 Genomes database ( http://browser . 1000genomes . org/Homo_sapiens/Gene/Summary ? db=core;g=ENSG00000139618;r=13:32889611-32973805;t=ENST00000380152 ) . Variant descriptions were according to the BRCA2 GenBank sequence NM000059 . 1 and the guidelines of the Human Genome Variation Society ( HGVS; http://www . hgvs . org/mutnomen/ ) . Mutant and wild type ( wt ) sequences were analyzed with NNSPLICE ( http://www . fruitfly . org/seq_tools/splice . html ) [56] , and Human Splicing Finder version 3 . 0 ( HSF; http://www . umd . be/HSF3/ ) [57] , which includes algorithms for splice sites , silencers and enhancers [31 , 58–62] . MGBR2_ex14-20 was assembled in four steps by overlapping extension PCR or classical restriction digestion/ligation cloning with three intermediate constructs: MGBR2EX17-18 , MGBR2EX16-18 , and MGBR2EX16-20 . All the inserts were amplified with Phusion High Fidelity polymerase ( Thermo Fisher Scientific , Waltham , MA , USA ) and primers indicated on S1 Table . Exons 17–18 were subcloned into the pSAD vector by overlapping extension PCR . Then , exon 16 was added by the same technique . Exons 19–20 were inserted between the Xhol and BamHI restriction sites of the 16–18 construct . Finally , exons 14–15 were introduced using the EagI and SacI restriction sites . All clones were functionally checked in MCF-7 cells . DNA variants were introduced with the QuikChange Lightning kit ( Agilent , Santa Clara , CA ) . The wt minigene MGBR2_ex14-20 was used as template to generate 52 BIC/BRCA Share DNA variants as well as seventeen exonic ( 17 and 18 ) and four intronic ( ivs17 ) microdeletions ( S2 Table ) . The first two and the last three nucleotides of each exon were always preserved to avoid any disruptions of the canonical acceptor and donor sites , respectively . Deletions were introduced by PCR-mutagenesis with chimeric 50-60mer primers containing 25–30 nucleotides of each end of the deletion . Approximately 2x105 MCF7 cells were grown to 90% confluency in 0 . 5 mL of medium ( MEME , 10% Fetal Bovine Serum , 2 mM glutamine , 1% Non-essential amino acids and 1% Penicillin/Streptomycin ) in 4-well plates ( Nunc , Roskilde , Denmark ) . Cells were transiently transfected with 1 μg of each minigene and 2 μL of Lipofectamine 2000 or low toxicity Lipofectamine ( Life Technologies , Carlsbad , CA ) . To inhibit nonsense mediated decay ( NMD ) , cells were incubated with cycloheximide ( Sigma-Aldrich , St . Louis , MO ) 300 μg/mL for 4 hours . RNA was purified with the Genematrix Universal RNA Purification Kit ( EURx , Gdansk , Poland ) with on-column DNAse I digestion to degrade genomic DNA that could interfere in RT-PCR . Retrotranscription was carried out with 400 ng of RNA and RevertAid H Minus First Strand cDNA Synthesis Kit ( Life Technologies ) , using gene specific primer RTPSPL3-RV ( 5’TGAGGAGTGAATTGGTCGAA 3’ ) . Samples were incubated at 42°C for 1 hour , and reactions were inactivated at 70°C for 5 min . Then , 1–2 μl of the resultant cDNA were amplified with SD6-PSPL3_RTFW ( 5’-TCACCTGGACAACCTCAAAG-3’ ) or RTBR2_ex16FW ( 5’-TATGGACTGGAAAAGGAATAC-3’ ) and RTpSAD-RV ( Patent P201231427 , CSIC ) ( sizes: 1012 and 1806 bp , respectively ) using Platinum Taq DNA polymerase ( Life Technologies ) . Samples were denatured at 94°C for 2 min , followed by 35 cycles consisting of 94°C for 30 sec , 59°C for 30 sec , and 72°C ( 1 min/kb ) , and a final extension step at 72°C for 5 min . Sequencing reactions were performed either using the kit BigDye Terminator v3 . 1 Cycle Sequencing Kit ( Applied Biosystems ) following the manufacturer's instructions or by the sequencing facility of Macrogen Europe ( Amsterdam , The Netherlands ) . All transcripts from exon 18 microdeletion c . 8004_8013del were subcloned into the pJet1 . 2 PCR cloning vector ( Thermo Fisher Scientific ) and sequenced . In order to quantify all transcripts , semi-quantitative fluorescent PCRs were undertaken at least in triplicate ( >234 assays were performed of 52 natural plus 26 artificial mutants; S2 Table ) with primers RTBR2_ex16-FW and FAM-RTpSAD-RV and Platinum Taq DNA polymerase ( Life Technologies ) under standard conditions except that 26 cycles were herein applied [19 , 63] . FAM-labeled products were run with LIZ-1200 Size Standard at the Macrogen facility and analyzed with the Peak Scanner software V1 . 0 . Only peaks with heights ≥ 50 RFU ( Relative Fluorescence Units ) were taken into account . Peak areas were used to quantify the relative abundance of each transcript that was the average of at least three experiments [19] . | A significant proportion of disease-causing mutations of inherited disorders impair splicing . Massive sequencing projects of genetic diseases generate thousands of sequence variations that require functional and clinical interpretations . We have shown that splicing reporter minigenes of the breast cancer genes BRCA1 and BRCA2 are useful tools to functionally test DNA variants . In this work , we have constructed a 7-exon BRCA2 minigene ( exons 14 to 20 ) where we mapped critical splicing regulatory sequences and tested 52 selected variants of exons 17 and 18 detected in breast cancer patients . We finely located three DNA segments on both exons that presumably contain splicing enhancer sequences . We observed that a total of 30 variants of any type disrupted the splicing patterns and , given the severity of their outcomes , we classified 20 of them as pathogenic or likely pathogenic . We also showed that a wide range of splicing elements were affected including canonical and novel 5’ and 3’ splice sites , the polypyrimidine tract and enhancer and silencer sequences . We concluded that splicing aberrations are frequent in Hereditary Breast and Ovarian Cancer and that minigenes are valuable tools to functionally classify DNA variants of any human disease gene under the splicing viewpoint . | [
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"intron... | 2017 | Functional classification of DNA variants by hybrid minigenes: Identification of 30 spliceogenic variants of BRCA2 exons 17 and 18 |
Cellular responses to Plasmodium falciparum parasites , in particular interferon-gamma ( IFNγ ) production , play an important role in anti-malarial immunity . However , clinical immunity to malaria develops slowly amongst naturally exposed populations , the dynamics of cellular responses in relation to exposure are difficult to study and data about the persistence of such responses are controversial . Here we assess the longevity and composition of cellular immune responses following experimental malaria infection in human volunteers . We conducted a longitudinal study of cellular immunological responses to sporozoites ( PfSpz ) and asexual blood-stage ( PfRBC ) malaria parasites in naïve human volunteers undergoing single ( n = 5 ) or multiple ( n = 10 ) experimental P . falciparum infections under highly controlled conditions . IFNγ and interleukin-2 ( IL-2 ) responses following in vitro re-stimulation were measured by flow-cytometry prior to , during and more than one year post infection . We show that cellular responses to both PfSpz and PfRBC are induced and remain almost undiminished up to 14 months after even a single malaria episode . Remarkably , not only ‘adaptive’ but also ‘innate’ lymphocyte subsets contribute to the increased IFNγ response , including αβT cells , γδT cells and NK cells . Furthermore , results from depletion and autologous recombination experiments of lymphocyte subsets suggest that immunological memory for PfRBC is carried within both the αβT cells and γδT compartments . Indeed , the majority of cytokine producing T lymphocytes express an CD45RO+ CD62L- effector memory ( EM ) phenotype both early and late post infection . Finally , we demonstrate that malaria infection induces and maintains polyfunctional ( IFNγ+IL-2+ ) EM responses against both PfRBC and PfSpz , previously found to be associated with protection . These data demonstrate that cellular responses can be readily induced and are long-lived following infection with P . falciparum , with a persisting contribution by not only adaptive but also ( semi- ) innate lymphocyte subsets . The implications hereof are positive for malaria vaccine development , but focus attention on those factors potentially inhibiting such responses in the field .
Malaria is caused by parasites of the genus Plasmodium that are transmitted from one human host to the next by Anopheline mosquitoes , putting an estimated 3 . 3 billion of the world's population at risk [1] . Upon inoculation by a mosquito , sporozoites initiate an asymptomatic infection of hepatocytes from which blood-stage forms emerge to invade and multiply exponentially within erythrocytes . The latter process underlies the full spectrum of morbidity and mortality associated with clinical malaria . Compounding this global public health burden is the fact that first infections do not immediately induce immunity . Instead , infants in endemic areas remain susceptible to multiple new symptomatic infections throughout childhood and early adulthood , and adults frequently still harbor sub-clinical parasitemia ( reviewed in [2] , [3] ) . Both poor induction ( priming ) of immune responses by the parasite and rapid attrition of such responses have been proposed as explanations , although the validity of both hypotheses has been brought into question ( discussed in [4] , [5] , [6] ) . Direct immunological evidence from studies in humans that support or reject these theories is limited . The commonly held view that immune responses to Plasmodium parasites are short-lived following exposure , is mainly based on the short half-life of specific antibodies ( reviewed in [7] ) . It would appear that cellular responses to individual antigens are also either relatively short-lived , i . e . declining within a few years of exposure [8] , [9] , [10] , or at least unstable [11] , [12] , [13] , [14] , [15] , but may persist occasionally [16] . Many field studies , however , suffer from a profound difficulty in controlling for exposure amongst study subjects , limiting interpretation thereof . Anecdotal evidence from historical malaria-therapy studies suggests that cellular proliferative responses to crude whole parasite antigen can be detected in donors several years after a single infection [17] . More recently , robust cellular cytokine responses were detected three months post infection in previously naïve volunteers [18] . Within these cellular immune responses , interferon-gamma ( IFNγ ) in particular is considered to play a major role ( reviewed in [19] ) . Experimental human malaria infections by bites of P . falciparum infected mosquitoes offer a controlled measure of exposure and a safe and well-established model , and have been performed on hundreds of volunteers over the past two decades primarily for assessing the efficacy of candidate malaria vaccines [20] . This model allows controlled studies on the development and maturation of intrinsic immune responses in the course of a malaria infection , and on how ( long ) cellular memory is maintained . Here we conducted a comprehensive longitudinal study of cellular responses , focusing on IFNγ production by multiple subsets of innate and adaptive immune cells , induced by both P . falciparum sporozoites ( PfSpz ) and asexual blood-stage parasites ( P . falciparum-infected red blood cells; PfRBC ) in malaria-naïve volunteers undergoing single or multiple experimental infections with P . falciparum . We show that even a single patent malaria episode induces robust cellular re-call responses to both parasite stages , persisting at almost undiminished levels at least 14 months post infection and involving both adaptive and innate compartments .
In vitro parasite-specific responses were measured in peripheral blood mononuclear cells ( PBMC ) isolated from two sets of human volunteers prior to and at several time points after exposure to P . falciparum infection . Group A volunteers ( n = 10 ) were exposed thrice to immunizing bites ( I ) of infected mosquitoes whilst under chloroquine prophylaxis and thereafter challenged ( C ) once again; Group B volunteers ( n = 5 ) received only a single infection in parallel with Group A challenge ( Figure 1 ) . Total lymphocyte responses to PfSpz and PfRBC were barely detectable above background prior to exposure ( day I-1 ) in both groups of volunteers ( Figure 2 ) . Re-call responses by lymphocytes to both PfSpz and PfRBC , as measured by IFNγ production following overnight re-stimulation , were detectable in Group A volunteers following exposure to immunizing bites ( day C-1 compared to I-1 , one-way ANOVA with Dunnet's post-test , p<0 . 05 for PfSpz and p<0 . 01 for PfRBC ) and remained high after re-challenge until day C+35 ( p<0 . 001 and p<0 . 01 , respectively ) ( Figure 2 . A+C ) . Of note , one volunteer displayed a disproportionally amplified IFNγ response to PfRBC at time point C+35 . For this reason , this volunteer was left out of statistical analysis as an extreme outlier . Re-call responses to PfRBC ( p<0 . 001 , I-1 compared to C+35 ) , and to a lesser extent also to PfSpz , became detectable in Group B volunteers following their first infection ( Figure 2 . B+D ) . This shows that cellular immune responses to whole parasites are readily inducible in previously-naïve human volunteers , following a small number of , or even a single P . falciparum infection . Most remarkably , in further experiments with samples collected at later time points ( days C+140 and C+400 ) , we found that parasite-specific cellular responses did not wane after exposure . Instead , they remained robust more than a year post-challenge , albeit with considerable inter-individual variation ( Figure 2 ) . Cellular responses to protein pools of either sporozoite-stage ( CSP and TRAP ) , liver-stage ( LSA-1 or Exp-1 ) or blood-stage ( AMA-1 , MSP-2 , MSP-3 and GLURP ) antigens ( all leading malaria vaccine candidates ) , however , were never detectable above background . Many different lymphocyte subsets , including αβT cells , γδT cells and NK cells , have variously been shown capable of responding to PfRBC . Therefore , we assessed IFNγ responses by those cell types to PfRBC prior to ( I-1 for Group A , I-1 and C-1 for Group B ) and post exposure ( C-1 and later for Group A , C+9 and later for Group B; flow cytometry gating strategy illustrated in Figure S1 ) . Relative proportions of lymphocyte subsets within the total peripheral population did not differ markedly over time at the various time points assessed ( Table S1 ) . The only exception were γδT cells , the relative numbers of which increased within the peripheral lymphocyte population post exposure in both sets of volunteers ( p = 0 . 0013 for Group A; p = 0 . 029 for Group B , one-way ANOVA , I-1 to C+35 ) . Response patterns in most lymphocyte subsets , including αβT cells , NKT cells and NK cells , mirrored the dynamics of the total lymphocyte response in relation to exposure: whereas almost no responses above background could be detected in volunteers at inclusion , IFNγ responses to PfRBC became clearly detectable following challenge ( Figure S2 ) . In contrast , a large proportion of γδT cells ( median 7 . 9% and 6 . 8% for Group A and B , respectively ) demonstrated the capacity to respond to PfRBC even prior to exposure . Following infection , this percentage increased still further ( p = 0 . 013 Group A; p = 0 . 003 Group B , one-way ANOVA I-1 to C+35 ) . Responses in ‘γδNKT’ cells , relatively infrequent in total number , resembled this pattern of regular γδT cells ( Table S1 and Figure S2 ) . Next , we assessed the relative contribution of the different lymphocyte subsets to the total IFNγ response at various time points during the study ( Figure 3 ) in volunteers of Group A . Few lymphocytes produced IFNγ in response to PfRBC prior to exposure ( I-1 ) , of which 63% ( median ) were γδT cells and 15% αβT cells , with γδNKT cells ( 11% ) and NK cells ( 1 . 9% ) making up most of the remainder . Interestingly , despite an increase in the overall proportion of responding cells over time , the relative contributions of the various lymphocyte subsets remained more or less stable following repeated exposure ( C+35 ) ( 57% , 22% , 6 . 7% and 4 . 1% , respectively ) . By day 400 post-challenge , the dominating cell subsets contributing to overall IFNγ production remained αβT and γδT cells ( 35% , 25% , 11% and 17% , respectively ) . The contribution of the various cell subsets to responses in Group B volunteers also remained comparable over time ( data not shown ) . Thus , not only ‘adaptive’ αβT cells and ‘semi-innate’ γδT cells , but clearly also ‘innate’ NK and NKT cells contributed to the overall increase in lymphocytes responding to P . falciparum by IFNγ production following exposure ( Figure 3 ) . A more in depth phenotypic analysis of responding T cell subsets in donors with sufficient responses at the latest time point ( C+400 , Figure S3 ) revealed that IFNγ-producing CD4+ T cells markedly outnumbered CD8+ T cells in response to both sporozoite and blood-stage parasites post-challenge . Following in vitro re-stimulation with PfRBC , 16% [13–22] ( median [IQR] ) and 26% [20–32] of IFNγ-producing T cells were of the CD4+CD8- T-helper phenotype in Group A and B volunteers , respectively . In contrast , only 4 . 5% [3 . 1–5 . 6] and 7 . 3% [4 . 7–8 . 8] were CD4-CD8+ cytotoxic T lymphocytes ( CTLs ) . The majority of IFNγ-producing T cells in response to PfRBC , however , were CD4-CD8- cells . Analysis in a subset of donors showed that these cells were predominantly γδT cells ( data not shown ) . The contribution of CD4+ T cells was even more pronounced for PfSpz-induced responses , with 70% [65–75] of IFNγ+ T cells belonging to the CD4+CD8- population in Group A volunteers , and only 1 . 7% [0 . 9–2 . 5] to the CD4-CD8+ population ( day C+400 , Figure S3 ) . Thus , whereas both CD4-CD8- T cells and CD4+ T cells dominated responses to PfRBC , the IFNγ response to PfSpz was primarily mediated by CD4+ T cells only . Early after treatment ( day C+35 ) in Group A volunteers , 84% [80–87] ( median [IQR] ) and 0 . 1% [0 . 0–0 . 4] of IFNγ-producing lymphocytes displayed effector memory ( EM , CD45RO+CD62L- ) and central memory ( CM , CD45RO+CD62L+ ) phenotypes , respectively , following 24-hour in vitro PfRBC re-stimulation . Remarkably , despite an overall increase in the response to PfRBC in Group A volunteers on day C+400 , the relative contributions of CD62L- EM and CD62L+ CM cells remained largely stable: 72% [67–75] and 0 . 6% [0 . 6–0 . 8] , respectively ( Figure 4 . A ) . Corresponding values for Group B volunteers at day C+35 were 76% [74–79] and 0 . 5% [0 . 3–1 . 1] and remained constant over time , both in terms of percentage of responding cells and in EM/CM distribution ( Figure 4 . B ) . Responses to PfSpz stimulation showed an EM/CM pattern very similar to PfRBC responses as determined for group A volunteers ( Figure 4 . C ) . γδT cells also displayed an EM phenotype ( CD45RO+CD62L- or CD62Lintermediate ) as shown in Figure S1 . C . Thus , in vitro parasite-specific re-call responses were primarily found in EM-type populations , which include both αβT cells and γδT cells , even months after infection . Cells of CD62L+ CM phenotype , in contrast , were detectable in only a negligible fraction of the total re-call response at all time points examined . Since both αβT cells and γδT cells display memory phenotypes and can mount adaptive responses , we assessed their respective ability to initiate cellular re-call responses to PfRBC . To this end , we separated and re-combined γδT cells and other PBMC ( consisting of approximately 80% αβT cells and 5% NK cells ) from both inclusion ( I; ‘Pf-naïve’ ) and 35 or 140 days post-challenge ( C; ‘Pf-experienced’ ) of volunteers from both groups for whom sufficient cells were available ( Figure 5 . A ) . Following in vitro stimulation , total numbers of IFNγ+ lymphocytes in naïve PBMC populations supplemented with Pf-experienced γδT cells were significantly higher than in populations containing only Pf-naïve cells ( I-I versus I-C; p<0 . 05 , One-way ANOVA ) . This suggests that the γδT compartment carries some immunological memory for PfRBC ( Figure 5 . B ) . Indeed , the PfRBC response by Pf-experienced γδT cells in some donors was more than twice as high compared to that by Pf-naïve γδT cells , even in the presence of otherwise naïve PBMC populations ( data not shown ) . IFNγ responses in PBMC populations containing Pf-experienced γδT-depleted cells ( mainly αβT cells ) also appeared higher than in populations containing only Pf-naïve cells ( I-I versus C-I; not significant ) . Whereas IFNγ has many direct effector functions , IL-2 is important for T cell proliferation and induction of cellular memory responses . In a final set of experiments , we therefore explored the dynamics of EM lymphocytes producing either IL-2 or IFNγ alone ( unifunctional ) , or both cytokines simultaneously ( polyfunctional cells ) , in response to PfRBC and PfSpz . In Group A volunteers , the percentage of total IL-2+ EM cells responding to PfRBC , although low in absolute numbers , increased significantly from 0 . 08% [0 . 04–0 . 12] ( median [IQR] ) of EM cells at day I-1 , to 0 . 31% [0 . 17–0 . 45] at day C-1 ( p<0 . 001 , one-way ANOVA with Dunnett's post-test ) and 0 . 22% [0 . 19–0 . 42] at day C+35 ( p<0 . 01 , Figure S4 . A ) and remained clearly detectable at day C+140 and day C+400 . This was in line with the increase in total lymphocyte IFNγ responses to PfRBC after immunization ( Figure 2 ) . Similarly to both total IFNγ and total IL-2 responses , the percentage of EM-type cells producing both IFNγ and IL-2 in response to PfRBC increased from 0 . 025% [0 . 003–0 . 078] on day I-1 to 0 . 14% [0 . 09–0 . 22] on C-1 ( p<0 . 01 ) and 0 . 13% [0 . 10–0 . 18] on day C+35 ( p<0 . 01 , Figure S4 . B ) and remained present up to day C+400 . The relative contribution of such polyfunctional cells to the overall number of cytokine producing EM cells , however , remained relatively stable with an apparent slight , but non-significant increase on day C-1 and C+9 ( Figure S5 ) . Total IL-2 and polyfunctional responses to PfSpz by EM cells from Group A volunteers remained low up to C+35 ( p = 0 . 8 and 0 . 1 , respectively , compared to I-1 ) . IL-2 increased from C+140 to C+400 ( p = 0 . 039 , paired Student's t-test; Figure S4 . A ) . A similar trend was seen for polyfunctional responses ( p = 0 . 15; Figure S4 . B ) . Interestingly , months after malaria infection , the contribution of IFNγ+IL-2+ EM cells to the total EM cytokine response towards PfSpz was relatively more pronounced than to that against PfRBC . Specifically , on day C+140 and C+400 the relative contribution of polyfunctional EM cells was 37% [25–62] and 19 . 2% [16–30] in response to PfSpz , compared to 3 . 3% [1 . 5–4 . 3] and 3 . 4% [2 . 0–5 . 3] in response to PfRBC ( p<0 . 001 and p<0 . 05 respectively; two-way ANOVA with Bonferroni post-test; data not shown and Figure 6 ) . Thus , although infrequent in total number , polyfunctional EM cells with specificity for both PfRBC and PfSpz were readily induced upon exposure , and formed a greater relative contribution to PfSpz than to PfRBC responses .
In this study we delineate the dynamics and composition of cellular immune responses to both sporozoites and asexual blood-stage Plasmodium falciparum parasites following infection in previously-naïve individuals . We demonstrate unequivocally that specific IFNγ responses to both stages of the malaria parasite are not only readily induced following infection , but also persist more or less undiminished over at least 14 months in the absence of further exposure . The main contributors to these whole parasite-specific IFNγ responses are γδT cells and CD4+ EM T cells , with NK cells making up a smaller remaining fraction of responding cells . We show that not only adaptive , but also semi-innate and innate lymphocytes responses exhibit an immunological re-call pattern and present evidence suggesting that immunological memory for PfRBC is carried within both the αβT cell and γδT cell compartments . Our demonstration of lengthy persistence of cellular immunological responses following P . falciparum infection in humans stands in contrast to the popularly held perception that clinical immunity to malaria is short-lived . As discussed previously by Struik et al . [6] studies reporting such short-lived immunity are mainly anecdotal and few consistent data pro or contra this hypothesis have been published . Our current findings prove that long-lived cellular responses can be adequately maintained , at least when induced under experimental conditions . A central mediator of such cellular immunological responses to the malaria parasite is the cytokine IFNγ ( reviewed in [19] ) . In vitro parasite-specific IFNγ responses have been shown by us and others to associate with protection against malaria both amongst volunteers undergoing experimentally induced infection [21] , [22] , [23] and naturally-exposed human populations [24] , [25] , [26] , [27] . Phenotypic characterization of the in vitro IFNγ response to whole blood-stage parasites ( PfRBC ) in malaria-naive donors has variously implicated ‘innate’ natural killer ( NK ) cells [28] , [29] , [30] , ‘semi-innate’ γδT cells [31] , [32] ( including NK-like γδT cells [33] ) and ‘adaptive’ αβT cells [32] , [34] , [35] . It remains unknown , however , how these intrinsic responses develop and mature in the course of a malaria infection and how ( long ) cellular memory is maintained . Consistent with findings by others [31] , [33] , we show that ‘semi-innate’ γδT cells comprise the largest population of lymphocytes responding with IFNγ production to PfRBC in malaria-naïve donors . Interestingly , this remains largely true following exposure , despite the obvious increase in ‘adaptive’ responses . Two factors may contribute to the overall increase in responding γδT cell numbers: i ) The overall proportion of γδT cells in the PBMC pool increases following exposure to parasites , which persists for at least a year . A transient dip in circulating γδT cells during infection , followed by reactive increase afterwards , has been observed before in primary [36] , [37] but not in repeated malaria infections [38] . ii ) A slightly increased proportion of these γδT cells responds to PfRBC following infection . This increase may represent the recruitment of PfRBC-specific γδT clones to the peripheral circulation or a non-specific bystander effect , since γδT cells can readily respond to P . falciparum lysate by proliferation in a polyclonal fashion [39] , [40] . Whatever the underlying mechanism , our data suggest that the γδT compartment does contribute autonomously to cellular immunological memory up to 14 months post infection , independently of other PBMC including αβT cells . In contrast , we and others have recently shown that the ‘re-call-like’ response observed in NK cells post infection is in fact fully dependent on αβT cells [30] , [41] . These data can be combined into a model in which ‘semi-innate’ γδT cells , ‘adaptive’ αβT cells and ‘innate’ NK cells all contribute to a robust and long-lived IFNγ response following infection with P . falciparum , although through different mechanisms . For γδT cells this is largely through an overall expansion of this compartment in peripheral blood , in addition to a minor increase in the proportion of responding γδT cells . For αβT cells the proportional increase in response is also relatively small , but in absolute terms these lymphocytes already make up the vast majority of PBMC populations . NK cells finally , although fewer in absolute terms , show a much larger proportional increase in response , albeit dependent on the increase in T cell responses [30] . The majority of responding T cells displays an EM ( CD45RO+ CD62L- ) phenotype , even over a year post infection , at least in donors with sufficient numbers of responding cells to assess this . Whether such a composition is also representative of extremely low responders , or whether those donors exhibit a relative response deficit in a particular lymphocyte sub-set , cannot as yet be determined . The apparent scarcity of responding CD62L+ CM cells may be partly due to the fact that CM cells by definition form only a minor population within the peripheral blood , residing primarily in ‘target’ tissues ( e . g . , skin and liver ) and lymph nodes . Another possibility is that this pattern is inherent to short-term in vitro assays such as ours where within the short timeframe of 24 hours , effector memory cells , which are defined by their ability to perform immediate ( cytokine producing ) effector function , will preferentially respond . Finally , the low number of CD62L expressing responding lymphocytes could be due to loss of CD62L expression , since following antigenic stimulation CM cells can differentiate into an effector memory phenotype and subsequently acquire effector function [42] , [43] . Thus the formal compartmental origin of responding cells cannot be determined with certainty from this assay . The importance of polyfunctional lymphocytes in immunological protection is believed to depend on i ) their higher cytokine production [23] and hence more potent effector capability compared to monofunctional cells [44] and ii ) their role in the induction and persistence of T cell memory [45] . We recently showed that the development of protection against infection with P . falciparum in human volunteers is associated with the induction of IFNγ+IL-2+ double-positive ( polyfunctional ) EM T cells in response to PfRBC [22] , [23] . Despite an overall increase in the number of responding lymphocytes up to one year post infection , we show here that the relative contribution of polyfunctional cells to the total response remains roughly constant . This may indicate that little differentiation takes place in the functionality of cellular immune responses to PfRBC following exposure [46] . It will be of obvious interest to explore this further in future studies and to determine whether such responses genuinely afford protection . In contrast to responses to the asexual stage of the malaria parasite , sporozoite-specific cytokine responses have received little attention to date . We find that similar to PfRBC responses , IFNγ responses to PfSpz are readily induced and persist following exposure to infected mosquito bites . Furthermore , as for PfRBC responses , IFNγ production dominates the total cytokine response . A striking feature of the anti-PfSpz response , however , is that polyfunctional IFNγ+/IL-2+ cells form a relatively larger component of this compared to PfRBC . Whether this represents a genuine acquisition of effector function of the anti-PfSpz response or conversely a failure of these lymphocytes to terminally differentiate into IFNγ single producers [46] remains to be determined . Our data demonstrate that there is no intrinsic deficit in either the induction or persistence of cellular responses to P . falciparum after experimental infection . This raises the obvious question as to why clinical immunity to malaria develops so slowly amongst naturally exposed populations [2] , [4] . More specifically , why do cellular responses to P . falciparum antigens in naturally exposed donors appear to be so transient/unstable [8] , [10] , [11] , [12] , [13] , [14] , [15] and tend in fact to be lower than in non-exposed donors [47] , [48] ? Several lines of reasoning may help to explain this paradox . Firstly , by the time treatment is sought by and initiated in patients in resource-poor endemic settings , their parasitemia is typically higher compared to that in our strictly-observed volunteers . High parasitemia has been shown to inhibit the development of immunity both in mice [49] and in humans [11] . This may be due to active suppression or elimination of responding T cells [50] , [51] by P . falciparum , resulting in reduced Pf-specific cellular responses following repeated or chronic infection [11] , [47] , [48] , [52] . Obvious accomplices are regulatory T cells [53] , [54] , [55] , [56] , and a comparison of the dynamics of regulatory T cells in natural and experimental infections would be informative in this regard . Secondly , underlying differences in the status of the immune system of inhabitants of the rural tropics may predispose to tolerant , as opposed to sterilizing , immune responses [57] . This may be due to e . g . malnutrition [58] or helminth co-infections [59] , [60] . Another factor may be the inherent immaturity in the immune systems of infants and young children , the stage in life at which malaria infections are typically first experienced in endemic settings [61] , [62] , as well as prior in utero exposure [63] . Indeed , IFNγ responses to P . falciparum antigens in children tend to be weaker than in adults [14] , [64] , [65] , [66] , [67] , although of course the effect of prior exposure in these studies cannot be distinguished from that of age per sé . In addition , immunization and in vitro PBMC re-stimulation in our experimental infection model were performed with homologous strain parasites , whereas in field studies prior strain exposure varies . Well-described target antigens for protective immunity exhibit high rates of genetic variation , hindering cross-protective immunity in the field [68] . Finally , the immune modulating effects of chloroquine might have enhanced the development of immune responses during the immunization process [69] , possibly contributing to the persisting immune responses in Group A . Despite these caveats in extrapolating our findings to the situation in endemic areas , we show that robust long-lasting cellular immune responses to malaria parasites can be readily induced under experimental conditions , and extend our understanding of how cellular immunological memory to P . falciparum develops and is maintained following exposure .
NF54 strain P . falciparum asexual blood-stage parasites , regularly screened for mycoplasma contamination , were grown in RPMI-1640 medium containing 10% human A+ serum at 5% hematocrit in a semi-automated suspension culture system , in the absence of antibiotics and in an atmosphere containing 3% CO2 and 4% O2 . For in vitro stimulation experiments , asynchronous asexual-stage cultures of NF54 strain parasites were harvested at a parasitemia of approximately 5–10% and mature asexual stages purified by centrifugation on a 27% and 63% Percoll density gradient [70] . This purification step results in preparations of 80-90% parasitemia , consisting of more than 95% schizonts/mature trophozoites . Preparations of parasitized red blood cells ( PfRBC ) were washed twice in PBS and cryopreserved at 150x106/ml in 15% glycerol/PBS in aliquots for use in individual stimulation assays . Cryopreserved PfRBC form almost as strong a stimulus as freshly-prepared PfRBC and have identical stimulatory characteristics ( Figure S6 ) . Their use in large experiments has logistical advantages , in addition to reducing confounding influences due to inter-batch variation . Mock-cultured uninfected erythrocytes ( uRBC ) were obtained similarly and served as controls . Sporozoites were obtained from Anopheles stephensi mosquitoes that were reared according to standard procedures in our insectary . Infected mosquitoes were obtained by feeding on gametocyte-containing cultures of NF54 strain P . falciparum , as described previously [71] . On day 21–28 after infection , the salivary glands of the mosquitoes were collected by hand-dissection . Salivary glands were collected in RPMI-1640 medium ( Gibco ) and homogenized in a custom glass grinder . Sporozoites were counted in a Bürker-Türk counting chamber using phase-contrast microscopy . Sporozoites were cryopreserved at 16×106/ml in 15% glycerol/PBS in aliquots for use in individual stimulation assays . Sporozoites that had undergone one freeze-thaw cycle were determined microscopically to be still intact , but were no longer able to glide ( assay described in [72] ) . To control for a possible immune-stimulatory effect of salivary gland remnants in the sporozoite preparation , salivary glands from an equal number of uninfected mosquitoes ( MSG ) were obtained similarly and served as a background control . All volunteers were recruited after giving written informed consent . The study was approved by the Institutional Review Board of the Radboud University Nijmegen Medical Centre ( CMO 2006/207 ) . The basic design and outcome of experimental human malaria infections at our centre has been described before [73] . For the study presented here [23] , 15 healthy malaria naïve Dutch volunteers were recruited and randomized double-blind to either Group A ( n = 10 ) or Group B ( n = 5 ) . Group A volunteers were immunized by exposure on three occasions , at monthly intervals , to the bites of 12-15 NF54 strain P . falciparum-infected mosquitoes , whilst continuously taking a standard prophylactic regimen of chloroquine ( 300mg base per week ) . Group B volunteers similarly took chloroquine and were exposed to the same number of bites , but from uninfected mosquitoes . Two months after the final exposure and one month after discontinuation of chloroquine prophylaxis , all 15 volunteers were challenged by exposure to the bites of 5 P . falciparum-infected mosquitoes and followed-up closely for symptoms and signs of malaria . As soon as they were found to be thick blood-smear positive , volunteers were treated with a standard curative regimen of artemether/lumefantrine ( AL ) consisting of six doses of 13 80/480 mg over three days . Duration and peak height of parasitemia in volunteers following each round of infection , as measured retrospectively by PCR [23] , is shown in Table S2 . Venous whole blood was collected into citrated CPT vacutainers ( Becton and Dickinson , Basel ) at inclusion ( day I-1 ) , and immediately prior to challenge ( day C-1 ) , during expected blood-stage malaria infection ( day C+9 ) , two weeks after treatment with AL ( day C+35 ) and again 4 . 5 months ( day C+140 ) and 1 . 1 year ( day C+400 ) after challenge ( Figure 1 ) . Peripheral Blood Mononuclear Cells ( PBMC ) were obtained by density gradient centrifugation , washed three times in cold PBS , enumerated , frozen down in fetal-calf serum containing 10% dimethylsulfoxide and stored in liquid nitrogen . Immediately prior to use , cells were thawed , washed twice in RPMI and re-suspended in complete culture medium ( RPMI 1640 Dutch modification ( Gibco ) containing 2 mM glutamine , 1mM pyruvate , 50 µg/ml gentamycine and 10% human A+ serum , ( Sanquin , Nijmegen ) ) for a final concentration of 2 . 5×106/ml . PBMC were transferred into 96-well round-bottom plates and stimulated in duplicate wells with either 5x106/ml ( final concentration ) cryopreserved PfRBC or uRBC , or 5 . 6×105/ml cryopreserved sporozoites or the extract of an equivalent number of uninfected mosquito salivary glands in a total volume of 200 µl/well for 24 hours at 37°C/5%CO2 . Dose and duration of stimulation were chosen based on earlier optimization assays . Initial experiments included samples from time points I-1 through C+35; in a later set of experiments , time points C+140 and C+400 were compared . In a subset of experiments , PBMC from time points I-1 through C+35 were instead stimulated with protein pools of individual purified sprorozoite-stage ( CSP and TRAP ) , liver-stage ( LSA-1 or Exp-1 ) or blood-stage ( AMA-1 , MSP-2 , MSP-3 and GLURP ) antigens in concentrations of both 5 and 30 µg/ml per antigen . Full length CSP [74] was kindly provided by A . Birkett , TRAP MR149A , MSP-2 MR141 [75] , PfExp-1 MR95 [76] by G . Corradin , MSP-3 [77] by C . Oeuvray , GLURP [78] by M . Theisen , LSA-1 [79] by T . Richie and AMA-1 [80] by A . Thomas . In these latter experiments 60 IU human recombinant IL-2 ( Proleukin , Novartis ) was added to the culture medium for optimal cellular responses . In all experiments , 100μL/well supernatant was removed 4 hours prior to cell harvest and replaced with 100μL/well fresh culture medium containing Brefeldin A ( Sigma ) with a final concentration of 10μg/ml . For recombination experiments , PBMC collected at inclusion ( I ) and post-challenge ( C ) from seven donors from Group A and B for whom sufficient cells were available , were divided into two aliquots . For two of these donors , cells from day 35 post-challenge were used and for the other five donors C+140 cells . One aliquot of each sample was depleted of γδT cells by magnetic beads , whereas untouched γδT+ cells were isolated from the second aliquot by negative selection ( Anti-TCR γ/δ MicroBead Kit and TCRγ/δ+T Cell Isolation Kit , respectively , both from Miltenyi Biotech ) , according to the manufacturer’s instructions . Following separation , autologous I/C γδT- and γδT+ cells were recombined at their original ratios . Purity of depletion was consistently >90% , whereas purity of negative selected untouched γδT+ cells varied between 40–80% . The majority of contaminating non-γδT cells in these negatively selected populations consisted of NK and other non-T lymphocytes . Since the proportion of γδT+ cells added directly reflected the proportion of these cells in the PBMC population ( I or C ) from which they were derived ( see also Table S1 ) , this proportion was higher in wells containing C γδT+ cells than in wells containing I γδT+ cells : 1 . 5 [1 . 1–2 . 1] , 4 . 7 [2 . 6–9 . 1] , 1 . 4 [1 . 1–1 . 8] and 3 . 9 [2 . 8–4 . 0] ( % of lymphocytes [IQR] ) respectively for I+I , I+C , C+I and C+C . CD3-CD56-γδT stain ( all time points ) : Following 24 hour of in vitro stimulation , PBMC were harvested and transferred to FACS tubes ( 250 , 000 cells/tube ) , washed once in FACS buffer ( 0 . 5% BSA/PBS ) and incubated for 15 minutes in 100 µl FACS buffer with fluorochrome-labelled mAbs against the cell-surface markers CD3-PerCP ( clone CK7 , BD Biosciences ) , TCR Pan γ/δ-PE ( clone IMMU510 , Beckman Coulter , Fullerton , CA , USA ) and CD56-APC ( clone MEM188 , eBioscience San Diego , CA , USA ) . Cells were washed again in FACS buffer and incubated for 15 minutes in 100 µl fixation medium A ( Caltag Laboratories , Carlsbad CA ) according to the manufacturer's instructions , washed and incubated for 15 minutes with IFNγ-FITC ( clone 4S . B3 , eBioscience ) in 100 µl permeabilization medium B . After a final wash step , cells were re-suspended in FACS buffer and acquired on a FACScalibur flow cytometer ( Becton Dickenson ) . Figure S1 . A shows the gating strategy for this staining . Effector memory phenotyping stain ( I-1 , C-1 , C+9 , C+35 ) : Following the procedure described above , cells were stained with CD45RO-PE ( clone UCHL1 ) , CD62L-PE-Cy7 ( clone DREG56 ) , IFNγ-FITC ( clone 4S . B3 ) and IL-2-APC ( clone MQ1-17H12 , all eBioscience ) . Figure S1 . B shows the gating strategy for this staining . Additional T cell phenotyping stain for C+140 and C+400: Following 24 hour of in vitro stimulation , PBMC were harvested and transferred to 96 wells V-plate ( 500 , 000 cells/well ) , washed once in PBS and incubated with 50 µl Live/Dead fixable dead cell stain kit Aqua ( Invitrogen , Carlsbad , CA , USA ) in PBS for 30 min on 4°C . Cells were washed in PBS and for a second time with FACS buffer ( PBS containing 0 . 5% albumin for bovine serum ( Sigma Chemical Co . ) ) , and stained in 50 µl FACS buffer with anti-TCR Pan γ/δ-PE ( clone IMMU510 , Beckman-Coulter ) , CD45RO-ECD ( clone UCHL1 , Beckman-Coulter ) , CD3-PerCP ( Clone UCHT1 , BioLegend , San Diego , CA , USA ) , CD62L-PE-Cy7 ( Clone DREG56 , eBioscience ) , CD4-Pacific Blue ( Clone OKT4 , eBioscience ) and CD8a-Alexa-fluor 700 ( clone HIT8a , BioLegend ) for 20 min at 4°C . After washing , cells were incubated with 50 µl fixation Medium A ( Caltag , S . San Francisco , CA , USA ) and subsequently , incubated with anti-IFNγ-FITC ( clone 4S . B3 , eBioscience ) and IL-2-APC ( Clone MQ1-17H12 , eBioscience ) in 50 µl permeabilization Medium B ( Caltag ) for 20 min at 4°C . Lymphocytes ( 100 , 000 ) gated by forward- and side-scatter characteristics were acquired on a CyAn ADP 9-color flow cytometer ( Beckman- Coulter ) . Figure S1 . C and S1 . D show the gating strategy for this staining . Flow cytometry analysis was performed using Cell Quest and FlowJo V9 . 1 software . Gating of lymphocytes and subsequent subgroups was performed as shown in Figure S1 . Gating of cells positive for IFNγ and/or IL2 was performed using a cut-off based on the geometric mean of cells cultured in medium only . Statistical analysis were performed using GraphPad Prism 5 . Differences in responses within volunteers between multiple time points or between stimuli were analyzed by repeated measures one-way ANOVA with Dunnett's or Bonferroni post-hoc test , as appropriate . Paired/repeated measures analysis was carried out exclusively on complete data sets obtained within a single experiment . Two-way analysis with Bonferroni post-test was performed in order to analyze data sets with multiple variables ( both time points and stimuli ) . One donor had to be excluded from all statistical analysis due to an extreme , but highly variable , outlying IFNγ response to PfRBC at time point C+35 . All statistical analyses were performed on data corrected for background: background responses were subtracted from the responses to parasite stimuli for every volunteer at every time point individually ( PfRBC - uRBC; sporozoite – mosquito salivary gland; parasite antigens – medium only ) ; negative values were set to zero . P-values <0 . 05 were considered statistically significant in all analyses . | A decade into the 21st century , malaria remains responsible for an intolerable global health burden and an effective vaccine is sorely needed . Compounding the many technical hurdles in developing such a vaccine , ( naturally-acquired ) immunity to malaria is generally perceived to be short-lived , although direct evidence from field studies is conflicting . To overcome this issue , we measured the development of immune responses against the malaria parasite Plasmodium falciparum in human volunteers undergoing experimental malaria infections for the first time , allowing a uniquely detailed analysis thereof . We found that cellular immune responses against two clinically-relevant life-stages of the parasite are not only rapidly acquired following even a single malaria infection , but also remain virtually undiminished over a year later – an unprecedented measurement . These findings refute conclusively the notion that an intrinsic defect exists in either the development or persistence of cellular immune responses against malaria . This realization , in conjunction with a growing recognition that such responses are indeed associated with clinical protection against malaria , markedly enhances the prospect of one day developing a successful vaccine . Simultaneously , however , these results re-focus attention on the question of why the development of long-lived immune responses is often inhibited under conditions of natural exposure . | [
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"immun... | 2011 | Longevity and Composition of Cellular Immune Responses Following Experimental Plasmodium falciparum Malaria Infection in Humans |
Altered expression of the E3 ubiquitin ligase UBE3A , which is involved in protein degradation through the proteasome-mediated pathway , is associated with neurodevelopmental and behavioral defects observed in Angelman syndrome ( AS ) and autism . However , little is known about the neuronal function of UBE3A and the pathogenesis of UBE3A-associated disorders . To understand the in vivo function of UBE3A in the nervous system , we generated multiple mutations of ube3a , the Drosophila ortholog of UBE3A . We found a significantly increased number of total boutons and satellite boutons in conjunction with compromised endocytosis in the neuromuscular junctions ( NMJs ) of ube3a mutants compared to the wild type . Genetic and biochemical analysis showed upregulation of bone morphogenetic protein ( BMP ) signaling in the nervous system of ube3a mutants . An immunochemical study revealed a specific increase in the protein level of Thickveins ( Tkv ) , a type I BMP receptor , but not other BMP receptors Wishful thinking ( Wit ) and Saxophone ( Sax ) , in ube3a mutants . Ube3a was associated with and specifically ubiquitinated lysine 227 within the cytoplasmic tail of Tkv , and promoted its proteasomal degradation in Schneider 2 cells . Negative regulation of Tkv by Ube3a was conserved in mammalian cells . These results reveal a critical role for Ube3a in regulating NMJ synapse development by repressing BMP signaling . This study sheds new light onto the neuronal functions of UBE3A and provides novel perspectives for understanding the pathogenesis of UBE3A-associated disorders .
Angelman syndrome ( AS ) is a neurodevelopmental disorder characterized by severe mental retardation , developmental delay , ataxia , seizures , speech impairment , and happy disposition [1 , 2] . It is caused by disruption of the ubiquitin protein ligase E3A ( UBE3A ) , which is expressed in the brain primarily from the maternal allele as a result of tissue-specific genomic imprinting [3 , 4] . While loss of UBE3A causes AS , a maternal 15q11–13 duplication encompassing UBE3A results in autism [5–7] . A point mutation of UBE3A identified in an autism proband disrupts its phosphorylation by protein kinase A and increases its ligase activity [8] . Thus , both loss and gain of UBE3A function are associated with neurodevelopmental and cognitive defects . UBE3A is involved in ubiquitin–proteasome-mediated protein degradation . Although several substrates of UBE3A have been identified , few have been implicated in neural development and function [9] . Ube3a mutant mice , a valid model of AS , show impairment in hippocampal long-term potentiation ( LTP ) [10 , 11] and experience-dependent synaptic plasticity in the visual cortex [12 , 13] , together with imbalanced excitatory/inhibitory neurotransmission [14] and altered intrinsic membrane properties [15] . Moreover , Ube3a has been firmly implicated in the regulation of dendrites and spine development in neurons [16–18] . While the underpinnings of UBE3A-associated disorders remain to be elucidated , a recent study has shown that Ube3a targets the small-conductance potassium channel SK2 for degradation , and decreased NMDA receptor activation due to an elevated SK2 protein level underlies the impaired LTP in Ube3a mice [11] . Abnormal development and function of excitatory synapses in conjunction with a reduced number of AMPA receptors in Ube3a mutant mice are attributed to decreased Ube3a-mediated proteasomal degradation of RhoA guanine exchange factor ( GEF ) Ephexin5 and synaptic protein Arc [19 , 20] . However , later studies showed that Arc is not a direct substrate of UBE3A [21 , 22] . Thus , the molecular mechanisms by which UBE3A regulates synapse development and function remain unclear . Null mutants of ube3a , the Drosophila homolog of human UBE3A [23] , show defects in locomotive behavior , circadian rhythms , and long-term memory [24 , 25] , as well as reduced dendritic branching and growth of terminal dendritic processes of sensory neurons [26] . Similar to ube3a loss-of-function mutants , overexpression of wild-type ube3a also leads to motor abnormalities , circadian rhythm defects , and decreased dendritic branching [24–26] . So far , it has not been shown if Drosophila ube3a regulates synapse development . No direct targets of Ube3a-involved proteasomal degradation have been definitely identified in Drosophila , despite a series of proteomic studies [23 , 27 , 28] . Bone morphogenetic protein ( BMP ) pathway plays a crucial role in neural development throughout evolution [29–31] . In this study , we show that Drosophila Ube3a regulates synapse development and function at neuromuscular junctions ( NMJs ) by ubiquitinating and promoting proteasome-mediated degradation of the type I BMP receptor Tkv , and that the negative regulation of Tkv by Ube3a is conserved in mammalian cells . These results offer novel insight into the intricate regulation of BMP signaling in the nervous system , and suggest a potential intervention strategy for UBE3A-associated disorders by manipulating BMP signaling via genetic and pharmacological means .
To examine the functions of Ube3a , we generated ube3a mutants through P-element-mediated excisions of EP3214 , an insertion in the first exon . Multiple imprecise excisions ( e . g . , ube3a8 and ube3a35 ) were obtained ( Fig 1B ) . In addition , two nonsense mutations ( ube3a549 and ube3a689 ) induced by the chemical mutagen ethyl methanesulfonate ( EMS ) were identified via a TILLING service ( see Materials and Methods ) ( Fig 1B ) . Western blotting using a mouse monoclonal antibody against the C-terminal peptide containing the HECT ( Fig 1B ) confirmed the absence of Ube3a protein in hemizygous ube3a549/Df ( 3L ) ED4470 ( which removes the ube3a locus completely ) and ube3a689/Df ( 3L ) ED4470 mutants and in homozygous ube3a35 mutants , whereas a truncated protein of 110 kDa was detected in ube3a8 mutants ( Fig 1C ) . Immunostaining of larval and adult tissues using the monoclonal Ube3a antibody 8F7 showed that the endogenous Ube3a was cytoplasmic and widely expressed in various tissues including ventral ganglia , muscles , wing discs , ovaries and testes with an obvious enrichment at presynaptic NMJ terminals ( S1 and S2 Figs ) . Both homozygous and hemizygous ube3a35 mutants , as well as independent null mutants generated in other laboratories [24 , 26] , were fully viable with no apparent developmental abnormalities , and both male and female adults were fertile . Given the synaptic localization of Ube3a in cultured hippocampal neurons [16] , the impaired LTP and defective synaptic transmission and plasticity observed in Ube3a mutant mice [10 , 11 , 14] , and the presynaptic enrichment of Ube3a ( S1 Fig ) , we hypothesized that Drosophila ube3a may play an important role at synapses . To test this possibility , we examined the NMJs of wandering third instar larvae by staining them with anti-cysteine string protein ( CSP ) , a synaptic vesicle marker , and anti-horseradish peroxidase ( HRP ) , which labels the presynaptic neuronal membrane . In ube3a35 null mutants , the total bouton number for muscle 4 NMJs in abdominal segments A2 and A3 was 33 . 4 ± 1 . 2 , which was significantly higher than 26 . 8 ± 1 . 1 in wild-type ( WT ) larvae ( P < 0 . 001 ) ( Fig 2A and 2B ) . Similar to homozygous ube3a35 mutants , allelic combination of ube3a35/ube3a549 and hemizygous ube3a35/Df ( 3L ) ED4470 and ube3a549/Df ( 3L ) ED4470 also showed more boutons than the wild type . The number of satellite boutons budding from a parental bouton in ube3a35 mutants was also significantly higher than in wild-type larvae; these satellites were more frequent at the distal ends of NMJ terminals ( Fig 2A and 2C ) . To confirm that the observed phenotype was attributable to loss of ube3a , we conducted rescue experiments using a genomic transgene . One copy of wild-type ube3a restored the number of total and satellite boutons in ube3a35 mutants ( Fig 2A , 2B and 2C ) . However , a ube3a genomic transgene carrying the missense mutation C941A disrupting the thioester bond with ubiquitin did not ( Fig 2A , 2B and 2C ) , although it was expressed at a level comparable to the wild-type genomic transgene . To determine whether ube3a exerts its effect on the pre- or postsynaptic side , we knocked down Ube3a expression by RNA interference ( RNAi ) in a tissue-specific manner . Targeted knockdown of ube3a in presynaptic neurons by elav-Gal4-driven Thu3266 RNAi resulted in a modest but significant increase in the number of total boutons ( 20 . 15% ) and a dramatic increase in satellite boutons ( 371 . 7% ) compared to wild-type larvae ( Fig 2 ) . Motoneuron specific knockdown of ube3a by OK6-Gal4 also showed overgrown NMJs ( S3 Fig ) , whereas knockdown of ube3a in postsynaptic muscles using C57-Gal4 had no effect on bouton number ( P > 0 . 05 compared to wild type; Fig 2 ) . Similar results were observed using an independent RNAi line VDRC45876 . These findings together demonstrate that Ube3a regulates NMJ synapse growth presynaptically . An increased number of satellite boutons at NMJs is closely associated with a defect in endocytosis [32–34] . To find out if ube3a mutant NMJs exhibited an endocytic defect , we first examined NMJ synapses by electron microscopy . The critical synaptic structures such as active zones and subsynaptic reticulum appeared normal in ube3a mutant boutons . Specifically , the mean density of synaptic vesicles ( SVs ) within a 200 nm radius of the active zone of transmitter release was normal in ube3a mutants compared to wild type ( S4 Fig ) , as reported previously [35] . However , significantly more enlarged vesicles > 60 nm in diameter ( also known as cisternae , presumably endosomes ) per bouton cross-section were observed in ube3a mutants ( 5 . 06 ± 0 . 90 in ube3a vs 1 . 19 ± 0 . 21 in wild type; n ≥ 38 boutons from ≥ 4 larvae , ***p < 0 . 001; S4 Fig ) , suggesting a vesicle formation defect . We then examined both evoked and spontaneous synaptic glutamate release at ube3a35 mutant NMJs using intracellular recordings . We first stimulated motor neurons at a low frequency of 0 . 3 Hz in the presence of 0 . 5 mM Ca2+ . The amplitudes of excitatory junctional potentials ( EJPs ) and miniature EJPs ( mEJPs ) in ube3a35 mutants did not differ from those in the controls ( Fig 3A and 3B ) . The mEJP frequency in ube3a mutants was similar to that in wild-type larvae ( Fig 3C ) . Representative traces of EJP and mEJP of wild type ( A ) and ube3a35 mutant ( B ) are shown in S5 Fig . Thus , the basal transmission appeared normal in ube3a mutants . We then examined the ability of ube3a mutants to maintain neurotransmitter release during intense stimulation . The EJP amplitudes in ube3a mutants under high-frequency stimulation of 10 Hz in the presence of 0 . 5 mM extracellular Ca2+ for 10 min declined much faster and remained at 64% of the initial response ( Fig 3 ) . In contrast , control animals sustained release at about 85% of the initial amplitude of EJP ( Fig 3D ) . The inability of ube3a mutants to maintain normal levels of transmission during intense activity is consistent with a specific defect in vesicle trafficking or recycling . Finally , to examine whether endocytosis is affected in ube3a mutant NMJ synapses , we performed fluorescent dye FM1-43 uptake experiments . There was intense labeling of FM1-43 at wild-type synaptic boutons , whereas ube3a35 mutants showed significantly reduced uptake of FM1-43 by 34 . 1% compared to wild type ( p < 0 . 001; Fig 3E and 3F ) . Importantly , the endocytosis defect could be fully rescued by one copy of the genomic ube3a transgene ( Fig 3E and 3F ) . The failure to maintain neurotransmission under tetanic stimulation and reduced dye uptake support that ube3a is required for efficient synaptic vesicle endocytosis . ube3a mutations resulted in more satellite boutons and endocytic defects ( Figs 2 and 3 ) . We investigated the underlying mechanism of the synaptic defects in ube3a mutants . Synapse formation requires the coordinated activity of several signaling cascades . At the Drosophila NMJ , the BMP pathway acts in a retrograde manner from muscles to motor neurons and promotes NMJ growth [30 , 34 , 36–39] . We hypothesized that the overgrowth of synaptic boutons in ube3a mutants may be caused by elevated BMP signaling . To test this possibility , we examined genetic interactions between ube3a and the major genes of the BMP signaling pathway , tkv and mad . Compared to wild type , muscle 4 NMJ terminals were overgrown in ube3a35 mutants as described above , but severely underdeveloped in tkv8/tkvK16713 mutants ( Fig 4A and 4B ) . In ube3a tkv double mutants , bouton numbers were similar to that of tkv single mutants ( Fig 4A and 4B ) , suggesting that the overgrowth of NMJ synapses produced by loss of ube3a may be mediated by alterations in BMP signaling . Furthermore , NMJ overgrowth in ube3a mutants was dependent on the level of Tkv and the BMP effector Mad . Loss of one copy of tkv , which alone had no effect on bouton number , reversed the increase in satellite bouton number caused by loss of Ube3a ( Fig 4A , 4B and 4C ) . Mutating one copy of mad also suppressed the overgrowth of NMJ synapses in ube3a mutants ( Fig 4B and 4C ) . These results indicate that the excessive synaptic growth induced by loss of ube3a is mediated by elevated levels of the BMP signaling components Tkv , Mad , or both . BMP receptor activation leads to phosphorylation of Mad ( pMad ) , which then translocates to the nucleus to activate target gene transcription . Elevated pMad levels are thus indicative of active BMP signaling [34 , 40 , 41] . To determine if ube3a loss-of-function does indeed lead to NMJ overgrowth through upregulated BMP signaling , we quantified the level of pMad in NMJ synapses and motoneuron nuclei . pMad staining intensity at NMJ synapses was significantly increased by 56 . 5% in ube3a35 mutants compared to wild type ( P < 0 . 001; Fig 5A and 5B ) . The intensity of pMad immunofluorescence was also significantly higher in motoneuron nuclei of ube3a mutants than in wild types ( P < 0 . 001; Fig 5A and 5B ) . Furthermore , pMad expression was elevated in larval brain extracts as measured by western analysis ( Fig 5C and 5D ) . One copy of the genomic ube3a transgene fully reversed the increased pMad levels at both NMJs and motoneuron nuclei of ube3a mutants ( Fig 5A and 5B ) . These results show that ube3a negatively regulates pMad expression at both NMJs and motoneuron nuclei . Remarkably , the increased pMad staining , together with reduced dye loading and faster rundown of EJP amplitudes , in ube3a mutants is fully rescued by reducing the dose of Tkv by half ( S6 Fig ) . Given that Ube3a is an E3 ubiquitin ligase , we examined the protein expression levels of BMP signaling components in ube3a mutants to determine whether any are Ube3a substrates . Western blotting of larval brain extracts showed that pMad level was significantly increased by 203% , while Mad level was increased by 71% in ube3a mutants , consistent with the staining results ( Fig 5A–5D ) . As a high quality of antibody against Tkv was not readily available , we took advantage of a yellow fluorescent protein ( YFP ) gene trap line that expresses functional YFP-tagged Tkv ( Tkv-YFP ) in the ventral nerve cord , including motoneurons under the control of the endogenous promoter ( S7 Fig ) . Western blotting with an anti-GFP antibody that also recognizes YFP , showed that the protein level of Tkv-YFP was increased by 216% in ube3a mutants compared to wild type ( P < 0 . 001 ) , while the level of the endogenous Sax and Wit , the other type I and type II BMP receptors , respectively , was unaltered ( Fig 5C and 5D ) . This suggests that Tkv is a primary target of Ube3a-mediated degradation . Indeed , the fluorescence intensity of elav-Gal4-driven Tkv-GFP was elevated by 59 . 2% at NMJ synapses of ube3a mutants compared to wild type ( Fig 5E and 5F ) . Quantitative real-time PCR , however , detected similar levels of tkv mRNA in the brains of ube3a35 mutant and wild-type larvae ( Fig 5G ) , indicating that the increase in Tkv protein expression in ube3a mutants is likely due to post-transcriptional regulation . As Tkv acts upstream of Mad , and Tkv protein level is obviously upregulated in ube3a mutants , we focused on the mechanisms mediating negative regulation of Tkv by Ube3a by examining the stability of Tkv protein in S2 cells at various time points after treatment with the protein synthesis inhibitor cycloheximide . In control cells transfected with double-stranded RNAs ( dsRNAs ) against GFP , Tkv level decreased markedly from 1 . 5 h to 9 h upon drug treatment ( Fig 6A ) . In Ube3a knockdown cells , however , a relatively stable level of Tkv was observed ( Fig 6A and 6B ) . Ube3a knockdown resulted in a significantly elevated level of pMad ( 1 . 6 times the control ) and Tkv ( 2 . 7 times the control ) at 48 h after dsRNA transfection ( Fig 6C and 6D ) . This effect was confirmed by using a distinct dsRNA targeting a different sequence of ube3a mRNA , demonstrating the specificity of Tkv downregulation by Ube3a . To determine whether Tkv stability is regulated by the proteasomal degradation pathway , Tkv protein level was measured in Ube3a-overexpressing S2 cells treated with the 26S proteasome inhibitor MG132 . In contrast to the upregulation of Tkv observed upon Ube3a knockdown , Tkv levels were significantly reduced by 50 . 17% in Ube3a-overexpressing cells compared with GFP-overexpressing control cells , and this effect was abolished by MG132 treatment ( Fig 6E ) . These results indicate that Ube3a negatively regulates Tkv protein levels by targeting the protein for proteasome-mediated degradation . Given the increased stability of Tkv in Ube3a knockdown cells and the involvement of the proteasome in Tkv degradation ( Fig 6 ) , Tkv may be a direct target for Ube3a-mediated ubiquitination and ensuing proteasome-mediated degradation . This model predicts a physical interaction between the two , and direct ubiquitination of Tkv by Ube3a . We investigated the physical interaction between Ube3a and Tkv by co-immunoprecipitation ( co-IP ) . In third instar larval brain extracts , endogenous Ube3a co-precipitated with Tkv-YFP using an antibody against GFP , but was absent in control immunoprecipitates using anti-IgG ( Fig 7A ) . We defined the regions mediating the interaction in S2 cells and found that the N-terminal 201–400 and 400–640 amino acid fragments of Ube3a each interacted with Tkv , while the STYKc domain of Tkv mediated its interaction with Ube3a ( S8 Fig ) . Co-localization of Tkv-GFP and Ube3a driven by elav-Gal4 was observed in the soma of motoneurons in the ventral ganglion ( 6 . 3 puncta positive for both Tkv-GFP and Ube3a per neuron , n = 16; Fig 7B ) , further supporting a physical interaction between Ube3a and Tkv . To establish whether Tkv is a direct substrate of Ube3a-mediated ubiquitination , we measured the level of unmodified and ubiquitinated Tkv in S2 cells . In Ube3a knockdown cells , Tkv poly-ubiquitination was reduced ( Fig 7C ) . Conversely , overexpression of Ube3a caused an increase in Tkv poly-ubiquitination ( Fig 7D ) . Poly-ubiquitination occurred at lysine 48 of ubiquitin ( Fig 7D ) ; a form of poly-ubiquitination that targets proteins for proteasomal degradation [42] . An in vitro ubiquitination assay further revealed that GST-Ube3a induced poly-ubiquitination of myc-TkvC , while neither GST alone , the control E3 ligase Parkin , nor a cocktail missing the essential component ubiquitin , led to TkvC poly-ubiquitination ( Fig 7E ) . To verify if the negative of BMP signaling by Ube3a occurred in vivo , we treated dissected larvae with MG132 for 4 h and observed a significantly increased level of pMad at both NMJs and motoneuron nuclei ( S9 Fig ) . Blocking proteasome function by expressing a dominant negative proteasomal subunit DTS5 in presynaptic neurons by elav-Gal4 also resulted in a similar increase of pMad staining ( S9 Fig ) . Western blotting of larval brain lysates showed a decreased level of ubiquitinated Tkv in ube3a mutants ( Fig 7F ) . These results demonstrate that Ube3a promotes ubiquitin-mediated degradation of Tkv . Given that Ube3a ubiquitinated Tkv and promoted its degradation by proteasome pathway ( Figs 6 and 7 ) , we aimed to identify specific amino acids of Tkv targeted by UBE3A . Mass spectrometry revealed two potential ubiquitinated residues , lysine 218 and 227 , in the C-terminal STYKc region of Tkv ( Fig 8A ) . To verify which specific sites of Tkv were ubiquitinated by Ube3a , we mutated lysine to arginine at two individual sites , namely , K218R and K227R . We compared the stability of wild-type and mutant Tkv protein in S2 cells by western blotting following treatment with cycloheximide to inhibit protein synthesis for 0 , 3 and 6 h . We found that the stability of K218R was comparable to that of wild-type Tkv , the levels of both decreased with time , while the amount of K227R remained stable within 6 h treatment of cycloheximide ( Fig 8B and 8C ) . Ubiquitination analysis showed that K218R was as sensitive as wild-type Tkv for ubiquitination in S2 cells by Ube3a in the presence of HA-Ub and MG132 ( Fig 8D and 8E ) . There was a concomitant significant reduction in wild-type and mutant Tkv protein level , while K227R was stable and ubiquitination resistant ( Fig 8D and 8E ) . These results demonstrate that K227 is a key target residue for ubiquitination by Ube3a . Given that Ube3a is evolutionarily conserved from Drosophila to vertebrates , we hypothesized that human UBE3A would interact with and negatively regulate ALK3 , a mammalian homolog of Tkv [43] . To test this possibility , we examined the co-immunoprecipitation of ALK3 with UBE3A in lysates of human HEK293 cells . An anti-HA antibody , but not a control anti-IgG , co-precipitated myc-ALK3 with HA-UBE3A ( Fig 9A ) . UBE3A knockdown in HEK293 cells using two different small interfering RNAs ( siRNAs ) produced a significantly increased level of endogenous ALK3 as well as a near two-fold increase in the level of pSmad; the mammalian counterpart of Drosophila pMad ( Fig 9B and 9D ) . Conversely , overexpression of UBE3A in HEK293 cells led to a significant decrease in ALK3 protein level ( 38 . 1% of the control; n = 3 , P < 0 . 001 ) , which was blocked by the proteasome inhibitor MG132 ( Fig 9C ) , implying that human UBE3A promotes the proteasomal degradation of ALK3 . Overexpression of wild type but not the ligase dead C833A mutant UBE3A significantly increased ubiquitination of myc-ALK3 , while GFP control did not ( Fig 9E ) . Despite the fact that the corresponding K227 in ALK3 is not critical for ubiquitination in HEK293 cells ( S10 Fig ) , consistent with the fact that some proteins have little specificity in ubiquitination sites [44] , our results demonstrate that Ube3a-mediated suppression of BMP signaling is conserved in mammalian cells .
The synapse is a critical substrate for cognitive function , so disorders associated with intellectual and cognitive deficits , such as AS and autism , likely involve altered pathways that disrupt synaptic development and plasticity . The present study shows for the first time that ube3a regulates synapse formation and synaptic endocytosis at the Drosophila NMJ . A previous study reported normal NMJ growth in ube3a15B mutants [35] . However , we showed here that the genetic background in homozygous ube3a15B mutants may suppress expression of satellite phenotype , as trans-allelic ube3a15B/ube3a35 and hemizygous ube3a15B/Def mutants showed excess satellite boutons ( S3 Fig ) . We noted that the satellite phenotype in ube3a mutants is mild compared to the classical endocytic endophilin and dap160/intersectin mutants [32 , 45 , 46] . Also , the fewer and larger SVs at active zones accompanied by an increase in amplitudes of mEJPs reported in endocytic mutants such as tweek and dap160/intersectin mutants [45–47] , were not observed in ube3a mutants . However , the significantly higher number of satellite boutons , reduced dye uptake , and defective recovery of EJP amplitudes under high-frequency stimulation , implicate a regulatory role for ube3a in endocytosis at NMJs . It is worth noting that a similar endocytic function has been reported for mammalian Ube3a at inhibitory synapses in the visual cortex [14] . There appears to be a reciprocal regulation between BMP signaling and endocytosis at the Drosophila NMJ . Endocytic mutants show upregulated BMP signaling as demonstrated by increased pMad staining at NMJs [40] . Trio , a Rac GTPase-specific GEF , is positively regulated by pMad at the transcriptional level in motoneuron nuclei for proper NMJ development [48] . Conversely , upregulation of BMP signaling by mutations in Dad , an inhibitory Mad that negatively regulates BMP signaling , and in S6KL ( S6 kinase like ) results in apparent endocytic defects [33 , 34] . In addition to the mutual regulation between the two processes , the multi-domain actin regulator Nwk functions at the interface of endocytosis and BMP signaling by physically interacting with both Tkv and endocytic proteins dynamin and Dap160/intersectin [40] . We found normal expression of endocytic proteins in ube3a mutant NMJs ( S11 Fig ) , and endocytic endophilin A mutants have been shown previously to have a normal level of Tkv [34] . Thus , we favor a model in which upregulated BMP signaling leads to overgrown NMJs and endocytic defects in ube3a mutants , and the NMJ defects in ube3a mutants could be attributable to altered actin-cytoskeletal formation via Trio-Rac-mediated and/or Nwk-mediated pathways . While ube3a mutation leads to an elevated level of BMP signaling , neuronal overexpression of Ube3a by elav-Gal4 or OK6-Gal4 does not result in downregulation of BMP signaling . This was demonstrated by overgrown NMJ terminals and a normal level of pMad at both NMJs and motoneuron nuclei ( S12 Fig ) . These results indicate that overexpression of Ube3a alone is not sufficient to downregulate BMP signaling in the neuromusculature . How Ube3a overexpression leads to overgrown NMJs remains to be determined . Similar overgrown NMJ phenotypes caused by Ube3a mutation and overexpression are consistent with previous reports of defective locomotion [24] and circadian rhythms [25] upon bidirectional changes in Ube3a expression . Using a series of biochemical assays , we showed that Ube3a physically interacts with Tkv and facilitates its proteasome-mediated degradation ( Figs 6 and 7 ) . This function of Ube3a was conserved in mammalian cell cultures ( Fig 9 ) . We identified K227 but not K218 in the cytoplasmic region of Tkv as being critical for its ubiquitination ( Fig 8 ) . We demonstrated that Ube3a normally functions specifically to downregulate Tkv expression by proteasomal degradation , resulting in reduced presynaptic BMP signaling . In the absence of Ube3a , BMP signaling is upregulated , resulting in overgrown NMJs and endocytic defects . The impact of Ube3a on Tkv is limited to the NMJ , as altered expression of Ube3a does not lead to corresponding changes in Tkv expression in wing discs , where the role of Tkv is well known ( S2 Fig ) . Thus , the negative regulation of Tkv by Ube3a occurs in a tissue specific manner . In which neuronal compartment is Tkv ubiquitinated ? Given that Ube3a ( S1 Fig ) , RING finger E3 ligase Highwire [49] , E3 ligase anaphase promoting complex/cyclosome ( APC/C ) [50] , and 20s proteasome subunit [51] are all enriched at NMJ synapses , we favor the possibility that Ube3a ubiquitinates Tkv at presynaptic terminals . We recently identified that an evolutionarily conserved , previously uncharacterized S6KL similarly regulates NMJ growth and endocytosis by promoting proteasomal degradation of Tkv [34] . As Ube3a biochemically and genetically interacts with S6KL ( S13 Fig ) , it remains possible that Ube3a and S6KL work synergistically in inhibiting NMJ growth by targeting Tkv for degradation In addition to Ube3a , another HECT-domain-containing E3 ligase Smurf also inhibits BMP signaling by targeting two independent signaling components , BMP receptors and downstream effector Smad in distinct developmental processes [43 , 52 , 53] . However , Smurf does not regulate NMJ growth [34] . As the protein level of Mad was mildly but significantly increased in ube3a mutant brains ( Fig 5C and 5D ) , it would be of interest to determine if Ube3a also targets Mad for proteasome-mediated degradation in NMJ development . In addition to its role as an ubiquitin E3 ligase , UBE3A has been reported to affect nuclear hormone receptor-mediated transcription by E3 ligase-independent mechanisms [21 , 54] . For instance , UBE3A was shown to inhibit the expression of the cyclin-dependent kinase inhibitor p27 at both transcriptional and post-translational levels [55] . Moreover , UBE3A inhibits estradiol-mediated transcription of the target gene Arc [21] . As with mammalian UBE3A , Drosophila Ube3a also acts as a transcriptional regulator; it activates transcription of Punch , which encodes GTP cyclohydrolase 1 , a component of the monoamine biosynthesis pathway [27] . In support of a transcriptional role , Ube3a orthologs of different species are localized in the nucleus [16 , 23 , 27] . However , the present study reveals that Ube3a functions as an ubiquitin ligase for Tkv but not as a transcriptional regulator since the level of tkv mRNA in ube3a brains was similar to wild type ( Fig 5G ) . Human UBE3A negatively regulated the protein levels of ALK3 , and consequently the downstream effector pSmad , in HEK293 cells ( Fig 9 ) . Therefore , it is tempting to speculate that elevated BMP signaling may contribute to a subset of the abnormalities observed in patients with AS . BMP receptors are expressed at specific sites , such as the hippocampus and cerebellum , where Ube3a is also expressed [10 , 56] . It remains to be determined if BMP signaling is upregulated in these brain regions that correlate with the clinical features of seizures , learning deficit and ataxia in patients with AS . BMP signaling regulates synapse development specifically at the calyx of Held in the auditory system in a way similar to that at Drosophila NMJ , but shows no effect on synapse development in the lateral superior olive of the auditory nucleus [31] . Given that AS mice show an enhanced seizure-like response to audiogenic challenge [22] , it would be improtant to determine if the development and function of the calyx of Held synapses are normal in Ube3a mutant mice . At the microscopic level , AS model mice exhibit normal dendritic elaboration but fewer and shorter dendritic spines in cerebellar Purkinje cells and pyramidal neurons in the hippocampus and cortex [16] . It is not known if BMP signaling plays a role in the formation of dendritic spines , although other targets of Ube3a such as Ephexin5 may regulate spine morphogenesis in hippocampal neurons [20] . In summary , we demonstrated that Drosophila ube3a plays an important role in regulating synapse formation and endocytosis by inhibiting BMP signaling via proteasome-mediated degradation of Tkv . The negative regulation of BMP signaling by Ube3a is conserved in mammals . These findings indicate that increased BMP signaling resulting from loss of UBE3A during development may contribute , at least in part , to the etiology of AS .
All Drosophila stocks were fed standard cornmeal food and maintained at 25°C . w1118 was used as a wild-type control unless otherwise indicated . We generated intragenic ube3a deletions ( ube3a8 and ube3a35 ) through P-element-mediated excisions of EP3214 . Transgenic lines expressing genomic ube3a+ and ube3aC941A ( containing a missense mutation in the codon for the critical catalytic cysteine residue ) were from J . Fischer . UAS-Tkv-GFP was from T . B . Kornberg . UAS-DTS5 was a gift from J . Belote via K . Broadie [51] . The EMS-induced nonsense mutations ube3a549 and ube3a689 were obtained from a TILLING ( targeting-induced local lesions in genomes ) service ( http://tilling . fhcrc . org ) . For tissue-specific rescue experiments , the pan-neural elav-Gal4 ( from Bloomington ) and muscle-specific C57-Gal4 ( from V . Budnik ) lines were used . RNAi lines P{GD450}v45876 and Thu3266 were obtained from the Vienna Drosophila RNAi Center ( VDRC ) and Tsinghua University ( Beijing , China ) , respectively . A yellow fluorescent protein ( YFP ) genetrap line labeling the endogenous Tkv with YFP was obtained from the Drosophila Genome Research Center ( stock number 115298; Kyoto , Japan ) . EP ( 3 ) 3214 , Df ( 3L ) ED4470 , tkv8 , tkvK16713 , mad12 , and witB11 were obtained from the Bloomington Stock Center . For overexpression studies , UAS-ube3a was obtained by amplifying the full-length cDNA of ube3a from a home-made cDNA pool derived from whole adults , and cloned into the vector pUAST . An UAS-ube3a insertion in the X chromosome was used in this study . To generate specific antibodies against Ube3a , a fusion protein containing amino acids 568–973 of Drosophila Ube3a with an N-terminal 6×His tag was produced in E . coli . Mouse monoclonal antibodies produced by clone 8F7 were shown to be specific for Ube3a by western blotting and immunostaining . Immunohistochemical analysis of larval NMJ synapses was performed as previously described [57] . The following antibodies were used: rabbit anti-Tkv ( 1:200; from M . B . O’Connor , University of Minnesota , Minneapolis , Minnesota ) , anti-CSP ( 1:1 , 000 , 6D6 from Developmental Studies Hybridoma Bank ( DSHB ) ) , rabbit anti-GFP ( 1:100 , #632460 from Clontech ) , rabbit anti-pMad ( 1:500; from P . ten Dijke , Leiden University , Leiden , Netherlands ) , anti-HRP conjugated with FITC or Texas red ( 1:50 , Jackson ImmunoResearch Laboratories ) , and anti-Ube3a ( 1:30 , 8F7 as described above ) . All primary antibodies were visualized using fluorophore-conjugated secondary antibodies , including Alexa Fluor 488 or 568-conjugated goat anti-mouse or anti-rabbit IgG ( 1:1 , 000 , Molecular Probes ) . To quantify fluorescence intensities from immunostaining , images of the entire muscle 4 NMJ elaboration or motoneuron nuclei were taken at identical settings for all genotypes without overexposure . The intensity of pMad and Tkv-GFP staining in Fig 5 was calculated as gray values normalized to the pMad- and HRP-positive areas , respectively . The gray values were automatically calculated using ImageJ software ( NIH; Bethesda , USA ) and presented as arbitrary units ( a . u . ) . All images were collected using a Leica SP5 confocal microscope and processed with Adobe Photoshop . For statistical analysis of NMJ morphology , the number of total boutons and satellite boutons of muscle 4 NMJ in abdominal segments A2 and A3 was quantified as previously described [57] . Electrophysiological recordings were performed at 20°C essentially following a conventional procedure with minor modifications [33 , 34] . For the basal transmission assay , wandering third-instar larvae were dissected in Ca2+-free HL3 . 1 saline and recorded in HL3 . 1 saline containing 0 . 5 mM CaCl2 . Intracellular microelectrodes with a resistance greater than 5 MΩ filled with 3 M KCl were used for the assay . Excitatory junction potential ( EJPs ) and miniature EJPs ( mEJPs ) were recorded from muscle 6 in the abdominal segments A2 or A3 for 120 seconds . EJPs were elicited by low frequency ( 0 . 3 Hz ) stimulation . We analyzed recordings from muscles cells with physiological resting potentials ≤ -60 mV and input resistances > 5 MΩ . For examining synaptic transmission under tetanic stimulation , synapses were stimulated at 10 Hz for 10 minutes and recorded in a modified HL3 . 1 saline with 0 . 5 mM extracellular Ca2+ . For the FM1-43 uptake assay , we followed a previously published protocol [34 , 58] . S2 cells were cultured in Schneider’s medium ( Invitrogen , Carlsbad , USA ) and transfected using Cellfectin II reagent ( Invitrogen ) . For the production of double-strand RNA ( dsRNA ) targeting ube3a and gfp , DNA fragments were synthesized by PCR using primers containing a T7 promoter sequence ( italicized ) : ube3a sense: 5’-TAA TAC GAC TCA CTA TAG GGA TTG CCG GAA ACC ACT GAT A-3’ and antisense: 5’-TAA TAC GAC TCA CTA TAG GGC TCC GTT CTC AAA TGG TGT G-3’ , and gfp sense: 5’-TAA TAC GAC TCA CTA TAG GGA TGG TGA GCA AGG GCG AGG A-3’ and antisense: 5’-TAA TAC GAC TCA CTA TAG GGC TTG TAC AGC TCG . The dsRNAs were transcribed from both strands of the PCR-amplified DNA fragments using a Megascript T7 kit ( AM1333; Invitrogen ) , and purified using an RNeasy kit ( Qiagen ) . To examine Tkv protein turnover , S2 cells were transfected with dsRNAs against ube3a or gfp ( control ) at an average transfection efficiency of about 46% , and treated 48 h later with 40 μg/ml cycloheximide ( Sigma ) for 0 , 1 . 5 , 3 , 6 , and 9 h . To determine whether the degradation of Tkv was proteasome-dependent , S2 cells were co-transfected with flag-Ube3a or flag-GFP plasmid together with myc-Tkv . After 48 h , cells were treated with 20 μM MG132 ( Sigma ) or mock treated for 6 h before being harvested for western blotting . Human HEK293 cells were maintained in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum ( Invitrogen ) at 37°C in a humidified incubator with 5% CO2 . For efficient RNAi knockdown of human UBE3A , UBE3A siRNA1 ( 5’-GGG UCU ACA CCA GAU UGC UTT-3’ ) [59] , siRNA2 ( 5’-CAA CUC CUG CUC UGA GAU ATT-3’ ) [60] , and a scrambled siRNA control ( 5’-UUG CGG GUC UAA UCA CCG ATT-3’ ) were synthesized and transfected into HEK293 cells using X-tremeGENE siRNA transfection reagent ( Roche ) . UBE3A and ALK3 ( also named BMPR1A ) clones were provided , respectively , by Dr . Peter M Howley and William C . Hahn at Harvard Medical School ( Cambridge , USA ) . UBE3A and ALK3 coding sequences were subcloned to generate pCMV-Tag2B-HA-UBE3A and pCDNA3-myc-ALK3 , respectively . IP assays of larval brains and ventral ganglia were carried out according to a previous report [61] . Immunoprecipitation from S2 or HEK293 cell lysates was performed following a previously described protocol [43] . Antibodies used for western blotting were: anti-myc ( 1:1000; 9E10 from Clontech ) , anti-flag ( 1:1 , 000; M2 from Sigma ) , anti-K48 ( 1:1 , 000; D9D5 from Cell Signaling Technologies ) , anti-GFP ( 1:1 , 000 ) , anti-Ube3a ( 1:300 ) , anti-HA ( 1:1 , 000; 3F10 from Roche ) , anti-ubiquitin ( 1:1000; P4D1 from Cell Signaling Technologies ) , anti-Wit ( 1:50; DSHB ) , anti-pSmad ( 1:1000; Cell Signaling Technologies ) , and anti-α-tubulin ( 1:25 , 000; mAb B-5-1-2 from Sigma ) . To analyze protein levels in different genotypes , larval brains and ventral ganglia were homogenized in ice-cold lysis buffer ( 50 mM Tris-HCl ( pH 7 . 4 ) , 150 mM NaCl , 1% ( v/v ) NP-40 , 0 . 1% ( w/v ) SDS , 1% ( v/v ) proteinase inhibitor ) . Western blots were probed with primary antibodies anti-Ube3a , anti-pMad ( 1:500 , Cell Signaling Technologies ) , anti-Wit , anti-GFP , and anti-α-tubulin , followed by HRP-conjugated secondary antibody ( 1:25 , 000; Sigma ) . For in vivo ubiquitination assay , S2 cells were transfected with plasmids using Cellfectin II reagent ( Invitrogen ) . The ubiquitination assay was performed according to the protocols described previously [43] . In brief , at 48 hr posttransfection , MG132 was added into the media at the final concentration 50μM . Cells were harvested 4 hr later and lysed with a lysis buffer ( 50 mM Tris [pH 7 . 5] , 120 mM NaCl , and 0 . 5% NP40 ) containing 1% ( w/v ) SDS to disrupt protein–protein interaction and boiled for 10 min , then diluted 10 times with cell lysis buffer . To detect the levels of ubiquitinated Tkv in vivo , 200 larval brains of each genotype ( elav-Gal4; tkv-GFP and elav-Gal4; tkv-GFP; ube3a35 ) were dissected and incubated with 50 μM MG132 ( Sigma ) in Schneider’s medium for 4 h to inhibit proteasome-mediated degradation before proceeding with IP . The brains were then homogenized in lysis buffer and the lysates were immunoprecipitated with anti-GFP . The ubiquitinated Tkv was examined by anti-ubiquitin antibody . For in vitro ubiquitination assay , the myc-tagged Tkv C-terminus ( myc-TkvC ) was synthesized by an in vitro translation kit containing rabbit reticulocyte lysates ( Promega ) . Ube3a was fused to GST , then expressed and purified from E . coli . E1 , E2 , HA-Ub ( all three from Boston Biochem ) , and the potential substrate myc-TkvC , together with the GST control , the E3 ligase Parkin control , or GST-Ube3a , were incubated at 30°C for 1 . 5 h in 40 μl ubiquitination reaction buffer ( 50 mM Tris-HCl ( pH 7 . 5 ) , 1 mM dithiothreitol , 50 mM NaCl , 5 mM MgCl2 , 2 mM ATP ) . Reactions were terminated by adding SDS-PAGE sample buffer and analyzed by western blotting . Mass spectrometry was performed as described previously [62] . myc-Tkv expressed in S2 cells was immunoprecipitated with an anti-myc antibody . The target protein was excised , digested with trypsin , fractionated by HPLC , and analyzed by a LTQ Orbitrap Elite mass spectrometer ( ThermoFisher Scientific , Waltham , MA ) . To further verify the sites of Tkv targeted by Ube3a , myc-Tkv mutants K218R and K227R were generated by site-directed mutagenesis . Total RNA was extracted from brains and ventral nerve ganglia of 40 third instar larvae following the standard Trizol reagent protocol ( Invitrogen ) . Power SYBR Green PCR Master Mix ( Applied Biosystems ) was used for quantitative real-time PCR . Actin mRNA level was amplified as an internal control using published primers [33] , whereas tkv cDNA was amplified with primers 5’-GTG ATA GGG CAG GGC GTA GT-3’ and 5’-AGT GGG TCT CGT TCT GTG GG-3’ . Student’s t tests were used for statistical comparisons between two groups . Multiple group means were compared by one-way ANOVA . Asterisks above a column indicate comparisons between a specific genotype and wild type , whereas asterisks above a bracket denote comparisons between two specific genotypes . Data are presented as mean ± standard error of the mean ( SEM ) . P-values < 0 . 05 were considered statistically significant . | Angelman syndrome ( AS ) , characterized by severe mental retardation , developmental delay , ataxia , seizures , speech impairment , and happy disposition , is caused by mutation of E3 ubiquitin ligase UBE3A; a critical enzyme involved in proteasome-mediated protein degradation . Increasing evidence demonstrates that overexpression or hyperactivation of UBE3A is associated with autism . Thus , both loss and gain of UBE3A functions result in neurodevelopmental and cognitive defects . However , the neuronal functions of UBE3A and the mechanism by which altered expression of UBE3A leads to developmental and cognitive defects are poorly understood . Using Drosophila melanogaster as a model system in conjunction with an array of biochemical and physiological assays , we showed that mutants of ube3a had excess synaptic boutons and endocytic defects at the neuromuscular junction terminals due to an elevated level of bone morphogenetic protein ( BMP ) signaling . Specifically , Ube3a directly binds and ubiquitinates the BMP receptor Thickveins for proteasomal degradation; a function that is conserved in mammalian cells . Negative regulation of BMP signaling by UBE3A suggests a previously unknown molecular mechanism that underlies the pathogenesis of UBE3A-associated AS and autism . | [
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"immunoprecip... | 2016 | Angelman Syndrome Protein Ube3a Regulates Synaptic Growth and Endocytosis by Inhibiting BMP Signaling in Drosophila |
Small nucleolar RNAs ( snoRNAs ) are localized within the nucleolus , a sub-nuclear compartment , in which they guide ribosomal or spliceosomal RNA modifications , respectively . Up until now , snoRNAs have only been identified in eukaryal and archaeal genomes , but are notably absent in bacteria . By screening B lymphocytes for expression of non-coding RNAs ( ncRNAs ) induced by the Epstein-Barr virus ( EBV ) , we here report , for the first time , the identification of a snoRNA gene within a viral genome , designated as v-snoRNA1 . This genetic element displays all hallmark sequence motifs of a canonical C/D box snoRNA , namely C/C′- as well as D/D′-boxes . The nucleolar localization of v-snoRNA1 was verified by in situ hybridisation of EBV-infected cells . We also confirmed binding of the three canonical snoRNA proteins , fibrillarin , Nop56 and Nop58 , to v-snoRNA1 . The C-box motif of v-snoRNA1 was shown to be crucial for the stability of the viral snoRNA; its selective deletion in the viral genome led to a complete down-regulation of v-snoRNA1 expression levels within EBV-infected B cells . We further provide evidence that v-snoRNA1 might serve as a miRNA-like precursor , which is processed into 24 nt sized RNA species , designated as v-snoRNA124pp . A potential target site of v-snoRNA124pp was identified within the 3′-UTR of BALF5 mRNA which encodes the viral DNA polymerase . V-snoRNA1 was found to be expressed in all investigated EBV-positive cell lines , including lymphoblastoid cell lines ( LCL ) . Interestingly , induction of the lytic cycle markedly up-regulated expression levels of v-snoRNA1 up to 30-fold . By a computational approach , we identified a v-snoRNA1 homolog in the rhesus lymphocryptovirus genome . This evolutionary conservation suggests an important role of v-snoRNA1 during γ-herpesvirus infection .
The Epstein-Barr virus ( EBV ) , a member of the γ-herpesvirus subfamily , possesses a large ( 170 to 180 kb ) double-stranded DNA genome . EBV infection is etiologically linked with various cancers of the lymphoid and epithelial lineages that include Burkitt's lymphoma ( BL ) , Hodgkin's disease , nasopharyngeal carcinoma ( NPC ) and post-transplant lymphoproliferate disease ( PTLD ) [1]–[4] . In vitro and in vivo , EBV transforms normal B cells through establishment of a type III latency during which a restricted set of viral genes is expressed ( eight Epstein-Barr nuclear antigens and two latent membrane proteins ) [5] . More restricted expression patterns such as latency type II in NPC and latency type I in BL have also been characterized . In fact , recent work on Burkitt's lymphoma has shown that a subset of these tumours display a latency pattern intermediate between latency I and III showing that the boundaries between the latency types are not always sharply established as initially thought [6] . More then two decades ago , the group of J . Steitz discovered two highly abundant ∼170-nt long non-coding RNAs ( ncRNAs ) in the EBV genome , designated as Epstein-Barr encoded RNAs ( EBER1 and EBER2 ) [7] . EBER RNAs have subsequently been shown to bind to human ribosomal protein L22 . However , no unequivocal biological functions could be assigned to EBER transcripts , up till now [8] . The list of non-coding RNAs encoded by EBV has since rapidly expanded with the recent discovery of 25 microRNAs ( miRNAs ) [9]–[14] . In addition to miRNAs , numerous other ncRNAs have been discovered in all three domains of life , i . e . Archaea , Bacteria and Eukarya , as well as in various viruses [15] , [16] . A large number of these ncRNA species were found to be involved in multiple regulatory functions including cellular differentiation and development , chromatin architecture , transcription and translation , alternative splicing , RNA editing , virulence and stress responses [17]–[20] . Small nucleolar RNAs ( snoRNAs ) consist of more than 200 stable ncRNA species in Eukarya of about 60 to 300 nt in size which are located in a sub-nuclear compartment , the nucleolus [21] , [22] . SnoRNAs guide nucleotide modifications within ribosomal RNAs ( rRNAs ) or spliceosomal RNAs ( snRNAs ) , i . e . 2′-O-ribose methylation or pseudouridylation , respectively . The snoRNA class has been identified in Archaea and Eukarya , but not in Bacteria , and is subdivided into box C/D and box H/ACA snoRNAs . In Eukarya , the majority of snoRNAs is located within introns of protein-coding genes and is processed by splicing followed by endo- and exonucleolytic cleavage [19] , [23] , [24] . Each member of the box C/D snoRNA family possesses characteristic sequence elements called box C ( PuUGAUGA ) and box D ( CUGA ) , optional degenerate C′/D′ boxes and a short 5′-3′ terminal stem structure [24] , [25] . 10–21 nt long sequence-specific antisense elements upstream of the boxes D/D′ guide the box C/D snoRNA core proteins fibrillarin , a RNA methyltransferase , Nop56 , Nop58 and the 15 . 5 kD protein to the target RNA . 2′-O-methylation of the ribose at the fifth nucleotide upstream of the D/D′ box on the target RNA is carried out by the fibrillarin core protein [24] . Box H/ACA snoRNAs possess a distinctive common ACA sequence motif at their 3′-terminus and one to two stem-loop structures linked by a hinge ( the so-called H-box motif: ANANNA , with N being any nucleotide ) , and guide the conversion of uridine to pseudouridine within the RNA target [26] , [27] . The large number of conserved modifications in functionally conserved regions of rRNAs , such as the peptidyl-transferase centre , has suggested an important role for rRNA modifications in fine-tuning the structure and/or function of rRNAs [28] . It is important to note that a significant number of so-called “orphan” snoRNAs , lacking rRNA or snRNA targets , have been identified in Eukarya [29] , [30] . However , the biological functions of orphan snoRNAs are still elusive . In this study , we report , for the first time , the identification of a functional C/D box snoRNA within the EBV genome . We demonstrate that this viral snoRNA exhibits all bona fide box C/D snoRNA features with respect to its processing and expression , nucleolar localization as well as to canonical core protein binding partners . We also provide evidence that v-snoRNA1 is processed into a 24 nt long miRNA-like species which might target the 3′-UTR of the viral DNA polymerase mRNA .
We have established an experimental strategy , designated as SHORT , to identify viral-induced ncRNAs in cord blood lymphocytes ( CBL ) infected with the EBV strain B95 . 8 [31] . The SHORT method is based on subtractive hybridisation of ncRNA populations of virus-infected cells from non-infected cells . NcRNAs , selectively expressed in the infected cell population , were subsequently converted into cDNAs . Sequencing of a small number , i . e . about 500 cDNA clones , allowed identification of several ncRNAs from the human as well as from the EBV genome whose expression was up-regulated upon viral infection [32] . Deep-sequencing analysis of 40 . 000 cDNA clones from this subtracted cDNA library further extended the list of differentially expressed ncRNAs ( Hutzinger et al . , manuscript in preparation ) . Interestingly , one of these sequences was represented by 95 cDNAs and exhibited all defining features of canonical C/D box snoRNA sequence motifs , i . e . C , C′ , D′ and D boxes [24] , [25] . Crucially , this potentially novel snoRNA species mapped to the EBV genome and was therefore designated as v-snoRNA1 ( Figure 1A , and see above; Accession number FN376861 ) . It is noteworthy that the canonical terminal stem-structure , formed by the 5′ and 3′ ends of eukaryal snoRNAs , was absent in the viral snoRNA , a feature shared with snoRNAs identified from archaeal or fungal species [33] , [34] . To assess expression of v-snoRNA1 , northern blot analysis was performed employing RNA from EBV-positive cell lines ( Rael , Raji , BL2-B95 . 8 , BL41-B95 . 8 and a LCL generated in vitro with the B95 . 8 virus ) or EBV-negative cell lines ( BL2 and BL41; Figure 1B ) . As expected , v-snoRNA1 could only be detected in infected cells but not in the EBV-negative control cells . Comparison with an internal RNA marker showed that the hybridized RNA species was 65 nt in size , which fully matched the size suggested by the original sequence obtained by cDNA cloning ( see above and Figure 1B ) . Repeated attempts to identify v-snoRNA1-precursor transcripts by northern blot analysis were unsuccessful ( unpublished data ) , suggesting that they are subjected to rapid processing . The v-snoRNA1 gene is located within the BamHI A rightward transcripts , known as BARTs , on the sense strand of the viral genome and maps about 100 nt downstream of the EBV mir-BART2 ( Figures 2A and 2B ) . The BARTs represent abundant RNA species in EBV that are expressed in all latently infected EBV-B cell lines , in peripheral blood B cells of EBV-positive individuals and , at higher levels , in nasopharyngeal carcinoma [35] , [36] . They do not encode for proteins but are processed into 22 different BART miRNAs ( Figure 2A ) [14] . Thereby , v-snoRNA1 as well as mir-BART2 arise from the same intron , which was found to be 4 . 9 kb in size in the AG876 strain ( Accession number AJ507799 ) [35] . BART transcripts were previously shown to be predominantly transcribed from the P1 promoter [36] . However , P2 promoter-initiated BARTs were also detected in different B-cell lines with the exception of the EBV-positive BL cell line Raji . As shown in Figure 1B , v-snoRNA1 expression was verified in all tested EBV cell lines , including Raji cells , although expression levels varied considerably . In particular , v-snoRNA1 was expressed in Raji cells at barely detectable levels . Therefore , we infer that v-snoRNA1 transcription can be initiated at the P1 promoter but that the P2 promoter might be required to obtain full expression . To determine the sub-cellular location of v-snoRNA1 within EBV-infected cells , we employed fluorescent in situ hybridization ( FISH ) with dye-labeled antisense oligonucleotides complementary to v-snoRNA1 . As a control , we also investigated the localization of U3 snoRNA , which is known to be localized in the nucleolus [37] , [38] . Examination of EBV-infected BL2 cells by confocal microscopy revealed that both v-snoRNA1 and U3 snoRNA in fact co-localized to the nucleolus ( Figure 3A ) . In contrast , a v-snoRNA1 hybridization signal was absent in non-infected B cells . Canonical C/D box snoRNAs have previously been shown to bind to four snoRNA core proteins: fibrillarin , Nop56 , Nop58 , and the 15 . 5 K protein , respectively . These proteins have previously been shown to be strictly required for RNA maturation , stabilization and function [22] , [39] . The C/D box proteins assemble with snoRNAs thus forming ribonucleo-protein complexes ( snoRNPs ) that localize to the nucleolus . In order to assess whether v-snoRNA1 assembles into a canonical C/D box snoRNP , binding of v-snoRNA1 to three of these canonical snoRNA-binding proteins ( fibrillarin , Nop56 and Nop58 ) was assessed by co-immunoprecipitation using specific antibodies . Immuno-precipitated samples were subsequently analyzed for the presence of v-snoRNA1 by northern blot analysis . These assays demonstrated that v-snoRNA1 and the canonical U81 snoRNA , used as a positive control , were both co-immunoprecipitated with similar efficiencies with antibodies against all three snoRNA-binding proteins ( Figure 3B ) . In contrast , none of the snoRNAs was precipitated in controls without antibodies or employing an IgG-specific antibody . Hybridization with an oligonucleotide specific for 5 . 8S rRNA was used to test for the specificity of the employed antibodies . Thereby , a faint , unspecific signal was detected in all samples after antibody addition , except the control without an antibody . This is likely caused by the high expression levels of 5 . 8S rRNA in our samples . From these results we conclude that the newly identified 65 nt long viral RNA transcript displays all hallmark features of a genuine box C/D snoRNA . A common trait shared by all herpesviruses is their ability to infect their target cells under several modes; cells can support lytic replication during which new virus progeny is replicated or instead induce virus latency . Viral proteins used in both modes are usually , but not always , distinct . We therefore assayed v-snoRNA1 expression in latently infected cells or in cells undergoing lytic replication . We took advantage of LCLs established with viruses that are devoid of the lytic immediate early gene BZLF1 ( ΔBZLF1 ) and therefore cannot initiate lytic replication [40] and examined v-snoRNA1 expression in these cells by northern blot analysis ( Figure 4 ) . Northern blot signals were clearly visible in these cells thereby demonstrating that v-snoRNA1 is a latent transcript . We then performed the same experiment with replication-competent 293/EBV-wt cells lytically induced by transfection of the BZLF1 gene ( Figure 4 ) . Comparison with non-induced cells showed that the v-snoRNA1 expression levels were up-regulated up to 30-fold following induction ( Figure 4 ) . V-snoRNA1 is therefore especially part of the EBV lytic expression programme . In an attempt to discover the function of v-snoRNA1 during the EBV life cycle , we constructed a recombinant virus that lacks a functional v-snoRNA1 . To this aim , the C-box motif of v-snoRNA1 from the B95 . 8 strain was exchanged against the sequence of the kanamycin resistance gene flanked by two FLP recombinase recognition sites ( Figure 5A ) . Excision of this cassette left an unrelated bacterial sequence containing a HindIII restriction site in place of the box C of v-snoRNA1 ( Figure 5A and 5B , lane 2 ) . DNA from the recombinant virus was stably transfected into 293 cells to generate a virus producer cell line , here referred to as 293/Δv-snoRNA1 . Multiple clones were screened for their ability to support virus replication . One of the replication-competent clones was chosen at random for further experiments . Recombinant episomes purified from this producer cell line and transformed into E . coli cells were found to be intact as assessed by restriction analysis ( Figure 5B , lane 3 ) . Sequencing of the recombination site on these rescued episomes confirmed exchange of the Box C against unrelated DNA TTTCCCGCGCCAAGCTTCAAAAGCGCTCTGAAGTTCCTATACTTTCTAGAGAATAGGAACTTCGGAATAGGAACTTCCAACC ( EBV DNA around the insertion is indicated in bold ) . A northern blot , performed on 293/Δv-snoRNA1 cells using a v-snoRNA1-specific probe , yielded negative results while signals could be clearly identified in the 293/EBV-wt positive control ( Figure 5E , left panel ) . We therefore conclude that the Δv-snoRNA1 virus is devoid of the viral snoRNA and that destruction of the putative C box of v-snoRNA1 is sufficient to exert this effect . We then conducted a series of experiments aiming at defining phenotypic traits of the mutant strain . We first assessed the ability of the 293/Δv-snoRNA1 to support viral replication . Viral titres were quantified either as packaged viral genome-equivalents ( physical titres ) or as green Raji units , i . e . as the concentration of viruses able to infect the Raji cell line determined by exposure to a limiting dilution of the viral supernatants ( functional titres ) . Both assays revealed nearly identical titres for both the mutant and the wild type control ( Figure 5D ) . The Δv-snoRNA1 viruses and producer cell line were then examined in electron microscopy; both displayed normal morphological features: encapsidation , primary and secondary egress were unchanged in the absence of the viral snoRNA ( unpublished data ) . We further evaluated viral gene expression by western blot or immunostains ( BZLF1 , EA/D-BMRF1 , gp350 ) . Again , we could not discern any differences between the mutant and its wild type counterpart ( unpublished data ) . We then exposed various established cell lines or primary cells to the Δv-snoRNA1 mutant and monitored the efficiency of infection by counting the percentage of GFP-positive ( 293 cell line , primary epithelial cells ) or EBNA2-positive ( primary B cells ) lymphocytes three days post-infection . The rate of infection was nearly identical in both wild type and mutant viruses ( unpublished data ) . We finally investigated the transforming capacity of the mutant by performing infections of normal resting B cells from three different normal individuals at decreasing multiplicity of infections ( Figure 5D ) . Wild type and mutant viruses both exhibited a transforming potential that resulted in a very similar number of outgrowing cell clones . We confirmed the identity of the viruses present in the growing LCLs by northern blot analysis; only LCLs generated by infection with wild type B95 . 8 virus expressed the snoRNA while those infected with Δv-snoRNA1 remained negative ( Figure 5E , right panel ) . The majority of snoRNAs have been found to target rRNAs or snRNAs by guiding ribose methylation or pseudouridinylation , respectively . In contrast , a number of snoRNAs lack telltale complementarities to canonical targets and hence are designated as “orphan” snoRNAs [19] , [24] , [30] . We therefore examined 18S and 28S rRNAs for putative v-snoRNA1 target sites using criteria established by Cavaille and Bachellerie [25]: the putative target sites were required to display at least a 7 nucleotides-long perfect complementarity with a region that ended within 3 nucleotides of the end of the snoRNA antisense boxes , and at most one nucleotide should be involved in a bulge or loop [25] . In particular we searched for putative target sites of the v-snoRNA1 box D antisense elements and for two potential alternative box D′ antisense elements ( see Figure 6A ) . Using a program that was successfully used to predict targets of bacterial ncRNAs [41] we identified two putative ribose methylation site within the 18S rRNA and 23 sites within the 28S rRNA for box D′ ( Table S1 ) . However , none of the predicted target sites coincided with known methylated nucleotides within 18S and 28S rRNA . The same strategy applied to box D failed to reveal any putative ribose methylation sites within rRNAs . Nevertheless , we experimentally tested the ribose methylation status of the highest-scoring predictions for rRNA targets ( Figure 6B ) by primer extension analysis [42] , [43] . However , no methylation at the predicted nucleotide positions C617 of human 18S rRNA and C3140 and C3152 of human 28S rRNA was observed in EBV-infected LCL B95 . 8 cells ( data not shown ) , suggesting that v-snoRNA1 is a member of the still growing class of orphan snoRNAs . In addition to full-length cDNA clones encoding v-snoRNA1 , we also identified nine identical partial cDNA clones of 24 nt in size in our cDNA library derived from the very 3′-end of v-snoRNA1 ( Figure 2B ) . Previously , two studies were able to demonstrate processing of specific snoRNA species into functional miRNAs [44] , [45] . Attempts to verify expression of the 24 nt long v-snoRNA1-derived processing product , designated as v-snoRNA124pp , by northern blot analysis with conventional DNA oligonucleotide probes or by splinter ligation [44] , [46] were unsuccessful ( data not shown ) . In contrast , by applying a locked nucleic acid ( LNA ) probe , complementary to v-snoRNA124pp , we were able to verify its expression ( Figure 7 ) . An additional hybridization signal at 40 nt was also observed that might represent a processing intermediate . All hybridization signals , except for full length v-snoRNA1 , were only detected in the 293/EBV-wt cells induced with BZLF1 , likely due to the high expression level of v-snoRNA1 within this strain . Notably , v-snoRNA124pp was not detected in the snoRNA knock-out strain ( Figure 7 ) . Since the 3′-UTR of the BALF5 mRNA exhibits full complementarity to v-snoRNA124pp ( Figure 8 ) we investigated whether it might serve as a potential target site for cleavage by applying a 5′-RACE approach , as previously described [47] , [48] . 5′-RACE products from the predicted 3′-UTR cleavage site were amplified by specific primers and sequenced ( Figure 8 ) . Indeed , we detected two clones corresponding exactly to a predicted cleavage site by v-snoRNA124pp 11 nt from its 5′-end in 293/EBV-wt cells induced with BZLF1 which exhibits highest expression levels of v-snoRNA1 ( Figures 4 and 7 ) . Remaining clones from this region exhibited shorter sequences likely due to exonucleolytic degradation of the BALF5 mRNA following initial cleavage by v-snoRNA124pp as described previously for plant miRNAs [47] . Notably , not a single sequence was observed that was longer than the expected size , which is indicative of a specific cleavage event triggered by v-snoRNA124pp and followed by exonucleolytic degradation . In contrast , no fragments cleaved within the 3′-UTR of BALF5 mRNA were observed in the snoRNA knock-out strain . The identification of a snoRNA species in a viral genome raised two obvious questions: is v-snoRNA1 conserved among the different herpesvirus subfamilies or even among several EBV strains and do v-snoRNA1 homologs exist in other virus families ? This prompted us to perform a BLAST alignment search using all available databases . This search showed that the v-snoRNA1 sequence is 100% conserved among the tested EBV strains ( B95 . 8 , AG876 , M81 , GD1 , Raji ) . It further revealed that the distantly related rhesus lymphocryptovirus ( rLCV ) genome ( exhibiting an overall sequence identity of 65% with the EBV genome; Accession number NC_006146 ) contains a 65 base pair sequence that shows 86% identity with v-snoRNA1 ( Accession number FN376863 ) . In particular , the canonical D , D′ and C , C′ boxes were universally conserved as well as antisense elements , preceding D or D′ boxes . This high degree of sequence identity did not extend to the v-snoRNA1 flanking regions; these showed only 69% sequence identity and were therefore clearly less conserved ( Figure 9A ) . Northern blot analysis , employing an rLCV-specific antisense oligonucleotide , confirmed that the rLCV sequence homolog of v-snoRNA1 is actively transcribed and processed into an RNA species of 65 nt in simian B cells ( Figure 9B ) . Despite the high degree of sequence identity between human and rLCV v-snoRNA1s , hybridization with the rLCV-specific probe did not detect its EBV counterpart . Altogether , these findings strongly indicate that rLCV also encodes a box C/D snoRNA homolog to v-snoRNA1 .
Herpes virus genomes carry numerous cellular gene homologs [49] . Many of these genes encode house keeping proteins but others serve more specialized functions e . g . within the host immune system . This is particularly true of γ-herpesviruses whose genomes encode homologs of cytokines ( e . g . CSF-1 and IL10 for EBV , IL6 for Kaposi's sarcoma-associated herpesvirus ( KSHV ) or of anti-apoptotic mediators ( e . g . BCL2 in EBV and KHSV ) . These striking homologies between a virus and a cellular genome were reinforced by the discovery that herpesviruses encode multiple miRNA clusters . Here we report that herpesviruses and their host share yet another fundamental ncRNA species . Deep-sequencing analysis of a subtracted cDNA library that was constructed to specifically identify transcripts expressed in EBV-infected B cells allowed discovery of a viral transcript that exhibited all defining features of a C/D box snoRNA . Indeed , v-snoRNA1 comprises canonical C/C′ as well as D/D′ boxes . It is of note that v-snoRNA1 is lacking the canonical terminal stem-structure usually encountered in eukaryal snoRNAs . In this respect , v-snoRNA1 appears to be closer to snoRNA species previously identified in fungi or in the domain of Archaea [33] , [50] . In addition to the EBV-encoded v-snoRNA1 , the genome of the Herpesvirus saimiri ( HVS ) , a member of the γ-herpesvirus family , was recently reported to encode seven small nuclear RNAs [51] , [52] . Thereby , in latently infected HVS-transformed T cells , the Herpesvirus saimiri U RNAs ( HSURs ) represent the most abundant viral transcripts . Similar to EBERs , HSURs are not essential for viral replication or transformation , but are involved in the activation of specific genes in virus-transformed T cells during latency [51] . V-snoRNA1 was found to be expressed in all samples of a panel of EBV-positive cell lines that included several BLs and in particular the latency I Rael cell line , LCLs and the 293/EBV-wt producer cell line ( Figure 1 ) . Detection of reduced levels of v-snoRNA1 in LCLs , generated with the BZLF1-null virus that therefore cannot undergo lytic replication , demonstrated that v-snoRNA1 is an integral part of the EBV latent transcription program ( Figure 4 ) . However , expression levels of v-snoRNA1 increased significantly up to 30-fold upon induction of the lytic replication cycle . This is consistent with a model that v-snoRNA1 serves , presumably different , functions in both the latent and the lytic mode of infection . Three findings demonstrated that v-snoRNA1 is likely to represent a fully functional ncRNA species . V-snoRNA1 was found to co-localize with canonical snoRNA to the nucleolus ( Figure 3 ) . Furthermore , we could show that v-snoRNA1 assembles into a canonical snoRNP that at least includes the fibrillarin , Nop56 and Nop58 proteins . Finally , selective destruction of the C box resulted in a complete down-regulation of steady state levels of v-snoRNA1 ( Figure 5E ) . This is consistent with previous work that ascribed an essential role in the regulation of the stability of snoRNA to this sequence motif [21] , [53] , [54] . V-snoRNA1 could be localized to the BARTs region which follows a complex splicing pattern and also encodes a cluster of non-coding miRNA genes ( Figure 2 ) . V-snoRNA1 was located outside the putative BARTs open reading frame and is therefore , as previously observed for canonical eukaryal snoRNAs , likely processed from an intron . The BARTs transcripts can be initiated from two promoters P1 and P2 [36] . Analysis of v-snoRNA1 expression levels showed a large degree of variation within the tested cell lines , as was also observed for EBV's miRNAs [55] . In principle , this could be related to the highly variable virus copy numbers among different EBV-positive cell lines . Alternatively , it may be related to the propensity of some of these cell lines to undergo lytic replication . The low expression levels of v-snoRNA1 in Raji are probably due to an inactive BART P2 promoter; this suggests that the P2 promoter initiates most of the v-snoRNA1 transcripts . The discovery of a snoRNA in a Herpesvirus genome prompted us to search for homologs in other viral or cellular genomes . This search revealed that the v-snoRNA1 is strictly conserved across five distinct EBV strains . It further led to the identification of a transcript within the rLCV genome that displays a high degree of homology to v-snoRNA1 . This genetic element comprises perfectly conserved canonical C/D and C′/D′ boxes and was expressed in a simian LCL which suggests that rLCV also encodes a snoRNA . Discovery of a v-snoRNA1 homolog in rLCV is not entirely unexpected; rLCV is the closest EBV relative as both genomes exhibit 65% sequence identity and , therefore , display more than 80% sequence identity for protein-coding genes and ncRNA genes . Indeed , seven rLCV miRNA were found to be closely related to their EBV counterparts [11] . The relatively crude approach ( BLAST ) we initially took failed to reveal further v-snoRNA1 relatives; we nevertheless consider that this question is still open and hope that our work will stimulate research in this direction . The strict conservation of v-snoRNA1 domains within various EBV strains and among evolution strongly suggests that this element serves an essential role in the natural history of EBV infection . We therefore initiated a series of experiments that aimed at defining potential functions of v-snoRNA1 . We thereby combined a computational with an experimental approach to determine putative ribosomal or spliceosomal RNA targets for v-snoRNA1 using previously identified criteria ( see results section ) . However , both attempts failed to identify any obvious rRNA candidates . Hence , v-snoRNA1 can be assigned in all probability to the class of so-called “orphan” snoRNAs that lack rRNA or snRNA targets ( see below ) . Another strategy to discover the function of v-snoRNA1 consisted in constructing a v-snoRNA1-null mutant and defining its phenotypic traits using well-characterized in vitro assays . As of now , the Δv-snoRNA1 mutant remained indistinguishable from its wild type counterparts in terms of lytic replication , infection and B cell transformation ( Figure 5 ) . However , this does not exclude that v-snoRNA1 serves an important function during the virus life cycle; unraveling miRNAs contributions to EBV infection has also proven a difficult enterprise . Aside from a few notable exceptions such as miR-BART5 and miR-BART2 that respectively target the cellular gene PUMA [56] and the viral gene BALF5 [57] or the BART cluster 1 and BHRF1-2 that respectively modulate LMP1 expression and BHRF1 mRNA processing [58] , [59] , the essential functions served by these ncRNAs remain unclear . Indeed , the B95 . 8 strain that lacks a large number of miRNAs perfectly replicates and immortalizes primary B cells with high efficiency . Recently , specific snoRNA species have been characterized as miRNA precursors , which are processed to mature miRNAs and assemble into a functional RNA induced silencing complex [60] , [61] . Indeed , by deep-sequencing we identified nine identical cDNA clones of 24 nt in size , that mapped to the very 3′-end of v-snoRNA1 . The expression of v-snoRNA124pp was verified by northern blot analysis employing a specific LNA oligonucleotide antisense probe ( Figure 7 ) . Thereby , the hybridization signal was especially apparent in 293/EBV cells induced by BZLF1 , which results in a 30-fold up-regulation of v-snoRNA1 expression; the hybridization signal was absent , however , in non-induced wild type cells . This could be explained by lower v-snoRNA1 expression levels in non-induced 293/EBV cells , compared to BZLF1-induced cells ( Figure 7 ) , resulting in reduced processing of v-snoRNA124pp below the northern blot detection limit . Alternatively , this finding could result from preferential processing of v-snoRNA1 into v-snoRNA124pp during lytic replication . Subsequently , by a 5′-RACE approach we also investigated a potential target for snoRNA124pp . Since the RNA species maps in antisense orientation to the 3′-UTR of the BALF5 mRNA , which encodes the viral DNA polymerase , BALF5 mRNA might represent a likely target site . As has been shown previously , the 3′-UTR of the BALF5 mRNA encodes in antisense orientation , in addition to v-snoRNA124pp , a bona fide EBV miRNA , designated as mir-BART2 . Thereby , it has been reported that mir-BART2 down-regulates the mRNA levels by cleavage within the BALF5 3′-UTR [57] . According to the proposed model , mir-BART2 thereby inhibits the transition from latent to lytic viral replication . By 5′-RACE analysis , we provide evidence that v-snoRNA124pp might also target BALF5 mRNA for cleavage and subsequent degradation . In contrast to mir-BART2 , however , expression of v-snoRNA124pp was only apparent upon induction of the viral lytic cycle by BZLF1 ( Figure 7 ) . Future experiments will focus on the function of v-snoRNA1 and v-snoRNA124pp especially in respect to its function in the latent and lytic cycles of EBV infection .
The cell lines BL2 , BL2 B95 . 8 , BL41 , BL41 B95 . 8 , CBL B95 . 8 , LCL B95 . 8 , Raji , Rael , HEK293 and LCL8664 were cultured in RPMI 1640 supplemented with 10% FCS , L-glutamine ( 2 mM ml−1 ) and antibiotics ( 100 U penicillin ml−1 and 100 µg streptomycin ml−1 ) . BL2 and BL41 are EBV-negative Burkitt's Lymphoma cell lines , BL2 B95 . 8 and BL41 B95 . 8 are cell lines infected with EBV strain B95 . 8 , Raji and Rael are EBV-positive Burkitt's lymphoma cell lines [62] , [63] . CBL B95 . 8 and LCL B95 . 8 cells were obtained after in vitro transformation of cord blood lymphocytes ( CBL ) or primary human blood lymphocytes ( LCLs ) with the B95 . 8 strain of EBV . The EBV deletion strain B95 . 8 , used in this study , lacks a 12 kb large portion of the genome [64] . LCL8664 is a rhesus LCV ( cercopithicine herpesvirus 15 ) -infected B-cell line derived from a retro-orbital B-cell lymphoma in a rhesus monkey [65] . 293/EBV-wt contains the wild type EBV B95 . 8 genome in a recombinant form . Two LCL/EBV-wt and LCL/ΔBZLF1 pairs were established by immortalization of B cells from two different donors with either wild type or BZLF1-negative recombinant viruses [40] . Total RNA from EBV-infected and non-infected cells was isolated by using the Tri Reagent method according to the manufacturers protocol . Northern blot analysis was performed as described in Mrazek et . al [32] applying a mix of five oligonucleotides ( F1: CCTCTCATCAGAATCTCAACC , F2: TCTCAACCGATTTCGTCAGC , F3: CGTCAGCCGCTTCAGACAG , F4: GACAGCCGCGGTTGTCATC , F5: GGTTGTCATCATCATCGGGAA ) covering the whole v-snoRNA1 sequence . For the detection of the homologous rhesus lymphocryptovirus a rLCV-specific v-snoRNA1 oligonucleotide ( 5′-AATCTCAACCAATTTCCTCAGC-3′ ) was used . Detection of v-snoRNA124pp by an LNA oligonucleotide ( 5′-CATCAGAATCTCAACCGATTTCGT-3′ , Exiqon ) was performed according to the standard protocol , except 60 µg RNA was loaded and membrane was washed under stringent conditions . 5 . 8S rRNA antisense oligonucleotide 5′-TCCTGCAATTCACATTAATTCTCGCAGCTAGC-3′ was used as negative control in immunoprecipitations . Ethidium bromide-stained 5S rRNA were used as loading control for normalization after polyacrylamid gel electrophoresis . Northern blot signals were either put onto Kodak MS-1 film , using an intensifier screen or analyzed with a Molecular Dynamics Storm PhosphorImager ( Image quant software version 5 . 0 ) . For the detection of the viral and U3 snoRNA the following amino-modified DNA oligonucleotides were used:AT*CTCAACCGATT*TCGTCAGCCGCT*TCAGACAGCCGCGGT*TGTCATCAT*CAT for v-snoRNA1 and GT*TCTCTCCCTCT*CACTCCCCAAT*ACGGAGAGAAGAACGAT*CATCAATGGCT*G for U3 ( the amino-modified T nucleotides are marked with asterisks ) . The probes were labeled with CY3 ( v-snoRNA1; Amersham Biosciences ) or Oregon Green 488 ( U3; Molecular Probes ) according to the manufacturers protocol . BL2 and BL2-B95 . 8 cells were washed in 1× PBS ( PBS: 100 mM Na2HPO4 , 20 mM KH2PO4 , 137 mM NaCl , 27 mM KCl , pH 7 . 4 ) and diluted in 1× PBS to an appropriate concentration . The cell suspension was dropped onto glass slides and hybridized according to [21] , . The slides were washed 3 times for 20 min after hybridization and mounted with 15 µl Mowiol containing 0 . 1 µg/ml DAPI . Slides were analyzed by confocal fluorescence microscopy ( LSM 510 META , Carl Zeiss GmbH ) using Zeiss LSM Software , version 3 . 2 . For the preparation of snoRNP extract , BL2-B95 . 8 cells were washed in 1× PBS , lysed in 5-fold amount of 1× RNP lysis buffer ( 25 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 0 . 2 mM EDTA pH 8 . 0 , 0 . 2% TritonX-100 ) , sonicated and incubated for 1 h on ice . After centrifugation steps at 18000×g , 4°C , 10 min and 30000×g , 4°C , 30 min the snoRNP extract was used for co-immunoprecipitation . 250 µl Protein A/G PLUS-Agarose ( Santa Cruz Biotechnology Inc . ) was washed three times in 1× PBS and resuspended with 1× RNP lysis buffer to receive a final volume of 125 µl . 50 µl of the suspension was added to the total cell lysate containing 500 µg protein extract for each approach and precleared for 1 h at 6°C during rotation . The precleared supernatant was equally distributed and incubated with specific antibodies for fibrillarin ( ab5821; Abcam ) , NOP56 , NOP58 , and IgG ( Santa Cruz Biotechnology Inc . ) for 1 h at 6°C . After addition of 12 µl of washed beads to each approach and rotation for 4 h at 6°C , samples were centrifuged at 800×g at 4°C for 5 min . The supernatant was used as a control for unbound RNA and the remaining beads were washed four times with 1 ml 1× RNP lysis buffer and the co-immunoprecipitated RNA was eluted with 200 µl IP elution buffer ( 100 mM Tris-HCl pH 7 . 5 , 150 mM NaCl , 12 . 5 mM EDTA pH 8 . 0 , 20% SDS ) after heating for 5 min at 95°C . The supernatant was used to perform phenol-chloroform-isoamylalcohol ( Fluka ) extraction , RNA was ethanol-precipitated over night and analyzed by northern blot analysis . The wild type EBV recombinant plasmid ( p2089 ) is cloned onto the prokaryotic F factor origin of replication and carries the green fluorescent protein ( gfp ) , the chloramphenicol ( cam ) resistance gene and the hygromycin ( hyg ) resistance gene [67] . The EBV snoRNA mutant was constructed by replacing the C box sequence motif ( B95 . 8 coordinates 153331–153341 ) with the kanamycin ( kan ) resistance gene using homologous recombination [68] . Composite primers were used whose internal parts ( underlined ) are specific for the kan resistance gene , and whose external parts ( 40 bp ) are specific for the snoRNA gene ( 5′-ACGCTCCCCTGGGGGCTTCATGATCCCACCGCCTTTCfCCGCGCCAAGCTTCAAAAGCGCTC-3′; 5′-CTCAACCGATTTCGTCAGCCGCTTCAGACAGCCGCGGTTGGAAGTTCCTATTCCGAAGTTCC-3′ ) . These primers allowed PCR-mediated amplification of the kan resistance gene through their internal sequences and then homologous recombination of the amplified PCR product with the EBV wild type genome via their external sequences . PCR amplification products were incubated with the restriction enzyme DpnI to remove traces of the parental plasmid and introduced by electroporation ( 1000 V , 25 µF , 100 Ω ) into E . coli DH10B cells carrying the recombinant virus p2089 and the temperature sensitive pKD46 helper plasmid encoding the phage lambda red recombinase to foster homologous recombination . Cells were grown in LB with cam ( 15 µg/ml ) at 37°C for an hour and then plated onto LB agar plates containing cam ( 15 µg/ml ) and kan ( 10 µg/ml ) . Incubation at 42°C induced the loss of the helper plasmid . DNA of positive clones was purified and analyzed with HindIII restriction enzyme to confirm correct recombination . The kan resistance gene was excised using the Flp recombinase cloned onto the temperature-sensitive plasmid pCP20 [69] which also carries the amp resistance gene . The bacterial clones that resulted from selection on cam/amp plates were further grown on cam plates at 42°C to induce the loss of the pCP20 plasmid . Resistant clones were then submitted to restriction analysis to confirm the expected restriction pattern . Sequencing further confirmed successful recombination and the intactness of the flanking regions . HEK293 cells were transfected with the properly recombined mutant viral DNA ( clone B 253 ) using Lipofectamine ( Invitrogen ) as described [70] . Selection of stable 293 cell clones carrying the EBV recombinant plasmid was performed by addition of hygromycin to the culture medium ( 100 µg/ml ) . Cell clones surviving selection were first assessed for GFP fluorescence and the positive clones were further expanded . Fifteen clones were assessed for their ability to support lytic replication by qPCR . Ten of those were found to produce virus at high levels , one of which was selected for further analysis . The cell clone used in this study is referred to as 293/Δv-snoRNA1 . Viral episomes from this clone were transferred back in E . coli and submitted to restriction analysis and sequencing . Circular plasmid DNA from 293/ΔsnoRNA and was extracted using a denaturation-renaturation method as described previously [71] . E . coli strain DH10B was transformed with the viral recombinant DNA by electroporation as described before [68] and clones were selected on LB plates containing cam ( 15 µg/ml ) . Single bacterial colonies were expanded and DNA plasmid preparation submitted to digestion with restriction enzyme HindIII . Producer cell clones 293/EBV-wt ( carrying p2089 ) and 293/Δv-snoRNA1 were transfected with a BZLF1 ( Accession number NC_007605 . 1 ) expression plasmid ( 0 . 5 µg/well ) to induce lytic cycle [72] using lipid micelles ( Metafectene , Biontex ) according to manufactures instructions . Virus supernatants were harvested four days post transfection , filtered through a 0 . 8 µm filter and stored at −80°C . Viral titers were determined by infecting 104 Raji cells with increasing dilutions of EBV-wt or Δv-snoRNA1 supernatants . Three days after infection , gfp-positive Raji cells were counted using a fluorescent microscope ( Leica ) . For immortalization assays , primary B cells were mixed with infectious supernatants at various multiplicities of infections ( MOI ) and seeded into U-bottom 96-well plates coated with gamma-irradiated WI38 feeder cells [73] at a concentration of 102 cells per well . Wells containing outgrowing LCL clones were counted . Detection of viral DNA and calculation of viral titers was carried out by quantitative real-time PCR ( qPCR ) using BALF5-specific primers and probe as described [74] . The DNA content was calculated using a serial dilution of Namalwa DNA , a human Burkitt's lymphoma cell line that contains two EBV genome copies per cell , as a standard curve . We predicted putative rRNA target sites for the snoRNAs in this study as follows . We first downloaded from Genbank the sequences of the human 18S ( Accession NR_003286 ) and 28S ( Accession NR_003287 ) rRNAs . The sequences of the antisense D-box ( TGACGAAATCGGTTGAGATT ) and D′-box ( TGACAACCGCGGCTGT ) were used to search for subsequences with good complementarity to the rRNAs with the program described in Mandin P et al . [41] . As the study of Cavaille & Bachellerie [25] indicated that snoRNA-rRNA interactions involve regions of at least 7 nucleotides complementarity that are located at most 3 nucleotides from the end of the snoRNA antisense box , and that bulges and loops of more than 1 nucleotide are disfavored , we implemented these constraints in our programs . That is , we first used relatively large penalties for the introduction and extension of bulges and loops ( a score penalty of 8 ) , and we restricted the maximum size of loops and bulges to 1 nucleotide . The energy parameters of nucleotide-nucleotide interactions were kept with their default values coded in the program . We then extracted only hybrids that contained at least 7 nucleotide-nucleotide pairs , that ended within 3 nucleotides of the end of the antisense box , and that did not contain more than one bulge or loop . 2-OH ribose methylation of rRNA was assayed as follows . Oligonucleotides ( 0 . 6 pM ) were 5′-end-labeled with 32P-γ-ATP and heat-denaturated after addition of 3 µg of total RNA ( LCL B95 . 8 ) for 2 min at 96°C . Primer annealing was performed in presence of 30 mM KCl and 25 mM Tris-HCl pH 8 . 4 for 30 min at 42°C . Reverse transcription was carried out for 45 min at 42°C in buffer containing 100 mM Tris/HCl pH 8 . 4 , 10 mM MgCl2 , 15 mM KCl , 10 mM DTT , 0 . 5/0 . 02/0 . 005 mM dNTPs and 0 . 4 U AMV reverse transcriptase . Additionally , a final concentration of 0 . 0625 mM dideoxynucleotides was added to the sequencing reactions . The reactions were stopped by addition of twice volume of 4 M NH4Ac and 20 mM EDTA , cDNA products were precipitated , resolved on a 10% denaturating polyacrylamide gel and visualized by autoradiography . Total RNA of 293/Δv-snoRNA1 and 293/EBV-wt induced by BZLF1 and was adaptor-ligated and reverse transcribed using a gene-specific primer ( 5′- TTCGCCCTTGCGTGTCCATTGT-3′ ) according to the FirstChoice RLM-RACE Kit ( Ambion ) . cDNA was PCR-amplified with the non-specific 5′ RACE outer primer and the same reverse primer and further amplified by nested PCR using the 5′ RACE inner primer and a second gene-specific reverse primer ( 5′- GCAAGGAGCGATTTGGAGAAAATAAAC-3′ ) . PCR DNA was gel purified , cloned ( pGEM-T Easy Vector System I , Promega ) and subjected to Sanger sequencing employing the ABI Prism 3100 capillary sequencer ( Perkin Elmer ) . v-snoRNA1: FN376861; BZLF1: NC_007605 . 1; 18S rRNA: NR_003286; 28S rRNA: NR_003287; Epstein-Barr-Virus genome , strain AG876: AJ507799; Rhesus lymphocryptovirus genome: NC_006146 | Epstein-Barr virus ( EBV ) infects about 90% of people worldwide and is associated with different types of cancer . So far , only two large virus-encoded non-coding RNAs ( EBER1 and EBER2 ) and 25 microRNAs ( miRNAs ) have been identified in the EBV genome . In this study , we report identification of the first member of another abundant non-coding RNA class , a small nucleolar RNA ( snoRNA ) , designated as v-snoRNA1 . We show that v-snoRNA1 is located in the nucleolus and interacts with the same proteins as reported for canonical eukaryal snoRNAs . Its biological function is consistent with its high conservation in a distantly related simian herpesvirus genome . Interestingly , v-snoRNA1 might serve as a miRNA-like precursor , which is processed into a 24 nt sized RNA species , designated as v-snoRNA124pp . The viral DNA polymerase BALF5 was identified as a potential target for v-snoRNA124pp . Taken together , these experiments strengthen the crucial function of v-snoRNA1 in EBV infection . | [
"Abstract",
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"Methods"
] | [
"infectious",
"diseases",
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] | 2009 | Expression and Processing of a Small Nucleolar RNA from the Epstein-Barr Virus Genome |
DNA sequences purified from distinct organisms , e . g . non vertebrate versus vertebrate ones , were shown to differ in their TLR9 signalling properties especially when either mouse bone marrow-derived- or human dendritic cells ( DCs ) are probed as target cells . Here we found that the DC-targeting immunostimulatory property of Leishmania major DNA is shared by other Trypanosomatidae DNA , suggesting that this is a general trait of these eukaryotic single-celled parasites . We first documented , in vitro , that the low level of immunostimulatory activity by vertebrate DNA is not due to its limited access to DCs' TLR9 . In addition , vertebrate DNA inhibits the activation induced by the parasite DNA . This inhibition could result from the presence of competing elements for TLR9 activation and suggests that DNA from different species can be discriminated by mouse and human DCs . Second , using computational analysis of genomic DNA sequences , it was possible to detect the presence of over-represented inhibitory and under-represented stimulatory sequences in the vertebrate genomes , whereas L . major genome displays the opposite trend . Interestingly , this contrasting features between L . major and vertebrate genomes in the frequency of these motifs are shared by other Trypanosomatidae genomes ( Trypanosoma cruzi , brucei and vivax ) . We also addressed the possibility that proteins expressed in DCs could interact with DNA and promote TLR9 activation . We found that TLR9 is specifically activated with L . major HMGB1-bound DNA and that HMGB1 preferentially binds to L . major compared to mouse DNA . Our results highlight that both DNA sequence and vertebrate DNA-binding proteins , such as the mouse HMGB1 , allow the TLR9-signaling to be initiated and achieved by Trypanosomatidae DNA .
Toll-like receptors ( TLRs ) play a crucial role in the recognition of invading pathogens and the subsequent activation of innate immune responses . Several studies revealed a role for intracellular TLR9 in host resistance to protozoan parasites infection including Trypanosoma brucei , Trypanosoma cruzi and Leishmania [1]–[6] . It was also reported that CpG oligonucleotides conveyed protective immunity in lethal murine Leishmaniasis [7] . Previously , it was shown that DNA from L . major stimulates TLR9 signaling in dendritic cells ( DCs ) . Importantly , DCs activation did not occur with DNA isolated from vertebrates , suggesting that this activation is specific for L . major DNA [8] . Previously the lack of immunostimulatory activity by naked vertebrate DNA has been explained by a combination of several factors such as CpG suppression , CpG methylation , presence of inhibitory motifs and saturable amount of DNA uptake [9] , [10] . However , the DNA sequences required for TLR9 activation are controversial , as studies have shown conflicting results regarding the nature of the DNA backbone , the route of DNA uptake and the cell type [11] , [12] . Until recently the prevailing paradigm was that TLR9 recognizes unmethylated CpG motifs , which are abundant in bacterial DNA but relatively scarce in mammalian DNA [13] . The idea that stimulatory properties of DNA correlate solely with the lack of CpG methylation may be an over simplification , as hypomethylated mouse DNA fails to activate B cells [14] . Several independent studies have demonstrated that the dependence on CpG motifs for TLR9 activation is restricted to synthetic phosphorothioate ( PS ) oligonucleotides and that natural phosphodiester ( PO ) oligonucleotides bind and activate TLR9 via the 2′deoxyribose backbone in a sequence-independent manner [11] , [15]–[17] . This result was consistent with the concept that the phosphodiester backbone acts per se as a TLR9 agonist . Despite the agonist role of PO backbone , some oligonucleotides sequences were described as stimulatory and others as inhibitory for the TLR9 receptor [10] , [13] . Optimal oligonucleotide sequences for TLR9 inhibitory activity were investigated either with PO or PS backbone , revealing a large range of activity in biological assays [17] . It has been proposed that discrimination between microbial and self DNA could be primarily dependent on the colocalization of DNA and TLR9 in endolysosomes [16] , [18] . In addition , upon cationic lipids–mediated enhanced endosomal translocation , non-canonical CpG motifs or vertebrate DNA can also trigger cell activation [16] , [19] and display TLR9-dependent and -independent activation . Pathogen-derived DNA may specifically access the TLR9-expressing endosomal compartment in the course of infection whereas host derived DNA may not . Indeed it has been shown that plasmacytoid dendritic cells ( pDCs ) can respond to self DNA via TLR9 signaling , when self DNA is targeted to the endocytic compartment due to its interaction with circulating auto-antibodies in systemic lupus erythematosus [20] or with the antimicrobial peptide LL37 ( cathelicidin antimicrobial peptide from hCAP18 ) in psoriasis [21] . Other proteins that directly bind to DNA are also involved in endosomal TLR9 activation such as High Mobility Group Box1 ( HMGB1 ) , SLPI ( Secretory Leucocyte Protease Inhibitor ) , granulin and CD14 which promote the selective uptake of nucleic acids [22]–[26] . In this work , we enquired on the molecular basis of the differences between Trypanosomatidae and vertebrate DNA , both being eukaryotic DNA , regarding TLR9 stimulation . We investigated the uptake of L . major and vertebrate DNA in DCs to assess whether the absence of stimulation by vertebrate DNA was due to its limited access to endosomal compartments . Since on one hand similar uptake was observed with the different DNAs and , on the other hand , vertebrate DNA could prevent TLR9 activation by parasitic DNA , we investigated whether their genomic sequence may be involved in their different stimulatory capacity . Therefore we analysed the presence of stimulatory or inhibitory motifs for TLR9 , described in previous studies , in both types of DNA . Furthermore , we investigated whether cofactors in DCs could be involved in the specific activation of TLR9 by parasite DNA . We focused on HMGB1 , a mammalian nuclear protein that exhibits a low affinity for linear double-stranded DNA , but which forms stable complexes with unusual or distorted DNA structure [27] . Indeed , HMGB proteins have been demonstrated to act as universal sentinels for nucleic acids [28] and HMGB1 is able to activate TLR9-dependent pathways , when complexed to CpG oligonucleotides [22] , [29] . This led us to speculate that HMGB1 might discriminate between vertebrate and parasitic DNA and therefore specifically enhance the activation of DCs by L . major DNA . Our results illustrate that Trypanosomatidae and vertebrate DNA differ in the frequency of stimulatory and inhibitory motifs and in their ability to associate with auxiliary factors , such as HMGB1 , that may promote the specific activation of TLR9 by parasitic but not vertebrate DNA in DCs .
Animals were housed in the Institut Pasteur animal facilities accredited by the French Ministry of Agriculture to perform experiments on mice in appliance of the French and European regulations on care and protection of the Laboratory Animals ( EC Directive 86/609 , French Law 2001–486 issued on June 6 , 2001 ) . The CETEA ( Comité d'Ethique pour l'Expérimentation Animale - Ethics Committee for Animal Experimentation ) "Paris Centre et Sud" reviewed and approved the animal care and use protocol under the approval number 2012–0059 . Six to 8 weeks old female C57BL/6 mice were purchased from Charles River Laboratories . TLR9-/- backcrossed to the C57BL/6 background for10 generations were provided by S . Akira ( Osaka University , Osaka , Japan ) . All mice were bred in our facilities and housed under specific pathogen-free conditions . Promastigotes of L . major LV39 , T . vivax , T . cruzi , T . brucei were propagated in vitro in adapted medium supplemented with 10% of Foetal Calf Serum . Genomic DNA from vertebrate kidney and lymphnodes purified cells and from L . major , T . vivax , T . cruzi , T . brucei parasites were prepared by proteinase K and RNase digestion followed by phenol/chloroform extraction and ethanol precipitation . Vertebrate and parasite DNA mean purified and naked DNA whereas all complexed DNA are purified DNA in which we added different factors . We used DOTAP ( cationic lipid N- ( 2 , 3-Dioleoyloxy-1-propyl ) trimethylammonium methyl sulfate ) ( Sigma-Aldrich ) , CpG ODN type B 1826 ( TCCATGACGTTCCTGACGTT ) , CpG ODN type A 2216 ( 5′-GGGACGATCGTG-3′ ) ( Sigma-Proligo ) , ODN 2088 ( 5′-TCCTGGCGGGGAAGT-3′ ) ( Eurogentec ) , imidazoquinoline Cl-097 ( InvivoGen ) , DNase I ( 2 U/ml ) ( BioLabs ) , DNAse II ( 1100 U/ml ) and glycyrrhizin ( Sigma-Aldrich ) . HMGB1 was kindly provided by Dr . V . Maréchal ( Centre de recherche des Cordeliers , France ) [30] . Residual lipopolysaccharide , quantified using the E-toxate assay ( Sigma ) was less than 100 fg per microgram of HMGB1 . Bone marrow ( BM ) cells were isolated by flushing mice femurs and tibias with PBS . After treatment with Red Blood Cells lysis buffer ( Sigma-Aldrich ) , BM cells were cultured in complete RPMI 1640 supplemented with GM-CSF from J558L cell line supernatant [31] . At day 8 , 75–80% of cells are BM derived dendritic cells ( BMDCs ) CD11c+CD11b+ . Gen2 . 2 is a plasmacytoid cell line pDC provided by a leukaemia patient [32] . Briefly , they grow on a murine fibroblast feeder cell line MS5 in RPMI , supplemented with 10% FCS , 1% L-glutamine , non-essential amino acids , gentamicin and 0 . 2% sodium pyruvate . BMDCs or Gen2 . 2 were cultured in 6-well plates ( 3×106 ) using complete RPMI 1640 . Cells were activated for 6 h with L . major , T . vivax , T . cruzi , T . brucei or vertebrate ( mouse , pig , sheep or human ) genomic DNA ( 40 to 2 . 5 µg ) , 0 . 25 µg CpG 1826 , 5 µg CpG 2216 or 0 . 25 µg Cl-097 . When indicated , stimulation was done with DNA complexed with DOTAP ( 10 µg for 2 . 5–5 µg of DNA ) or with HMGB1 ( 1 µg ) , SLPI ( 20 µg ) or LL37 ( 2 µg ) . Before being added to the cells , DNA was incubated with DOTAP or the various peptide/protein 20 min at RT . Each factor was tested alone to induce no stimulation by itself . In some experiments , cells were treated with chloroquine at 20 µM for 1 h before activation . For DNA competition experiments , cells were incubated with both parasite and vertebrate DNAs . Supernatants and cells were harvested for ELISA or RNA extraction . IL-6 and TNFα were quantified in cell culture supernatants using the BD OptEIA TNFα and IL-6 ELISA set ( BD Biosciences ) . All ELISA procedures were performed according to the manufacturer's protocol . RNA was extracted from BMDCs or Gen2 . 2 using a microRNeasy extraction kit ( Qiagen ) . A trace of genomic DNA was removed by RNAse free-DNAse set . RNA ( 2 µg ) was reverse transcribed using ( 200 U ) Moloney murine leukemia virus reverse transcriptase ( SuperScript II , Invitrogen ) . Subsequent real time PCR was performed on Step One Plus ( Applied Biosystems ) using Taq polymerase or SYBER green ( Taq-Man Universal or SYBER Green PCR master mix , Applied biosystems ) . Flow cytometric data were acquired on a four-color FACS Calibur cytometer ( BD Biosciences ) and analysis was done with Cell Quest Pro software . For surface phenotyping , the following antibodies were used: anti-human CD45RA-FITC ( MEM-56 ) , CD11c-APC ( BU15 ) , HLA-DR-FITC ( LT-DR ) , CD123-PE ( 9F5 ) ; anti-mouse CD11b-PE ( M1/70 ) , CD11c-APC ( HL3 ) ( BD Bioscience ) . Uptake of propidium iodide-stained DNA in CD11c-APC cells was performed on FL3 channel . For DNA uptake experiments , BMDCs were plated on a µ-slide 8 well ibiTreat ( ibidi ) then stimulated for 1 h with L . major or mouse DNA . DNA was stained overnight with propidium iodide ( PI ) and precipitated in ethanol . Cells were fixed with 2% paraformaldehyde for 20 min at RT . Images were taken using a Leica SP5 scanning confocal microscope with an ×63 oil objective . DAPI and propidium iodide signal was acquired following respective excitation at 405 nm and 561 nm and respective emission at 420/465 nm and 577/690 nm , in sequential captures with optical sections of 0 . 4–0 . 8 µm . All microscope parameters were kept constant between experiments . Icy software ( version 1 . 3 . 6 . 0 ) was used for merge analysis and image presentation [33] . ImageJ software ( version 1 . 47q ) was used to calculate the average DNA uptake into cells . Gel retardation experiments were performed as previously described [34] with the following modifications . Increasing amounts of HMGB1 protein ( 0 . 125 µg to 2 . 5 µg ) were incubated for 20 min with 250 ng of sonicated parasite or vertebrate DNA in a buffer containing 0 . 15 M NaCl , 10 mM Tris-HCl pH 7 . 6 . The complexes were loaded on a 1% agarose-TBE gel . Following electrophoretic migration the gels were either immediately transferred onto PVDF ( polyvinyl difluoride ) membranes ( Amersham Biosciences ) or stained in a solution of 0 . 5 µg/ml ethidium bromide ( EtBr ) for 45 min before transfer . EtBr did not stain the gel before transfer to avoid diffusion of free HMGB1 . Then membranes were probed with antibodies against HMGB1 ( Abcam , 1∶1000 ) . BMDCs ( 3×106 ) were stimulated with CpG 1826 ( 1 µg ) , L . major or vertebrate DNA ( 20 µg ) for 30 min and 1 h . The cells were lysed in buffer ( 20 mM TrisHCl ( pH 7 . 4 ) , 10 mM NaCl , 3 mM MgCl2 ) with anti-proteases for 30 min at 4°C . After centrifugation at 3000 rpm , the cytoplasmic fraction was harvested and the nuclear fraction extracted with the buffer from Subcellular Proteome Extraction kit ( Calbiochem ) . The fractions were analysed by Western Blotting , run in a 10% SDS-PAGE , probed with antibodies against HMGB1 ( 1∶1000 , Abcam ) , actine ( 1∶10000 , Sigma ) , histone H3 ( 1∶5000 , Abcam ) and revealed with an anti-rabbit or anti-mouse immunoglobulin-horseradish peroxidase conjugates ( 1∶10000 , Serotec ) . Quantification was performed with ImageJ software . L . major or vertebrate DNA ( 1 µg ) was incubated with DNAse I or II at different concentrations for 30 min at 37°C , and 10 min at 75°C in buffer ( 10 mM Tris-HCl , 2 . 5 mM MgCl2 , 0 . 5 mM CaCl2 , pH 7 . 6 or 150 mM Na acetate-HCl , 5 mM EDTA pH 4 . 5 respectively ) . With cytoplasmic extract ( up to 5 µg ) , DNA was incubated for 2 h at 37° and 10 min at 75° . Cleavage products were analysed by 0 . 7% agarose gel electrophoresis , stained with EtBr . The genomes analysed are referenced in GenBank Assembly database as: GCA_000002725 . 2 for Leishmania major genome strain Friedlin by the Friedlin Consortium , GCA_000001635 . 4 for mouse ( Mus musculus ) genome by the Genome Reference Consortium Mouse and GCA_000001405 . 13 for human ( Homo sapiens ) genome by the Genome Reference Consortium Human . The Trypanosomatidae genomes referenced T . cruzi strain CL Brener Esmeraldo-like , T . brucei strain TREU 927 and T . vivax strain Y486 ( 2013-01-16 versions for all ) were taken from Trypanosomatidae database TritrypDB ( http://tritrypdb . org/tritrypdb/ ) [35] . All bioinformatic analyses , including motif counts and determination of genome size , were made from this same dataset . The different motifs were searched in each chromosome or in the whole genome with in-house software ( wcount ) . The motif is represented using the IUPAC ( International Union of Pure and Applied Chemistry ) nucleotide ambiguity code . Statistical significance was tested using Prism 5 . 0 ( GraphPad Software ) by Mann-Whitney test ( for cells activation and chromosomes analysis ) and Wilcoxon signed-rank test ( for genomes analysis , to test whether rO/E is different from 1 ) . Error bars in all figures represent SEM , with the midline representing the mean value . Here is the list of accession numbers/ID numbers for genomes mentioned in the text: Genome sequences from the primary assemblies for the other Trypanosomatidae organisms were obtained in TriTrypDB ( http://tritrypdb . org/tritrypdb/ ) and are publicly accessible in the cited link in Data Summary/Genomes and Data Types . The genomic sequences are available under: The proteins studied in the text are listed below , publicly accessible in Uniprot database:
It was previously shown that L . major DNA could activate cytokine expression in BMDCs ( bone-marrow derived DCs ) from C57BL/6 mice but had no effect on BMDCs from TLR9-deficient mice . We show here that this property is shared by other Trypanosomatidae DNA ( T ) including T . cruzi , T . brucei and T . vivax ( Figure 1A and Figure S1 ) . When Trypanosomatidae DNAs are complexed with DOTAP to enhance the endosomal translocation of DNA , a 8-fold lower amount of DNA induces higher cytokine production by BMDCs in comparison to naked DNA ( Figure 1A ) . While we observe an increase in the expression of cytokines ( IL-6 and TNFα ) proportional to the amount of L . major DNA added , we do not detect either TLR9 -dependent or -independent activation with different vertebrate DNAs until 40 µg/ml and at that point we detect minimal activation . In addition the activation of DCs by vertebrate DNA complexed with DOTAP is 10 times lower than that obtained with 4 times less DNA from L . major ( Figure 1B and Figure S2A ) . We used CpG ( 0 . 25 µg/ml ) and LPS ( 100 ng/ml ) as controls to test the capacity of the cells to be activated by stimuli requiring TLR9 or not ( Figure 1C and Figure S1 ) . Each mouse chromosome is at least 20-fold longer than any L . major chromosome . Therefore , we investigated whether the low level of activation by vertebrate DNA could be due to its size , which may prevent its uptake by the cell . L . major DNA sonicated into 200 to 500 base pair fragments ( Figure S2B ) induced the production of proinflammatory cytokines , while sonicated vertebrate DNA did not ( Figure 1D ) , demonstrating that chromosomal size discrepancy did not account for the differences between L . major and vertebrate DNA in TLR9 activation . To address whether human TLR9 could also discriminate between L . major and vertebrate DNA , we investigated TLR9 signaling in human plasmacytoid DCs ( pDCs ) . Because of their low frequency in human blood , we used a human pDCs cell line GEN2 . 2 CD123+ HLA-DR+ , derived from leukemic pDCs [32] , which were activated by TLR9 and TLR7 agonists ( CpG and Cl-097 ) ( Figure S3 ) . Only L . major DNA induced the increase of IFNα2 and IFNβ in pDCs ( Figure 2 ) . No comparable activation was observed with the same quantity of vertebrate DNA , even in the presence of DOTAP . The activation was impaired by chloroquine treatment , which inhibits the endosomal acidification necessary for TLR9 activation . Thus , in bone marrow derived DCs from mouse and in a human plasmacytoid cell line that have been only investigated , we showed that L . major DNA induced TLR9 signaling at least 10 times more efficiently than vertebrate DNA . Differential DNA uptake could account for the difference for TLR9 signaling between L . major and vertebrate DNAs . To compare their uptake in BMDCs , both purified DNAs were labeled with propidium iodide ( PI ) and added to the cells . To avoid PI diffusion , the process of DNA uptake was analysed after one-hour incubation with the cells by confocal microscopy ( Figure 3A and 3B ) or flow cytometry ( Figure 3C ) . We detected 6–10% of BMDCs containing exogenous full-length DNA with both techniques . Surprisingly we found the same proportion of DNA-containing BMDCs when exogenous sonicated DNA was used ( Figure 3A , 3B and 3C ) . Thus , the uptake of L . major and vertebrate DNA is not significantly different . We also investigated whether L . major and vertebrate DNAs could compete for cellular uptake and tracked their internalization in BMDCs by flow cytometry . No difference in L . major DNA uptake was observed in presence of vertebrate DNA ( Figure 3 ) . Degradation of exogenous DNA by DNAses may be a limit to TLR9 activation . Since the DNase content is much higher in phagocytic cells , such as DCs , than in other cells , we compared the relative sensitivity of L . major and mouse genomic DNA to increasing concentrations of both DNase I or II ( Figure 4 ) . DNase I and II nucleases are usually involved in the digestion of DNA that originated outside the nucleus [36] . We observed that the complete degradation of L . major DNA requires ten times more purified DNase I or II or 2 times more cytoplasmic extract than for vertebrate DNA ( Figure 4 ) . Thus , L . major DNA is intrinsically more resistant to DNase than vertebrate DNA suggesting that the parasitic DNA could persist longer in the cells . Given the different properties of L . major and vertebrate DNA regarding TLR9 activation and DNase sensitivity , we wondered whether these DNA might be in competition for TLR9 activation . The addition of different vertebrate DNA ( mouse or pig ) to L . major DNA inhibited the activation of BMDCs induced by L . major DNA alone . Indeed , the production of IL-6 and TNFα by BMDCs is significantly reduced ( Figure 5A ) . This inhibition increases in relation to the concentration of vertebrate DNA ( Figure 5B ) . The percentage of inhibition reached approximatively 30 to 50% depending on the species with an identical amount of vertebrate and L . major DNA and reaches up to 70% to 85% in the presence of a two fold excess vertebrate DNA . It should be noted a slightly higher inhibition with pig versus mouse DNA ( 10 µg ) characterized by a lower production of IL-6 ( Figure 5A ) but not statistically different with 20 µg of DNA ( Figure 5B ) . Neither toxic effect nor inhibition of LPS activation was observed with high concentration of DNA ( 20 or 40 µg ) ( Figure 1B and Figure S4 ) , indicating that this inhibition was specific of the TLR9 activation pathway . We also noticed that sonicated vertebrate DNA and inhibitory oligonucleotide inhibited the activation induced by L . major DNA ( Figure S4 ) . Since sonicated vertebrate DNA did not cause cellular activation ( Figure 1D ) while exhibiting an inhibitory capacity ( Figure S4 ) we could conclude that full-length DNA and degraded vertebrate DNA have the same properties . Importantly this would suggest that the higher sensitivity of vertebrate DNA to cellular DNAses should not interfere with its inhibitory capacity . Additionnal experiments demonstrated that mouse DNA could also inhibit the activation of BMDCs induced by T . cruzi DNA alone ( Figure 5C ) . The percentage of inhibition was about 90% when vertebrate DNA was added to T . cruzi parasite DNA . Inhibition by vertebrate DNA may therefore be generalized to other Trypanosomatidae DNAs . The inhibition by naked vertebrate DNA could reflect a competition between both DNAs for TLR9 activation and suggest that discrimination between Trypanosomatidae and vertebrate DNAs involved their genomic sequences . We analyzed the genomic frequency of motifs affecting the activation or inhibition of TLR9 in L . major and vertebrate ( mouse and human ) DNA . 3′extension with polyG reduces nuclease sensitivity [37] . In agreement with the greater resistance of L . major DNA to DNase , we found that the relative frequency of polyG8 motif ( represented here as ( GGGG ) 2 ) was 4 times larger in the genome of L . major than in the mouse genome ( Figure 6A and Table S1 ) . Additionally , we searched for the CpG motifs GACGTT or GTCGTT , respectively defined as the mouse and human optimal TLR9 activating motifs [13] , [38] . These stimulatory motifs are 6 and 13 times more frequent in L . major than in mouse and human genomes respectively . In contrast , the inhibitory telomeric motif TTAGGG [39] is 2 times less frequent in the L . major genome than in the mouse genome ( Figure 6A and Table S1 ) . To extend these observations , we examined all the combinations around the dinucleotide CpG in the canonical motif ( RRCGYY ) and other motifs that are analogous to oligonucleotides previously described as activators ( HRWCGTTN ) [10] , [13] that are found in every class of CpG . We also investigated combinations around G-rich sequence described to have inhibitory properties ( WKKVGGGG ) and the optimal TLR9 inhibitory sequence CCNDDNNGGG [10] , [17] . Table 1 shows the total number of each set of motifs in the different genomes . We also computed the number of expected motifs given the frequency of each nucleotide and genome size . From these data , we obtained the ratio of observed over expected motifs ( rO/E ) for each genome . For stimulatory motifs RRCGYY and HRWCGTTN , the ratio is around 1 in L . major genome . This ratio is lower in the mouse and human genomes ( respectively 0 . 20 and 0 . 13 ) . The TLR9 inhibitory motifs CCNDDNNGGG and WKKVGGGG are rare in the L . major genome ( rO/E of 0 . 33 and 0 . 93 respectively ) . In human and mouse genomes inhibitory motifs are more frequent than expected ( between 1 . 3 and 1 . 8 ) . We analyzed the distribution of stimulatory and inhibitory motifs in each of the 36 chromosomes of L . major and then compared it statistically with that of the 21 mouse chromosomes and 24 human chromosomes ( Figure 6B ) . The rO/E values for the activating motifs RRCGYY and HRWCGTTN were very similar among chromosomes of the same genome . The rO/E values for the inhibitory motifs CCNDDNNGGG and WKKVGGGG were very similar in the 36 chromosomes of L . major ( <1 ) , but more diverse among mouse and human chromosomes . Importantly , rO/E values for inhibitory motifs were systematically and very significantly lower in L . major than in human and mouse genomes ( p<0 . 0001 for both , Mann-Whitney test ) . Conversely , the rO/E values of stimulatory motifs were systematically and significantly higher in L . major than in human and mouse genomes ( p<0 . 0001 for both , Mann-Whitney test ) . Thus , in contrast to human and mouse genomes that have counter-selected TLR9-stimulatory motifs and over-represented TLR9-inhibitory motifs , our results show that in L . major genome , there is no selection of motifs affecting the activation of TLR9 . We wondered whether these observations could be extended from L . major to other Trypanosomatidae DNA . The ratios rO/E for both stimulatory motifs RRCGYY and HRWCGTTN are identical and reach 1 . 1 , 0 . 8 , 0 . 9 respectively in L . major , T . cruzi and T . brucei; for T . vivax the ratios are 0 . 68 and 0 . 91 ( Figure 7 and Table 1 ) . However , these ratios are always higher in Trypanosomatidae genomes than in vertebrate genomes . In contrast , the ratio of the two inhibitory motifs is more variable between Trypanosomatidae genomes . The ratios are between 0 . 3 and 0 . 9 for L . major , T . cruzi and T . vivax genome and slightly higher than 1 only for T . brucei . As the genomes of those Trypanosomatidae parasites have not all been assembled yet , we were not able to analyze the motifs distribution on their chromosomes . Therefore , we calculated the ratios S/I between each stimulatory and inhibitory sequence ( Table 2 ) . The ratio between the canonical stimulatory motif RRCGYY and each inhibitory motif is slightly higher in L . major than T . cruzi and higher in T . cruzi than T . brucei . Interestingly , the order of the ratios matches well the order of activation . With the second stimulatory motif HRWVGTTN , the ratio S/I are around 2 but they represent around 20% of the canonical motif RRCGYY , except in L . major genome ( 10% ) . All the S/I ratios in Trypanosomatidae genome are 3 to 10 times higher than those in vertebrate genome ( Table 2 ) . Overall , this analysis demonstrates that the contrast observed in the genomic frequency of inhibitory and stimulatory motifs between L . major DNA and human and mouse genomes is shared with the other Trypanosomatidae DNA . Different factors such as cationic peptides can interact with DNA and facilitate its access to the endosomal TLR9 receptor . We observed an overall increase in the expression of cytokine mRNA in BMDCs when L . major DNA was complexed with HMGB1 proteins or with cationic peptides such as LL37 and SLPI ( secretory leucocyte protease inhibitor ) ( Figure S5 ) . We focused on HMGB1 since it could mediate TLR9 activation by DNA at a low concentration . To determine whether HMGB1 could modify the immunostimulatory properties of DNA , BMDCs were stimulated either with L . major or vertebrate DNA alone , as well as with pre-formed HMGB1-DNA complexes . Stimulation with L . major DNA-HMGB1 complexes doubled cytokine mRNA expression and secretion compared with DNA alone ( Figure 8A and 8B ) , whereas HMGB1-vertebrate DNA complex or HMGB1 alone did not . Similarly , no cellular stimulation was observed with sheep , pig or mouse DNA complexed with SLPI or LL37 peptides under these conditions ( Figure S6 ) . Therefore , enhanced DCs activation by SLPI , LL37 , HMGB1 is only observed in the presence of parasitic DNA . Activated immune cells , including dendritic cells , can secrete HMGB1 in response to various pro-inflammatory stimuli . Since HMGB1 increases the stimulatory activity of L . major but not that of vertebrate DNA , we wondered whether these two DNA could stimulate HMGB1 translocation from nucleus to cytoplasm in DCs . We showed here that the presence of extracellular DNA ( CpG , L . major or vertebrate ) was sufficient to promote a gradual release of HMGB1 from the nucleus to the cytoplasm: which is the first step of HMGB1 secretion . The accumulation of cytoplasmic HMGB1 reached a peak 30 min after stimulation with CpG and 60 min with the two eukaryotic D ( Figure 8C ) . The absence of histone H3 in the cytoplasm indicated that cytoplasmic HMGB1 did not result from nuclear lysis . We next intended to evaluate whether extracellular forms of HMGB1 could mediate TLR9 activation in BMDCs exposed to parasite DNA . For this purpose cells were exposed to L . major DNA in the presence of glycyrrhizin , an inhibitor of extracellular HMGB1 [40] . Addition of this inhibitor reduced two-fold the DNA-triggered cytokine response ( Figure 8D ) , confirming that the presence of extracellular HMGB1 contributed to BMDCs activation by parasitic DNA . We next determined whether this effect could be due to the ability of HMGB1 to interact differentially with parasitic and vertebrate DNA . We tested this hypothesis with a gel retardation assay using sonicated DNA incubated with increasing amounts of HMGB1 protein passively transferred to a PVDF membrane . As shown in Figure 9A , HMGB1 complexed with DNA had a different electrophoretic mobility than the HMGB1 alone ( lane H ) , that did not migrate into the gel . Importantly , HMGB1 formed complexes with sonicated L . major DNA even for the lowest ratios of HMGB1/DNA , whereas it barely interacted with vertebrate DNA at the highest ratios . In HMGB1/L . major DNA lanes 3–7 ( left part Figure 9A ) , little free HMGB1 is found , except at the highest molar ratios in lanes 6 ( 25∶1 ) and 7 ( 50∶1 ) . In contrast , in HMGB1/vertebrate DNA lanes 3–7 ( right part Figure 9A ) a larger amount of free HMGB1 is observed in lanes 5 to 7 . Quantification showed an increasing amount of bound HMGB1 on L . major DNA ( from lane 3 to 7 ) while very low amount of HMGB1 was complexed with vertebrate DNA in the same conditions ( Figure S7A ) . This result indicates that HMGB1 binding differs between -vertebrate and L . major DNA . To highlight the size and electrophoretic pattern of complexed DNA ( Figure 9B left ) , we subjected our gels to ethidium bromide ( EtBr ) staining before transfer . We found that increasing amounts of HMGB1 induce a dose-dependent retardation with both vertebrate and L . major DNA , albeit to a lesser extent . As observed earlier , higher amounts of HMGB1 are bound to L . major DNA ( Figure S7B ) . In this condition , we no longer detect free HMGB1 with vertebrate DNA , suggesting that the small free HMGB1 proteins diffuse rapidly during the EtBr staining step ( Figure 9B right ) . Similar experiments were performed with T . cruzi , T . brucei and T . vivax DNA . Even though all sonicated Trypanosomatidae DNA have the same size , the DNA retardation profiles are different when DNA is bound with HMGB1 ( Figure 9C ) . The amount of DNA bound HMGB1 depends on the nature of the parasite DNA and on HMGB1/DNA ratio ( Figure 9C and Figure S7C ) . However , more HMGB1 is attached to Trypanosomatidae DNA than to vertebrate DNA , indicating that these Trypanosomatidae DNAs share the same property as L . major DNA . Taken together , our results indicate that HMGB1 release by BMDCs is similar in response to parasite and vertebrate DNA . However , the propensity of HMGB1 to bind preferentially to parasitic DNA correlates with the increased activation of BMDCs in response to parasitic DNA .
While TLR9 shares a common function of nucleic acid recognition along with other TLRs ( TLR3 , TLR7 and TLR8 ) , it is also involved in parasite recognition [1] , [2] , [4] , [8] , [41] , [42] . Previously , it has been reported that DNA from certain protozoan parasites ( B . bovis , T . cruzi , T . brucei ) stimulated B cell proliferation and macrophage activation [1] , [43] , [44] . Here we provided experimental evidences that account for the specific activation of TLR9 pathway by L . major and other Trypanosomatidae DNA , which is not the case of vertebrate DNA . Previously , it has been proposed that the discrimination between microbial and self-DNA is based on the endosomal localization of TLR9 and the failure of self-DNA to access endosomes [16] , [18] . Here we have demonstrated that the minimal immunostimulary activity by vertebrate DNA compared to L . major DNA is not due to a limited accessibility for TLR9 since we observed the same uptake rates for both DNAs in BMDCs . By enhancing DNA translocation in endosomes with DOTAP , there was a significant increase in DCs activation by L . major DNA that remained TLR9-dependent while there was a low cellular activation only by a larger amount of complexed vertebrate DNA . In quantitative terms , four times more vertebrate DNA complexed to DOTAP displays 10% of the stimulatory activity of L . major DNA . Therefore , the same amount of DNA taken up by BMDCs may be sufficient to cause cellular activation by parasite DNA , but not by vertebrate DNA . We also eliminated the possibility that the lack of activation by vertebrate DNA was due to its large genomic size , as the differences in the BMDCs activation between L . major and vertebrate DNA persisted when the DNA were reduced to the same size by sonication . DNA-binding protein and cofactors such as UNC93B1 are also implicated in the endosomal TLR9 recognition . UNC93B1 mutant mice are highly susceptible to L . major and to T . cruzi , showing the involvement of TLR9 but also TLR7 and TLR3 in resistance to L . major infection [41] , [42] . Our work sheds light on the involvement of auxiliary protein associated with L . major DNA in TLR9 activation . We observed an increase in the expression of proinflammatory cytokines in DCs activated by L . major DNA complexed with different peptides as LL37 , SLPI or HMGB1 . We assumed a potential role of HMGB1 in the specific stimulation of L . major DNA by BMDCs , since HMGB1 increases the recognition of CpG-ODN by TLR9 and extracellular HMGB1 accelerates its delivery to the receptor [22] , [29] . Indeed , we have observed an increase in the expression of cytokines in stimulated BMDCs by HMGB1 complexed to L . major DNA but not when HMGB1 is alone or complexed to vertebrate DNA . In resting immune cells , HMGB1 is highly abundant in the nucleus but shuttles between it and the cytoplasm [45] . Following the activation by L . major and vertebrate DNA , the shuttle system is disturbed and HMGB1 gradually accumulates in the cytoplasm before being eventually secreted as described by Ivanov , after CpG stimulation of BMDCs . The extracellular contribution of HMGB1 was proved herein by the fact that glycyrrhizin [40] , a known inhibitor of extracellular HMGB1 , decreased cytokine production in response to DNA . HMGB1 may interact with DNA out of the cell , to eventually act as a co-stimulating factor . However we may also consider that this interaction take place within the cell , as suggested by the rapid cellular uptake of DNA and the subsequent translocation of HMGB1 after DNA activation . To define more precisely HMGB1 activity at the molecular level , we compared the interaction of HMGB1 with both DNAs . Although HMGB1 could interact with both DNAs in vitro , there was surprinsingly more HMGB1 on L . major than on vertebrate DNA . Similar observations were made for other Trypanosomatidae DNA ( T . cruzi , T . vivax , T . brucei ) . This strongly suggested that intrinsic differences between vertebrate and parasitic DNA might favour HMGB1 binding to parasitic DNA , therefore enhancing its contribution through TLR9-dependent pathways . Obviously , it is tempting to associate HMGB1 binding for parasitic DNAs to their composition and/or structure . First , L . major DNA as other Trypanosomatidae DNA is composed of a nuclear and a kinetoplastic DNA , consisting of a network of particular DNA structures ( maxi and mini-circles ) [46] . HMGB1 is considered to be a non specific single- or double-stranded DNA binding protein with special affinity for distorted DNA structures such as supercoiled DNA or DNA minicircles [27] . Secondly , the L . major genome is more GC rich than the mouse or the human genome ( 63% against 42% ) . Interestingly , one report described that HMGB1 has some preference for binding CpG-rich oligonucleotides over GpC/GpG ODNs on single-stranded DNA [29] . HMGB1 has also been reported to preferentially bind to stable and high-ordered structures as G-tetrads [47] , resulting from polyG sequences , which reduces nuclease sensitivity [37] . L . major DNA is more resistant to both nucleases , DNases I and II , than vertebrate DNA . DNase I is a nuclease responsible for degrading extracellular DNA . Dnase II is an ubiquitous lysosomal endonuclease that requires an acidic environnement to cleave DNA [36] . Our experiments suggest that the parasitic DNA could persist longer in the cell and therefore act as a better activator for TLR9 . Besides , this correlates with the higher proportion of polyG sequences in L . major DNA than in mouse DNA . Despite its greater sensitivity to DNases , vertebrate DNA was proved to inhibit TLR9 activation by L . major . This implies that the differences found between vertebrate and Trypanosomatidae DNA are due to their intrinsic properties and their nucleotidic motifs . Initially , TLR9 was identified as the receptor for oligonucleotides containing unmethylated CpG motifs [9] . It has been proposed that Trypanosomatidae DNA ( T . cruzi , T . brucei ) are hypomethylated and stimulate the expression of inflammatory cytokines [4] , [43] . Overmethylation of T . cruzi and T . brucei reduced but did not eliminate the stimulatory activity of these Trypanosomatidae DNA . Moreover , it has been found that even predominantly or completely unmethylated DNA was still not stimulatory [9] , [14] . Therefore , the idea that stimulatory properties of DNA correlate solely with the presence of unmethylated CpG motifs may be an oversimplification [14] . This implies that vertebrate DNA could contain unknown structural motifs that inhibit the immunostimulatory function of its unmethylated CpG motifs . More recently , it has been shown that the DNA sugar backbone 2′deoxyribose represents a prime determinant for the interaction between single-stranded DNA and TLR9 . In its natural phosphodiester state , the base-free 2′deoxyribose backbone acts as a basal TLR9 agonist and the addition of DNA bases , even lacking CpG motifs , enhances its agonist activity [11] . This suggests that any mammalian or pathogen DNA could activate TLR9 . However , along with other works [10] , [13] , we have shown that naked vertebrate DNA fails to activate innate immune cells . Besides , it has been reported that both stimulatory and inhibitory DNA oligonucleotides can interact with TLR9 , which also suggested a non specific process of recognition , but only stimulatory oligonucleotide could induce conformational changes leading to MyD88 recruitment and TLR9 signaling [48] . Competition for TLR9 activation has been already observed between CpG and inhibitory oligonucleotides [10] , [49] , [50] . In the presence of vertebrate DNA , we observed a similar inhibition of the activation induced by L . major DNA . Thus , vertebrate DNA could also be an effective TLR9 ligand . Altogether the data mentioned above on the differences between L . major and vertebrate DNA , with respect to HMGB1 interaction , resistance to DNase and DNA competition for TLR9 signaling , led us to compare their genomic sequences . Canonical and non canonical stimulatory and inhibitory sequences were investigated in both types of genome . The ratio of observed to expected ( rO/E ) stimulatory sequences is on average five times more in L . major DNA than in mouse and human DNA , whereas the ratio for inhibitory sequences is on average two times lower . This suggests that vertebrate genomes have counter-selected stimulatory motifs and selected for inhibitory motifs , presumably to avoid auto-immunity and/or better discriminate non-self DNA [18] . These differences in their sequence are moreover consistent with the observed competition between L . major and vertebrate DNA . Further analysis of different Trypanosomatidae genomes confirmed the presence of more stimulatory and less inhibitory sequences , compared to vertebrate genomes . Inhibition by vertebrate DNA can be generalized to other Trypanosomatidae DNA since it is based on a competition between DNA motifs contributing to TLR9 activation or inhibition . Until now very few data were available regarding nucleotide sequence and cellular events involved in the differential recognition of parasite and vertebrate DNA by TLR9 . Interestingly , the stimulatory activity of T . cruzi DNA is correlated with the finding that mouse- and human- like CpG motifs for TLR9 are clustered on retrotransposon VIPER ( vestigial interposed retroelement ) elements and mucin-like glycoprotein genes in the T . cruzi genome [4] . However , in L . major DNA , the stimulatory motifs are distributed throughout the whole genome and not concentrated in particular genomic regions as for T . cruzi . As it has been demonstrated by Krieg et al , 1998 , with adenovirus DNA that some serotypes are immunostimulatory and other not , due to differences in stimulatory or neutralizing CpG , we are convinced that the disbalance between stimulatory an inhibitory sequences could explain why L . major is a potent activator DNA , in comparison of vertebrate DNA . Moreover we agree with the data from Stacey et al , 2003 , wich suggested that a low frequency of active CpG may never reach sufficient concentration within the cells to cause cellular activation . It is interesting to note that human TLR9 also recognizes L . major DNA , leading to TLR9 signaling , but not the self-DNA . This ability of TLR9 to discriminate pathogen DNA from the self DNA is mentioned as a lock for additional security , enabling the cell to maintain its integrity [18] . This work brings further insights into how TLR9 discriminates between Trypanosomatidae and vertebrate DNA . We show that DNA sequences in Trypanosomatidae trigger activation of TLR9 . Additionally , we show for the first time the involvement of HMGB1 in the reponse to L . major . This result suggests that the interaction of parasite DNA with DNA-binding protein is involved in TLR9 signaling and , thus , in the innate immune response to this parasite . | Distinct laboratory mouse based models have allowed elucidating some of the processes that account for so called resistance or vulnerability to the Leishmania major parasite cutaneous inoculation . The outcome ranges from rapid healing – C57BL/6 mice- to progressive nonhealing ones – BALB/c mice . Distinct cell lineages contribute to sense and process molecules derived from the L . major parasite . Previous studies revealed a role for intracellular Toll-like receptor 9 ( TLR9 ) in host resistance to Leishmania major . L . major DNA is involved in innate immune response , since it induces TLR9 signaling and activation of dendritic cells . We were interested to further explore L . major DNA sequences focusing on their features as ( a ) either direct TLR9 agonists or antagonists ( b ) as well as once partnering with endogenous DNA binding proteins . We more specifically used mouse dendritic cells as sensing cells of L . major DNA as well as DNA from other Trypanosomatidae in comparison with vertebrate DNA . Overall , the data underscore a counter-selection of TLR9 agonist motifs in vertebrate DNA which is not found in Trypanosomatidae DNAs and suggest how TLR9 could discriminate between pathogen and self DNAs , to maintain the cellular integrity . | [
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"comparat... | 2014 | TLR9 Activation Is Triggered by the Excess of Stimulatory versus Inhibitory Motifs Present in Trypanosomatidae DNA |
Rio de Janeiro , Brazil , experienced a severe dengue fever epidemic in 2008 . This was the worst epidemic ever , characterized by a sharp increase in case-fatality rate , mainly among younger individuals . A combination of factors , such as climate , mosquito abundance , buildup of the susceptible population , or viral evolution , could explain the severity of this epidemic . The main objective of this study is to model the spatial patterns of dengue seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro . As blood sampling coincided with the peak of dengue transmission , we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance . We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model ( GAM ) . Three neighborhoods were investigated: a central urban neighborhood , and two isolated areas characterized as a slum and a suburban area . Weekly mosquito collections started in September 2006 and continued until March 2008 . In each study area , 40 adult traps and 40 egg traps were installed in a random sample of premises , and two infestation indexes calculated: mean adult density and mean egg density . Sera from individuals living in the three neighborhoods were collected before the 2008 epidemic ( July through November 2007 ) and during the epidemic ( February through April 2008 ) . Sera were tested for DENV-reactive IgM , IgG , Nested RT-PCR , and Real Time RT-PCR . From the before–after epidemics paired data , we described seroprevalence , recent dengue infections ( asymptomatic or not ) , and seroconversion . Recent dengue infection varied from 1 . 3% to 14 . 1% among study areas . The highest IgM seropositivity occurred in the slum , where mosquito abundance was the lowest , but household conditions were the best for promoting contact between hosts and vectors . By fitting spatial GAM we found dengue seroprevalence hotspots located at the entrances of the two isolated communities , which are commercial activity areas with high human movement . No association between recent dengue infection and household's high mosquito abundance was observed in this sample . This study contributes to better understanding the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence , recent dengue infection , and vector density . In conclusion , the variation in spatial seroprevalence patterns inside the neighborhoods , with significantly higher risk patches close to the areas with large human movement , suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro . Surveillance guidelines should be further discussed , considering these findings , particularly the spatial patterns for both human and mosquito populations .
Dengue is a mosquito-borne viral infection , considered a major public health problem in many tropical regions of the world , including Brazil [1] , [2] . Aedes aegypti is the most important dengue vector worldwide [3]–[5] and the only known vector in Brazil [6] . Dengue infection can manifest itself as clinically unapparent , an undifferentiated febrile illness , classic dengue fever ( DF ) , or dengue hemorrhagic fever ( DHF ) . Prevalence of dengue is highest in tropical areas of Asia and the Americas , with 50–100 million estimated cases of dengue fever and 250 , 000–500 , 000 cases of dengue hemorrhagic fever occurring annually worldwide as explosive outbreaks in urban areas [7] , [8] . In Brazil , three dengue virus serotypes ( DENV ) have been introduced through Rio de Janeiro in the past three decades: DENV-1 in 1986 [9] , DENV-2 in 1990 [10] , and DENV-3 in 2000 [11] . Figure 1 shows the time series of dengue cases in Rio de Janeiro State from 2000 to 2008 [12] . The introduction of DENV-3 in the state of Rio de Janeiro led to severe epidemics in 2002 with the largest number of cases ( 288 , 245 notified ) , with 1 , 831 DHF cases and 91 deaths , corresponding to 1 , 735 reported cases per 100 , 000 inhabitants [13] , and a case-fatality ratio of 3 . 15∶10 , 000 . Eight years later , in 2007–2008 , during the current study , Rio de Janeiro ( and Brazil ) experienced the most severe dengue epidemics ever reported in terms of morbidity and mortality [14] . During this period , 322 , 371 cases and 240 deaths were registered , with 100 deaths due to DHF/dengue shock syndrome ( DSS ) and 140 due to other dengue-related complications [12] . That represented a case-fatality rate of 9 . 4∶10 , 000 . Contrasting with the previous epidemics , the 2008 epidemic , essentially caused by DENV-2 , was characterized by a higher incidence of severe cases in children . In fact , 36% of deaths reported occurred in individuals ≤15 years old [12] , [15] . Rio de Janeiro presents highly favorable conditions for transmission of dengue [13] , as shown by serological cross-sectional surveys carried out after the arrival of DENV-1 and DENV-2 . In 1987 , after the first wave , 45 . 5% of schoolchildren were positive for DENV-1 haemagglutination inhibition antibodies ( HAI ) [16] . HAI antibody persists for a long period , but is highly cross-reactive [3] . In the neighbor city of Niterói , 55% of schoolchildren were positive in 1988 , and 66% in 1992 ( after the arrival of DENV-2 ) [17] , [18] . In Paracambi , another neighbor city , 29 . 2% schoolchildren were positive in 1997 [19] . Dengue surveillance and control in large urban areas with high levels of dengue transmission pose important challenges . Clinical surveillance is impaired by the high proportion of asymptomatic infections [20] , [21] , [22] , and mosquito surveillance is very time and resource consuming . Moreover , despite the theoretical association between vector abundance and risk of transmission , the quantitative nature of this relationship is poorly known [23] . Understanding the epidemiology of this disease requires studies that integrate epidemiological and entomological data [19] , [21] , [24] , [25] . The main objective of this study is to model the spatial patterns of seroprevalence in three neighborhoods with different socioeconomic profiles in Rio de Janeiro . As blood sampling coincided with the peak of dengue transmission , we were also able to identify recent dengue infections and visually relate them to Aedes aegypti spatial distribution abundance . We analyzed individual and spatial factors associated with seroprevalence using Generalized Additive Model ( GAM ) .
Surveys were performed in three neighborhoods of Rio de Janeiro city: Higienópolis , Tubiacanga , and Palmares , which differ in human population density , sanitation , vegetation cover , and history of dengue ( Fig . 2 ) . Since neighborhoods were large and heterogeneous , we restricted the survey to an area of approximate 0 . 25 km2 in each one [26] . The serological surveys were carried out in July-November 2007 and February-April 2008 , the latter coinciding with the 2008 high transmission period [12] . The study areas had been under entomological surveillance since September 2006 ( see Mosquitoes surveillance section ) [26] . The entomological surveillance consisted of weekly collections of Ae . aegypti eggs and adults using traps located in 80 households per site . All householders participating in the entomological surveillance were invited to participate in the serological surveys . Only 72 out of 240 householders agreed to participate ( 13 in Higienópolis , 31 in Tubiacanga and 28 in Palmares ) . To increase the sample , we invited additional residents from nearby houses , reaching a total of 171 participating households ( 19 in Higienópolis , 93 in Tubiacanga and 59 in Palmares ) , with 337 individuals ( 44 in Higienópolis , 162 in Tubiacanga and 131 in Palmares ) . Since previous studies reported lower seropositive rates in the younger age classes [16] , [18] , [19] , we concentrated our sample effort in the age group of 1–20 years old to increase the chance of detecting seroconversion events [30] . However , due to problems related to participant refusal , particularly for small children in the urban area , older people were included as well , to increase the sample size . The range and median age in the sample is presented in Table 1 . A questionnaire was applied to each enrolled individual , with questions regarding sex , age , education level , yellow fever ( YF ) vaccination status , clinical symptoms of dengue-like disease and past dengue episodes . The location of each household was determined by a hand-held , 12 channel global positioning system ( Garmin ) , which accurate to 15 m . Recent dengue infection was defined by the detection of DENV IgM antibodies in any sample ( first or second sample ) within the last 6 weeks or so . Seroprevalence was defined by detection of DENV IgG antibodies in the first sample ( July–November/2007 ) . Seroconversion was defined only for the paired samples – negative in the first sample and positive in the second one – considering both IgM and IgG . Primary infection was defined as a negative IgG in the first sample with positive IgM in the second and secondary infection when DENV IgG antibodies were detected in the first sample . Individuals with DENV IgM antibodies were considered asymptomatic cases when clinical definition of dengue – high fever , accompanied by at least two of the associated symptoms: headache , myalgia , arthralgia retro-orbital pain and rash – was not met [31] . A blood sample ( 5 mL ) was collected from all participants during the household visit , stored at −20°C and processed within 12 hours . Sera were tested for DENV- reactive IgM and IgG immunoglobulin by using PANBIO dengue IgM capture and dengue IgG indirect Elisa ( Brisbane , Australia ) . Viral RNA for the nested RT-PCR and real-time RT-PCR assays was extracted from 140 µL of serum samples by the QIAamp Viral RNA Mini Kit ( QIAGEN , Valencia , CA ) , according to the manufacturer's instructions . RNA was eluted in 60 µL of buffer ( AVE ) and stored at −70°C . For the quantitative TaqMan assay , a 10-fold-dilution series containing a known amount of target viral RNA ( 107 RNA copies/mL ) was used for RNA extraction . The nested RT-PCR protocol for DENV detection and typing was performed on serum samples , which tested DENV IgM positive according to [32] . One-step real-time RT-PCR assays were performed in the ABI Prism 7000 Sequence Detection System ( Applied Biosystems , Foster City , CA ) in all IgM positive samples . Briefly , samples were assayed in a 25 µl reaction mixture containing 5 µl of extracted RNA , 1 µl of 40X Multiscribe enzyme plus RNAse inhibitor , 12 . 5 µl TaqMan 2X Universal PCR Master Mix ( Applied Biosystems , Foster City , CA ) and 300 nM of each specific primer and fluorogenic probe . Positive and negative controls were included . To detect specific DENV1-2 , primer and probe sequences were obtained from [33] . To detect specific DENV-3 , primer and probe sequences were obtained from [34] . The TaqMan probe was labeled at the 5′ end with the 5-carboxyfluorescein ( FAM ) reporter dye and at the 3′ end with 6-carboxy-N , N , N′ , N′-tetramethylrhodamine ( TAMRA ) quencher fluorophore . The number of viral RNA copies detected was calculated by generating a standard curve from 10-fold-dilutions of DENV-3 RNA , isolated from a known amount of local virus propagated in Aedes albopictus C6/36 cells [13] , the titer of which was determine by plaque assay . The same model of DENV-3 standard curve was applied to build DENV-1 and DENV-2 curves . Quantitative interpretation of the results obtained was performed by interpolation from the standard curve included in each independent run for each serotypes . Entomological surveillance was carried out with two types of traps for ovipositing females , egg traps and adult traps . Egg traps are black plastic containers , filled with 300 ml of a 10% hay infusion , and a wooden paddle held on the wall for oviposition [26] , [35] , [36] , [37] . Adult traps ( version 1 . 0 , Ecovec Ltd ) consists of a matte black container ( 16 cm high×11 cm diameter ) with approximately 280 ml of water and a removable sticky card . A synthetic oviposition attractant was used to attract gravid female mosquitoes [38] . Surveillance was conducted weekly from September , the 6th 2006 to March , 24th 2008 in the three study areas , encompassing two wet-hot seasons and one dry-cool season . In each study area , 40 adult traps and 40 egg traps were installed in a random sample of premises [26] . Two infestation indexes were calculated: mean adult density ( MAD = number of trapped female Ae . aegypti/number of adult traps and mean egg density ( MED = number of collected eggs/number egg traps ) . Details on the entomological methods and results are described in [26] . To evaluate potential heterogeneities in the spatial distribution of mosquito abundance during the serological surveys , we aggregated the weekly entomological collections over time , from April/2007 to March/2008 , into a single index . Recent dengue infections are plotted on this vector abundance map to inspect for possible associations . Breteau Index ( number of Ae . aegypti-positive containers per 100 houses ) measured in March , June , August , November of 2007 and January and April of 2008 in each study area was also obtained from Public Health Office of Rio de Janeiro city . The number of recent dengue infections was very small , and consequently , not statistically modeled ( descriptive data in Table 1 ) . To compare and possibly to advance further investigations , the coordinates of negative and positive ( in any sample ) DENV IgM antibodies were mapped over the aggregated distribution of adult mosquito abundance . The technique to build the interpolated surface is presented in the section below . To compare seroprevalence among the areas we standardized the proportion of positive samples ( direct method ) using the total number of samples in all areas . Seroprevalence data was analyzed using a Generalized Additive Model ( GAM ) : a statistical model that extends the generalized linear models to include non-parametric smoothing terms . In the generalized linear model , the response variable belongs to the exponential family , and its mean value is related to the linear predictors through a link function . The canonical link function for binomial response , such as positive or negative sera , is the logit link . To evaluate possible non-linearity of the age effect on the outcome we used a smooth-spline and plotted the predicted against the observed value . The spatial distribution was modeled using a bi-dimensional smooth function [39] . The complete model thus included a set of directly observed covariates and a function – in our case , a thin plate spline – applied on the geographical coordinates of each household , as depicted in the equation below: is the response variable , are the slope coefficients of the model , so is the adjusted odds ratio , are the explanatory variables at the individual and household levels , the function is a smooth function of geographic co-ordinates and are the residuals . All covariates with a p-value ≤0 . 10 in the univariate analysis were included in the multivariate model . The approach used to analyze the spatial distribution started with a model with just the smooth function of the coordinates . Then explanatory variables were included successively until the final adjusted model was obtained . Contour lines at p-value ≤0 . 05 were drawn on the maps to identify areas with significantly higher ( red lines ) and lower risk ( blue lines ) than the overall mean . In the case of the mosquito interpolation surface , the adults counts were the outcome variable and the smoothed geographic coordinates of the adult traps were the independent variables . All statistical analyses were performed using the statistical software R 2 . 8 . 1 [40] , with library mcgv [41] . Ethical clearance was obtained from the Ethical Committee in Research ( CEP 365/07 ) from the Oswaldo Cruz Foundation , Ministry of Health , Brazil . Written consent to participate in the two surveys was obtained from each participant and in case of minor , from their legal guardians .
All administrative areas containing the studied neighborhoods had a history of dengue cases recorded by the local public health authorities [42] . Figure 3 shows the time series of reported dengue cases from Public Health Office of Rio de Janeiro city , with a clear peak between December/2007 and April/2008 , during the present study . In 2008 , the attack rates were: 45 . 94/‰ in Higienópolis , 35 . 17 in Galeão area ( where the neighborhood of Tubiacanga is located ) and 19 . 68 in Vargem Pequena area ( where the suburban slum of Palmares is located ) . Aedes aegypti abundance was consistently high throughout the year in the urban and suburban sites ( Higienópolis and Tubiacanga ) , and low in the suburban slum ( Palmares ) . The largest increase in notified dengue fever cases began in December/2007 and apparently was not preceded by an increase in vector density as measured by our study . The mosquito indices ( MAD and MED ) time series fluctuated over the time . An increase in summer is clear in both suburban areas , but not in the urban area . The bars at the bottom of the picture , showing the number of recent dengue infections relative to the number of collected blood samples , coincide with the high peak of the 2008 epidemic . The Breteau index ranged from 4 . 20 to 11 . 32 in Higienópolis , 4 . 10 to 20 . 51 in Tubiacanga and 3 . 30 to 15 . 38 in Palmares . Table 1 shows the results of the serological surveys . From 337 individuals , 247 provided paired serum samples ( 73 . 3% ) ( Higienópolis: paired/unpaired = 28/16; Tubiacanga = 117/45; Palmares = 102/29 ) . Age of participants ranged from 1 to 79 years , with an average of 16 . 9 . There were 156 ( 46 . 3% ) males and 181 ( 53 . 7% ) females . For education level , 29 ( 8 . 6% ) were illiterate , 241 ( 71 . 5% ) reported elementary school , 56 ( 16 . 6% ) high school , and 11 ( 3 . 3% ) college . Only 6 . 2% of the study subjects reported vaccination against yellow fever and 16% reported a previous history of dengue . The combination of four methods provided diagnostic confirmation of dengue infection as follows: previous exposure to dengue ( IgG ) in the first survey detected in 199 ( 61 . 0% ) out of the 326 individuals . Recent dengue infection ( IgM ) was detected in 30 individuals ( 4 in Higienópolis , 7 in Tubiacanga , and 19 in Palmares ) , which were subjected to nested RT-PCR and real-time RT-PCR ( Table 1 ) . DENV-RNA was detected in 5 individuals ( 4 DENV-2 and 1 DENV-3 ) , by Nested RT-PCR and Real Time RT-PCR ( TaqMan ) . Adopting quantitative real-time RT-PCR , we examined levels of DENV-RNA . The results revealed low viral RNA , ranging from 1 to 45 RNA copies/mL . Dengue seroprevalence varied between the study areas . The age standardized proportions were 60 . 26% in Higienópolis , 56 . 07% in Tubiacanga and 77 . 44% in Palmares ( Table 1 , Fig . 4 ) . In Higienópolis , the urban area , participation in the study was the lowest in all age groups , and the largest number of samples was in the interval of 5 to 9 years old . Frequency of seropositive samples increased with age ( Fig . 4 ) . In Tubiacanga a non-linear relationship between age and seroprevalence was observed , with a plateau at about 15 year old ( Fig . 5 ) . In the other two areas , the relationship between seroprevalence and age was linear and significant . Due to the non-linearity observed in Tubiacanga , we categorized the variable age , using cut points at 10 and 20 years old , to analyze the effect of age on seroprevalence in the multivariate models . The variable sex was significant only in Tubiacanga , while self-reported past dengue was a predictor of seropositivity in Tubiacanga and Palmares . Yellow fever vaccination was not statistically associated with dengue seropositivity in any study area ( Table 2 ) . Prevalence smooth maps , with darker gray colors indicating higher odds ratio ( OR ) , are shown in Figure 6 . In Higienópolis , the urban area , the spatial distribution of seroprevalence showed a linear North-South trend , with the highest odds ratios three times larger than the average value . However , no location in this area presented statistically significant differences in OR . Tubiacanga , the suburban area , presented similar variation in spatial odds ratio , with a high OR 3 . 0 region in the middle of the map , and this variation in chance significant ( depicted by the red line in the map ) . In Palmares , the suburban slum , we observed the highest differences in seroprevalence distribution , with significantly high risk patch with OR = 56 on the Northeast , where the main access to the community is located . Towards the South , a protective spatial effect is evident , and an area with a protective effect was observed , located close to a forested area . The OR maps resulting from the models adjusting for individual covariates ( sex and age ) presented a very similar pattern , and therefore are not shown . Figure 7 shows maps of adult Ae . aegypti abundance . Dots indicate the location of surveyed households with and without cases of recent dengue infection . Darker shades of gray indicate higher levels of mosquito abundance , measured in terms of relative risk ( RR ) . Visual inspection , the only possible analysis due to the small number of recent dengue infections , suggests no evidence of a coincident pattern . In the urban area , Higienópolis , mosquito RR varied from ca 0 . 25 to 4 . 5 , with a significantly high mosquito density area ( depicted in red in the map ) . Only one of the four new infections is located inside or close to this area . In the suburban area , Tubiacanga , spatial variability in mosquito density was smaller , with RR going up to 3 . Recent dengue infections are spread evenly over the entire area , just two in seven located inside a mosquito hotspot . Palmares , the suburban slum , showed the smallest variation in the vector density – with mosquitoes homogeneously covering the whole area , and recent dengue infections are also homogeneously distributed over the region , without any detectable pattern .
High dengue virus activity in Brazil during the past 20 years is evidenced by the large number of reported cases , in almost all states [13] , [21] , [22] . Rio de Janeiro , located in the Southeast Region of Brazil , is one of the most densely populated cities and has always been an important entry point for dengue viruses into the country [13] , [43] , [44] ( Fig . 3 ) . In 2008 , DENV-2 was the predominant serotype [12] , [42] . In the current study , we confirmed the co-circulation of DENV-2 and DENV-3 serotypes in 5 individuals ( 4 DENV-2 and 1 DENV-3 ) , by molecular methods , DENV-2 serotype invaded Rio de Janeiro 19 years before this study [10] , when it caused an epidemic that resulted in about 100 . 000 notified cases . The 2008 DENV-2 epidemic struck a population were most children had no previous contact with this serotype , while most in the 10–20 years old group probably had experienced previous infections with either DENV-2 or DENV-3 . Our results confirm this epidemiological scenario , with a high predominance of recent infections in children under 15 years old ( 18/30 ) . Although the number of recent dengue infections was small , we decided to present the data because it is rare to have any recent infection data in population surveys . The epidemic that occurred during our field work presented the largest number of severe cases in children [12] , [42] . However , in our data , only 23 . 3% of infections were symptomatic , suggesting that even during such severe epidemic , silent circulation of the virus is highly prevalent [20] , [21] , [45] , [46] . A consequence of high frequency of asymptomatic infections is that measures of notified cases greatly underestimate the true incidence of infection and difficult the identification of high risk transmission areas within cities [47] . We observed events of recent dengue infection in residences located in areas with low mosquito densities , suggesting that infection took place out of the residence , either in other premises – school , for instance – or outdoors , ( where children in these neighborhoods stay most of daytime , when Aedes mosquitoes are more active ) . However , the lack of coherence between household mosquito counts and recent dengue infection should be further investigated in future work , by comparing the current data with infected Ae . aegypti information [48] . In parallel , information on human population movement patterns could also bring further insight on dengue fever transmission dynamics and the main places of transmission , eventually serving to build an early warning system for dengue outbreaks . Entomological surveillance is of great importance for early detection of transmission risk and for directing vector control measures . However , in Brazil , vector surveillance using Premise and Breteau indices correlates poorly with dengue incidence [49] , [50] , [51] , and moderately with the rate of epidemic growth [25] . In Puerto Rico a study [52] to investigate the relationship between serological and epidemiological surveys and mosquito density showed that none of the household characteristics evaluated was significantly associated with recent dengue infection , except the number of female Ae . aegypti per person . In Colombia , the only entomological factor related to dengue infection in humans was the pooled infection rate of mosquitoes . It would be helpful to discover the threshold of mosquito density that would trigger an epidemic [51] , [53] . Epidemiological studies have identified statistical risk factors for human infection or diseases [54] , [55] , [56] . Statistical models can bridge the gaps between landscape ecology , vector biology and human epidemiology , providing a sound approach to understanding risk and planning for control in heterogeneous environments , especially when the models are based on the ecology of the local vector populations [55]–[58] . Additionally , understanding the space and time distribution of risk for mosquito-borne infections is an important step in planning and implementing effective infection control measures [59] , [60] . This is because space and time are two important dimensions in describing epidemic dynamics and risk distribution [61] . Our results point to larger spatial heterogeneity in dengue seroprevalence in the most isolated areas – Tubiacanga and Palmares . In Tubiacanga , seroprevalence concentrated in the area with more intense commercial activity , schools and the main bus station . In Palmares , seroprevalence was concentrated in the slum entrance , also an area of high commercial activity and human movement . We hypothesize that such isolated populations are too small to maintain the dengue virus endemically and that the observed seroprevalence maps are the result of multiple viral introductions through the last 20 years , always through the same entrance . Such spatial clustering of dengue has being reported in the literature [45] , [46] , and supports the hypothesis that mosquito-borne disease incidence is highly focal [46] , [62] . On the other hand , a spatial pattern was not observed in Higienópolis , a neighborhood with multiple accesses and surrounded by slums with high population density . These results highlight the important role on dengue transmission , of public spaces where human movement is intense , possibly more important than the households . Further characterization of human movement patterns should provide additional information in the understanding of dengue transmission dynamics [63] . Some authors have suggested that people rather than mosquitoes rapidly move dengue virus within and among communities [64] , [65] . The present study is consistent with this information . Our results must be considered in the context of the limitations of the serological survey . First , the small number of recent dengue infections precluded a more adequate modeling of incidence versus mosquito density associations . Second , the age distribution , particularly in Higienópolis , was not comparable to the other areas . Third , households in the entomological and serological surveys did not match exactly what may precluded the identification of association between mosquito abundance and risk of infection . This study contributes to a better understanding of the dynamics of dengue in Rio de Janeiro by assessing the relationship between dengue seroprevalence , recent dengue infection , and vector density . In conclusion , the variation in spatial seroprevalence patterns inside the neighborhoods , with significantly higher risk patches close to the areas with the greatest human movement , suggests that humans may be responsible for virus inflow to small neighborhoods in Rio de Janeiro . Surveillance guidelines should be further discussed , considering these findings , specially the spatial patterns for both human and mosquito populations . | Dengue is a major public health problem in many tropical regions of the world , including Brazil , where Aedes aegypti is the main vector . We present a household study that combines data on dengue fever seroprevalence , recent dengue infection , and vector density , in three neighborhoods of Rio de Janeiro , Brazil , during its most devastating dengue epidemic to date . This integrated entomological–serological survey showed evidence of silent transmission even during a severe epidemic . Also , past exposure to dengue virus was highly associated with age and living in areas of high movement of individuals and social/commercial activity . No association was observed between household infestation index and risk of dengue infection in these areas . Our findings are discussed in the light of current theories regarding transmission thresholds and relative role of mosquitoes and humans as vectors of dengue viruses . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [
"ecology",
"public",
"health",
"and",
"epidemiology",
"virology"
] | 2009 | Spatial Evaluation and Modeling of Dengue Seroprevalence and Vector Density in Rio de Janeiro, Brazil |
The Mre11-Rad50-Xrs2 nuclease complex , together with Sae2 , initiates the 5′-to-3′ resection of Double-Strand DNA Breaks ( DSBs ) . Extended 3′ single stranded DNA filaments can be exposed from a DSB through the redundant activities of the Exo1 nuclease and the Dna2 nuclease with the Sgs1 helicase . In the absence of Sae2 , Mre11 binding to a DSB is prolonged , the two DNA ends cannot be kept tethered , and the DSB is not efficiently repaired . Here we show that deletion of the yeast 53BP1-ortholog RAD9 reduces Mre11 binding to a DSB , leading to Rad52 recruitment and efficient DSB end-tethering , through an Sgs1-dependent mechanism . As a consequence , deletion of RAD9 restores DSB repair either in absence of Sae2 or in presence of a nuclease defective MRX complex . We propose that , in cells lacking Sae2 , Rad9/53BP1 contributes to keep Mre11 bound to a persistent DSB , protecting it from extensive DNA end resection , which may lead to potentially deleterious DNA deletions and genome rearrangements .
Similarly to what is seen in higher eukaryotes , in S . cerevisiae the ends of a double-strand DNA break ( DSB ) are recognized and bound by the Mre11-Rad50-Xrs2 ( MRX ) complex and the Ku70-Ku80 heterodimer , which compete for end binding . Once the MRX complex , together with CDK1-phosphorylated Sae2 ( CtIP in human ) , initiates resection of the DNA ends , Ku70-Ku80 binding and NHEJ ( non-homologous end-joining ) are prevented [1] , [2] , [3] , [4] . Subsequent 5′–3′ long-range resection can then occur by one of two pathways: the first utilizes the RecQ helicase Sgs1 ( BLM in human ) , in cooperation with the endonuclease Dna2 , and the second utilizes the exonuclease Exo1 [5] , [6] , [7] , [8] , [9] . The regulation of DSB end resection is very important to choose the right pathway to repair a DSB and avoid chromosomal rearrangements [10] , [11] . Whereas classical NHEJ requires little or no resection , HR ( homologous recombination ) is characterized by extensive exonucleolytic degradation of one strand . Blocking DNA end resection affects the efficiency and accuracy of how a DSB is repaired . For example , inhibiting resection leads to de novo telomere addition , and eventually loss of a portion of a chromosome [12] , [13] . On the other end , extensive DNA end resection could lead to accumulation of unstable DNA intermediates and eventually to the highly error-prone microhomology-mediated end joining ( MMEJ ) and single-strand annealing ( SSA ) events , which may cause DNA deletions and translocations [14] , [15] , [16] . It is now clear that the DNA damage checkpoint response ( DDR ) plays a central role in regulating DSB end resection . In fact , while resection proceeds , the formation of RPA-coated ssDNA activates the upstream kinase Mec1 ( ATR in mammals ) and the effector kinase Rad53 ( Chk2 in mammals ) , which in turn phosphorylates and inhibits Exo1 [17] . Interestingly , Exo1 is regulated through a DDR pathway in human cells , too [18] , [19] . Moreover , studies both in yeast and mammals showed that Exo1 and other DNA end-processing enzymes are inhibited through a physical structural “barrier” formed by Rad9 oligomers ( 53BP1 in mammals ) bound near a DSB [10] . RAD9 was originally identified as the first checkpoint gene in S . cerevisiae and recognized as an “adaptor” protein , linking the upstream kinase Mec1 to the activation of effector kinases Rad53 and Chk1 . Rad9 is recruited to chromatin through three different pathways: i ) the constitutive interaction with the histone H3 methylated at the K79 residue by Dot1 [20] , [21] , [22]; ii ) the binding to the histone H2A phosphorylated at the S129 residue by Mec1 [23]; iii ) the interaction with Dpb11 [24] , [25] . In particular , phospho-H2A mediated Rad9 recruitment spreads many kilobases around a DNA lesion [26]; whereas Dpb11 appears to be more specific at the site of lesion , by binding to a damage-induced phosphorylation in the Ddc1 subunit of the 9-1-1 complex [25] , [27] , [28] . All of these three pathways cooperate for efficient checkpoint arrest and cell survival after genotoxic treatments throughout the cell cycle . Moreover , Rad9 contains motifs that are necessary for its oligomerization and DNA damage checkpoint signalling [24] , [29] , [30] . Notably , the Rad9-mediated inhibition of DSB resection is a regulatory function conserved throughout evolution . In fact , 53BP1 facilitates NHEJ at the expense of HR , protecting DNA ends from inappropriate 5' resection , in cooperation with the telomere binding protein RIF1 [31] , [32] , [33] , [34] , [35] . Here , we show that in the absence of Sae2 , or in presence of mutations affecting Mre11 nuclease activity , Rad9 dimers and/or oligomers , recruited near a DSB mainly by Dpb11 interaction , inhibit the short-range DNA end processing , thereby preventing Mre11 removal from the lesion and limiting Rad52 recruitment by an Sgs1-dependent mechanism . As a consequence , DSB ends cannot be kept efficiently tethered to each other , and repair through an SSA process is prevented . We propose a novel molecular role of Rad9/53BP1 to protect genome integrity from extensive DNA degradation and rearrangements during DSB repair , also suggesting important implications for malignant transformation in mammalian cells .
It is known that deletion of the RAD9 gene in yeast leads to faster DSB resection and repair through an SSA process [36] , [37] . To further understand the role of Rad9 in DSB processing and repair , we decided to combine the deletion of RAD9 gene with mutations in genes encoding factors either involved in the short-range ( SAE2 ) , or the long-range ( EXO1 , SGS1 ) DSB resection [38] . We took advantage of the YMV80 background , in which the galactose-induced expression of the HO nuclease causes a single DSB at a specific site on chromosome III . Repair of this DSB occurs mainly through SSA between flanking homologous leu2 repeats one of which is 25kb from the DSB [39] . We deleted RAD9 , EXO1 , SGS1 and SAE2 to obtain all viable single , double and triple mutant combinations . Although the sae2Δ sgs1Δ double mutant is a synthetic lethal combination [40] , [41] , rad9Δ interestingly suppresses sae2Δ sgs1Δ lethality ( S1A Fig . ) . Therefore , it was possible to test the sae2Δ sgs1Δ rad9Δ triple mutant cells . After plating the cells in the presence of galactose to induce one DSB , we found that viability of the sae2Δ and sgs1Δ single mutant and sgs1Δ exo1Δ double mutant was severely reduced ( Fig . 1A ) , as expected [6] , [7] , [42] . We also found that the deletion of RAD9 gene effectively rescued the viability of the sae2Δ , sgs1Δ and sae2Δ exo1Δ mutant strains following one DSB ( Fig . 1A ) . Interestingly , the viability of the sae2Δ sgs1Δ rad9Δ and exo1Δ sgs1Δ rad9Δ triple mutant cells was very low in the presence of one DSB . Moreover , the HO-induced lethality of the sae2Δ sgs1Δ rad9Δ mutant was not rescued by the expression of the Sgs1-K706A protein variant ( S1B Fig . ) , whose helicase activity is severely reduced [43] . While the failure to repair the DSB in the exo1Δ sgs1Δ rad9Δ triple mutant was expected , since at least one of the Exo1 and Sgs1-dependent pathways is necessary to extensively resect a DSB , the result obtained with the sae2Δ sgs1Δ rad9Δ mutant was surprising . We therefore concluded that an Exo1-independent , Sgs1-dependent pathway is necessary for the viability of sae2Δ cells following a DSB in the absence of RAD9 . Since Sae2 stimulates the activity of the MRX complex in the first step of the DSB end processing [44] , we considered the possibility that RAD9 deletion may also rescue an Mre11 nuclease defective mutant or the rad50Δ mutant , in which the MRX complex is disassembled . Interestingly , we found that rad9Δ suppresses the nuclease-defective mre11-D56N mutant [45] , through an SGS1-dependent pathway , while it does not rescue rad50Δ mutant , as expected [36] ( Fig . 1B ) . These results suggest that the nuclease activity of the MRX complex is dispensable for the DSB repair in rad9Δ cells; however , the MRX complex must be physically present , likely playing an essential structural role . Indeed , rad50Δ mutation does not rescue sae2Δ cell viability following a DSB ( Fig . 1B ) . Of note , deletion of RAD9 also suppresses the double mutant mre11-D56N sae2Δ , further indicating that Mre11 and Sae2 work together in the same pathway ( Fig . 1B ) . Importantly , the deletion of RAD9 rescues sae2Δ cell viability through an EXO1-independent , SGS1-dependent pathway also in presence of camptothecin ( Fig . 1C ) , a topoisomerase-aborting agent that causes formation of end-blocked DSBs [46] . To further investigate the findings shown in Fig . 1A at the molecular level , we tested the kinetics of DSB repair by Southern blotting in cells blocked in G2/M cell cycle phase by nocodazole . In agreement with the cell lethality reported in Fig . 1A , we found that the efficiency of the DSB repair is reduced in both the sae2Δ and sgs1Δ single mutants , as previously described [6] , [7] , [42] , and it is severely compromised in sae2Δ sgs1Δ rad9Δ ( Figs . 2B and 2C ) . On the contrary , DSB repair is accelerated and very efficient in the rad9Δ , sae2Δ rad9Δ and sgs1Δ rad9Δ mutants ( Figs . 2B and 2C ) . These results indicate that , in the absence of Rad9 , an Sgs1-dependent mechanism is necessary to efficiently repair a DSB in sae2Δ cells . To test if Sgs1 cooperates with Dna2 to repair a DSB in sae2Δ rad9Δ mutant cells , we took advantage of an auxin-based degradable Dna2 protein variant ( Dna2-DEG ) . This is a common genetic strategy to induce the degradation of a protein by the addition of auxin compound to the cell culture medium [47] , and it is particularly useful in the case of an essential gene , such as DNA2 . By Southern blotting analysis , we found that the sae2Δ rad9Δ double mutant cells do not repair a DSB in the absence of Dna2 ( Fig . 2D and 2E ) . Therefore , taking all the data in Fig . 2 together , we concluded that the deletion of RAD9 rescues sae2Δ cells through a DSB resection mechanism mediated by the Sgs1-Dna2 pathway . In addition , we ruled out the possibility that in the absence of Rad9 , the DSB can be repaired more efficiently through a strand invasion-based mechanism ( such as a break-induced replication process [48] ) . In fact , we observed faster DSB repair and high viability when we analysed the sae2Δ rad9Δ rad51Δ triple mutant , in which break-induced replication is impaired , but SSA is not inhibited ( S2 Fig . ) . A critical step to repair a DSB through SSA is 5′ to 3′ resection of the DSB end . Therefore , based on our results in Figs . 1 and 2 , we hypothesized that in sae2Δ sgs1Δ rad9Δ triple mutant DSB resection may be affected , as it was shown in the sae2Δ single mutant [6] , [7] , [42] , while it should be faster in sae2Δ rad9Δ double mutant . To test the kinetics of DSB processing we used JKM139 background derivatives , where prolonged expression of HO causes an irreparable DSB at MAT locus , because of the absence of HML and HMR homologous cassettes . Therefore , the analysis of the formation of the 3′ single-stranded ( ss ) DNA is not biased by a repair process [49] . Using Southern blotting of denatured DNA after restriction enzyme digestion [50] , we tested the formation of the 3′ ssDNA filament ( as depicted in Fig . 3A ) , after the induction of one DSB in each sister chromatid , in G2/M-blocked cells . As expected , we found that the formation of a long 3′ ssDNA tail is slightly delayed in the absence of SAE2 , EXO1 and SGS1 genes , and it is severely compromised in the exo1Δ sgs1Δ double mutant [6] , [7] , [51] . Interestingly , we found more extensive 3′ ssDNA in the absence of Rad9 in all the mutants tested , except the exo1Δ sgs1Δ rad9Δ triple mutant ( Figs . 3B , 3C and S3 ) . These results support the model that both the Exo1 and the Sgs1-dependent pathways cooperate to resect a DSB , and rule out the hypothesis that additional nuclease ( s ) may take over to process a DSB in the absence of Rad9 . However , we noticed that in the sae2Δ sgs1Δ rad9Δ triple mutant strain the appearance of ssDNA is slightly delayed compared to wild type and sae2Δ rad9Δ strains ( Figs . 3B and 3C ) . This result may suggest that the initiation of DSB resection is affected in sae2Δ sgs1Δ rad9Δ cells . To test more precisely DNA processing near a DSB we employed a quantitative PCR-based method [52] . In particular , by this procedure we determined if the RsaI restriction enzyme can cut the DNA at a specific site 150 bp from the HO-cut site , thus indicating whether DSB resection has already passed beyond this site , since , as resection proceeds , the RsaI site becomes single stranded and resistant to digestion , which results in a PCR fragment amplification ( see scheme in Fig . 3D ) . Thus , the rate of PCR fragment amplification , normalized to the efficiency of HO cutting , corresponds to the rate of resection [52] . We also tested with the same procedure another RsaI site 4800 bp from the HO cut site , as a control . Interestingly , we noticed a higher amount of un-resected DNA at 150 bp proximal the DSB site , between 60 and 180 minutes after the cut in nocodazole blocked sae2Δ and sae2Δ sgs1Δ rad9Δ triple mutant cells with respect to the wild type and sae2Δ rad9Δ mutant ( Fig . 3E ) . However , at later time points resection has efficiently passed beyond the RsaI site 4800 bp far from the HO cut site ( Fig . 3F ) , not only in the wild type and sae2Δ rad9Δ cells , but also in the sae2Δ sgs1Δ rad9Δ triple mutant cells , according to the visualization of the 3′ ssDNA formation by denaturing Southern blotting ( Figs . 3B and 3C ) . These studies revealed one striking unexpected result: although sae2Δ sgs1Δ rad9Δ triple mutant cells resect a DSB and expose an extended 3′ ssDNA ( Figs . 3B , 3E and 3F ) , they are severely compromised in DSB repair through SSA ( Figs . 2B and 2C ) , suggesting that the long-range resection is not the limiting step to repair a DSB in these cells , rather the defect is different from simply creating enough ssDNA to allow SSA to take place . Therefore , we hypothesize that an Sgs1-dependent mechanism contributes to efficiently initiate DSB processing in the absence of both Rad9 and Sae2 , and the kinetics of the initial step of resection would become somehow critical to complete the subsequent steps of the SSA repair . We then investigated whether the faster DSB end processing that we observed in sae2Δ rad9Δ cells would be associated with reduced NHEJ events , which are significantly elevated in the sae2Δ cells [53] . To this aim , we treated cells of JKM139 strains with nocodazole to block cell cycle in G2/M phase and we added galactose to induce one persistent DSB in each sister chromatid . Cells were kept in nocodazole for 2 hours to avoid potential interference caused by cell cycle transition , before plating in the presence of galactose . In this condition , the continued expression of HO leads to a recurrent cut of the MAT locus and precludes precise religation , until the sequence of the HO site is corrupted by deletion/addition of few bases and the ends are joined by imprecise NHEJ [54] . This is a relatively inefficient process in yeast , with a frequency of about 1-3×10−3 in wild type cells [54] . We found that the frequency of imprecise NHEJ events is increased in sae2Δ cells , in agreement with previous finding [53] , while it is slightly reduced in the absence of Rad9 . Interestingly , deletion of RAD9 reduces NHEJ events to wild type value in sae2Δ cells ( Fig . 3G ) . These results suggest that Rad9 plays a critical role to balance NHEJ and HR events in G2/M phase , likely acting at an early step of DSB processing , leading to increased NHEJ events in the absence of Sae2 . The delay in DSB resection in sae2Δ cells has been correlated with a prolonged Mre11 binding at the DSB site [42] , [55] . More recently , it was also shown that an Sgs1-dependent process can contribute to remove Mre11 from a DSB in sae2Δ cells , promoting DSB resection and repair through homologous recombination [56] . Therefore , we decided to investigate Mre11 binding near a DSB by a chromatin immunoprecipitation-after-crosslinking-protocol ( ChIP ) , followed by quantitative PCR ( qPCR ) , with primers specific for the DSB site . Contrary to wild type , rad9Δ or sgs1Δ cells , we found greater and persistent levels of Mre11 bound near DSB ends in sae2Δ cells ( Fig . 4A ) , supporting previous analysis of the Mre11 foci by microscopy [51] , [56] , and by ChIP [55] . Importantly , we found a decrease in fold enrichment of Mre11 binding to the DSB site in sae2Δ rad9Δ cells , but not in the sae2Δ sgs1Δ rad9Δ triple mutant cells ( Fig . 4B ) . These results suggest that the deletion of RAD9 gene promotes an Sgs1-dependent process to remove Mre11 from DSB ends in the absence of Sae2 , supporting and expanding recent findings [56] , and it may explain the high efficiency of SSA repair and viability of the sae2Δ rad9Δ that we showed in Figs . 1 and 2 . Moreover , the prolonged binding of Mre11 near the DSB further supports previous results in Fig . 3 , showing that short-range resection in the sae2Δ and sae2Δ sgs1Δ rad9Δ triple mutant cells is delayed . Since it is known that Mre11 persistence at a DSB limits the recruitment of Rad52 [4] , [57] , which is necessary to establish DNA end-tethering and HR pathways [58] , [59] , we investigated by immunofluorescence Rad52 loading onto one DSB in all the mutants described . We found that deletion of RAD9 totally restores Rad52 binding in sae2Δ cells through an Sgs1-dependent mechanism ( Fig . 4C ) . These results correlate with the analysis of Mre11 binding in these mutants ( Fig . 4B ) , and suggest that the limiting step to efficiently complete an SSA process in nocodazole-blocked sae2Δ and sae2Δ sgs1Δ rad9Δ cells is not the delay in DSB resection per se ( Figs . 3B and 3C ) , but rather the reduced binding of Rad52 . Rad52 is a critical factor to maintain DSB ends tethered to each other , which was suggested to be a relevant event in HR [42] , [58] , [59] , [60] , [61] . As we showed that the deletion of RAD9 allows Rad52 binding in sae2Δ cells ( Fig . 4C ) , we investigated whether it may also contribute to rescue DSB end-tethering defect in these cells . To this end , we took advantage of a specific yeast background in which the DNA proximal to the irreparable HO break could be visualized by binding of a LacI-GFP ( green fluorescent protein ) fusion protein to multiple repeats of the LacI repressor binding site , LacO . These arrays are integrated at a distance of 50 kb on either side of the HO cleavage site on chromosome VII [58] . Cultures of the original wild type and isogenic sae2Δ , sae2Δ rad9Δ and sae2Δ sgs1Δ rad9Δ derivative strains were arrested in mitosis and kept blocked by nocodazole treatment during break induction by galactose addition . After 2 hours to ensure HO cut formation , we observed two LacI-GFP spots in only 12 . 5%±2 . 1% of the wild type cells , and 11 . 0%±3 . 1% in sae2Δ rad9Δ mutant cells , thus indicating their ability to hold the broken DNA ends together . In contrast , 42 . 3%±3 . 8% of sae2Δ and 42 . 5%±4 . 8% of sae2Δ sgs1Δ rad9Δ cells showed two LacI-GFP spots , indicating a failure in DSB end-tethering ( Fig . 4D , and see also [42] , [62] ) . Therefore , we conclude that the deletion of RAD9 rescues both the Rad52 binding and DSB end-tethering in sae2Δ cells , contributing to efficiently repair a DSB through an SSA process that requires the resection of 25 kb of DNA between the repeats ( Fig . 2A ) . It was previously suggested that Rad9 limits DSB resection acting as a physical barrier toward the actions of nucleases , through a function distinct from its role in DNA damage checkpoint signalling [10] . Therefore , we sought to address if a checkpoint-independent function of Rad9 was involved to limit sae2Δ cells viability following one DSB . To this aim , we tested the chk1Δ rad53-K227A double mutant in the YMV80 background , in which the Rad53 kinase activity is dead and both the two checkpoint-signaling pathways acting downstream Rad9 are abrogated . By plating the cells in the presence of galactose to induce one HO cut , we found that the viability of the sae2Δ chk1Δ rad53-K227A triple mutant cells is reduced , similarly to sae2Δ cells ( Fig . 5A ) . This result indicates that signaling through Rad53 and/or Chk1 is not involved into the mechanism by which Rad9 limits SSA repair in sae2Δ cells . In order to further understand how Rad9 inhibits SSA repair in sae2Δ cells , we then investigated specific mutations that affect Rad9 binding to a DSB . It is known that Rad9 constitutively binds chromatin through the interaction between its TUDOR domain and the histone H3 methylated at the K79 by Dot1 [20] , [21] , [22] . In addition , Rad9 binds chromatin around a DSB site through the interaction of its BRCT domain with the histone H2A phosphorylated at the S129 ( γ-H2AX ) by upstream kinase Mec1 and Tel1 [23] . Further , Rad9 is recruited near a DNA lesion through the interaction with Dpb11 protein . In particular , Dpb11 binds the CDK1-dependent phosphorylated S462 and T474 Rad9 residues , reinforcing the Rad9 binding to damaged DNA and promoting Rad9 phosphorylation by Mec1 [25] . To test the contribution of the different pathways that mediate Rad9 binding to chromatin , we analysed the viability in the presence of HO-induced DSB of specific mutations that abrogate each of them in the YMV80 background . The deletion of DOT1 gene eliminates the H3K79 methyl transferase Dot1 protein , and greatly reduces the constitutive binding of Rad9 to chromatin [21] , [24] . As expected [36] , deletion of DOT1 leads to a faster long-range DSB resection in sae2Δ cells ( S4A and S4B Figs . ) . However , by the qPCR-based method , we found that the initial short-range resection is still delayed in these double mutant cells ( S4C Fig . ) , suggesting that the Dot1-dependent resection barrier may have a role only at distal region from the cut site . Indeed , by plating the YMV80 derivative cells in the presence of galactose to induce one DSB , we found that deletion of DOT1 gene does not rescue sae2Δ lethality ( Fig . 5A ) . Further , we deleted SAE2 gene in a strain that expresses the H2A-S129A histone variant , which is not phosphorylatable by Mec1 and Tel1 kinases and leads to a faster DSB resection [63] . We also deleted SAE2 gene in a strain that expresses the Rad9-S462A-T474A ( hereafter we refer to rad9-S462A-T474A as rad9-2A ) protein variant , which does not interact with Dpb11 [25] . Interestingly , both the failure to phosphorylate the H2A-S129 site and the rad9-2A mutation increase the viability of sae2Δ cells after one DSB , with the major contribution done by the mutation that abrogates the Rad9-Dpb11 interaction ( Fig . 5A ) . Taking all these genetic results together , we concluded that the recruitment of Rad9 near the DSB site , mediated by its interaction with Dpb11 and partially with γ-H2AX , limits sae2Δ cells viability when a DSB must be repaired by SSA . Consistently with our genetic evidence , we found an increased binding of Rad9 close to an irreparable DSB in sae2Δ cells by ChIP analysis ( Fig . 5B ) , which correlates with the increased binding of Mre11 ( Figs . 4A and 4B ) . Of note , the Rad9-2A protein variant does not bind near a break ( Fig . 5B ) , supporting the viability data of the sae2Δ rad9-2A double mutant cells following one DSB ( Fig . 5A ) . Moreover , Rad9 binding close to the break is only partially dependent on γ-H2AX and not by Dot1 ( S5 Fig . ) , in agreement with cell viability of the sae2Δ h2a-S129A and sae2Δ dot1Δ double mutants ( Fig . 5A ) . Then we tested if the capability of Rad9 to form oligomers at the DNA damage site [29] , [30] , [64] was involved in inhibiting sae2Δ cells viability following a DSB . To this aim , we introduced a plasmid vector that expresses either the rad9-7xA allele or the RAD9 gene as a control , by transformation into rad9Δ and sae2Δ rad9Δ YMV80 derivatives . The Rad9-7xA protein variant cannot be phosphorylated at critical sites by upstream Mec1 and Tel1 kinases ( see also Fig . 5C ) , and is unable to oligomerize [29] , [64] . After plating cells in the presence of galactose to induce one DSB , we found that the expression of the Rad9-7xA protein variant rescues the lethality of sae2Δ cells , contrary to the wild type Rad9 ( Fig . 5D ) . This result suggests that the oligomerization of Rad9 molecules is implicated in limiting SSA repair in sae2Δ cells . To further support this conclusion , we took advantage of the rad9-ΔBRCT-FKBP chimeric allele , which leads to the production of a truncated variant of Rad9 protein , in which the C-terminal BRCT domains are replaced with a FKBP tag [24] . It was shown that the Rad9-ΔBRCT-FKBP protein variant , which cannot form oligomers due to the absence of the BRCT domains , can dimerize in the presence of the small inducing molecule AP20187 , binds chromatin and partially transduces the checkpoint signal ( S6B Fig . and see also [24] ) . Consistent with our hypothesis , we found that the rad9-ΔBRCT-FKBP mutation does not rescue sae2Δ lethality in the presence of AP20187 , while the viability in the sae2Δ rad9-ΔBRCT-FKBP double mutant cells is almost identical to the wild type value ( Fig . 5E ) , further suggesting that the dimerization/oligomerization of Rad9 affects SSA repair .
It is now clear that DSB processing is a finely regulated process , which acts at the crossroad between HR and NHEJ recombination pathways . Indeed , as soon as a DSB is resected , homologous recombination pathways can be used to repair the break in lieu of NHEJ , with important implications for chromosome rearrangements and genome integrity . Similarly to what seen in higher eukaryotes , three distinct nucleases cooperate to resect a DSB in S . cerevisiae . According to a model recently proposed for meiotic DSBs [65] , Mre11 , activated by Sae2 [44] , introduces a nick near a DSB , triggering a bidirectional nucleolytic degradation of the 5′ strand: Exo1 and Dna2-Sgs1 resect the DNA in the 5′-to-3′ direction from the nick , while the Mre11 complex resects the DNA in the 3′-to-5′ direction toward the DSB ends . In G2/M blocked cells , it appears that the Exo1 and Dna2-Sgs1 pathways cannot actively resect a DSB starting from its ends , which are occupied by Ku70-Ku80 complex [1] . Indeed , it was suggested that the Mre11 activity might contribute to the removal of Ku complex , clearing the ends [2] , [3] , [11] , [65] , [66] . Importantly , in the absence of a functional Sae2 , the Mre11-dependent DSB processing is compromised , and Ku-dependent NHEJ events and translocations increased [62] . In addition , Mre11 and Rad52 binding are , respectively , increased and reduced in sae2Δ cells ( Fig . 4 , and see [4] , [57] ) , which are severely defective in repairing a DSB through SSA ( Fig . 2 , and see also [6] , [42] ) . Moreover , sae2Δ cells cannot keep the DSB ends tethered , which was shown to be relevant for DSB repair ( Fig . 4 , and see [42] , [58] , [60] ) . Here , we show that the deletion of the RAD9 gene suppresses all these phenotypes of sae2Δ cells . Indeed , we found that deletion of RAD9 leads to a faster 5′–3′ resection both through the Exo1 and Dna2-Sgs1 pathways , but the Dna2-Sgs1 pathway becomes essential , in the absence of Sae2 , to efficiently initiate DSB processing and repair through an SSA process that requires 25 kb DNA resection ( Figs . 2 and 3 ) . We also found elevated levels of Mre11 bound near an HO-induced break both in sae2Δ and sae2Δ sgs1Δ rad9Δ mutants , accordingly with a defect in Rad52 binding and DNA end-tethering ( Fig . 4 ) . The requirement of DSB end-tethering for SSA repair has never been explored before , however it is relevant to underline that Rad52 is important for end-tethering [58] , and also our results indicate that a defect in end-tethering is linked with a failure to accomplish SSA repair . Further investigation will be required to fully understand the interplay between SSA and end-tethering . Interestingly , recent findings underlined a role of exonuclease processing of a DSB in maintaining broken chromosome ends in close proximity [61] . Taken all these findings together , we suggest that the prolonged binding of Mre11 near the break site may represent the critical barrier to efficiently initiate DSB resection , load Rad52 and establish end-tethering in the absence of Sae2 , and it can be by-passed by a resection-based mechanism mediated by Sgs1-Dna2 in the absence of Rad9 . A similar role to remove Mre11 from a DSB site in sae2Δ cells was recently shown for Sgs1 , in the absence of Ku70-Ku80 complex [56] . Indeed , deletion of KU70 suppresses sae2Δ cells sensitivity to low doses of CPT and other DSB inducing agents [1] , [3] . Surprisingly , we did not see a rescue of sae2Δ cells lethality by deleting KU70 after a DSB that can be repaired through an SSA process between two homologous leu2 repeats 25kb far from each other , although deletion of RAD9 suppresses the sae2Δ ku70Δ double mutant ( S7 Fig . ) . One possibility is that Rad9 , bound near a DSB site , may limit the Sgs1-Dna2 activity starting from the break ends , leading to prolonged Mre11 binding . This might occur in cooperation with Ku complex , bound to the DSB ends , or rather it might represent a second distinct mechanism to limit DSB ends resection and DNA end-tethering . Alternatively , or in addition , Ku and Rad9 may limit DSB processing in different cell cycle phases . Indeed , the Ku complex acts on a DSB mainly in G1 , while Rad9 acts predominantly in G2/M phase [36] , [67] , [68] . Genetic and biochemical evidence in Fig . 5 suggest that Rad9 protein dimerization and/or oligomerization , together with Rad9 interactions with Dpb11 and partially with γ-H2AX , are important to limit short-range resection and repair in sae2Δ cells . Indeed , Dpb11 is recruited on to the DNA lesion through the interaction with the 9-1-1 complex [28] , and both the 9-1-1 complex and Dpb11 are recruited rapidly near a DSB site [69] , likely at the ssDNA-dsDNA junction [70] . It is possible that the interactions with γ-H2AX , as well as with the histone H3 methylated at Lys79 by Dot1 , become more important to recruit Rad9 in a distal region from the DSB site , contributing to slow down the long-range resection , which is not the limiting step in sae2Δ cells . This hypothesis is supported by the fact that DNA damage sensitivity of fun30Δ cells , that resect slower a DSB because of their inefficient Rad9 removal from chromatin flanking a DSB [37] , is partially rescued in the absence of γ-H2AX or Dot1 [37] , [63] . Of importance , deletion of DOT1 gene does not rescue sae2Δ cells ( Fig . 5A ) . Notably , although Rad9 binding close to the break is not particularly elevated in wild type cells , it is enriched in sae2Δ cells ( Fig . 5C ) . Consistent with our genetic evidence , Rad9 binding close to DNA ends depends on Dpb11 , partially on the histone γ-H2AX , but not on the histone H3 methylated at Lys79 by Dot1 ( Figs . 5B and S5 ) . Possibly , these data are in agreement with the low amount of modified histones detected in chromatin within 1–2 kb of the break [22] , [26] , [71] , [72] , [73] . Overall , our genetic and molecular results suggest a model shown in Fig . 6 , in which Rad9 , in addition to its known role in inhibiting long-range resection , may affect the initial short-range processing of an HO-induced DSB . In fact , Rad9 , once recruited close to a DSB end in G2 phase mainly through the interaction with Dpb11 , limits the Sgs1 dependent resection starting from DNA ends , whenever Mre11 is blocked near the DNA ends . In the future it will be interesting to investigate whether Rad9 plays a similar role in limiting rapid and coincident resection of dirty radiation-induced DSBs , in cells lacking Sae2 and/or Mre11 [74] . We believe that our findings might have important implications for understanding how the genome stability is preserved , especially in higher eukaryotes , whose genomes are enriched of repeats and SSA events can be particularly frequent . In fact , it becomes clear that too-efficient DSB resection can lead to an excessive initiation of homologous recombination and accumulation of toxic DNA intermediates and rearrangements between repeats [16] . Moreover , DSB resection may lead to highly error-prone alternative ends joining ( A-EJ ) and MMEJ events [14] , [16] . In this view , our results in yeast might help to understand recent finding in human cells at the molecular level , showing a role for 53BP1 in protecting from BLM and CtIP-Mre11 dependent A-EJ events and genome rearrangements [75] . Furthermore , our findings suggest that the functional interplay between 53BP1/Rad9 and Mre11 may also have a physiological relevance to protect from error-prone imprecise NHEJ events in genomic regions containing no repeats . It is also worth mentioning that the inactivation of 53BP1 was shown to potentiate homologous recombination and increase DNA damage tolerance of cancer-prone BRCA1 -/- cells [32] , [76] , [77] , [78] , with severe implications for therapeutic treatments . In conclusion , we show novel insights on the structural barrier induced by Rad9 , together with Dpb11 and γ-H2AX , to limit DSB processing and repair . The Sgs1-Dna2 pathway becomes essential to efficiently remove hypo-active Mre11 from a DSB site , in the absence of Sae2 and Rad9 , triggering DSB resection and repair . The efficient removal of Mre11 from the DSB site is essential not only to switch to the more processive long-range resection , but also to allow an efficient recruitment of the recombination factor Rad52 . This allows the maintenance of DSB end-tethering , which is an important prerequisite to complete repair , especially for those lesions that require extensive resection . These events increase in the absence of Rad9 and might contribute to accumulation of toxic HR events , leading to genome rearrangements and genetic instability .
All the strains listed in S1 Table are derivative of JKM139 , YMV80 and yJK40 . 6 . To construct strains standard genetic procedures of transformation and tetrad analysis were followed . Deletions and tag fusions were generated by the one-step PCR system [79] . For the indicated experiments , cells were grown in YP medium enriched with 2% glucose ( YEP+glu ) , raffinose 3% ( YEP+raf ) or raffinose 3% and galactose 2% ( YEP+raf+gal ) . All the synchronization experiments were performed at 28°C . DSB end resection in JKM139 derivative strains was analyzed on alkaline agarose gels using a single-stranded RNA probe as described previously [36] , [50] . TCA protein extract was prepared [80] and separated by SDS-PAGE . Western blotting was performed with anti-Rad53 ( EL7 ) , anti-HA ( 12CA5 ) , anti-Rad9 ( generously provided by N . F . Lowndes ) , and anti-actin using standard techniques . Repair of an HO-induced DSB in YMV80 background was analyzed by a Southern blotting procedure described previously [39] . YMV80 derivative strains were inoculated in YEP+raf , grown O/N at 28°C . The following day , cells were normalized and plated on YEP+raf and YEP+raf+gal . Plates were incubated at 28°C for three days . Viability results were obtained from the ratio between number of colonies on YEP+raf+gal and YEP+raf . Standard deviation was calculated on three independent experiments . JKM139 derivative strains were inoculated in YEP+raf , grown O/N at 28°C . The following day , after cell cycle block in G2/M by nocodazole , 2% galactose was added to one part of the culture to induce HO cut . After 2 hours of HO induction , cells were normalized and plated on YEP+raf and YEP+raf+gal . Plates were incubated at 28°C for three days . Viability results were obtained from the ratio between number of colonies on YEP+raf+gal and YEP+raf . Standard deviation was calculated on three independent experiments . ChIP analysis was performed as described previously [69] . Input and immunoprecipitated DNA were analysed by quantitative PCR using a Biorad MyIQ2 system or a Biorad CFX connect . The oligonucleotides used are listed in S2Table . Data are presented as fold enrichment at the HO cut site ( 0 . 15 or 4 . 8 kb from the DSB ) over that at the PRE1 locus on chromosome V , then normalized to the corresponding input sample . The obtained fold enrichment values were normalized to the fold enrichment of the t0 sample . Standard mean error ( SEM ) was calculated on three independent experiments . Quantitative PCR ( qPCR ) analysis of DSB resection was performed accordingly to [52] . The oligonucleotides used are listed in S2 Table . The DNA was digested with the RsaI restriction enzime ( NEB ) that cuts inside the amplicons at 0 . 15 kb and 4 . 8 kb from the DSB , but not in the PRE1 control region on chromosome V . qPCR was performed on both digested and undigested templates using StoS Quantitative Master Mix 2X SYBR Green ( Genespin ) with the Biorad MyIQ2 PCR system . The ssDNA percentage over total DNA was calculated using the following formula: % ssDNA = {100/[ ( 1+2ΔCt ) /2]}/f , in which ΔCt values are the difference in average cycles between digested template and undigested template of a given time point and f is the HO cut efficiency measured by Southern blot analysis . Cells of strains derivative from yJK40 . 6 background were grown in YEP+raf and blocked 3 hours in G2 with nocodazole . 160 µM CuSO4 was added one hour before inducing HO cut with galactose , accordingly to [58] . Samples taken at the indicated time were analysed with a fluorescence microscope . Cells with 2 LacI-GFP foci separated by more than 0 . 5 µm were considered defective in DSB end-tethering . | DNA double strand breaks ( DSBs ) are among the most deleterious types of damage occurring in the genome , as failure to repair these lesions through either non-homologous-end-joining ( NHEJ ) or homologous recombination ( HR ) leads to genetic instability . The 5′ strand of a DSB can be nucleolytically degraded by several nucleases and associated factors , including Mre11 , CtIP/Sae2 , Exo1 and Dna2 together with Bloom helicase/Sgs1 , through a finely regulated process called DSB resection . Once resection is initiated , error-prone NHEJ is prevented . Several findings suggest that DSB resection is a double-edged sword , if not finely regulated , since on one hand it is needed for faithful HR , but on the other it may lead to extensive DNA deletions associated with genome instability . Both in mammals and yeast , 53BP1/Rad9 protein binds near the lesion and counteracts the resection process , limiting the formation of ssDNA . By using S . cerevisiae as a model organism , here we show that Rad9 oligomers block the removal of hypo-active Mre11 protein from a persistent DSB , thus limiting initiation of resection and the recruitment of the recombination factor Rad52 , in the absence of Sae2 . Altogether , these findings pinpoint a critical role of 53BP1/Rad9 in balancing HR and NHEJ repair events throughout the cell cycle . | [
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"h... | 2015 | Functional Interplay between the 53BP1-Ortholog Rad9 and the Mre11 Complex Regulates Resection, End-Tethering and Repair of a Double-Strand Break |
More than 95% of the human population is infected with human herpesvirus-6 ( HHV-6 ) during early childhood and maintains latent HHV-6 genomes either in an extra-chromosomal form or as a chromosomally integrated HHV-6 ( ciHHV-6 ) . In addition , approximately 1% of humans are born with an inheritable form of ciHHV-6 integrated into the telomeres of chromosomes . Immunosuppression and stress conditions can reactivate latent HHV-6 replication , which is associated with clinical complications and even death . We have previously shown that Chlamydia trachomatis infection reactivates ciHHV-6 and induces the formation of extra-chromosomal viral DNA in ciHHV-6 cells . Here , we propose a model and provide experimental evidence for the mechanism of ciHHV-6 reactivation . Infection with Chlamydia induced a transient shortening of telomeric ends , which subsequently led to increased telomeric circle ( t-circle ) formation and incomplete reconstitution of circular viral genomes containing single viral direct repeat ( DR ) . Correspondingly , short t-circles containing parts of the HHV-6 DR were detected in cells from individuals with genetically inherited ciHHV-6 . Furthermore , telomere shortening induced in the absence of Chlamydia infection also caused circularization of ciHHV-6 , supporting a t-circle based mechanism for ciHHV-6 reactivation .
Human herpesvirus 6 ( HHV-6 ) is a ubiquitous pathogen with >90% seroprevalence in healthy adults . Although the process of viral latency is not completely understood , in some cases it is achieved by the integration of the viral genome into telomeric regions of host cell chromosomes ( ciHHV-6 ) [1] , and then subsequently vertically transmitted through the germ line [1]–[3] . Approximately 1% of the human population carries genetically inherited HHV-6 . After becoming latent , HHV-6 persists in a dormant state with minimal viral transcription or translation in human host cells and without the production of infectious virions and any detectable clinical complications . However , under various physiological conditions , latent HHV-6 is reactivated and forms infectious viral particles ( for further details see reviews [4]–[6] ) . Reactivated HHV-6 has been associated with various human diseases [7]–[10] . The ∼160 kb linear double-stranded genome of both species of HHV-6 ( HHV-6A and -6B ) is flanked by two distinct regions , ranging from 8 to 13 kb in length [11]–[13] , called direct repeats ( DR ) at the left ( DRL ) and the right ( DRR ) ends of the genome , respectively . Multiple passages of HHV-6 in the laboratory have led to the shortening of DR due to the deletion of specific regions in DRL and DRR [11] , [12] . Both the DR regions possess two well-defined stretches of telomeric repeats ( T1 and T2 ) . These repeat regions contain several copies of the sequence ( TTAGGG ) n , which are also found at the termini of linear eukaryotic chromosomes . The left end of each DR has short heterogeneous stretches of telomeric repeats ( DRL-T1 and DRR-T1 ) whereas the right end of both the DRs has a single long stretch of homogeneous telomeric repeats ( DRL-T2 and DRR-T2 ) . Several other herpesviruses including Marek's disease virus ( MDV ) and HHV-7 have a similar genome organization containing multiple stretches of telomeric repeats at both ends . Although chromosomal integration of HHV-7 has not been identified so far , it has been suggested that homologous recombination between viral telomeric repeats and human telomeres mediates the integration of HHV-6 [14] and MDV [15] into the host cell genome . The presence of telomeric repeats within the viral genome may have dual functions , required for both the integration ( to acquire latency ) and its excision ( to reactivate from latency ) [14] , [16] . However , the reactivation machinery and the exact mechanism for HHV-6 reactivation are currently unknown . We have previously shown that replication of the ciHHV-6 genome is efficiently reactivated in blood cells of patients that are infected with C . trachomatis without the formation of viral particles [17] . In this study , we have used Chlamydia infection as a model to understand the mechanism of ciHHV-6 reactivation . Our results provide strong evidence for the existence of a t-circle based mechanism for the circularization of the integrated viral genome , which is possibly independent of the viral infectious cycle .
The reproducible and strong reactivation of ciHHV-6 replication by Chlamydia suggests that chlamydial infection triggers the exit of the integrated virus from the host genome and the subsequent formation of circular viral DNA , which functions as a template for rolling circle replication . Since previous work has demonstrated that HHV-6 contains telomere-like sequences within its genome and it integrates within the telomeres of eukaryotic chromosomes we investigated the role of these sequences in ciHHV-6 reactivation . We devised a hypothesis for the reactivation mechanism based on the following considerations: ( 1 ) since telomeres are dynamic DNA structures , they are subject to reorganization by the telomere maintenance machinery [18] . Therefore , the HHV-6 reactivation may be a consequence of the direct changes of telomeres at chromosomal ends . ( 2 ) The reactivated HHV-6 must form a circular DNA to allow rolling circle replication . ( 3 ) The circular HHV-6 DNA must maintain at least one complete and reconstituted DR with the packaging signal sequences pac1 and pac2 . These sequences are required for the packaging and assembly of intact viral particles . ( 4 ) If the telomeric repeats mediate viral reactivation , excised extra-chromosomal HHV-6 should have variable telomeric-sequence lengths . Based on these considerations , we propose the model presented in Figure 1 as a basic mechanism for the formation of complete and reconstituted viral DNA . HHV-6 integrates into telomeric regions of human chromosomes possibly by homologous recombination [2] , [14] and in the process loses the distal end of the viral genome including the DRR- pac2 signal sequence essential for the packaging of viral DNA [2] , [16] ( Step 1; Figure 1 ) . During the cell cycle , telomeric repeats can be added to the end of chromosomes by the cellular telomerase complex containing the RNA subunit hTR and the catalytic subunit , hTERT . We therefore propose that the overhanging end ( step 1 , DRL; Figure 1 ) of ciHHV-6 will progressively shorten during subsequent cell divisions until the host telomerase complex is able to bind to the exposed heterogeneous viral telomeric repeats and add telomeric repeats to stabilize the chromosomal ends . This process should lead to the loss of the pac1 sequence from the DRL of the integrated viral genome ( Figure 1 ) . We hypothesize two ways by which the viral genome can subsequently be excised from the chromosome: ( i ) by homologous recombination within the integrated viral genome leading to circular viral DNA formation possibly mediated by the telomeric circle ( t-circle ) formation machinery of the host cell or ( ii ) by telomeric loop ( t-loop ) formation by branch migration and Holliday junction resolution ( See reviews [18]–[20] ) . T -circles are duplex or single-stranded extra-chromosomal DNA circles formed from telomeric repeat sequences at the ends of human chromosomes and play a key role in maintenance of telomeres [20] whereas t-loops are loop like structures , frequently found at telomeric ends of chromosomes , which stabilize the telomere through the formation of the multiprotein shelterin complex [18] . T-loop formation is frequently observed in many different cell types; whereas single homologous recombination events during alternate lengthening of telomeres is suggested to form circular DNA molecules ( t-circles ) in the absence of telomerase activity [21] , [22] . Since the extra-chromosomal HHV-6 DNA must be in a circular form for rolling circular replication , we considered both the t-circle and/or t-loop formation as possible mechanisms by which ciHHV-6 can form extra-chromosomal circular viral DNA . There are two major possibilities for the successful reconstitution of the circular viral genome . A homologous recombination event between DRL-T1 and DRR-T1 would lead to the formation of a circular viral genome with a fixed length of DR-T2 and the presence of an incomplete DRL in the human genome of reactivated cells . Alternatively , the left end of the DRL could be first removed by a shorter t-circle formation process ( Step 2 , Figure 1 ) , resulting in telomeric elongation of the chromosomal end from a homogenous telomeric repeat region of DRL ( DRL-T2 ) ( Step 3 , Figure 1 ) . A second t-circle formation between DRL-T2 ( Step 4 , Figure 1 ) and DRR-T2 would result in the excision of the whole viral genome from the chromosome thereby generating a circular viral genome with a single reconstituted DR ( Step 4 , Figure 1 ) . The circular viral genome can further undergo rolling circle amplification to form concatemeric viral DNA that can be cleaved to form linear double-stranded viral DNA molecules including two complete DRL and DRR sequences ( Step 5 , Figure 1 ) . Reactivation of ciHHV-6 from human telomeres may be initiated by structural changes at the chromosomal ends . To analyze whether chlamydial infection has any impact on chromosomal ends , changes in telomere length were measured by telomere restriction fragment analysis during C . trachomatis infection . This assay determines telomere lengths by digesting DNA with frequently cutting restriction enzymes that do not cleave within telomeric sequences . Interestingly , we observed strong telomere shortening between 24–36 h of Chlamydia infection in different cell types including wild type HeLa ( Figure 2A ) , HeLa229 ( Figure S1A ) and one of the ciHHV-6A cell lines ( HSB-ML ) ( Figures 2B ) , which was followed by partial repair of telomeric ends . The presence of any nonspecific DNA degradation during Chlamydia infection was excluded by control hybridizations ( Figure S1A ) . Termination of chlamydial infection by the addition of doxycycline , 24 h post infection , prevented telomere shortening indicating an active involvement of Chlamydia in this process ( Figures 2B , S1A ) . Interestingly , persistent Chlamydia , a viable but non-productive form of Chlamydia induced by addition of penicillin , inhibited telomere repair ( Figure 2C ) , suggesting that both telomere shortening and repair are actively induced by Chlamydia infection . The loss of telomeric sequences and subsequent defective telomere repair were also detected by fluorescent in situ hybridization ( FISH ) 48 h after Chlamydia infection ( Figure 2D ) , where several single chromatids in Chlamydia infected cells showed weak or no telomeric signal ( Figure 2D ) . To test if HHV-6 reactivation involves t-circle formation after Chlamydia infection , we applied neutral-neutral 2D DNA electrophoresis . This method enables the discrimination between linear and circular DNA of the same size ( Figure S1B ) due to their differential migration in agarose gels [23] . This unusual migration behavior of DNA can be further resolved by either increasing the voltage or agarose concentration . Based on this principle , DNA is separated in two different dimensions during 2D DNA electrophoresis , first according to mass and then according to shape . The method has been previously extensively used to study the organization of telomeric DNA [23]–[28] . Interestingly , we detected increased t-circle formation in primary human PBMCs ( Figure 2E ) as well as in HeLa cells ( Figure S1C ) after Chlamydia infection . Thus , our data provide strong evidence for changes in telomere length and increased t-circle formation during Chlamydia infection , which can contribute to ciHHV-6 excision from human telomeres and subsequent reactivation . The presence of well-defined stretches of telomeric repeats within the viral DR could potentially lead to the formation of t-circles of variable sizes thereby generating viral DNA containing telomeric repeats of differing lengths . To investigate the excision of viral genomes as a consequence of t-circle formation , we investigated two different viral reactivation scenarios . We have frequently observed viral integration into host cell chromosomes during productive infection of HSB-2 cells . These cells productively infected with HHV-6A ( Figure S2A ) contained a fraction of the replicating viruses integrating into the telomeres ( Figure S2B ) and therefore could serve as source for virus replication and reactivation . Alternatively , we selected HSB-ML cells , which in contrast harbor ciHHV-6A and undergo viral reactivation and formation of extra-chromosomal viral DNA upon infection with Chlamydia ( see Materials and Methods for details ) . To compare the length of tandem arrays of telomeric repeats , extra-chromosomal viral DNA was isolated from these cells using low melting DNA gel electrophoresis and then subjected to telomere restriction fragment analysis . In addition , S1 nuclease digests were used to monitor the amount of single-stranded nucleic acids in the isolated DNA . Differential lengths of telomeric repeats ranging from 0 . 25 to 2 kb in length were detected during productive HHV-6 infection in HSB-2 cells and in HSB-ML cells after virus reactivation ( Figure 3A ) . To check for the presence of multiple conformations of extra-chromosomal viral genomes , 2D DNA electrophoresis was performed with total DNA from HHV-6A-infected HSB-2 cells and ciHHV-6 HSB-ML cells reactivated by chlamydial infection . We detected circular HHV-6 DNA ( marked with a white arrowhead in Figure 3B ) in addition to the linear viral genome ( marked with a red arrowhead ) in HSB-2 cells , which co-hybridized with two different telomeric probes as well as with the HHV-6 specific probe ( Figure 3B ) . However , HSB-ML cells contained very low amounts of circular DNA upon reactivation by Chlamydia infection . In addition , we observed a distinct band of viral DNA that was smaller in size in both samples from the different cell-lines ( Figure 3B , blue arrow head ) , which may represent a shorter form of circular viral DNA . Full-length circular as well as linear double-stranded HHV-6 DNA was also detected in the total DNA isolated from primary PBMCs from one ciHHV-6 patient ( Figure 3C ) with ongoing natural viral reactivation at the time of blood sample collection . During further analysis , single-stranded circular HHV-6 DNA was detected in Chlamydia reactivated HSB-ML cells ( marked with yellow arrowhead in Figure S2C ) , whereas this form was hardly detectable in HHV-6A infected HSB-2 cells ( Figure S2C ) . Single-stranded circular viral DNA was clearly longer in size than the average telomeric circle in eukaryotic cells ( Figure S2C ) and was not present in control DNA samples ( Figure S2D ) . S1 nuclease treatment digested both forms of circular DNA ( Figure S2E ) thereby confirming the presence of nicked circular double-stranded and/or single-stranded circular viral DNA in HHV-6A-infected cells . To verify the presence of short t-circles in ciHHV-6A harboring HSB-ML cells , we gel purified DNA bands of approximately 10 kb in size ( verified for presence of HHV-6 by southern hybridization ) and performed TEM analysis . We observed mostly circular DNAs of varying sizes ( Figure 3D ) whereas control DNA preparations from uninfected HSB-2 cells ( HHV-6A negative ) did not contain any circular DNA . Thus , these results support our hypothesis that short t-circles carrying viral DR are formed in ciHHV-6 cells . The absence of homogeneous stretches of telomeric repeats at DRL-T1 suggested that telomere addition and chromosomal end maintenance might begin from the DRL-T2 region . Therefore , we expected the formation of shorter t-circles between telomeric repeats added to DRL-T1 and DRL-T2 ( Step 2 , Figure 1 ) . This process should generate a shorter DRL without most of the DRL ORFs . To test this hypothesis , we performed Southern hybridization analysis with total DNA from HSB-2 cells with both , chromosomally integrated HHV-6 and ongoing productive viral infection ( Figures S2A , S2B ) and from uninfected HSB-2 cells ( Figure S3A ) . Re-hybridization of the same blot with 2 different HHV-6 probes complementary to the two ends of the DRL as well as with a telomere specific probe confirmed the formation of short t-circles in these cells . DNA bands of the same length , detected by 2 different HHV-6 probes , could also originate from head-to-tail fused DNA concatemers . However , the length of head-to-tail fused concatemers should differ from those originating only from short t-circle formation ( described in detail in Figures S3B , S3C ) , supporting the hypothesis that frequent t-circle formation removes parts of the viral DRL leading to the generation of short circular DNA molecules containing viral DR . T-circle formation between DRL-T1 and DRL-T2 ( Step 2 , Figure 1 ) should result in chromosomal ends having overhanging DRL-T2 ( Step 3 , Figure 1 ) . To test this , we performed Southern hybridization analysis with total DNA from HHV-6 infected and uninfected HSB-2 cells and detected an approximately 950 bp fragment in infected HSB-2 cells with a probe hybridizing outside of the DRL that was not detected by a DR-specific probe ( Figures 4A , 4B ) . Interestingly , this band gave a poor telomeric hybridization signal , indicating the presence of an extremely short telomere at its left end . Similar restriction digestion and Southern hybridization experiment was carried out using total DNA from a haploid chronic myeloid cell line ( KBM-7 ) [29] , infected with HHV-6A , which allows productive virus infection ( Figure S4A ) . Viral DNA ending at DRL-T2 as well as different sizes of short t-circles were detected in these cells ( Figure 4C ) . Thus , the data suggest that part of the integrated HHV-6 DNA lacks DRL-T1 and contains a very short telomeric overhang starting at DRL-T2 . We detected distinct bands of short circular viral DNAs in HSB-2 cells with productive viral infection and in the Chlamydia infected HSB-ML cells ( Figure 3B , marked with blue arrowhead ) . These short circular DNAs did not hybridize with a probe located in the U1 region , outside the viral DR , demonstrating that these short t-circles do not contain viral DNA outside the DR . The size of these bands correlate with the shorter DNA fragments from gel purified extra-chromosomal DNA ( Figure 3A , marked with red arrowhead ) indicating that short circular DNA molecules containing HHV-6 DR ( Step 2 , Figure 1 ) are frequently present in these cells and can be detected by various methods . Since ciHHV-6 blood DNA samples cannot be assessed for the presence of short t-circles by Southern analysis due to an insufficient DNA yield , we used inverse PCR to test for the presence of short t-circles in total DNA from freshly isolated ciHHV-6 PBMCs as well as some of the previously described cell lines carrying ciHHV-6 ( detailed experimental approach is described in Figure S4 ) . We amplified fragments of different sizes ( Figures 4C ) , which were subsequently confirmed by southern hybridization using multiple probes and in part by sequencing to distinguish between short DRL-T1 and DRL-T2 containing t-circles ( see Text S1 ) . Variable lengths of telomeric repeats were detected in all the sequenced products , which did not show any major sequence differences within the viral DR . Our data indicate that shorter t-circle formation from ciHHV-6 DRL is a frequent event since several different sizes of short circular DNA containing partial DRL and its telomeric repeats were detected in all the cell types tested . Minor differences in the length of short t-circles were observed in the total DNA isolated before and after Chlamydia-mediated ciHHV-6 reactivation in HSB-ML cells and in one sample from ciHHV-6 PBMCs ( P4 ) ( Figure 4D ) . We detected several smaller amplification products using the HHV-6 probe 1 ( Figure 4D ) , which was not detected by telomere probes . This results from the generation of incomplete PCR products due to difficulties in amplification of DNA from within highly GC-rich telomeric repeat regions . Thus , these results confirm our hypothesis that short extra-chromosomal t-circle formation is a frequent event and it is not altered by the subsequent reactivation of the viral DNA . Validation of the final steps of the proposed model for HHV-6 reactivation required the detection of circular viral DNA with a single reconstituted DR ( Step 4 , Figure 1 ) . We used inverse PCR with an inverse primer pair ( table S1 ) located outside the DR ( Figure 5A ) to amplify circular viral DNA from several different cell types ( Figures 5A , B ) . Once again , variable lengths of telomeric repeats were observed in extra-chromosomal HHV-6 DNA from HSB-2 cells ( Figure 3A ) . Therefore , we size fractionated the full-length HHV-6A DNA from HSB-2 cells and used it separately for inverse PCR and subsequent Southern hybridization to determine the sequence composition of the different PCR fragments . We amplified circular HHV-6 DNA from HSB-2 cells as well as from one of the ciHHV-6 PBMCs ( P4 ) infected with C . trachomatis ( Figure 5B ) . In addition , PCR amplified DNA bands were gel purified , cloned and sequenced . Sequencing of PCR products confirmed the results of Southern analysis . The results clearly differentiated three distinct groups of DRs within these samples . We identified a fully reconstituted DR ∼9 . 7 kb in one fraction of total DNA from HSB-2 cells . Two other fractions contained a ∼8 kb smaller DR and one distinct fragment of ∼3 . 2 kb was detected in all the fractions of viral DNA from HSB-2 cells as well as in the total genomic DNA isolated after Chlamydia mediated reactivation of ciHHV-6 PBMC ( P4 ) . Interestingly , these fragments represented reconstituted short DRs , which lacked most of the DR ( DR1–DR7 ) ( Figure S5A ) . We also observed smaller incomplete DRs in HSB-2 cells that were not detected with probes located between DRL-T1 and DRL-T2 or the telomeric probe ( Figures S5B , S5C , S6 ) indicating recombination between DRL-T2 and DRR-T1 facilitated by short telomeric repeats . Sequencing reads of variable sizes of HHV-6 DNA containing a single DR confirmed two possible combinations for t-circle formation , either between DRL-T2 and DRR-T1 or between DRL-T2 and DRR-T2 resulting in reconstituted DRs . We observed strong variation in the size of the reconstituted DR-T1 ( Figure S6 ) . Interestingly , circular HHV-6 DNA with incomplete DR were observed in ciHHV-6 PBMC ( P4 ) only after Chlamydia infection , thereby confirming the viral DNA circularization event during chlamydial reactivation of ciHHV-6 . Even though circular DNA was present in Chlamydia reactivated HSB-ML cells ( Figure 3C ) , we could not detect any circular viral DNA by inverse PCR in these cells . This may be due to sequence variations in the primer-binding region or formation of a longer DR , which cannot be amplified in these PCR conditions . Mammalian telomeric TTAGGG repeats bind the key dimeric DNA binding protein telomere repeat binding factor-2 ( TRF2 ) , which plays a key role in maintaining telomere integrity [30] . A mutant of TRF2 with a deletion in the N-terminal basic domain ( TRF2ΔB ) has previously been shown to induce homologous recombination mediated t-loop formation and subsequent telomere loss [25] . To find experimental evidence for t-circle dependent ciHHV-6 reactivation , we over-expressed human TRF2ΔB ( Figure 6A ) in various cell types . As expected , TRF2ΔB over-expression induced telomere shortening in all the ciHHV-6 cell types tested ( Figure 6B ) and caused cell death within 5–7 days after lentivirus infection . Since TRF2ΔB is known to induce t-circle formation , we predicted that circularization of ciHHV-6 would be observed in these cells leading to circular extra-chromosomal viral DNA formation . Extra-chromosomal circular viral DNA with a single DR was detected by inverse PCR ( as described in Figure 5 ) and confirmed by Southern analysis using a HHV-6 specific probe ( Figure 6C ) . Control cells that did not undergo t-circle formation did not contain circular viral DNA molecules . In addition , fragments were purified , cloned and sequenced to verify the origin of the DNA . Thus , our results confirmed the involvement of the host cell t-circle formation machinery in ciHHV-6 reactivation .
Although reactivation of latent HHV-6 has implications in the progression of many diseases including MS and CFS [8] , [10] , [31] , the exact mechanism for latent HHV-6 reactivation , including that of ciHHV-6 , remains unknown . We recently described Chlamydia infection as a natural trigger to excise the ciHHV-6 genome from the host cell telomere . In this study , we have followed an experimental approach to understand the mechanism of ciHHV-6 reactivation . We found chromosomal integration of HHV-6A in HSB-2 cells during productive viral infection ( Figure S2B ) . Furthermore , we have previously reported the presence of ciHHV-6 in HeLa cells after HHV-6A infection [32] and other human cell lines have been generated carrying ciHHV-6 [2] , [16] . Bearing in mind that about 1% of humans carry genetically inherited HHV-6 , we propose that the integration of the HHV-6 genome into human chromosomes is a frequent event . Reactivation of these integrated HHV-6 sequences likely involves their excision from human chromosomes leading to the formation of extra-chromosomal HHV-6 genomes and subsequent replication . HHV-6 contains a potential origin of lytic replication site ( OriLyt ) within its linear viral genome [33] . However , a linear genome cannot function as a template for viral replication . Therefore , circularization of the genome is required for its continued replication . Although some evidence exists for head-to-tail fusion and circularization of HHV-6 during viral DNA replication [13] , [34] , this cannot explain the reactivation mechanism of ciHHV-6 . For example , head-to-tail end fused viral DNA would maintain the same viral genome size during productive infection with identical lengths of telomeric repeats ( DR-T2 ) within the viral genome . However , we observed viral DNA with varying lengths of telomeric repeats during viral replication ( Figures 3A , S5 , S6 ) corroborating similar results published from other laboratories [16] , [35] , [36] . As previously demonstrated [16] , [37] , we detected viral DNA with a single reconstituted DR ( Figure 5 ) , a DNA configuration that cannot originate from end fusion . Therefore , recombination events involving telomeric repeats within viral genomes are likely necessary for viral DNA circularization and subsequent replication . As HHV-6 integrates within the telomeric repeats located at the ends of human chromosomes , telomeric recombination events may facilitate the excision and circularization of integrated HHV-6 . Since C . trachomatis infection reactivates ciHHV-6 replication [17] , we investigated the effect of chlamydial infection on host cell telomere integrity . Cells infected with C . trachomatis experienced drastic telomere shortening ( Figures 2A , 2B , S1A ) and subsequent repair , which was dependent on the presence of viable and active bacteria , leading to increased t-circle formation . Changes in telomere length are frequently correlated with increased t-circle formation [25] , [26] , [38] , supporting the hypothesis that Chlamydia-mediated telomere alteration initiates circularization of ciHHV-6 . In line with this notion , single-stranded viral DNA was detected in Chlamydia-infected ciHHV-6 cells ( Figure S2C ) which is also consistent with the model since telomeric circle formation frequently leads to formation of single-stranded circular telomeric DNA [24] . In addition , we recapitulated ciHHV-6 circularization and viral genome reconstitution by t-circle formation and telomere shortening independent of Chlamydia infection by modulating telomeric protein complexes ( Figure 6C ) . Telomeres are regulated and maintained by the multiprotein shelterin complex , which includes TRF2 [18] . TRF2 plays a crucial role in preventing non-homologous end joining at the end of functional telomeres through the formation of t-loops , thereby protecting telomeres from potentially harmful deletions [18] . However , the deletion of the N-terminal basic domain of TRF2 ( TRF2ΔB ) enhances t-loop formation through t-loop homologous recombination [25] . We utilized these properties of TRF2ΔB to induce t-loop formation in ciHHV-6 cells and showed that enhanced t-loop formation led to weak but definite circularization of viral DNA ( Figure 6C ) . Our results thus provide direct evidence for the involvement of the telomere maintenance machinery in viral reactivation . It is a well-known phenomenon that HHV-6A and -6B produce high amounts of viral DNA during productive infection but the formation of infectious viral particles is inefficient [39] . We propose that the reactivation of ciHHV-6 from human telomeres is an incomplete process because of the high frequency of shorter t-circle formation that only rarely results in the successful reconstitution of a complete viral genome . Frequent loss of viral DNA between DR1–DR6 in laboratory strains of HHV-6 and packaging of incomplete HHV-6 DNA lacking parts of DR ( DR1–DR6 ) has been previously reported [39] . We have also detected loss of either most of the DR ( from DR1–DR8 ) or parts of the DR ( between DR1–DR7 ) in various cell types during ciHHV-6 reactivation ( Figures S5 , S6 ) . On the basis of these results , we propose that the infectious nature of HHV-6 genome may be independent of the completeness of the reconstituted circular viral genome corroborating with earlier reports showing the presence of incomplete DR in infectious viral particles [39] . Previous observations of the loss of identical lengths of DR from both ends of HHV-6 DNA [39] supports our model of HHV-6 replication from a circular DNA intermediate containing a single DR . Our results indicate a predominant role of DRL-T2 during viral circularization ( Figures S5 , S6 ) . This reinforces the idea that most of the left part of the viral DRL between pac2 and DRL-T2 is preferentially removed from the integrated viral genome thereby producing overhanging viral DNA ends at DRL-T2 ( Step 3 , Figure 1 ) , which can subsequently recombine with the telomeric repeats of DRR ( both DRR-T1 or DRR-T2 ) to form a reconstituted circular viral genome . The observation of DRL-T2 overhangs at the end of chromosome with frequent short telomeric repeats ( Figures 4B , 4C ) is in line with this hypothesis . Recent studies have utilized single telomere length analysis ( STELA ) assays to show similar short , unstable telomeric repeats at the sites of HHV-6 integration [16] , [40] . However , results obtained with STELA assays should be interpreted with caution since extra-chromosomal telomeric circle-encoded linear DNA containing parts of the viral DR may also be amplified by this technique . To our knowledge , this is the first report to show how the telomere maintenance machinery is exploited to reactivate a latent virus after a prolonged non-infectious state . The enormous prevalence of HHV-6 infection and the possibility of chromosomal integration of other common viruses such as HHV-7 , suggests that our data can form a basis to understand HHV-6 reactivation and the subsequent medical consequences for several million people worldwide .
For the study of latent ciHHV-6 activation , established ciHHV-6 cell line , HSB-ML ( a tetraploid T-cell line derived from HSB-2 cells with 2–5 copies of ciHHV-6 ) , JL-LCL and PL-LCL were kindly provided by the HHV-6 Foundation , USA ( www . hhv-6foundation . org/ , www . bioworldantibodies . com ) . Haploid chronic myeloid cell line KBM-7 [29] was a kind gift from Prof . Thijn R . Brummelkamp . Fresh blood samples from 5 individuals with ciHHV-6 were provided by the HHV-6 Foundation , USA . Viral load was re-verified by qPCR , which confirmed the ciHHV-6 status of these cells . Wild type HeLa ( ATCC CCL-2 ) , HeLa229 ( ATCC CCL-2 . 1 ) and HSB-2 [32] were grown in RPMI 1640 media and 5% fetal bovine serum ( FBS ) at 37°C and 5% CO2 . Fresh PBMCs were isolated as described previously [17] . The ciHHV-6 blood samples were collected under written informed consent under IRB# CI001-HHV-6 approved by The Essex Institutional Review Board Committee , USA . Cells were infected with C . trachomatis at a multiplicity of infection ( MOI ) of 1–5 as described previously [32] . Total DNA was extracted from whole blood samples using QIAamp DNA Blood Mini Kit ( Qiagen , Germany ) following the manufacturer's protocol . DNA extraction from all the cultured cells was done using DNAzol ( Invitrogen ) following manufacturer's protocol . In particular , all the experiments involving HHV-6 DNA analysis were carried out using DNA samples extracted with DNAzol as this method is non-invasive and maintain the genomic DNA in a non-shearing form . To study HHV-6 reactivation , ciHHV-6 cell lines and fresh blood samples from individuals with ciHHV-6 , were infected with C . trachomatis serovar L2 at an MOI of 1–5 . Chlamydial infection was monitored by phase contrast microscopy . After 2–3 days of infection , cells were grown in fresh media supplemented with 1 µg/ml of doxycycline , which allowed Chlamydia-infected cells to recover . For telomere length analysis , total DNA from HeLa229 cells was digested with MspI and HhaI , which do not cut telomeric DNA , for overnight and then separated on a 0 . 8% agarose gel . These gels were subsequently used for Southern hybridization . As a control , the same DNA samples were digested with HindIII and processed similarly . For Southern hybridization , agarose gels were incubated in 0 . 125M HCl for 8–10 min and then in DNA denaturation buffer ( 1 . 5M NaCl , 0 . 5M NaOH ) for 30 min . DNA was transferred to Nylon-XL membrane ( Amersham Hybond-XL , GE life sciences ) by capillary transfer using denaturation buffer for transfer . After transfer , membrane was washed with neutralization buffer ( 3M NaCl , 0 . 3M Tri-sodium citrate , 0 . 5M Tris , pH 8 . 0 ) for 15 min and was subsequently pre-incubated in hybridization buffer ( GE life sciences , USA ) . After 1 h of pre-incubation , either random primed probes ( GE life sciences , USA ) or end labeled probes ( Table S1 ) were added to the hybridization buffer and incubated overnight at 42°C . Membranes were washed and exposed overnight to phosphor storage screens ( Fujifilm ) , which were then scanned by Typhoon 9200 imager ( GE Healthcare ) . PCR amplified Ctr LcrH/SycD gene product of 136 bp was used for random priming and subsequent as probe . For HHV-6A probe 5 and 6 ( Figure 4C ) , PCR products were amplified using primer pairs described in Table S1 and were used for random priming . Separation of DNA in neutral–neutral 2D gels was performed as previously described [24] . Briefly , 8–10 µg of DNA was digested with appropriate enzymes and was first separated on 0 . 4% agarose at low voltage in 0 . 5× TBE , and the gel was stained with 0 . 3 µg/ml ethidium bromide . The lane was cut and placed on a clean gel support at 90° to the direction of the first electrophoresis , cast with 1 . 1% agarose containing 0 . 3 µg/ml ethidium bromide and run in 0 . 5× TBE . The first dimension was run overnight at 1 V/cm , and the second at 4 V/cm for 4 h , both at room temperature . Southern blot analyses were performed as described above . Total DNA containing HHV-6 DNA was separated using a 0 . 6% low melting agarose gel for overnight . After ethidium bromide staining , the desired bands were cut out and eluted using the phenol-chloroform extraction method . Viral DNA was purified from low melting agarose gel . Prolonged exposure to UV light was prevented in order to avoid any DNA break . For visualizing double-stranded DNA , purified DNA in TE-buffer was mixed with ammonium acetate and cytochrome c ( 50–200 ng DNA in 2–10 µl TE-buffer , 200 µl 0 . 2 M ammonium acetate , 0 . 8–2 . 0 µl of 1% cytochrome c [in distilled water] ) and 100 µl drops were placed on parafilm . After incubation for 20 min at room temperature , the cytochrome c coated DNA was picked up by touching collodion-coated grids to the surface of the drops . Grids were immediately stained with 5×10−5 M uranyl acetate in 90% ethanol or 30 sec , washed for 30 sec in 90% ethanol , air dried and metal coated with platinum/palladium by rotary shadowing under an angle of 5–7% . 100 ng of total genomic DNA was used to amplify short t-circles using a primer pair facing against each other ( see table S1 ) and Phusion high-fidelity master mix with GC buffer ( Thermo scientific ) . The following amplification cycles were used: Initial denaturation at 98°C for 2 minutes , 28 cycles of denaturation at 98°C for 30 seconds , primer annealing at 64°C for 30 seconds and primer extension at 72°C for 7 minutes . Final extension was done at 72°C for 30 minutes . Amplified PCR products were run on 1% agarose gel and were used for Southern hybridization . Amplified PCR products were cloned into TOPO 2 . 1 vector and sequenced using M13 forward and reverse primers . 100 ng of total genomic DNA was used to amplify circular or concatemeric HHV-6 DNA having a single direct repeat ( DR ) using a primer pair facing against each other ( see table S1 ) and LA Taq ( Takara Biosciences ) . Long PCR amplification was performed as follows: an initial cycle of denaturation at 92°C for 4 minutes was followed by 10 cycles of denaturation at 92°C for 10 seconds , primer annealing at 64°C for 30 seconds and primer extension at 68°C for 6 min , followed by 20 additional cycles under similar conditions except that the primer extension time was increased for 20 seconds per subsequent cycle . PCR was terminated with a final extension step for 30 minutes at 72°C . Amplified PCR products were run on 1% agarose gels and subjected to Southern hybridization . Amplified PCR products were cloned into TOPO 2 . 1 vector and sequenced using M13 forward and reverse primers . For inverse PCR in Figure 6C , a different primer pair ( For3 and Rev3 , see Table S1 ) was used . FISH and Co-FISH experiments were performed using the following protocol . Metaphase spreads were prepared after 2–3 hrs of colcemid treatment using standard cell biology techniques . For co-FISH , slides were hybridized with 2 different probes using previously described techniques [41] . For co-FISH with blood cells , PBMCs were stimulated for 72 h with 10 µg/mL PHA and then cultured in RPMI1640 media containing 100 units/mL IL-2 and 10% FCS . A custom designed Alexa-488 tagged PNA oligo probe ( Panagene , South Korea ) against HHV-6 ( Alexa488-OO-GCG TCA TAA TGC TCA ACA-CONH2 ) was used for FISH analysis using manufacturer's protocol . Alexa488-tagged Tel-G probes and Cy5-tagged Tel-C probe were purchased from Eurogentec , Germany ( Cat No . PN-TC055-005 , TG055-005 ) . For single chromatid telomere staining ( Figure 2D ) , HeLa cells were incubated with 5-bromo-2′-deoxyuridine ( BrdU ) and 5-bromo-2′-deoxycytidine ( BrdC ) . Newly synthesized DNA strands were subsequently digested with Exonuclease III . To validate the origin of extra-chromosomal HHV-6 DNA from the ciHHV-6 , we separated extra-chromosomal HHV-6 DNA from the chromosomal DNA by agarose gel electrophoresis . DNA from both the fractions were eluted and used for amplification of viral U94 ORF by PCR . Amplified DNA was cloned into TOPO 2 . 1 vector and sequenced . Constructs for TRF2 and TRF2ΔB overexpression [25] were obtained from Addgene , USA . Detailed protocol for lentivirus generation and infection are previous described [42] . Rabbit monoclonal TRF2 antibody was purchased from Abcam , UK ( Cat no . ab108997 ) . | Human herpesviruses ( HHVs ) can reside in a lifelong non-infectious state displaying limited activity in their host and protected from immune responses . One possible way by which HHV-6 achieves this state is by integrating into the telomeric ends of human chromosomes , which are highly repetitive sequences that protect the ends of chromosomes from damage . Various stress conditions can reactivate latent HHV-6 thus increasing the severity of multiple human disorders . Recently , we have identified Chlamydia infection as a natural cause of latent HHV-6 reactivation . Here , we have sought to elucidate the molecular mechanism of HHV-6 reactivation . HHV-6 efficiently utilizes the well-organized telomere maintenance machinery of the host cell to exit from its inactive state and initiate replication to form new viral DNA . We provide experimental evidence that the shortening of telomeres , as a consequence of interference with telomere maintenance , triggers the release of the integrated virus from the chromosome . Our data provide a mechanistic basis to understand HHV-6 reactivation scenarios , which in light of the high prevalence of HHV-6 infection and the possibility of chromosomal integration of other common viruses like HHV-7 have important medical consequences for several million people worldwide . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [] | 2013 | Reactivation of Chromosomally Integrated Human Herpesvirus-6 by Telomeric Circle Formation |
The genetic diversity of Trypanosoma cruzi , the etiological agent of Chagas disease , has been traditionally divided in two major groups , T . cruzi I and II , corresponding to discrete typing units TcI and TcII-VI under a recently proposed nomenclature . The two major groups of T . cruzi seem to differ in important biological characteristics , and are thus thought to represent a natural division relevant for epidemiological studies and development of prophylaxis . To understand the potential connection between the different manifestations of Chagas disease and variability of T . cruzi strains , it is essential to have a correct reconstruction of the evolutionary history of T . cruzi . Nucleotide sequences from 32 unlinked loci ( >26 Kilobases of aligned sequence ) were used to reconstruct the evolutionary history of strains representing the known genetic variability of T . cruzi . Thorough phylogenetic analyses show that the original classification of T . cruzi in two major lineages does not reflect its evolutionary history and that there is only strong evidence for one major and recent hybridization event in the history of this species . Furthermore , estimates of divergence times using Bayesian methods show that current extant lineages of T . cruzi diverged very recently , within the last 3 million years , and that the major hybridization event leading to hybrid lineages TcV and TcVI occurred less than 1 million years ago , well before the contact of T . cruzi with humans in South America . The described phylogenetic relationships among the six major genetic subdivisions of T . cruzi should serve as guidelines for targeted epidemiological and prophylaxis studies . We suggest that it is important to reconsider conclusions from previous studies that have attempted to uncover important biological differences between the two originally defined major lineages of T . cruzi especially if those conclusions were obtained from single or few strains .
Trypanosoma cruzi is the etiological agent of American Trypanosomiasis , also known as Chagas disease . Recent estimates suggest that about 15 million people in Latin America are infected with this parasite , and 12 to 20 thousand people die every year of the disease [1] . In nature , the parasite has two different cycles: a sylvatic cycle in which T . cruzi cycles between triatomines and wild mammalian reservoirs ( e . g . opossums , raccoons , armadillos ) , and a domestic cycle in which T . cruzi infects humans through domiciliated triatomines [2] , [3] . Since the 1980's the genetic variability and population structure of T . cruzi have been extensively characterized with a wide array of genetic markers [4] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , [14] . Three main conclusions have been drawn from these studies: 1 ) T . cruzi has a mainly clonal mode of reproduction [5] , [6] , [12] , although historical and experimental evidence of sporadic genetic exchange has been uncovered [9] , [10] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] . 2 ) The genetic variability of T . cruzi can be divided in two major groups [7] , [25] , [26] , [27] , [28] , [29] , originally termed T . cruzi I and T . cruzi II [30] . T . cruzi II was additionally divided in 5 distinct subgroups or stable discrete typing units ( DTUs IIa-IIe ) [8] , [31] . 3 ) DTUs IId and IIe are hybrids , the result of recent genetic exchange between ancestors of lineages IIb and IIc [10] , [19] . Although a new intraspecific nomenclature was recently proposed [32] , renaming the six major T . cruzi DTUs ( I , IIa-IIe ) as TcI-TcVI , no changes in the inferred division of T . cruzi in the two major evolutionary groups T . cruzi I ( DTU TcI ) and T . cruzi II ( DTUs TcII-VI ) ) were implied or proposed . The two major groups of T . cruzi seem to differ in important biological characteristics ( e . g . pathogenicity in mice , doubling time of epimastigotes in vivo , susceptibility to drugs ) , and thus are thought to represent a natural division relevant for epidemiological studies and development of prophylaxis [33] , [34] , [35] . For instance , in the southern region of South America , where Chagas disease is most devastating , it has been observed that T . cruzi II strains ( TcII-VI ) are usually responsible for human infections , whereas T . cruzi I strains ( TcI ) are usually associated with the sylvatic cycle [36] , [37] , [38] , [39] , [40] , [41] . Further , in regions north of the Amazon basin T . cruzi I strains are the main cause of Chagas disease , although the most acute manifestations of the disease are seemingly less common than in the southern cone of South America where most research on the disease has been conducted [22] , [38] , [42] . Thus , the current consensus is that T . cruzi II strains ( TcII-VI ) are more pathogenic to humans than T . cruzi I strains ( TcI ) , although at least one author has clearly stated that the six DTUs ( TcI-VI ) should be considered the only relevant units of analyses for epidemiology and clinical studies [14] . Although the division of T . cruzi in two major evolutionary lineages has become deeply rooted in the literature , even leading to a recent suggestion that they correspond to two different species [43] , there are strong reasons to doubt that this classification truly reflects the evolutionary history of this parasite . First , this classification is mostly based on codominant molecular markers ( e . g . allozymes , microsatellites , RAPDs ) , which are not as phylogenetically informative as nucleotide sequences . Second , most studies that have used nucleotide sequences have not used an outgroup species in the phylogenetic reconstruction [11] , [23] , [44] , [45] . That is a critical issue since the lack of outgroups does not allow for proper rooting of the tree and may lead to artificial evolutionary groupings . Further , with two exceptions [10] , [46] , the studies that have included outgroup sequences have failed to interpret the observed phylogenies in the context of the proposed division of T . cruzi in two major evolutionary groups . Third , in each of the few studies where outgroup sequences have been included , the two expected major monophyletic lineages corresponding to T . cruzi I ( TcI ) and II ( TcII-VI ) are not observed [10] , [12] , [18] , [19] , [46] , [47] , [48] , [49]; instead , the evidence suggests that T . cruzi II ( TcII-VI ) is not a natural group since it appears to be paraphyletic . To understand the diverse phenotypic differences among different T . cruzi strains and the potential connection between that variability and different manifestations of Chagas disease , it is essential to have a correct reconstruction of the evolutionary history of T . cruzi . A classification that represents evolutionary relationships is highly desirable because it may play an important role in strategic decisions about control and prophylaxis of Chagas disease . Here we present results from the largest sequence-based phylogenetic study of T . cruzi to date . We describe separate and combined phylogenetic analyses of nucleotide sequences from 31 nuclear genes and 1 mitochondrial region and provide estimates of the time of divergence of the main lineages of T . cruzi . We show that there is overwhelming evidence that T . cruzi II ( TcII-VI ) is not a natural evolutionary group but a paraphyletic lineage , and we provide a clear hypothesis of relationships among the six major DTUs of this parasite . Further , we estimate the time of diversification of T . cruzi strains and assess whether the sequence data is consistent with the two hybridization events that have been proposed for this species .
For every locus we collected sequences from Trypanosoma cruzi strains representing five of the six principal subgroups or discrete typing units ( DTUs ) of T . cruzi: TcI ( I ) , TcIV ( IIa ) , TcII ( IIb ) , TcIII ( IIc ) and TcV ( IId ) ( Table 1 ) [8] . Data from the sixth subgroup , TcVI ( IIe ) , was already available as part of the T . cruzi genome sequence ( www . genedb . org ) [50] . Additional T . cruzi strains were sequenced in 9 of the 29 newly amplified loci ( Tables 2 and S1 ) . Sequences were also collected from two closely related bat trypanosomes , T . cruzi marinkellei ( Strain N6 ) and T . vespertilionis ( Strain 593 ) , which were used as outgroups . All the strains used in this study have been widely characterized with a diverse array of genetic markers [6] , [8] , [9] , [10] , [18] . Purified DNA samples for all strains sequenced were provided by Michel Tibayrenc and Christian Barnabé from the Centre d'Etudes sur le Polymorphisme des Microorganismes ( CEPM ) , CNRS ( Montpellier , France ) . New sequence data was collected for 29 nuclear loci ( Table 2 ) . In addition , previously published data sets from one mitochondrial region ( COII-ND1 ) and two nuclear genes ( DHFR-TS , TR ) [10] , [18] were also included in the analyses , for a total of 32 loci . PCR primers were designed for 28 of the nuclear loci using Primer3 ( Table S2 ) [51]; primers for the intergenic region of Hsp70 were previously published [20] . Loci were selected using the published genome sequence of the CL Brener strain of Trypanosoma cruzi [50] . Annotated loci were randomly selected from the genome based on two criteria: 1 ) lack of paralogous copies in the genome to avoid amplification of non-orthologous genes , 2 ) presence of conserved regions between both CL Brener haplotypes ( if present ) that would allow the design of conserved primers . The nuclear loci are located in 19 of the 41 predicted chromosomes of T . cruzi based on a recent genome assembly [52] ( Table 2 ) . Six of the 32 loci did not have a putative homolog in T . brucei . Putative function information for each locus was obtained from GeneDB and by conducting a blastp search on the T . brucei predicted protein database in GeneDB . Conditions for the PCR amplifications were: 35 cycles of a 30 second denaturation step at 94°C , annealing at 56–60°C for 30 seconds , and extension at 72°C for 1 minute . PCR primers were used for bidirectional sequencing on a 3730xl DNA Analyzer ( Applied Biosystems ) . Sequences were edited using Sequencher ( GeneCodes ) . In cases where sequences had polymorphic nucleotides ( determined by the presence of multiple double peaks in the chromatogram ) , PCR fragments were cloned using the TA cloning kit ( Invitrogen ) and three to five cloned PCR fragments were sequenced to identify both haplotypes . Singleton mutations that were observed only in the sequences from cloned fragments and not in the sequences from the PCR products were not included in the final sequence of each haplotype used in the analyses . Sequences have been deposited in GenBank ( Accession Numbers HQ859465- HQ859886 ) . Sequences were manually aligned using SE-AL version 2 . 0 [53] . A Neighbor Joining ( NJ ) tree was reconstructed for each data set and each topology was used to estimate maximum likelihood parameters for different models of nucleotide substitution . The most appropriate nucleotide substitution model to analyze each locus was chosen using Modeltest 3 . 7 [54] . Maximum likelihood ( ML ) trees were individually obtained for each locus using ML heuristic searches in PAUP* 4 . 0b10 [55] using the tree bisection-reconnection ( TBR ) branch swapping algorithm . Bootstrap support values were obtained by ML analyses of 100 pseudoreplicates of each dataset . MrBayes 3 . 1 . 2 [56] , [57] was used to conduct Bayesian analyses using the substitution models chosen by Modeltest 3 . 7 [54] . We ran two independent simultaneous Markov Chain Mote Carlo runs with four chains each for 100 , 000 generations and sampled trees every 10 generations . If the standard deviation of split frequencies were not below 0 . 01 after analyses were done , the analyses were ran for an additional 100 , 000 generations and were stopped after convergence ( i . e . standard deviation of split frequencies ≤ 0 . 01 ) . Parameters and corresponding trees were summarized after discarding the initial 25% of each chain as burnin . Data from the 32 loci were concatenated ( 26 , 329 nucleotides per strain ) to reconstruct a consensus phylogenetic tree . Nuclear loci from the hybrid strains of T . cruzi , TcV ( IId ) and TcVI ( IIe ) , usually have two different haplotypes , one of which groups with TcII ( IIb ) and the other with TcIII ( IIc ) [10] , [18] . To analyze the concatenated data using haplotypes from the two hybrid strains included ( SO3 cl5 , CL Brener ) , we sorted each haplotype accordingly depending on the results from the ML and Bayesian phylogenetic analyses , concatenating haplotypes that had the same phylogenetic position ( i . e . that grouped with the same “parental” clade ) . The concatenated alignment was analyzed using ML methods as described above . Bayesian analyses were performed in MrBayes 3 . 1 . 2 as described above , for 100 million generations with two parallel searches , with a burnin of 10% of the generations [56] , [57] . To test the topological congruence among the gene trees , we used PAUP* 4 . 0b10 [55] to perform the incongruence length difference test ( ILD ) among all data sets [58] . In addition , the Shimodaira-Hasegawa congruency test [59] was performed on each dataset as well as in the concatenated dataset in order to compare the likelihood of the phylogeny obtained by ML and the likelihood of the tree when T . cruzi I and II ( TcI and TcII-VI ) are enforced to be monophyletic ( see Topology H , Figure 1 ) . This was done in order to assess the support of the current division of T . cruzi in two major phylogenetic groups . Non-neutral evolutionary patterns can affect inferences of phylogenetic relationships ( e . g . [60] ) . Therefore each locus was examined for evidence of positive selection acting across the complete sequence and among codon sites using the codeml application from the PAML package [61] . Pairs of nested models were compared using a likelihood ratio test ( LRT ) under the assumption that the LRT statistic follows a chi-square distribution with the number of degrees of freedom dependent on the estimated number of parameters differentiating the nested models . We compared three pairs of nested site models: 1 ) M1 ( neutral ) versus M2 ( selection ) ; 2 ) M7 ( beta ) versus M8 ( beta & ω ) ; 3 ) M8 versus M8a ( beta & ω = 1 ) [62] , [63] . Significance of the LRT of M1 vs M2 and M7 vs M8 was determined using 2 degrees of freedom . Since M8a is not fully nested on M8 , a strict LRT for these two models is not possible . However , it has been suggested that significance of the LRT can be determined by halving the p value from a chi-square test with 1 degree of freedom [61] . Likelihood Ratio Tests ( LRT ) were performed to evaluate the null hypothesis that each locus of the concatenated dataset evolved under a molecular clock [64] . The molecular clock was rejected in only 3 genes ( DHFR-TS , Tc00 . 1047053504059 . 20 , Tc00 . 1047053509561 . 20 ) ( Table S4 ) . The remaining 22 loci in which the molecular clock was not rejected , and that had a homolog in T . brucei , were concatenated for these analyses . Divergence dates were estimated using Bayesian analysis in BEAST v1 . 5 . 3 [65] . Both the strict and relaxed Lognormal clock models were used to estimate divergence times on the mitochondrial and the concatenated nuclear loci data sets . Analyses were run separately for nuclear and mitochondrial sequences since previous analyses gave very different estimates for each type of data [10] . All analyses were conducted without any topological constraints using the HKY substitution model with the gamma plus invariant sites as the site heterogeneity model , with 4 gamma categories , as well as partitioning of codons into 3 positions . All priors were set to default values , except for the divergence estimate between T . cruzi and T . brucei , which was set to 100 million years ago ( mya ) under a normal distribution with 10 mya as the standard deviation . This date ( 100 mya ) is a conservative estimate of the time to the last common ancestor of T . cruzi and T . brucei using the time of separation of Africa and South America [66] . Times of divergence were obtained by converging 10 independent Markov Chain Monte Carlo ( MCMC ) runs in Tracer v1 . 5 [65] in order to ensure convergence between the runs . Burnin of 20% of the samples was used . Each run had a chain length of 10 million , with sampling every 1000 chains . Although the mitochondrial data had been previously analyzed using a simpler method [10] , we decided to reanalyze them with the Bayesian framework described above to compare previous estimates with the new Bayesian estimates . The Relaxed Lognormal Clock model allows assessing how clock-like the data are ( i . e . whether there is large rate heterogeneity among lineages ) , by using the estimate of the ucld . stedv parameter . A value of 0 means that the data is reasonably clock-like , whereas a value much greater than 1 indicates that the data has considerable rate heterogeneity among lineages [67] . The nuclear data set had a ucld . stdev of 0 . 392 , while the mitochondrial data set had a higher ucld . stdev value ( 0 . 701 ) , indicating higher rate heterogeneity among lineages . However , the Relaxed Lognormal Clock model for the mitochondrial data set did not converge even after combining 10 independent runs in Tracer . Therefore the estimates of the mitochondrial data with this model were not reliable and are not presented . In addition , we analyzed T . cruzi genome sequence data [50] to obtain synonymous substitution ( Ks ) values for all annotated genes that had a single copy of each Esmeraldo-like ( TcII ( IIb ) ) and non-Esmeraldo-like ( TcIII ( IIc ) ) ortholog in the genome sequence . Our phylogenetic analyses ( see below ) show that nucleotide distances between Esmeraldo-like and non-Esmeraldo-like alleles from the heterozygous genome strain represent maximum distances within T . cruzi . Thus , those distances can be used to estimate the time to the most recent common ancestor of the major extant lineages of the parasite . A list of 4 , 568 Esmeraldo-like and non-Esmeraldo-like orthologs was obtained from Table S1 of El-Sayed et al [68] and sequences were downloaded from TriTrypDB ( tritrypdb . org ) . The orthologous sequences were pairwise-aligned using ClustalW [69] and the resulting alignments were passed to PAML for estimation of Ks using the codeml program with the pairwise distance estimation option ( runmode = -2 ) [61] . The average Ks value ( 0 . 0404 ) was used to estimate the time back to the most recent common ancestor of extant T . cruzi lineages using an estimate of the mutation rate for T . brucei [70] , [71] ( see Discussion ) .
The predominant clonal mode of propagation of T . cruzi and lack of evidence of intragenic recombination in the data ( not shown ) allow using nuclear gene sequences for reconstructing intraspecific phylogenies . The 31 nuclear loci we analyzed are randomly distributed in the genome . They are located in 19 of the 41 predicted chromosomes of T . cruzi , and when located on the same chromosome the loci are at least 30 Kb apart ( in most cases >100 Kb apart ) ( Table 2 ) . The ML and Bayesian phylogenetic analyses of each one of the 32 individual loci ( Figure S1 ) produced seven different topologies ( Figure 1 ) . The ILD partition test confirmed that at least one of these trees was significantly different from the others ( p = 0 . 01 ) . All 32 loci confirm the paraphyletic nature of T . cruzi II . Analyses of 24 of the 32 loci produced individual phylogenetic trees with the same topology ( topology A ) , including the three genes that we previously analyzed [10] , [18] ( Table 2 ) . Sequences from T . cruzi II strains were never monophyletic in any of the genes surveyed ( represented by Topology H ) . Topology A is consistent with a history of divergence in which T . cruzi II strains are paraphyletic . To test the validity of the division of T . cruzi in two major groups , we performed the Shimodaira-Hasegawa test on each gene tree [59] . The test was conducted to determine if a constrained topology representing the division of T . cruzi into two different reciprocally monophyletic lineages , T . cruzi I ( TcI ) and T . cruzi II ( TcII-VI ) , was as good an explanation of the data as the ML trees obtained for each gene . For every gene the constrained topologies in which T . cruzi I and T . cruzi II were reciprocally monophyletic were significantly worse than the ML phylogenies ( Table S3 ) , rejecting the prevalent idea that T . cruzi is divided in the two major evolutionary lineages T . cruzi I ( TcI ) and T . cruzi II ( TcII-VI ) . ML and Bayesian phylogenetic trees reconstructed with the concatenated multilocus dataset ( Figure 2 ) were also congruent with the ubiquitous topology A found on the majority of analyses of individual loci ( Figure 1 , Figure S1 ) . All internal nodes in this topology are strongly supported either by ML or Bayesian analyses ( Figure 2 ) . Moreover , a constrained phylogeny consistent with the current division of T . cruzi in two major reciprocally monophyletic groups is significantly worse than the best ML tree from the multilocus concatenated dataset ( p < 0 . 0001 ) . This result provides further evidence that the current division of T . cruzi in two major evolutionary lineages [30] is a classification that does not reflect evolutionary relationships among strains of T . cruzi . The basic relationships suggested by our analyses show that there are two major clades in the phylogeny of T . cruzi . The first clade , which harbors the most genetic diversity , includes DTUs TcI ( I ) , TcIV ( IIa ) , TcIII ( IIc ) , and one haplotype from each of the two hybrid DTUs TcV ( IId ) and TcVI ( IIe ) . The second lineage includes DTU TcII ( IIb ) and the other haplotype from each of the two hybrid DTUs TcV and TcVI . In 26 of the 32 nuclear loci analyzed we observed divergent allele sequences in members of both hybrid DTUs ( TcV , TcVI ) ( Figure 1: Topologies A , C ) , in 4 loci both hybrid DTUs were homozygous or had barely divergent alleles ( Figure 1: Topologies B , D , G ) , and in 2 loci one of the hybrid DTUs was homozygous while the other still had divergent alleles ( Figure 1: Topologies E , F ) . Consistent with previous analyses [10] , [19] , we only observe evidence of one major hybridization event during the history of T . cruzi: between the ancestors of DTUs TcII and TcIII to generate DTUs TcV and TcVI ( see Discussion ) . Only 8 of the 32 genes show evidence that some of their nucleotide sites have been under positive selection ( Table 3 ) . However , of these eight genes only four were highly significant in all three tests ( M1 vs M2 , M7 vs M8 , M8 vs M8a ) . Three of the genes were only significant at the 5% level , but not at the 1% level , and only significant when M8a was compared to M8 . The reconstructed phylogeny from 2 of the 8 genes that showed evidence of selection was different from the main topology A ( Tc00 . 1047053506529 . 310: Topology C; Tc00 . 1047053510765 . 50: Topology C ) , but in none of those two cases sequences from all T . cruzi II strains were monophyletic . The other six genes that showed evidence of positive selection produced topology A . These results show that the loci used in this study are mostly evolving neutrally ( 24 out of 32 loci ) and that phylogenetic analyses from 75% of the neutrally evolving loci ( 16 of 24 ) rendered the most common topology A ( Figures 1 and 2 ) , suggesting that results from the phylogenetic analyses have not been biased by loci that have been under positive selection . The Molecular clock was rejected on the concatenated dataset ( p<0 . 001 ) . Therefore , each individual locus was tested for the molecular clock and loci for which a homolog could be confidently identified in T . brucei and for which the Likelihood Ratio Test could not reject the Molecular clock ( 21 loci , Table S4 ) were chosen to become part of a concatenated dataset suitable to run the Bayesian divergence time analyses . The divergence estimates from the mitochondrial dataset differ significantly from the nuclear loci estimates ( Table 4 ) . The estimated time to the most recent common ancestor ( tMRCA ) using mitochondrial data suggest that T . cruzi's major lineages diverged during the Miocene ( tMRCA = 11 . 0 ( 7 . 0–15 . 2 ) mya ) , estimates that are similar to those presented by Machado and Ayala [10] using less sophisticated methods . On the other hand , the dates estimated with the concatenated data from 20 nuclear loci point towards a Pleistocene origin of T . cruzi ( tMRCA = 1 . 36 ( 1 . 0–1 . 7 ) mya ( strict ) ; tMRCA = 2 . 18 ( 0 . 9–3 . 7 ) mya ( relaxed ) ) ( Table 4 , Figures 3 and S2 ) . Those dates are more recent than previously estimated divergence times using a single locus ( TR: tMRCA = 3 . 91 mya ) [10] . We also obtained very similar divergence estimates from the concatenated data set of all nuclear loci that had a homolog in T . brucei ( 24 loci , Table S4 ) including genes that rejected the molecular clock hypothesis ( not shown ) . The discrepancy between the dates estimated with the mitochondrial and nuclear loci is likely the result of saturation of substitutions between the mitochondrial sequences of T . cruzi and the T . brucei outgroup used for the time calibration . Within T . cruzi the largest distance at silent sites ( Ks ) in the mitochondrial genes used is at least 6 times larger than that of any nuclear gene ( Table 3 ) , but most importantly substitutions at silent sites between T . cruzi and T . brucei are overly saturated ( Ks = 77 . 32 ) . This observation is not surprising given the large divergence time between the two species , but leads to an overestimation of divergence times in more recently diverged lineages . For that reason we will not discuss the mitochondrial estimates any further . The data allowed estimating the age of the major hybridization event in the history of T . cruzi: the generation of DTU's TcV and TcVI ( IId and IIe ) by hybridization of DTUs TcII and TcIII ( IIc and IIb ) . The time of this event was estimated using the observed divergences between alleles from the putative parental and hybrid lineages ( i . e . TcII vs TcV-TcVI and TcIII vs TcV-TcVI ) . This hybridization event occurred <1 mya , well before T . cruzi entered in contact with humans in South America , and the two independent estimates of the event are remarkably similar although the estimates from the strict clock model ( tMRCA = 0 . 49 ( 0 . 3–0 . 6 ) mya , 0 . 49 ( 0 . 3–0 . 6 ) mya ) are more recent than the estimates from the relaxed lognormal clock model ( tMRCA = 0 . 8 ( 0 . 3–1 . 4 ) mya , 0 . 73 ( 0 . 3–1 . 3 ) mya ) ( Table 4 , Figures 3 and S2 ) .
From the early 1990's T . cruzi was divided in two major groups , T . cruzi I and T . cruzi II [7] , [25] , [27] , [28] , [29] , [30] . One of the groups , T . cruzi II , was further divided into 5 stable Discrete Typing Units ( DTUs TcI-TcVI ) based on additional genetic data [8] , [31] , [32] . Our study aims to clarify the phylogenetic relationships among the currently defined six major DTUs and represents a comprehensive molecular phylogenetic analysis of the largest nucleotide sequence dataset collected for this parasite ( 26 , 329 nucleotides per strain ) . Although we focused the sequencing on the seven strains listed in Table 1 , for 10 of the 32 loci we obtained sequences from 20–48 strains ( Tables 2 and S1 ) . Results from the more deeply sampled loci are consistent with the overall results , and in particular there is no evidence of additional recombination/hybridization events ( see below ) . The predominantly clonal population structure of T . cruzi [5] , [6] , [12] justifies sampling a limited number of strains representing the six major lineages of this parasite . The strains that constitute the core of the data presented here are widely studied standard laboratory strains which have been consistently used to make inferences about genetic and biological variability in T . cruzi . There is no indication that those strains represent outliers within T . cruzi and as such they are useful for making inferences about major evolutionary events in this parasite . The concatenated phylogeny ( Figure 2 ) is well supported and its topology is consistent with results from previous analyses of smaller sequence datasets that used outgroup sequences [10] , [46] . Furthermore , it corresponds to the most commonly reconstructed topology using single loci ( Topology A , Figure 1 ) . This phylogeny shows that T . cruzi is divided in two clearly defined clades that do not correspond to the two originally defined major lineages T . cruzi I and T . cruzi II . Results from Shimodaira-Hasegawa tests applied to every locus ( Table S3 ) provide strong evidence that the previously defined lineage T . cruzi II is paraphyletic and therefore does not represent a natural evolutionary lineage . One of the clades of the concatenated phylogeny includes TcI , TcIII , TcIV and one of the haplotypes from each of the two hybrid lineages TcV and TcVI . The other clade includes TcII and the alternative haplotypes from hybrid lineages TcV and TcVI . The phylogenetic placement of DTU TcIV ( IIa ) is less well resolved than the position of the other lineages . Although the bootstrap support of the branch separating TcIV from the TcI-TcIII-TcV-TcVI clade is 72% in the concatenated tree , the phylogenetic position of TcIV is quite variable in the individual trees ( Figure S1 ) . In 11 of the 24 trees consistent with Topology A ( Figure 1 ) the placement of TcIV is the same as in the concatenated phylogeny and is supported with bootstrap values >55% ( >80% in 5 trees ) . It is likely that the most sensible approach to attain full resolution of the phylogenetic position of TcIV is to increase the number of loci sampled . The availability of genome sequences of additional T . cruzi strains ( e . g . [72] ) should help resolve this issue . Our results show that the classification of T . cruzi in two major evolutionary lineages [30] , which has become deeply rooted in the literature , does not reflect the evolutionary history of this species . This classification arose from analyses of codominant molecular markers ( e . g . allozymes , microsatellites , RAPDs ) and PCR fragment sizes of different regions of rRNA genes and a mini-exon [7] , [25] , [26] , [27] , [28] , [29] , and appeared to be consistent with results from phylogenetic analyses of small nucleotide sequence datasets [11] , [23] , [44] , [45] . However , none of those analyses included data from outgroups , a critical issue since lack of data from outgroup taxa does not allow for proper rooting of phylogenies and can generate artificial evolutionary groupings . Data from outgroups allow differentiating between derived ( apomorphic ) and ancestral ( plesiomorphic ) characters , which is fundamental for conducting proper phylogenetic analyses [73] . In our locus by locus analyses using outgroup data we never obtained topology H ( Figure 1 , Table 2 ) , which corresponds to the phylogeny in which all T . cruzi II strains ( TcII-VI ) are monophyletic as suggested by the two group classification of T . cruzi . However , when we conducted the same analyses for every locus removing the outgroup sequences and rooting the tree at the longest internal branch ( midpoint rooting ) , topology H was reconstructed 4 times ( Table 3 ) . Furthermore , in those analyses without outgroup we observed a different tree reconstructed in 15 of the 32 genes analyzed ( Table 3 ) . Those results suggest that the lack of outgroups in previous phylogenetic analyses of T . cruzi could be partially responsible for the original partition of the genetic diversity of this species in two major lineages . The observation of distinct PCR fragment sizes in different regions of rRNA genes or mini-exon sequences [7] , [27] , [28] , [29] was instrumental for the original division of T . cruzi in two major groups . Our phylogenetic results show that those studies simply uncovered derived character states in T . cruzi I ( TcI ) strains for the molecular traits studied , but the uncovered similarities in traits across strains do not correspond to actual evolutionary relationships among the strains . Presence-absence morphological or molecular characters can be useful for finding similarities among organisms but their utility for inferring evolutionary relationships is limited when the number of characters is very small and there is no additional supporting information . Without the context of a supported phylogeny it is not possible to determine if the observed character similarity truly reflects shared ancestry or homoplasy , as evidenced by the spurious relationships first described for T . cruzi . Our calculations point towards a Pleistocene origin of the extant lineages of T . cruzi ( tMRCA = 1 . 36 ( 1 . 0–1 . 7 ) mya ( strict ) ; tMRCA = 2 . 18 ( 0 . 9–3 . 7 ) mya ( relaxed ) ) ( Table 4 , Figures 3 and S2 ) . Furthermore , the major hybridization event that led to the origin of DTU's TcV and TcVI ( IId and IIe ) by hybridization of DTUs TcII and TcIII ( IIc and IIb ) occurred <1 mya , well before T . cruzi entered in contact with humans in South America . Estimated divergence times are dependent on the available calibration point ( s ) , which in this study was the estimated separation time of Africa and South America ( ∼100 mya ) based on geological evidence [66] . That date is thought to be the last time T . cruzi and T . brucei shared a common ancestor [74] , [75] . Older divergence estimates for all the clades in the phylogeny can be obtained if older separation dates of Africa and South America are considered . However , obtaining estimates of T . cruzi divergence time as old as those suggested in other studies ( e . g . 37–88 mya ) [76] , [77] requires using unrealistic calibration dates . Even if there are uncertainties about the calibration point , the estimated recent divergence of T . cruzi is consistent with the small nucleotide divergences observed among the different lineages ( Table 3 ) and leads to reasonable estimates of substitution rates in T . cruzi . The estimated silent site substitution rates per year ( 8 . 4–5 . 2×10−9 ) based on the average silent site divergence in T . cruzi ( Ks = 0 . 0228 ) and the estimated divergence times using nuclear loci ( Table 4 ) fall within the range of silent site substitution rates estimated for other organisms [71] , [78] . Further , independent estimates of the age of divergence of T . cruzi can be obtained using estimates of the nucleotide substitution rate per million year ( my ) and the observed average divergence at silent sites [79] . Using the estimated mutation rate in T . brucei ( 1 . 65×10∼9 per generation ) [71] and its generation time ( 7–10 generations/year ) [80] , we obtain an estimate of the neutral mutation rate of 0 . 0115–0 . 0165 per my . Using that substitution rate and the observed average silent site divergence for 4569 single copy heterozygous genes from the T . cruzi genome ( Ks = 0 . 0404 ) , the tMRCA of T . cruzi is estimated to be 1 . 73–1 . 21 mya , consistent with the phylogeny-based estimates obtained using BEAST ( Table 4 ) . The recent divergence dates are also consistent with the idea that the diversification of T . cruzi was linked to the origin of its blood-sucking triatomine vectors , which occurred in the last 5 my [81] , [82] . Molecular clock calibrations using cytochrome b sequences suggest a Pleistocene origin of Rhodnius prolixus and R . robustus [83] , and the observation of almost identical transposable elements in R . prolixus and opossums and squirrel monkeys suggest a very recent association of vector and hosts [84] . Previous studies have established that hybridization events have played an important role during the diversification of this parasite [10] , [11] , [19] , [23] , [85] . Two different scenarios involving hybridization events have been proposed to explain the current genetic structure of T . cruzi . The first scenario proposes that a recent single hybridization event took place between the ancestors of DTU's TcII ( IIb ) and TcIII ( IIc ) , which generated hybrid DTUs TcV ( IId ) and TcVI ( IIe ) [10] , [11] . The second scenario proposes that in addition to the recent hybridization event responsible for hybrid DTUs TcV and TcVI , there was an ancestral hybridization event between the ancestors of DTUs TcI ( I ) and TcII that gave rise to the ancestors of DTUs TcIV ( IIa ) and TcIII [23] , [85] . Our results provide additional evidence supporting the single recent hybridization event leading to the evolution of hybrid DTUs TcV ( IId ) and TcVI ( IIe ) [10] , [11] , [19] . The main evidence is the presence of multiple heterozygous loci with divergent alleles , where the alleles have close genetic distances to alleles from the putative parental lineages TcII ( IIb ) and TcIII ( IIc ) . This pattern was first observed in several nuclear genes [10] , [19] and later observed across thousands of genes in the genome sequence of T . cruzi strain CL Brener ( TcVI ) [50] . In this study we observed this pattern in 26 out of the 32 nuclear loci analyzed ( Figure 1 , Topologies A and C ) . More importantly , we did not observe any additional putative hybridization events that could be identified from loci with multiple polymorphic nucleotide sites . Our estimates of the age of the hybridization event suggest that this hybridization occurred less than 1 mya ( Table 4 , Figures 3 and S2 ) , consistent with the observation that the alleles from the hybrid lineages have few nucleotide differences with the alleles from the putative parental lineages . The ancestral hybridization event previously proposed [23] , [85] requires the heterozygosity from the ancestral hybrid lineage to be lost through genome-wide homogenization by homologous recombination or gene conversion , given that the extant DTUs TcIV ( IIa ) and TcIII ( IIc ) show widespread homozygosity . This scenario suggests that the homogenization process should have left clear signals of the ancestral hybridization in patterns of SNP variation , which should show mixed signals of phylogenetic affinity to either one of the parental lineages . Unfortunately , two missing key factors in the original phylogenetic analyses conducted to support the ancestral hybridization event [23] have likely contributed to misinterpreting the data . The first and most important factor is the lack of outgroup sequences in the phylogenetic analyses . Our study shows that failure to include outgroup sequences can alter phylogenetic reconstruction in T . cruzi ( Table 3 ) . The second factor is the lack of bootstrap support values on key nodes of the trees that support the ancestral hybridization scenario . We question the evidence for the ancestral hybridization scenario on three grounds . First , the origin of DTUs TcIII ( IIc ) and TcIV ( IIa ) is fairly recent , only about twice as old as the recent hybridization event leading to the origin of hybrid DTUs TcV ( IId ) and TcVI ( IIe ) ( Table 4 , Figures 3 and S2 ) . It is therefore difficult to explain why there is still so much widespread allelic heterozygosity left in the hybrid DTUs TcV and TcVI , while there is ( potentially ) none left in DTUs TcIII and TcIV . For instance , the sequence of the genome strain CL Brener ( TcVI ) contains over 30 Mb of combined contig size in non-repetitive heterozygous regions and only 2 Mb in homozygous regions ( see Table S2 from [50] ) . Given that pattern , it is clear that the proposed homogenization process that led to widespread loss of heterozygosity in the ancestor of DTUs TcIII and TcIV needs to be very different ( at least in speed ) than the process currently occurring in the recent hybrid strains . Second , the suggestion that DTUs TcIII and TcIV show mosaic sequences with SNPs that match DTUs TcI ( I ) or TcII ( IIb ) [23] , [85] is hard to reconcile with patterns observed in our data , in data from a recent study [46] , and in the sequenced strain of T . cruzi . To our knowledge there are no examples of obvious mosaic sequences in CL Brener , and , more importantly , the presence of interspersed SNPs matching either of the putative parental lines in small sequenced regions ( ∼1–2 Kb ) will require fairly high rates of recombination which are not consistent with what is observed in the genome strain or in sequences from the hybrid strains . Third , a prediction of the ancestral hybridization scenario is that one should observe mixed phylogenetic signals across different loci [23]: in some loci , alleles from DTUs TcIV and TcIII will show strong phylogenetic affinities with alleles from DTU TcI , and in other loci with alleles from DTU TcII; other loci would show little phylogenetic resolution if they are mosaics from both ancestral parental lineages . Here , we have shown that there is overwhelming support ( i . e . strong phylogenetic signal ) linking alleles from DTUs TcIII and TcIV with alleles from DTU TcI ( Figure 1 , topology A ) , and in no case did we observe strong support for a link of DTUs TcIII and TcIV with alleles from DTU TcII ( Figure 1 , topology H; Table S3 ) . To explain this pattern under the ancestral hybridization scenario one would also need to propose an additional mechanism whereby during homogenization there was gene conversion biased towards the allele from DTU TcI . Interestingly , the genome sequence of T . cruzi shows an excess of TcII-like homozygous regions relative to TcI-like homozygous regions ( see Table S2 from [50] ) , contrary to the biased gene conversion towards TcI alleles required to explain our data under the ancestral hybridization scenario . As the most appropriate explanation should be the most parsimonious , we suggest that the scenario requiring a single hybridization event leading to the generation of the extant hybrids DTUs TcV ( IId ) and TcVI ( IIe ) is the only one that is currently strongly supported by data . The analysis of complete genome sequences from multiple lineages of T . cruzi should provide a definitive test of the ancestral hybridization scenario , but it is telling that analyses of the large number of randomly selected loci presented here are not consistent with predictions from that hypothesis . We have reconstructed the evolutionary history of the major lineages of the human parasite Trypanosoma cruzi using nucleotide sequences from one mitochondrial region and 31 unlinked nuclear loci . Our results show that the original classification of T . cruzi in two major groups , T . cruzi I ( TcI ) and T . cruzi II ( TcII-VI ) , does not reflect the evolutionary history of the parasite , that its diversification into the current extant lineages was recent ( <1–3 mya ) , and that there is only strong evidence for one major hybridization event that occurred <1 mya , well before T . cruzi entered in contact with humans in South America . It is possible that by sampling a small number of strains one could miss detecting rare recombination or hybridization events ( although we did not see this in loci that were more deeply sampled ) . Thus , future multilocus phylogenetic studies should also attempt conducting more in-depth sampling of strains . Based on our results we suggest that it is important to reconsider conclusions from previous studies that have attempted to uncover important biological differences between the two originally defined major lineages of T . cruzi . Conclusions from studies that report results of analyses from one or few strains that do not encompass all the genetic variability of the artificial group “T . cruzi II” should be carefully dissected to determine if the findings do in fact reflect fundamental biological differences between the natural group “T . cruzi I” and the artificial group “T . cruzi II” or simply reflect differences among the specific DTUs studied . A thorough review of the literature suggests that many of the studies that report differences , or lack thereof , between the two originally defined lineages of this parasite are typically based on observations from very few strains ( Flores-López and Machado , in prep . ) . Future work should focus on trying to determine if , as previously suggested [14] , the currently defined six major lineages of this parasite ( TcI-TcVI ) , for which we now have well supported evolutionary relationships , do indeed represent independent relevant groups for epidemiological studies and development of prophylaxis . | Trypanosoma cruzi is the protozoan parasite that causes Chagas disease , a major health problem in Latin America . The genetic diversity of this parasite has been traditionally divided in two major groups: T . cruzi I and II , which can be further divided in six major genetic subdivisions ( subgroups TcI-TcVI ) . T . cruzi I and II seem to differ in important biological characteristics , and are thought to represent a natural division relevant for epidemiological studies and development of prophylaxis . Having a correct reconstruction of the evolutionary history of T . cruzi is essential for understanding the potential connection between the genetic and phenotypic variability of T . cruzi with the different manifestations of Chagas disease . Here we present results from a comprehensive phylogenetic analysis of T . cruzi using more than 26 Kb of aligned sequence data . We show strong evidence that T . cruzi II ( TcII-VI ) is not a natural evolutionary group but a paraphyletic lineage and that all major lineages of T . cruzi evolved recently ( <3 million years ago [mya] ) . Furthermore , the sequence data is consistent with one major hybridization event having occurred in this species recently ( < 1 mya ) but well before T . cruzi entered in contact with humans in South America . | [
"Abstract",
"Introduction",
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] | [
"genetics",
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"biology",
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] | 2011 | Analyses of 32 Loci Clarify Phylogenetic Relationships among Trypanosoma cruzi Lineages and Support a Single Hybridization prior to Human Contact |
Regulator of G-protein signaling ( RGS ) proteins primarily function as GTPase-accelerating proteins ( GAPs ) to promote GTP hydrolysis of Gα subunits , thereby regulating G-protein mediated signal transduction . RGS proteins could also contain additional domains such as GoLoco to inhibit GDP dissociation . The rice blast fungus Magnaporthe oryzae encodes eight RGS and RGS-like proteins ( MoRgs1 to MoRgs8 ) that have shared and distinct functions in growth , appressorium formation and pathogenicity . Interestingly , MoRgs7 and MoRgs8 contain a C-terminal seven-transmembrane domain ( 7-TM ) motif typical of G-protein coupled receptor ( GPCR ) proteins , in addition to the conserved RGS domain . We found that MoRgs7 , but not MoRgs8 , couples with Gα MoMagA to undergo endocytic transport from the plasma membrane to the endosome upon sensing of surface hydrophobicity . We also found that MoRgs7 can interact with hydrophobic surfaces via a hydrophobic interaction , leading to the perception of environmental hydrophobiccues . Moreover , we found that MoRgs7-MoMagA endocytosis is regulated by actin patch-associated protein MoCrn1 , linking it to cAMP signaling . Our studies provided evidence suggesting that MoRgs7 could also function in a GPCR-like manner to sense environmental signals and it , together with additional proteins of diverse functions , promotes cAMP signaling required for developmental processes underlying appressorium function and pathogenicity .
In the rice blast fungus Magnaporthe oryzae , the appressorium is a special infection structure produced by the fungus to penetrate the host plant . Appressorium formation and function depend on signal transduction pathways , including G protein-coupled receptors ( GPCRs ) /G protein-mediated cAMP signaling [1 , 2] . Once extracellular surface cues are sensed by GPCRs , such as the non-canonical GPCR Pth11 at the plasma membrane ( PM ) , the GPCR stimulates the specific G-protein Gα subunit for activating the cAMP signaling pathway [2] . M . oryzae contains three distinct Gα subunits ( MoMagA , MoMagB , and MoMagC ) [3 , 4] and other conserved pathway components , such as adenylate cyclase MoMac1 , cAMP-dependent protein kinase A catalytic subunits MoCpkA , and MoCpk2 [1 , 5–7] . Together , they regulate not only growth but also appressorium formation and pathogenesis . In addition , M . oryzae contains at least eight RGS ( regulator of G-protein signaling ) and RGS-like proteins ( MoRgs1 to MoRgs8 ) . Previous studies found that all these RGS proteins have certain regulatory functions in various aspects of growth and pathogenicity with MoRgs1 , MoRgs2 , MoRgs3 , MoRgs4 , MoRgs6 , and MoRgs7 being mainly involved in appressorium formation and MoRgs1 , MoRgs3 , MoRgs4 , and MoRgs7 in full virulence [3 , 8] . Despite such understandings , detailed mechanisms associated with specific RGS proteins remain not fully understood . In particular , RGS-like MoRgs7 and MoRgs8 proteins that also contain a seven-transmembrane domain ( 7-TM ) ‚which is a hallmark of GPCRs important in signal perception and transduction . In eukaryotes , GPCRs are well known for their role as heterotrimer ligand-regulated guanine-nucleotide exchange factors ( GEFs ) [9] . A ligand/agonist binding to a GPCR activates GPCR and promotes GPCR to mediate the exchange of GTP on the Gα subunit of the heterotrimer , leading to Gα dissociation from the Gβ-Gγ and activation of G protein-mediated signal transduction pathway , including the cAMP signaling pathway . In plant pathogenic fungi and oomycetes , it is generally considered that GPCRs have functions in perception of the environmental cues . This function enables plant pathogens to coordinate their metabolism with environment and to develop infection structures [10–12] , although how these GPCRs detect environmental cues remains not clear . Previous studies have found that RGS proteins such as human Rgs14 contain a C-terminal GoLoco/G protein regulatory motif that exhibits an in vitro GDP-dissociation inhibitor for Gα ( i ) [13] . Since MoRgs7 or MoRgs8 contain the 7-TM domain , we were interested in revealing whether MoRgs7 or MoRgs8 has additional functions mimicking a GPCR . Here we found that MoRgs7 , but not MoRgs8 , is involved in a distinct regulating mechanism . MoRgs7 couples with MoMagA to undergo endocytosis that is triggered by sensing surface hydrophobicity . Interestingly , MoRgs7 can sense environmental hydrophobic cues through interacting with the hydrophobic surface . In addition , MoRgs7 endocytosis depends on the actin-binding coronin homologue protein MoCrn1 . Together , they contribute to G-protein/cAMP signaling required for appressorium function and pathogenicity .
Despite containing a relatively conserved RGS/RGS-like domain , 8 RGS proteins of the blast fungus are structurally divergent [8] . MoRgs7 and MoRgs8 , in particular , contain a long C-terminus domain that was analyzed by transmembrane domain prediction systems ( http://mendel . imp . univie . ac . at/sat/DAS/DAS and www . cbs . dtu . dk/services/TMHMM ) to have a GPCR-like 7-TM motif ( S1 and S2A Figs ) . MoRgs7 was demonstrated to have a role in appressorium function and pathogenicity , and this role is dependent on the 7-TM domain [8 , 14] . To dissect the roles of MoRgs7 domains , the RGS domain was deleted ( S2A Fig ) and the mutant allele containing the 7-TM was fused to GFP and expressed in the ΔMorgs7 mutant . The fusion proteins MoRgs7Δ7-TM:GFP and MoRgs7:GFP [14] were also expressed in the ΔMorgs7 mutant as a control . Analytical results showed that the ΔMorgs7 mutant expressing 7-TM:GFP still remained a relatively high cAMP concentration , similar to the ΔMorgs7 mutant [8] but not the wild-type strain ( S2B Fig ) . In hydrophobic surfaces , about 8% of ΔMorgs7 conidia improperly generated two appressoria ( S2C Fig ) , which could also be observed in the ΔMorgs7/7-TM strain ( S2C Fig ) . The ΔMorgs7/7-TM strain was also attenuated in virulence , similar to the ΔMorgs7 mutant ( S2D and S2E Fig ) . In contrast , the expression of MoRgs7-GFP was able to suppress most of the defects in the ΔMorgs7 strain . These tests showed that the 7-TM and RGS domains are important for MoRgs7 function in cAMP and virulence . However , the test failed to establish an independent role of the 7-TM . MoMagA plays a major role in cAMP signaling , appressorium formation and pathogenesis in M . oryzae and it is also one of the three Gα subunits demonstrated to interact with MoRgs7 [8] . To investigate functional mechanisms of MoRgs7-MoMagA interaction , we first validated the interaction through co-immunoprecipitation ( co-IP ) . In addition to MoMagA , the constitutively active form of MoMagA , MoMagAG187S [3] was also included in the test . The result showed that MoRgs7 can interact with both MoMagA and MoMagAG187S and that the 7-TM and the RGS domain both can interact with MoMagA ( Fig 1A and 1B ) . Since GPCRs undergo endocytosis for receptor recycling [15] , and both of MoRgs7 and MoMagA were localized to late endosomes that are the main components of the endocytic pathway , we hypothesized that MoRgs7 and MoMagA may also undergo actin-dependent endocytosis . To test this , we employed actin polymerization inhibitor latrunculin B ( LatB ) to disrupt endocytosis as previously described [16 , 17] . At 3 h post-inoculation , MoRgs7:RFP and MoMagA:RFP signals remained very strong at the PM of the germ tube , in contrast to DMSO control ( Fig 1C and 1D ) . Given that 4-bromobenzaldehyde N-2 , 6-dimethylphenyl ( EGA ) inhibits early to late endosome transport [18] , it was applied and that led to an appearance of MoRgs7 and MoMagARFP signals in MoRab5:GFP-labeled early endosomes in germ tubes , in contrast to DMSO control ( Fig 1E and 1F ) . Without EGA treatment , MoRgs7:RFP was predominantly localized to Rab7:GFP-labeled late endosomes ( Fig 1E ) . These co-localizations of proteins with endosomes were corroborated by Pearson correlation coefficient statistical analysis . Taken together , MoRgs7 and MoMagA movement follows the common endocytic pathway . To further validate MoRgs7 and MoMagA endocytosis , we photobleached MoRgs7 and MoMagA fluorescence in late endosomes of the germ tubes on hydrophobic surfaces and examined the fluorescence recovery dynamic using Fluorescence Recovery After Photobleaching ( FRAP ) at 3 h post-inoculation . In addition , we applied the microtubule-destabilizing benomyl to inhibit endosome trafficking via microtubuleand cycloheximide to inhibit newly synthesized fluorescent proteins moving into endosomes [19] . We found that endocytosis promotes recovery of RFP fluorescence of MoRgs7 and MoMagA in late endosomes within 90 sec ( Fig 2A and 2B ) . Furthermore , we used FRAP to bleach the fluorescence in endosomes in the germ tube on the hydrophilic surfaces at 3 h post-inoculation . The recovery of fluorescence of MoRgs7:RFP and MoMagA:RFP in the endosomes was rarely detected ( Fig 2A and 2B ) , suggesting that MoRgs7 and MoMagA are rarely internalized through endocytosis upon the perception of the hydrophilic surface . Intriguingly , the absence of MoRgs7 and MoMagA endocytosis on the hydrophilic surface did not couple with accumulation of MoRgs7:RFP or MoMagA:RFP signals at the PM of the germ tubes ( Fig 2C and 2D ) . As treating germinated conidia with LatB on hydrophilic surfaces for 1 h still could not cause accumulation of RFP signals at the PM ( Fig 2C and 2D ) , we thus reasoned that in response to exposure to hydrophilic cues MoRgs7 and MoMagA were rarely sent to the PM from intracellular systems . MoRgs8 also contains a 7-TM domain . To examine whether MoRgs8 undergoes similar endocytosis , we expressed MoRgs8:GFP in Guy11 and observed MoRgs8 localization during appressorium development on the hydrophobic surface . However , MoRgs8:GFP was found to be evenly distributed in the cytoplasm of germ tubes ( Fig 3A ) . When compared with MoRgs7:GFP ( Fig 3B ) , MoRgs8:GFP did not display any obvious endosome-localization patterns in the germ tubes . Further , LatB failed to cause any effects to MoRgs8:GFP distribution ( Fig 3A ) . In contrast , the MoRgs7:GFP signal was enhanced at the PM in response to LatB ( Fig 3B ) . These results revealed that MoRgs8 may function differently from MoRgs7 . Since the above results showed that the hydrophobic surface , not the hydrophilic surface , induces the PM localization of MoRgs7 in germ tubes during appressorium development , we hypothesized that MoRgs7 is possibly involved in sensing hydrophobic surfaces and the 7-TM may have a role in this process . We hypothesized that MoRgs7 at the PM may attach to hydrophobic surfaces in a hydrophobic interactive manner , and formation of such interactions by PM proteins including MoRgs7 is a step in the perception of hydrophobic cues . To test this hypothesis , we first examined whether MoRgs7 has the ability to bind to hydrophobic materials by performing an affinity precipitation assay with phenyl-agarose gel beads . The phenyl groups attached to the beads are highly hydrophobic . The beads were then incubated with MoRgs7:GFP and the GFP protein ( a negative control ) , respectively , in a high concentration of salt solution containing 1 . 5 M NaCl and 1 . 5 M MgSO4 . This allowed proteins to bind to the beads , as at high salt concentration non-polar side chains on the surface upon protein can interact with the hydrophobic groups [20] . Then we washed the beads to remove unbound proteins using a series of aqueous solutions with different salt concentrations . If an intense hydrophobic interaction between the protein and phenyl groups was formed , the protein will be hardly removable from beads even by low salt concentration solution containing 0 . 3 M NaCl and 0 . 3 MMgSO4 , or containing 0 . 2 M NaCl and 0 . 2 M MgSO4 . After washing , we used Western-blot analysis to detect the amount of MoRgs7:GFP or GFP that remained bound to beads . The results indicated that MoRgs7:GFP , but not GFP , remained in the elution ( Fig 4A ) . This suggested that MoRgs7 has astrong ability to interact with hydrophobic materials and this ability may allow MoRgs7 to mediate a hydrophobic interaction between the pathogen and the hydrophobic surface . In addition , the hydrophobicity of 7-TM of MoRgs7 was tested and found to have hydrophobicity as full-length MoRgs7 ( Fig 4A ) , and deletion of 7-TM decreased the level of hydrophobicity of MoRgs7 , suggesting that this 7-TM is critical for hydrophobicity of MoRgs7 . The results also indicated that MoRgs8 has a weak hydrophobicity compared to MoRgs7 despite having a 7-TM , suggesting that the characteristic of 7-TM is varied from MoRgs7 to MoRgs8 . We then investigated whether MoRgs7 forming a hydrophobic interaction with hydrophobic surfaces is an approach of M . oryzae to detect hydrophobic cues . Given that urea and ethylene glycol can interrupt hydrophobic interactions by causing a disordering of water molecules on hydrophobic regions [21 , 22] , they were applied to germinating conidia on hydrophobic surfaces at 1 h-post inoculation when most of conidia only germinated with a germ tube . In the presence of 0 . 5 M ethylene glycol or 0 . 1 M urea , appressorium formation was about 50% lower than that of water treatment at 4 h post-inoculation , even though almost 80% of conidia developed appressorium at 10 h post-inoculation ( Fig 4B and 4C ) . Moreover , in the presence of 1 M ethylene glycol or 0 . 8 M urea , less than 20% of conidia developed appressoria even at 10 h post-inoculation . Most of conidia only germinated germ tubes with or without swelling at terminals . These results implied that a successful hydrophobic interaction formation is a critical step in hydrophobic surface recognition by M . oryzae . To examine the nature of MoRgs7-MoMagA endocytosis and whether MoRgs7 internalization is dependent on MoMagA , we determined the rate of MoRgs7 internalization in the wild-type strain Guy11 and the ΔMomagA mutant using FRAP analysis . We found that MoRgs7 internalization had a normal rate in the ΔMomagA as that in Guy11 ( S3A and S3B Fig ) . In addition , the internalization rate of MoMagA was also the same in Guy11 and the ΔMorgs7 strain ( S3C and S3D Fig ) . These results suggested that MoRgs7 and MoMagA do not depend on each other in internalization . To further understand the endocytosis process of MoRgs7 , we searched for additional protein partners of MoRgs7 through a yeast two-hybrid ( Y2H ) screening and identified a coronin protein homolog , MoCrn1 , as two polypeptides of 148 and 273 amino acids , from a cDNA library in the pGADT7 vector . MoRgs7 cDNA was inserted into pGBKT7 as bait . The interaction between MoCrn1 and MoRgs7 was specific , as an interaction between MoCrn1 and other RGS proteins , including MoRgs1 , MoRgs3 and MoRgs4 , cannot be established ( Fig 5A ) . The interaction was further validated by co-IP and bimolecular fluorescence complementation ( BiFC ) . The co-IP assay indicated that both the 7-TM and the RGS domains could interact with MoCrn1 , independently ( Fig 5B and 5C ) . BiFC revealed that MoCrn1 interacts with MoRgs7 during appressorium development ( Fig 5D ) . The YFP signal could be detected at the PM of germ tubes while some weak signals appeared in the cytoplasm ( Fig 5D ) , suggesting that the interaction is more often to occur at the PM . To investigate the interaction at the PM of germ tubes , we further conducted co-localization assay with co-expression of MoCrn1:GFP and MoRgs7:RFP in Guy11 . And their co-localization at the PM in germ tubes of conidia on the hydrophobic surface was examined at 3 h post-inoculation ( S6A Fig ) . However , we failed to detect the co-localization at the PM in germ tubes because the small amount of PM-localized MoRgs7:RFP is present ( S6A Fig ) , as shown above ( Fig 1C ) . MoCrn1:GFP formed actin patches-like structures , as described for coronin in Neurospora crassa [23] . But , from a small number of conidia , slightly obvious PM-localized MoRgs7:RFP was observed in germ tubes and partly co-localized with MoCrn1 patches ( S6A Fig ) . The co-localization result suggested that a small amount of PM-localized MoRgs7 indeed has the opportunity to interact with MoCrn1 . In the eukaryotic cells , coronin proteins act as F-actin binding proteins and regulate actin-related processes such as membrane trafficking [24] . We tested whether MoCrn1 associates with actin in M . oryzae using Lifeact , a living cell actin marker described previously [17 , 25 , 26] . The MoCrn1:GFP and Lifeact:RFP were co-expressed in Guy11 and co-localization of MoCrn1:GFP and Lifeact:RFP was examined under a confocal microscope . We observed that MoCrn1:GFP and actin were dispersed in nascent appressoria after 6 h of incubation ( S5A Fig ) , and that MoCrn1 punctate patches were localized to the membrane . However , MoCrn1:GFP formed ring-like structures in mature appressoria , which were highly co-localized with the F-actin network at the center of mature appressoria ( S5A Fig ) . We also observed that MoCrn1:GFP were co-localized with actin at sub-apical collar region of hyphae andactin patches in hyphae andconidia ( S5A Fig ) . The interaction between MoCrn1 and F-actin was again demonstrated through Y2H and binding assays ( S5B and S5C Fig ) . We next investigated whether MoCrn1 affects the actin organization by generating a ΔMocrn1 mutant , in which MoCRN1 gene knock-out was validated by Southern-blot ( S4 Fig ) , and expressing Lifeact:RFP in the ΔMocrn1 mutant and Guy11 . In Guy11 , the hyphal tip regions were occupied with many actin patches that are associated with the PM ( S5D Fig ) . However , about 20% of the hyphae formed some abnormal , enlarged actin patches in the cytoplasm of ΔMocrn1 ( S5D Fig ) . Also , the enlarged actin patches could be found in over 10% of ΔMocrn1 conidia ( S5E Fig ) , likely due to actin aggregation . Moreover , we found that Guy11 formed normal ring-like actin structure at the base of 80% appressoria , compared to 72% in ΔMocrn1 that displayed a disorganized actin network . This observation was confirmed by line-scan analysis ( S5F Fig ) . Thus , we concluded that MoCrn1 regulates actin assembly and the ΔMocrn1 mutant displays minor defects in actin structures . In the budding yeast Saccharomyces cerevisiae , Crn1 interacts with the microtubule [27] . The Δcrn1 mutant cells as well as cells overexpressing Crn1 showed microtubule defects and the mutant Δcrn1 is more sensitive than wild type strains to benomyl [28] . To determine whether MoCrn1 also affects the microtubule , the pYES2 construct containing the full-length MoCrn1 cDNA was expressed in the yeast Δcrn1 mutant . On SD plates containing 10 , 20 , and 30 μg/ml benomyl , Δcrn1 exhibited most significant inhibition in growth compared to the wild type strain BY4741 ( S5G Fig ) . However , there was no significant difference between the Δcrn1 strain expressing MoCRN1 and BY4741 . Further , we examined Guy11 , the ΔMocrn1 mutant , and the complemented strain for benomyl resistance . On CM plates with 10 , 20 and 30 μg/ml benomyl , we found that ΔMocrn1 was less sensitive to benomyl than Guy11 and the complemented strain ( S5H Fig ) . Together , these results suggested that MoCrn1 has conserved microtubule-related functions . As MoCrn1 interacts with MoRgs7 and is localized to the PM associated actin patches that represent endocytic pits [29] , we hypothesized that MoCrn1 may function as an adaptor protein to direct MoRgs7 to endocytic pits/vesicles for internalization during appressorium development . To prove this , we investigated whether MoCrn1 affects MoRgs7 endocytosis by observing the spatial distribution of MoRgs7:RFP in germinated conidiaonthe hydrophobic surface at 3 h post-inoculation . Despite of that endosome-localized MoRgs7 was found in both the ΔMocrn1 mutant and Guy11 , the ΔMocrn1 mutant displayed a higher concentration of MoRgs7:RFP at the PM of the germ tube than Guy11 did ( Fig 6A ) . FRAP analysis indicated the fluorescence recovery of MoRgs7:RFP in ΔMocrn1 was evidently delayed than that in Guy11 ( Fig 6C ) , suggesting that the diffusion of MoRgs7:RFP fluorescence into endosomes was impaired . This is consistent with our hypothesis that MoCrn1 is implicated in MoRgs7 internalization during appressorium development . Since MoRgs7 and MoMagA are both internalized via endocytosis , we also examined if MoCrn1 has a role in the MoMagA internalization through a protein-protein interaction . We first validated the interaction between MoCrn1 and MoMagA . In Y2H , we found that MoCrn1 interacts with MoMagA and this interaction was specific , since MoCrn1 was not found to interact with MoMagB and MoMagC ( Fig 5E ) . In addition , MoCrn1 did not interact with MoMagAG187S and MoMagAQ208L ( Fig 5E ) , the twoactive forms of MoMagA [3] . The interaction between MoCrn1 and MoMagA was again confirmed by co-IP ( Fig5F ) and BiFC assays ( Fig5G ) . In BiFC assay YFP is observed at the PM of germ tubes , revealing that MoCrn1 can interact with MoMagA at the PM of germ tubes during appressorium development . Moreover , similar to the co-localization of MoCrn1 with MoRgs7 , from a small number of conidia the partial co-localizaiton between MoCrn1 and MoMagA was also found at the PM in germ tubes ( S6B Fig ) . We next tested whether MoCrn1 affects the MoMagA distribution during appressorium development on hydrophobic surfaces . In Guy11 , we have observed that MoMagA:RFP displayed the endosome localization pattern in germ tubes and conidia . In ΔMocrn1 , we could still observe MoMagA:RFP on late endosomes , but there was a significant increase in the membrane localization of MoMagA:RFP ( Fig 6B ) . We again employed the FRAP assay to determine MoMagA internalization and found that the recovery of fluorescence of MoMagA:RFP in endosomes was slower in ΔMocrn1 than that in Guy11 ( Fig 6D ) . These results confirmed that MoCrn1 is important for MoMagA internalization during appressorium development . MoCrn1 is co-localized with F-actin so that MoCrn1 is similar to the adenylate cyclase associated protein MoCap1 that functions in cAMP signaling [6] . To examine whether MoCrn1 is required for MoCap1 localization , we expressed MoCap1:GFP in ΔMocrn1 and observed that the actin-like localization pattern of MoCap1 was completely disrupted in appressoria , conidia and hyphae of ΔMocrn1 ( S8 Fig ) . Strikingly , MoCap1 preferred to form cytoplasmic aggregations . Additionally , we found that MoCrn1 interacts with MoCap1 by performing a co-IP assay ( Fig 8F ) , in which the strain co-expressing MoCrn1:GFP and MoCap1:S was used . These results led us to conclude that MoCrn1 has a crucial role in recruiting MoCap1 to actin patches . MoCrn1 has been associated with MoRgs7 , MoMagA , and MoCap1 that all have a role in cAMP signaling . Indeed , we found that the ΔMocrn1 mutant also showed attenuated cAMP levels ( S7A Fig ) and a delay in appressorium formation ( S9 Fig ) . At 4 h post-germination , nearly 40% of ΔMocrn1 conidia formed appressorium on a hydrophobic surface compared with 80% of Guy11 did . However , over 80% of ΔMocrn1 conidia could still form the appressorium at 6 h post-germination ( S9 Fig ) . An incipient collapse assay indicated that MoCrn1 contributes to full turgor generation , since the collapse rate of the appressorium was significantly higher in ΔMocrn1 than in Guy11 and the complemented strains ( S7B Fig ) . Intracellular cAMP levels regulate the degradation of glycogen and lipid that are required for proper turgor generation in the appressorium [5 , 30] . We thus compared the degradation of glycogen and lipid betweentheΔMocrn1mutant and Guy11 strains . Conidia were allowed to germinate on hydrophobic surfaces and iodine and Neil Red were used to stain glycogen and lipid , respectively [31] . At 6 h post-inoculation , glycogen appeared in the early appressorium ( S7C Fig ) , and it broke down in 68 . 4% of the Guy11 appressoria after 16 h and 87% after 24 h , in comparison to 22 . 4% of ΔMocrn1 appressoria after 16 h and 53% after 24 h ( S7E Fig ) . Resembling to the glycogen , lipid degradation in ΔMocrn1 appressoria was slower than Guy11 . Lipid bodies disappeared in 44% of ΔMocrn1 appressoria at 16 h , compared to 86 . 4% of Guy11 appressoria ( S7D and S7F Fig ) . These results indicated that MoCrn1 is indispensable for an efficient degradation of glycogen and lipid necessary for the appressorial turgor generation . We further evaluated the ΔMocrn1 mutant for pathogenicity on rice . The conidial suspensions from Guy11 , ΔMocrn1 , and the complemented strain were sprayed onto the susceptible rice cultivar CO-39 . ΔMocrn1 produced fewer lesions than Guy11 and the complemented strain , which were confirmed by lesion quantification ( Fig 7A ) . We also performed rice sheath penetration assays by observing 100 appressoria each strain and classifying invasive hyphae ( IH ) types as previously described [17] . We observed that over 40% of ΔMocrn1 appressoria were defective in penetration and 55 . 6% of appressoria that penetrated and formed less extended IH . In contrast , 90% of Guy11 appressoria successfully penetrated rice cells and about 50% of that produced strong IH ( Fig 7B ) . To explore whether MoCrn1 regulates turgor generation involving the process of cAMP signaling , the incipient collapse assay was performed . We found that exogenous 8-Br-cAMP could suppress the defect of ΔMocrn1 in turgor generation ( S7B Fig ) . The numbers of the collapsed appressoria in the ΔMocrn1mutant were reduced by 20% and 10% with 1 and 2 mM cAMP , respectively , compared to those without 8-Br-cAMP . In addition , the ΔMocrn1 mutant appressorium underwent successful glycogen and lipid breakdown following 8 and 16 h , respectively , following treatment with 5 mM 8-Br-cAMP ( S7E and S7F Fig ) . Furthermore , 1 or 2 mM 8-Br-cAMP addition to the conidia suspensions in the inoculation of detached barley leaves could suppress the defect of ΔMocrn1 in infection to some degree ( Fig 7C ) . This result was also confirmed by the penetration assay , in which 8-Br-cAMP treatment restored the penetration defect to almost 80% of the ΔMocrn1 appressoria in comparison to 43 ± 4 . 9% of ΔMocrn1 without cAMP ( Fig 7B ) . This is similar to the effect of the ΔMocrn1mutant that expresses the constitutively active form of MoMagA , MoMagAG187S ( S7G and S7H Fig and Fig 7A ) . To examine the ability of MoCrn1 in binding multiple proteins , we identified putative actin binding domains and characterized their function . Human coronin Arg29and Arg30 are thought to be important for the interaction with F-actin [32 , 33] . The alignment showed that a majority of coronins contain a conserved basic amino acid at these two positions ( Fig 8A ) . In addition , the C-terminal coiled-coil ( CC ) domain is important for coronins to interact with the actin nucleation complex Arp2/3 [34] . Accordingly , we mutated His29 to Asp29 and deleted the CC domain of MoCrn1 , and fused the mutant proteins with GFP ( Fig 8B ) . We found that MoCrn1H29D and MoCrn1ΔCC mutants had completely altered actin-like localization patterns ( Fig 8C ) . To further analyze the effects of these mutant alleles , we performed the co-IP assay and found that MoCrn1H29D and MoCrn1ΔCC mutants failed to interact with MoRgs7 , MoMagA , and MoCap1 ( Fig 8D , 8E and 8F ) . We also expressed MoCrn1H29D and MoCrn1ΔCC mutants in ΔMocrn1 . FRAP analysis showed that the expression of MoCrn1H29D and MoCrn1ΔCC caused no effect on delayed endocytosis of MoRgs7 and MoMagA in ΔMocrn1 ( Fig 9 ) . HPLC analysis revealed cAMP levels of the strain expressing MoCrn1H29D or MoCrn1ΔCC comparable to that of the ΔMocrn1 mutant ( Fig 7D ) . Moreover , virulence and the degradation of appressorial glycogen and lipid in the MoCrn1H29D and MoCrn1ΔCC strains were also indistinguishable from those of the ΔMocrn1 mutant ( Fig 7E , 7F and 7G ) . Taken together , these results suggested that MoCrn1 function is dependent on its ability to interact with F-actin , MoRgs7 , MoMagA , and MoCap1 .
We here investigated the distinct functional mechanism of RGS and 7-TM-containing protein MoRgs7 beyond its RGS functions . We found that MoRgs7 has a GPCR-like endocytosis pattern and is predominantly localized to late endosomes similar to other signaling proteins , including MoRgs1 , MoMagA , and MoMac1 . Such late endosome localizations of signaling proteins are critical to GPCR function and for cAMP signal transduction . Our results further showed that MoRgs7 couples with MoMagA to undergo endocytosis . Interestingly , by inhibiting endocytosis , we could observe increased PM localization of MoRgs7 and MoMagA . And by inhibiting trafficking from the early endosomes to the late endosomes , we could observe the early endosome localization of MoRgs7 and MoMagA . Understanding how pathogen receptors recognizethe plant surface signal has a beneficial effect on the controlling rice disease at early stages . Our results provided evidences that MoRgs7 serves as a GPCR-like receptor to detect environmental hydrophobic cues . The affinity precipitation assay with phenyl-agarose gel beads indicates that MoRgs7 has strong ability to form hydrophobic interaction with hydrophobic materials , revealing that MoRgs7 can form interaction with hydrophobic surface when MoRgs7 is localized to the PM . Importantly , disruption of such hydrophobic interaction during M . oryzae germinating on the hydrophobic surface led to the aberrant appressorium formation . We also noted that the ΔMorgs7 mutant developed defective appressoria , even though no decrease in appressorium formation frequency . Based on these studies , we concluded that forming hydrophobic interactions with hydrophobic surface by MoRgs7 and other membrane proteins is a critical step in recognizing hydrophobic surface cues . We reasoned that MoRgs7 may undergo a functional process similar to mammalian GPCRs . In mammalian cells , when a ligand binds to a GPCR , ligand can activate GPCR by inducing conformational changes in GPCR , subsequently the active GPCRs can activate the Gα proteins and are transported by endocytosis to sustain downstream signaling , be recycled , or be degraded from endosomes [35] . Considering our studies and previous findings by others in mammalian cells , we proposed a functional model of MoRgs7 ( Fig 10 ) . In this model , MoRgs7 acts as a GPCR during appressorium development to interact with the hydrophobic surface . Subsequently , this interaction induces MoRgs7-MoMagA endocytosis that is regulated by MoCrn1 . MoRgs7 facilitates activating cAMP signaling from endosomes along with MoMagA . Conversely , MoRgs7 may elevate its GAP activity to regulate MoMagA when cAMP signaling is fully activated . Thus , MoRgs7 has dual roles in regulating signal transduction . How MoRgs8 that also contains 7-TM domain but lacks sensory functions is not understood . MoRgs8 was distributed in the cytoplasm of germ tubes but did not undergo endocytosis . MoRgs8 could be involved in a mechanism distinct from MoRgs7 and future studies are needed to address such distinct mechanism ( s ) . There was precedence that endocytosis of RGS proteins plays a role in promoting Gα-mediated signaling . In Arabidopsis thaliana , in response to glucose , RGS protein AtRgs1 internalizes via endocytosis to uncouple itself from Gα protein AtGPA1 anchored in the PM , leading to AtGPA1 sustaining activation . And this process is required for both G-protein-mediated sugar signaling and cell proliferation [36] . However , other details including the initiation of MoRgs7-MoMagA complex disassembly following endocytosis remain not understood . We recently reported a distinct mechanism of how M . oryzae might negatively regulate the GAP activity of MoRgs7 . This mechanism implicates the MoMip11 protein that interacts with MoRgs7 and the GDP bound MoMagA , but not the GTP bound MoMagA ( Fig 10 ) [14] . MoMip11 prevents MoRgs7 from interacting with the GTP bound MoMagA , therefore interfering with MoRgs7 GAP function by sustaining MoMagA activation [14] . During endocytic vesicle formation , a series of adaptor proteins in cytoplasm can accumulate at endocytic sites . Those adaptors serve to select endocytic cargos and specifically bind to cargos , recruiting their cargos to endocytic pits/vesicles [29 , 37] . Since we found that endocytosis of MoRgs7 and MoMagA are independent of each other , we considered that the adaptor protein ( s ) for the two proteins can anchor MoRgs7 or MoMagA to endocytic pits even though MoRgs7 and MoMagA do not interact with each other . Despite of that , the MoRgs7-MoMagA interaction is still important for MoRgs7 to regulate MoMagA activity . To further investigate the physiological function of MoRgs7 and MoMagA endocytosis , coronin protein MoCrn1 that emerges as an adaptor protein for MoRgs7 and MoMagA was identified and characterized . MoCrn1 is localized to actin patches that represent endocytic sites , interacting with MoRgs7 and MoMagA and regulating their endocytosis . Disruption of MoCrn1 by gene deletion or point mutations ( H29D mutation and CC domain deletion ) not only attenuated MoRgs7 and MoMagA endocytosis , but also led to a decreased cAMP level that is lower than the threshold for proper appressorium development . Our results support that MoRgs7 and MoMagA endocytosis regulated by MoCrn1 facilitates initiating cAMP signaling and appressorium development . However , for BiFC assays to test MoCrn1-MoRgs7 and MoCrn1-MoMagA interactions we queried why the YFP fluorescence evenly distributes at the PM of germ tubes , not just at the actin patches . A possible explanation is that , before MoCrn1 accumulates at actin patches , the cytoplasm-localized MoCrn1 has already bound to the cytoplasmic peptides of PM-localized MoRgs7 and MoMagA . At later stage , these interactions enable MoCrn1 to direct MoRgs7 and MoMagA to endocytic pits/vesicles . Coronin proteins are known as regulators of the cytoskeleton and membrane trafficking in a number of species including yeast , Neurospora crassa , Dictyostelium discoideum , Drosophila , and human [23 , 24] . In D . discoideum and mammalian cells , coronins have evolved to be modulators of signal transduction . Those coronins are critical for Rac1 GTPase activation and Rac1-dependent signaling [33 , 38] . Additionally , upon cell surface stimulation coronin 1 interacts with and activates Gα to stimulate cAMP/PKA pathway in neuronal cell , even though how coronin 1 activates Gα is less clear [39] . Compared to those studies , our work revealed that MoCrn1 is involved in a distinct mechanism to facilitate Gα-cAMP signaling . MoCrn1 has an adaptor protein-like function by directing MoRgs7 and MoMagA to endocytic pits to promote their internalization . This function , thereby allows MoCrn1 to have a role in facilitating cAMP signaling . However , the function was not found yet for other eukaryote coronins , thus it is not known whether coronin is generally required for endocytosis of RGS and Gα proteins in eukaryotes except M . oryzae . Interestingly , MoCrn1 also interacts with MoCap1 that is thought as one of activators of MoMac1 [6] . Based on the above , we proposed that MoCrn1 is likely to be a hub or organizing protein of the network of MoRgs7-MoMagA-MoCap1 .
The M . oryzae Guy11 strain was used as wild type for transformation in this study . For vegetative growth , small agar blocks were taken from the edge of 7-day-old cultures and cultured in liquid CM medium for 48 h . For conidiation , strains were cultured on SDC plates at 28°C for 7 days in the dark , followed by constant illumination for 3 days [8 , 17 , 31 , 40–43] . The MoCRN1 deletion mutant was generated using the standard one-step gene replacement strategy [44] . First , two approximate 1 . 0 kb of sequences flanking of MoCRN1 ( MGG_06389 ) were amplified with two primer pairs MoCRN1-F1/MoCRN1-R1 , MoCRN1-F2/MoCRN1-R2 , the resulting PCR products ligated with the HPH cassette released from pCX62 . The protoplasts of wild type Guy11 were transformed with the vectors for targeted gene deletion by inserting the hygromycin resistance HPH marker gene cassette into the two flanking sequences of the MoCRN1 gene . For selecting hygromycin-resistant transformants , CM plates were supplemented with 250 μg/ml hygromycin B ( Roche , USA ) . To generate complementary construct pYF11-MoCRN1 , the gene sequence containing the MoCRN1 gene and 1 . 0 kb native promoter was amplified with MoCRN1-comF/ MoCRN1-comR . Yeast strain XK1-25 was co-transformed with this sequence and XhoI-digested pYF11 plasmid . Then the resulting yeast plasmid was expressed in E . coli . To generate the complementary strain , the pYF11-MoCRN1 construct was introduced into the ΔMocrn1 mutant and pYF11 contains the bleomycin-resistant gene for M . oryzae transformants screen [31 , 44] . EcoRV was used to digest the genomic DNA from Guy11 and the ΔMocrn1 mutant . The digest products were separated in 0 . 8% agar gel and were hybridized with the MoCRN1 gene probe . The probe was designed according to the disruption strategy and was amplified from Guy11 genomic DNA using primers MoCRN1-InterF/MoCRN1-InterR . To confirm MoCRN1 replacements , labeled MoCRN1 probe was used to hybridize the EcoRV-digested genomic DNA from the ΔMocrn1 mutant and wild-type Guy11 . The copy number of the HPH gene in the ΔMocrn1 mutant was detected using labeled HPH fragments that amplified from the plasmid of pCB1003 with primers FL1111/FL1112 . The whole hybridization was carried out according to the manufacturer’s instruction for DIG-High Prime . The conidia were suspended in a 0 . 2% ( w/v ) gelatin solution ( 5×104 spores/ml ) , then the solutions were sprayed onto 2-week-old seedling of susceptible rice ( Oryza sativa cv . CO-39 ) and also inoculated into 3-week-old rice CO-39 as described . Then the plants were incubated at 25°C with 90% humidity in the dark for the first 24 h , followed by a 12h/12h light/dark cycle . Lesions were observed after 7 days of incubation [41] . For pathogenicity assay with detached barley leaves [40] , three 20 μl droplets of the conidia suspensions ( 1×105 , 1×104 , 1×103 spores/ml , respectively ) added cAMP solution or not , were placed onto the upper side of the 7-day-old barley ( cv . Four-arris ) leaves . Then the leaves were incubated at 25°C with 90% humidity and in the dark for the first 24 h , followed by a 12h/12h light/dark cycle . Lesions were observed after 5 days of incubation . To visualize glycogen , the samples were stained by iodine solution containing 60 mg/ml KI and 10 mg/ml I2 for 1 min . Nile red solution consisting of 50 mM Tris/maleate buffer ( pH 7 . 5 ) and 2 . 5 mg/ml Nile red ( 9-diethylamino-5H-benzo-a-phenoxazine-5-one , Sigma ) , was used to treat the samples for 3 min , then the samples were examined under a fluorescence microscope with RFP channel [17 , 26 , 30] . The DNA fragments for expressing GFP fusion proteins were respectively inserted into the pYF11 construct that contains bleomycin resistant gene and G418 resistancegene , and the DNA fragments for expressing S-tag fusion proteins were respectively inserted into the pXY203 construct hat contains hygromycin gene . Then the constructs for expressing GFP and S-tag fusion proteins were co-transformed into wild-type strain Guy11 , and the transformants resistant to hygromycin and bleomycin or G418 were isolated . The total protein of the transformants was extracted from mycelium using protein lysis buffer [1 M Tris-Cl ( pH7 . 4 ) , 1 M NaCl , 0 . 5 M EDTA , 1% Triton×100] and incubated with anti-GFP agarose beads ( GFP-Trap , Chromotek , Martinsried , Germany ) for 4 h , followed by washing beads with washing buffer ( 50 mM Tris HCl , 150 mM NaCl , pH 7 . 4 ) for 4 times . The proteins that bind to the beads were eluted by 0 . 1 M glycine HCl ( pH 3 . 5 ) and were probed by anti-GFP and anti-S antibodies . MoCRN1 and MoACT1 full-length cDNAs were cloned and inserted into pGEX4T-2 and pET32a , respectively . These constructs were transformed into E . coli strain BL21 for expressing proteins . Bacterial lysate containing GST:MoCrn1 protein was incubated with 30 μl GST agarose beads for 2 h . Then the beads were washed by washing buffer for 4 times and incubated with His:MoAct1 protein for 2 h , followed by washing beads with using washing buffer ( 50 mM Tris HCl , 150 mM NaCl , pH7 . 4 ) for 4 times again . The beads were boiled to elute proteins , and eluted proteins ( output ) were probed with anti-GST and anti-His antibodies . Constructs of BD:MoMagA , BD:MoMagB and BD:MoMagC were used in previous experiments and kept in our lab . Full-length cDNAs of MoCRN1 was cloned and inserted into pGADT7 ( AD ) vector . Full-length cDNAs of MoCAP1 , MoMagAG187S , MoMagAQ208L and MoACT1 genes were inserted into pGBKT7 ( BD ) vector . To examine the interaction of proteins , the AD and BD constructs were co-transformed into yeast strain AH109 and the transformants were grown on SD-Trp-Leu medium . Then the Trp+ and Leu+ transformants were isolated and assayed for growth on SD-Trp-Leu-His-Ade medium added X-α-Gal . The germinated conidia with 3 h of incubation on hydrophobic or hydrophilic surfaces were treated with cycloheximide and benomyl as described [17] . FRAP were performed using a fluorescence microscope Zeiss LSM710 . Regions containing MoRgs7:RFP and MoMagA:RFP in germ tube were selected for photo-bleaching . Photobleaching was carried out using an Argon-multiline laser at a wavelength of 561 nm with 80% laser power and 80 iterations in ROI . Images were acquired with 2% laser power at a wavelength of 555 nm every 5 sec . For quantitative analyses , fluorescence intensity was measured using the ZEISS ZEN blue software and fluorescence recovery curves were fitted using following formula: F ( t ) = Fmin + ( Fmax − Fmin ) ( 1-exp−kt ) , where F ( t ) is the intensity offluorescence at time t , Fmin is the intensity of fluorescence immediately post-bleaching , Fmax is the intensity of fluorescence following complete recovery , and k is the rate constant of the exponential recovery [45] . Mobile Fraction was calculated as the following formula: Mf = ( Fend − F0 ) / ( Fpre − F0 ) , where Fend is the stable fluorescent intensity of the punctae after sufficient recovery , F0 is the fluorescent intensity immediately after bleaching , and Fpre is the fluorescent intensity before bleaching [46] . LatrunculinB ( Cayman , USA ) is dissolved in DMSO at a concentration of 25 mg/ml . Conidia incubated on the coverslips with hydrophobic surface were treated with LatB ( final concentration 0 . 1 μg/ml ) for 30 min , while the controls were treated with 5% DMSO . Then samples were washed with distilled water . Cycloheximide ( MedChemExpress , USA ) was solved in distilled water and the germinated conidia were treated with a final concentration 10 μg/ml for 10 min . Then samples were washed with distilled water . Benomyl ( Aladdin , Shanghai , China ) was solved in 0 . 1% DMSO and added to germinated conidia with a final concentration 1μg/ml . Then the samples were washed with distilled water . EGA ( Merck , USA ) was solved in 5% DMSO and was applied to samples with concentration 5 μg/ml for 1 h . The total proteins were extracted from the Guy11 strain expressing MoRgs7:GFP or GFP , respectively , and were incubated with 100 mg of Phenyl-agarose beads ( Senhui Microsphere Tech , Suzhou , China ) in 1 . 5 ml microcentrifuge tubes at 10°C for 16 h . After incubation , the tubes were centrifuged ( 13000 g , 5 min ) to remove the suspension . The beads were then gently washed with a series of aqueous solutions with different concentrations of NaCl and MgSO4 ( 1 . 5/1 . 0/0 . 8/0 . 5/0 . 3/0 . 2/0 . 1 M NaCl and MgSO4 , 10 mM HEPES , pH 7 . 0 ) , respectively , for 3 times to remove the unbound proteins . 100 μl of 1% SDS solution was added to the washed beads , followed by boiling the SDS solution and beads for 10 min to obtain elution , which was examined by western-blot using anti-GFP antibody . All the samples were observed under a confocal fluorescence microscope ( Zeiss LSM710 , 63× oil ) . The filter cube sets: GFP ( excitation spectra: 488 nm , emission spectra: 510 nm ) , RFP ( excitation spectra: 555 nm , emission spectra: 584 nm ) . Exposure time: 800 ms . ImageJ software was applied to calculate Pearson correlation coefficient for analyzing co-localization of GFP fusion protein with RFP fusion protein . One area of interest was photographed with GFP and RFP channels respectively and photographs were opened using ImageJ software . Picture type was set to 8 bits . The “colocalization finder” in “plugin” section was applied to the pictures and Pearson correlation coefficient was calculated . All of the strains were cultured on CM medium at 28°C , were cut into 1×1 mm squares , and were cultured in liquid CM for another 2 days . Filtering to collect mycelium and quickly ground into powder in liquid N2 . 1 mg of mycelium was mixed with 20 μl of 6% TCA solution . Samples were centrifuged ( 1 , 377 × g , 15 min ) , the top layers were collected and were washed twice with five times the volume of anhydrous ether . The pellet was collected for HPLC . HPLC analysis was done with a programmable Agilent Technology Zorbax 1200 series liquid chromatograph . The solvent system consisted of methanol ( 90% ) and water ( 10% ) , at a flow rate of 1 ml per minute; 0 . 1 mg of cAMP solution per milliliter was eluted through the column ( SBC18 , 5 μl , 4 . 6 × 250 mm ) and was detected at 259 nm UV . Each sample was eluted through the column in turn and peak values were detected with the same time as the standard [47] . For construction of pHZ65:MoMagA vector used to express MoMagA-N’YFP , the N’YFP sequence was inserted into the alphaB-alphaC loop of MoMagA as described [48] , then the MoMagA sequence containing N’YFP and the native promoter was fused with the pYF11 plasmid . For construction of vector used to express MoMagA:RFP , the RFP sequence was also inserted into the alphaB-alphaC loop of MoMagA . Then the MoMagA sequence containing the native promoter was fused with pYF11 plasmid . For construction of other vectors used to express proteins tagged with RFP or GFP , RFP or GFP was fused to protein sequence C-terminals , then protein sequences containing their native promoters were fused with the pYF11 plasmid . MoRGS7 ( MGG_11693 ) , MoRGS8 ( MGG_13926 ) , MoMagA ( MGG_01818 ) , MoCRN1 ( MGG_06389 ) , MoCAP1 ( MGG_01722 ) | The 7-TM domain is considered the hallmark of GPCR proteins , which activate G proteins upon ligand binding and undergo endocytosis for regeneration or recycling . Among eight RGS and RGS-like proteins of M . oryzae , MoRgs7 and MoRgs8 contain a 7-TM domain in addition to the RGS domain . We found that MoRgs7 can form hydrophobic interactions with the hydrophobic surface . This interaction is important in sensing hydrophobic cues by the fungus . We also found that , in response to surface hydrophobicity , MoRgs7 couples with Gα subunit MoMagA to undergo endocytosis leading to the activation of cAMP signaling . Moreover , we found that such an endocytic event requires functions of the actin-binding protein MoCrn1 . Our results revealed that MoRgs7 also functions as a GPCR-like receptor protein to sense surface cues and activate signaling required for pathogenesis , providing new insights into G-protein regulatory mechanisms in this and other pathogenic fungi . | [
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... | 2019 | The seven transmembrane domain protein MoRgs7 functions in surface perception and undergoes coronin MoCrn1-dependent endocytosis in complex with Gα subunit MoMagA to promote cAMP signaling and appressorium formation in Magnaporthe oryzae |
In human and porcine cysticercosis caused by the tapeworm Taenia solium , the larval stage ( cysts ) can infest several tissues including the central nervous system ( CNS ) and the skeletal muscles ( SM ) . The cyst’s proteomics changes associated with the tissue localization in the host tissues have been poorly studied . Quantitative multiplexed proteomics has the power to evaluate global proteome changes in response to different conditions . Here , using a TMT-multiplexed strategy we identified and quantified over 4 , 200 proteins in cysts obtained from the SM and CNS of pigs , of which 891 were host proteins . To our knowledge , this is the most extensive intermixing of host and parasite proteins reported for tapeworm infections . Several antigens in cysticercosis , i . e . , GP50 , paramyosin and a calcium-binding protein were enriched in skeletal muscle cysts . Our results suggested the occurrence of tissue-enriched antigen that could be useful in the improvement of the immunodiagnosis for cysticercosis . Using several algorithms for epitope detection , we selected 42 highly antigenic proteins enriched for each tissue localization of the cysts . Taking into account the fold changes and the antigen/epitope contents , we selected 10 proteins and produced synthetic peptides from the best epitopes . Nine peptides were recognized by serum antibodies of cysticercotic pigs , suggesting that those peptides are antigens . Mixtures of peptides derived from SM and CNS cysts yielded better results than mixtures of peptides derived from a single tissue location , however the identification of the ‘optimal’ tissue-enriched antigens remains to be discovered . Through machine learning technologies , we determined that a reliable immunodiagnostic test for porcine cysticercosis required at least five different antigenic determinants .
Human and porcine cysticercosis caused by the larval stage of Taenia solium , is acquired by the ingestion of this parasite’s eggs . After activation by several gastrointestinal agents , the oncospheres penetrating the intestinal wall later establish in different tissues and organs including the skeletal muscles ( SM ) and the brain . In humans , establishment of cysts in the central nervous system ( CNS ) causes neurocysticercosis ( NC ) , a serious and pleomorphic disease that can become highly debilitating [1] . Heterogeneity of human NC has been associated , at least in part , with the number and localization of the cysts in the CNS [2] , as well as to many other factors including a complex immune response directed to a number of cyst’s antigens [3 , 4 , 5 , 6] . The molecular factors associated with the tissue localization of the T . solium cysts remain poorly understood [7] . Other pathogenic microorganisms ( S . pneumoniae , Campylobacter jejuni , Escherichia coli , Trypanosoma brucei , etc . ) , show tissue preference linked to a number of specific pathogen’s proteins [8 , 9 , 10 , 11 , 12] . Information available on proteomics changes of flatworm parasite infections is limited . However , we know that parasites respond to hormones , cytokines and other host’s molecules [13] . The availability of several tapeworm genomes [14] has allowed to detail this complex host-parasite cross-communication including insulin , EGF/FGF , TGF-b/BMP , among others ( for an updated review see [15] ) . Insulin responsiveness has been described for Schistosoma mansoni , Taenia crassiceps and Echinococcus multilocularis [16 , 17 , 18] . The differential effects of steroid hormones during parasite infections is also well documented [19] . Some parasites also have the ability to respond to host cytokines; for example , S . mansoni has receptors to TNF-α and TGF-β and proteomic and genomic changes have been reported in response to those cytokines [20 , 21 , 22] . The advent of high throughput proteomic techniques greatly widens our power to approach these old questions in molecular helminthology . In this context , body fluids of the host may affect proteome expression of infectious agents , for example , E . coli growing in a media supplemented with urine show a differential proteome signature [23] . Furthermore , several proteomic changes of Streptococcus pyogenes have been reported in response to serum supplementation [24] . The molecular factors associated with the tissue localization of helminth parasites within the host tissues has been less explored; in the case of Trichinella spiralis several changes have also been reported between parasites isolated from different host tissues [25] . However , important advances in helminth proteomics , including metacestode cystic/vesicular larval forms , have been reported [26–29] . It is conceivable that the host tissue’s molecular environment modulates the protein expression of pathogens , including parasites . Accordingly , specific proteomic profiles of parasites could be associated with a certain tissue localization . Understanding the proteome changes of parasites in different host tissues , can provide insights not only on the molecular networking occurring in complex host parasite relationships , but it could also be useful for the design of more effective vaccines , drugs , as well as for the improvement of available diagnostic procedures . Here we benefited from isobaric quantitative proteomics to elucidate the proteomic changes of T . solium cysts obtained of SM and CNS of pigs . A protein profile was found associated with each tissue localization , allowing the identification of 42 tissue-enriched antigens and the design of 14 synthetic antigenic peptides that were evaluated for antibody recognition using infected and uninfected pig’s sera . Our results indicated that an optimal immunological diagnosis for porcine cysticercosis requires at least five different epitopes from several tissue-enriched antigens . A remarkable finding was the conspicuous and abundant presence of host proteins in the protein extracts of the cysts; 891 host proteins were identified and quantified . We present initial findings suggesting that several intact host’s proteins might play a significant role in tapeworm’s physiology .
Methanol−chloroform precipitation of the reduced and alkylated protein extracts was performed prior to protease digestion . Samples of 400 μg of each protein extract were resuspended separately in 100 μL of 8 M urea in 50 mM HEPES , pH 8 . 2 . After solubilization , the protein extracts were diluted to 4 M urea with 50 mM HEPES , pH 8 . 2 , and digested at RT for 3 h with endoproteinase Lys-C ( Wako , Japan ) at 5 ng/μL . The mixtures were then diluted to 1 M urea with 50 mM HEPES , pH 8 . 2 , and trypsin was added at a 50:1 protein-to-protease ratio . The reaction was incubated overnight at 37°C and stopped by the addition of 100% TFA to a final pH < 2 . Peptides were desalted using 50 mg tC18 SepPak solid-phase extraction cartridges ( Waters , Milford , MA ) and lyophilized . Desalted peptides were resuspended in 100 μL of 200 mM HEPES , pH 8 . 2 . Peptide concentrations were determined using the microBCA assay ( Thermo Fisher Scientific , Waltham , MA ) . One-hundred micrograms of peptides from each sample was labeled with TMT reagent . TMT-10 reagents ( 0 . 8 mg , from Thermo Fisher Scientific ) were dissolved in anhydrous acetonitrile ( 40 μL ) , of which 10 μL were added to the peptides along with 30 μL of acetonitrile ( final acetonitrile concentration of approximately 30% ( v/v ) ) . The labeling reaction proceeded for 1 h at room temperature and then was quenched with hydroxylamine ( Sigma , St . Louis , MO ) to a final concentration of 0 . 3% ( v/v ) . The TMT-labeled samples were mixed equally , vacuum centrifuged to near dryness , desalted using 200 mg solid-phase C18 extraction cartridge ( Sep-Pak , Waters ) , and lyophilized . The TMT-labeled peptides were fractionated using BPRP HPLC . An Agilent 1100 pump equipped with a degasser and a photodiode array ( PDA ) detector ( set at 220 and 280 nm wavelength ) from Thermo Fisher Scientific ( Waltham , MA ) were used . Peptides were subjected to a 50 min linear gradient from 5% to 35% acetonitrile in 10 mM ammonium bicarbonate pH 8 at a flow rate of 0 . 8 mL/min over an Agilent 300 Extend C18 column ( 5 μm particles , 4 . 6 mm ID , and 220 mm in length ) . Beginning at 10 min of peptide elution , fractions were collected every 0 . 38 min into a total of 96 fractions , which were consolidated into 24 , of which 12 nonadjacent samples were analyzed . Samples were dried via vacuum centrifugation . Each eluted fraction was acidified with 1% formic acid and desalted using StageTips [31] , dried via vacuum centrifugation , and reconstituted in 4% acetonitrile , 5% formic acid for LC−MS/MS analysis . All mass spectrometry data were collected on an Orbitrap Fusion mass spectrometer ( Thermo Fisher Scientific , San Jose , CA ) coupled to a Proxeon EASY-nLC II liquid chromatography ( LC ) pump ( Thermo Fisher Scientific ) . Peptides were eluted over a 100 μm inner diameter micro-capillary column packed with ∼0 . 5 cm of Magic C4 resin ( 5 μm , 100 Å , Michrom Bioresources ) followed by ∼35 cm of Accucore resin ( 2 . 6 μm , 150 Å , Thermo Fisher Scientific ) . For each analysis , we loaded ∼1 μg of the peptide mixture onto the column . Peptides were separated using a 90 min gradient of 6−26% acetonitrile in 0 . 125% formic acid at a flow rate of ∼350 nL/min . The dynamic exclusion duration was set at 90 s , with a mass tolerance of ±7 ppm . Each analysis used the multinotch MS3-based TMT method [32] on an Orbitrap Fusion mass spectrometer , which has been shown to reduce ion interference compared to MS2 quantification . The scan sequence began with an MS1 spectrum ( Orbitrap analysis; resolution 120000; mass range 400−1400 m/z; automatic gain control ( AGC ) target 2 × 105; maximum injection time 100 ms ) . The 10 most-abundant MS1 ions of charge states 2−6 were fragmented , and multiple MS2 ions were selected using a Top10 method . MS2 analysis was composed of collision induced dissociation ( quadrupole ion trap analysis , AGC 4 × 103; normalized collision energy ( NCE ) 35; maximum injection time 150 ms ) . Following acquisition of each MS2 spectrum , we collected an MS3 spectrum as described previously [32] , in which multiple MS2 fragment ions were captured in the MS3 precursor population using isolation waveforms with multiple frequency notches . MS3 precursors were fragmented by high energy collision-induced dissociation ( HCD ) and analyzed using the Orbitrap ( NCE 55; AGC 5 × 104; maximum injection time 150 ms , resolution was 60 , 000 at 400 Th ) . Instrument data files were processed using a SEQUEST-based in-house software pipeline [33] . Spectra were converted from . raw to mzXML using a modified version of ReAdW . exe . A database containing all predicted ORFs for entries from the parasite ( T . solium genome database; http://www . genedb . org/Homepage/Tsolium; downloaded March 31 , 2015 ) and the host ( Sus scrofa database; http://www . uniprot . org/proteomes/ ? query=taxonomy:9823; downloaded March 31 , 2015 ) was used . This database was concatenated with another database composed of all protein sequences in the reverse order . Searches were performed using a 50 ppm precursor ion tolerance for total protein level analysis . The product ion tolerance was set to 0 . 9 Da . These wide mass tolerance windows were chosen to maximize sensitivity besides SEQUEST searches and linear discriminant analysis [34 , 35] . TMT tags on lysine residues and peptide N termini ( +229 . 163 Da ) and carbamidomethylation of cysteine residues ( +57 . 021 Da ) were set as static modifications , while oxidation of methionine residues ( +15 . 995 Da ) was established as a variable modification . Peptide-spectrum matches ( PSMs ) were adjusted to a 2% false discovery rate ( FDR ) [35] . PSM filtering was performed using a linear discriminant analysis , as described previously [33] , while considering the following parameters: XCorr , ΔCn , missed cleavages , peptide length , charge state , and precursor mass accuracy . For TMT-based reporter ion quantitation , we extracted the signal-to-noise ( S/N ) ratio for each TMT channel and found the closest matching centroid to the expected mass collapsed to a 1% peptide FDR and then collapsed further to a final protein-level FDR of 1% . Moreover , for protein assembly , principles of parsimony were used to produce the smallest protein set , necessary to account for all observed peptides . Proteins were quantified by summing reporter ion counts across all matching PSMs using in-house software , as described previously [36] . Briefly , a 0 . 003 Th window around the theoretical m/z of each reporter ion ( 126 , 126 . 1278 Th; 127N , 127 . 1249 Th; 127C , 127 . 1310 Th; 128N , 128 . 1283 Th; 128C , 128 . 1343 Th; 129N , 129 . 1316 Th; 129C , 129 . 1377 Th; 130N , 130 . 1349 Th; 130C , 130 . 1410 Th; 131 , 131 . 1382 Th ) was scanned for ions , and the maximum intensity nearest the theoretical m/z was used . PSMs with poor quality , MS3 spectra with TMT reporter summed signal-to-noise ratio less than 387 , or no MS3 spectra were excluded from quantitation [32] . The RAW files will be made available upon request . Protein quantitation values were exported for further analysis in Excel , Perseus 1 . 5 . 2 . 4 and GraphPad prism v6 . Proteins with more than three missing channels were discarded , in the case of identifications based in a single peptide , that peptide was present in at least 7 samples . The selection of the tissue-enriched proteins ( Fig 1 ) was based on the comparison of fold changes between CNS and SM cysts using a multiple T-test and Benjamini-Hochberg correction with a 5% of FDR ( there were 5 CNS samples , unfortunately , one sample of CNS cysts was discarded at the end , due to poor data quality ) . Proteins with a P-value <0 . 01 ( n = 261 ) and proteins without changes ( lowest coefficient of variation , n = 50 ) were chosen to predict their antigenic regions . A detailed explanation is found in the S2 Fig . Initially , the antigenicity algorithm [37] and the B cell epitope algorithm [38] were used to quantitatively estimate the proteins with the higher antigenicity . Only the proteins predicted by both algorithms with a high percentage of antigen/epitope were selected ( n = 42 ) . The peptide selection was based on the following criteria: length of at least 15 amino acids ( average size of predicted antigenic regions = 14 . 1 ) ; coincidence in the prediction of at least 5 amino acids by both algorithms , and at least , 10 amino acids should be predicted by one of the algorithm . The resulting peptides were submitted to an algorithm that was trained with a set of synthetic peptides of proven utility in diagnostic procedures as well as with a set of peptides that were not useful [39]; peptides with the highest probability of recognition by antibodies were selected . A total of ten peptides were selected ( one from each protein ) ; 4 peptides derived from proteins that were abundant in SM cysts , 4 from CNS cysts and 2 from proteins that did not show change in both tissues . All peptides were purchased from GenScript ( USA ) . Proteins from the host ( Sus scrofa ) were annotated using the PantherGo algorithm [40 , 41]; in the case of T . solium proteins , only proteins with a P-value<0 . 01 were submitted to Argot2 algorithm [42–44] using a threshold of 200 . Disulfide bonds , N-linked glycosylation sites , transmembrane regions , signal peptides , and GPI-anchoring sites were predicted for selected proteins using several algorithms [45–56] . The insoluble fraction of T . solium cysts , the VF and the synthetic peptides were tested by ELISA . Briefly , 1 . 5 μg of the insoluble fraction and of the VF , as well as 500 ng of each synthetic peptide were used to coat separate wells of microtiter plates . After overnight incubation at 4°C with mild agitation , the plates were washed , blocked for 2 h with 1% albumin in PBS-0 . 05% Tween 20 ( PBST ) and incubated with different pig sera , diluted 1:200 in PBST and incubated overnight at 4°C . A HRP coupled anti-pig IgG hyperimmune serum was used ( diluted 1:4 , 000 ) as secondary antibody . The reaction was developed using OPD ( 0 . 4 mg/mL ) for about 3–5 min and stopped with 3N HCl . Absorbance at 492 nm was determined in a Multiskan FC ( Thermo-Fisher Scientific ) . The total saline extract was passed through a column of Protein G coupled to Sepharose 4B . The bound IgG was eluted using 0 . 1 M glycine pH 2 . 3 and immediately neutralized with Tris 1M , pH 7 . 3 . Fractions containing the bound IgG were concentrated using an Amicon system ( 10 kDa cutoff ) and washed several times using PBS , pH 7 . 3 . The purified IgG was quantified by Non-Interfering protein assay ( GBiosciences ) . The IgG purified from the cysts protein extracts was tested for antibody activity through conventional ELISA and western-blotting procedures . For ELISA , microtiter plates were separately coated using 1 . 5 μg of VF or the insoluble protein fraction of cyst tissue ( see above ) in carbonate buffer , pH 9 . 6 . After overnight incubation at 4°C with mild agitation , the plates were washed three times using PBST and blocked using 1% albumin in PBST for 1 h at room temperature . After another washing cycle , the plates were incubated overnight at 4° C with the IgG fraction purified from the T . solium cysts . A pool of sera from 15 cysticercotic pigs was also used in similar assays for comparison . Dilutions for both the IgG purified from the cysts and the pool of sera from the infected pigs are shown below . After washing , the plates were incubated with a HRP-coupled rabbit anti-pig IgG hyperimmune serum ( diluted 1:1000 ) for 1h at room temperature . The reaction was developed using OPD ( 0 . 4 mg/mL ) for about 3–5 min and stopped with 3N HCl . Absorbance at 492 nm was determined in a Multiskan FC ( Thermo-Fisher Scientific ) . In the case of western-blotting , 20 μg of the VF and the insoluble fraction were resolved through 12% SDS-PAGE and transferred onto a nitrocellulose membrane . The membranes were blocked overnight using 10% of skim milk in PBS and incubated with 10μg/mL of the IgG purified from T . solium cysts in 10% skim milk at room temperature . After three washings using PBS-Tween 0 . 1% , the membrane strips were incubated with the rabbit anti-pig IgG secondary antibody ( diluted 1:85 , 000 ) for 2h at room temperature . The antigen-antibody reaction was developed using a West femto chemiluminiscence kit ( Thermo ) following the manufacturer’s instructions . For each subset of k antigenic peptide measures and n subjects , predictive accuracy was measured by Leave One Out Cross Validation . Here , n independent training/testing procedures using a Support Vector Machine ( SVM ) were performed . Each training set consisted in all except one individual value , and testing set being the individual left out . Accuracy is computed as the fraction of times each individual test was correctly classified for that particular selection of k peptides . Source code for SVM implementation is found in S1 Data and is contained in scikit-learn package [SKLEARNREF] with default parameters [57] . Cysts ( CNS and SM ) were fixed in Zamboni solution . Afterwards , all samples were dehydrated and embedded in paraffin . Heat-mediated antigen retrieval was performed on 5-μm sections , using a 0 . 1 M sodium citrate solution ( pH 6 . 0 ) in a high-pressure sterilizer ( 120°C for 5 min ) and endogenous peroxidase was consumed by incubation with 0 . 3% ( v/v ) H2O2 in PBS for 10 min at RT . Afterwards , the tissue section on slides were washed three times with PBS and maintained in a blocking solution ( 0 . 1% BSA in PBS , Sigma-Aldrich ) for 10 min . After washing with PBS , the slides were incubated overnight with the primary antibody ( the list of antibodies used could be found in S1 Table ) , diluted 1:50 , in PBS-0 . 1% BSA , at 4°C . After washing several times with PBS , the tissue sections were incubated with the corresponding second antibody ( HRP-conjugated ) 1:1000 for 30 min at 37°C . Peroxidase activity was visualized by incubating the samples for 2 min with 3-diaminobenzidine tetrahydrochloride ( DAB , MP Biomedicals ) . Reaction was stopped with water , and sections were counterstained with hematoxylin , dehydrated , cleared , and mounted with resine ( Gold Bell ) . The single labeled sections were examined and photographed under light microscopy ( Nikon Eclipse 80i ) using a digital color video camera ( Nikon Digital Sigth ) . The second antibody controls could be found in S3 Fig . All relevant information are within the manuscript or supplementary material . The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [58] partner repository with the dataset identifier PXD00527 . The source code for the support vector machine is available in the S1 Data; protein and peptide identifications can be found in S2 and S3 Data; the subset of highly antigenic proteins can be found in S4 Data; the functional annotation of the tissue-enriched proteins in S5 Data and several cestode proteome comparison in S6 Data . Briefly , 50 μg of VF and insoluble fraction of cysts tissue were resolved by 12% SDS-PAGE , the gels were transferred onto nitrocellulose membranes . The membranes were blocked overnight using 10% of skim milk in PBS and incubated with the primary antibody diluted 1: 3000 in 10% skim milk at room temperature ( S1 Table ) . After three washings using PBS-Tween 0 . 1% , the membrane strips were incubated with the corresponding secondary antibody diluted 1:50 , 000 in PBST . The antigen-antibody reaction was developed using a West femto chemiluminiscence kit ( Thermo ) following the manufacturer’s instructions . We compared our proteomic dataset with several comprehensive proteomic studies performed in Echinococcus granulosus [26] , E . multilocularis [27] , Mesocestoides corti [28] and the theoretical secretome of T . solium [59] . In the case of Echinococcus and Mesocestoides proteomes , the sequences of the identified proteins in those studies were obtained from WormBase ( www . parasite . wormbase . org/ ) . After , those sequences were blasted against the T . solium database ( http://www . genedb . org/blast/submitblast/GeneDB_Tsolium ) . Then , the top-ranked protein was considered the T . solium homologue of a certain Echinococcus or Mesocestoides protein ( the complete list can be found in S6 Data ) . The Animal protocol was revised and approved by the Ethical Committee for the Care and Use of Laboratory Animals at the Institute for Biomedical Research , Universidad Nacional Autónoma de México , under the license number ID 199 which follows the guidelines stated by the National Institutes of Health Guide for the Care and Use of Laboratory Animals .
The proteome of the larval phase of T . solium was a complex mixture of parasite and host proteins . Using a TMT-multiplexed strategy , we were able to identify and quantify over 4 , 200 proteins across the nine cyst samples . Among these proteins , 3 , 368 were identified as parasite proteins , whereas 891 proteins were of host origin ( Fig 1A ) . To our knowledge , this is the largest number of identified and quantified proteins in a multiplex assay for a cestode parasite to date . All the proteins were found across all the samples . More than 99 . 4% of proteins ( including host or parasite ) were identified in the nine samples . However , in the case of proteins TsM_000997700 and TsM_000195700 , single peptides were only present in 8 samples and absent in only one . The protein changes observed between parasites obtained from different hosts and tissues were relatively discrete; the large majority of the identified and quantified cyst proteins remained at similar levels of expression , i . e . , more than 3 , 200 proteins were found within a fold change of -1:1 ( Fig 1B and 1C ) for the SM and CNS cysts of the five pigs analyzed . Quantified host proteins were more variable between cysts from different tissues than between cysts from different pigs , thereby supporting the reproducibility of protein changes across the study ( Fig 1B and 1C ) . However , several parasite and host proteins were enriched for certain tissue localization of the cysts . For example , protocadherin alpha 6 ( P = 0 . 0003 ) , actin type 5 ( p = 0 . 0002 ) , a component of the γ-tubulin complex ( P = 0 . 0001 ) , a subunit of the splicing factor 3A ( P<0 . 0001 ) and a protein associated with microtubules ( P = 0 . 0001 ) , were more abundant for cysts dissected from SM . On the other hand , proteins significantly associated to cysts dissected from the CNS of the pigs included a DNA topoisomerase 1 ( P = 0 . 0001 ) , alanine aminotransferase ( P = 0 . 0002 ) , an aldo-keto reductase ( P = 0 . 0002 ) , dnaJ protein ( P = 0 . 0001 ) , a protein containing a carbohydrate kinase domain ( P<0 . 0001 ) and two hypothetical proteins ( P<0 . 0001 and P = 0 . 0003 ) ( Fig 1D ) . Two groups of host proteins were also found enriched for each tissue localization of the cysts ( Fig 1E ) . Several studies consistently detected intact host proteins in protein extracts of Taeniid parasites [30 , 60–64] . In a recent report , we identified 17 host proteins in the vesicular fluid of T . solium cysticerci [63] . The results reported here , to our knowledge , are by far the largest set of host proteins reported within the tissues and fluids for any cestode parasite , suggesting a highly complex and close contact between the porcine and the cysts proteins . It has been proposed that the host proteins are up-taken through a non-specific mechanism such as fluid phase endocytosis [60] . In our dataset , the host proteins were more variable than cysts proteins , this could be associated with a differential composition of the cysts microenviroment , CNS vs SM ( S2 and S3 Data ) . Gene ontology analysis allowed determining that a diversity of host proteins were present; categories included metabolic enzymes involved in pathways like glycolysis or fructose/galactose metabolism , as well as signaling proteins including those participating in the integrin and ubiquitin-proteasome system . Functions of the uptaken host proteins included RNA binding , chaperones , oxidoreductases , ribosomal and isomerases ( Fig 2A ) , those pathways were also enriched for the skeletal muscle proteome of the pigs [65] , suggesting that the up-taken host proteins reflect the composition of the cysts micro-environment ( S5 Data ) . It has been proposed that the cysts use the up-taken host proteins , including immunoglobulins , as a source of amino acids [66 , 67] . The amino acid composition of the host proteins resulting from cysts obtained from CNS and SM was very similar; the biggest differences were found for aspartic acid and serine , reaching only an increase of 1 . 2% and a decrease of 1 . 5% , respectively ( compared with S . scrofa proteome ) . The similar amino acid composition of up-taken host proteins in CNS and SM cysts is consistent with the concept of an unspecific mechanism for the host protein uptake by the cysts ( Fig 2B ) . We also explored the question of the host proteins tissue localization . Tissue localization studies were carried out to determine the distribution of several host proteins within the cyst’s tissues . We selected host proteins related to iron metabolism in the host: haptoglobin ( Hp ) , hemoglobin ( Hb ) , hemopexin ( Hpx ) , hepcidin and ferritin; other host proteins such as LDL , albumin and IgG , were used for comparison . Two experimental approaches were employed: cyst protein fractionation followed by western blotting and immuno-localization in tissue-sections . Through western blotting we found the majority of host proteins in the vesicular fluid , as well as in the soluble fraction of cyst’s tissue ( Fig 2C ) . Abundant host proteins such as IgG and albumin were detected in the three protein fractions tested ( soluble and insoluble fraction of cyst´s tissue and in the vesicular fluid ) . Hemopexin ( Hpx ) was found in the tissue’s extracts ( soluble and insoluble fractions ) and was not detected in the vesicular fluid; in the case of the insoluble fraction of cysts tissue , the immuno-reactive band was detected at the same molecular weight as the positive control ( serum ) and in the soluble fraction a band with a slightly increased molecular weight was detected . LDL was found present in the cyst’s tissue soluble protein extract and scarce in the vesicular fluid ( Fig 2C ) . In the case of the host proteins related to iron metabolism , the most abundant ones found in the cyst’s tissues were Hp and Hb; for Hp several bands were recognized ( most of the bands were shared with the positive control ) , but others only appeared in the cysts extracts . In the case of Hb , immunoreactive bands were detected in the cysts tissue . After immune-histochemical analysis we found a conspicuous distribution of Hp and Hb in the cyst’s tissues , particularly in tissue surrounding the spiral canal of the invaginated scolex . Hepcidin and ferritin were also found in the cyst’s subtegumentary tissue , but in the case of ferritin in cysts extracts , the immuno-reactive bands had lower molecular weight than the band in serum ( Fig 2C and 2D ) . All tested host proteins ( with the exception of ferritin ) were detected in their expected molecular weight in gels , suggesting that at least a fraction of the protein is intact . This idea was explored further using as a model the uptaken host IgG . IgG was located on the outer surface of cysts in both CNS and SM cysts , with a more intense signal in SM cysts ( Fig 3A ) . This localization was consistent with a previous report [68] . To explore the antibody activity of the uptaken host IgG; we purified host IgG from total saline extracts of SM cysts through affinity chromatography using protein G ( Fig 3B ) . The purity of the isolated pig IgG was evaluated by SDS-PAGE and western blot ( Fig 3C ) . Heavy and light IgG chains were detected at the expected molecular weights ( 50 and 25 kDa ) , suggesting that pig IgG was uptaken intactly . Two assays were performed to test the recognition of T . solium antigens by the purified pig IgG: ELISA and western blot using vesicular fluid ( VF ) or the insoluble fraction of the cysts as parasite antigens and the purified IgG as primary antibody ( Fig 3D ) . The purified pig IgG reacted both , with the VF and the insoluble fraction of cysts antigens in a saturable and specific way . For western blotting , both antigenic fractions , VF and the insoluble fraction reacted with the purified IgG from the cysts ( as shown in Fig 3E ) . As expected , several bands were recognized and were shared with the band obtained using sera from cysticercotic pigs ( Fig 3D ) , indicating that uptaken host immunoglobulins retained their antigen-binding activity . To explore the molecular functions and biological processes of the T . solium proteins identified for each tissue localization , we performed a k-means clustering analysis using a subset of cysts proteins with a significant fold change ( P-value<0 . 01 , n = 261 ) . Two major clusters were identified , one for each tissue localization ( Fig 4 ) . For CNS cysts ( Fig 4A ) , 116 proteins were abundant for parasites of this tissue localization ( compared with SM parasites ) . These proteins were associated with metabolic processes , transport and phosphorylation . In the case of SM cysts ( Fig 4B ) , methylation , signal transduction and microtubule-based processes were the most frequently observed categories . For comparison , 48 proteins with the lowest coefficient of variation that remained in similar levels between cysts from different tissues were selected , including proteins associated with ubiquitination , phosphorylation and mitochondrial processes ( Fig 4C , S5 Data ) . The relevance of those pathways in explaining both preferential localizations of the cysts , in terms of adaptation and survival within the host tissues , deserves future study . As mentioned above , several host and parasite proteins were associated with the tissue localization of the cysts . To investigate more thoroughly that possibility , several previously described antigens ( reviewed in [69] ) were queried for in our database . As shown in Fig 3 , several relevant antigens in cysticercosis ( i . e . , paramyosin , GP50 and a calcium binding protein ) , were more abundant in SM cysts than in CNS cysts ( Fig 5A ) . Moreover , we mined our database to search for other antigens enriched for each tissue localization . The case of the tetraspanin family appeared to be especially interesting as tetraspanins are relevant antigens in schistosomiasis [70] and hydatidosis [71] . Our results showed the expression of five members of the tetraspanin family; of these , two proteins were enriched in the CNS localization and one in the SM localization of the cysts , while the other two have no detectable changes . These proteins: TsM_000744700 and TsM_001075800 were subsequently analyzed ( Fig 5B ) . Initially , the large extracellular loop of these proteins was deduced using several algorithms ( see Materials and Methods ) . In those tetraspanins , the protective domain ( the protein region associated with protection in vaccination trials ) is located within the large extracellular loop [70 , 71] . Therefore , this portion of the protein was analyzed for antigenicity using algorithms for B cell epitope-prediction . Two peptides were chosen from each protein and synthesized through a commercial service ( TsM_000744700: VQGPSDYDGK , NAVQKFECCGVQ; TsM_001075800: YNPNTPEGKGPA , FCCRKDQDCPITE ) ( Fig 5C ) . To explore if these four peptides ( p744700-1 and 2; p1075800-1 and 2 ) were recognized by antibodies in the sera of cysticercotic pigs , two groups of 15 sera ( cysticercotic and non cysticercotic ) from pigs bred in rural endemic areas were used . As shown in Fig 5D , the four peptides were recognized by several infected animals , with the peptide FCCRKDQDCPITE ( p1075800-2 ) having the strongest antibody recognition . The differential abundance of several antigenic proteins ( GP50s , paramyosin , E/S protein M13 , calcium-binding protein , tetraspanins , etc . ) between SM and CNS cysts , provides evidence about the presence of antigens that were enriched for SM or CNS cysts . Our next goal was the identification of highly antigenic tissue-enriched proteins; here we defined a tissue-enriched protein as one with differential abundance between CNS and SM cysts ( p value<0 . 01 ) . The high antigenicity was defined using B cell epitope and antigenicity predictors , see Materials and Methods . First , we selected 261 proteins with a significant fold change ( P value<0 . 01 ) and 48 proteins with the lowest coefficient of variation , for comparison . Those proteins were analyzed through several antigenicity algorithms ( see Materials and Methods and S2 Fig ) . Several proteins were predicted as strongly antigenic by one algorithm ( antigen/epitope content ≥ 70% ) . Another group of proteins was also predicted as highly antigenic by both algorithms , although with a lower antigen/epitope content ( 50% ) ( Fig 6A ) . Using this approach , 40 highly antigenic proteins were identified ( the complete list of proteins can be found in S4 Data ) . To experimentally test the reliability of our antigenic prediction , 10 proteins were selected ( Fig 6A and 6B ) . Of these proteins , four were enriched for CNS cysts , four were enriched for SM cysts and two proteins with a low coefficient of variation between CNS and SM cysts , none of these proteins had been studied before in T . solium . Then , a single epitope was selected for each protein ( selected epitopes had to be predicted by both algorithms ) . After the synthesis of the antigenic peptides ( Fig 6B ) , they were evaluated for antibody recognition by ELISA , using the same two groups of sera mentioned above . For a peptide to be considered as a valid antigen , the difference between the recognition of the cysticercotic and the non cysticercotic pig sera had to be statistically significant . Nine of 10 peptides ( with the exception of one based on pinin ) were significantly recognized by the sera from cysticercotic , in comparison with the sera from non cysticercotic pigs ( Fig 7 ) . These data , suggest that the proteins from which the peptides were originated are immunologically recognized in porcine cysticercosis; then we have identified several tissue-enriched antigens; interestingly , a peptide that was enriched for SM ( p165800 ) and other for CNS ( p223100 ) cysts , produced the highest difference between the cysticercotic and non cysticercotic pig sera ( Fig 7A and 7B ) . The recognition by the IgG present in the sera of cysticercotic pigs , suggested that there is a subset of tissue-enriched antigens for cysts located in different host tissues . However , whether the rest of the predicted antigenic proteins are valid antigens in cysticercosis requires further screening . The tissue-enriched antigens could be exploited for the improvement of current diagnostic tools for cysticercosis . A diagnostic test for cysticercosis would ideally include antigenic determinants for each possible tissue localization of the cysts , as well as antigens that are not affected by the tissue-localization of the cysts . To explore the diagnostic potential of those tissue-enriched antigens , several combinations of peptides were used in mixtures . The initial mixture was made using the peptides that were previously found to produce the highest optical densities , when tested separately with the same cysticercotic pig sera: p223100 , p165800 , p1075800-2 and p239000 ( 1: 1: 1:1 ) ; two concentrations were employed ( Fig 8 ) . As shown in Fig 8A , the lowest concentration produced better results . However , not all sera from the cysticercotic animals produced a significantly positive reaction when compared with the non cysticercotic pig’s sera . Other combinations of synthetic peptides were also tested , including a mixture of the 14 peptides that produced the worst performance ( Fig 8B ) . We also tested combinations of peptides from SM-abundant proteins ( Fig 8C ) , or/and SM constitutive proteins ( Fig 8D ) . Interestingly , when the mixture included the best peptide for each tissue localization , p223100 for CNS and p165800 for SM , 14 out of 15 cysticercotic and non cysticercotic pig sera were clearly differentiated ( Fig 8E ) . However , we were not able to improve the performance obtained using the two crude protein extracts from the cysts , indicating that the 'ideal' antigenic subset will require further investigation . In this study , each pig showed a differential response for each peptide and peptide mixture ( Fig 8F ) ; the idiosyncrasy of individual humoral host immune responses against T . solium cyst antigens is well known [3] , as it is in other infectious diseases [72–74] . In addition , the considerable genetic/antigenic variation between cysts obtained from different endemic areas it is frequently reported [75–77] . The immuno-diagnosis of an infectious disease is often performed using a single antigen , i . e . , using a single protein/peptide or antibody to discriminate between healthy and infected hosts . In the case of infections caused by E . granulosus , the use of AgB and 8 kDa proteins have been tested as diagnostic agents . However , new methodological approaches are needed for parasite infections such as schistosomiasis , echinococcosis and cysticercosis , to discriminate between infected hosts with low-parasite loads [1 , 2; 78 , 79] . A novel approach involves the machine-learning models that have proven useful in the diagnosis and prediction of several diseases . Several algorithms have been developed for the diagnosis of breast [80] , colorectal [81] and non-small cell lung cancer [82] . Distinct antigenic response patterns ( ARP ) may constitute better representations of the pathogen’s fingerprints than single-peptide responses . Thus , a multi-antigenic peptide testing ( MAPT ) can identify such ARP for each infection . To explore the viability of a MAPT using our synthetic peptides , we constructed an antigen response space ( ARS ) , where each individual is represented by a single point . The position of each individual point ( one pig’s serum ) depends of its antigenic response to several peptides . For k antigenic peptides considered , k OD measures determine the individual position in ARS . In this sense , an ARP can be defined as a particular region in ARS where all infected hosts are present . Machine-learning algorithms can be directly used to identify boundaries of such regions . It should be noticed that a given ARS could represent a corresponding antigenic peptide subset . To explore the potential of the synthetic peptides to define an ARS for pig’s cysticercosis , all possible combinations of peptides were evaluated . Analysis was performed taking 14 single peptide measures , 5 peptide mixtures measures , and a combination of both . Thus , 16 , 383 , 31 and 524 , 287 possible ARS representations were evaluated in each case . Evaluations were performed with leave-one-out cross validation and a support vector machines as a classifier ( see Materials and Methods ) . Number of errors achieved ( expressed as percentage ) by the best and worst combination for all possible number of peptides were used simultaneously for ARS constructions . As depicted in Fig 9A–9C , the use of peptide combinations usually produced better results than individual peptides . For comparison , we produced an image of ARS using peptide combinations and cysts protein extracts ( Fig 9D and 9E ) . Using this approach we were able to discriminate infected versus non-infected pigs . This discrimination resulted in a similar performance to the one obtained using complex crude cysts extracts ( Fig 9D and 9E ) . Based on our current preliminary results , developing an accurate immunodiagnostic test for cysticercosis , requires a number of specific antigens from cysts of different tissue localizations within the host , as well of antigens from cysts obtained from different geographical areas . In addition , the use of novel-analytical tools such as machine-learning models , can efficiently discriminate between healthy and infected hosts . In contrast , we tested this approach using sera from non-cysticercotic ( n = 8 ) and neurocysticercotic patients ( n = 12 ) . As expected , our ARS approach produces better results than using a single peptide or peptide mixture . However , sensitivity was about 75% ( S4 Fig ) indicating that selection of adequate peptides/proteins for diagnosis in humans will require separate studies .
Several studies have recently focused on deciphering the proteome in Taeniid parasites . The proteomes of the whole larva , the protoscolex , the pre-adult stage and some immunogenic proteins have being characterized for Echinococcus spp . [83–87] . The proteome of T . solium has been less explored , although the composition of the excretion/secretion products [88] , the proteins of activated oncospheres [89] and a small group of immunogenic proteins have been reported [62] . Moreover , an algorithm for the identification of unique mass spectra for Taeniid parasites has been developed [90] . In addition to the fact that these are still initial efforts , a relevant aspect that remains uncharacterized refers to the proteomic changes associated with the tissue localization of the cysts in the host . Knowing these changes might be essential to understand the tissue preference of the cysts . Although T . solium cysts can establish in a variety of tissues they appear to show preference towards the skeletal muscles and several locations in the central nervous system , including the brain . In this report , we describe the proteome of T . solium cysts obtained from CNS and SM of infected pigs . We used state-of-the-art quantitative isobaric proteomics to identify and quantify more than 4 , 200 proteins in a single assay . This is the largest number of identified and quantified proteins so far described for a cestode parasite . A challenging finding is the high amount of host proteins in all crude extracts of T . solium cysts [60–63] . The presence of intact host proteins in the extracts from cestode parasites has been known for six decades [60–64 , 91] . Some recent reports on Echinococcus spp . proteomics have also identified a variety of host proteins in the protein extracts of this cestode , for example , 43 proteins were identified in the cysts fluid [27] and up to 293 proteins were identified as excretion/secretion ( E/S ) products [59] . In our study , we were able to quantify 891 proteins of host origin , the highest number of host proteins identified for a cestode parasite , which brings back the interest on the role of host proteins in the cyst’s physiology . However , if Taenia spp . contains more host proteins than Echinococcus spp . remains to be elucidated; both studies were performed using different proteomic ( as well as sampling ) strategies . Here , we benefited from high throughput and state-of-the-art multiplexed proteomics that enabled us to identify a significant number of cyst and host proteins . Herein , one out of each five proteins identified resulted of host origin . These identified host proteins are involved in a number of metabolic , physiologic , signaling and regulatory processes for the pig . It is worth remembering that the T . solium genome revealed a greatly simplified organism , lacking a number of metabolic processes ( biosynthesis of amino acids , fatty acids , etc . ) as a result of its evolutionary adaptation to parasitism [14] . It is conceivable that the host proteins present in the cysts ( associated with metabolic and signaling functions ) could play a role for the parasite , beyond being a mere source of amino acids . In the case of E . granulosus , the identified host proteins were also associated with metabolic processes , response to stimuli and regulation of biological processes [26] . It is conceivable that some host proteins retain their function and could play a role on metacestode physiology . In order to explore this idea , we carried out functional assays and tissue localization studies for a group of host proteins . For example , highly abundant host proteins like albumin and IgG were found in all protein fractions obtained from the cysts , indicating that their presence is ubiquitous in parasite’s tissues and fluid . Another example were LDL and hemopexin , which were found in the cyst’s tissue but were scarce in the vesicular fluid . Cestode parasites have a reduced capacity for lipid biosynthesis [14] . In the case of Schistosoma mansoni ( trematode ) , several proteins have been identified as LDL-binding proteins [92 , 93] and LDL was found associated with parasite’s tegument [94] . In our study , we found the LDL protein associated with cysts tissue . However , if Taenia spp . parasites have a subset of specialized proteins to bind and uptake LDL from the host remains to be seen . Hpx was abundant in the cysts tissue extracts , while scarce in the VF; interestingly , in the soluble fraction of cysts tissue , the Hpx band showed a slight increase in the apparent molecular weight , while in the insoluble fraction the band was detected at the same molecular weight as in the control serum . In the case of Hp and Hb , several bands were detected ( especially for Hp ) ; this finding can be explained by the presence of Hp in different forms: the free form , as well as in complexes with Hb . Furthermore , some bands could be the result of Hp/HpHb complex degradation by cysts proteases . We have recently described that intact and functional Hp are present in the cyst’s tissue and could be associated with the iron uptake by the cysts [64] . Here we widen the scope of our investigation on the possible involvement of host proteins in the cyst’s iron metabolism . We carried out tissue localization studies for several host proteins associated with the iron metabolism ( hepcidin , ferritin , hemoglobin and haptoglobin ) . The four proteins were detected in the cyst’s tissue , being Hb and Hp the most abundant and widely distributed within the cysts , suggesting that a relevant portion of iron uptake by the larvae might be supported by these host proteins . Hepcidin is a master regulator of iron metabolism produced by the liver and its active form is a peptide of 25 amino acids . Hepcidin binds to ferroportin and induces its lysosomal degradation , thus decreasing the iron export by the target cell [95] . However , hepcidin signaling appears to be restricted to mammals [96]; at least , no reports about a cestode homologue ferroportin are available; future studies are need to explore the role ( if any ) of hepcidin in cestodes biology . On the other hand , ferritin is considered the major iron storage protein [97] . Using specific antibodies , we found ferritin present in the subtegumentary tissue of cyst bladder wall , suggesting that it could also play a role for the parasite , the bands that were detected in protein extracts of cysts had a decrease in the molecular weight ( compared with the control ) . However , after searching the T . solium genome database for ferritin , we found that the cyst has two homologues with a very similar predicted molecular weight , therefore , host and parasite ferritins appears to be undistinguishable in molecular size ( ≈20 kDa ) . Therefore , it is possible that the immuno-localized ferritin is a combination of host and cysts ferritin stocks . Whatever the source of ferritin is , its localization in close contact with the host tissue suggests that cysts accumulates specialized molecules for iron storage . Albumin appears to be involved in the maintenance of parasite’s osmotic pressure in the vesicular fluid , fulfilling a similar function to the role it plays for the host [61] . In addition , immunoglobulins have been proposed as a source of amino acids for the cysts [66 , 67] . We determined the antigen-binding activity of host IgG purified from total protein cyst’s extracts through ELISA and western blotting , testing their ability to react with cysts antigens using two protein crude extracts . Purified IgG from the cysts showed a clear antibody activity through the recognition of several antigenic bands ( those bands were also shared when sera from cysticercotic pigs were used ) , suggesting that at least a part of the uptaken host IgG were specific antibodies directed against cysts proteins . Several other host proteins could also retain their function . Many other uptaken host proteins could play a physiological role , for the parasite . It could also be that potentially deleterious host proteins are simply removed from the host-parasite interface . Ascertain if the host proteins play functions in the physiology of the cysts is an open area of research that could disclose a number of unexpected results . With respect to the T . solium cysts proteins identified and quantified in our proteomic assays , the changes found between CNS and SM cysts were discrete; more than the 90% of the identified and quantified proteins ( >3 , 100 ) were grouped within a fold change of -1 and 1 . A tissue-enriched protein pattern ( including cysts and host proteins ) was associated to each cysts tissue localization . These protein patterns could represent a homeostatic adaptation to the biochemical conditions in different tissue environments ( SM vs CNS ) . Our dataset was compared with others previous proteomic reports for helminths [26–28; 59] . From our dataset , 167 proteins were considered excretion/secretion proteins ( compared with the T . solium theoretical secretome [59] ) ( S6 Fig , and S6 Data ) . In addition , almost 30% of the T . solium gene products were considered ‘hypothetical’ , meaning that those genes could not be functionally annotated . Among those hypothetical proteins , the expression of 357 proteins was validated here ( S6 Fig and S6 Data ) . After comparison with the proteomes of E . granulosus , E . multilocularis and M . corti , 14 proteins were common to the four cestodes ( S6 Data ) ; those proteins included: a 14-3-3 family member , a fatty acid binding protein , a protein with EGF domain , a lactate dehydrogenase , etc . Indicating that the proteome of cestode parasites are usually highly complex mixtures of parasite and host proteins . The relative consistence of high amounts of host proteins and the relevance of those common proteins identified between the four cestodes need future investigation . After this initial characterization , several antigens were found enriched in the SM localization of the cysts ( paramyosin , a calcium-binding protein , E/S antigens , etc . ) . Similarly , other proteins belonging to different families ( tetraspanins and GP50s antigens ) were also differentially found between CNS and SM cysts . Tetraspanins are integral membrane proteins directly exposed to the host [70 , 71] and have been considered vaccine candidates in several helminth infections [98–100] . However , since tetraspanins are highly polymorphic , vaccination trials have produced controversial results [101] . For T . solium , the tetraspanin family has been poorly characterized , only one member ( T24 ) with a good performance as a diagnostic antigen [102] , has been described . In this report , five members of the tetraspanin family were quantified; two were associated with the CNS localization of the cysts and one with the SM localization . To investigate if those proteins are antigens during cysticercosis , two peptides were chosen from the amino acid sequence of either TsM_000744700 or TsM_001075800 . The four peptides were recognized by antibodies occurring in the sera of naturally infected pigs ( four pigs showed a significant recognition of both proteins ) . The strongest recognition was associated with p1075800-2 , derived from the SM-enriched tetraspanin . Regarding T . solium T24 tetraspanin , glycosylation strongly influenced its antibody recognition [102] . It remains to be seen whether the antibody-recognition of the tetraspanins studied here can be increased using recombinant and glycosylated forms . The diagnostic antigen GP50 , is a GPI-anchored glycoprotein with affinity to Lens culinaris lectin , this protein is a promising candidate agent for the immunodiagnosis of NC . Nevertheless , it showed a poor performance when sera from patients having a single viable cyst in the CNS were tested [103 , 104] . Two GP50 proteins were found among our proteomic data ( S5 Fig ) . The “canonical” GP50 was associated with the SM localization of the cysts , while a “truncated” form was slightly increased in the CNS cysts . The truncated CNS-abundant GP50 lacked a predicted GPI-anchoring site , in addition to less disulfide bonds and predicted N-linked glycosylation sites . A diagnostic test based on the combination of these two GP50s deserves further study . We hypothesized that several tissue-enriched antigenic proteins can be used as markers for the tissue localization of cysts . This idea was explored through a combination of theoretical and experimental approaches . Initially , 261 proteins with significant fold changes were selected for epitope prediction using two algorithms; 40 proteins with high antigenic or high epitope content were found enriched either in SM or CNS cysts . Ten proteins were then selected for experimental testing through the synthesis of a single antigenic peptide chosen for each protein . All peptides were recognized by antibodies in the sera of infected animals , but with great variability . When tested with sera from cysticercotic and non-cysticercotic pigs , 9 out of 19 peptides were significantly recognized ( p value < 0 . 01 ) by the sera from infected animals . The only exception was the peptide derived from a pinin: p455200 . These results support the existence of tissue-enriched antigens . The immunodiagnostic potential of those peptides was also tested: peptides were used alone or in mixtures for recognition by the same group of cysticercotic and non-cysticercotic pig’s sera . The best results were obtained with several peptide combinations; in fact , the best combination included peptides derived from SM and CNS-enriched cysts proteins . This can only be considered as an initial study about the potential utility of tissue-enriched antigens; future studies are being conducted using the full recombinant proteins to increase the sensitivity of the immunodiagnostic tests . A number of antigens have been tested as diagnostic agents . We hypothesized that testing multiple antigens , could produce a better strategy to distinguish between healthy and cysticercotic pigs . A machine-learning strategy was employed and 540 , 701 combinations were analyzed . Peptide mixtures produced better results than individual peptides . Using five mixtures of peptides allowed to discriminate between cysticercotic and non cysticercotic sera . Our results suggested that , at least five different antigenic determinants are required in order to develop an efficient diagnostic test , able to differentiate between the two groups of sera . Unfortunately , as those synthetic peptides were tested with sera from naturally infected pigs , we do not have relevant information about those infections , such as primary vs secondary infection , co-infections , and nutritional status . The tissue-dwelling , larval phase of cestodes is usually characterized by host immunomodulatory activities [105] . The observation that some SM and CNS enriched proteins were recognized by antibodies present in the sera of infected animals , could have implications on our understanding about the modulation of the host immune response by cestode parasites .
High-throughput proteomics using a TMT-multiplexed strategy allowed the identification and quantification of over 4 , 200 proteins across the nine samples of T . solium cysts . The T . solium cyst’s proteome constitutes a mixture of host and parasite proteins ( one of each 5 proteins were of host origin ) . T . solium cysts obtained from either naturally or experimentally infected pigs have several proteins and antigens enriched for SM or CNS localizations . The identified host proteins were highly diverse and were involved in a number of metabolic and signaling processes . Through immuno-localization studies carried out for several host proteins , we found that they are localized in a variety of cysts tissues ( tegumentary or subtegumentary tissues in the bladder wall or in the scolex ) . Other host proteins were detected in the vesicular fluid . Here , we also showed that several host proteins are uptaken intactly , as an example , IgG retained their antige-binding activity . Exploring the functional activity of host proteins in the cyst’s tissue certainly deserves further studies . The parasite’s antigens that were found enriched for a certain tissue , could be used for the design of highly effective immunodiagnostic methods by combining the peptides/proteins derived from SM and CNS enriched antigens . Using several peptide mixtures and machine-learning models we were able to distinguish between cysticercotic and non cysticercotic pigs with an efficiency that is comparable to the current diagnostic methods using complex cyst’s crude extracts , however , the appropriate subset of tissue-enriched antigens remains to be identified . Development of an optimal immunodiagnostic test for human and porcine cysticercosis requires the use of SM and CNS enriched antigens; variation of those antigens in the cysts isolated from different endemic areas remains to be analyzed , though . This assessment could be crucial for the improvement of the current diagnostic tests . Characterization of the antigenic proteins enriched with each tissue localization of the cysts , is worth studying not only for the design of more efficient immunological tests for human and porcine cysticercosis , but also because they could be involved in complex tissue specific immunomodulatory processes . | Human and porcine cysticercosis caused by Taenia solium is a parasite disease still endemic in developing countries . The cysts can be located in different host tissues , including different organs of the central nervous system and the skeletal muscles . The molecular mechanisms associated with the tissue localization of the cysts are not well understood . Here , we described the proteome changes of the cysts obtained from different host tissues from infected pigs using quantitative multiplex proteomics . We explored the diversity of host proteins identified in the cyst’s protein extracts and we also explored the immune-localization of several host-related proteins within the cysts , and propose their possible function . We identified several proteins and antigens enriched for a given tissue localization . Several synthetic peptides designed from these tissue-enriched antigens were tested trough ELISA . Using a combination of peptide mixtures and machine learning technologies we were able to distinguish non cysticercotic and cysticercotic pig’s sera . The tissue-enriched proteins/antigens could be useful for the development of improved immuno-diagnostic tests capable of discriminate the tissue-localization of the cysts . | [
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... | 2017 | Quantitative multiplexed proteomics of Taenia solium cysts obtained from the skeletal muscle and central nervous system of pigs |
Fragile X syndrome ( FXS ) , the leading cause of inherited intellectual disability , is caused by epigenetic silencing of the FMR1 gene , through expansion and methylation of a CGG triplet repeat ( methylated full mutation ) . An antisense transcript ( FMR1-AS1 ) , starting from both promoter and intron 2 of the FMR1 gene , was demonstrated in transcriptionally active alleles , but not in silent FXS alleles . Moreover , a DNA methylation boundary , which is lost in FXS , was recently identified upstream of the FMR1 gene . Several nuclear proteins bind to this region , like the insulator protein CTCF . Here we demonstrate for the first time that rare unmethylated full mutation ( UFM ) alleles present the same boundary described in wild type ( WT ) alleles and that CTCF binds to this region , as well as to the FMR1 gene promoter , exon 1 and intron 2 binding sites . Contrariwise , DNA methylation prevents CTCF binding to FXS alleles . Drug-induced CpGs demethylation does not restore this binding . CTCF knock-down experiments clearly established that CTCF does not act as insulator at the active FMR1 locus , despite the presence of a CGG expansion . CTCF depletion induces heterochromatinic histone configuration of the FMR1 locus and results in reduction of FMR1 transcription , which however is not accompanied by spreading of DNA methylation towards the FMR1 promoter . CTCF depletion is also associated with FMR1-AS1 mRNA reduction . Antisense RNA , like sense transcript , is upregulated in UFM and absent in FXS cells and its splicing is correlated to that of the FMR1-mRNA . We conclude that CTCF has a complex role in regulating FMR1 expression , probably through the organization of chromatin loops between sense/antisense transcriptional regulatory regions , as suggested by bioinformatics analysis .
Fragile X syndrome ( FXS , OMIM #300624 ) , the most studied and best known FRAXopathy , is the leading cause of inherited intellectual disability ( ID ) [1] . FXS is caused by the expansion beyond 200 repeats ( full mutation ) and subsequent methylation of the polymorphic CGG sequence within the 5′ untranslated region ( 5′ UTR ) of the FMR1 gene , an X-linked gene which contains a CpG island in its promoter [2] . The methylation of cytosines of both the expanded CGGs and of the neighboring CpGs , as well as other heterochromatic histone modifications , cause the transcriptional silencing of the FMR1 gene and the lack of the FMRP protein [3] , [4] . FMRP is an RNA-binding protein , which inhibits the translation of messenger RNAs ( mRNAs ) , especially within post-synaptic vesicles of the dendritic spines . Its absence impairs synaptic plasticity , which is thought to be the cause of ID [5] . Previous reports described rare individuals of normal intelligence , carrying a transcriptionally active unmethylated full mutation ( UFM ) [6]–[8] . Cell lines derived from these individuals might reflect the status of FXS cells before epigenetic silencing , that is thought to occur at about 11 weeks of gestation [9] . Indeed , the epigenetic characterization of their FMR1 locus showed histone H3 and H4 hyperacetylation , lysine 4 of histone 3 ( H3-K4 ) methylation , lysine 9 of histone 3 ( H3-K9 ) hypomethylation , lysine 27 of histone 3 ( H3-K27 ) dimethylation and lack of DNA methylation [7] , [8] . This epigenetic status is compatible with an euchromatic conformation of the FMR1 locus , allowing transcription . A similar epigenetic status can be induced by treatment of FXS cells with the DNA demethylating agent 5-aza-2-deoxycytidine ( 5-azadC ) , which also causes histone changes ( hyperacetylation , H3-K4 methylation ) , the latter actually preceding DNA demethylation [4] , [10] , [11] . In accordance with these results , silencing of FMR1 in human embryonic stem cells seems to begin from histone modifications prior to DNA methylation [12] . In FXS cell lines DNA methylation extends further to approximately 1 kb upstream the CGG repeat sequence [13] . In wild-type ( WT ) alleles a zone of transition between methylated and unmethylated sequences was described around 650 to 800 nucleotides upstream the CGG repeat , with CpGs being unmethylated all the way down to the FMR1 promoter . This methylation boundary ( MB ) appears to be lost in completely methylated FXS alleles . The boundary is also conserved in the mouse genome , even if human and mouse are only 46 . 7% identical in the 5′ region upstream the FMR1 gene [13] . Methylation boundary regions are characterized by the presence of binding sites for various nuclear proteins including CTCF ( CCCTC-binding factor ) , the first insulator protein found in mammals [14] . CTCF is a widely expressed nuclear protein , which binds different DNA target sequences through its 11 zinc-finger domains [15] , [16] . It was first discovered as a negative transcriptional regulator , interacting with various sequences in the promoter of the chicken , mouse and human C-MYC oncogene [17] , [18] . Subsequent studies recognized its involvement in several functions , including transcriptional activation or repression , X chromosome inactivation , genomic imprinting , methylation-dependent chromatin insulation and higher-order chromatin organization through the establishment of DNA loops [19]–[22] . CTCF has been implicated in the organization of both the structure of the chromosomal fiber within each individual chromosome and of the chromosome territories within the cell nucleus . Many CTCF binding sites reside within promoters , as well as in inter- and intra-genic regions [23] . The relationship between CTCF binding patterns and DNA methylation is currently unknown . Pre-existing methylation can antagonize CTCF binding in vitro [24]–[26] . A recent study of overall methylation status showed that 98% of CTCF sites were unmethylated in at least one of the 13 cell types tested , confirming an inverse relationship between DNA methylation and CTCF occupancy [27] . Despite that , it is still unclear whether demethylation facilitates subsequent CTCF binding and whether bound CTCF maintains the corresponding domain in an unmethylated status . An important regulatory role of CTCF was described in expanded triplet diseases . Specific binding sites for this protein were recognized flanking the CTG triplet at the DM1 locus of myotonic dystrophy [28] . Recent evidence suggests that both CTCF binding and CpG methylation may contribute to CTG repeats instability [29] , [30] . In a transgenic mouse model for spinocerebellar ataxia type 7 ( SCA7 ) , CTCF regulates ataxin-7 gene expression and is required for SCAANT1 ( SCA7 antisense noncoding transcript 1 ) expression . Loss of SCAANT1 de-represses ataxin-7 sense transcription in a cis-dependent manner and is accompanied by chromatin remodeling [31] . In Friedreich ataxia ( FRDA ) , caused by expansion of a GAA repeat sequence in intron 1 of the FXN gene , CTCF depletion was observed in the 5′ UTR of the mutant alleles . This depletion is associated with high levels of the transcript antisense of FXN ( FAST-1 ) , supporting the hypothesis of an epigenetic silencing of the corresponding “sense” gene [32] . Four CTCF binding sites have been identified within the FMR1 locus , suggesting a role of this protein in the regulation of the gene [33] . In the same report , an antisense transcript of the FMR1 gene ( FMR1-AS1 ) spanning the expanded CGG repeat was identified in normal and premutated alleles , but not in FXS alleles . The authors suggested a possible pathogenic role of FMR1-AS1 in FXS and also in the fragile X tremor-ataxia syndrome ( FXTAS ) associated with premutated alleles . However , they did not study the presence of the antisense transcript in UFM cells . In this paper we investigate the role of CTCF in transcriptional regulation of the FMR1 gene and in chromatin organization of the corresponding locus including the methylation boundary region , in different cell lines derived from normal ( WT ) , FXS and UFM individuals , respectively . Through molecular and bioinformatics approaches we demonstrate that CTCF does not preserve the methylation boundary of the FMR1 locus , but is required for its proper transcription . Significant results were obtained from the further characterization of the rare UFM cell lines by mapping the methylation boundary region and by measuring the FMR1 antisense transcript .
The extended region upstream the CGG repeats described by Naumann et al . [2009] [13] was analyzed in three classes of cell lines ( WT , FXS and UFM ) , both lymphoblasts and fibroblasts . Bisulfite sequencing of the methylation boundary in WT cell lines confirmed the results already reported [13] , with a DNA methylation boundary located at CpG pairs 70–71 in lymphoblastoid cells ( Figure S1A ) and 73–74 in fibroblasts ( Figure S1B ) , respectively . As expected , no boundary was present in FXS cells . Despite the presence of the CGG expansion , the transcriptionally active UFM cell lines retained the methylation boundary as in WT cells , both in lymphoblasts and in fibroblasts ( Figure S1A and B ) . We went on to quantify FMR1-AS1 transcript levels and observed higher levels of transcription in UFM lymphoblasts ( around 6-fold higher ) and fibroblasts ( around 3-fold higher ) compared to WT , while no antisense transcript was detected in FXS cells , as expected [33] ( Figure 1A ) . These results showed that the antisense transcript follows the same expression pattern as the sense RNA [8] . Amplification and sequencing analysis of FMR1-AS1 cDNA in WT and UFM cells confirmed the presence of the splicing corresponding to the intron 1 of the sense transcript ( Figure 1B ) , despite the recognition of a non-canonical AC-CT splice site in the antisense mRNA . Moreover , UFM cells presented a second isoform of antisense transcript , which retained the non-canonical splicing in intron 2 , like in premutation alleles [33] ( Figure 1B ) . Based on FMR1-AS1 data , we may hypothesize a co-regulation mechanism for sense and antisense transcription at the FMR1 locus . CTCF binding sites on the FMR1 gene were previously reported [33] . We now include one additional site obtained from the database available online at http://insulatordb . uthsc . edu/ [34] , designated MR ( methylated region ) site , located at −5557 bp upstream the FMR1 transcription start site . A schematic outline of all CTCF binding sites within the FMR1 locus included in our study is represented in Figure 2 . We first studied the three CTCF binding sites in the promoter and near exon1 , flanking the CGG repeat sequence , and in the intron 2 region , near one of the transcription starting site of FMR1-AS1 in UFM cell lines . ChIP assay results demonstrated the binding of CTCF to these three sites in UFM fibroblasts and lymphoblasts ( Figure 3A–C ) . The level of binding in UFM was significantly higher compared to FXS cells , both fibroblasts and lymphoblasts , in all sites analyzed . In promoter and exon 1 regions lymphoblasts showed similar CTCF binding levels in UFM and WT ( Figure 3A ) , while in WT fibroblasts CTCF binding levels were significantly higher ( p<0 . 05 ) compared to UFM ( Figure 3B ) . In WT cells , we confirmed CTCF binding to the MB site between CpG pairs 66–69 . As expected , no CTCF binding was found in FXS fibroblasts , given the complete methylation of this region . Instead , UFM fibroblasts showed binding levels similar to those of WT cells ( Figure 3D ) , demonstrating that CTCF binding is strictly related with the unmethylated status of FMR1 locus . The MR binding site at −5557 bp corresponds to CpG 98 , which is fully methylated in all cell lines under investigation . Expectedly , we did not detect CTCF binding in any of them , both fibroblasts and lymphoblasts ( data not shown ) . We speculated that after DNA demethylation CTCF might rebind to its sites on the FMR1 locus in FXS cells . Our previous studies demonstrated that treatment of FXS lymphoblastoid cells with the demethylating agent 5-azadC induces FMR1 transcriptional reactivation , consequent to demethylation of the 52 CpGs of the promoter [10] , [11] . After a 7 day-treatment with 5-azadC of a FXS lymphoblastoid line , we did not observe any significant change in cell viability . We obtained a 25% transcriptional reactivation of FMR1 and a related eight-fold increase of FMR1-AS1 transcript ( data not shown ) . However , as indicated in Figure 4 , 5-azadC treatment did not restore CTCF binding to the reactivated FMR1 gene in exon 1 , promoter and boundary region ( MB site ) . After demonstrating that CTCF binds to the FMR1 regulatory region in transcriptionally active cells , we went on to investigate whether CTCF protein had a regulatory function in FMR1 gene transcription . We transfected synthetic siRNAs specific for CTCF transcript into WT and UFM fibroblasts to reduce CTCF mRNA and to verify the effect of this reduction on FMR1 transcription . In each knock-down experiment CTCF mRNA depletion was confirmed by quantitative RT-PCR , in comparison with GAPDH mRNA levels , used as control ( data not shown ) . The CTCF reduction was also confirmed on protein levels both in WT and UFM cells ( Figure 5A ) . The residual CTCF transcription was around 15–20% in both fibroblast lines ( Figure 5B ) . On the other hand , the effect on FMR1 transcription was variable . In about two thirds of all knock-down experiments performed on both cell lines , no modification in FMR1 transcription was observed , while in the remaining third we observed a near 50% reduction of FMR1 transcription , as exemplified in Figure 5B . Interestingly , the FMR1 mRNA decrease was accompanied by a similar reduction of the FMR1-AS1 transcription in both cell lines ( Figure 5B ) . We also found that CTCF knock-down coupled with FMR1 reduction resulted in lower levels of CTCF bound to the FMR1 sites in the promoter and exon 1 of WT cells ( Figure 6 ) . In those CTCF knock-down experiments in which FMR1-mRNA remained unmodified , ChIP assay demonstrated no variation in CTCF binding at the promoter and exon 1 in WT as well as in UFM cells ( Table 1 ) . The next step was to establish whether overexpression of CTCF transcript could affect the transcription of FMR1 . This was accomplished by transfecting a plasmid containing the variant 1 of human CTCF open reading frame into WT , UFM and FXS fibroblasts . The levels of overexpression ranged from 40 to 180 folds compared to the untreated controls , as confirmed by qRT-PCR ( Figure 7A ) . Even in presence of the highest CTCF overexpression , the level of FMR1 transcript remained substantially unmodified in all cell lines analyzed ( Figure 7B ) . To understand the molecular events underlying the variable results of CTCF knock-down experiments , we investigated the DNA methylation status and the chromatin organization of the FMR1 locus after CTCF depletion coupled with FMR1 reduction in WT and in UFM fibroblasts . Surprisingly , when we analyzed the methylation of promoter CpGs by bisulfite sequencing , all 52 CpGs were found unmethylated , as in the untreated controls . We extended our observation to the upstream region , observing that the methylation boundary persisted after CTCF depletion and FMR1 transcript reduction ( Figure 8A and B ) . Therefore , CTCF knock-down did not induce the spreading of methylation from the boundary to the FMR1 promoter region , even in presence of a CGG expansion ( Figure 8B ) . On the other hand , FMR1 transcriptional reduction was found to correlate with histone epigenetic changes . In fact , in those experiments in which CTCF knock-down did not correlate with FMR1 reduction , no variation of epigenetic marks ( i . e . methylation of H3-K4 and H3-K9 ) was observed in the promoter and exon 1 of WT fibroblasts ( Table 1 ) . Instead , in those experiments in which CTCF knock-down correlated with FMR1 transcript reduction , we observed a decreased methylation of H3-K4 in both regions analyzed ( promoter and exon 1 ) and increased methylation of H3-K9 in the promoter region , compared to the untreated WT cells ( Figure 9 ) . These changes are representative of a more heterochromatic configuration of the locus , correlating with the reduction of FMR1 transcription . Our data support a mechanism of transcriptional co-regulation between FMR1 sense and antisense , supporting a different role for CTCF protein rather than that of insulator . Based on the variability of FMR1 transcription after CTCF knock-down , we shifted our focus on the role of this protein as chromatin organizer particularly in the loops formation . In order to explore the possibility that CTCF bound to its sites near the FMR1 gene transcription start site ( TSS ) shapes regulatory chromatin loops , we performed a statistical and computational analysis of DNA structural properties of known regulatory loops determined by 5C experiments [35] , compared to those of control genomic regions , and trained a machine learning algorithm to discriminate between real and control DNA loops ( Text S1 and Figure S2 ) . All putative CTCF-mediated loops in the proximity of the FMR1 gene TSS were tested in silico , pairing the CTCF binding sites illustrated in Figure 2 . We simulated the CGG expansion by adding 200 CGG triplets to the 5′UTR of the FMR1 gene . The results of this predictions are reported in Table 2 . All loops involving the intron 2 binding site , in which a FMR1-AS1 transcriptional start site was identified , were predicted with high confidence both in WT and in the expanded allele . The in silico analysis excluded loops formation between exon 1 and all the other CTCF binding sites .
Emerging evidence underlines the dynamic status of the chromatin , previously thought to be static , showing that a given region may be condensed ( heterochromatin ) and decondensed ( euchromatin ) , according to the cell needs for transcriptional activity of that region . The discovery of proteins capable of establishing physical , as well as functional connections among distant genomic regions , even among different chromosomes , adds complexity to an already intricate network of gene-gene interactions . CTCF can be considered a leading candidate mediating these complex interactions [14] . In fact , it plays different roles in a gene-specific and context-specific manner depending on the possibility of creating homodimers and heterodimers with other proteins , such as cohesin , RNA Polymerase II and Parp1 [36]–[38] . CTCF was the first protein to be identified with a role of insulator , involved in the maintenance of the methylation boundaries in mammals [21] . Recently a methylation boundary region , which seems to prevent methylation to spread downstream , was reported in WT cell lines approximately 1 kb upstream the FMR1 gene promoter , but not in FXS cells [13] . Other regions with this function were described in the myotonic dystrophy gene DMPK , in the ICR ( Imprinted Control Region ) of IGF2 and in the neighboring BLU and RASSF1A loci of the 3p21 . 3 gene cluster region [30] , [24] , [39] . Triplet repeat expansion disorders often undergo transcriptional regulation by the CTCF protein , suggesting a role of CTCF also in FMR1 gene transcriptional regulation . Binding sites for CTCF in the FMR1 locus were already identified [33] , and now confirmed by our study , particularly in the promoter , exon 1 and intron 2 , in which is located one of the transcriptional start site of the FMR1-AS1 . We firstly showed that these three sites are bound to CTCF in UFM cells , both lymphoblasts and fibroblasts , and the binding level is quite similar to WT cells . These latter cell lines showed differences in CTCF binding in the two cell types analyzed ( lymphoblasts and fibroblasts ) and these variations should be related to differences between primary fibroblasts and Epstein-Barr-transformed and clonal lymphoblasts , as previously observed for other chromatin marks [4] , [8] , [27] . A CTCF binding site located in the FMR1 methylation boundary was already described [33] . We now demonstrate for the first time the existence of the methylation boundary in UFM cells , supporting the hypothesis of a regulatory role played by the boundary region in preventing gene silencing . Interestingly , the CTCF binding site located in this border region , between CpG pairs 66 and 69 in WT cells , was also observed in UFM cell lines , but not in FXS cells , as expected given the CpGs methylation status of the latter . We then tried to restore CTCF binding to the FMR1 gene in FXS cell lines by inducing DNA demethylation with 5-azadC . DNA demethylation resulted in FMR1 transcription reactivation as expected , while CTCF binding to its specific sites on promoter , exon 1 and boundary region was not restored . This result might be explained by failure of drug-induced DNA demethylation to reverse all modifications that occur during gene silencing . As observed on p16 and MLH1 gene , 5-azadC treatment did not completely restore normal histone code and post-translational modifications of DNA binding proteins to reestablish long-term expression [40] , [41] . We previously observed that transcriptionally reactivated FXS cell lines restored epigenetic changes consistent with an euchromatic status , without fully reaching the euchromatic configuration typical of normal control cell lines [4] . We also demonstrated that 5-azadC-induced demethylation is partial and transient . After 4 weeks from 5-azadC withdrawal , the FMR1 promoter resumed its methylated status [11] . Therefore it can be inferred that CTCF binding , even if it occurred after 5-azadC demethylation , would not by itself sufficient to maintain the unmethylated status of the FMR1 gene . These data seemed to suggest a functional role of the CTCF protein in regulating FMR1 gene transcription . To investigate this potential role , we induced both silencing and overexpression of CTCF transcript . In those experiments in which siRNA-mediated CTCF knock-down did not correlate with FMR1 transcript reduction , epigenetic marks ( CTCF binding , H3-K4/H3-K9 methylation ) were unmodified in promoter and exon 1 regions . On the other hand , the level of CTCF protein still bound to the gene was found reduced in CTCF knock-down experiments coupled with FMR1 mRNA reduction . Moreover , FMR1 decreased expression correlated with increased levels of heterochromatinic marks , such as H3-K4 demethylation and H3-K9 hypermethylation in the 5′ UTR of the gene . Interestingly , these epigenetic changes , known to favor heterochromatinic configuration , were not followed by the spreading of DNA methylation from the boundary region towards the FMR1 promoter , not only in WT alleles , but also in UFM alleles , suggesting that a CGG expansion is not by itself sufficient to induce methylation , even in absence of CTCF . This latter result implies that CTCF does not work as an insulator at the FMR1 locus . Therefore , other still unknown proteins must act as barrier elements in this specific region , as already hypothesized [13] . There are a number of boundaries that may function in a CTCF-independent manner through the binding of proteins known to act as transcriptional regulators , such as USF1 [42] , YY1 and EVI1 , or through non-coding RNAs [43] . Particularly , USF1 is one of the major transcription factors that bind the FMR1 promoter region . Its binding is partially inhibited by DNA methylation and it might be a hypothetical candidate as insulator for the FMR1 gene [44] . Interesting results came from the FMR1 antisense transcript characterization , particularly in UFM cell lines , both before and after CTCF transcriptional silencing . The FMR1 antisense RNA is transcribed starting from the second intron of the gene in WT and premutated alleles [33] . We detected , for the first time , FMR1-AS1 RNA in UFM cell lines and also showed that the levels of this antisense transcript were higher in UFM cells , compared to normal controls , similar to what happens with the sense transcript [7] . The antisense transcript splices a 9 . 7 kb intron corresponding to the FMR1 intron 1 , that uses the complementary splice donor and acceptor to FMR1 , representing a non-consensus CT to AC splice site . Moreover we observed in UFM cells the same splicing variant of the FMR1-AS1 previously described as premutation-specific alternative splicing in intron 2 that also uses a non-consensus CT-AC splice site [33] . Furthermore , after CTCF depletion the reduction of FMR1 mRNA was always coupled with the decrease of FMR1-AS1 transcript . These data indicated a co-regulation of transcription and splicing mechanisms at the FMR1 locus in transcriptional active alleles . On the other hand , CTCF knock-down did not have always the same effect: in only one third of all the experiments we observed a diminished transcription of both sense and antisense FMR1 . These results suggested a partial and/or indirect role of CTCF in regulating FMR1 expression and led us to hypothesize that the sites located within the FMR1 locus may form chromatin loops mediated by CTCF homodimers capable of bringing in close proximity molecular machineries for transcription , splicing and epigenetic modifications . The formation of these loops would be partially affected by CTCF knockdown but not by CTCF overexpression , i . e . additional CTCF protein would not affect loop formation [45] , [46] . Loss of CTCF-mediated chromosomal organization through disruption of this loop could exert a negative effect on FMR1 transcription . On the other hand , it would seem that other factors , yet to be identified , could activate self-preserving mechanisms that maintain FMR1 transcription unchanged despite the absence of the loop , as observed in a fraction of our experiments . Indeed , how chromatin configurations may influence gene expression still remains unclear . The “loop” hypothesis was supported by antisense transcription data , as well as by CTCF depletion/overexpression experiments . The presence of a CTCF binding site in FMR1 intron 2 , near one of the transcription starting sites of FMR1-AS1 , previously observed by Ladd et al . [33] , was confirmed in our cell lines by ChIP assays . Our hypothesis was that this CTCF site is involved in the chromatin looping together with one of the 5′-UTR sites within the active FMR1 gene both in normal and in the expanded alleles , such as UFM . This loop may not form after 5-azadC-induced demethylation , which cannot reestablish native epigenetic modifications . In fact , as previously observed , 5-azadC effect is only transient [11] . The region surrounding the FMR1 promoter ( approximately 50 kb ) was previously studied through 3C technique , which demonstrated reduced interaction frequencies [47] . This work did not take into account the behavior of the chromatin region surrounding the active FMR1 gene with CGG expansion , such as in premutation and UFM cells . The 3C technique is only capable of detecting chromatin loop interactions greater than 10 kb and for this reason a chromatin loop formation in our region of interest cannot be excluded . We investigated the possibility of looping between CTCF sites using an in silico analysis of DNA structural characteristics of experimentally validated DNA regulatory loops . For this purpose , we elaborated a new predictor system that showed good performances in discriminating between real loops and control genomic regions . This predictor ( SVM ) confirmed that putative loops can form involving the CTCF binding site in intron 2 , both in WT and in expanded alleles . The bioinformatics approach takes into account parameters concerning the nucleotide sequence but not molecular and epigenetic characteristics , such as DNA methylation . In silico data should be interpreted considering the biological context in which the FMR1 gene is located . Therefore , loop formation in FXS alleles was excluded by the existence of DNA methylation of the entire region upstream the FMR1 promoter , that prevents CTCF from binding its sites . The formation of loops between intron 2 and MR sites could also be excluded because the MR site is located in a region that is extensive methylated in WT and in expanded alleles . Our in silico results affirmed that a chromatin loop mediated by CTCF homodimers can exist between intron 2 and the methylation boundary region or promoter in normal and UFM alleles . These bioinformatics data will deserve further experimental validations . In conclusion our results delineate a role for CTCF as transcriptional regulator of FMR1 expression through chromatin organization . CTCF was firstly described as the only known insulator [48] , but we show that it does not act as an insulator on the methylation boundary upstream the FMR1 gene . A role of CTCF in genome and locus organization acting to secure long-range intra- and inter-chromosomal interactions was abundantly described [22] . Our results define an indirect role for CTCF in modulating bidirectional transcription through FMR1 locus chromatin organization and loop formation . Indeed , reduction of FMR1 sense and antisense transcription after CTCF depletion underscores the importance of the CTCF-mediated loop complex . This study will be help in further clarifying the processes by which cell type specific patterns of gene expression can be established and maintained .
Lymphoblastoid cell lines were established by Epstein–Barr virus transformation from peripheral blood lymphocytes of FXS , UFM and normal control ( WT ) males . The FXS cell lines employed in these experiments were E3 and S1 , with 250 and 450 CGGs , respectively; the UFM cell line ( MA ) contains 265–430 CGGs [8]; two different WT cell lines obtained from normal control males . Lymphoblasts were grown in RPMI1640 medium ( Sigma Aldrich ) supplemented with 20% fetal bovine serum , 2 . 5% L-glutamine and 1% penicillin/streptomycin at 37°C with 5% CO2 . Primary fibroblast cultures were obtained from skin biopsies derived from the UFM individual ( MA ) . We have also employed one FXS line ( GM04026 ) and three WT lines ( GM05381 , GM03349 and GM07492 ) , provided by the Coriell Institute ( Camden , USA ) . Fibroblasts were grown in BIO-AMF2 complete medium ( Biological Industries ) . FXS lymphoblasts were treated with the demethylating agent 5-azadC ( Sigma-Aldrich ) , as previously described [10] . Cells were seeded at 7×105 cells/ml and 5-azadC was added daily at 1 µM ( final concentration ) for 7 days . At the end of the treatment , cells were harvested to measure viability with the propidium iodide method ( Nucleocounter , Sartorius/Stedim ) and to perform RNA and DNA extraction . Knock-down of CTCF transcripts was carried out in UFM and in all three WT fibroblast lines with synthetic siRNAs ( Dharmacon , USA ) . Complete sequences of the siRNAs are listed in Table S1 . Negative control to check the efficiency of CTCF depletion was performed using scramble siRNA ( IDT ) . In accordance with the protocol of the manufacturer , 40 nM of siRNA were transfected by Lipofectamine RNAiMAX ( Invitrogen , USA ) and cultures were harvested after 72 hours . The human open reading frame of CTCF was transfected into the cells through the expression plasmid pCMV6-Entry ( C-terminal Myc- and DDK-tagged ) ( Origene ) . 100 ng of plasmid DNA was transfected in fibroblasts with Lipofectamine 2000 ( Invitrogen , USA ) and cells were collected after 48 h , according to manufacturer's instructions , and after 120 h to asses if a longer overexpression could affect FMR1 transcription . Proteins extracted from untreated and siRNA-treated WT and UFM fibroblasts were resuspended in Laemli buffer , boiled , separated on 8% polyacrylamide gel electrophoresis , transferred to Hybond-ECL membrane ( GE Healthcare ) , immunostained and visualized after film exposure using the ECL Western Blotting Kit ( GE Healthcare ) , according to the manufacturer . Primary antibodies were used at the following concentrations: 1∶1000 anti-CTCF rabbit policlonal antibody ( Millipore ) and 1∶10000 anti-GAPDH mouse antibody ( Sigma-Aldrich ) . Genomic DNA was isolated from siRNA-treated and untreated fibroblasts both WT and UFM by DNeasy Blood & Tissue kit ( Qiagen ) The DNA concentration was checked both by absorbance measurements at 260 and 280 nm and on agarose gel . Bisulfite DNA transformation was performed as previously described [11] . Each transformed DNA was amplified in 7 independent PCR reactions , then pooled and recovered from the agarose gel with the StrataPrep DNA Gel extraction kit ( Stratagene ) . The purified PCR products were cloned with the StrataClone PCR cloning kit ( Stratagene ) , according to the manufacturer's instructions . After bacterial plating and overnight incubation at 37°C , white colonies were picked and plasmid DNA was extracted . After a pre-screening of the clones with PCR using specific plasmid primers ( M13 forward and reverse ) , amplification products were sequenced in both directions with BigDye Terminator v3 . 1 Cycle Sequencing kit ( Applied Biosystems ) on a 3130 Genetic Analyzer ( Applied Biosystems ) . The modified primers are those described by Naumann et al . [13] . Total RNA was extracted by TRIzol ( Invitrogen , USA ) . RNA concentration and purity were checked on agarose gel and by UV spectrophotometer . RNA samples were treated with TURBO DNA-free DNase ( Ambion ) to remove contaminating DNA . Afterwards , 1 µg of total RNA was retro-transcribed into cDNA by MoMLV-RT ( Invitrogen , USA ) using random hexamers . For a relative quantification of each transcript , the following pre-developed TaqMan assays ( Applied Biosystems ) were used: CTCF ( Hs00902008_m1 ) , GAPDH ( 402869 ) , FMR1 ( Hs00233632_m1 ) . For FMR1-AS1 , custom-made assay was designed ( ASFMR1F 5′-CCTCTGCCAACTCAGTGCTATTAG-3′; ASFMR1R 5′-CATGACCTAGTCTGGGGTGGAG-3′; ASFMR1Probe 5′- ( FAM ) -TGGAATCATCTCCCC- ( TAMRA ) -3′ ( Applied Biosystems ) , according to Ladd et al . [33] . The real-time RT-PCR was performed on a ABI7900HT ( Applied Biosystems ) . The cycle parameters were: 2 minutes at 50°C and 10 minutes at 95°C , followed by 40 cycles with 15 seconds at 95°C ( denaturation ) and 1 minute at 60°C ( annealing/extension ) . To analyze the FMR1-AS1 transcript , cDNA was generated using specific primers , with a linker ( LK ) sequence: 5′-CGACTGGAGCACGAGGACACTGA-3′attached to the 5′ end . Primers were those employed by Ladd et al . [33] . cDNA was produced using Superscript III ( Invitrogen ) , according to the manufacturer instruction's . PCR were performed using the LK primer ( as forward ) and antisense specific reverse primers . The amplicons were sequenced on an 3130 Genetic Analyzer ( Applied Biosystems ) . ChIP assay was performed according to the manufacturer ( Upstate Biotechnology , USA ) . After 10 minutes at 37°C with 1% formaldehyde , cells were seeded and washed with 1× PBS and Protease Inhibitor Cocktail ( Sigma-Aldrich ) . To obtain 200–1000 bp DNA fragments , cell pellets were sonicated . Histone methylation analysis was performed using two different antibodies against dimethyl lysine 9 ( H3-K9 , 07–441 , Upstate Biotechnology ) and dimethyl lysine 4 ( H3-K4 , 07–030 , Upstate Biotechnology ) on histone 3 . Binding of CTCF protein was assayed using the specific antibody ( 07-729 , Millipore ) . In each ChIP assay antibody against rabbit IgG ( 1862244 , Thermo Scientific ) was employed and also no template control was included . Immunoprecipitated DNA ( IP-DNA ) was extracted by standard procedure ( phenol/chloroform/isoamilic alcohol 25∶24∶1 ) and then quantified by real-time PCR ( ABI7900HT , Applied Biosystems ) using fluorescent probe and primers specific for both FMR1 and HPRT . Primers and probes employed for PCR analysis are listed in Table S2 . Standard curves for the three FMR1 and for the single HPRT amplicon were constructed with five different DNA dilutions of known concentration ( X axis = log[X] ) and the corresponding Ct values ( Y axis ) . The unknown amount of methylated histone and CTCF-binding IP-DNA of FMR1 and HPRT ( X axis = log[X] ) was calculated from Ct values , through the standard curve plot . Normalized FMR1 levels were estimated dividing the amount of FMR1 IP-DNA by the amount of HPRT IP-DNA . All variables were analyzed by means of descriptive statistics ( mean , median , standard deviation and standard error of mean ) . Data were analyzed with non-parametric statistical Kruskal-Wallis test and with K sample test . The level of significance was set at p≤0 . 05 . Data analysis was performed using STATA Intercooled v . 9 . 2 software ( Stata Co . ; College Station , Lakewag , TX , USA ) . In order to analyze the structural characteristics of CTCF-mediated DNA loops , a bioinformatics approach was developed and is detailed in the Text S1 . Briefly , a machine learning method was trained to recognize known chromatin loops from control genomic regions , and then used to test putative regulative loops in the proximity of FMR1 transcription start site . Supplementary Data are available online: Supplementary Figures S1 , S2 , Supplementary Tables S1 , S2 , Supplementary Text S1 and Supplementary References S1 [34] , [35] , [49]–[58] . | Fragile X syndrome is the most common cause of inherited intellectual disability , accounting for about 1∶3000 males and 1∶4000 females . It is caused by a dynamic mutation of FMR1 , a gene mapping on the X chromosome and containing a CGG repeat in its promoter region . Expansion of this unstable sequence beyond 200 repeats ( full mutation ) is followed by DNA methylation and histone changes , leading to the transcriptional inactivation of FMR1 and to the lack of the FMRP protein . Recently , an antisense transcript ( FMR1-AS1 ) spanning the CGG repeats and a region of transition of DNA methylation ( boundary ) located upstream of the CGG repeats have been identified in transcriptional active FMR1 alleles . Several nuclear proteins bound to the methylation boundary have been described , such as the zinc-finger protein CTCF , the first known insulator in mammals . This protein is an important transcriptional regulator of genes harboring trinucleotide repeats and it is mostly active in chromatin organization . For the first time , we have investigated the role of CTCF protein in the transcriptional regulation of the FMR1 gene . Our results define a complex role for CTCF acting through chromatin organization of the FMR1 locus . | [
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] | 2013 | Role of CTCF Protein in Regulating FMR1 Locus Transcription |
Rotifers of Class Bdelloidea are remarkable in having evolved for millions of years , apparently without males and meiosis . In addition , they are unusually resistant to desiccation and ionizing radiation and are able to repair hundreds of radiation-induced DNA double-strand breaks per genome with little effect on viability or reproduction . Because specific histone H2A variants are involved in DSB repair and certain meiotic processes in other eukaryotes , we investigated the histone H2A genes and proteins of two bdelloid species . Genomic libraries were built and probed to identify histone H2A genes in Adineta vaga and Philodina roseola , species representing two different bdelloid families . The expressed H2A proteins were visualized on SDS-PAGE gels and identified by tandem mass spectrometry . We find that neither the core histone H2A , present in nearly all other eukaryotes , nor the H2AX variant , a ubiquitous component of the eukaryotic DSB repair machinery , are present in bdelloid rotifers . Instead , they are replaced by unusual histone H2A variants of higher mass . In contrast , a species of rotifer belonging to the facultatively sexual , desiccation- and radiation-intolerant sister class of bdelloid rotifers , the monogononts , contains a canonical core histone H2A and appears to lack the bdelloid H2A variant genes . Applying phylogenetic tools , we demonstrate that the bdelloid-specific H2A variants arose as distinct lineages from canonical H2A separate from those leading to the H2AX and H2AZ variants . The replacement of core H2A and H2AX in bdelloid rotifers by previously uncharacterized H2A variants with extended carboxy-terminal tails is further evidence for evolutionary diversity within this class of histone H2A genes and may represent adaptation to unusual features specific to bdelloid rotifers .
Rotifers of Class Bdelloidea are freshwater invertebrates of widespread occurrence that have attracted particular interest because their apparent lack of both males and meiosis suggests they are ancient asexuals [1] . Bdelloids are also of interest because of their extraordinary ability to survive and continue reproduction after desiccation at any life stage [2] , [3] and doses of ionizing radiation that cause hundreds of DNA double-strand breaks ( DSBs ) per genome [4] . In contrast , rotifers of their sister class , the facultatively sexual monogonont rotifers , can survive desiccation only at a specific stage in their life cycle , as resting eggs [5] , [6] , and are not unusually resistant to ionizing radiation [4] . Since the H2A histones and some of their variants are well conserved in other eukaryotes and are involved in DSB repair and in certain meiotic processes [7] , we speculated that bdelloid H2A histones may be unusual . In order to test this expectation , we investigated histone H2A genes and proteins of two species of bdelloid rotifers , Adineta vaga ( A . vaga ) and Philodina roseola ( P . roseola ) , which represent two distantly related families within the Class . Histones are architectural proteins that package eukaryotic DNA into nucleosomes , being essential in the maintenance , expression , and replication of the genome . The genes coding for the four canonical histones , H4 , H3 , H2B and H2A , which make up the nucleosome , are expressed during the S-phase of the cell cycle when the nuclear DNA is synthesized and are clustered in most metazoan genomes . These replication-dependent histone genes typically do not contain introns in animals and their mRNAs represent the only known cellular mRNAs that are not polyadenylated , ending instead in a highly conserved stem loop . The processing step in replication-dependent histone mRNA biosynthesis is a 3′-end endonucleolytic cleavage between the stem-loop and a so-called histone downstream element ( HDE ) [8]–[11] . In contrast , replication-independent histone genes encode variants of the canonical histones that are found outside of histone gene clusters and are expressed throughout the cell cycle . These variant histone genes may contain introns and their transcripts are polyadenylated [12] . Of the histone proteins , the H2A family includes the largest number of described variants and displays the greatest degree of diversity in carboxy-terminal tail length and sequence [12] , [13] . One of these variants , H2AX , of wide occurrence in eukaryotes , is characterized by a unique and invariant C-terminal SQ ( E/D ) Φ- ( end ) motif , where Φ indicates a hydrophobic residue . It has been demonstrated , primarily in yeast and mammals [14] , [15] , that this highly conserved motif of H2AX is a consensus sequence for serine phosphorylation by PI3 kinases and that the serine residue is always located four amino acids from the C-terminal residue . In response to DSBs , H2AX becomes phosphorylated at this serine over large regions ( ∼2 Mb ) surrounding the sites of breakage . Although the mechanistic implications of phosphorylation of the SQ ( E/D ) motif in H2AX are not fully understood , it is apparently required for normal DSB repair throughout the eukaryotic kingdom , being involved in the retention and accumulation of repair and checkpoint proteins to DNA breaks [for review] , [ see 7] , [14]–[19] . Moreover , it has been demonstrated in several eukaryotes that phosphorylated H2AX also plays a role in meiotic processes , including repair of meiotic DNA breaks made by SPO11 [20]–[23] , prophase meiotic sex chromosome inactivation [23]–[25] and telomere movement [26] . With the exception of the nematode Caenorhabditis elegans , which lacks H2AX , it is ubiquitous throughout eukaryotes while the fruit fly Drosophila melanogaster has a H2AZ/H2AX chimeric H2A named H2AvD [16] . Considering the extreme radiation resistance of bdelloid rotifers [4] and the likelihood that , as in Deinococcus radiodurans , such resistance is an adaptation to repair and survive damage associated with desiccation including extensive DNA breakage [27] , [28] , one might expect in these organisms a high percentage of nucleosomal core H2A to be replaced by H2AX . For example in Saccharomyces cerevisiae , canonical H2A is replaced by H2AX and high levels of homologous recombination ( and thus double strand breaks ) occur [29] . Instead , we found that none of the H2A genes in the two bdelloid species have the H2AX-defining SQ ( E/D ) motif two amino acids from the C-terminal end and none of the bdelloid H2A genes is similar to canonical H2A . The absence of H2A and H2AX in bdelloid rotifers contrasts with their ubiquitous presence in other eukaryotes and with the presence of canonical H2A in the monogonont rotifer Brachionus plicatilis ( B . plicatilis ) . The three different types of H2A genes we found in bdelloid rotifers are apparently unique to bdelloids and form distinct lineages that evolved from canonical H2As . We also found that the regions of the genome containing histone gene clusters are organized as two co-linear pairs , consistent with the degenerate tetraploidy of bdelloid rotifers [30] , [31] , with one pair lacking an H2A gene in the cluster while the other cluster contains an H2A gene , designated H2Abd , that has an unusual C-terminal tail . Although present in a cluster containing the canonical H4 , H3 and H2B genes , it is not H2Abd that is highly expressed under normal conditions in the nucleosomes of both bdelloid species; instead , the principal H2A found in the nucleosomes is an unusual H2A variant coded by a gene designated H2Abd1 that is not located in the histone gene cluster . It seems reasonable to speculate that the various unusual features of bdelloid H2A histones are associated with the adaptation of bdelloids to survive desiccation and perhaps also with their lack of meiosis .
Primary genomic fosmid libraries of A . vaga and P . roseola were separately probed with PCR amplification products obtained by using primers based on highly conserved regions of the canonical H3 and H2A histone genes ( indicated in Figure 1B ) . Individual fosmids hybridizing to both probes should contain the clustered histone H3 and H2A genes while fosmids hybridizing only to the H2A probe would be expected to contain the H2AX variant or any other non-clustered H2A variant that may be present and which , like H2AX , has a primary sequence similar to that of canonical H2A . Fosmids that hybridized to either or both probes ( ∼120 in P . roseola and ∼225 in A . vaga ) were tested by PCR and by direct sequencing , leading to the isolation of ∼80 fosmids from P . roseola and ∼180 fosmids from A . vaga containing histone H3 and H2A genes . All fosmids from both bdelloid species containing canonical H3 fell into one of four categories , each coding for the same highly conserved H3 amino acid sequence ( Figure S1 ) , but clearly distinguishable at synonymous sites . One fosmid of each category from both A . vaga and P . roseola was fully sequenced ( ∼35 kb ) and annotated giving contigs Avhis-1 ( EU652315 ) , Avhis-2 ( EU850438 ) , Avhis-3 ( EU652316 ) , Avhis-4 ( EU850439 ) and Prhis-1 ( EU850440 ) , Prhis-2 ( EU652317 ) , Prhis-3 ( EU652318 ) and Prhis-4 ( EU850441 ) respectively ( Figure 1A , Figure S1 ) [see also 30] . Two of these fosmids from each species , designated co-linear pair A , contain genes for the canonical histones H4 , H3 , H2B and a variant of H2A , and are highly similar . Fosmids of the other pair found in both species and designated co-linear pair B , are also highly similar to one another but lack the H2A gene ( Figure 1A , Figure S1 ) . Pair B is considerably diverged from pair A ( Ks ca 45 percent ) and some non-histone genes present in each pair are not present in the other . This pattern is consistent with the degenerate tetraploidy of bdelloid genomes [30] , [31] . The H2A gene found in half of the histone clusters in both A . vaga and P . roseola and designated H2Abd , has a long and unique carboxy-terminal tail with a sequence unlike the C-terminal tail of any canonical or variant H2A known in other metazoans ( Figure 1B , Genbank accession numbers for the two nucleotide copies in A . vaga EU853686 , EU853685 and in P . roseola EU853693 , EU853694 ) . Other fosmids in both bdelloid species were found to contain histone H2A genes not in clusters , but also with a uniquely long carboxy-terminal tail and are designated variants H2Abd1 and H2Abd2 . The H2A gene H2Abd1 is present in four copies in both A . vaga and P . roseola , in two co-linear pairs of contigs , only one of which includes a gene for H2B ( Figure 1A ) and with about 50 percent synonymous divergence between gene copies in different pairs , again consistent with degenerate tetraploidy [30] , [31] ( Genbank accession numbers for the nucleotide copies a , b , c , d in A . vaga EU853687 to EU853690 and in P . roseola EU853695 to EU853698 ) . H2Abd2 , the third H2A variant , also found in both bdelloid species , is not clustered with any histone gene , and is present only as two closely similar copies within a co-linear pair of contigs ( Figure 1A , Genbank accession numbers for the two nucleotide copies a and b in A . vaga EU853691 , EU853692 and in P . roseola EU853699 , EU853700 ) . The bdelloid histone H2A variants and the canonical H2A genes we found in the monogonont rotifer B . plicatilis are aligned along with the canonical H2A genes and H2A variants of other eukaryotes in Figure 1B . Only the variants H2AX and H2AZ , found in most eukaryotic lineages are represented in the alignment . The macroH2A and Barr-body deficient H2A ( H2A Bbd ) variants are not included because they are vertebrate-specific [13] . All three types of bdelloid H2A genes , H2Abd , H2Abd1 and H2Abd2 , code for C-terminal amino acid sequences extending 28–43 amino acid residues beyond the canonical LLPKK motif and are typically longer than those found in other metazoans , with the exception of human macroH2A ( Figure 1B and Table S1 ) . Interestingly , none of the bdelloid-specific H2A C-terminal tails resemble those of other canonical H2As represented in Genbank and all lack the SQ ( E/D ) Φ- ( end ) motif characteristic of H2AX , indicating that both of these highly conserved proteins are absent from bdelloid rotifers . Since all H3 and H2A-containing fosmids were examined and the same three H2A variant genes , in the same organization , were found in both A . vaga and P . roseola , it is likely that we have identified all copies of the H2A genes containing a canonical H2A core . The canonical H2A genes we found in the monogonont rotifer B . plicatilis closely resemble the canonical H2A genes present in most eukaryotes and differ substantially from the bdelloid-specific H2A variants ( Figure 1B ) . The presence of all three H2A variants in species representing two different bdelloid families [32] but not in the monogonont suggests that they are characteristic of the entire class Bdelloidea and have arisen after the separation of bdelloids and monogononts but before the bdelloid radiation . In order to confirm the absence of canonical histone H2A , and to determine which histone H2A replaces it in the nucleosomes of P . roseola and A . vaga , we compared the histones in the nucleosomal fraction of both bdelloid species with those of the monogonont rotifer B . plicatilis and human HeLa cells by denaturing gel electrophoresis ( SDS-PAGE - Figure 2 ) and liquid chromatography-tandem mass spectrometry ( LC-MS/MS ) of peptides following enzymatic digestion . Except for the bdelloid H2A , all rotifer histones displayed an electrophoretic mobility indistinguishable from to that of their human homologs . The identity of rotifer histones was further verified by LC-MS/MS , confirming the presence of the canonical histone proteins H4 , H2B and H3 in bdelloid nucleosomes and all four canonical histones in monogononts . The region of the gels between rotifer H4 and H2B and the three prominent bands of mass greater than that of rotifer H3 ( Figure 2 ) were also examined by LC-MS/MS . Only the first prominent band of greater mass than H3 from each bdelloid proved to be a histone ( band H2Av in Figure 2 ) . This band was identified as H2Abd1 by mass-spectrometric analysis of carboxyl terminal tails . Such detailed analysis also identified peptides coded by each of the four copies of the gene H2Abd1 in both bdelloids as well as a minor quantity of peptides corresponding to H2Abd from A . vaga ( an example for H2Abd1 of P . roseola is given in Figure S2 ) . No peptides from either bdelloid species coded by H2Abd2 were detected by LC-MS/MS . The substantial mass difference observed in Figure 2 between band H2Av of A . vaga and that of P . roseola is consistent with the difference in C-terminus tail length and the calculated mass for proteins coded by H2Abd and H2Abd1 in A . vaga and P . roseola ( Table S1 ) . The results of the SDS-PAGE/LC-MS/MS analysis corroborate the findings from the genomic sequence data: canonical H2A is absent from both bdelloid species and is replaced by the variant H2Abd1 and , at a much lower level , by H2Abd . There is little similarity in amino-acid sequence among the three different H2A variant C-terminal tails in a given bdelloid species ( Figure 1B ) . There is also considerable interspecies amino-acid difference between C-terminal regions of the same variant although a few short motifs are conserved . The C-tails of the histones coded by the four copies of H2Abd1 in both A . vaga and P . roseola were aligned and represented in Logos format with the ‘tallest’ residues representing the most conserved amino acids ( Figure 3B ) . Within this C-terminal tail the framed block resembles a putative four-residue long S ( T ) PK ( R ) K ( R ) class of minor groove DNA binding motifs in which P has a strict position at i+1 [33] . A variety of these SPKK motifs have been found in termini of histone H1 and in the N-terminal tail of sea urchin histones H2B [34] , [35] but also in the N-terminal tail of Drosophila centromeric H3 [33] . Until our study , its presence in the C-terminal of H2A was known only in plants [36] . In all these instances the SPKK motifs mediate histone interactions with linker DNA in the minor groove . The P . roseola H2Abd1 C-terminal tails contain such a motif while in A . vaga a variation of it appears to be present ( Figure 3B ) . The amino acid alignment of the two copies of both H2Abd and H2Abd2 in A . vaga and P . roseola is given instead of the Logos representation ( Figure 3A , 3C ) . Although no similar SPKK class of DNA binding motifs was found in these variants , there are several conserved amino acids . Excluding the distinctive C-terminal tails ( starting at the arrow in Figure 1B ) , the bdelloid H2A genes all have an amino acid sequence closely similar to that of the canonical eukaryotic H2A . The H2A residues involved in histone-histone interactions , such as those of loop 1 that interacts with the other histone H2A and those of the docking domain that contacts the H3-H4 dimer , are well conserved between the three bdelloid H2A variants and canonical H2A ( Figure 1B ) . Such conservation is also characteristic of H2AX , while all other H2A variants differ substantially from the canonical H2A [29] , [37] . H2AZ diverges specifically in three different regions including the above histone-histone interaction zones ( see Figure 1B ) . The alignment of Figure 1B suggests that the three unusual bdelloid H2A variants are closely related to canonical H2A over the entire histone fold domain ( see also the phylogenetic analysis below ) . We also examined the characteristics of the DNA sequence beyond the stop codon of the different bdelloid histone H2A variants and the canonical H3 , H4 and H2B genes . Typically , only the replication-dependent histone genes expressed during DNA synthesis have a characteristic , unique 16-nucleotide stem-loop sequence in the 3′ untranslated region [8]–[11] . In contrast , all of the bdelloid histone genes depicted in Figure 1A except H2Abd2 have the same 16-nucleotide stem-loop sequences 40–80 bp beyond the stop codon ( Figure 3D and Table S1 ) . The stem loop is similar to those in other metazoans , consisting of a four-nucleotide loop ( CTTT ) and a six base-pair stem ( Figure 3D ) . In addition to the 16 nucleotides of the stem-loop structure , there is a high degree of conservation of the ten nucleotides before the stem ( not shown ) . There is also a conserved AT-rich region at the position of a putative histone downstream element ( HDE ) , 4–12 bp downstream of the stem-loop in all of the histone genes of A . vaga and P . roseola except H2Abd2 ( Figure 3D ) . A similar region is present in the replication-dependent histone genes of C . elegans and is believed to be involved in histone 3′ mRNA processing [11] . Both H2A variants H2Abd and H2Abd1 in both bdelloid species contain the stem-loop motif beyond the stop codon , as well as a putative polyadenylation signal similar to that of H2AX . This latter variant , ubiquitous in other eukaryotes but absent in bdelloids , is packaged in nucleosomes during DNA-replication and is also deposited preferentially in response to DNA double strand breaks [38] . H2Abd2 does not contain this stem-loop motif but has a putative polyadenylation signal . Another unusual feature of bdelloid histones is the presence of introns in each of the various histone genes ( canonical histones and variants ) in one or both bdelloid species , except for the H2B gene adjacent to H2Abd1 ( Table S1 ) . The length of the introns ranges from 52 to 76 bp , which is typical of bdelloid introns [39] . This contrasts with the absence of introns in the canonical replication-dependent histone genes in other animals , although they are present in the canonical histone genes of plants and fungi [40] , [41] . Inter-species comparisons of the ratio of amino acid changes to synonymous changes ( Ka/Ks ) in the bdelloid histone gene sequences indicate that the amino acid sequences of the clustered H2B , H3 and H4 genes ( Figure 4A , right column ) are highly conserved except for 2 amino acids in the N-terminal region of H2B . Such conservation is characteristic of eukaryotic canonical histones . The H2A variants H2Abd , H2Abd1 and H2Abd2 are also highly conserved , with the exception of their C-terminal tails and a short region in the N-terminal region of H2Abd ( Figure 4A , left column ) . In order to detect and measure selection on bdelloid rotifer H2A proteins we used the programs SELECTON [42] , [43] and PAML [44] , [45] . For both programs we used an amino acid based nucleotide alignment and corresponding phylogenetic tree ( tree represented in Figure 4B ) . The H2A histone fold domains of the different bdelloid H2A variants , but not their C-terminal tails , are under strong purifying selection as detected by SELECTON ( results not shown ) and also seen in Figure 4A . The program PAML was used to search for signal of positive selection in the bdelloid H2A genes; it implements a likelihood ratio test for positive selection based on dN/dS rate ratios [46] on specific branches [47] , on individual codon sites [48] , or on both simultaneously ( i . e . , a branch-site method for testing positive selection on individual codons along specific lineages ) [49] . No significant branch specific selection was found . The PAML models used for detecting site-specific selection were M1a and M7 for neutral evolution and M2a , M8 for positive selection . All models were significantly better than model M0 indicating that the dN/dS ratio varies along the sequence but no significant positive selection was detected , as the comparisons M1a-M2a and M7-M8 were not significantly different . The phylogenetic tree represented in figure 4B clusters the two bdelloid species for each specific H2A variant . It therefore appears that the different H2A variants arose before the separation of the two bdelloid families and have been diverging since mostly through neutral evolution ( as detected by SELECTON , results not shown ) . A multiple amino acid alignment of canonical H2A genes and H2A variants was carried out in MAFFT [50] , [51] ( result not shown ) . The H2A variants included in this alignment are H2AX and H2AZ from distinct eukaryotic lineages , the vertebrate-specific H2A variants macroH2A and Barr-body deficient H2A ( H2A Bbd ) , and the bdelloid H2A variants ( H2Abd , H2Abd1 and H2Abd2 ) . Based on this alignment we inferred the phylogeny of the H2A proteins using a maximum likelihood approach as implemented in Bootstrap Raxml [52] ( Figure 5 ) . Due to the highly different types of H2A genes included ( belonging to different eukaryotic lineages ) , several parts at the root of the tree are unresolved but some distinct groups are apparent . Congruent with previous phylogenies [16] , [29] the vertebrate-specific variant H2A Bbd ( purple ) forms a distinct cluster outside the canonical H2A group while vertebrate MacroH2A ( light blue ) is a distinct lineage within canonical H2As . The H2AZ variants ( green ) , having a role in transcription [13] and thought to be universally conserved , clearly form a monophyletic group distinct from canonical H2A . The evolution of the H2AX gene ( red ) is different from the other H2A variants because it had multiple evolutionary origins within the eukaryotic kingdom as concluded previously [16] , [29] and entirely replaced canonical H2A in fungi and Giardia ( Figure 5 ) . The H2A variants of the bdelloid rotifers ( orange ) form a distinct lineage , with H2Abd , H2Abd1 and H2Abd2 clustering with the canonical H2A genes of the monogonont rotifer B . plicatilis ( Figure 5 ) . This analysis demonstrates that the bdelloid-specific H2A genes are not closely related to any of the other H2A variants but evolved from a canonical H2A of a common monogonont-bdelloid ancestor . We investigated in more detail the convergent evolution of H2AX found here and also by Li et al . [16] and Malik&Henikoff [29] by repeating the phylogenetic analysis in bootstrap Raxml using only H2A and H2AX sequences of specific plant , insect , vertebrate and fungi species in order to obtain a better alignment than in the previous analysis . It appears from this phylogeny ( Figure 6 ) that the H2AX variants evolved multiple times but at a higher-order level than indicated in the previous phylogenies ( Figure 6 ) [16] , [29] . Indeed , the H2AX variants cluster together rather then with canonical H2As within the plants , vertebrates and insects and , hence , have a single origin within each of these groups .
While the bdelloid canonical histones H2B , H3 and H4 are highly similar to their counterparts in other eukaryotes , we find that the bdelloid complement of H2A histones is highly unusual , with carboxy-terminal tails that are much longer than those of canonical H2A and that are unlike any other eukaryotic H2A variants . The bdelloid H2A histones may be classified as heteromorphous variants because the extent of amino acid sequence change involves a large portion of the C-terminal tail and not merely a few changes as is typical of H2A isoforms [13] . Even the H2A gene H2Abd found in half of the histone clusters in both bdelloid species codes for an unusual C-terminal tail and it seems apparent that canonical H2A is absent from bdelloid rotifers . One of the bdelloid variants , the unclustered H2Abd1 gene , is highly expressed in the embryos of both species during normal growth , while expression of the clustered H2Abd gene was detected at a substantially lower level and only in A . vaga . The H2Abd and H2Abd1 sequences in both bdelloid species specify both the stem-loop motif characteristic of the replication-dependent histones in other eukaryotes and a putative polyadenylation signal in the 3′ UTR characteristic of replication-independent histone variants . Since both of these bdelloid-specific H2A variants H2Abd and H2Abd1 have a stem loop beyond the stop codon and were found in the nucleosomal fraction , they are probably the H2A proteins incorporated into nucleosomes during normal DNA replication in bdelloid embryos , the only life stage in which mitosis occurs in the somatic cells of these eutelic organisms . These bdelloid H2A variants may also be expressed at other times throughout the cell cycle , as observed for H2AX in other eukaryotes [38] , while H2Abd2 variants in both species lack the stem-loop motif and the corresponding histones were not found in the protein analysis of nucleosomal fractions . Nevertheless , considering the strong purifying selection under which they have evolved , the histones coded by these variants are almost certainly expressed and incorporated into nucleosomes under some specific conditions . The monogonont rotifer B . plicatilis , belonging to the sister class of bdelloids , has canonical H2A and appears to lack variants similar to those present in bdelloids . Since the three bdelloid H2A variants are found in each of the two studied species belonging to distantly related families , and as the bdelloid H2As group together with the canonical H2A of monogonont rotifers in the H2A phylogenetic tree ( Figure 5 ) , it seems likely that all these variants evolved from a canonical H2A ancestor . The evolutionary process that took place involved the alteration and extension of the H2A carboxy-tail by at least 25 amino acids and the appearance of conserved motifs . One of these motifs , found in the variant expressed in the nucleosomes ( H2Abd1 ) , seems related to the S ( T ) PK ( R ) K ( R ) class of DNA-binding motifs and may play a role in the interaction with linker DNA and the packaging of the nucleosome . Moreover , the protein extension of the H2A C-terminal tail is in a region of the nucleosome close to the binding site of histone H1 and hence may affect the structure or dynamics of the nucleosome [12] , [16] . Indeed , H2A constitutes the largest heterogeneous family of histone variants that are active in distinct aspects of chromatin conformation and genomic function and the results presented here are consistent with the evolutionary diversity within the H2A family . The high degree of sequence conservation observed within the histone fold domains of the different bdelloid H2A variants is consistent with the general finding that H2A variability is largely confined to the carboxy-terminal domain , both in length and composition [12] . The inter-species variability found in the carboxy-tails of each bdelloid H2A variant ( Figure 3A , B , C ) could be the result of neutral evolution after the separation of the two families , as seen in the SELECTON analysis , and may suggest that the extension has a more significant role than its particular amino-acid sequence . By analogy with the radiation- and desiccation-resistant bacterium Deinococcus radiodurans , in which prolonged desiccation causes extensive DNA breakage [27] , [28] , it is likely that bdelloid radiation resistance similarly reflects an adaptation to survive DNA breakage associated with the frequent desiccation events they experience in the ephemerally aquatic habitats they typically inhabit [4] . DNA breakage in other eukaryotes is accompanied by phosphorylation at the serine in the invariant S[−4]Q ( E/D ) ( I/L/F/Y ) motif found in H2AX of protists , fungi , plants and animals . In fungi and Giardia , the H2AX variant has completely replaced the canonical H2A . Considering the involvement of H2AX in the cellular response to DSBs and its ubiquitous occurrence in eukaryotes , we expected to find H2AX genes and a high percentage of H2AX proteins in bdelloid nucleosomes . Instead , none of the bdelloid H2A genes contain the S[−4]Q ( E/D ) motif characteristic of H2AX . Although SQ occurs at the final two residues of A . vaga H2Abd and 26 amino acids from the C-terminal end of P . roseola H2Abd2 , it is notable that these SQ residues are present in a different H2A variant in each species . They are therefore not conserved across bdelloid families and may therefore not represent a functional motif . Further , in all other eukaryotes the SQ motif characteristic of H2AX in which the serine is phosphorylated requires an adjacent acidic residue ( glutamic or aspartic acid ) that follows the SQ , a carboxy terminal hydrophobic residue , and an invariant position with regard to the carboxyl terminus [37] . Since the bdelloid SQ sequences lack these defining characteristics , we may conclude that there is no H2AX variant in either bdelloid species . It therefore appears that H2AX is dispensable for bdelloid DNA DSB repair , representing an extraordinary exception to the ubiquity of H2AX across eukaryotes . Although the functional significance of the unusual features of bdelloid H2A histone variants has not yet been investigated experimentally , the most plausible explanation of our findings is that they have evolved from canonical H2A as part of the ensemble of adaptations that have allowed bdelloid rotifers to survive desiccation and its attendant burden of DNA damage . One may speculate that differences in the conditions and possible nature of DNA breakage may have driven the evolution of different ensembles of H2A variants among eukaryotes . Such an explanation emphasizes the apparent evolutionary flexibility of H2A and its variants as compared to other histone genes and leads to the evolutionary question as to how H2AX and H2A variants , like those found in bdelloids , are reinvented in the mold of canonical H2A [29] .
Fosmid genomic libraries were constructed from sheared genomic DNA of the bdelloid species Adineta vaga by J . Hur and Philodina roseola by K . Van Doninck and P . Wang . Genomic DNA was extracted from purified bdelloid eggs as described previously [4] , [53] except that CsCl density-gradient purification was replaced by phenol∶chloroform extraction . The Epicentre CopyControl Fosmid Library Production Kit ( EPICENTRE Biotechnologies ) was used to construct fosmids of each bdelloid species as previously described [30] . PCR-derived histone probes , using primers based on highly conserved regions of H3 and H2A , were used to screen the genomic libraries of bdelloid rotifers . Each library of each of the above mentioned bdelloid rotifer species was separately hybridized with probes for H3 and H2A . The DNA of all the selected histone fosmids was extracted manually [54] and tested by PCR and direct sequencing of fosmid templates to confirm the presence or absence of each histone gene H3 , H4 , H2B and H2A , and to verify which type of H2A gene was present . Histone genes were characterized by BLASTX searches on the National Centre for Biotechnology Information non-redundant databases . Exons and introns were mapped by comparison to homologous amino acid sequences using the software genewise [55] . Gene prediction and the mapping of introns were also verified using the program genemark self-trained on the C . elegans genome [56] and the translation tool Expasy . The canonical H2A primers used to make the probes for the bdelloid rotifers could also be used to amplify all H2A genes of the monogonont rotifer B . plicatilis containing a canonical H2A core . For both bdelloid species , four fosmids containing the histone clusters and each copy of canonical H3 were selected for complete sequencing ( ∼35 kb ) . DNA from each of these fosmids was purified using Nucleobond Purification kits ( BD Biosciences ) , sheared to a size range of 3–5 kb with a Genemachines Hydroshear ( Genomic Solutions ) and subcloned in TOPO vectors ( Invitrogen ) for shotgun sequencing . The resulting sequences were assembled into single contigs as described in [31] and the complete detailed annotation is published in a separate paper [30] . The multiple alignments of the H2A genes and their variants were done using the online version MAFFT v6 [50] , [51] with the BLOSUM62 matrix . The “Mafft-homologs” option was enabled only for the alignments including less than 30 sequences . The algorithms used were G-INS-i and L-INS-i when macroH2A sequences were respectively excluded or included in the alignment . To determine which model of protein evolution would best fit our data we used ProtTest v1 . 4 [57] . The phylogenetic analyses were carried out with the maximum likelihood approach as implemented in the online version of Bootstrap Raxml [52] available on the CIPRES Portal ( http://www . phylo . org/sub_sections/portal/ ) . The following parameters were applied: Dayhoff substitution matrix ( selected by ProtTest ) , empirical base frequencies , maximum likelihood search and 1 , 000 bootstrapping runs . The trees obtained were displayed using FigTree v1 . 1 . 2 ( http://tree . bio . ed . ac . uk/software/figtree ) . The bdelloid H2Abd1 amino-acid carboxy-terminus tails or the nucleotide sequences beyond the stop codon were also aligned using MAFFT and displayed as Logos with the interface Weblogo [58] , [59] to emphasize the conserved motifs . The Logos format is a graphical representation of aligned sequences where the size of the letter is proportional to the frequency of that particular residue in that position . For the sliding window analysis , coding sequences of histone genes were first aligned according to their translated peptide sequences with RevTrans 1 . 4 [60] using the Dialign 2 method . Sliding windows of the Ka/Ks ratio , among histone genes from the same co-linear pair but in different species , were then generated with DnaSP 4 . 0 [61] using 50 bp windows and 10 bp steps . To measure the nature and magnitude of natural selection acting on bdelloid H2A genes , an amino acid based nucleotide alignment using MAFFT and a corresponding phylogenetic tree with Bootstrap Raxml were built and then used in the program SELECTON for a so-called “High-precision” analysis ( http://selecton . tau . ac . il/ ) [42] , [43] . This program evaluates the dN/dS ratio ( ω ) [46] . Neutral evolution predicts an ω = 1 whereas significantly higher and lower values than 1 are respectively interpreted as evidence for positive and purifying selection . Furthermore , we used PAML v4 . 1 [44] , [45] to test for positive selection along sequences and branches . PAML tests different codon substitution models and performs a likelihood ratio test of positive selection based on the dN/dS ratio . We tested branch-specific selection for every internal branch in the tree . Site-specific selection was tested by comparing different models: “M0” which corresponds to a single dN/dS ratio along the sequence , “M1a” and “M7” for neutral evolution ( dN/dS = 1 ) and “M2a” and “M8” for positive selection ( dN/dS>1 ) . Histone proteins were extracted from A . vaga , P . roseola and B . plicatilis embryos following a modified protocol of Tops et al . [62] . The A . vaga and P . roseola rotifer cultures were bleached to obtain clean bdelloid eggs and embryos . B . plicatilis embryos were obtained from a filtered , snap-frozen B . plicatilis biomass ( received from Terry Snell ) washed with 0 . 1% SDS and then bleached . After the bleach treatment , the clean bdelloid and monogonont embryos were washed with extract buffer ( 10 mM HEPES , pH 7 . 1; 5 mM MgCl2 , 2 mM DTT , 10% glycerol and complete protease inhibitor tablets ( Roche ) ) and finally resuspended in 0 . 5 volume extract buffer . The suspension was dripped in N2 ( l ) and the resulting frozen egg balls were ground in a cold mortar . The obtained powder was thawed on ice and sheared using a chilled dounce homogenizer ( 30 strokes , tight pistol ) . The obtained crude extract was centrifuged for 10 min at 14000 rpm to separate the pellet ( with nuclei and membranes ) from the soluble cytosol . The pellet was washed twice with extract buffer and subsequently resuspended in extract buffer with 0 . 4N sulfuric acid and left at 4°C overnight . After centrifugation at 14000 rpm for 10 min at 4°C , the acid soluble histone proteins in the supernatant were precipitated with 20% Trichloroacetic acid ( TCA ) . The obtained histone protein pellet was dried 10 min at 95°C and kept at −20°C or immediately resuspended in 1× alkaline sample buffer , heated at 100°C for 10 min and separated by electrophoresis on 15% Tris-glycine SDS-polyacrylamide gels as previously described [63] . Human cells were obtained from the Maniatis laboratory ( MCB , Harvard University ) , washed with extract buffer ( as above ) and finally resuspended in 0 . 5 volume extract buffer . The following steps of the histone protein extraction of human cells were identical to the one described for bdelloid and monogonont embryos . The Coomassie blue stained bands of bdelloids and monogononts on the SDS-PAGE gels were excised ( from the lowest band of the gel up to ∼25 kD ) and washed with 50% acetonitrile in water . Histones in gel slices were digested with trypsin and subjected to microcapillary reverse-phase HPLC nano-electrospray tandem mass spectrometry ( LC-MS/MS ) on an LTQ-Orbitrap mass spectrometer ( ThermoFisher , San Jose CA ) . Acquired MS/MS spectra were then correlated with public sequences using the algorithm SEQUEST and custom programs developed in house . The MS/MS peptide sequences were then reviewed in detail for consensus with known proteins and the results manually confirmed for fidelity . The histone protein extractions , SDS-PAGE gels and mass spectrometry analyses of specific bands were done twice for each rotifer . In addition , de novo sequencing and additional LC-MS/MS analyses against the translated sequences known for bdelloid and monogonont histones were performed with alternative proteolytic enzymes ( chymotrypsin , pronase and elastase ) to extend the overall coverage of the carboxyl terminal tails of the histone H2A variants . Exhaustive coverage and redundant acquisition of peptides was maximized by the in-house program Enzyme Optimizer designed to choose a multi-enzyme strategy based on proteotypic peptide properties . DNA sequences have been deposited at Genbank under accession numbers EU652315 to EU652318 , EU850438 to EU850441 and EU853685 to EU853700 . | Bdelloid rotifers are microscopic animals common in ephemeral freshwater environments throughout the world . They are unusual not only because they have been reproducing without males for millions of years , but also because they can survive long periods of complete desiccation at any life stage and exposure to levels of ionizing radiation that cause hundreds of DNA double strand breaks per genome . Canonical histones ( H2A , H2B , H3 , and H4 ) are highly conserved proteins that package DNA in the nucleus and are involved in the regulation of chromatin metabolism . Because the conserved histone variant of canonical H2A , H2AX , is involved in the repair of DNA double strand breaks , we tested the possibility that bdelloid H2A histones are unusual . Strikingly , we find that bdelloids lack both H2A and H2AX , the absence of which is in contrast to their ubiquitous presence in other eukaryotes . Instead , we find that bdelloid rotifers replaced their canonical H2A protein by H2A variants not found in any other eukaryote . These results gain particular interest in view of the extreme resistance of bdelloid rotifers to desiccation and ionizing radiation and their attendant ability , possibly unique among metazoans , to repair massive levels of DNA breakage . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"molecular",
"biology/molecular",
"evolution",
"evolutionary",
"biology/genomics"
] | 2009 | Phylogenomics of Unusual Histone H2A Variants in Bdelloid Rotifers |
The evolution of tetrapod limbs from fish fins enabled the conquest of land by vertebrates and thus represents a key step in evolution . Despite the use of comparative gene expression analyses , critical aspects of this transformation remain controversial , in particular the origin of digits . Hoxa and Hoxd genes are essential for the specification of the different limb segments and their functional abrogation leads to large truncations of the appendages . Here we show that the selective transcription of mouse Hoxa genes in proximal and distal limbs is related to a bimodal higher order chromatin structure , similar to that reported for Hoxd genes , thus revealing a generic regulatory strategy implemented by both gene clusters during limb development . We found the same bimodal chromatin architecture in fish embryos , indicating that the regulatory mechanism used to pattern tetrapod limbs may predate the divergence between fish and tetrapods . However , when assessed in mice , both fish regulatory landscapes triggered transcription in proximal rather than distal limb territories , supporting an evolutionary scenario whereby digits arose as tetrapod novelties through genetic retrofitting of preexisting regulatory landscapes . We discuss the possibility to consider regulatory circuitries , rather than expression patterns , as essential parameters to define evolutionary synapomorphies .
The tetrapod limb is made out of a proximal-to-distal series of long bones , the stylopod , zeugopod in the arm , and the digits in the hand , the latter of which are separated from the former two by the mesopodium , an articulation based on an array of small roundish bones [1]–[4] . This skeletal organisation evolved during the Devonian as an adaptation to the buoyancy-lacking environment of the land [5] , [6] . The fossil record indicates that limbs evolved from fins via successive steps of distal elaboration , eventually resulting in the formation of the autopod as a tetrapod-specific evolutionary novelty , with fin radials or distal fin radials as putative evolutionary precursors of digits [7]–[9] . During mammalian limb development , the activity of both HoxA and HoxD gene clusters is essential and the absence of these two loci leads to rudimentary and truncated appendages [10] . All long bones of the limb require the activation of Hox genes in different though partially overlapping combinations . Initially , Hoxd9 to Hoxd11 and Hoxa11 are expressed in the developing proximal limb ( the presumptive arm ) . Subsequently , in a second phase of transcriptional activation , Hoxd9 to Hoxd13 as well as Hoxa13 are expressed in presumptive digits [11]–[14] . The existence of distinct regulatory modules for long bones on either side of the mesopodial articulation ( the wrist and ankle ) , together with the separated evolutionary trajectories of these elements , has supported the view that tetrapod limbs are genetically organized following a specific bimodal pattern of proximal ( arm and forearm ) and distal ( digits ) long bones , which as such is not present in fish fins ( refs . in [1] ) . The characterization of Hoxa and Hoxd expression patterns during fish fin bud development has re-enforced the view that changes in Hox genes' regulation were instrumental in the transformation of fins into limbs [1] , [2] , [15]–[19] . The exact nature of these changes , however , has remained controversial . The analysis of fin buds from various fish species lead to different conclusions regarding the existence in fishes of the late and distal phase of Hoxd gene expression , associated with the development of tetrapod digits ( Figure 1A ) . This phase was indeed either considered as a tetrapod novelty [18] , [20] , implying an origin close to the stem of tetrapods , or alternatively as more ancestral and already present in fish [21]–[24] . This latter scenario suggests a deeper homology between fin radials and distal limb structures [16] , [21] , [25] , which could potentially qualify distal fin radials as digit homologs [16] . Regarding Hoxa genes , the expression of Hoxa11 and Hoxa13 is largely overlapping in fins [20] , [21] , [24] , [26] , instead of the mutually exclusive patterns observed in limbs , and is thus of little help in providing a proximo-distal ( P-D ) reference point . These analyses primarily rely on the comparison between gene expression domains whose interpretation is complicated when highly divergent structures are considered , such as fins and limbs [1] , and hence whether or not any homology can be inferred from such expression analyses is unclear . The assessment of fish DNA sequences orthologous to tetrapod digit enhancers in transgenic mice indeed indicated their potential for regulating gene transcription in developing appendages [27] , [28] . However , these fish enhancers , related to tetrapod digit control sequences , appeared to drive transgene expression primarily in more proximal mouse limb territories rather than in digits . As an alternative to using gene expression to infer homologies , we looked at whether a comparison between the regulatory mechanisms underlying Hox gene transcription in both tetrapod and fish appendages could be more informative . The transcriptional regulation of the HoxD gene cluster during limb development becomes rather well understood . The successive proximal and distal waves of expression are controlled by distinct enhancer-containing regulatory landscapes , located in gene deserts on opposite sides of the gene cluster . A proximal landscape is located on the 3′ side of the gene cluster , whereas the distal ( digit ) landscape extends on the 5′ side [29]–[31] . These regulatory landscapes are regions of active enhancer-promoter interactions , as defined by chromosome conformation capture ( 4C ) , and their genomic extents and properties strongly suggest that they correspond to recently defined topological domains ( Figure 1B ) [31]—that is , ca . 100 kb to megabase large chromatin domains , which provide a permissive environment for long-range enhancer—promoter interactions [32] , [33] . Hoxd9 to Hoxd11 , which are located in the central part of the gene cluster , successively interact with either one of these 3′ and 5′-located regulatory landscapes depending upon which series of enhancers are active , thus switching their contacts from one landscape to the other at the time of the transition between cells with a proximal fate to cells forming the presumptive digits [31] . In contrast , genes that are situated at either extremity of the cluster always interact within their neighbor landscape and will not switch their contacts . Hoxd13 for instance will only interact with 5′-located enhancers and , as a consequence , will be transcribed only in the distal limb territory . Therefore , a bimodal chromatin organization of the HoxD locus prefigures the bimodal expression of Hoxd genes with their proximal and/or distal specificities , leading to the tetrapod P-D limb axis [31] . The expression patterns of Hoxa genes suggested that this collinear property of Hoxd genes may also apply to their Hoxa paralogs and each gene cluster on its own is capable of specifying a complete limb P-D axis , as demonstrated by the full deletion of either HoxA or HoxD [10] , [34] , [35] . However , whether or not these functional similarities reflect a conservation of regulatory strategies remained elusive . Here , we report that this mode of regulation is globally conserved between both gene clusters , suggesting that its emergence predated the origin of tetrapods . In addition , we looked at the situation in fishes and analyzed the regulatory potential of their Hox clusters in the context of transgenic mice .
We first evaluated whether the bimodal regulatory strategy observed at the HoxD cluster was particular to this locus or , in contrast , was shared with HoxA during limb development , in which case such regulatory modalities would likely predate the duplication of Hox clusters and hence the emergence of tetrapods . We looked at the expression patterns of Hoxa genes to see how well they adhere to the proximal-to-distal restrictions observed for Hoxd genes in budding limbs [12] , [13] , [36] . Although a weak expression of Hoxa4 was scored proximal to the digits in E12 . 5 limbs , strong expression of Hoxa9 and Hoxa10 was detected both in developing digits and in a more proximal domain , corresponding to the presumptive forearm . In contrast , both Hoxa13 and the Hoxa11 antisense transcript ( Hoxa11as ) [37] accumulate only in the distal , presumptive digit domain and in the future wrist ( Figure 2A ) . A noticeable difference with Hoxd genes was observed , however , as Hoxa11 transcripts are absent from this distal domain , while present in the proximal territory , suggesting that Hoxa11 may escape the distal regulation imposed on the Hoxa9 to Hoxa13 genes , unlike in the case of HoxD [38] , where Hoxd9 to Hoxd13 genes are coregulated in digits . It has , however , recently been shown that Hox13 group genes repress Hoxa11 in the distal limb [39] . In the absence of Hoxa13 function , the expression of Hoxa11 shifts into the distal limb bud to partially overlap with the expression of the inactivated Hoxa13 transcript , as detected by using a 3′UTR probe ( Figure 2B , compare left and central panels ) . When doses of Hoxa13 and Hoxd13 functions were progressively removed , the distal extension was strengthened and Hoxa11 transcripts were found almost throughout the entire developing autopod ( Figure 2B , right panels ) , much like its antisense Hoxa11as transcript in the wild-type condition . Although this result indicates that both Hoxa13 and Hoxd13 products repress Hoxa11 expression , it also demonstrates that the Hoxa11 promoter can readily respond to the distal regulation , much like Hoxa13 . Therefore , it appears that the HoxA cluster , like HoxD , is the target of a distal limb ( digit ) global enhancer , which can regulate at least two distinct promoters . On the other hand , Hoxa4 , Hoxa9 , Hoxa10 , and Hoxa11 are transcribed in a wider territory , including the proximal limb region , suggesting that as for the HoxD cluster , Hoxa genes are regulated by two distinct regulatory modules during limb budding and patterning . This regulatory dichotomy may correlate with another similarity between the HoxA and the HoxD cluster—that is , the fact that HoxA too is located at the junction between two topological domains [32] . These data were , however , obtained in ES cells and thus we further characterized the three-dimensional chromatin dynamics of the HoxA cluster during limb development , in comparison with forebrain cells where all Hox genes are inactive , at least at this stage . We implemented circular chromosome conformation capture and deep sequencing ( 4C-seq ) [40] , [41] , using Hoxa4 , Hoxa9 , Hoxa11 , and Hoxa13 as baits in E12 . 5 dissected presumptive digits , proximal limb , and forebrain cells . The distribution of contacts over an 8 Mb DNA interval ( Figure S1A ) , as judged by the number of sequence reads , shows that ca . 90% of the interactions are concentrated within the regions corresponding to four topological domains as determined in ES cells and located on either side of the cluster ( Figure S1B , shaded area from −2 to +2 ) , with particularly strong contacts with the regions corresponding to the two flanking domains ( Figure S1B , from −1 to +1 ) . This observation was strongly reminiscent of the situation described for the HoxD cluster ( Figure S1B , bottom and [31] ) . Within the domains of high interactions ( i . e . , the shaded areas in Figure S1B ) , the occurrence of contacts was quantified and no difference was observed in the distribution of interactions for either Hoxa4 or Hoxa13 , when either proximal or distal limb bud samples were used . Hoxa4 establishes interactions primarily with the 3′ neighborhood of the gene cluster in both distal ( Figure 3; 72% ) and proximal ( 71% ) samples , whereas Hoxa13 mostly contacts the opposite , 5′-located landscape in the same two samples ( Figure 3; 66% and 63% , respectively ) ( the 3′ and 5′ orientation of the cluster is given following the direction of transcription of Hox genes ) . In contrast , both Hoxa9 and Hoxa11 increase their interactions with the 5′-located landscape in digit cells , when compared to proximal limb cells ( Figure 3A , B; from 26% to 39% and from 39% to 53% , respectively ) . This shift in contacts observed with more centrally located Hoxa genes ( Hoxa9 , Hoxa11 ) is comparable to the situation described for the HoxD cluster ( Figure 3D , E , Figure S2 , and [29] , [31] ) . The increase in interactions between these genes and the 5′ landscape in distal cells suggests that several Hoxa genes located at the 5′ extremity of the cluster are coordinately regulated in the presumptive digit domain . These results and the analogy with the HoxD cluster are in line with the presence of functional enhancer sequences in the 5′ landscape , capable of activating transcription with distal limb specificity ( Figure S3 ) [42] , [43] . Because the HoxA cluster appears to respond to a bimodal regulation that shares several features with that reported for Hoxd genes [31] , we propose that this operational mode is a core component of both Hoxa and Hoxd gene regulation during limb proximal to distal patterning and thus likely predates the emergence of tetrapods . The data obtained from the forebrain samples show that this partitioning between 5′ and 3′ regulatory landscapes is only partially tissue-specific and largely independent from the transcriptional activity , as noted for a large proportion of topological domains ( Figure 3C , D , E and Figure S2 ) [32] , [33] . Because this chromatin partitioning at and around the tetrapod HoxA and HoxD clusters is associated with distal and proximal regulatory capacities , we looked at its presence in fish Hox clusters as a potential indication that distinct regulations may also be at work during fin development . Data obtained from limb tissues , brain , and ES cells all show this biased distribution in interactions corresponding to the existence of two flanking topological domains , indicating that such a structural organization exists in both expressing and nonexpressing tissues . Consequently , we used whole zebrafish embryos at day 5 postfertilization ( dpf ) to visualize the interaction profiles of related fish Hox clusters , instead of dissected fin bud tissues , which would have met our technical limitations due to their small size and the amount of tissue required for 4C analysis . Teleosts underwent an additional genome duplication and have up to eight Hox cluster loci [44]–[46] , of which HoxAa , HoxAb , and HoxDa are the most relevant for fin development [24] , [47] . Accordingly , we used viewpoints in Hoxa4a , Hoxa9a , Hoxa11a , Hoxa13a , Hoxa2b , Hoxa11b , Hoxa13b , Hoxd4a , Hoxd10a , Hoxd11a , and Hoxd13a for 4C experiments ( Figure 4 and Figure S4 ) . We observed that fish Hox13 genes also display a clear bias in their interactions toward their 5′ flanking neighborhood ( Figure 4 ) . For example , Hoxa13a , Hoxa13b and Hoxd13a show 67% , 79% and 66% , respectively , of their total contacts with their 5′ landscapes . In contrast , only 27% of the contacts established by Hoxa4a and 26% of the contacts established by Hoxd4a were scored over their 5′ landscapes , these latter genes interacting mostly with the 3′ neighborhood of the gene clusters ( 73% and 74% respectively ) . Therefore , as in the mouse , genes located at either end of the clusters establish preferential contacts with either their 3′ or 5′ neighboring landscape . In contrast , interactions involving Hoxa9a , Hoxa11a , Hoxa11b , Hoxd10a , or Hoxd11a—that is , genes located at more central positions—are rather equally distributed between the two landscapes on either side of the cluster ( Figure 4 ) . We thus concluded that the chromatin partitioning observed in tetrapods at the HoxA and HoxD loci is also present in fishes . These results suggest that the structural component of the mechanism underlying the distinct proximal and distal phases of Hox gene expression predates the evolution of tetrapod limbs . Therefore , a resemblance greater than anticipated may exist between distal fins and limb structures , as recently proposed [16] , [21] , [22] . The bias of fish Hox13 genes to contact their immediate 5′ environment suggested that , similar to their tetrapod counterparts , they might be used as the distal contribution of a bimodal regulatory strategy . We investigated the potential presence in these fish landscapes of enhancers driving limb-specific expression . Accordingly , we generated transgenic mice with fish Hox clusters including their entire 5′ flanking regions . We selected Pufferfish ( Tetraodon nigroviridis ) BACs because , due to the compressed genome of this species [48] , they permit the transgenic analysis of entire syntenic regions . Mice transgenic for the fish HoxAa 5′ landscape showed expression of Hoxa11a , Hoxa13a , and Evx1 in hindlimb buds , but with a proximal-only specificity , whereas no distal expression was observed despite the presence of the 5′ flanking genomic region ( Figure 5A ) . Likewise , the fish Hoxa10b , Hoxa11b , and Hoxa13b genes were strongly expressed in mouse limb buds transgenic for the fish HoxAb 5′ landscape . Here again , however , the expression domain matched a proximal zone and transcription was not scored in developing digits ( Figure 5B ) . Because the pufferfish HoxAb BAC contains both the 5′ and 3′ neighborhoods , we implemented 4C-seq on transgenic mouse limbs and could confirm that strong interactions occurred between both Hoxa13b and Hoxa11b with the 5′ flanking region , despite the transcriptional outcome , which was restricted to a proximal domain ( Figure S5 ) . Also , the HIBADHb , TAX1BP1b , and JAZF1b genes , located next to Hoxa13b , were co-expressed with HoxAb genes , further illustrating that a global regulation is associated with this 5′ landscape ( Figure 5B ) , as is the case for the mouse locus where these genes are co-expressed along with Hoxa13 [49] . Of note , the onset of the fish Hoxa13b expression in transgenic limb occurs in distal limb bud cells located underneath the apical ectodermal ridge ( AER; Figure 6A , arrowhead ) , similar to the “late” expression pattern of this gene during fin bud development . In mice , however , the expression territory of this fish transgene does not follow the distal extension of the bud and thus remains at a more proximal position ( Figure 6A , arrows ) . This result illustrates the difficulty of using relative parameters such as “proximal” or “distal” when assigning homology between fins and limbs ( Figure 6B ) . Altogether , the fish regions syntenic to the mouse HoxA cluster failed to elicit expression in presumptive digit cells during limb budding . Instead , when introduced into mice , fish HoxA genes were all transcribed in proximal limb domains . We also analyzed the HoxDa cluster by using two BACs extending either 5′ or 3′ from the fish cluster . The 5′ BAC covers a region of the fish genome syntenic with the digit regulatory landscape , upstream of the mouse HoxD cluster [29] , whereas the 3′ BAC is syntenic with the proximal limb regulatory landscape [31] . In both cases , when introduced into transgenic mice , the fish Hoxda genes were expressed in a restricted domain , always located in the proximal limb bud , whereas no transcript was detected distally ( Figure 5C ) . In this context , the fish genes were expressed according to their relative proximity to the flanking landscapes; Hoxd4a , Hoxd9a , and Hoxd10a were indeed preferentially transcribed whenever their closely located 3′ landscape was included , whereas Hoxd11a , Hoxd12a , and Evx2 were preferentially expressed when the opposite 5′ landscape was present . However , the same proximal specificity was observed in both cases , suggesting that regulatory domains exist on both sides of the fish HoxDa cluster , which are able to control fish Hoxda gene transcription in a proximal domain of the mouse limb bud , rather than in the digits ( Figure 5C ) . These results are in agreement with the capacity of zebrafish , skate [27] , and coelacanth [28] sequences orthologous to mouse HoxD “digit enhancers” to drive expression essentially in proximal , rather than distal , domains of murine transgenic limb buds .
Our results show that , similar to the HoxD gene cluster , the HoxA cluster establishes preferential contacts with the two flanking genomic neighborhoods , such that Hoxa13 strongly interacts with the telomeric DNA ( i . e . , with its 5′ side ) , whereas Hoxa4 contacts its centromeric ( i . e . , on the 3′ side ) landscape . The existence of such a structural bias in both gene clusters suggests that the ancestral gene cluster , before its duplication at the root of the vertebrate taxon , already displayed such a general bimodal chromatin structure . This may indicate the presence of a generic regulatory constraint imposed to these gene clusters , such as the necessity to functionally separate , in space and time , the most posterior genes from their anterior neighbors , the former proteins being generally dominant over the latter [50] . This split of both HoxA and HoxD clusters into two chromatin domains precisely matches the results obtained by using Hi-C on ES cell material [32] . Interestingly , however , the same dataset reveals that neither HoxB nor HoxC seem to display this feature , suggesting it may have been lost subsequently . This might relate to the fact that these latter two gene clusters are truncated either for their anterior ( HoxC ) or posterior ( HoxB ) genes . Our 4C experiments also confirmed that many interactions were present in all the tissues assayed , regardless of their transcriptional activity , as previously observed [29] , [31] . In addition , the general extent of our interaction domains precisely coincided with the topological domains as defined by using the Hi-C dataset of Dixon et al . [32] , further suggesting that many of those interactions associated with such topological domains are constitutive in nature . For example , the strong 3′ HoxA interacting peak observed at the border between topological domains −2 and −1 ( Figure 3 , Chr6: 51 , 120 , 000 ) was present in all tissues investigated . This peak colocalizes with both proximal limb enhancers ( elements 406 and 407 and human element 1465 ) and branchial arch enhancers ( elements 402 to 406 ) , as reported in a genome-wide enhancer screen [43] . It may be that such a constitutive contact anchors the Hox cluster at the vicinity of tissue-specific enhancers , thus working as a priming mechanism for enhancer–promoter interactions . In this context , the presence of constitutive contacts with anchoring points rather than with the actual enhancers themselves might reflect the fact that Hox genes are regulated by multiple tissue-specific enhancers in time and space . The presence of a constitutive , poised regulatory architecture may have evolved at these loci to facilitate the successive implementation of multiple regulations , by providing a stable framework to be complemented by tissue-specific factors . The problem raised by the fin-to-limb transition shows that developmental expression patterns cannot always be used to infer homologies between distinct species . Because both Hoxd13 and Hoxa13—that is , the two tetrapod genes essential for digit development—display this strong regulatory tropism towards their upstream genomic neighborhoods , we looked at whether the related fish Hox genes would display the same behavior and found that fish Hox gene clusters have the same conformational organization . This observation suggested a level of conservation between the regulation of these genes in both tetrapods and fishes higher than anticipated . However , the existence of such separated chromatin domains including the fish Hox13 genes and their flanking genomic sequences does not lead to a clear partitioning of regulatory activities , at least when introduced into transgenic mice . All fish regulatory landscapes assayed , taken from either sides of the clusters , indeed elicited comparable proximal expression in mouse limbs and were thus unable to respond to those signals , triggering the emergence of the digital plate in mouse . The existence in fishes , of regulatory landscapes showing proximal specificities in transgenic murine limbs , may be related to the fact that fins can display elaborate proximal-to-distal patterns , as illustrated by combinations of radials and distal radials . Both zebrafish and paddlefish , as well as shark Hox , genes appear to be activated in a partially heterotopic manner consistent with the presence of these distinct fin segments [21] , [22] , [24] , and hence such P-D patterns may result from biphasic regulations emanating from opposite regulatory landscapes . In this view , it is conceivable that the regulatory balance between these two landscapes in fishes contributes to the wide variety of P-D patterns observed in the fins of various species ( Figure 7 ) [51] . Given the inability of fish regulatory sequences to activate transcription in the mouse digital plate , however , this P-D division would not be homologous to the regulatory partitioning observed between the arm and the hand in tetrapods . The bimodal limb bauplan is characterized by a clear morphological separation between the long bones of the arm and the forearm , on the one side , and of the hand , on the other side . This separation is controlled by opposite regulatory landscapes and gives rise to the presence in between of a nodular articulation critical for the function of the limbs and not observed in any fish fins: the mesopodium [1]–[3] . Because the development of long bones requires high doses of HOX products whereas a lower dose is associated with carpal-like small bones [52] , it was proposed that the mesopodium results from the offset between the proximal and distal Hox expression territories , made possible by the existence of distinct regulatory landscapes [31] . In this context , a potential scenario emerges for the fin-to-limb transition whereby two partially overlapping expression domains in fins progressively segregated to generate entirely distinct expression territories . This model hypothesizes the evolution of a bimodal “proximal–proximal” patterning system in fins ( without mesopodium ) into a bimodal “proximal–distal” system in limbs , including an articulation and thus postulates the transformation of a regulatory landscape from a “proximal” to a “distal” specificity . The mechanisms underlying this “regulatory homeosis” are elusive , but modifications in the structure and function of the AER , a source of growth factors in the tip of growing limb buds , may have been instrumental . During fin development , the cessation of endoskeletal expansion coincides with the transformation of the AER into the apical ectodermal fold ( AEF ) from which the exoskeletal fin rays will develop [53] . Various models have predicted that the folding of the ectodermal layer plays a key role in the termination of fin distal growth , possibly due to the interruption of AER-derived proliferative signals by its dense extracellular matrix [17] , [18] , [53]–[56] . In this view , the abrogation of ectodermal folding in tetrapods may have lead to a prolonged exposure to AER signals , leading to increased Hox expression and extended distal growth , thus resulting in the formation of the autopod . However , we show here that this model cannot fully account for our transgenic results , as expression of fish Hox genes is not observed distal to the mesopodium , even in the absence of ectodermal folding . We conclude that there is an intrinsic inability of fish enhancers to respond to the distal limb regulatory program in the mouse . Consequently , the absence of a clear distal expression territory in fin buds separated from ( but concomitant with ) the proximal expression domains is likely not caused by a mere physical obstacle induced by the folding of the ectodermal layer . Rather , an ancestral fish 5′ regulatory landscape may have evolved to better respond to distal ectodermal signals , and the reinforced transcription of Hox genes distally might have promoted supplementary growth by delaying ectodermal folding . This situation is illustrated by the effect of overexpressing Hoxd13a in zebrafish fins , which leads to increased distal growth at the expense of the AEF [17] . Alternatively , the capacity for ancestral fish enhancers to respond to the appropriate distal signals may have existed from early on but be repressed , in which case tetrapod loci may have simply overcome this repression , for instance , through the loss of repressor binding sequences . It has been pointed out that chondrichthyans or actinopterygians could be more informative regarding the fin-to-limb transition than extant teleosts [17] , [21] , which may have lost primitive characters . Yet fins of all these species consist of both radials and distal radials and exhibit similar HoxA and HoxD expression patterns [15] , [16] , [20]–[22] , [24] , [47] . Furthermore , our results with transgenic pufferfish sequences are consistent with the patterns found when enhancers isolated from more primitive fishes were used . In all cases indeed [27] , [28] , these enhancers did not elicit expression patterns as distal as one would have expected for bona fide digit enhancers [29] , [57] . In conclusion , although digits are likely formed through the action of tetrapod-specific Hox enhancers , the underlying regulatory circuitry relies upon an ancestral framework already implemented in fish , illustrating the retrofitting of preexisting genomic infrastructure . In this context , the question regarding the homology between fin radials and digits may receive different answers depending on which level is considered within the regulatory hierarchy . Fish have the necessary genes and higher order regulatory architecture to form digits and likely implement the 5′ regulatory landscape to pattern distal fin radials [16] . Accordingly , digits could be considered as a specialized type of distal radials as both structures rely on a unique ancestral regulatory strategy . However , the fish 5′ regulatory landscapes are unable to specify a distinct digit territory and , as such , this regulatory feature defines a clear tetrapod synapomorphy . Therefore , a qualification of distal radials as digits ( senso “classical” homology , that is , with a common ancestral structure ) is not supported by our results .
All animal experiments were performed according to Swiss regulations under license no . 1008/3482/0 ( to D . D . ) . 4C libraries were constructed as described before [41] . Mouse libraries consisted of 52 dissected E12 . 5 proximal forelimb buds , distal forelimb buds , or forebrains . Zebrafish libraries consisted of approximately 300 5 dpf embryos from the TU strain . Transgenic mouse libraries containing the Tetraodon HoxAb ( C0AA043AG01 ) BAC contained 48 E12 proximal and distal hindlimb buds . The sequencing data for these samples were combined and processed as a whole limb sample . For the mouse baits used for 4C , the primary restriction enzyme used was NlaIII ( New England Biolabs , R0125L ) , and the secondary restriction enzyme was DpnII ( New England Biolabs , R0543M ) . For the zebrafish baits , the primary restriction enzyme was DpnII ( New England Biolabs , R0543M ) , and the secondary enzyme was TaqαI ( New England Biolabs , R0149M ) . In the latter case , DNA was cut for 8 h at 65°C . For the Tetraodon baits , assessed in transgenic mice , the primary restriction enzyme used was DpnII ( New England Biolabs , R0543M ) , and the secondary enzyme was NlaIII ( New England Biolabs , R0125L ) . For each viewpoint , between 1 . 3 and 2 . 6 µg of the 4C library was amplified using 16 individual PCR reactions with inverse primers containing Illumina Solexa adapter sequences ( Table S2 ) . Multiplexed samples were sequenced on the Illumina HiSeq system using 100 bp single-end reads according to the manufacturer's specifications . 4C-seq reads were sorted , aligned , and translated to restriction fragments using the 4C-seq pipeline of the BBCF HTSstation ( available at http://htsstation . epfl . ch [41] ) . Mouse samples were mapped to the ENSEMBL Mouse assembly NCBIM37 ( mm9 ) and zebrafish samples were mapped to the ENSEMBL Zebrafish assembly Zv9 . Transgenic Tetraodon samples in mouse were mapped to a custom genome containing the Tetraodon BAC ( C0AA043AG01 ) and ENSEMBL Mouse assembly NCBIM37 ( mm9 ) , thus minimizing the chance of mapping nonspecific reads . The directionality of signal was calculated on 4C-seq patterns over the regions mentioned in Table S1A . Data are summarized in Table S1B . In the figures , smoothed 4C-seq patterns ( running mean , window size 11 ) are visualized except in Figure S4B , which shows unprocessed data . Topological domains shown to complement the 4C-seq experiments are ES cell HiC data take from ( http://chromosome . sdsc . edu/mouse/hi-c/database . php ) [32] . Mouse domains selected for 4C-seq analyses correspond to two topological domains located centromeric and telomeric of the clusters ( i . e . , four domains in total ) and are described in Figure S1 . The zebrafish regions were selected on basis of synteny with the mouse domains analyzed . Similar experiments involving the HoxD cluster as shown in Figure S2A , B were previously reported [31] . The experiments shown here were , however , repeated together with the analysis of Hoxa genes in order to compare datasets produced under the exact same conditions . BAC constructs were identified using the Genoscope Tetraodon genome browser ( http://www . genoscope . cns . fr/externe/tetranew/ ) . BAC numbers and genomic positions ( TETRAODON8 ) correspond to HoxAa , C0AB048AA04 ( Chr21:2 , 888 , 799–3 , 037 , 908 ) ; HoxAb , C0AA043AG01 ( Chr8:6 , 699 , 347–6 , 844 , 622 ) ; HoxDa 3′ , C0AB015CD05 ( Chr2:13 , 313 , 310–13 , 458 , 212 ) ; HoxDa 5′ , C0AB043BH04 ( Chr2:13 , 417 , 090–13 , 578 , 446 ) . BAC clones were obtained from Genoscope , France . A PISceI meganuclease site was introduced into the vector backbones using standard EL250 cell-based recombineering technology . BAC DNA was prepared using a Nucleobond Midiprep Kit , linearized with PISceI ( New England Biolabs , R0696L ) , incubated with SDS according to the manufacturer's instructions , 2× chloroform-phenol purified , ethanol precipitated , and dialyzed against microinjection buffer containing protamines [70 µM spermidine ( Sigma , S2626 ) , 30 µM spermine ( Sigma , S3256 ) ] . Constructs were microinjected using standard protocols for pronuclear injection . BAC lines were genotyped using primer pairs every 5 to 10 kb in combination with deep sequencing using 4C-seq and mapping of the reads on the BAC sequence to confirm its integrity . A HoxAb transgenic line was mapped using embryonic hindlimb samples ( Figure S5 ) , and adult mouse ear samples of HoxDa 3′ and 5′ BAC lines were processed using 4C-seq specifically for the purpose of integrity mapping using a viewpoint located in Hoxd11a ( unpublished data ) . BAC diagrams in Figure 5 represent the regions that were found to be integrated using PCR ( all lines ) or 4C-seq data ( HoxAb , HoxDa 3′ , and HoxDa 5′ ) in the transgenic lines presented . The Hoxa13 and Hoxd13 mouse knockout lines were previously described [58] , [59] . In situ hybridization was performed as described [60] with a temperature of prehybridization , hybridization , and posthybridization steps increased to 68 . 5°C . For Tetraodon probes , the SSC concentration in the hybridization mix was lowered to 1 . 3× to increase specificity ( for the Evx2 probe , 0 . 5×SSC was used ) , and the posthybridization SSC washes were done using 4×30 minutes 2×SSC-T . In all experiments using transgenic Tetraodon probes , wild-type embryos were coprocessed for each probe and stage to monitor specificity of the probes ( unpublished data ) . Except in brain vesicles , susceptible to probe trapping , nonspecific signal was never observed using the conditions described above . Probes were amplified using PCR from BAC DNA or limb cDNA and cloned into pGEMTE easy vector systems ( Promega A1360 ) . Primer sequences are given in Table S3 . DIG-labeled RNA probes were synthesized using Sp6 or T7 polymerase ( Promega ) . Probes for Hoxd11 and Hoxa13 were described previously [61] , [62] . The probe used to detect the Hoxa11 sense transcript was kindly provided by Dr . C . Fromental-Ramain and corresponds to a ScaI-HpaI fragment in the 3′ UTR of Hoxa11 ( mm10: Chr6:52 , 242 , 847–52 , 243 , 385 ) . In situ hybridization images were acquired using Leica Application Suite software v3 . 3 . 1 in combination with a Leica DFC300FX camera and Leica MZFLIII microscope . Images were edited in Adobe Photoshop software using the brightness/contrast function . Limb buds shown in Figure 1B stained for Hoxa13 are right side limb buds coming from the same embryos as the left side limb buds stained for Hoxa11 and are mirrored for purpose of comparison . Similarly , the Hoxa4 sample in Figure 1A is a mirror image right side forelimb bud . In Figure 1A the same wild-type forelimb specimen is used as in Figure 1B to illustrate the wild-type expression of Hoxa11 . Unprocessed 4C-seq data for mouse and zebrafish samples are available from the Gene Expression Omnibus repository under accession number GSE47644 . Ensembl IDs for genes used in this study are as follows: Mouse ( Mus musculus ) , Hoxa4; ENSMUSG00000000942| Hoxa9; ENSMUSG00000038227| Hoxa10; ENSMUSG00000000938| Hoxa11; ENSMUSG00000038210| Hoxa11as; ENSMUSG00000086427| Hoxa13; ENSMUSG00000038203| Hoxd4; ENSMUST00000111980| Hoxd11; ENSMUSG00000042499| Hoxd13; ENSMUSG00000001819|; Zebrafish ( Danio rerio ) , Hoxa4a; ENSDARG00000057724| Hoxa9a; ENSDARG00000096510| Hoxa11a; ENSDARG00000009045| Hoxa13a; ENSDARG00000007609| Hoxa2b; ENSDARG00000023031| Hoxa9b; ENSDARG00000007009| Hoxa13b; ENSDARG00000036254| Hoxd4a; ENSDARG00000059276| Hoxd10a; ENSDARG00000057859| Hoxd11a; ENSDARG00000059267| Hoxd13a; ENSDARG00000059256|; Pufferfish ( Tetraodon nigroviridis ) , Hoxa11a; ENSTNIG00000001767| Hoxa13a; ENSTNIG00000009207| Evx1; ENSTNIG00000000875| Hoxa10b; ENSTNIG00000001780| Hoxa11b; ENSTNIG00000000494| Hoxa13b; ENSTNIG00000001781| HIBADHb; ENSTNIG00000018428| TAX1BP1b; ENSTNIG00000018429| JAZF1b; ENSTNIG00000018430| Hoxd4a; ENSTNIG00000001765| Hoxd9a; ENSTNIG00000016957| Hoxd10a; ENSTNIG00000001775| Hoxd11a; ENSTNIG00000001776| Hoxd12a; ENSTNIG00000001777| Evx2; ENSTNIG00000001817| . | Our upper limbs differ from fish fins , notably by their subdivision into arm and hand regions , which are separated by a complex articulation , the wrist . The development of this anatomy is associated with two distinct waves of expression of the Hoxa and Hoxd genes during development . Would such a shared expression pattern be sufficient to infer homology between fish fins and mouse limbs ? We investigated this question here , looking at whether the two phases of Hox gene transcription that are observed during tetrapod limb development also occur during zebrafish fin development . We find the answer is “not quite . ” For although the mechanisms that regulate the expression of Hoxa and Hoxd are comparable between zebrafish fins and mouse limbs , when the genomic regions that regulate Hox gene expression in fish fins are introduced into transgenic mice , they trigger Hox gene expression in only the proximal limb segment ( the segment nearest the body ) and not in the presumptive digits . We conclude that although fish have the Hox regulatory toolkit to produce digits , this potential is not utilized as it is in tetrapods , and as a result we propose that fin radials—the bony elements of fins—are not homologous to tetrapod digits . | [
"Abstract",
"Introduction",
"Results",
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"and",
"Methods"
] | [
"biology"
] | 2014 | Conservation and Divergence of Regulatory Strategies at Hox Loci and the Origin of Tetrapod Digits |
Intracellular parasites of the genus Leishmania generate severe diseases in humans , which are associated with a failure of the infected host to induce a protective interferon γ ( IFNγ ) -mediated immune response . We tested the role of the JAK/STAT1 signaling pathway in Leishmania pathogenesis by utilizing knockout mice lacking the signal transducer and activator of transcription 1 ( Stat1 ) and derived macrophages . Unexpectedly , infection of Stat1-deficient macrophages in vitro with promastigotes from Leishmania major and attenuated LPG1 knockout mutants ( lpg− ) specifically lacking lipophosphoglycan ( LPG ) resulted in a twofold increased intracellular growth , which was independent of IFNγ and associated with a substantial increase in phagosomal pH . Phagosomes in Stat1−/− macrophages showed normal maturation as judged by the accumulation of the lysosomal marker protein rab7 , and provided normal vATPase activity , but were defective in the anion conductive pathway required for full vesicular acidification . Our results suggest a role of acidic pH in the control of intracellular Leishmania growth early during infection and identify for the first time an unexpected role of Stat1 in natural anti-microbial resistance independent from its function as IFNγ-induced signal transducer . This novel Stat1 function may have important implications to studies of other pathogens , as the acidic phagolysosomal pH plays an important role in antigen processing and the uncoating process of many viruses .
Protozoan parasites of the genus Leishmania generate a variety of pathologies collectively termed leishmaniasis that afflict millions of people worldwide [1] . Depending on parasite species and host immune response , the pathologies range from mild cutaneous , self-healing lesions generated by L . major , to the fatal visceral disease caused by L . donovani . Leishmania is transmitted during blood feeding of infected sand flies , which inoculate highly infective metacyclic promastigotes into the mammalian host [2] . Following uptake by host macrophages , metacyclics differentiate into the amastigote form that replicates inside the fully acidified phago-lysosome of the host cell . From this site the parasite modulates the response of the host cell and immune system [3] , [4] . Release of IL-4 and IL-10 by infected macrophages and accessory immune cells establishes a TH2 response permissive for parasite growth and responsible for acute disease with fatal outcome in immuno-compromised individuals and susceptible BALB/c mice [5] , [6] . In contrast , immuno-competent individuals and genetically resistant mouse strains , including C57BL/6 , B10 , and SV129 [7] , mount a Th1 response and are able to contain parasite growth during later stages of the infection by the production of IL-12 that entails development and expansion of histocompatibility complex MHC class II-restricted Th1 cells [8] , [9] . Interferon γ ( IFNγ ) secreted by these cells elicits a pleiotropic anti-microbial response in macrophages that is transduced by the inducible transcription factor Stat1 [10] , [11] , a cytosolic latent transcription factor that forms dimers and translocates into the nucleus following tyrosine phosphorylation by Janus family tyrosine kinases [12] . There , Stat1 induces expression of iNOS and pro-inflammatory cytokines including IL-12 , TNFα , and IL1β , which are required for resistance to various parasitic , bacterial and viral pathogens . A role for Stat1 distinct from its function as inducible transcription factor has been suggested [13] . Stat1-deficient fibroblast cell lines showed reduced expression of the low molecular mass proteins LMP-1 and LMP-2 [14] , [15] , and the caspases ICE , Cpp32 and Ich-1 , associating constitutive Stat1 activity with antigen processing and apoptosis [14] . Here we report evidence for a novel physiological function of Stat1 in phagosomal acidification , which was independent from IFNγ and its activity through the well known roles of this important transcription factor in immune function . The selective defect of Stat1−/− cells allowed us for the first time to test the role of phagosomal pH on Leishmania survival in situ .
Groups of Stat1-deficient mice and SV129 isogenic controls , or susceptible BALB/c mice , were inoculated with 106 infective L . major promastigotes , and the ability to resolve the infection was assessed during 12 weeks post-infection . In resistant SV129 mice , the parasites elicited a transient lesion , which was completely resolved in all 11 animals 70 days after the infection ( Figure 1A ) . In contrast , SV129 Stat1−/− mice were unable to control the infection and showed progressive lesion development similar to susceptible BALB/c mice with ultimately fatal outcome , as previously shown [16] . We further investigated this defect by in vitro infection of peritoneal exudate macrophages ( PEM ) . Intracellular Leishmania growth was assessed in untreated and LPS/IFNγ-activated PEMs from wild-type and Stat1-deficient mice by nuclear staining and fluorescence microscopy [17] . Parasites showed robust intracellular growth in untreated control PEMs , which was completely abolished in activated cells ( Figure 1B , left panel ) . In contrast , Stat1−/− PEMs were highly permissive for intracellular Leishmania growth , even in LPS/IFNγ-treated cells ( Figure 1B , right panel ) . In immunocompetent hosts , L . major infection is controlled by the induction of leishmanicidal NO in response to IFNγ-producing Th1 cells , which in turn differentiate in an IL12-dependent manner . IFNγ/LPS-treated PEMs from Stat1−/− mice were unable to produce IL12 or nitric oxide , while robust levels were detected in the supernatants of treated controls ( Figure 1C ) . Together these data confirm the crucial role of IFNγ in controlling Leishmania infection through Stat1-mediated cytokine and NO production , and further sustain the importance of macrophage activation in anti-leishmanial resistance . During the macrophage infection studies , we consistently observed a trend towards increased intracellular parasite growth in naïve Stat1−/− PEMs when compared to wild-type controls . We quantified this unexpected effect following infection with promastigotes form wild-type L . major and mutant lacking the abundant surface lipophosphoglycan through inactivation of the LPG1 gene [17] . As expected from previous results [17] , survival of lpg− promastigotes in SV129 PEM was reduced by 75% ( Figure 2A ) . A similar reduction was observed in Stat1−/− PEMs confirming our previous results that intracellular elimination of lpg− is independent from IFNγ-mediated effects [18] . Surprisingly , even though the infections were performed in the absence of IFNγ and thus under conditions where Stat1 should be inactive , survival of both wild-type and lpg− promastigotes was increased in Stat1−/− PEMs by more than twofold ( Figure 2A ) . In contrast , lesion-derived wild-type amastigotes survived equally well in Stat1−/− macrophages and controls regardless of host or parasite phenotype ( Figure 2A , right panel ) . We first tested if increased promastigote survival in Stat1−/− cells resulted from their failure to produce leishmanicidal NO ( see Figure 1C , right panel ) . Stat1−/− PEMs and controls were treated with the NO-inhibitor NMMA and intracellular parasite survival was determined as described above and compared to untreated controls . Again , Stat1−/− PEMs were more permissive for intracellular Leishmania growth compared to the wild-type ( WT ) control , even in the presence of NMMA ( Figure 2B ) . Both control and Stat1−/− PEMs produced similar amounts of superoxide during phagocytosis , which was strongly reduced upon treatment of the supernatants with superoxide dismutase ( Figure 2C ) . These data rule out a role for reactive nitrogen or oxygen radicals ( or the absence thereof ) in increased Stat1−/− Leishmania survival . We followed the maturation of phagosomes into acidic phago-lysosomes by fluorescence ratio determination . Monolayers of untreated or LPS/IFNγ treated SV129 control and Stat1−/− PEMs were incubated with zymosan-FITC and intra-vesicular pH was determined spectrophotometrically by establishing the ratio of pH-independent to pH-dependent florescence at 450 and 495 nm respectively . Following phagosome alkalinization in the presence of 10 µM NH4Cl ( open arrow head ) , equilibration and removal of the base ( closed arrow head ) , phagosomes of untreated control PEMs equilibrated at an intra-vesicular pH of 5 . 3 consistent with previous findings ( Figure 3A ) [19] , [20] . In contrast , phagosomes of untreated Stat1-deficient cells failed to fully acidify and showed a substantial increase of 0 . 6 units in intra-vesicular pH to pH 5 . 9 ( Figure 3A , left panel ) . Treatment of the cells with LPS/IFNγ substantially inhibited acidification of WT and Stat1-deficient phagosomes , which equilibrated at pH 5 . 9 and 6 . 3 respectively ( Figure 3A , right panel ) . Thus macrophage activation results in increased phagolysosomal pH thereby ruling out the possibility that residual IFNγ production in WT PEMs may contribute to the observed difference in phagosomal acidification . We analyzed cytoplasmic and lysosomal pH in cells incubated for 12 h in DMEM with 10 µM BCECF-AM and 2 . 5 mg/ml of dextran-FITC respectively ( Figure 3B ) . Both control and Stat1-deficient cells provided a neutral cytoplasmic pH of 6 . 8 to 6 . 9 and an acidic lysosomal pH of 5 . 2 . Addition of increasing concentrations of NH4Cl ( 10 , 20 and 50 µM , not shown ) allowed us to determine a buffering capacity of 54±8 mmoles/mpH for either macrophage [21] . We next established that the pH defect of Stat1−/− PEMs occurs also during Leishmania infection , using FITC surface-labeled Leishmania and intra-vesicular fluorescence-ratio measurement . We used axenic amastigotes from L . donovani , which do not express LPG and thus eliminate concerns regarding the release of labeled LPG into other cell compartments and its effect on phago-lysosomal fusion [22] , [23] . Similar to the zymosan control , Stat1−/− phagosomes do not fully acidify following uptake of labeled amastigotes and equilibrate at 0 . 3 pH units higher than controls ( Figure 3C ) . Thus , Stat1−/− PEMs show a selective defect in phagosomal acidification independent from lysosomal pH , which may enhance intracellular parasite survival . Maturation of phagosomes into an acidic , hydrolase-rich compartment depends upon interactions with the endocytic network and the fusion with late endosomes or lysosomes [24] . Thus partial acidification of phagosomes in Stat1-deficient macrophages may result from a failure to interact with these acidic organelles . We established a detailed kinetics of phagosomal acidification by fluorescence ratio measurement . Control and Stat1−/− PEMs were incubated with zymosan-FITC for 20 min at 4°C and intra-vesicular pH was determined during synchronous uptake induced by temperature shift to 37°C . PEMs from both control and deficient mice provided similar kinetics of phagosome acidification during the first minutes after zymosan uptake , however Stat1−/− phagosomes equilibrated shortly after at 0 . 5 pH units above the pH attained in control PEMs ( Figure 4A ) . Phagosome maturation was further studied by accumulation of the late endosomal marker protein rab7 [25] . During the synchronous uptake of Texas Red-labeled zymosan , rab7 was absent in early phagosomes of control and Stat1-deficient PEMs ( up to 20 min post-incubation ) and detected in perinuclear vesicular compartments ( data not shown ) . Rab7 was first detected in phagosomes of both control and Stat1−/− PEMs 30 min after zymosan uptake and was maintained thereafter for the rest of the incubation period ( Figure 4B ) . Thus the defect in phagosomal acidification is independent from lysosomal fusion as judged by the recruitment of the lysosomal marker Rab7 . Vesicle acidification is achieved by the combined action of an electrogenic H+-ATPase , which pumps protons into the lumen , and a chloride-channel that short-circuits the electrical potential across the membrane , allowing proton transport further to continue . We tested if a defect in one of these activities accounts for the elevated phagosomal pH in Stat1-deficient macrophages . Phagosomes containing FITC-conjugated zymosan were isolated from control and Stat1-deficient bone marrow-derived macrophages ( BMM ) , diluted into the reaction mixture containing ATP and reactions were started by the addition of MgSO4 ( Figure 5 , closed arrows ) . Phagosomes from control mice showed a rapid but transient decrease in vesicular pH by 0 . 3 pH units to 5 . 95 ( s . d . 0 . 04 ) during the first minute after MgSO4 addition ( Figure 5 , left panel ) . Phagosomes from Stat1−/− BMMs were able to initiate phagosome acidification ( Figure 5 , middle panel ) but showed a pH decrease of only 0 . 15 pH units to 6 . 13 ( s . d . 0 . 04 ) . This acidification profile indicates the presence of a functional H+-ATPase that provides limited activity most likely due to a defect in charge neutralization compared to the control ( p<0 . 002 for the difference observed one minute after ATP addition ) . This hypothesis was further sustained in K2SO4-treated control preparations . Replacement of chloride with impermeant anion sulfate eliminates the charge neutralization normally conferred by the chloride channel , a treatment that resulted in partial acidification of Stat1+/+-preparations similar to the one observed in Stat1−/− preparations ( Figure 5 , right panel ) . We tested the charge neutralizing activity in reconstituted vesicles from membrane preparations of control and Stat1-deficient BMMs . Mg2+-ATP-dependent proton transport was determined following quenching of acridine orange fluorescence , a weak base that accumulates in acidic compartments and shows a pH-dependent decrease in fluorescence during vesicle acidification [26] . Vesicles derived from both cell types were able to initiated acidification upon addition of MgSO4 in the presence of ATP , however vesicles derived from Stat1-deficient cells acidified only partially when compared to the control ( Figure 6A , left panel ) . Acidification was restored to normal levels in these preparations in the presence of valinomycin , a potassium ionophore that eliminates the chloride-dependence of acidification by collapsing the potential generated by the proton pump . These data show that Stat1-deficient macrophages are defective in charge neutralization most likely due to a chloride channel dysfunction [19] , [27] . Western Blot analysis of crude and phagosomal extracts ( Figure 6B and data not shown ) with polyclonal antibody AB656 [26] revealed similar levels in expression of the chloride channel family members detected by this antibody in control and Stat1-deficient preparations , suggesting that the defect in the mutant cells may be linked to a difference in activity rather than expression of chloride channel proteins , or results from the absence of chloride channel species not detected by this antiserum . Immediately following phagocytosis by host macrophages , Leishmania promastigotes transiently inhibit phagolysosomal fusion , a process mediated by LPG [18] , [23] . We recently showed that this delay in phagosome maturation did not alter survival of either wild-type or lpg−parasites [18] . The Stat1−/− PEMs allowed us for the first time to test the effect of phagosomal pH on parasite survival in situ , providing a second perspective on our previous findings . Control and Stat1−/− PEMs previously labeled with dextran-FITC were infected synchronously with either wild-type or lpg1− Leishmania and fusogenic phagosomes were identified by florescence microscopy 3 h later as described [18] . As previously shown , wild-type parasites reside in non-fusogenic phagosomes ( Figure 7A ) . As expected form the absence of LPG , phagosomes containing lpg1− parasites were highly fusogenic [23] , [28] . Significantly , the exposure to lysosomal content in SV129 control and Stat1−/− cells had no effect on parasite survival during the first 2 days post-infection , when Leishmania-containing phagosomes are generally fully acidified ( Figure 7B ) . In contrast , parasite numbers showed a substantial increase in Stat1−/− PEMs between day 2 and day 5 post-infection , when amastigote differentiation was completed and intracellular growth initiated . Together these data suggest that Stat1−/− PEMs show normal fusogenic properties during Leishmania infection . Additionally , the fact that LPG-deficient parasites show no difference in intracellular survival during the first 48 h in WT and Stat1−/− macrophages , despite the significant difference in their phagolysosomal pH , further supports the conclusion that killing of the LPG-deficient mutant is independent of phagosome acidification .
The inducible transcription factor Stat1 transmits the immune-protective effects of IFNγ during viral , bacterial and parasitic infections [10] , [11] , [16] , [29] , [30] . Previously , a constitutive activity of Stat1 has been identified that regulates target gene expression in an IFNγ-independent manner [14] , [15] . However , the significance of this pathway on host immunity and its impact on the interpretation of studies performed in Stat1-deficient animals had not been studied . Here we describe for the first time a novel function of constitutive Stat1 in modulation of phagosomal acidification . Fusion of phagosomes with hydrolase-rich , acidic compartments including lysosomes and endosomes [31] establishes a hostile environment to potential pathogens as well as comprising a key compartment for antigen presentation [32]–[34] . The relevance of lysosomal degradation in anti-leishmanial resistance has been genetically defined by studies of the natural-resistance-associated macrophage protein , NRAMP1 [35] , a transmembrane phosphoglycoprotein which confers natural resistance to a variety of intracellular pathogens [36] by regulating the intra-phagosomal pH [37] . By utilizing in vitro Leishmania infection assays we identified a selective defect in phagosomal acidification in Stat1-deficient macrophages ( Figure 3 ) , which resulted in a twofold increase of intracellular parasite survival during a 5 days infection period ( Figure 2 ) . The selective Stat1−/− defect in acidification allowed us to investigate in situ the role of phagosomal pH on Leishmania survival and growth . A potential role for acidic pH in anti-leishmanial resistance has been put forward by Desjardins and co-workers based on the observation that promastigotes reside transiently in non-fusogenic phagosomes [23] , [28] , [38] . This effect is mediated by the major surface glycoconjugate LPG , which is released from the parasite surface into the host cell cytoplasm , where it interferes with vesicular fusion [22] , [39] . Hence , Leishmania may have evolved an intracellular survival strategy reminiscent to other pathogens , including Toxoplasma [40] , Legionella [41] and Mycobacteria [20] , [36] , all of which avoid contact with the lysosomal content . Increased survival of intracellular L . major in Stat1-deficient host cells seems to support a role for phagosomal acidification in anti-leishmanial resistance . However , we and others have provided previously compelling evidence that Leishmania promastigotes are perfectly well adapted for survival in acidic environments . Promastigotes grow normally at pH 5 . 5 [42] , and their surface glycocalyx confers resistance to lysosomal hydrolases in insect and vertebrate hosts [43]–[46] . We previously showed that intracellular survival of attenuated lpg− mutants was restored to wild-type levels in oxidant-deficient phox−/− host cells , although extensive fusion of parasite-containing phagosomes with host cell lysosomes occurred [18] . Here we confirmed these data and showed that intracellular parasite burden was similar in control and Stat1−/− PEMs for the first 48 h of infection despite the difference in phagosomal pH during this time period ( Figure 7 ) . Both survival of wild-type and attenuated lpg− mutant parasites was equally enhanced in Stat1−/− PEMs between day 2 and day 5 post-infection ( Figures 2A and 7B ) , suggesting that the pH-dependent activity compromised in Stat1−/− PEMs acts independent of LPG and its effects on oxidant resistance or phago-lysosomal fusion . Acidic pH is maintained in phago-lysosomes by the combined action of v-ATPases that transport protons across the membrane , and chloride channels that neutralize the transmembrane potential by counter ion conductivity . Stat1−/− PEMs were normal in phagosome maturation as judged by the kinetics of phago-lysosomal fusion and the accumulation of the late endosomal marker protein rab7 in the mutant phagosomes ( Figure 4A and 4B ) . Dissociation of the molecular events required for vesicular acidification in Stat1−/− cells by ratio-fluorescence measurements indicated functional vATPase activity ( Figure 5 ) , which was limited by the increasing transmembrane potential during proton transport and a selective defect in charge neutralization ( Figure 6 ) . The mechanism how Stat1 regulates counter-ion conductivity remains elusive and is currently under investigation . Possible mechanisms include a direct transcriptional activation of chloride channel expression or indirect effects on expression of regulatory molecules that modify chloride channel activities , such as p53 [47] , erk7 [48] or c-Src [49] . In summary , our data provide evidence for a novel IFNγ-independent function of Stat1 in phagosome acidification , which may have important implications for the interpretation of data previously obtained by others in Stat1-deficient animals . For example , Stat1−/− mice have been recently shown to display an unexpected increase in bone mass , which was attributed to a dysregulation of osteoclast differentiation [50] . Bone remodeling occurs by terminally differentiated cells of the monocyte-macrophage lineage termed osteoclasts , which generate an acidic compartment on the surface of the bone required for resorption ( [26] and references therein ) . Conceivably , a defect in Stat1−/− osteoclast in vesicular acidification similar to the one we describe here for Stat1−/− macrophages may have a major impact on bone homeostasis and thus may substantially participate in increased bone formation observed in these mice . More significantly , Stat1−/− mice were widely used to study the role of IFNγ-mediated immunity to various pathogens . Given the importance of vesicular pH in either resistance to bacterial and protozoan pathogens , and its relevance in the uncoating process during viral entry , the role of constitutive Stat1 activity in innate anti-microbial resistance may have to be re-investigated in light of its potential role in acidification .
129/Sv control mice and mice inactivated for Stat1 expression ( referred to as Stat1−/− or Stat1-deficient , [11] ) were purchased from Taconic ( Germantown , NY ) . All animals were handled in strict accordance with good animal practice as defined by the relevant national and/or local animal welfare bodies , and all animal work was approved by the appropriate institutional committee . Leishmania major strain LV39clone5 ( Rho/SU/59/P , [51] ) was grown in M199 medium at 26°C as previously described [52] . The LPG-deficient lpg1− null mutant was maintained in media supplemented with 16 µg/ml hygromycin B and 20 µM puromycin as described [17] . Axenic amastigotes of L . donovani ( strain LD1SR , [53] ) were cultured at 37°C in M199 supplemented with 20% FCS at pH 5 . 5 according to Zilberstein et al . [54] . Virulence was assessed following inoculation of 106 promastigote parasites from day 4 of stationary culture into the footpad of 6 to 8 weeks old female Stat1−/− mice and congenic SV129 controls . Infections were monitored by comparing the thickness of the injected and uninjected footpads with a Vernier caliper . Murine bone marrow macrophages ( BMM ) were obtained from the femurs of female mice and differentiated in vitro in the presence of M-CSF as described [55] . Peritoneal exudate macrophages ( PEM ) were elicited by injection of 2 ml endotoxin-free starch suspension ( 2% w/v in normal saline ) into mice . Cells were isolated three days later by peritoneal lavage using cold Dulbecco's modified Eagles medium ( DMEM ) , washed and resuspended in DMEM/10% FBS . For infection , PEM were seeded in 12 well plates onto 18 mm glass cover slips ( 3×105 cells/ml ) and non adherent cells were removed by washing after 30 min incubation at 37°C in 5% CO2 . Adherent PEM were infected with complement-opsonized promastigotes from day 4 of stationary growth [56] or lesion-derived amastigotes at a multiplicity of infection of 10 parasites per macrophage . Following 2 hours incubation at 33°C in DMEM 0 . 7% BSA under serum free conditions , non-phagocytosed parasites were removed by multiple washing steps with DMEM without FBS and incubation was proceeded for another 5 days at 33°C . Growth of extracellular parasites was prevented during this period by washing the cells once a day . The number of intracellular parasites was monitored at 2 h , 24 h , 48 h and120 h post-infection by nuclear staining and fluorescence microscopy as described [17] . All culture media were tested to be endotoxin-free using the Pyrotell LAL test kit ( Associates of Cape Cod Inc . , MA ) . Superoxide was measured by the ferricytochrome reduction assay [57] . PEMs were washed with Hank's buffered saline solution ( HBSS ) , and incubated for 90 min at 37°C with zymosan ( 10 particles per cell ) , purified metacyclic WT ( MOI = 10 ) or lpg1− promastigotes ( MOI = 3 ) in 80 µM ferricytochrome c/HBSS . Supernatants were cleared by centrifugation at 4° and the concentration of reduced cytochrome c was determined spectrophotometrically at 550 nm ( ε550 nm = 2 . 1×104 M−1 cm−1 ) . The background was determined in equally treated control cells in the presence of 100 ng/ml superoxide dismutase ( Sigma ) in Hank's Balanced Salt Solution ( HBSS ) . NO-derived nitrite in culture supernatants was determined by the Griess reaction [58] . Briefly , 100 µl were removed from conditioned medium , incubated with an equal volume of Griess reagent ( 1% sulfanilamide/0 . 1% naphthyl ethylene diamine dihydrochloride/2 . 5% H3PO4 ) at room temperature for 10 min , and the NO2− concentration was determined in spectrophotometrically a at 550 nm using NaNO2 as a standard . IL-12 ( p40 ) levels were determined in the PEM culture supernatants by an ELISA capture method ( Pharmingen , San Diego , CA ) . Briefly , microtiter plates coated with a capture monoclonal anti-IL-12p40 antibody were incubated with 100 µl of culture supernatant , and bound IL-12 was detected with polyclonal rabbit anti-IL12p40 antibody and peroxidase-conjugated sheep anti-rabbit antibody . Cells were washed once in phosphate buffered saline ( PBS ) , permeabilized with 100% methanol ( −20°C ) for 30 seconds and re-hydrated for 10 min at RT in PBS . Preparations were sequentially incubated for 20 min at 37°C with 1/100 dilutions of rab7 primary antibody ( Santa Cruz , CA ) and 1/100 dilution of FITC conjugated anti-rabbit secondary antibodies as described [59] . Zymosan particles or amastigote parasites were labeled for 20 min at 4°C with NHS-carboxyfluoresceine ( 250 µg/ml , Boehringer Mannheim , Germany ) or Succinate-Texas Red ( Molecular Probes , OR ) in 100 mM NaHCO3 , 150 mM NaCl at pH 7 . 6 , and washed three times in serum-free DMEM by centrifugation at 1000×g for 5 min . PEM were seeded in 12 well plates onto 18 mm glass cover slips ( 3×105 cells/ml ) , and incubated overnight ( at least 12 h ) in DMEM supplemented with 10% FCS and 2 . 5 mg/ml FITC-conjugated dextran ( 10 kD , lysine fixable , Molecular Probes , OR ) . Cells were washed vigorously and incubated at 4° for 20 min with stationary-phase promastigote parasites at a multiplicity of infection ( MOI ) of 10 parasites per host cell . were infected for 2 h at 33° at for WT or synchronous parasite uptake was achieved For synchronous infections , parasites were incubated to allow attachment , Free parasites were removed by washing , and synchronous infection was achieved by temperature shift to 37°C [60] . Fusogenic FITC-positive phagosomes were quantified by fluorescence microscopy on paraformaldehyde-fixed preparations over a period of 3 hrs following uptake . All pH measurements were performed in situ with conjugates of fluorescein isothiocyanate . The pH response of the conjugated dye was calibrated in solution and in cells where intracellular compartments were equilibrated with medium pH as described previously [19] . Monolayers of peritoneal macrophages were incubated with fluorescein-conjugated parasites or zymosan particles for 30 min at 37°C in a humidified CO2 incubator ( ratio ca . 10 particles or parasites per macrophage ) . Cells were washed rigorously , incubated further for 2 h at 37°C and phagosomal pH was assessed in an Aminco SPF-500 spectrofluorimeter as previously described [61] . Parasite- and zymosan-conjugates were calibrated in each of the cells employed in these studies ( not shown ) . The pKs of the free dye and dye conjugates were identical in solution and for intracellular measurements indicating that they were reporting the vesicle pH and not conditions particular to the particle surface , compartment or dye conjugate [62] , [63] . These measurements were used to determine vesicle pH in the following studies . Cells were incubated in 10 µM in 2′ , 7′-bis ( 2carboxyethyl ) -5-carboxyfluoresceine-tetraacetoxymethyl ester , BCECF-AM ( Molecular Probes , OR ) , for 30 min and washed as previously described [64] . Intracellular cytoplasmic fluorescence was calibrated , and intracellular pK and pH response were determined using buffered Nigericin solutions [61] , [64] . Macrophage monolayers were incubated overnight ( at least 12 h ) in DMEM supplemented with 10% FCS and 2 . 5 mg/ml FITC-conjugated dextran ( 10 kD , lysine fixable , from Molecular Probes , OR ) . Cells were washed vigorously and endo-lysosomal pH was assessed by ratio-fluorescence determination . The buffering capacity was determined as described [21] . Macrophage monolayers were allowed to phagocytose FITC-conjugated zymosan , collected by scraping in turtle buffer supplemented with 1 mM dithiothreitol [26] and disrupted in a tight fitting Dounce homogenizer . Undisrupted cells and debris were removed by centrifugation at 1500×g for 5 min and the phagosomes sedimented at 10000×g . The pellet was suspended in 140 mM KCl , 10 mM HEPES pH 7 . 0 , and acidification of the vesicles was initiated by the addition of 2 . 5 mM potassium ATP and 1 mM MgSO4 . The intravesicular pH was assessed using ratio-fluorescence determinations following calibration of intra-phagosomal pH with Nigericin [61] , [64] . Isolated phagosomes containing unlabeled zymosan were disrupted by one freeze-thaw cycle at −70°C , zymosan particles were removed by centrifugation at 2000×g and the membrane fraction was pelleted at 100000×g for 60 min at 4°C . The assay was performed as described [26] . Western blot analysis was performed using the enhanced chemiluminescence ( ECL ) detection kit from Amersham International , UK . Cellular extracts were resolved by SDS-PAGE and electroblotted onto nitro-cellulose membrane ( Amersham International , UK ) . Antibody incubation and detection were performed according to the protocol supplied with the kit . Primary antibody AB656 [26] was diluted 1/200 . | Protozoan parasites of the genus Leishmania generate a variety of pathologies , collectively termed leishmaniasis , which afflict millions of people worldwide . Leishmania is transmitted during the blood meal of infested sand flies that inoculate highly infective metacyclic promastigotes into the mammalian host . Following uptake by host macrophages , metacyclics differentiate into the amastigote form that replicates inside the acidified phago-lysosome of the host cell . The cytokine interferon-γ activates infected macrophages to kill intracellular Leishmania through the production of nitric oxide . This process is mediated through Stat 1 , a cytosolic transcription factor that translocates into the nucleus in response to the cytokine , where it induces a pleiotropic anti-microbial response . By utilizing Stat1-deficient macrophages we found evidence for a novel interferon-γ-independent physiological function of Stat1 in acidification of the host cell phago-lysosome . Stat1-deficient macrophages showed higher phago-lysosomal pH and increased susceptibility to Leishmania infection , which was linked to a defect in cellular chloride channel function . Vesicular pH and acidification are important factors affecting the infective cycle of bacterial and protozoan pathogens , and the uncoating process during viral entry . Thus , the role of cytokine-independent Stat1 functions in innate anti-microbial resistance may have a greater impact on host-pathogen interactions than previously appreciated . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis"
] | 2009 | A Novel Role for Stat1 in Phagosome Acidification and Natural Host Resistance to Intracellular Infection by Leishmania major |
Olfactory receptor neurons ( ORNs ) must select—from a large repertoire—which odor receptors to express . In Drosophila , most ORNs express one of 60 Or genes , and most Or genes are expressed in a single ORN class in a process that produces a stereotyped receptor-to-neuron map . The construction of this map poses a problem of receptor gene regulation that is remarkable in its dimension and about which little is known . By using a phylogenetic approach and the genome sequences of 12 Drosophila species , we systematically identified regulatory elements that are evolutionarily conserved and specific for individual Or genes of the maxillary palp . Genetic analysis of these elements supports a model in which each receptor gene contains a zip code , consisting of elements that act positively to promote expression in a subset of ORN classes , and elements that restrict expression to a single ORN class . We identified a transcription factor , Scalloped , that mediates repression . Some elements are used in other chemosensory organs , and some are conserved upstream of axon-guidance genes . Surprisingly , the odor response spectra and organization of maxillary palp ORNs have been extremely well-conserved for tens of millions of years , even though the amino acid sequences of the receptors are not highly conserved . These results , taken together , define the logic by which individual ORNs in the maxillary palp select which odor receptors to express .
Odor discrimination is based on the differential activities of olfactory receptor neurons ( ORNs ) , which in turn depend on the odor receptors that the ORNs express [1 , 2] . This raises an intriguing problem: how do individual ORNs select , from among a large repertoire , which receptor genes to express ? Two models—a deterministic model and a stochastic model—are often proposed to explain the problem of receptor gene choice [3] . In the deterministic model , different receptor genes contain different combinations of cis-acting elements , and an individual gene is selected in those ORNs with corresponding transcription factors . In the stochastic model , individual receptor genes are selected by an unknown , singular entity or process that can act on only one gene at a time . In mammals , the expression of an individual receptor is restricted to a particular zone of the olfactory epithelium , but within a zone , the choice of one receptor by a neuron is widely believed to be accomplished via a stochastic mechanism , followed by negative-feedback inhibition [4–6] . Only a single allele of an OR gene is expressed in an ORN [7] , a property that has recently been found to be widespread among 4 , 000 autosomal genes surveyed in the human genome [8] . A 2 . 1-kb region called the H element , defined by its high homology between human and mouse , was shown to be required for normal expression of several OR genes adjacent to it [4] . Further analysis of the H element suggested an elegant model in which it also acts as a trans-acting enhancer element that allows stochastic activation of a single OR gene in each neuron [5]; however , recent data have favored a model in which the primary function of the H region is to act in cis , as one of many cis-regulatory elements required for OR expression in the mouse [4 , 9 , 10] . These results focus attention on the question of how cis-regulation might underlie the strikingly sophisticated problem of receptor gene choice . The fruit fly Drosophila melanogaster contains two olfactory organs , the antenna and the maxillary palp , each covered with olfactory sensilla ( Figure 1A ) . Each sensillum contains ORNs , usually two , combined according to a strict pairing rule . In the antenna , each ORN class is restricted to a zone of the antennal surface , with zones showing varying degrees of overlap ( Figure 1A and [11] ) . In the maxillary palp , physiological data showed that different types of sensilla , and by extension , different classes of ORNs , appear to be largely if not completely coextensive , as if the maxillary palp constituted a single zone [12] . There are 60 Odor receptor ( Or ) genes , most of which are expressed in either the antenna or the maxillary palp [13–16] . Each receptor is expressed in ORNs of a single functional class; ∼37 ORN classes have been defined [11 , 12 , 17–19] . Most ORN classes express a single receptor [19–22] . In an earlier study , we identified two regulatory elements that are required for organ-specific expression of receptor genes [23] . Within an organ , we found no evidence for a negative-feedback mechanism . However , we identified a cis- regulatory element required for receptor expression in one ORN class . These findings suggested the possibility that neuron-specific odor receptor choice in Drosophila may depend on a sophisticated combinatorial code of cis-regulatory elements , as opposed to a stochastic mechanism followed by a negative feedback mechanism . The results thus laid a foundation for a systematic investigation of the most challenging aspect of the problem: how different receptors are expressed in different ORNs of an individual organ . The maxillary palp was chosen because it offers the virtue of numerical simplicity . It contains ∼120 ORNs , which are housed in three types of sensillum: pb1 , pb2 , and pb3 . Each sensillum contains two ORNs: pb1 contains pb1A and pb1B; pb2 contains pb2A and pb2B; pb3 contains pb3A and pb3B . The odor response profile of each ORN has been defined and a receptor-to-neuron map has been established [12 , 21] . Seven Or genes are expressed in the maxillary palp , with two genes coexpressed in the pb2A neuron . We systematically identified novel regulatory elements that dictate the proper expression of the maxillary palp Or genes in the correct ORNs , that is , elements that underlie the receptor-to-neuron map . These elements were identified by using a phylogenetic approach , much as the H element was identified through a comparison of two species . We compared the regulatory regions of orthologs from two Drosophila species whose genomes have been sequenced , and we identified elements that are evolutionarily conserved and that are specific to individual maxillary palp Or genes . Analysis of these elements across all 12 sequenced Drosophila genomes identified six that are conserved particularly highly . Functional analysis of these six elements reveals that some act positively to express individual Or genes in a subset of ORNs , and some act negatively to restrict the expression of individual Or genes to a single ORN class . Repression can be mediated via upstream or downstream regions , and in one case is mediated by the transcription factor Scalloped . Some elements are also used in other chemosensory organs , and some are conserved upstream of genes required for ORN axon targeting , sorting , and guidance . Taken together , the data support a model in which the receptor-to-neuron map is constructed via a system of molecular zip codes . Or genes contain three classes of regulatory elements: elements that specify expression in the correct organ , positive elements that activate Or genes in a subset of ORN classes within an organ , and negative elements that restrict expression to a unique ORN class within that organ . We propose that the concerted action of these three classes of elements thus solves a formidable biological regulatory problem . We carried out a functional analysis of the D . pseudoobscura maxillary palp . Surprisingly , we found a remarkable degree of conservation in the response spectra of the ORNs over tens of millions of years of evolution . The receptor-to-neuron map is also conserved .
We examined the spatial organization of ORN classes in the maxillary palp . First , an anti-Elav antibody was used to illustrate the distribution of the entire population of ORN nuclei of the maxillary palp ( Figure 1B ) . Second , we carried out a multiple-label experiment to differentially mark ORNs of the three types of sensilla: ORNs of the pb1A class were labeled in green , pb2B in yellow , and pb3A in red . The three classes of ORNs show extensive spatial overlap ( Figure 1C ) . These results are consistent with the intermingling of sensillum types that are observed when recordings are taken from sensillar shafts [12] . The spatial overlap of ORN nuclei indicates that the identity of an ORN and , by extension , its choice of a receptor gene , are not dictated solely by its spatial position in a field . We previously compared the upstream regions of the two Or genes coexpressed in pb2A to identify regulatory sequences shared by these two genes , but not by any other maxillary palp Or gene [23] . To identify upstream regulatory elements for the other five maxillary palp Or genes , we used a different strategy based on phylogenetic analysis . D . melanogaster and D . pseudoobscura diverged tens of millions of years ago [24] and contain orthologous receptor genes . We examined the upstream regions of orthologous Or genes for conserved elements shared by the members of each orthologous pair , but not by any of the other maxillary palp Or genes . Accordingly , we identified all conserved upstream sequences greater than 6 base pairs ( bp ) in length for each pair of orthologs using DOT-PLOT analysis ( Figure S1A ) , and from these conserved elements we selected those that were specific to each gene . The analysis was focused on the 500 bp that are upstream of the translational start site , because in a previous study , this extent of DNA was sufficient to confer faithful expression to a GAL4 reporter gene in the case of each of two maxillary palp Or genes analyzed in detail [23] . One pair of orthologs , Or85d and its D . pseudoobscura counterpart , was exceptionally well-conserved in the 500-bp upstream region , showing 80% identity . To identify discrete conserved elements within the region upstream of Or85d , we expanded our analysis to include a more divergent species , D . virilis . Conserved , gene-specific elements were identified for each of the five Or genes analyzed ( Figure 1D ) . The number of such elements varies: Or59c contains one , whereas Or42a contains six . In the special case of Or85d , two elements are shared by D . virilis and D . melanogaster upstream of Or85d , but are not found upstream of any other maxillary palp Or gene . To identify the best candidate for a regulatory element for each of these receptor genes , we used a powerful bioinformatic approach that takes advantage of the recent sequencing of the genomes of ten other Drosophila species: D . simulans , D . sechellia , D . yakuba , D . erecta , D . ananassae , D . persimilis , D . willistoni , D . virilis , D . mojavensis , and D . grimshawi . The upstream regulatory regions of the orthologous receptor genes from all 12 species were aligned ( Figure S1B ) using the genome browser at the University of California Santa Cruz , and each of the elements was mapped onto the alignment . Using this approach , we were able to identify the gene-specific element with the highest sequence conservation for each of the receptor genes ( Figures 1E and Figure S1 ) ; in the case of Or42a , two elements were nearly identical in their extent of conservation , and we have analyzed both . To determine whether the evolutionarily conserved , gene-specific elements have a regulatory function , we tested them in vivo using two complementary approaches , one based on a loss of function and one on a gain of function . For each gene , we analyzed the element with the highest sequence conservation . We did not analyze Or85d elements because we lacked a faithful Or85d-GAL4 driver . Or46a is expressed in the pb2B neuron , and its upstream region contains two conserved , gene-specific elements ( Figures 1D and 1E and Figure S1 ) . One of these elements , 46a1 , is more highly conserved . It is 10 bp long , its sequence shows 93% identity across the 12 species , and its position is conserved . A 1 . 9-kb region of DNA upstream of Or46a drives faithful expression of a GAL4 reporter in pb2B ( Figure 2A and [21] ) . However , when the 46a1 element is mutated , the 1 . 9-kb region no longer drives expression ( Figure 2B ) . In most cases , no cells are labeled; in rare cases , a single ORN is labeled ( n = 0 . 52 ± 0 . 24 cells/maxillary palp; n = 8 independent lines examined; n > 10 maxillary palps examined per line ) . The simplest interpretation of these results is that the 46a1 element is necessary for Or46a expression in pb2B . We then asked whether the 46a1 element can drive expression in the context of a minimal promoter . We placed four copies of 46a1 upstream of a TATA box and found that this small construct can in fact drive expression in maxillary palp cells ( Figure 2C ) . Many , if not all , of the cells could be identified as ORNs , because they contain dendrites and axons; their identity is considered further below . Expression from this artificial promoter could also be detected in a small subset of neurons in the main gustatory organ , the labellum ( unpublished data ) . Or71a is expressed in pb1B . Its upstream region contains multiple gene-specific elements , of which the longest and best conserved is 71a3 , consisting of 16 bp and showing 97% sequence identity . This element was tested in the context of the Or71a 5′ + 3′ construct , which contains sequences both upstream and downstream of Or71a [21] . This construct drives faithful expression of GAL4 when the 71a3 element is intact ( Figure 2D and [21] ) , but not when it is mutated ( Figure 2E; n = 0 . 25 ± 0 . 1 cells/maxillary palp; n = 8 independent lines examined; n > 20 maxillary palps examined per line ) . When multiple copies of 71a3 were placed upstream of a TATA box , the construct drove GAL4 expression in maxillary palp cells that can be identified as ORNs by virtue of their dendrites and axons ( Figure 2F ) . Low levels of expression could also be detected in a small subset of cells in the labellum ( unpublished data ) . Or59c is expressed in pb3A , and its upstream region contains a single gene-specific conserved element , 59c1 , which is 11 bp long and shows 97% sequence identity across nine species ( Figure 2G ) ; the region containing the 59c1 sequences could not be identified in three of the most distantly related species , D . virilis , D . mojavensis and D . grimshawi . We have tested its function by placing multiple copies upstream of a TATA box and found that this minimal promoter drove robust expression of GAL4 in the maxillary palp ( Figure 2H ) . Expression was not detected in the labellum . Earlier studies have shown that the expression of a subset of the maxillary palp Or genes requires the POU domain transcription factor Acj6 [25] , which is expressed in all ORNs of the maxillary palp [46] . Acj6 also controls axon targeting specificity of a subset of maxillary palp ORNs . The 46a1 , 71a3 , and 59c1 elements do not contain predicted Acj6 binding sites ( Bai L , Carlson JR , unpublished results ) , and the transcription factors that act on these sequences are unknown . To test whether the factors that act on these neuron-specific elements are dependent on acj6 , we examined the expression of the minimal promoter constructs in an acj66 background . In the acj66 mutant , although the expression of the Or46a-GAL4 driver is lost , which is consistent with the loss of Or46a mRNA observed previously [13] , the expression of the 46a1 minimal promoter construct is still strong ( Figure 2I and 2J ) . These results suggest that the factors that direct expression from the 46a1 motif are independent of acj6 for their expression and function ( Figure 2K ) . An alternative possibility is that another transcription factor can compensate for the loss of acj6 . Expression of the Or71a-GAL4 driver can be detected in acj6 , and the expression of the 71a3 minimal promoter construct can also be detected ( Figure 2L and 2M ) . These results suggest that the factors binding to 71a3 do not require acj6 for their expression or function ( Figure 2N ) . In the case of Or59c , we find that acj6 is required both for expression of the gene and for the minimal promoter ( Figure 2O and 2P ) . These results suggest that acj6 is required directly or indirectly for the expression of the 59c1 binding factor or for its function at the 59c1 site ( Figure 2Q ) . Or42a is expressed in pb1A , and 4 . 1 kb of upstream DNA drives faithful expression of GAL4 in maxillary palp ORNs [21] . Two elements are nearly identical in their high conservation: 42a4 ( 98% ) and 42a6 ( 98% ) , and we tested the function of both elements in vivo . 42a6 maps only three bp from 42a5 ( Figure 1D ) . We constructed a small deletion that eliminates both 42a6 and 42a5 elements , and we found no effect on Or42a-GAL4 expression ( unpublished data ) . The longer of the two most highly conserved elements at Or42a , 42a4 , contains an inverted repeat: AGTGTAAAAGTTTACACTT . We were surprised to find that mutation of this element led to a 2-fold increase in the number of labeled maxillary palp cells , from 18 . 2 ± 1 . 8 ( n = 9 maxillary palps ) to 33 . 2 ± 3 . 7 ( n = 9 maxillary palps quantified from two independent lines; n = 8 independent lines examined , n > 20 maxillary palps examined/line ) ( Figure 3A–3C ) . The simplest interpretation of this result is that 42a4 is a negative regulatory element that represses Or42a in a subset of ORNs . To test this interpretation , we first carried out a double-label experiment using probes for the endogenous Or42a mRNA and for the green fluorescent protein ( GFP ) that is driven by the mutant promoter via GAL4 . We found that all Or42a+ cells express GFP , but that GFP is also expressed in an additional subset of cells ( Figure 3D ) . To identify the cells that ectopically express GFP , we undertook a series of additional double-label experiments . We found that the GFP+ cells do not express Or59c mRNA , indicating that they are not pb3A neurons ( Figure 3E; 0% of the GFP+ neurons are Or59c+; n = 8 maxillary palps ) ; nor are they paired with cells that express Or59c mRNA , indicating that they are not pb3B neurons . In another experiment , GFP+ cells did not label with an Or33c probe ( only 3% of the GFP+ neurons appear Or33c+; n = 8 maxillary palps ) , indicating that they are not pb2A neurons; however , GFP+ cells were often found paired with Or33c+ cells ( arrowheads ) , indicating that many GFP+ cells are pb2B neurons ( Figure 3F ) . The identity of these GFP+ cells as pb2B neurons was confirmed directly in another double-label experiment using a probe for Or46a mRNA ( Figure 3G; 94% of the cells labeled with Or46a mRNA were GFP+; this value is the mean of values determined from n = 8 maxillary palps ) . The simplest interpretation of these results is that positive regulatory elements in the Or42a upstream region are capable of driving expression not only in the pb1A neuron but also in the pb2B neuron . The 42a4 element represses expression in pb2B neurons , thereby restricting expression to a single ORN class , pb1A . The ectopic expression of an Or42a promoter in Or46a+ neurons suggested a relationship between these two genes . Further evidence for a relationship came from analysis of the minimal promoter containing multiple copies of 46a1 ( Figure 2C ) . This promoter drove GFP expression in more ORNs than could be accounted for by Or46a+ neurons alone . A double-label experiment showed that while most of the GFP+ cells are in fact Or46a+ , some are Or42a+ ( Figure 3H ) . The reciprocal relationship between Or42a and Or46a misexpression suggests that Or42a may contain an unidentified positive regulatory element , 42ax , that is similar in sequence to 46a1 , with both sites able to bind a transcription factor present in both pb1A and pb2B . To test this interpretation , we examined the 500 bp upstream region of Or42a for an element similar , but not identical , to 46a1 ( GACATTTTAA ) . We identified a sequence , TATATTTTAA , identical to 46a1 at the 8 underlined positions , at −455 bp . Moreover , these two sequences share an ATTTTA core , which has been shown to function as a binding site for basic helix-loop-helix transcription factors at other loci . TATATTTTAA is not found upstream of any other maxillary palp Or genes . This 42ax sequence is conserved in sequence ( 80% identity ) and location in seven of the 12 Drosophila species . It will be interesting to identify the transcription factor that binds 46a1 and then test directly its binding to 42ax . When DNA upstream of Or59c was fused to GAL4 , expression of the reporter GFP was not faithful ( Figure 4A; n = 5 independent lines ) ; the same result was obtained when upstream regions of varying lengths were used ( either 2 . 1 kb , which extends to the next upstream gene , or 5 . 2 kb , which includes upstream coding sequences ) . Double-label experiments using an Or59c probe revealed misexpression in many Or59c– cells; moreover , many Or59c+ cells did not express GFP . Some of the misexpressing cells are the neighboring pb3B neurons , which can be seen to be paired with Or59c+ pb3A cells ( arrowheads in Figure 4A; 75% of the cells neighboring the Or59c+ cells were GFP+ , n = 9 palps ) . To identify the other ORNs that ectopically express the Or59c-GAL4 construct , we carried out double-label experiments with other Or genes . Misexpression was also observed in pb1A cells , which express Or42a ( 96% of the Or42a+ cells misexpressed GFP , n = 9 palps ) , but not in the pb1B cells ( Figure 4B ) , nor in the pb2A or B cells ( Figure 4C ) . In summary , misexpression is specific to pb1A and pb3B . Because neither of the varying lengths of upstream DNA sequences were sufficient to restrict GAL4 expression to the Or59c+ cells , we added 3′ sequences to the construct . Initially , 500 bp of DNA taken directly from the region immediately downstream from the Or59c stop codon was added downstream of the GAL4 coding region . Between the downstream sequences of Or59c and the GAL4 coding region was the Hsp70 3′ untranslated region ( UTR ) , which is present in the GAL4 vector and which is often present in promoter-GAL4 analysis . This Or59c 5′ + 3′ construct showed much less misexpression in Or59c− cells ( Figure 4D ) . The total number of GFP+ cells declined from 49 . 7 ± 1 . 3 to 27 . 3 ± 2 . 1 ( SEM; n = 10 in each case ) . However , some misexpression remained , and only 62% of the Or59c+ neurons were GFP+ . We then removed the Hsp70 3′ UTR sequences , such that the Or59c downstream sequences were in close proximity to the 3′ end of the GAL4 coding region and the Or59c 3′ UTR is used . This construct drove faithful expression ( Figure 4E; n = 8 independent lines examined ) . Thus , there is a negative regulatory element downstream of Or59c that restricts expression of this gene to pb3A neurons , and either there is a requirement that the native 3′ UTR be used , or else there is a regulatory factor that acts on this element in a context-dependent fashion in order to achieve this negative regulation . We note with interest that the inclusion of the downstream sequences , without the Hsp70 sequences , also drove expression in Or59c+ neurons that had previously failed to express the reporter , suggesting that the downstream sequences are required for positive as well as negative regulation of Or59c . Inspection of the sequences downstream of Or59c that repressed misexpression revealed a binding site for the transcription factor Scalloped ( Sd ) , AAATATTT [26] ( Figure 5A ) . This site is well-conserved among a number of other species ( Figure S2A ) . Sd has been shown to be expressed in olfactory organs [27] . To confirm and extend the description of sd expression we used an enhancer trap line , sdETX4 [27] , and confirmed that sd is expressed in a subset of cells in the maxillary palp ( Figure 5B and 5C ) . To test whether sd represses Or59c , we carried out in situ hybridizations to the maxillary palp of a hypomorphic sd mutant , sd1 ( Figure 5D ) . We found a 40% increase in the number of Or59c+ neurons ( Figure 5E ) . By contrast , there was no increase in the number of Or42a+ neurons ( Figure 5D and 5E ) . There was , however , an increase in the number of Or85d+ cells , and we note with interest that there is another type of Sd binding site , TAAAATTA [26] , 737 bp downstream from the stop codon of Or85d . The Or59c-GAL4 construct that contains only upstream sequences , Or59c 5′ , misexpresses in two ORN classes , the neighboring pb3B cell ( Or85d+ ) and pb1A ( Or42a+ ) , as shown above in Figure 4 . We asked whether sd is expressed in these two ORN classes . Using an Or59c probe , which labels the pb3A cell , we found that sd is in fact expressed in neighboring cells ( Figure 5F ) , but not in pb1A cells , which express Or42a ( Figure 5G ) . These results suggest that Sd may repress the Or59c gene in pb3B . If so , we would expect that in an sd mutant , we would observe cells that coexpress Or59c and Or85d . We tested this possibility by carrying out double-label in situ hybridizations in two different hypomorphic alleles of sd , sd1 , and sdSG29 . 1 [28] . In both alleles , we found Or59c+ Or85d+ cells ( Figure 5H ) , but not Or59c+ Or42a+ cells ( unpublished data ) . Thus repression of Or59c in the neighboring pb3B cell requires both a Sd binding site and Sd . Since Sd represses Or59c in pb3B , why doesn't Sd also repress Or85d in pb3B , given that both Or genes have Sd binding sites ? The simplest explanation is that the two Sd binding sites are distinct . There are several potential interacting partners with which Sd may interact to form a functional transcription factor [26 , 29] , and the pb3B cell may contain a partner necessary for repression at the Or59c binding site but not a partner necessary for repression at the Or85d binding site . If a faithful Or85d-GAL4 construct becomes available , it will be interesting to replace the Or85d-type Sd binding site with the Or59c-type Sd binding site , to determine whether the Or59c-type site confers repression in the pb3B cell . We note that Or85d-GAL4 constructs containing only the 5′ regions of Or85d , which lack the Sd binding site , drive misexpression in a number of non-neuronal cells of the maxillary palp ( Figure S2B ) . Most of the labeled cells lack dendrites and axons , and when labeled with a membrane-bound GFP , as opposed to with RNA probes that label the cell bodies , these cells appear larger than ORNs . These results suggest that Sd may interact with a binding partner in non-neuronal cells to repress Or85d expression in these cells . Or42a is expressed in the larval olfactory system as well as in the maxillary palp [21 , 30] . The Or42a-GAL4 construct shows expression in one ORN in each of the bilaterally symmetric larval olfactory organs , the dorsal organs ( Figure 6A ) . We also observed expression in two neurons of the labellum , the taste organ on the adult head ( Figure 6A ) . To determine whether the conserved elements identified in our analysis of maxillary palp receptor choice can act in these other chemosensory organs , we examined Or42a-GAL4 constructs in which these elements were mutated . A mutation that affects both 42a6 and 42a5 , which did not affect expression in the maxillary palp , had no effect on expression in these other organs . However , mutation of 42a4 , which relieved repression of Or42a in other maxillary palp ORNs , also relieved repression of Or42a-GAL4 in the larval olfactory organs and the labellum ( Figure 6B ) : in both cases supernumerary neurons were labeled . In the labellum , ∼8–10 pairs of neurons were labeled . These results suggest that the molecular mechanisms underlying receptor gene choice in the maxillary palp overlap with those specifying receptor expression in other chemosensory organs . In this study we have identified and functionally characterized a number of regulatory elements that operate in directing the formation of the receptor-to-neuron map of D . melanogaster . Because the newly defined elements we have analyzed here are conserved in sequence and position among Drosophila species , we predicted that the programmed regulation leading to the formation of receptor-to-neuron maps would be conserved as well . To test this prediction , we carried out a physiological analysis of the D . pseudoobscura maxillary palp . Although each of the seven Or genes expressed in the maxillary palp has an ortholog expressed in the D . pseudoobscura maxillary palp ( as described [21] and unpublished data ) , we expected that their odor response profiles would have diverged a great deal over the course of tens of millions of years . We did not know a priori whether we would be able to correlate D . pseudoobscura ORNs with D . melanogaster counterparts . We were surprised to find that the profiles of the maxillary palp ORNs are remarkably well conserved between these two species ( Figure 7 ) . Despite the tens of millions of years of separation , each ORN class in D . melanogaster has a counterpart in D . pseudoobscura , and their responses to a panel of ten diverse odorants are strikingly similar . Not only are the magnitudes of the responses well conserved , but the modes of the responses , i . e . , excitation versus inhibition , are conserved . For example , both the pb2B ORN of D . melanogaster and its D . pseudoobscura counterpart are excited by 4-methyl phenol and inhibited by 3-octanol . The orthologous receptors show amino acid identity as low as 59% in the case of Or71a ( Figure S3 ) , and in no case exceeded 84% , the identity determined for Or42a . Thus pb1B in D . melanogaster , which expresses Or71a , shows the same specificity for 4-methyl phenol and 4-propyl phenol as the corresponding ORN in D . pseudoobscura , although Or71a is only 59% identical between the two species . The conservation of odor response spectra allows us to determine that the stereotyped pairing of ORNs is also conserved in the two species . These results suggest that not only are the response spectra of the odor receptors conserved with respect to a diverse panel of odorants , but that the program of receptor gene expression is also conserved between these distantly related species . Given the success in identifying gene-specific elements required for the expression of individual Or genes in individual classes of ORNs , we asked whether the same approach could be used to identify sensillum-specific elements required uniquely by the Or genes that are expressed in the neighboring ORNs of a common sensillum . We searched for sensillum-specific elements conserved in the upstream regions of D . melanogaster and D . pseudoobscura Or genes . Only one element , AAATCAATTA , was found upstream of all orthologs expressed in a particular sensillum type ( Figure S4A and [23] ) . Mutational analysis of this element in the Or42a promoter did not , however , appear to affect expression ( Figures S4B–S4E ) . Furthermore , expression was not affected by mutation of the more proximal of the two copies of this element in the Or71a upstream region ( unpublished data ) . These results suggest that this element is not required for expression in the pb1 sensillum .
We have analyzed the problem of how individual ORNs select which receptor genes to express , a fundamental problem that underlies all odor coding . In Drosophila , the foundation of olfactory perception is a stereotyped receptor-to-neuron map . The developmental process by which this map is constructed has been examined here using an analysis of evolutionary conservation as a point of departure . We identified conserved , gene-specific elements flanking five maxillary palp receptor genes . Functional analysis of the six most highly conserved elements confirmed that elements upstream of four of these genes act either positively or negatively in gene regulation , thereby validating the experimental approach . Two elements did not appear to be required for normal gene regulation; however , it is possible that they act in a redundant fashion or that they mediate a response to such epigenetic factors as feeding status , mating status , or circadian rhythm , which we did not examine . The elements varied in length from 7 to 19 bp; some of the longer ones could be composite sites that bind more than one factor . Several of the sites contain AT-rich cores , reminiscent of binding sites for certain classes of transcription factors including POU domain proteins . One element , 42a4 , contains two iterations of an octamer , in an inverted repeat . Two elements , 46a1 and 71a3 , overlap with a Dyad-1 element , CTA ( N ) 9TAA , a positive regulatory element that is required for normal maxillary palp expression and that is found upstream of all of these maxillary palp Or genes [23] . The close juxtaposition of regulatory elements suggests an interaction among the regulatory proteins that they bind . Our strategy for identifying these elements required that each be specific to a single maxillary palp Or gene . The identification of these elements reveals that each gene contains at least one unique element that is not shared with any other maxillary palp Or genes . This need not have been the case: the system could alternatively have been composed entirely of nonunique regulatory elements , each shared by multiple genes , but in unique combinations . In any case , in the maxillary palp the combinatorial code of cis-acting elements appears to include both unique and shared elements ( e . g . , Dyad-1 ) . The regulatory elements and the logic by which they operate are summarized in Figure 8 . Positive regulatory elements direct expression in subsets of maxillary palp ORNs . Negative regulatory elements restrict this expression to a single ORN class . Overall , the correct expression pattern is determined by the interplay of positive and negative elements . The negative regulation we have observed is highly specific . When the 42a4 element was ablated , Or42a misexpression was observed specifically in pb2B . One possible interpretation is that pb2B and pb1A , the cell that normally expresses Or42a , share a positively acting transcription factor that other ORNs lack . Thus the two ORNs with contexts that are permissive for Or42a expression are not neighboring ORNs that share a sensillum , but ORNs in different sensilla , with very different odor response profiles . Reciprocally , a positively acting element upstream of Or46a , which is expressed in pb2B , drives expression not only in pb2B but also in pb1A . This connection between pb1A and pb2B suggests a developmental relationship that remains to be defined in mechanistic terms . This study has concentrated on receptor gene choice in the maxillary palp , on account of its numerical simplicity . Does a system of molecular zip codes also underlie the process of receptor gene choice across the entire odor receptor repertoire ? In addition to the seven maxillary palp receptors , the Or gene family contains 53 other members expressed in the antenna or the larval olfactory system [19 , 30–32] . Using a comparative bioinformatic approach , we performed a large-scale analysis of sequence conservation in the 500 bp upstream of each of 42 Or genes across all 12 Drosophila species ( Figure S5 and Text S1 ) . We found great diversity in the number , lengths , and distribution of highly conserved upstream regions . Within the most highly conserved of these regions we identified a variety of elements that are shared among subsets of Or genes ( Figure S6A and S6B ) . This analysis , then , reveals a combinatorial structure to the organization of shared elements upstream of these receptor genes . This pattern supports a model in which a combinatorial code of positive and negative regulatory elements dictates the proper expression of each Or gene . What kind of proteins accomplish this regulation ? In C . elegans , several kinds of transcription factors have been elegantly shown to play roles in specifying ORN identity and receptor expression [33] . In the mouse , a LIM-homeodomain protein , Lhx2 , is required for normal ORN differentiation and expression of OR genes [34 , 35] . In Drosophila the POU domain protein Acj6 is required for the expression of a subset of Or genes [36] . We have also shown that Sd , a TEA domain-containing transcription factor , is critical in restricting the expression of some Or genes to their proper ORNs . Sd has been shown to act as a repressor in other systems and in fact is required for normal taste behavior in both larvae and adults [37] . Another aspect of receptor gene choice depends on proteins of the Notch pathway: receptor choice in neighboring ORNs of a sensillum appears to be coordinated via asymmetric segregation of regulatory factors from a common progenitor [23 , 38] . Some elements that are essential to odor receptor gene choice are also located upstream of genes required for axon guidance and sorting ( Figure S7 and Text S1 ) . The presence and positions of these elements have been conserved for tens of millions of years of evolution . The presence of Or regulatory elements upstream of ORN axon-guidance genes could reflect a relationship between receptor gene choice and axon targeting . In addition to selecting particular Or genes for expression , ORNs send axons to particular glomeruli in the antennal lobe of the brain . ORNs that express the same Or gene send axons to the same glomerulus [16 , 19] . Thus the olfactory system contains both a stereotyped receptor-to-neuron map and a stereotyped connectivity map in the antennal lobes . The tight coordination between receptor gene choice and axonal projection could in principle arise in part from overlap in the mechanisms underlying these processes . In mammals , odor receptors play a role in ORN targeting [39–41] . In Drosophila , ORN targeting does not require the receptors [20] , but could require the regulatory apparatus used to express the receptors . Acj6 provides an example of a link between the two processes: it acts both in receptor expression and ORN axon targeting ( Figure 2 ) [13 , 25] . Moreover , we have found that Acj6 is required for the activity of one of the regulatory elements identified here . We found a remarkable similarity of function between the maxillary palp ORNs of two species that diverged more than tens of millions of years ago . We had expected that over this time interval , the odor specificities of the ORNs would have diverged markedly to serve differing needs of the two evolving species . Instead , every ORN class showed strikingly similar responses , with few exceptions . The results show that two odor receptors can differ a great deal in amino acid sequence and still exhibit a very similar odor specificity . The organization of the organ in the two species is also identical , in that corresponding ORNs are combined according to the same pairing rules . This high degree of conservation suggests a critical role for the maxillary palp in odor coding and in the generation of olfactory-driven behavior . The conservation of regulatory elements and organization also suggests that the two species use common mechanisms to specify the receptor-to-neuron map . The regulatory challenge confronted by the Drosophila olfactory system represents an extreme among problems of gene regulation . It requires the storage and deployment of a great deal of information . Our data support a model in which Or gene expression is controlled by a system of molecular zip codes . Each Or gene contains elements that dictate expression in the proper olfactory organ [23] , positive regulatory elements that specify expression in a subset of ORN classes , and negative regulatory elements that restrict expression to a single ORN class . This logic and the components that execute it have solved such a challenging problem with such efficiency that they have apparently been well conserved for tens of millions of years .
Drosophila stocks were raised at 25 °C . Wild-type flies were Canton-S unless otherwise indicated . sd1 and sdETX4 , referred to here as sd{PlacZ} , were obtained from the Drosophila Stock Center ( Bloomington , Indiana ) . sdSG29 . 1 was a gift from S . Cohen . D . pseudoobscura was from the Drosophila Species Resource Center ( Tucson , Arizona ) . w; UAS-mCD8-GFP/CyO;UAS-mCD8-GFP was used as a source of GFP unless otherwise indicated . All DNA constructs were sequenced and then injected along with Δ2 , 3 transposase plasmid into w1118 flies . Multiple transgenic lines , in most cases eight , were generated and tested for each construct . To identify gene-specific conserved sequences in the upstream maxillary palp Or genes , we used ClustalW alignments and DOT-PLOT analysis ( MacVector ) . To map identified cis-elements to sequences and identify overrepresented motifs , the DNA-PATTERN ( STRINGS ) and OLIGO-ANALYSIS programs were used at the RSA tools website ( http://rsat . scmbb . ulb . ac . be/rsat/ ) . For the identification of conserved sequences the Drosophila genome browser at http://genome . ucsc . edu/ was used . A multiple alignment was constructed using MULTIZ from the best-in-genome pairwise alignments generated by BLASTZ . Large-scale predictions of conserved elements were obtained from the multiple alignments using the PhastCons program with the most-conserved option . Shared elements were identified using the OLIGO-ANALYSIS program at the RSA tools website . The wild-type Or42a 4 . 1-kb promoter-GAL4 construct has been described previously [21] . In ( 42a4 ) -GAL4 , the 42a4 element , which contains an inverted repeat ( AGTGTAAANNTTTACACT ) , was mutated to ( AGTG–––TTTGGATCC ) , resulting in a deletion within the first half-element and the substitution of a BamHI recognition sequence in the second half-element ( italicized ) . This was accomplished by PCR amplification of two promoter fragments , one terminating immediately upstream of the TAAA in the first octamer of the 42a4 element , and the second wasa fragment extending from immediately downstream of this element to the start codon of Or42a . Primers for these PCR reactions contained the BamHI restriction site in place of ACACTT . The PCR products were AT-cloned into pGEM-T Easy . Subsequent ligation of the two PCR fragments resulted in the desired replacement in the context of the Or42a 4 . 1-kb promoter-transgene . In the ( 42a5+6 ) -GAL4 construct a small deletion was designed to delete both the 42a5 and the 42a6 elements , which are separated by 3 bp ( TGTGAACGATTGCAGCCTG ) . This was achieved by using a similar approach as for 42a ( 4 ) -GAL4 , but in this case the two primers , containing BamHI sites at their ends , were designed to start immediately upstream of 42a6 and immediately downstream of 42a5 . Ligation of the appropriate fragments led to the replacement of the entire 19-bp region , comprising the two elements , by a BamHI site . In the ( 46a1 ) -GAL4 construct the 46a1 element ( GACATTTTAA ) was mutated by replacing the first six bases with a BamHI restriction site . This was achieved using a PCR cloning strategy similar to the ones described for the Or42a constructs . In the ( 71a3 ) -GAL4 construct the 71a3 element ( TGAATTTTAATTGAAA ) was mutated to ( GCTAGCTTAATTGAAA ) by replacing the first six bases with a NheI restriction site using a PCR cloning strategy similar to the one described earlier , resulting in the desired mutation in the context of the Or71a 5′ + 3′-GAL4 construct . We note that 46a1 and 71a3 each overlaps with a Dyad-1 motif , CTA ( N ) 9TAA , a positive regulatory element that is required for expression of Or genes in the maxillary palp [23]; the mutations of 46a1 and 71a3 were designed so as not to affect the Dyad-1 motif . The Or59c 2 . 1-kb promoter-GAL4 construct has been described in [21] and has been shown to express in a large number of non-endogenous cells in the palp . The Or59c 5′ + 3′-GAL4 was constructed by cloning a 0 . 5-kb fragment of DNA that lies immediately downstream of the Or59c stop codon into the SpeI/BamHI site that is positioned downstream of the GAL4-hsp70 3′ UTR in pG4PN . The 0 . 5-kb fragment was PCR-amplified from Canton-S genomic DNA with primers designed to add a Spe1 site to the 5′ end and a BamHI site to the 3′end . The Or59c ( 5′ + 3′ direct ) -GAL4 construct was made in several steps . First the 0 . 5-kb fragment of DNA immediately downstream of the Or59c stop codon , described above , was cloned into the BamHI/Spe1 site of pSK+ to generate plasmid pSK3' . Second , the GAL4 coding region was cloned as a HindIII fragment into pSK3' to yield pSKGAL4 . The Or59c 5′ region was excised from the Or59c 2 . 1kb-GAL4 vector using KpnI/NotI ( blunted ) and it was KpnI/blunt cloned into the Kpn1/Apa1 ( blunted ) site of the pSKGAL4 plasmid . Finally the KpnI/SpeI fragment from this plasmid was ligated with the KpnI/SpeI fragment of pG4PN to yield Or59c complex-GAL4 . Complementary pairs of oligonucleotides were designed such that upon annealing , they would yield a double-stranded DNA fragment that includes multiple copies of the corresponding conserved elements and overhangs on either side for EcoR1 restriction enzyme sites . These fragments were cloned directly into the EcoR1 site of the pPTGAL Drosophila transformation vector [42] . The 46a1 sequence was GACATTTTAAATGCCCTAATGACATTTTAAATGCCCTAATGACATTTTAAATGCCCTAATGACATTTTAA . The 71a3 sequence was CTAATTGAATTTTAATTGAAACGTCACTAATTGAATTTTAATTGAAACGTCACTAATTGAATTTTAATTGAAACGTCA . The 59c1 sequence was GCAAACTGTAATTAGAGGACCGCAAACTGTAATTAGAGGACCGCAAACTGTAATTAGAGGACCGCAAACTGTAATTAGAGGACC . We note that the constructs for 46a1 and 71a3 contain Dyad-1 motifs , but these motifs are not sufficient to drive expression in the maxillary palp [23] . The underlined sequences indicate the gene-specific elements , and the italicized sequences indicate the Dyad-1 sequences . For each minimal promoter construct , at least two independent lines were examined , and n > 20 maxillary palps were examined for each line . In situ hybridization and immunohistochemical localization were performed as in [21] . Mouse anti-βGAL antibody ( 1:1000 ) , and rabbit anti-GFP ( 1:250 ) were obtained from Promega . To generate a high-resolution map of the nuclei of the three sensilla types ( Figure 1C ) , ( 42a4 ) -GAL4/UAS-GFP; UAS-GFP/+ was used to label pb1A and pb2B in green , and Or46a and Or59c in situ hybridization probes were used to label with red the pb2B and pb3A cells , respectively . Thus pb1A was labeled green , pb2B was labeled yellow ( red and green ) ; pb3A was labeled red . Confocal Z-stacks consisting of nine optical sections of each palp were analyzed in Photoshop . Positions of the labeled nuclei were manually marked with the corresponding color at each optical plane , and the 9 stacks were compressed to generate a 2-D representation of all the labeled neurons . Odors were delivered and action potentials were recorded as described previously [20] and in Text S1 . | Odors are detected by olfactory receptor neurons ( ORNs ) . Which odor an individual neuron detects is dictated by the odor receptors it expresses . Odor receptors are encoded by large families of genes , and an individual neuron must thus select the gene it expresses from among many possibilities . The mechanism underlying this choice is largely unknown . We have examined the problem of receptor gene choice in the fruit fly Drosophila , whose maxillary palp contains six functional classes of ORNs , each expressing different odor receptor genes . By comparing the DNA sequences flanking these genes in 12 different species of Drosophila , we have identified regulatory elements that are evolutionarily conserved and specific to each odor receptor . Genetic analysis of these elements showed that some act positively to dictate expression in a subset of ORNs , while others act negatively to restrict the expression of a receptor gene to a particular ORN class . We identified a transcription factor , Scalloped , that mediates repression . We were surprised to find that the odor response spectra of these neurons have been well-conserved for tens of millions of years , even though the amino acid sequences of their receptors have diverged considerably . | [
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] | 2008 | A Regulatory Code for Neuron-Specific Odor Receptor Expression |
We project forward total Zika virus disease ( ZVD ) under varying hazards of infection and consider how the age distribution of disease burden varies between these scenarios . Pathogens with age structured disease outcomes , such as rubella and Zika virus , require that management decisions consider their impact not only on total disease incidence but also on distribution of disease burden within a population . Some situations exhibit a “paradox of control” in which reductions of overall transmission decrease the total incidence but increase the incidence of severe disease . This happens because of corresponding increases in the average age of infection . Beginning with the current population structure and demographic rates of Brazil , we project forward total ZVD burden as measured by cases occurring in pregnant women and document the scenarios under which a paradox of control for ZVD management emerges . We conclude that while a paradox of control can occur for ZVD , the higher total costs from increasing the average age of infection will only be realized after several decades and vanish under conservative discounting of future costs . This indicates that managers faced with an emerging pathogen are justified to prioritize current disease incidence over potential increases in severe disease outcomes in the endemic state .
Zika virus ( ZIKV ) , a mosquito-borne pathogen first identified in Uganda in 1947 [1] and subsequently responsible for sporadic outbreaks [2] , has attracted major attention from health officials and the public at large as a result of an ongoing large outbreak in the Americas . The South American Zika virus disease ( ZVD ) outbreak began in Brazil in 2015 [2] and rapidly spread through South and Central America , with an estimated 500 , 000-1 , 500 , 000 cases in Brazil alone [3] . While Zika virus disease ( ZVD ) is usually asymptomatic or mild [2] , it has been linked to more severe complications in pregnant women [4] . The complication of greatest concern is microcephaly , where ZVD infection during fetal development impedes brain development . Concerns over microcephaly have led to calls for women to delay or strategically time pregnancy [5 , 6] . However , given the limited access to contraception and family planning services in much of Latin America [7] , it may be more practical to focus on population-level control efforts that do not rely on individual behavioral modification . In particular , there has been renewed attention on potential vector control strategies [8] to reduce the attack rate ( fraction of susceptible individuals experiencing infection ) across the entire population . For many diseases , minimizing attack rate is a straightforward way to reduce disease-associated mortality and morbidity . Attack rates determine not only the overall level of incidence , but also the average age of infection , with higher attack rates resulting in lower average age of infection [9] . For a disease which causes the most severe outcomes in younger individuals , such as measles , this suggests that reducing incidence also shifts the burden of disease away from the most vulnerable individuals . For a disease in which outcome severity can increase with age , such as rubella [10–12] or ZVD , decreases in the attack rate can shift cases into more vulnerable age classes . This may result in a “paradox of control” in which a reduction in incidence increases mortality and morbidity [13 , 14] . The paradox of control can lead to situations with multiple locally optimal management equilibria [15 , 16] and is the reason current WHO policy for rubella vaccination does not recommend implementing routine coverage below a threshold that is expected to reduce both total incidence and incidence in most-affected classes . The tradeoff in ( usually mild ) cases averted to a potential increase in incidence of congenital rubella syndrome ( CRS ) as seen in the Greek experience [17] is deemed unacceptable . However , analyses of the tradeoff between rubella incidence and CRS burden [13 , 18] have been based on an equilibrium incidence assumption . As ZVD is a newly emerging pathogen in a previously naïve population , it is not at equilibrium yet and we do not know what the incidence and age distribution will be at equilibrium . Additionally , our understanding of ZVD is rapidly expanding as new control methods such as genetically modified mosquitoes [19] and ZIKV vaccines [20–22] may change the eventual equilibrium level and distribution of ZIKV incidence . We believe that cost-benefit evaluations of ZIKV policy interventions should focus primarily on the transient dynamics with discounting of future cases as is common in the economic literature [23] . Such discounting has previously been applied to understand the benefits of polio eradication [24–28] . In this paper , we use an age-structured model to study the potential short-term and long-term consequences of changes to a constant background ZIKV attack rate on incidence of ZVD and of high-risk cases in reproductive-age women during the transient dynamics following introduction . Our results show that the paradox of control is much weaker under transient dynamics , and almost always vanishes under even conservative discounting rates . We conclude that early interventions that reduce attack rates will always improve public health , and the paradox of control need only be considered when interventions have been delayed to a time when incidence has approached equilibrium levels .
To evaluate the impact of an emerging pathogen with age-structured virulence , we construct a two-part model characterizing the underlying demographic structure , which can be well described with available census data , and overlay a disease incidence model , which describes a process with greater uncertainty . For our case we consider the initial conditions as the population structure of Brazil in 2015 ( Fig 1 ) since Brazil was the most heavily impacted country in the recent outbreak and presents an interesting case study given a current age distribution that is disproportionately skewed towards the most vulnerable age classes . We additionally consider an idealized “developing” population ( Fig 2 ) to consider the dependence of our results on the initial population distribution . The population is projected forward using recently estimated age specific fertility rates [29] ( Fig 3 ) . We assume individuals are born susceptible and removed from the susceptible population at an annual rate corresponding to the hazard of ZVD , and that individuals who are infected once retain lifetime immunity to future infection . We then consider the burden of ZVD in terms of the risk of ZVD-related birth defects . Actual rates of ZVD-related birth defects in different settings have been estimated as ranging from 11% [30] to 42% [31] and may vary by stage of pregnancy [32] . For purposes of our model , the total cost of ZIKV is defined as the number of births that occur in women who experience ZVD in the same year as their pregnancy . We project forward population dynamics and ZVD incidence over fifty years to generate a cumulative cost of ZIKV . In light of potential improvements in prenatal care for pregnancies coinciding with ZVD or control methods such as the release of genetically modified mosquitoes [19 , 33 , 34] or a vaccine [20–22] , we weight present cases more heavily than future cases using the geometric rate 1 ( 1 + r ) t for cases t years in the future and an annual discounting rate r . Such discounting is standard practice in many areas of social policy [23] , as well as in disease management [24–28] . With the ongoing development of additional management options [19–22 , 33 , 34] and screening and pre-natal/neo-natal treatment [35] , there is reason to believe that future costs projected based on current ZVD risks may not be fully realized . Given that the hazard of encountering ZIKV infection is uncertain and likely to vary both in time and across spatial scales , we generate projections across a wide range of potential hazard rates . We consider the cumulative costs of ZIKV as a function of hazard rates in order to identify the possibility of a paradox of control under the assumption that ZVD hazard , while unknown , may be increased or decreased as a function of the intensity of control efforts . Our model is a numerical approximation of an age-structured epidemic model with time-dependent infection risks , combined with Lotka’s renewal equation for projecting the age structure of a population [36] . Models with similar forms have been studied since the 1920s [37 , 38] , based on McKendrick’s partial differential equation [39] . Let S ( t , a ) be the density of susceptible individuals of age a at time t . We assume a perfect sex ratio of 50/50 . Individuals die at rate μ ( a ) , depending on their age , and become infected at rate λ , independent of age and time . Infected individuals are assumed to become permanently immune against infection as soon as they are infected . New susceptible individuals are born at rate l ( a ) per susceptible person of age a . We assume ZVD infection has no measurable impact on the population’s large-scale demographic structure , so l ( a ) can be picked to reflect the collective birth rate of susceptible and resistant individuals . Thus S ( t + 1 , a + 1 ) = ( 1 − λ − μ ( a ) ) S ( t , a ) , ( 1 ) S ( t , 0 ) = ∑ a = 0 ∞ l ( a ) S ( t , a ) , ( 2 ) M ( t ) ∝ λ ∑ a = 0 ∞ l ( a ) S ( t , a ) , ( 3 ) C ( T ) ∝ ∑ t = 0 T ∑ a = 0 ∞ λ l ( a ) S ( t , a ) ( 1 1 + r ) t , ( 4 ) with the initial age-distribution of susceptibles S ( 0 , a ) and the maternity function l ( a ) estimated from census data [29] . The annual number of at-risk births M ( t ) in year t is proportional to the infection hazard λ and the total number of susceptible births . The cumulative discounted future cost of the ZVD epidemic C ( T ) is proportional to the total number of at-risk births from the start of the epidemic up until year T , discounted at annual rate r . Given uncertainty about the degree of overlap between human birth seasonality in the Southern hemisphere [40] and the relative level of microcephaly risk in different trimesters of pregnancy [32] the appropriate proportionality constant is currently unknown . However , since we assume demographic patterns such as birth timing to be unaffected by ZVD , the value of this scalar proportionality constant will not affect the relative ordering of different projections under our model . The actual hazard of ZVD infection is unknown , and potential values for R0 range between 2 . 2 and 14 . 8 [41 , 42] . We therefore consider the incidence of ZVD in high-risk age classes under varying annual hazard rates of ZIKV infection , with annual susceptible attack rates between 0 and 0 . 2 , the highest end of which would correspond to an equilibrium mean age of infection between 3 and 4 years of age . We compare both the year-over-year and cumulative incidence of ZVD in at-risk age classes over a fifty year time window , and consider the impact of discounting future costs at the geometric rate 1 ( 1 + r ) t for cases t years in the future and a discounting rate r . We consider annual discount rates of 3% and 10% as these are commonly used in both social policy and disease management evaluation [23–28] . Changes in the annual hazard rate ( potentially modulated by control intensity ) result in changes to both the equilibrium incidence and average age of infection . We have also explored some cases of age and time-dependent infections hazards ( λ ( a , t ) ) , notably oscillating hazard rates across different years ( supplement ) and find no impact on our qualitative conclusions .
Considering the potential total number of at-risk births over the duration of 50 years with varying levels of ZVD incidence yields projections where intermediate levels of ZVD incidence lead to the highest total number of at-risk births while extremely high or extremely low ZVD incidence both result in a lower total burden . Since ZVD is an emerging infection , the age distribution of cases following introduction will simply match the population’s age distribution . As ZVD becomes established in a population , the age distribution will begin to shift towards younger individuals [9 , 43] . The effect of the shifting age distribution is seen as the cost of ZVD as measured in cases in pregnant women tends to decline for any given hazard rate until an equilibrium is reached ( Fig 4 ) . The cumulative burden of ZVD and microcephaly is determined both by the transient spread of ZVD through the initially naive population and the long-term endemic level of incidence once ZVD is established within the population . While high hazard rates lead to a larger initial outbreak , they also result in most of the population acquiring immunity before reaching reproductive age , limiting the potential for microcephaly in the future . Placing possible hazard rates on the x axis , we consider the total cost over a fifty year window ( Fig 5 ) . Under the parameters we used , the greatest total burden of ZVD occurs when the annual hazard of contracting ZVD is 0 . 09 , implying that efforts to reduce transmission in regions where hazard is higher than that could be counterproductive unless they succeed in reducing hazard below that threshold . For example , reducing the annual hazard from 0 . 15 to 0 . 12 would result in an estimated 36 , 500 additional cases of ZVD among pregnant women during the fifty year window of our projection . However , most of the additional cases will occur later in time , by which point there may be medical advances in prenatal care or ZVD control that mitigate the potential for harm . To account for potential discounting of distant future cases relative to near future cases , we weight ZVD cases in our simulation according to the geometric rate 1 ( 1 + r ) t for cases t years in the future and a discounting rate r . When penalizing current cases more heavily than future cases , we find a reversal of our initial result , returning to the intuitive conclusion that more zika is always worse than less . In the case of our projection based on Brazilian demographics , any discounting rate greater than 1 . 1% is sufficient to eliminate the paradox of control . We consider also a stylized “developing world” age distribution , with a heavily child-biased age distribution ( Fig 2 ) . In this case , the relative costs of near-term and future cases are shifted by the smaller proportion of the population currently at risk ( Fig 6 ) , and a steeper discounting rate of 5 . 55% is necessary to eliminate the paradox of control ( Fig 7 ) . However , this discount rate is still within typical ranges used in setting social policy [23] . To illustrate the divergence from previous literature’s finding of a paradox of control in rubella-endemic settings [11 , 17 , 18 , 51] , we consider the same projections but with a population whose initial susceptible age structure corresponds to having had a constant infection risk over their lifetimes ( Fig 8 ) . This approximates an endemic-disease scenario . In this endemic context , a paradox of control materializes for all discounting rates ( Fig 9 ) because there is no initial large outbreak in the higher-hazard scenarios to offset lower long-term caseload in reproductive individuals . In case of cycles in hazard rates , our qualitative conclusions are broadly unchanged . However , sufficiently long cycles may increase the minimum discounting rate necessary to eliminate the paradox of control by permitting cohorts born during the lower-hazard phase of the cycle to reach reproductive age before encountering ZVD infection . As an illustrative example , we consider below hazard rates that cycle on a five year period ( Fig 10 ) .
Higher transmission intensities effectively frontload the total burden of ZVD incidence . Some have argued [44] that the higher long-term incidence of ZVD in low transmission settings should be considered a point against aggressive control efforts to reduce ZIKV transmission . However , policymakers may not be neutral in regards to the timing of potential cases . If two scenarios project similar numbers of cases , it may be preferable to follow the one that delays the burden until later years in light of the expectation that new treatments or preventive measures may be developed in the meantime . Likewise , even a scenario that predicts more total cases over a long time window may be preferred if it involves a lower level of incidence over the time frame of greatest interest to decision makers . Consistent with Bewick et al [44] , efforts to limit the size of an initial outbreak of an introduced pathogen such as ZIKV must be traded off against the implications for population-level immunity and long term incidence . We emphasize that possible future cases are less immediately pressing than current cases , and factoring in this prioritization of the present reinforces the importance of limiting disease exposure for at-risk individuals . This aligns with simulation studies suggesting that , regardless of management action , the largest number of cases ( and thus the greatest cost ) will be concentrated in the initial outbreak before endemic establishment [44 , 45] . We wish to emphasize that our results do not contradict the well-established concept of endemic stability used to justify the avoidance of rubella immunization in some countries . Our conclusions that discounted cumulative future costs from ZIKV are effectively monotonically increasing in infection risk only applies at the start of an epidemic when the population is entirely naive . As the population ages and the infection incidence approaches endemic equilibrium levels , the paradox of control re-emerges , as shown in Figs 8 and 9 . Our model does not account for all possible details of long-term ZVD dynamics—the true picture is likely more complicated due to the uncertainty about the extent of sexual transmission [46 , 47] and similarity to dengue virus transmission [48] . To the extent that ZVD outcomes depend on the stage of pregnancy and how mosquito population density aligns ( or not ) with human birth seasonality [6 , 40] , our projections may overstate the total ZVD burden by estimating the number of at-risk births rather than actual cases of microcephaly . However , this should be a uniform overestimate of the true cost , without biasing comparisons of different transmission intensities . We do not account for costs of ZVD aside from microcephaly risk , such as potential strain interactions with dengue fever [49] or link to Guillain-Barre Syndrome [50] , both of which would increase the accounting of near-term costs and decrease the future preference for ZVD infection in early childhood . | The intuitive response to an emerging outbreak is to halt , or at least reduce , transmission . However , in some circumstances , reducing overall transmission and incidence may be counterproductive from a public health perspective as public health interventions affect both the total level and the distribution of disease burden . We consider the scenarios under which reducing transmission of an emerging pathogen such as Zika virus may increase the costs associated with disease in the most vulnerable segments of the population—in this case , reproductive-age women . We conclude that after applying standard discounting rates to future cases , the “paradox of control” as evaluated from the time of introduction vanishes and reducing hazard of infection uniformly reduces the total costs associated with severe disease . | [
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"bi... | 2018 | Unintended consequences and the paradox of control: Management of emerging pathogens with age-specific virulence |
Trf4p and Trf5p are non-canonical poly ( A ) polymerases and are part of the heteromeric protein complexes TRAMP4 and TRAMP5 that promote the degradation of aberrant and short-lived RNA substrates by interacting with the nuclear exosome . To assess the level of functional redundancy between the paralogous Trf4 and Trf5 proteins and to investigate the role of the Trf4-dependent polyadenylation in vivo , we used DNA microarrays to compare gene expression of the wild-type yeast strain of S . cerevisiae with either that of trf4Δ or trf5Δ mutant strains or the trf4Δ mutant expressing the polyadenylation-defective Trf4 ( DADA ) protein . We found little overlap between the sets of transcripts with altered expression in the trf4Δ or the trf5Δ mutants , suggesting that Trf4p and Trf5p target distinct groups of RNAs for degradation . Surprisingly , most RNAs the expression of which was altered by the trf4 deletion were restored to wild-type levels by overexpression of TRF4 ( DADA ) , showing that the polyadenylation activity of Trf4p is dispensable in vivo . Apart from previously reported Trf4p and Trf5p target RNAs , this analysis along with in vivo cross-linking and RNA immunopurification-chip experiments revealed that both the TRAMP4 and the TRAMP5 complexes stimulate the degradation of spliced-out introns via a mechanism that is independent of the polyadenylation activity of Trf4p . In addition , we show that disruption of trf4 causes severe shortening of telomeres suggesting that TRF4 functions in the maintenance of telomere length . Finally , our study demonstrates that TRF4 , the exosome , and TRF5 participate in antisense RNA–mediated regulation of genes involved in phosphate metabolism . In conclusion , our results suggest that paralogous TRAMP complexes have distinct RNA selectivities with functional implications in RNA surveillance as well as other RNA–related processes . This indicates widespread and integrative functions of TRAMP complexes for the coordination of different gene expression regulatory processes .
Gene expression in eukaryotes depends on highly complex mechanisms for production of mature RNA molecules . Precursors of mRNAs , ribosomal RNAs ( rRNAs ) , transfer RNAs ( tRNAs ) , small nucleolar RNAs ( snoRNAs ) , and small nuclear RNA ( snRNAs ) undergo stepwise processing and maturation , which includes 5′-capping , splicing , 3′-polyadenylation , endo- and exonucleolytic trimming , and base modifications . All these processes are error-prone and thus , RNA maturation has to be monitored by nuclear and cytoplasmic RNA quality control pathways to remove potentially harmful aberrant RNAs [1] , [2] . In the budding yeast Saccharomyces cerevisiae , nuclear RNA surveillance is mediated by the combined action of the Trf4/5-Air1/2-Mtr4 ( TRAMP ) complex and the exosome that promote rapid degradation of nonfunctional RNAs [3]–[10] . The TRAMP complex consists of either one of the two paralogous non-canonical poly ( A ) polymerases Trf4p and Trf5p forming TRAMP4 and TRAMP5 complexes , respectively , the RNA binding proteins Air1 or Air2 , and the RNA helicase Mtr4p [5]–[7] . In contrast to the canonical poly ( A ) polymerase Pap1p , which adds long poly ( A ) tails to the 3′-end of mRNAs that facilitates nuclear RNA export and increases the stability and translation of messages [11] , [12] , the Trf proteins add short poly ( A ) tails to their substrate RNAs , which is assumed to trigger efficient decay of the RNAs by recruitment of the nuclear exosome complex [5]–[7] . Initially , Trf4 protein was identified as a key player in the surveillance and degradation of hypomodified initiator tRNA ( tRNAiMet ) [4] . Further studies revealed more widespread roles of TRAMP complexes to assist the exosome-mediated degradation and trimming of several types of non-coding RNAs ( ncRNAs ) including precursors of rRNAs , tRNAs , snoRNAs , snRNAs , and of aberrant pre-mRNAs that are defective in 3′ end cleavage , splicing , or export to the cytoplasm [1] , [6]–[9] , [13]–[17] . Many of these RNA substrates are part of ribonucleoprotein ( RNP ) complexes and pre-ribosomes suggesting that most if not all newly synthesized nuclear RNPs are subject to quality control by TRAMP and the exosome . Another major class of potential RNA targets for TRAMP complexes are the so-called ‘cryptic unstable transcripts’ ( CUTs ) [7] . CUTs are small , capped and fairly unstable transcripts that are expressed at such low levels that they can only be readily detected in nuclear RNA degradation mutants such as rrp6Δ . Originally detected in some intergenic regions ( IGRs ) [7] , the recent systematic exploration of CUTs by RNA sequencing and tiling arrays suggests the existence of hundreds of CUTs that preferentially originate from nucleosome-free 5′ promotor regions , or from the 3′-ends of protein-coding genes [18] , [19] . However , whether these CUTs have a biological role , or merely reflect transcriptional noise made from nucleosome-depleted regions is not known [18] , [19] . Most studies investigating the functions of TRAMP complexes focused on TRAMP4 and much less is known about TRAMP5 [20] , [21] . Trf4p and Trf5p share 56% amino-acid sequence similarity and loss of both poly ( A ) polymerases is lethal [22] . The conditional depletion of Trf5p in trf4Δ mutant cells increases the steady-state levels of specific RNAs , such as the 3′-extended forms of U14 snoRNA , the 23S pre-rRNA and the CUT NEL025c that accumulate in either single mutant indicating that Trf4p and Trf5p have at least partially overlapping substrate specificities in vivo [7] , [15] , [20] , [23] . Besides RNA quality control and processing , Trf proteins may also participate in DNA-related processes . Originally , TRF4 was identified in a screen for mutations that are synthetically lethal with top1 , which encodes the DNA topoisomerase I [24] . A top1 trf4-ts double mutant was defective in several mitotic events , such as sister chromatid cohesion , chromosome condensation at the rDNA loci , and chromosome segregation [22] , [24]–[26] . These defects were suppressed by overexpression of TRF5 suggesting that both Trf4p and Trf5p have roles in DNA metabolism and heterochromatin formation [22] . Moreover , Trf4p as well as the orthologous protein Cid14 in S . pombe stimulate the RNA-mediated silencing of heterochromatic transcripts and control rDNA copy numbers [24] , [27]–[32] . Hence , it was postulated that RNA-mediated recruitment of Trf4p and Trf5p may promote chromatin remodeling through regulation of histone modifying enzymes at specific chromatin loci [23] . Although the above mentioned studies revealed some substrates and functions for complexes containing Trf4 ( TRAMP4 ) and Trf5 ( TRAMP5 ) , a comprehensive view of the substrate specificities and potential functional implications of the different TRAMP complexes is still lacking . We therefore wished to obtain a global picture of the RNA substrates that are regulated by the TRAMP4 and TRAMP5 complexes . To this end , we have used DNA microarrays to systematically map the RNA targets of Trf4p and Trf5 . Surprisingly , we found that the different TRAMP complexes per se regulate only marginally overlapping sets of RNAs in the cell . Furthermore , the polyadenylation-defective form of Trf4p ( Trf4p-DADA ) suppressed most of the altered expression pattern as seen in the trf4Δ mutant cells suggesting that the TRAMP polyadenylation activity is not essential for RNA regulation . We further demonstrate that Trf4p and to a lower extent Trf5p promotes the degradation of a group of introns through an exosome-dependent but polyadenylation-independent mechanism . Moreover , Trf4p but not Trf5p stimulates RNA degradation mechanisms that are functionally linked to telomere maintenance and to antisense RNA-mediated regulatory pathways of gene expression . These results suggest widespread and distinct roles of different TRAMP complexes in the regulation of gene expression .
TRAMP complexes promote the exosome-assisted degradation of diverse ncRNAs and aberrant or nonfunctional RNAs [4]–[7] , [14]–[16] . To identify additional specific RNA targets for the TRAMP4 and TRAMP5 complexes , we measured the relative changes of gene expression of S . cerevisiae cells lacking either trf4 ( trf4Δ ) or trf5 ( trf5Δ ) compared to wild-type ( WT ) cells using yeast oligo microarrays that contained features representing all annotated yeast ORFs , ncRNAs , introns , rRNA precursors , as well as some intergenic regions ( IGRs ) and tiled regions downstream of a few genes ( see Materials and Methods ) . To this purpose , total RNA isolated from exponentially growing cells was reverse transcribed with a mixture of random nonamers and oligo ( dT ) primers . Cy5 fluorescently labeled cDNAs derived from total RNA isolated from either the trf4Δ or the trf5Δ mutants were then competitively hybridized with Cy3 labeled cDNAs from WT cells . To define a list of arrayed features determining transcripts that significantly changed expression in the trf4Δ , the trf5Δ and the trf4Δ/TRF4-DADA mutants ( which are explained below ) , we arbitrarily selected those features that changed relative expression at least 2-fold ( average of three biological replicates ) with false discovery rates ( FDRs ) of less than 5% [33] ( Figure 1A; a list of the selected features is provided in Table S1 ) . Similar results were obtained by statistical analysis with Cyber-T [34] followed by selection of those features with a p-value of less than 0 . 05 [34] ( for a comparison of FDRs and p-values see Table S2 ) . To further visualize the relation among the 715 features selected by this analysis , we hierarchically clustered the features and experiments ( Figure 1A ) . To identify common themes among the differentially expressed mRNAs in the trf4Δ and trf5Δ mutants , we searched for common Gene Ontology ( GO ) annotations among the 550 transcripts for which GO annotations were available at the Saccharomyces Genome Database ( SGD; Table S3 ) . Not surprisingly , most of the 715 selected features showed increased steady-state levels in trf mutants ( 691 features , 97% ) , which is in agreement with the idea that Trf4p and Trf5p promote RNA degradation and their depletion hence leads to the accumulation of RNAs that are normally targeted by these proteins ( Figure 1A ) . More interestingly , although deletions of trf4 and trf5 are synthetically lethal , which may suggest common functions and targets , we found that the vast majority of the affected transcripts overlapped only marginally though significantly ( Figure 1B ) . Only 33 transcripts changed expression in both the trf4Δ and the trf5Δ mutants; among these , 27 transcripts were selectively increased ( Figure 1B ) and represented rRNA processing intermediates , mRNAs encoding chaperones ( SSB1 , HSP150 , and TIR2 ) or enzymes involved in glucose metabolism ( TDH2 , TDH3 , ADH2 , and PDC1 ) . These results suggest that trf4 and trf5 specifically affect very different groups of transcripts in vivo . However , we wish to point out that the comparison of gene expression profiles of single trf4 and trf5 deletion mutants may not reveal the full spectra of the in vivo targets; particularly in cases where either functional Trf4 or Trf5 proteins can fully substitute the absence of the other paralog . Consistent with previous reports [6] , [7] , [14]–[16] , 72 of the 422 features ( 17% ) that accumulated at least 2-fold in the trf4Δ mutant were ncRNAs , such as snoRNAs ( 27 features ) and RNAs derived from intergenic regions ( IGRs; 20 features ) , or autonomously replicating sequences ( ARSs; 4 features; Figure S1A , Figure S2 , and Table S1 ) . Interestingly , 13 of the 20 IGRs overlap with CUTs that have been recently mapped by massive sequencing of RNAs bound to the nuclear cap-binding protein Cbp20p isolated from conditional trf4Δ rrp6Δ double mutants [18] , or that were accumulated in rrp6Δ mutants and identified with tiling arrays [19] . ( A comparison of selected IGRs and CUTs is provided in a separate worksheet of Table S1 . ) Ty1 retrotransposons represented the second most abundant class of transcripts with altered expression in the trf4Δ strain ( Figure S1 ) , as 68 out of the 98 probes specific for TyA and TyB exhibited an average 4-fold increase in relative expression levels compared to the WT strain ( Figure S3A ) . This result was further confirmed by quantitative real-time PCR ( qRT-PCR ) analysis with primers specific for a sequence overlapping the TyA and TyB boundary ( Figure S3B ) . In contrast to trf4Δ cells , the expression of the Ty1 elements was slightly decreased in the trf5Δ mutant ( ∼−1 . 5-fold ) and unchanged in cells lacking the exosome subunit Rrp6p ( rrp6Δ ) ( Figure S3B ) . Ty1 transcription and transposition is regulated by the trans acting antisense regulatory RTL-RNA that is transcribed divergently to TyA from an internal promoter and is degraded by the 5′ to 3′ exoribonuclease Xrn1p [27] . In agreement with a previous report [27] , we found that the steady state levels of RTL-RNA were unaffected in rrp6 mutants . Conversely , RTL-RNA levels were slightly increased ( >1 . 5-fold ) in the trf4Δ mutant and decreased ( ∼1 . 5-fold ) in the trf5Δ mutant ( Figure S3B ) . Since both the Ty1 elements and the negative regulator RTL-RNA were simultaneously increased in the trf4Δ mutant and decreased in the trf5Δ mutant , but remained unchanged in the exosome mutant rrp6Δ , we speculate that the TRAMP/exosome pathway is not involved in either the degradation of the TyA and TyB mRNAs or of the antisense regulatory RTL-RNA . However , the opposite effect of trf4 or trf5 deletions on the levels of the TY1- and RTL-RNAs suggests that TRAMP4 and TRAMP5 likely act through a yet uncharacterized mechanism to regulate the expression of the TY1 locus . Deletion of TRF5 caused the accumulation of only 11 ncRNAs ( 4% ) out of the 269 features ( representing 220 GO annotated genes ) for which we measured significantly altered expression levels ( Figure S1B ) . This includes one snoRNA ( SNR68 ) , and four IGRs likely representing two CUTs ( CUT857 , CUT195 ) and the stable untranslated transcript SUT180 [19] ( Table S1 ) . However , the majority ( 94% ) of the trf5-affected transcripts can be assigned to protein-coding mRNAs . A GO analysis among these messages revealed overrepresentation of mRNAs coding for cytoplasmic proteins involved in translation ( e . g . 19 ribosomal protein genes , p<0 . 01 ) or act in diverse metabolic processes such as glycolysis ( 7 genes , p<0 . 01 ) , sulphate assimilation ( 5 genes , p<0 . 003 ) , and nitrogen metabolism ( 21 genes , p<0 . 003; GO analysis of annotated transcripts is shown in Table S3 ) . Except for 7 messages coding for proteins acting in glycolysis ( p<0 . 01 ) , these themes could not be seen among the mRNAs that were affected in the trf4Δ mutant which preferentially encode nuclear proteins ( 116 genes , p<10−17 ) . In conclusion , it appears that deletion of trf4 or trf5 affected the steady-state level of a large variety of mRNAs that function in diverse cellular pathways and may reflect in part the pleiotropic defects of trf4Δ and trf5Δ mutants [22] , [24]–[26] . Our results also indicate that degradation of ncRNAs is mainly promoted by Trf4p . We next aimed at identifying the set of transcripts that require the polyadenylation activity of Trf4 for efficient degradation . For this purpose we constructed a trf4Δ/TRF4-DADA mutant strain , where the polyadenylation defective allele TRF4-DADA [5] is episomally expressed in trf4Δ cells under the control of the NOP1 promoter ( see Materials and Methods ) . Trf4p-DADA contains two aspartate to alanine mutations in the poly ( A ) polymerase catalytic site which renders the enzyme inactive [5] . Similar to the microarray experiments with the trf4Δ and the trf5Δ mutants , we compared transcript levels of the trf4Δ/TRF4-DADA mutant to that of the WT strain harboring the empty vector ( BY4741/pNOPPATA1L ) . Surprisingly , the expression levels of more than 90% of transcripts that were significantly altered in trf4Δ mutant cells were almost fully restored to WT levels by the overexpression of the TRF4-DADA allele ( Figure 1 , Figure S1C ) . Only 57 transcripts were more than 2-fold enriched ( FDR<5% ) in cells expressing the TRF4-DADA allele as compared to WT ( Figure 1B ) , 18 of them ( 32% ) are ncRNAs ( Figure S1C ) . Although the relative abundance of most SGD annotated rRNA intermediates , snoRNAs , and IGRs was reduced in trf4Δ/TRF4-DADA compared to the trf4Δ mutant cells ( Table S1 ) , 31 ncRNAs ( 7 rRNA intermediates , 15 SNRs , and 9 IGRs ) still exhibited increased steady-state levels ( on average between 1 . 5-fold and 4-fold; FDR<5% ) relative to the WT cells ( Figure S2 , Table S1 ) . Similar results were found for the RNA component NME1 of RNase MRP and for a group of short dubious ORFs ( YJL047C-A , YBR072C-A , YGR121W-A , and YBR182C-A ) that were also enriched in rrp6Δ mutants [19] and , hence , most likely do not encode proteins but rather correspond to CUTs . Some of these ncRNAs are highly abundant such as rRNAs and snoRNAs . It therefore appears that highly expressed and structured RNAs strongly depend on the polyadenylation activity of Trf4p although they represent only a minor fraction ( 10% ) of Trf4 targets . However , this fraction may recruit a considerable amount of Trf4 complexes in vivo and thus , a substantial fraction of the total RNA turnover mediated by Trf4p may depend upon Trf4 catalytic activity . In addition to ncRNAs such as rRNA intermediates , snoRNAs , and IGR RNAs/CUTs , our microarray data showed that a group of introns , some of which containing snoRNAs , were specifically accumulated ( 2- to 8-fold; FDR<5% ) in either the trf4Δ mutant ( Trf4-dependent introns ) or the trf5Δ mutant ( Trf5-dependent introns; Figure 2A , Table S1 ) . To rule out that accumulation of these introns simply reflects increased transcript levels of the pre-mRNAs , we compared the relative changes of intron abundance with that of the corresponding pre-mRNAs and mature mRNAs as revealed with arrayed probes that specifically detect intron-exon junctions and exons ( Figure 2B and 2C ) . We found that unlike introns , the corresponding pre-mRNAs and mature mRNAs were not significantly changed in the trf4Δ mutant compared to WT cells . Likewise , the cognate pre-mRNAs and mature mRNAs of the Trf4-dependent introns were also unchanged in the trf5Δ and trf4Δ/TRF4-DADA mutants ( Figure 2B , Table S1 ) . Thus , this analysis indicates that only spliced-out introns , such as those of the RPS9A , RPL7B , and GCR1 genes , specifically accumulate in the trf4Δ mutant . To validate this finding , we carried out qRT-PCR experiments with primers either specific for the introns , the pre-mRNAs , or the mRNAs of RPS9A , RPL7B , and GCR1 . Consistent with our microarray data , the levels of introns but not those of pre-mRNAs or mature mRNAs were increased in the trf4Δ mutant compared to WT cells ( Figure S4 and results not shown ) . As Trf4p promotes the exosome-mediated degradation of targeted RNAs through its polyadenylation activity [1] , [5]–[7] , we also analyzed the steady-state levels of introns in the rrp6Δ exosome mutant and in trf4Δ/TRF4-DADA mutant cells . Similarly to what has been observed in the trf4Δ mutant , introns accumulated in cells lacking rrp6 but no significant change in the expression of the pre-mRNAs and mature mRNAs of RPS9A , RPL7B , and GCR1 was detected ( Figure S4 and data not shown ) . Conversely , overexpression of the TRF4-DADA allele in trf4Δ cells restored WT levels for nine of the 13 Trf4-dependent introns , or reduced their abundance to values slightly above ( 1 . 5 fold ) the WT levels ( Figure 2A , Figure S4 , Table S1 , and results not shown ) . This indicates that the polyadenylation-defective Trf4-DADA protein also participates in the regulation of “normal” steady-state levels of introns in vivo . Unlike to what we observed in the trf4Δ mutant , however , the increased levels of the Trf5-dependent introns ( Figure 2A; RPL16A-INT and RPL40A-INT in Figure S4 ) coincided with similar amounts of the related pre-mRNAs and mature mRNA transcripts ( Figure 2C , Table S1 , and data not shown ) , strongly suggesting that accumulation of introns in the trf5Δ mutant reflects increased relative abundance of unspliced pre-mRNAs . To test whether Trf5p could efficiently target spliced-out introns in the absence of Trf4p , we analyzed intron accumulation by qRT-PCR experiments upon conditional TRF4 or TRF5 depletion . In this experiment , total RNA was isolated from a trf4Δ trf5Δ double mutant strain complemented with a plasmid either expressing TRF4 or TRF5 under the control of the GAL1 promoter ( for details see Materials and Methods ) . As shown in Figure 2D , an one hour shift of cells to media supplemented with glucose to repress expression of TRF4 or TRF5 , led to an enrichment of all the introns tested . Conversely , no change in the abundance of introns was observed in control experiments performed with total RNA purified from WT cells that were transformed with the empty vector ( BY4741/pYC6-CT; results not shown ) . Taken together , these results suggest that Trf4p likely promotes the exosome-mediated degradation of a group of spliced-out introns through a mechanism that is not dependent on polyadenylation . In addition , as depletion of TRF5 in trf4Δ cells caused intron accumulation in vivo , we infer that Trf4p and Trf5p are functionally redundant for intron decay ( Figure 2D ) . To identify RNAs associated with TRAMP4 , we performed in vivo cross-linking and ribonucleoprotein-immunopurification experiments followed by microarray analysis of bound RNAs ( X-RIP-Chip ) . Cells expressing recombinant tandem-affinity purification ( TAP ) -tagged Trf4 protein were cross-linked with formaldehyde , and Trf4-containing ribonucleoprotein complexes were recovered by affinity selection on IgG-coupled beads ( see Materials and Methods ) . Cells expressing TAP-tagged Trf4 proteins fully restore Trf4 functions and were previously used to purify functional TRAMP complexes [5] . As a control for non-specifically enriched RNAs , the same experiment was done with untagged WT cells and with cells expressing Fpr1-TAP , a peptidyl-prolyl-cis-trans-isomerase not expected to bind RNA . About 70% of Trf4-TAP and 60% of Fpr1-TAP was captured from the whole cell extract ( WCE ) as shown by dot-blot analysis ( Figure 3A , left panel ) . Moreover , Air2p , a well-known component of the TRAMP4 complex [5] , [6] , co-purified with crosslinked Trf4-TAP but was absent in control purifications performed with untagged WT cells ( Figure 3A , right panel ) . We isolated total RNA from extracts ( input ) and from the immunopurified samples and labeled cDNAs derived from the RNAs with Cy3 and Cy5 fluorescent dyes , respectively . The differentially labeled samples were mixed and competitively hybridized on yeast oligo arrays . In this assay , the ratio of the two RNA populations at a given array element provides a measurement for enrichment of the respective RNA with the TRAMP4 complex [35] , [36] . Because of the relatively high variation of array data between biological replicates , we rank ordered the data and determined percentile ranks for each analyzed feature ( 0 , no enrichment; 1 high enrichment; Dataset S2 ) . In agreement with known functions of TRAMP4 on ncRNAs , we found that many small and stable ncRNAs such as snoRNAs and tRNAs were highly enriched in purified cross-linked TRAMP4 complexes . However , these transcripts were also strongly enriched in the control isolates and thus , only limited conclusions can be drawn from this analysis . Nevertheless , despite the high background from small ncRNAs in these experiments , we found that spliced-out introns were selectively enriched in the Trf4-TAP RNA isolates when compared to control isolates ( Kolmogorov-Smirnov test: p = 2 . 5×10−5; Figure 3B , data for all intron probes are shown in Table S4 ) . The corresponding probes for the mature mRNAs were not enriched ( p = 0 . 12; Figure 3C ) , suggesting specific association of the TRAMP4 complex with spliced introns but not with the respective pre-mRNAs . This finding is consistent with our previous observation for accumulation of certain introns but not of the corresponding mRNAs in the trf4Δ mutant ( Figure 2 and Figure S4 ) : For 11 ( 78% ) of the 14 introns that were significantly changed in either trf4Δ and trf5Δ mutants ( Figure 2A ) and for which X-RIP-Chip data were available , we found higher ranking with TRAMP4 complexes compared to controls ( Table S4 ) , whereas no such preference was seen for the respective ORF probes ( two of the six corresponding ORFs were higher ranked with TRAMP4 complexes ) . We further analyzed whether expression levels of the TRAMP4 associated introns were commonly changed in single trf4Δ or trf5Δ mutants . The relative expression levels for 48 introns that were preferentially enriched with TRAMP4 complexes ( percentile ranks greater than 0 . 85 ) compared to the controls , were mostly unchanged in either trf4Δ or trf5Δ mutants ( average log2 ratios = 0 . 035 and −0 . 1 in trf4Δ and trf5Δ , respectively; Table S4 ) . Possibly , Trf4p and Trf5p act redundantly in the decay of most spliced-out introns and therefore no changes of relative expression levels can be seen in single mutants . To further corroborate this idea , we measured the expression of introns for the two genes RPS24A and RPL2B that were enriched in TRAMP4 affinity isolates ( average percentile ranks of 0 . 83 and 0 . 9 , respectively ) but for which expression levels were not significantly changed in neither trf4 nor trf5 mutants , by Northern blot analysis with intron specific probes . As expected , these introns were detectable in total RNA derived from the rrp6Δ exosome mutant and from the mutant of the debranching enzyme dbr1Δ , which was used as a positive control for intron detection [37]–[39] ( Figure 3D ) . However , both introns could not be readily detected in total RNA derived from either the trf4Δ or the trf5Δ single mutant strains , but they were strongly accumulated in RNA samples isolated from conditional trf4 ( ts ) trf5Δ double mutants . This result is reminiscent of our finding for the RPS9A , RPL7B , and RPL40A introns that became increasingly enriched in conditional double mutants ( Figure 2D ) . In conclusion , these data strongly suggest functional redundancy between Trf4p and Trf5p in the degradation of introns in vivo . Yeast telomeres ( TEL ) consist of a complex mosaic of telomeric and subtelomeric sequences , where the X element sequence is the only region common to all chromosome ends . Some subtelomeric regions contain a conserved helicase-encoding repetitive sequence ( Y′ sequence ) located within terminal telomeric repeats ( TR; Figure 4A ) [40] . It has recently been reported that cryptic transcripts originating from transcriptionally repressed loci , such as TEL05L , accumulate in strains lacking components of the TRAMP4 or the exosome complex [30] . Consistent with this , we found that transcripts spanning across HMLα1 and ARS318-HMR of the silenced mating cassettes and across putative subtelomeric ORFs ( YBL109W , YDR543C , YHR217C , and YKL225W ) were highly abundant in the trf4Δ and the rrp6Δ mutants ( Table S1 , Figure 4B , and Figure S5A ) . In particular , the subtelomeric transcripts originate from telomeres that either contain ( TEL02L , TEL04R , and TEL08R ) or lack ( TEL11L ) the Y′ sequence element ( Figure 4B ) . Similar to what has been reported previously [30] , they are commonly oriented in the 5′ to 3′ direction towards the centromere ( results not shown ) . Neither subtelomeric RNAs transcribed from the opposite strand towards the telomeres nor telomeric TERRA RNAs [41] were detected ( results not shown ) . Although overexpression of TRF4-DADA reduced the abundance of these subtelomeric RNAs in trf4Δ mutant cells , their steady-state levels were still about 1 . 5–2 . 2 fold higher than in WT cells ( Figure 4B ) . This decrease in the abundance of subtelomeric RNAs seen in the trf4Δ/TRF4-DADA mutant indicates that the polyadenylation activity of Trf4p may enhance the degradation of these RNA molecules in vivo ( Figure 4B ) . Increased expression for two of these RNAs ( YDR543C and YKL225W ) was also found in strains deficient of trf5 as shown by qRT-PCR experiments ( Figure 4B ) . Interestingly and in contrast to trf4Δ mutants , the trf5Δ mutant exhibited also changes in the relative expression of factors that positively ( SIR2 , SIR3 , and MCM10 ) or negatively ( SAS5 ) regulate chromatin silencing ( Figure S5B ) . Thus , it could be that accumulation of subtelomeric RNAs in the trf5Δ mutant reflects defects in pathways other than RNA turnover . To test whether any correlation existed between subtelomeric RNA accumulation and the structural integrity of telomeres , we performed Southern blot experiments with XhoI digested genomic DNA to determine the length of Y′ containing telomeres ( Figure 5A and 5B ) . Y′ telomeres were on average shortened by ∼120 bp in the trf4Δ mutant and ∼40 bp in the rrp6Δ exosome mutant ( Figure 5A ) . Conversely , the length of Y′ telomeres was similar to that of the WT strain in the trf5Δ mutant or in trf4Δ mutant cells complemented with a plasmid ( pNOPPATA1L ) carrying the WT allele of TRF4 ( Figure 5A ) . Intriguingly , shortening of telomeres in the trf4Δ mutant was also strongly suppressed by overexpression of TRF4-DADA , where telomeres were about 40 bp shorter than in the WT strain ( Figure 5B ) . These results showed that telomere shortening in trf4Δ cells is a reversible event achieved by reintroduction of episomally expressed Trf4 proteins . In addition , our results strongly suggest that Trf4p exerts a role in telomere maintenance mainly through a mechanism that is independent of polyadenylation . The results from these Southern blotting experiments do not indicate any straight correlation between telomere shortening and accumulation of the subtelomeric RNA molecules . In fact , although subtelomeric RNAs were more abundant in the rrp6Δ mutant compared to the trf4Δ or the trf4Δ/TRF4-DADA mutant strain ( Figure 4B ) , only disruption of trf4 resulted in a severe shortening of the telomeres . Moreover , some subtelomeric RNAs ( YDR543C and YKL225W; Figure 4B ) also highly accumulated in the trf5Δ mutant , which did not show any recognizable change in telomere length ( Figure 5A ) . To investigate whether misregulation of the telomerase components could be the cause of the telomere shortening , we carried out qRT-PCR experiments with primers specific for the TLC1 , EST1 , EST2 , and EST3 subunits ( Figure 5C ) [42] , [43] . In the rrp6Δ mutant , the steady-state levels for the mRNAs encoding these telomerase subunits were more than 2-fold increased compared to the WT strain , suggesting a consequent increase in the activity of the holoenzyme in this mutant . In contrast , only the TLC1 RNA was 2 . 6-fold increased in the trf4Δ mutant , whereas no change was detected for EST1 , EST2 , and EST3 mRNAs levels ( Figure 5C ) . It was reported that overexpression of TLC1 causes telomere shortening in yeast because of the specific sequestration of the telomeric factors yKu70 and yKu80 , which promote telomerase recruitment [42] . Thus , the imbalance in the expression level between TLC1 and the other subunits of the telomerase may in part account for for the telomere shortening observed in the trf4Δ mutant . This hypothesis is further supported by the observation that overexpression of the TRF4-DADA allele not only suppressed the telomeric defect of the trf4Δ mutant , but also coincided with the restoration of expression of the TLC1 RNA subunit to WT levels ( Figure 5C ) . Furthermore , these results indicate that Trf4p promotes TLC1 turnover through a polyadenylation-independent mechanism . Consistent with the proposed connection between TLC1 overexpression and telomere shortening , we found no change of TLC1 RNA abundance in the trf5Δ mutant ( Figure 5C ) . It is noteworthy , however , that the unaltered telomere length found in the trf5Δ mutant might also reflect increased expression levels ( >3-fold ) of factors such as EST3 , CST6 , and MET18 , which participate in the maintenance of telomeres in vivo ( Figure 5C ) [44] . Besides the many mRNAs for which relative expression levels were significantly increased in strains devoid of Trf4p or Trf5p , the expression of a few genes including those coding for proteins involved in phosphate metabolism ( PHO3 , PHO5 , PHO11 , PHO12 , and PHO89 ) were significantly decreased ( Table S1 ) . The relative abundance of these mRNAs was almost fully restored to WT levels by the overexpression of the TRF4-DADA allele as shown by microarray and qRT-PCR experiments ( Figure 6 , Figure S6 , and Table S1 ) . Such reduced expression of the PHO genes has also previously been observed in nuclear exosome mutants [16] . Particularly for PHO84 and PHO5 , it was shown that Rrp6p affects the stability of corresponding antisense RNAs involved in the transcriptional control of their cognate sense mRNAs [19] , [29] , [45] . To assess whether the decreased levels of PHO5 , PHO11 , and PHO89 mRNAs in trf4Δ , trf5Δ , and rrp6Δ exosome mutants correlates with increased levels of corresponding antisense RNAs , we carried out strand-specific qRT-PCR experiments with primers specific for antisense RNAs that span across the PHO promoter regions ( Figure 6B , Figure S6 ) . Antisense RNAs could be detected in all the strains tested , including the WT strain , however , their levels were more than 2-fold increased in trf4Δ and rrp6Δ but not in trf5Δ mutants . The abundance of the antisense RNAs was decreased to WT levels by overexpression of TRF4-DADA ( Figure 6B , data for PHO5 and PHO89 are shown in Figure S6 ) . Therefore , similar to PHO84 [29] , the expression of PHO5 , PHO11 , and PHO89 is likely modulated by antisense RNAs , the degradation of which is promoted by the exosome and the Trf4 protein , and does not require the polyadenylation activity of Trf4p . In addition , although loss of Trf5p did not cause any change in the expression of the PHO antisense transcripts , the reduced steady state level of the PHO5 , PHO11 , and PHO89 mRNAs suggests that Trf5p , through an yet unknown mechanism , may also participate with Trf4p and the exosome in fine tuning the expression of the PHO genes .
Trf4p and Trf5p are non-canonical poly ( A ) polymerases that activate RNA turnover and quality control pathways by targeting aberrant and short-lived RNA substrates to the nuclear exosome for degradation [1] , [4]–[7] , [15] , [20] . Trf4 and trf5 are synthetically lethal and depletion of Trf5p strengthens the defects in RNA maturation of trf4Δ mutants , suggesting that Trf4p and Trf5p have partially overlapping functions in vivo [6] , [7] , [20] . To globally investigate the extent of functional redundancy and to systematically identify Trf4p- and Trf5p-specific RNA targets , we used microarrays to compare RNA expression profiles of S . cerevisiae mutant strains lacking Trf4p or Trf5p with that of WT cells ( Figure 1 , Table S1 ) . We found that almost all ( >90% ) of the 715 features that were at least 2-fold changed , were selectively increased in either the trf4Δ or the trf5Δ mutants . This finding is in agreement with known functions of these proteins in RNA degradation and their depletion is therefore expected to lead to the accumulation of RNA targets [1] , [5]–[7] , [20] . However , in contrast to the proposed functional redundancy of Trf4p and Trf5p , we found that trf4 and trf5 deletion affected barely overlapping sets of transcripts ( Figure 1A ) . Such heterogeneity of the genes with altered expression was previously reported for different mutants of the exosome complex , possibly reflecting differential target specificities by the different subunits of the complex [16] . Interestingly , the trf4Δ and the trf5Δ mutants differed in the number of ncRNAs that accumulated in the cell . NcRNAs represented 17% and 4% of the transcripts that were selectively increased ( >2-fold , FDR<5% ) in trf4Δ and trf5Δ mutants , respectively . However , our microarrays cover only a fraction of the experimentally defined CUTs derived from intergenic regions ( IGRs ) [18] , [19] . Moreover , functional antisense RNAs are also not detected with our oligo arrays including the antisense RNAs spanning the promoter region of different PHO genes ( Figure 6 , Figure S5 ) [29] , [45] . Nevertheless , application of qRT-PCR with antisense-RNA specific primers suggests that both TRAMP4 and TRAMP5 complexes as well as the exosome participate in RNA-mediated regulatory mechanisms to modulate the expression of several PHO genes [29] but that only TRAMP4 triggers the exosome-mediated degradation of regulatory antisense PHO RNAs in vivo . In conclusion and consistent with previous reports [6] , [7] , [14]–[16] , our experiments support a major role for Trf4p in the exosome-mediated degradation of ncRNAs and suggest that TRAMP4 and TRAMP5 may function on specific subsets of RNAs in vivo . However , it remains to be further investigated how the TRAMP4 and the TRAMP5 complexes achieve specificity for their selective targets . TRAMP4 and TRAMP5 consist of structurally similar protein complexes [1] , [5] , [7] , therefore specificity could be conferred by protein-protein interactions that are engaged by Trf4p or Trf5p and by the Air1p or Air2p subunits [5]–[8] , [20] . Misfolding of the RNPs or the association of proteins with aberrant RNAs may act as selectivity factors that eventually favor the recruitment of either TRAMP4 or TRAMP5 to the RNP target . Several groups have previously demonstrated that the polyadenylation activity of Trf4p stimulates the exosome-mediated degradation of different RNA species in vivo and in vitro [4]–[6] . Consistently , rRNA processing intermediates , snRNAs , snoRNAs , and a few CUTs accumulate as non-polyadenylated molecules in the trf4Δ or the trf5Δ mutant strains [6] , [7] , [14] , [15] , [20] . Intriguingly , even though polyadenylation activity is required for the degradation of highly structured RNAs in vitro , it was reported that a polyadenylation-defective form of Trf4p ( Trf4p-DADA ) can also activate degradation of RNAs by the exosome [9] , [30] . Moreover , a polyadenylation-defective trf4 mutation can rescue the lethality of trf4 and trf5 double mutants [7] . These findings lead to a model , which proposes that the polyadenylation activity of Trf4p may not generally be necessary to guide RNA to the exosome for degradation . However , the universality of this model and whether there might be sets of RNAs that differentially depend on polyadenylation activity has not been addressed so far . Surprisingly , we found that Trf4p-DADA almost fully suppressed the altered gene expression profile of the trf4Δ mutant upon overexpression ( Figure 1 , Table S1 ) . This finding generally supports and extends the model introduced above: Since Trf4p-DADA only partially rescues the accumulation of selected RNAs in the trf4Δ mutant , we suggest that the polyadenylation activity of Trf4p enhances the degradation of most target RNAs by the exosome , but this function is not essential . Polyadenylation in combination with the helicase activity of Mtr4p , which has a marked preference for binding to poly ( A ) RNAs [46] , may be required for digestion of highly structured RNAs . This may be exemplified by the higher fraction of non-coding RNAs among the RNAs that remained accumulated in trf4Δ mutants overexpressing TRF4-DADA ( Figure S1 ) . However , additional mechanisms may account for the suppression of the trf4 mutation by Trf4p-DADA . For instance , since the TRAMP complexes share common subunits , an intriguing speculation is that Trf4p-DADA , in the context of TRAMP4 , recruits Trf5p to target RNAs . Trf5p then adds poly ( A ) tails to facilitate exosome-mediated degradation . In agreement with this idea is the finding that deletion of trf5 in the polyadenylation-defective trf4-236 mutant enhanced the defect in the degradation of CUTs compared to either single mutant [6] . Although this model could explain some of the observed effects in our system ( Figure 2D ) , it cannot account for the observation that Trf4p-DADA rescues the lethality of trf4 trf5 double mutants [7] . Whereas the mechanism of splicing has been extensively investigated , very little is known about the degradation of spliced-out introns [38] , [39] , [47] . In this work , we showed by combined crosslinking-RNA-immunopurification experiments that TRAMP4 likely interacts directly with introns in vivo ( Figure 3 ) . We also provide experimental evidence supporting a role for TRAMP4 in the degradation of spliced-out introns , which is largely independent of the polyadenylation activity of Trf4p ( Figure 2 , Figure S4 ) . However , we could not find a simple correlation between the introns that were highly associated with TRAMP4 , and the relative changes of expression in single trf4Δ or trf5Δ mutants . Moreover , because the expression levels of some introns became exclusively affected in trf4 trf5 double mutants , Trf5p may promote the breakdown of introns in the absence of Trf4p suggesting functional redundancy between Trf4p and Trf5p in intron decay . Further experiments are required to unravel the contributions of different TRAMP complexes in intron decay and to delineate the exact extent of functional redundancy . We envisage that after splicing , intron lariats are rapidly converted into linear forms by the debranching enzyme Dbr1p . Subsets of specific linear introns are then captured by TRAMP complexes to be eventually degraded by the nuclear exosome . Additional pathways may also exist , which involve the 5′ to 3′ exoribonuclease Rat1 and the endonuclease RNaseIII . In fact , lariats that contain RNaseIII binding sites can also undergo internal cleavage by RNaseIII irrespective of the Dbr1-mediated debranching , generating cleavage products that are eventually degraded by exoribonucleases [38] . Transcription at heterochromatin regions was recently reported to occur in S . cerevisiae and S . pombe cells that lack Trf4p or Rrp6p [30] , [48] . Consistent with these reports , we detected the accumulation of a number of RNAs originating from silent mating type cassettes and subtelomeric transcripts in the trf4Δ and rrp6Δ mutants , and to a lower extent in trf5Δ cells ( Figure 5 , Figure S5 ) . This activity is partially dependent on the polyadenylation activity of Trf4p and on a functional exosome ( Figure 4B ) . Although further experiments are needed to elucidate how Trf4p and the exosome contribute to the silencing of heterochromatin domains , we hypothesize that during degradation of subtelomeric RNAs , TRAMP4 , and the exosome modulate the interaction or the accessibility of chromatin remodeling factors such as Sir2 and Set1 [49] , [50] within sites of heterochromatin formation [49] , [50] . There is a growing body of evidence that suggests interactions of Trf4p and chromatin remodeling factors ( reviewed in [23] ) . Transcription of heterochromatin regions can regulate important physiological pathways . In S . cerevisiae and S . pombe strains with mutations in TRAMP or exosome components , accumulation of heterochromatic CUTs has been linked to changes in rDNA copy numbers [30] , [31] . Likewise , high levels of telomeric repeat-containing RNAs ( TERRA ) were shown to act in telomere maintenance in mammalian cells [51] and yeast [41] . In addition to alteration in the rDNA copy number [30] , we discovered that the trf4Δ mutant of S . cerevisiae exhibits a severe shortening of telomeres and that telomeres were only mildly reduced in the rrp6Δ mutant ( Figure 5A ) . Similarly to what was reported for the regulation of the rDNA repeats [30] , telomere maintenance was not strictly dependent on the polyadenylation activity of Trf4 ( Figure 5B ) . Although accumulation of subtelomeric RNAs may perturb the chromatin integrity at the telomeres and negatively affect the telomerase activity , additional mechanisms probably account for the severe shortening of chromosome ends in the trf4Δ mutant . In fact , our results do not provide any straight evidence of a direct link between the extent of subtelomeric RNA accumulation and the severity of telomere shortening . Rather it emerged that the telomeric phenotype of the trf4Δ mutant can in part reflect imbalances in the expression level between the protein subunits Est1p , Est2p , Est3p , and the RNA component TLC1 of the telomerase . We propose that Trf4p stimulates the exosome-mediated degradation of TLC1 through a polyadenylation-independent mechanism . However , in contrast to what happens in cells defective in rrp6 , trf4 deletion causes only high levels of TLC1 , whereas the expression of EST1 , EST2 , and EST3 remains unchanged . It was previously demonstrated that recruitment of the telomerase holoenzyme is mediated by the heterodimeric Ku70/80 complex , which binds the chromosome ends and interacts with the telomerase via a small stem loop region of TLC1 [42] . Thus , the excess of TLC1 in the trf4Δ mutant could interfere with the recruitment of the telomerase at the chromosome ends and ultimately lead to telomere shortening . To conclude , in this work we provide experimental evidence demonstrating that in addition to RNA surveillance , Trf4p and Trf5p participate in post-transcriptional regulatory networks that connect RNA degradation with DNA metabolism and gene regulation ( Figure 7 ) . Although the polyadenylation activity of Trf4p clearly enhances the efficiency of degradation of a broad variety of RNAs via the TRAMP4/exosome complex , expression of the Trf4 protein rather than its polyadenylation activity emerged to be essential for the maintenance of effective post-transcriptional regulatory pathways in the cell .
Manipulations of S . cerevisiae strains were performed by standard procedures . Cells were grown in YPD ( 1% yeast extract , 2% peptone , 2% glucose ) , YPGal ( 1% yeast extract , 2% peptone , 2% galactose ) , or in synthetic minimal medium ( 0 . 67% Bacto-yeast nitrogen base without amino acid , 2% glucose , and amino acid supplements as required ) at 30°C . Temperature shifts to 37°C were done in a shaking water bath . Yeast strains are described in Table S5 . The trf5Δ and rrp6Δ mutant strains were purchased from Open Biosystems . Replacement of the trf5 and the rrp6 genes with the kanMX6 cassette was confirmed by PCR following the manufacturer's instructions . The strain with C-terminal TAP-fusion of FPR1 ( YNL135C ) was purchased from BioCat ( Heidelberg , Germany ) . The correct integration of the TAP-tag was verified by PCR . The trf4Δ strain is a derivative of BY4741 in which the trf4 gene was replaced with the natMX4 marker by homologous recombination as previously reported [52]; primer sequences can be provided upon request . To complement trf4Δ with the wild type allele of trf4 the coding region of trf4 was PCR amplified from S . cerevisiae BY4741 genomic DNA with primers XmaI-trf4-Fw ( 5′-GTCCCGGGAAATATGGGGGCAAAGAGTGTAAC-3′ ) and trf4-Rev-SalI ( 5′-ACGTCGACTTATTAAAGGGTATAAGGATTATAT-3′ ) ( restriction sites are underlined ) . The insert was cloned in pGEMT-easy vector ( Promega ) , digested with XmaI and SalI restriction enzymes and ligated into the same sites on the pNOPPATA1L vector to generate pNOPPATA1L ( pNOP1::TRF4 ) . Trf4Δ cells were transformed with pNOPPATA1L ( pNOP1::TRF4 ) and transformants were selected for leucine prototrophy in synthetic medium at 30°C . The correct integration of the fragment was verified by sequencing . Control trf4Δ/pNOPPAT1L and BY4741/ pNOPPATA1L strains were selected for leucine prototrophy onto synthetic medium after transformation of trf4Δ and BY4741 cells with the pNOPPAT1L plasmid . To express trf4 or trf5 from an inducible pGAL1 promoter the coding regions of trf4 and trf5 were PCR amplified from S . cerevisiae BY4741 genomic DNA with primers SacI-trf4-Fw ( 5′-GTGAGCTCAAATATGGGGGCAAAGAGTGTAAC-3′ ) and trf4-Rev-XhoI ( 5′ACCTCGAGTTATTAAAGGGTATAAGGATTATAT-3′ ) or BamHI-trf5-Fw ( 5′-AAGGATCCCATAATGACAAGGCTCAAAGCAAAATA-3′ ) and trf5-Rev-XhoI ( 5′-AGCTCGAGTTATTAAAGAGCCTGGCCTTTAGAG-3′ ) . The fragments were cloned into pGEMT-easy vector , digested with SacI-XhoI or with BamHI-XhoI and ligated into the same sites of pYC6/CT ( Invitrogen ) to generate pSAL1 ( pGAL1::TRF4 ) or pSAL2 ( pGAL1::TRF5 ) , respectively . trf4Δ trf5Δ mutant cells complemented with wild type TRF4 by the pRS416-TRF4 plasmid were successively transformed with either pSAL1 or pSAL2 . Transformants were selected onto YPD supplemented with blasticidin ( InvivoGen ) 150 µg/ml at 30°C . To induce the loss of the pRS416-TRF4 plasmid , blasticidin resistant colonies were inoculated three times on synthetic medium supplemented with 2% galactose , blasticidin ( 15 µg/ml ) and 5-fluoro-orotic acid ( 1 µg/ml; Zymo Research ) at 30°C . Transformation with pSAL1 or pSAL2 and loss of pRS416-TRF4 was confirmed by restriction digestion with SacI-XhoI or with BamHI-XhoI of plasmid DNA preparations purified from clones that were uracil auxotrophic , blasticidin resistant , and glucose sensitive . Total RNA was extracted with the hot phenol extraction method . Single yeast colonies were inoculated in 5 ml YPD or YPGal medium supplemented with the appropriate amount of selective drug ( G418 , 200 µg/ml; clonNat , 100 µg/ml ) and incubated overnight at 30°C ( pre-cultures ) . Pre-cultures were diluted to an OD600 of 0 . 1 in 50 ml of fresh YPD or YPGal medium without drugs and grown at 30°C to an OD600 of 0 . 7 . Cells were collected by centrifugation for 5 min at 3 , 000 g and resuspended in AE buffer ( 50 mM Na-acetate , 10 mM EDTA , pH 5 . 3 ) with 1% SDS . After adding one volume of phenol ( pH 5 . 3 ) , the suspension was vigorously shaken for 1 min and incubated at 65°C for 4 min in a heating block ( Thermomixer comfort , Eppendorf ) . The aqueous phase was separated from the phenol phase by centrifugation at 20 , 000 g and extracted again with phenol ( pH 5 . 3 ) and then with chloroform . Total RNA was precipitated from the aqueous phase by the addition of 2 . 6 volumes of ice-cold ethanol and of 1/10 volume of 1 M Na-acetate ( pH 5 . 3 ) for 20 min on ice . The precipitated RNA was recovered by centrifugation at 20 , 000 g for 30 min at 4°C , the pellet was washed with 70% ethanol and resuspended in DEPC-treated water . To remove contaminating DNA , RNA preparations were treated with DNA-free™ ( Ambion ) according to the manufacturer's instructions . The integrity of RNA samples was routinely checked by gel electrophoresis ( 1 . 2% agarose - 6% formaldehyde ) in 1× HEPES buffer ( 50 mM HEPES [pH 7 . 8] , 10 mM EDTA ) and RNA was quantified by UV-spectrophotometry ( A260 ) with a Nanodrop device ( Witeg AG ) . Single colonies of the trf4Δ trf5Δ/pSAL1 or of the trf4Δ trf5Δ/pSAL2 mutant strains were inoculated in YPGal liquid medium supplemented with blasticidin ( 150 µg/ml; InvivoGen ) at 30°C and grown overnight . The following day , cultures were diluted to an OD600 of 0 . 1 in 300 ml of fresh YPGal medium and grown at 30°C to an OD600 of 0 . 7 . Cultures were equally split into three tubes and cells were collected by centrifugation at RT for 5 min at 3 , 000 g . After centrifugation , one-third of the culture was rapidly frozen in liquid nitrogen and stored at −70°C ( t0 time point ) ; one-third was resuspended in YPGal and incubated at 30°C for 1 h ( t1 Gal time point ) , while the rest of the culture was inoculated in YPD at 30°C for 1 h ( t1 Glc time point ) . Cells were collected by centrifugation and stored at −70°C . Total RNA was purified from the cell pellet as described above . DNA microarrays contained 10 , 944 oligo probes ( 70-mers ) from the Array-Ready Oligo Set Version 1 . 1 representing 6 , 388 S . cerevisiae ORFs , and the Yeast Brown Lab Oligo Extension Version ( YBOX vers . 1 . 0 ) with 3 , 456 probes to detect ncRNAs , rRNA precursors , introns , exon-intron and exon-exon junctions , other sequences predicted to be expressed , additional probes for genes with high cross-hybridization potential and controls for array quality measurements and normalization . Details of oligonucleotide selection and probe sequences are available from the Operon website ( www . operon . com ) . All microarray data are available at the Stanford Microarray Database ( SMD ) or at the Gene Expression Omnibus ( GEO ) with accession number GSE16107 . The probes were printed on epoxy coated glass slides ( Nexterion slide E ) at the Center for Integrative Genomics , University of Lausanne , Switzerland . Oligo arrays were blocked in 5× SSC , 0 . 1 mg/ ml BSA , 0 . 1% SDS for 1 h at 42°C , and subsequently washed three times in 0 . 1× SSC for 5 min at RT , rinsed in water for 30 s , and dried by centrifugation ( 500 g for 2 min ) . The slides were used the same day . Microarray analysis was performed by competitive hybridization of Cy3 and Cy5 fluorescently labeled cDNA . Total RNA ( 25 µg ) was reverse transcribed with SuperScript RT II ( Invitrogen ) in the presence of 2 . 5 mM aminoallyl-dUTP ( Sigma ) and dNTPs , with a 1∶1 mixture of dT20V and random nonamer ( N9 ) primers ( 5 µg of each , Sigma ) . After first strand cDNA synthesis , RNA was hydrolyzed with 0 . 1 M NaOH and 0 . 1 M EDTA at 65°C for 15 min , and samples were neutralized with 0 . 35 M HEPES ( pH 8 . 0 ) . Clean up of the reaction mix was performed in Microcon-YM30 ( Millipore ) filled with distilled water . Amino-allyl containing cDNA was eluted with 100 mM NaHCO3 ( pH 9 . 0 ) and covalently linked to either fluorescent Cy3 or Cy5 NHS-monoester ( GE Healthcare ) . Thereby , cDNAs derived from wild-type control cells were labeled with Cy3 , the ones derived from mutant cells with Cy5 . Unincorporated dyes were removed with the QIAquick PCR Purification Kit ( Qiagen ) . The samples were mixed in standard formamide based hybridization buffer ( Ocimum Biosolution Hybridzation Solution , Cat . No . 1180-000010 ) supplemented with 1 mg/ml poly ( A ) in a final volume of 20 µl , and competitively hybridized to yeast oligo arrays in a sealed hybridization chamber ( Corning ) at 42°C for 12–16 h . Arrays were successively washed in three buffer chambers filled with 2× SSC ( 300 mM NaCl , 30 mM Na-citrate , pH 7 . 0 ) , 0 . 2% SDS; 2× SSC; and 0 . 2× SSC . The first wash was performed at 42°C for 12 min , the subsequent washes at RT for 12 min . After briefly rinsing in ethanol , microarrays were scanned with an Axon Instruments Scanner 4200A ( Molecular Devices ) . Scanning parameters were adjusted to give similar fluorescent intensities in both channels . Data were collected with GenePix Pro 5 . 1 ( Molecular Devices ) and spots with abnormal morphology were excluded from further analysis . Array data were exported to Acuity 4 . 0 ( Molecular Devices ) and normalized to the mean of ratio of medians = 1 excluding the signals from control features . We collected three biological replicates each for determining the relative changes of transcript levels in the trf4Δ , trf5Δ and trf4Δ/TRF4-DADA mutant cells compared to the respective wild-type cells ( total of 9 arrays ) . Data were filtered in Acuity for regression correlation ( Rgn2>0 . 5 ) , signal to noise ratio >2 . 5 in both channels , and only features that met these criteria in >60% of arrays were considered for further analysis ( total 7481 features; Dataset S1 ) . Data were exported into Microsoft Excel to determine percentile ranks and to perform SAM ( version 3 . 0 [28] ) . We used the web interface for Cyber-T ( http://cybert . microarray . ics . uci . edu/ ) to employ statistical analyses based on regularized t-tests that use a Bayesian estimate of the variance among gene measurements within an experiment [34] . The 715 unique features ( 9 . 5% of all analyzed features ) that were on average at least 2-fold changed with an FDR<5% in either the trf4Δ , trf5Δ , or trf4Δ/TRF4-DADA replicates were compiled ( Table S1 ) . The genes and arrays were hierarchically clustered based on Pearson correlations with Cluster 3 . 0 [53] and the result was visualized as a heatmap with Java TreeView 1 . 0 . [54] ( Figure 1A ) . Commonly enriched GO terms among list of genes were retrieved with GO Term Finder that uses a hypergeometric distribution with Multiple Hypothesis Correction ( i . e . , Bonferroni Correction ) to calculate p-values ( SGD; www . yeastgenome . org ) . qRT-PCR was performed with an ABI Prism 7000 Sequence Detection System ( ABI Prism ) and the Power SYBR Green PCR Master Mix ( Applied Biosystems ) according to the manufacturer's instructions . The first strand cDNA was synthesized with 5 µg of total RNA , 50 µM oligo ( dT ) 20 , 0 . 1 µM random hexamers and SuperScript RT III ( Invitrogen ) . RNA was subsequently hydrolyzed with 125 mM NaOH and 10 mM EDTA at 65°C for 15 min . The mix was neutralized with 400 mM Tris-HCl ( pH 8 . 0 ) and loaded onto a Microcon-YM30 ( Millipore ) concentrator column filled with 10 mM Tris-HCl ( pH 8 . 0 ) . After centrifugation for 8 min at 13 , 500 g the microcon was filled again with 10 mM Tris-HCl ( pH 8 . 0 ) . This step was repeated twice . After elution , the cDNA was used as template for PCR with the following conditions: 95°C for 10 min; 40 cycles at 95°C for 15 s , and 60°C for 1 min . Transcript abundance was calculated as log2 of normalized ratios with the Pfaffel method of relative quantification [55] . Data were normalized to actin mRNA levels . ( All primers used for quantitative real time PCR analysis and for strand specific reverse transcription are listed in Table S6 . ) Primer sequences for the strand specific synthesis of the antisense-Ty1 ( RTL ) cDNA and of the antisense-PHO5 , -PHO11 , and -PHO89 cDNAs can be provided upon request . 1 L of fresh YPD medium was inoculated with an overnight pre-culture of yeast cells ( OD600 = 0 . 1 ) that were further cultured at 30°C to an OD600 = 0 . 7 . RNAs and proteins were cross-linked with 1% formaldehyde that was added directly to the culture for 7 min at RT . The cross-linking reaction was subsequently quenched by the addition of 125 mM glycine ( pH 7 . 0 ) for 5 min at RT . During cross-linking and quenching reactions the cultures were maintained under constant shaking at 100 rpm . Cells were harvested by centrifugation ( 1 , 500 g ) at 4°C , washed twice with 50 ml of ice-cold PBS , and lysed in 5 ml of ice-cold lysis buffer ( 20 mM Tris-HCl [pH 7 . 5] , 140 mM KCl , 1 . 8 mM MgCl2 , 0 . 1% NP-40 , 0 . 1 mM DTT , 10% glycerol , 0 . 2 mg/ml heparin , 0 . 5 µg/ml Leupeptin , 0 . 8 µg/ml Pepstatin , 50 U/ml SUPERaseIn [Amersham] ) by grinding in mortar filled with liquid nitrogen . Contaminating DNA was digested with 20 U/ml RNAse-free DNase I ( Promega ) . The WCE was centrifuged twice at 13 , 000 g for 10 min at 4°C to remove cell debris . The protein concentration of the extract was determined with the Bradford method ( Bio-Rad Protein Assay , BioRad ) . To purify total RNA from extracts for microarray analysis ( input RNA sample ) , 100 µl of WCE was digested with Proteinase K ( 0 . 4 mg/ml ) for 30 min at 37°C , heated up to 70°C for 45 min to reverse the formaldehyde cross-linking , and proteins were extracted with phenol-chloroform-isoamyl alcohol ( PCI , 25∶24∶1 ) . RNA was precipitated with 1 . 5 M LiCl at −20°C overnight and collected by 30 min centrifugation ( 14 , 000 g ) at 4°C . The RNA pellet was washed twice with 70% ethanol and resuspended in DEPC-treated water . Cross-linked TAP-tagged proteins were captured from the WCE as follows: 300 µl rabbit IgG-coupled agarose beads ( Sigma ) were equilibrated at 4°C in lysis buffer supplemented with 5% BSA . WCE was added to the blocked IgG beads and mixed on a rotator overnight at 4°C . TAP-tagged proteins were then recovered by spinning down the IgG beads at 72 g for 2 min at 4°C . Beads were thoroughly washed three times with ice-cold lysis buffer supplemented with increasing concentrations of NaCl ( 100 mM , 200 mM , and 350 mM ) . RNP complexes were digested in 1 ml of elution buffer ( 50 mM Tris-HCl [pH 7 . 0] , 1% SDS , 5 mM EDTA , 10 mM DTT , 140 mM KCl , 5% glycerol , 0 . 01% NP-40 ) with 100 µl Proteinase K ( 4 mg/ml ) for 20 min at 37°C . Formaldehyde cross-linking was reversed by incubation of the eluate at 70°C for 45 min in a gently shaken heating block . Immunopurified RNA ( IP-RNA ) was isolated by extraction with PCI and isopropanol precipitation . The RNA pellet was washed twice with 70% ethanol and resuspended in DEPC-water . For the microarray analysis of the IP-RNA , 5 µg of total RNA ( input RNA ) and 500 ng of IP-RNA were converted into Cy3 and Cy5 fluorescently labeled cDNA , respectively , and samples were competitively hybridized on yeast oligo arrays as described above . We collected data from three biological replicates with Trf4-TAP , from two replicates with Fpr1-TAP and from one untagged control ( BY4741 strain ) sample . Array data were filtered in Acuity for signal to noise ratio >3 for the channel with the input RNA ( Cy3 ) , and percentile ranks for filtered data were calculated based upon the log2 of the Cy5/Cy3 ratio in each experiment with Excel ( Dataset S2 ) . Northern blotting experiments were performed as previously described [56] , [57] . Briefly , 35 µg of total RNA in RNA loading buffer ( 50% formamide , 6% formaldehyde , 50 mM HEPES [pH 7 . 8] , 0 . 25% xylene cyanol , 0 . 25% bromophenol blue , 10% glycerol ) was loaded on a 1 . 5% agarose-6% formaldehyde gel and fractionated in 1× HEPES buffer ( 50 mM HEPES [pH 7 . 8]; 10 mM EDTA ) at 50–60 Volts for 15 h . After washing of the gel in distilled water for 15 min , the RNA was partially cleaved with 75 mM NaOH for 15 min . The gel was neutralized in a solution comprised of 5 M Tris-HCl ( pH 7 . 0 ) and 1 . 5 M NaCl for 15 min , and equilibrated in 10× SSC for 20 min . Capillary transfer of the RNA to Hybond-N+ membranes ( Amersham ) was performed in 10× SSC over night . RNA was UV-crosslinked to the membrane in a UV Stratalinker 1800 ( Stratagene ) with 1200 µJ . DNA probes for hybridization were prepared by random incorporation of α-[32P] dATP with the Random Prime DNA Labeling Kit ( Roche ) . Unincorporated α-[32P] dATP was removed by MicroSpinTM G-25 Columns ( GE Healthcare ) . DNA templates for the preparation of the randomly labeled probes were produced by PCR amplification with primer pairs rps24A-int-Fw ( 5′-AGAAATGGTATGTTAAAAAGTGCTCAGATG-3′ ) and rps24A-int-Rev ( 5′-CAGCGTCAGACTGAGAAAAAAC-3′ ) or rpl2B-int-Fw ( 5′-CGCATAATTATGGCAAATGTTATGAAGG-3′ ) and rpl2B-int-Rev ( 5′-CGAATAACTCTACCTGTTTAAATGAGG-3′ ) to detect the RPS24A and RPL2B introns , and primer pairs rps24A-ex-Fw ( 5′-TCTGACGCTGTTACTATCCGTACTA-3′ ) and rps24A-ex-Rev ( 5′-AATCGGCGTTACGACGAGCAACCT-3′ ) or rpl2B-ex-Fw ( 5′-CACACCAGATTAAGACAAGGTGCT-3′ ) and rpl2B-ex-Rev ( 5′-GAACCACGTAGTAAACCGGTTCTTCT-3′ ) to detect the RPS24A or RPL2B mRNAs . The DNA template for the preparation of the randomly labeled PGK1 probe was previously described [56] . Hybridization was carried out in rolling tubes in hybridization buffer containing 50% formamide , 5× SSPE ( 750 mM NaCl , 50 mM NaH2PO4 , 5 mM EDTA , pH 7 . 4 ) , 5× Denhardts solution , 1% SDS , and 200 µg/ml salmon sperm DNA according to standard procedures . The result of the hybridization was visualized with a Phosphor Imager . Two µl of protein samples were directly spotted onto the nitrocellulose membrane ( Whatman ) for dot blot analysis . For Western blots , proteins were separated on 12% polyacrylamide gels , transferred to nitrocellulose membranes , and incubated with antibodies indicated in the figure legends . The anti-TAP antibodies were previously described [5] . To generate anti-Air2 antibodies a C-terminal fragment of Air2p ( comprising amino acids 210–344 of Air2p ) was cloned in pET22b ( Novagen ) and expressed in the Escherichia coli strain BL21 . The resulting C-terminal Air2p fragment contained a [His]6 tag fusion on its C-terminus . The protein was expressed in LB medium according to the manufacturer ( Novagen ) and affinity purified on Ni2+-NTA agarose ( Sigma ) under denaturing conditions as described [5] . After further purification on reverse phase chromatography ( GE Healthcare ) in FPLC , approximately 100 µg of the purified protein was used for three injections into a rabbit ( Eurogentec ) . Peroxidase-conjugated swine anti-rabbit antibodies ( DAKO ) served as secondary antibodies for detection of the primary antibodies with the ECL Plus Western blotting detection system ( Amersham ) . Telomere length measurement was carried out as previously described [44] . Genomic DNA was prepared from yeast cells grown in YPD and according to standard procedures . DNA from each strain was digested overnight with the restriction enzyme XhoI and fractionated by 1% agarose gel electrophoresis in 1× TBE buffer ( 90 mM Tris-borate , 2 mM EDTA ) at 40 Volts for 15 h . DNA was transferred to a Hybond-N+ membrane ( Amersham ) and Southern blot was performed by hybridization with a telomeric probe ( 26G; 5′-TGTGGGTGTGGTGTGTGGGTGTGGTG-3′ ) that was end-labeled with γ-[32P] ATP and T4 polynucleotide kinase ( Biolabs ) . All hybridizations were done in 200 mM Na2HPO4 , 1 mM EDTA , 2% SDS , 1% BSA and 50 µg/ml salmon sperm DNA . The average telomeric length for each lane was estimated by a 1 kb DNA ladder ( peqLab ) that was run in a lane next to the XhoI digested genomic DNA . The ladder was probed with the same DNA ladder after γ-32P end-labeling . | The discovery that most regions of the genome are actively transcribed into non-coding RNAs has dramatically increased interest in their function and regulation . Recent data from us and others have shed light on the molecular machinery that promotes the decay of such transcripts . In the yeast S . cerevisiae , Trf4p and Trf5p are alternative subunits of the so-called TRAMP complex , which degrades aberrant and short-lived RNAs . They add short poly ( A ) tails to their substrate RNAs that function as landing pads for exonucleases mediating RNA decay . Although alternate compositions of TRAMP complexes exist , the RNA substrate specificities and the processes controlled by them have not been determined . Applying a genome-wide approach , we describe overlapping yet distinct functional implications of different TRAMP complexes , and we demonstrate strong connections between RNA quality control and other RNA–related processes such as telomer length maintenance . Moreover , our study shows that the degradation of specific target RNAs is not strictly dependent on the polyadenylation activity of Trf proteins in vivo . These results suggest novel and integrative functions of TRAMP complexes for RNA regulation . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"molecular",
"biology/mrna",
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] | 2009 | Distinct Roles of Non-Canonical Poly(A) Polymerases in RNA Metabolism |
Neural tube defects ( NTDs ) , including spina bifida and anencephaly , are common birth defects whose complex multigenic causation has hampered efforts to delineate their molecular basis . The effect of putative modifier genes in determining NTD susceptibility may be investigated in mouse models , particularly those that display partial penetrance such as curly tail , a strain in which NTDs result from a hypomorphic allele of the grainyhead-like-3 gene . Through proteomic analysis , we found that the curly tail genetic background harbours a polymorphic variant of lamin B1 , lacking one of a series of nine glutamic acid residues . Lamins are intermediate filament proteins of the nuclear lamina with multiple functions that influence nuclear structure , cell cycle properties , and transcriptional regulation . Fluorescence loss in photobleaching showed that the variant lamin B1 exhibited reduced stability in the nuclear lamina . Genetic analysis demonstrated that the variant also affects neural tube closure: the frequency of spina bifida and anencephaly was reduced three-fold when wild-type lamin B1 was bred into the curly tail strain background . Cultured fibroblasts expressing variant lamin B1 show significantly increased nuclear dysmorphology and diminished proliferative capacity , as well as premature senescence , associated with reduced expression of cyclins and Smc2 , and increased expression of p16 . The cellular basis of spinal NTDs in curly tail embryos involves a proliferation defect localised to the hindgut epithelium , and S-phase progression was diminished in the hindgut of embryos expressing variant lamin B1 . These observations indicate a mechanistic link between altered lamin B1 function , exacerbation of the Grhl3-mediated cell proliferation defect , and enhanced susceptibility to NTDs . We conclude that lamin B1 is a modifier gene of major effect for NTDs resulting from loss of Grhl3 function , a role that is likely mediated via the key function of lamin B1 in maintaining integrity of the nuclear envelope and ensuring normal cell cycle progression .
Modifier genes have been ascribed significant influence in determining susceptibility to disease in complex traits , as well as partial penetrance and variable expressivity of monogenic conditions [1] . Moreover , modifier genes are considered largely responsible for the phenotypic variation observed when mutations are bred onto different genetic backgrounds in mice . However , identification of modifier genes and determination of their functional effects presents a considerable challenge . Understanding the genetic basis of neural tube defects ( NTDs ) , such as spina bifida and anencephaly , typifies these difficulties . NTDs are common , severe congenital malformations resulting from failure of closure of the neural tube during embryonic development [2] . In humans , they are among the commonest birth defects , affecting around 1 per 1000 pregnancies worldwide . However , the causes are not well understood owing to their multigenic inheritance and the potential influence of environmental factors , either predisposing or ameliorating [3] , [4] . The potential complexity of NTD genetics is illustrated by the fact that more than 200 different genes have been implicated as potential contributors to the overall burden of NTDs , with neural tube closure phenotypes in mouse strains carrying naturally occurring or targeted mutations [5]–[7] . Additionally , in many of these models penetrance is influenced by genetic background , indicating the presence of modifier genes . The curly tail ( ct ) mouse mutant is among the most extensively characterised models of NTDs [8] . Approximately 5–10% of homozygous ct/ct embryos develop cranial NTDs ( exencephaly ) , while 15–20% exhibit spinal NTDs ( spina bifida ) , due to failure of closure of neural folds in the prospective brain and low spinal region , respectively . The major ct gene corresponds to a hypomorphic allele of the transcription factor grainyhead-like-3 ( Grhl3 ) , null mutants of which display spina bifida with 100% penetrance [9]–[11] . Expression of Grhl3 is diminished in the hindgut of ct mutant embryos , due to an upstream regulatory mutation , resulting in a diminished cellular proliferation rate in the hindgut endoderm [12] , [13] . The consequent dorso-ventral growth imbalance leads to excessive ventral curvature of the caudal region of the embryo and , hence , mechanical suppression of neural tube closure at the posterior neuropore [14] . The incidence of curly tail NTDs can be influenced by multiple environmental and genetic factors [8] , [15]–[18] . In addition , NTD frequency is also markedly affected by backcross to different strains , indicating the presence of modifier loci in the curly tail genetic background [19] . Thus , it is apparent that the genetic component of predisposition to NTDs is multifactorial in ct , as in humans . In the current study , we identified lamin B1 as a modifier gene for NTDs in curly tail mice . Lamins are intermediate filament proteins of which the A-type , lamins A and C , are encoded by LMNA while , among the B-type , lamin B1 is encoded by LMNB1 and lamins B2 and B3 , are encoded by LMNB2 . The nuclear lamina is a protein complex underlying the inner nuclear membrane and composed of a meshwork of lamin polymers and lamin-binding proteins [20]–[22] . In addition to a key structural role in assembly and maintenance of the nuclear envelope , it has become clear that lamins have multiple functions in a diverse range of cellular properties . Thus , lamins influence nuclear shape and size as well as anchoring of protein structures , including nuclear pore complexes , in the nuclear envelope [23] , [24] . Additionally , lamins function in DNA synthesis and transcriptional regulation both through interaction with chromatin , to mediate sub-nuclear chromosomal positioning , and by direct interactions with transcription factors [25]–[29] . Highlighting the importance of lamin function , a number of clinically distinct diseases , termed laminopathies , have been found to result from mutation of LMNA [20] , [30] . These include muscular dystrophy disorders ( e . g . Emery-Dreyfus muscular dystrophy ) , lipodystrophies , progeria syndromes ( e . g . Hutchinson-Gilford progeria syndrome and Atypical Werner syndrome ) and peripheral neuropathy ( Charcot-Marie-Tooth disease type 2B1 ) . In contrast to LMNA , coding mutations in LMNB1 have not so far been associated with human disease , although genomic duplication of LMNB1 is thought to cause a progressive demyelinating disorder , adult-onset autosomal dominant leukodystrophy [31] , [32] . Mice homozygous for a loss of function allele of Lmnb1 die at birth with reduced growth , impaired lung development and cortical abnormalities in the brain [33] , [34] , while Lmnb2 knockouts exhibit neuronal migration defects in the cerebral cortex and cerebellum [35] . Lmnb1/lmnb2 double knockouts exhibit a reduced thickness of the brain cortex , with altered cell cycle exit of neuronal progenitors and neuronal migration defects [29] , [34] . Forebrain-specific deletion of lmnb1 or lmnb2 , allowed study of brain phenotypes at post-natal stages and showed that both genes are individually required for normal development of the cortex [34] . In the current study we identified a polymorphic variant form of lamin B1 , present on the genetic background of the curly tail strain . The reduction in length of a series of glutamic acid residues , from nine to eight , was found to cause significant reduction in the stability of the lamin B1 interaction within the nuclear lamina . Genetic analysis , involving generation of curly tail sub-strains carrying combinations of the lamin B1 variant and Grhl3ct mutation demonstrate a dramatic effect of lamin B1 on frequency of NTDs . In parallel , lamin B1 has a profound effect on nuclear morphology and proliferative capacity . Overall , our findings show that Lmnb1 can act as a modifier gene affecting risk of NTDs , an effect that appears to be mediated through impaired cell cycle regulation which summates with the effect of Grhl3 mutation .
In a proteomic analysis of the curly tail mutant , two-dimensional protein gels were generated from samples at embryonic day ( E ) 10 . 5: the stage of spinal neural tube closure . Comparison of stage-matched embryos revealed differential migration of a series of three spots , which migrated to a more basic position in gels derived from ct/ct samples than the equivalent spots in congenic wildtype ( +ct/+ct ) control gels ( Figure 1A–1C ) . This migration change was apparent by the complete absence of the three spots that were detected in the +ct/+ct gels from the ct/ct gels and vice versa . This difference was detected both in analysis of whole embryos and in isolated caudal regions that encompassed the posterior neuropore ( PNP ) , the region of active neural tube closure . In both strains , these spots were identified by liquid chromatography tandem mass spectrometry as lamin B1 ( Table S1 ) . Variation in abundance of some other spots between genotypes was observed , however , no spots other than those corresponding to lamin B1 showed a difference in migration . Neither the abundance of Lmnb1 mRNA nor total lamin B1 protein abundance were found to differ between ct/ct and +ct/+ct embryos , by real time qRT-PCR or western blot respectively ( Figure 1D–1F ) . Moreover , the sites of Lmnb1 expression at neurulation stages were also comparable between genotypes as determined by whole mount in situ hybridisation ( Figure 1G–1H ) . Expression was apparent throughout most of the embryo with the exception of surface ectoderm and the heart ( Figure S1 ) , where staining intensity was much lower than in other tissues . Altered migration of lamin B1 during the isoelectric focussing step of 2-DE results from a charge difference between the protein in ct/ct and +ct/+ct samples . Such a difference could potentially result from an alteration in primary sequence and the Lmnb1 coding region was therefore sequenced in ct/ct and +ct/+ct genomic DNA and cDNA . A synonymous polymorphism , C612T ( annotated as SNP 18: 56868078 ) , was found in exon 1 of the ct/ct sequence . In addition , a three base-pair GAG deletion ( annotated as Deletion 18: 56909394 ) was noted in exon 10 . This deletion corresponds to one of a sequence of GAG nucleotides at position 1657–1683 of the coding sequence , encoding a stretch of nine glutamic acid ( Glu ) residues in the tail domain of the wild-type protein ( Figure 2A , 2B ) . Thus , the curly tail Lmnb1 gene encodes eight Glu residues at amino acids 553–560 ( here denoted Lmnb18E to indicate number of glutamic acids ) , as opposed to nine Glu ( residues 553–561 ) encoded by the +ct/+ct sequence ( denoted Lmnb19E ) . Since Glu carries a negative charge , it appeared likely that the difference in number of Glu residues is responsible for the migration difference of lamin B1 spots on 2D gels generated from ct/ct and +ct/+ct samples . The Glu repeat in the lamin B1 tail domain is predicted to form an alpha-helix ( PSIPRED secondary structure prediction [36] ) . Loss of a residue would impose a hundred degree rotation on the C-terminal region of the protein . The helix is likely to be capable of interacting with the inner nuclear phospholipid membrane [37] . Given that this region contains another strong membrane interactor , the C-terminal farnesylcysteine , we hypothesised that the interaction of lamin B1 with the nuclear membrane could be affected by variation in the number of Glu residues . We therefore used fluorescence loss in photobleaching ( FLIP ) to investigate possible functional effects on the stability of the lamin B1 tail domain within the nuclear envelope . Full length laminB1-YFP fusion proteins appeared to be stably integrated into the nuclear lamina without apparent difference between variants . We also tested truncated forms of the protein as these have previously been found to provide greater sensitivity to altered properties in this assay [26] . Fusion proteins comprising a nuclear localisation sequence , YFP and the forty C-terminal residues of lamin B1 were expressed in primary mouse embryonic fibroblasts ( MEFs ) and subjected to FLIP , as previously performed for human lamin B1 [26] . The decline in fluorescence intensity in the unbleached area of membrane was much more rapid in cells expressing Lmnb18E compared with Lmnb19E ( Figure 2C ) . After 100 seconds , there was an approximately 43% decline in intensity in cells expressing Lmnb18E compared with only a 21% decline with Lmnb19E ( p<0 . 001 , t-test ) . This significant difference between variants persisted throughout the analysis , and is indicative of increased mobility , and hence decreased stability of interaction of Lmnb18E within the nuclear envelope . Sequencing of exon 10 of lamin B1 in a series of mouse strains showed that the wild-type ( Lmnb19E ) variant of lamin B1 is found in the majority of strains including C57BL/6 , C3H/HeJ , SWR , DBA/2J , BALB/c , LPT/Le and CAST/EiJ . However , the Lmnb18E variant occurs in CBA/Ca , a sub-strain of which ( CBA/Gr ) contributed to the genetic background of the curly tail strain [38] . The variant was also present in the 101 strain and hence in mice harbouring the splotch ( Sp2H; Pax3 ) mutation , which arose in a mutagenesis experiment on a mixed CBA/101 genetic background [39] . The 18: 56868078 SNP and Deletion 18: 56909394 were found to be in linkage disequilibrium . Thus , the Lmnb18E variant in ct/ct is characteristic of this particular genetic background . Embryos of the CBA/Ca strain do not exhibit developmental abnormalities under normal laboratory conditions , indicating that the Lmnb18E variant alone is insufficient to cause NTDs . Nevertheless , given the possible effect on stability of the lamina , we speculated that this variant could represent one of the modifier genes that are major determinants of penetrance of the curly tail defect . To test this idea , we inter-crossed ct/ct and +ct/+ct mice to generate sub-strains of mice carrying different combinations of the Lmnb1 variant ( i . e . Lmnb18E and Lmnb19E; abbreviated hereafter as L8E and L9E ) and the Grhl3 mutant allele ( Grhl3ct or Grhl3+; abbreviated as Gct and G+ ) . Each sub-strain was maintained in homozygous form for both Lmnb1 and Grhl3 alleles , that is: ( i ) L8E/8E; Gct/ct ( denoted ct8E ) ; ( ii ) L8E/8E; G+/+ ( denoted +ct;8E ) ; ( iii ) L9E/9E; Gct/ct ( denoted ct9E ) ; ( iv ) L9E/9E; G+/+ ( denoted +ct;9E ) . In the +ct strain the genetic background is approximately 97% curly tail [9] and in each sub-strain it is predicted to be 99 . 5% curly tail ( see Figure S2 for breeding scheme ) . Embryos were collected at E11 . 5–15 . 5 and analysed for the presence or absence of NTDs . Among embryos of the ct8E sub-strain , the range and frequency of phenotypes was closely similar to that observed in the curly tail ( ct ) strain which has the same genotype at the Lmnb1 and Grhl3 loci . Defects included spina bifida , tail flexion defects and exencephaly ( Figure 3B–3D ) , while other embryos appeared normal ( Figure 3A ) . Importantly , however , varying the Lmnb1 genotype produced a striking difference in frequency of NTDs ( Figure 3E ) . Thus , spina bifida occurred at significantly lower frequency in the ct9E sub-strain ( 5 . 8% ) than in curly tail ( 14 . 2% ) or in the ct8E sub-strain ( 15 . 8% ) . Therefore , homozygosity for the Lmnb18E variant confers approximately three-fold higher risk of spina bifida in Gct/ct embryos , compared with homozygosity for the Lmnb19E variant . Interestingly , although cranial NTDs occur at lower frequency than spina bifida in the curly tail strain , we also observed the rate of exencephaly to be significantly reduced among ct9E embryos ( 3 . 0% ) compared with curly tail ( 6 . 4% ) or ct8E embryos ( 8 . 2% ) . As expected , the frequency of exencephaly in the latter two strains did not differ significantly ( Figure 3E ) . Although the genetic background of each sub-strain was predicted to be approximately 99 . 5% curly tail we could not exclude a possible effect of the region of DNA that is tightly linked and inherited with lmnb1 . We therefore examined the possibility that a neighbouring gene to lmnb1 could vary in expression between the ct9E and ct8E sub-strains . Using a list of genes that are located within a 41 Mb interval of chromosome 18 centred on lmnb1 , we interrogated microarray data generated from RNA of the caudal region of stage-matched ct/ct and +ct/+ct embryos ( E10 . 5; 28–29 somite stage ) . Among 11 differentially expressed genes ( p<0 . 05; fold-change 1 . 5-fold or greater ) , 4 showed a similar trend of differential expression on qRT-PCR analysis of independent ct/ct and +ct/+ct samples . However , none of these genes varied in expression when analysed by qRT-PCR in stage-matched ct9E and ct8E samples ( Table S2 ) , suggesting that the phenotypic difference between the sub-strains does not result from differential expression of genes located in proximity to lmnb1 . Instead , variation in expression between ct/ct and +ct/+ct samples seem likely to be due to downstream effects of the Grhl3ct mutation in ct/ct embryos . Embryos of the wild-type congenic curly tail strain ( +ct;9E , genotype: L9E/9E; G+/+ ) do not develop exencephaly , spina bifida or tail flexion defects ( Figure 3E ) [9] . However , when the Lmnb18E variant was bred onto the Grhl3 wild-type genetic background , to produce mice of L8E/8E; G+/+ genotype ( +ct;8E ) , we observed a low frequency of tail flexion defects , indicative of delayed PNP closure ( Figure 3E ) . Exencephaly was also occasionally observed ( Figure 3E ) . These data demonstrate that the presence of the Lmnb18E variant can predispose to defects of cranial and spinal neural tube closure , even in the absence of the Grhl3 mutation . Although curly tail NTDs are partially penetrant , affected embryos can be recognised on the basis of an enlarged PNP at E10 . 5 [40] . In order to examine the effect of Lmnb1 variants on the progress of spinal neural tube closure directly , PNP length was measured in a series of embryos at E10 . 5 ( Figure 4 ) . Among embryos that were wild-type at the Grhl3 locus ( +ct and +ct;8E ) , PNP length diminished rapidly between the 26 and 31 somite stages and , by the 30–31 somite stage , the PNP was very small ( 12 out of 37 embryos ) or closed ( 25 of 37 embryos ) . There was no detectable difference between embryos with Lmnb18E/8E and Lmnb19E/9E genotypes . In contrast , mean PNP lengths were significantly larger in the Grhl3ct/ct sub-strains , reflecting an overall delay in closure . Although mean PNP length did not differ between curly tail and the ct8E sub-strain , embryos of the ct9E sub-strain exhibited a more rapid reduction in PNP length from the 28–29 somite stage onwards ( Figure 4 ) , indicative of an overall normalisation of spinal neural tube closure . The distribution of PNP lengths in embryos of the ct9E sub-strain was shifted towards smaller values , with a significantly lower mean PNP length . Moreover , only a few ct9E embryos showed very large PNPs , whereas a greater proportion of embryos had completed PNP closure by the 30–31 somite stage ( 8 of 30 compared with 1 out of 20 among the ct8E sub-strain; p<0 . 05 , z-test; Figure S3 ) . These observations on PNP length correlate with the diminished frequency of spina bifida in the ct9E sub-strain later in development . Generation of the curly tail sub-strains provided an opportunity to test directly whether the variation in number of Glu residues is responsible for the 2-DE migration difference of lamin B1 in curly tail and wild-type samples . 2D gels were generated from mouse strains expressing the Lmnb18E ( ct , ct8E , +8E ) or Lmnb19E ( +ct , ct9E ) variants . In each case the migration pattern corresponded with the number of Glu residues ( Figure S4 ) , confirming that the characteristic strain-dependent 2-DE pattern reflects the Lmnb1 polymorphism . We hypothesised that the mechanism by which variation in lamin B1 sequence affects risk of NTDs could relate to the apparent effect on stability of the nuclear lamina , as shown by FLIP . In order to further examine the effects of the lamin B1 variants , we examined nuclear morphology in MEFs derived from embryos of differing strains . We previously showed that Grhl3 is expressed in MEFs and that the expression deficit is observed in cells derived from curly tail embryos , as in the embryos themselves [41] . Immunostaining for lamin A and lamin B1 allowed visualisation of nuclear shape and , among curly tail MEFs , many nuclei showed a high degree of irregularity in shape , including herniations and/or lobulations ( Figure 5A ) . Moreover , in a proportion of curly tail cells , lamin B1 staining was discontinuous . Lamin A showed a similar distribution to lamin B1 , suggesting that the variant lamin B1 imposes a dysmorphic phenotype on the nuclear lamina as a whole . Abnormalities were much less frequent in nuclei of the +ct;9E and C57BL/6 strains , carrying wild-type alleles of Lmnb1 and Grhl3 . To provide a quantitative measure of nuclear morphology , the contour ratio ( 4 ? ? ? ×area/perimeter ) of DAPI-stained nuclei was analysed ( Figure 5B , 5C ) . The mean contour ratio was significantly lower for ct nuclei than for any of the other strains ( Figure 5B ) . Consistent with these findings , compared with other strains examined , a significantly greater proportion of ct nuclei showed a contour ratio of less than 0 . 7 ( Figure 5C ) , which is considered abnormal [42] . The curly tail nuclear dysmorphology phenotype was rescued by the presence of the Lmnb19E variant in the ct9E sub-strain ( Figure 5 ) , correlating with the apparent increased stability of the lamina when this variant is present , as observed by FLIP ( Figure 2C ) . Interestingly , in MEFs from a transgenic ct strain , ctTgGrhl3 in which Grhl3 expression is reinstated by over-expression from a Grhl3-containing BAC [9] , the nuclear morphology was intermediate between that of ct and ct9E MEFs ( Figure 5 ) . Thus , although ctTgGrhl3 mice are on an identical genetic background to ct , including the Lmnb18E variant , it appears that over-expression of Grhl3 is sufficient to partially ameliorate the nuclear dysmorphology phenotype . The mean contour ratio of nuclei was higher , and the proportion of abnormal nuclei was lower , for C57BL/6 than any of the other strains , including +ct;9E ( Figure 5 ) . Thus , in addition to lamin B1 sequence and Grhl3 expression , other factors associated with the curly tail genetic background may influence nuclear morphology . Overall , among strains with the curly tail genetic background , those that express the Lmnb19E variant ( +ct;9E and ct9E ) have a significantly higher mean contour ratio ( Figure 5B ) and fewer dysmorphic nuclei ( Figure 5C ) than those that express the Lmnb18E variant ( ct and ctTgGrhl3 ) . The effect of the Lmnb18E variant on nuclear morphology and the known function of lamins in nuclear function , including DNA replication [24] , prompted us to investigate the effect of the Glu variant on proliferative capacity in ct cells . MEFs were plated and counted after 4 hours ( t = 0 ) and after successive 24 hour periods up to 5 days . Growth curves showed that ct8E MEFs proliferate significantly more slowly than their ct9E counterparts over the first four days in culture ( p<0 . 05; Multiple linear regression , R2 = 0 . 948 ) and then undergo a ‘proliferative crisis’ where cell numbers cease to increase ( Figure 6A ) . The experiment was performed on three separate occasions using independent cell lines , with the same result each time . Therefore , in addition to nuclear dysmorphology , the Lmnb18E variant is associated with an apparent reduction in proliferative capacity in ct cells . In contrast , ct9E cells continued to proliferate at a similar rate to wild-type +8E cells at day 5 ( Figure 6A ) . In accordance with the growth curve data , we also noted that when MEFs were repeatedly passaged , ct8E fibroblasts show a dramatic loss of proliferative capacity from passage 5 onwards , whereas ct9E continue to exhibit similar doubling times up to at least passage 8 . To further investigate cell cycle properties of ct8E and ct9E cells , labelling with 5-ethynyl-2′-deoxyuridine ( EdU; to monitor S-phase progression ) and immunostaining for phospho-histone H3 ( pH 3; a marker of mitosis ) were performed on day 0 . This is well before the profound loss of proliferative capacity that occurs in ct8E cells after extended culture and it was therefore predicted that differences , if present , may be subtle . However , corresponding with growth curve data , we observed significantly fewer EdU-labelled ct8E cells than ct9E cells ( Figure 6B ) , together with a non-significant reduction in pH 3 labelling ( cells in G2/M phase ) and mitotic index . Consistent with the reduced EdU labelling in ct8E cells , indicating that fewer cells had passed through S-phase , we observed a slightly lower proportion of EdU/pH 3 double-labelled nuclei . However , there was no difference between strains in the number of double-labelled cells as a proportion of the total number of EdU-labelled cells ( Figure 6B ) , suggesting that progression from S-phase to G2 is not defective in ct8E cells . We next examined the expression of key regulators of cell cycle expression by qRT-PCR , 4 hours after plating ( t = 0 , as for cell cycle analysis ) and after 5 days of culture ( t = 5 ) . The reduced proliferative capacity of ct8E cells during the initial growth period was associated with significantly lower expression of Ccnd1 , encoding cyclin D1 ( Figure 6C ) . After 5 days , the expression of Ccna2 and Ccnb1 ( encoding cyclin A2 and cyclin B1 , respectively ) was also significantly reduced in ct8E compared with ct9E cells , consistent with diminished cell cycle progression [43] , [44] . Conversely , there was a dramatic increase in expression of p16Ink4a ( Figure 6C ) , which suppresses cell cycle progression through inhibition of cyclin D-dependent kinases [45] and is a hallmark of cells entering senescence . The expression of p16Ink4a was also increased in ct9E cells at t = 5 compared with t = 0 , but to a much lesser extent . In addition , at both stages ct8E cells also exhibited a significant reduction in expression of Smc2 , which encodes a core component of the condensin I and II complexes that play key roles in chromosome condensation during mitosis [46] , [47] . We conclude that changes in expression of cell cycle-associated proteins are consistent with reduced cell cycle progression in cells expressing the Lmnb18E variant , compared with those expressing the wild-type Lmnb19E variant . Finally , we tested whether the Lmnb1 variants were also associated with differences in cellular proliferation rate in the developing embryo . Analysis was performed on the neural folds and hindgut at the axial level of the closing PNP , at the stage at which the underlying defect in proliferation in the hindgut of affected curly tail embryos was reported [12] , [13] . Consistent with the findings in cultured cells , the EdU labelling index was lower in ct8E than in ct9E embryos , particularly in the hindgut ( Figure 6D , Table S3 ) . Mitotic index was similar in the sub-strains ( Table S3 ) . The diminished S-phase progression of cells in the hindgut of ct8E embryos corresponds with the proliferation defect that is known to underlie spinal NTDs in curly tail embryos .
The multifactorial , partially penetrant genetics of the curly tail mouse provided an opportunity to investigate the Lmnb1 polymorphism as a potential modifier of susceptibility to NTDs . In the context of the genetic background of the curly tail mouse , we observed a major effect of lamin B1 on development of the neural tube , the embryonic precursor of the brain and spinal cord . Curly tail sub-strains expressing the Lmnb18E variant demonstrate failure of neural tube closure with significantly higher frequency than those that express wild-type protein . Thus , although both the curly tail sub-strains ( ct9E and ct8E ) are homozygous for the Grhl3ct mutation , which results in diminished Grhl3 expression [9] , there is a three-fold difference in the frequency of NTDs depending on the co-existing Lmnb1 genotype . Strikingly , although exencephaly occurs at much lower frequency than spina bifida , Lmnb1 also affected the penetrance of these defects to a similar extent as spinal NTDs , with approximately 65% reduction in frequency among ct9E compared with ct8E embryos . Interestingly , it appears that the Lmnb18E variant may confer susceptibility to NTDs even in the absence of a Grhl3 mutation , at least in the context of the ct genetic background . Thus , +ct;8E embryos that are wild-type for Grhl3 but which carry the Lmnb18E variant developed occasional tail flexion defects and/or exencephaly . In contrast , spinal NTDs can be prevented by transgenic over-expression of Grhl3 expression ( ctTgGrhl3 ) [9] , despite the presence of the Lmnb18E variant . The possible functional effect of polymorphic variants has been explored in very few proteins , to date . We found that the loss of a single Glu , in Lmnb18E , compromises the stability of lamin B1's interaction within the nuclear lamina . This effect is predicted to result from disturbance of the conformation of the C-terminal region of the protein , owing to the location of the variant Glu residue in a predicted alpha-helix . The effect of the Glu repeat polymorphism on lamina stability in FLIP analysis correlates with the observation of a higher proportion of dysmorphic nuclei in ct MEFs that express the Lmnb18E variant compared with Lmnb19E . Abnormalities in lamin immunostaining and nuclear shape are reminiscent of cells with nuclear envelope abnormalities , such as from progeria models [42] , lamin B1 mutant mice [33] , [34] and following shRNA-mediated silencing of lamin B1 [48] . Using contour ratio analysis , abnormal nuclei were observed in around 47% of primary embryonic curly tail fibroblasts ( current study ) , compared with 68% of primary dermal fibroblasts derived from a patient with Hutchison-Gilford progeria syndrome [42] . Only 7–15% of nuclei among control fibroblasts exhibited such abnormalities . In these previously reported examples , abnormalities of cell proliferation , chromosome position , transcription factor localisation and gene expression have all been noted [22] , [26] , [33] . We found a strong correlation between frequency of dysmorphic nuclei in MEFs derived from embryos of the ct strain , and frequency of NTDs . For example , among mice homozygous for the Grhl3ct hypomorphic allele , presence of the wild-type Lmnb19E led to a reduced NTD frequency and an increased proportion of ‘normalised’ nuclei in MEFs . These findings suggest that nuclear lamina function plays a contributory role to the efficiency of neural tube closure during embryogenesis . Whether altered nuclear structure directly affects NTD risk or is a secondary marker of altered lamin B1 function is not known . To investigate the cellular mechanism by which lamin B1 affects embryonic development we focussed on a possible effect on cell cycle progression , in view of the known tissue-specific cell cycle defect that underlies spinal NTDs in curly tail mice [8] . Lamin B1 functions in nuclear envelope breakdown/assembly and mitotic spindle formation [23] , [25] , [49] . In addition , lamin B types are spatially associated with and required for DNA synthesis during S-phase [50] . Effects of lamin B1 dysfunction on cell cycle regulation could also be mediated through altered regulation of gene expression . For example , sequestration of the transcription factor Oct-1 at the nuclear periphery is lost in cells expressing a truncated form of lamin B1 , resulting in mis-expression of target genes , including cell cycle mediators [27] , [51] . In ct fibroblasts expressing the Lmnb18E variant , analysis of growth curves and cell cycle markers revealed diminished proliferative capacity and premature senescence , accompanied by characteristic changes in expression of cell cycle mediators . Cell labelling experiments suggest that the reduced proliferation rate of ct8E cells does not result from a defect at the S-phase/G2 transition but more likely from impairment of G1 or G1/S transition . Such an idea is consistent with the reduced expression of cyclin D1 , which promotes progression through G1/S . The proliferative crisis that occurs in ct8E following extended culture is accompanied by reduced expression of cyclins A2 and B1 , which function at G2/M [52] , and increased expression of p16Ink4a . Although our study addresses an amino acid change rather than reduced expression , these observations are consistent with recent studies showing that silencing of Lmnb1 expression reduces proliferation rate and induces premature senescence in fibroblast cell lines [53] . Altered cell cycle exit is also thought to be responsible for reduced thickness of the cortex in lmnb1/lmnb2 knockout embryos [29] , [34] . Rather than a generalised growth retarding effect of the lamin B1 variant , it appears that there is an additive effect with the Grhl3ct mutation . Cell cycle differences between ct8E and ct9E cells therefore suggest a mechanism by which Lmnb1 genotype affects the morphogenetic movements of neural tube closure in curly tail mutant embryos . It was previously found that: ( i ) the cellular basis of spinal NTDs in curly tail mutant embryos involves a proliferation defect in cells of the hindgut which causes excessive axial curvature [12]; and ( ii ) inhibition of proliferation by anti-mitotics or experimental growth retardation increases frequency of cranial NTDs [18] , [54] . Therefore , the reduction in cellular proliferation rate resulting from the combination of diminished Grhl3 expression together with perturbation of lamin B1 function , would be predicted to exacerbate both spinal and cranial neurulation , as we observe . In support of this model , and correlated with prevention of NTDs in embryos , reinstatement of Grhl3 expression in cultured cells that express the Lmnb18E variant partially normalises nuclear morphology ( e . g . in ctTgGrhl3 ) and proliferative capacity ( e . g . growth curves of +ct;8E and ct9E cells do not differ ) . Moreover , in vivo analysis confirmed that proliferation is diminished in the hindgut of ct8E compared with ct9E embryos , which suggests an explanation for their greater susceptibility to spinal NTDs . Overall , our findings show that Lmnb1 is a modifier gene that has a significant influence on the risk of NTDs in curly tail ( Grhl3ct ) embryos . We propose that the Lmnb18E polymorphism and Grhl3ct mutation interact genetically to influence nuclear morphology and proliferation , and hence susceptibility to NTDs . The influence of gene-gene interactions on susceptibility to NTDs in the curly tail model parallels the apparent multigenic etiology of the corresponding human conditions . Thus , it appears possible that some individuals carry ‘risk’ alleles that are insufficient to cause NTDs when present in isolation , but confer susceptibility to NTDs when co-inherited with other predisposing alleles . We speculate that variation in human lamin B1 , either in the Glu repeat or elsewhere in the protein , would be worthy of investigation in the context of human NTDs .
Curly tail ( ct/ct ) , genetically-matched ( partially congenic ) wild-type ( +ct/+ct ) and transgenic curly tail mice carrying a Grhl3-expressing BAC ( Grhl3ct/Grhl3;Tg ( Grhl3 ) 1NDEG , here referred to as ctTgGrhl3 ) were as described previously [8] , [9] . A two-step breeding programme ( Figure S2 ) was used to generate mice carrying different combinations of the Grhl3 alleles ( referred to as Grhl3+ or Grhl3ct ) and Lmnb1 variants ( referred to as Lmnb19E and Lmnb18E ) . Mice of genotype Grhl3ct/ct; Lmnb18E/8E , Grhl3ct/ct; Lmnb19E/9E and Grhl3+/+; Lmnb18E/8E were selected and inter-crossed to establish independent colonies . The Grhl3ct allele was genotyped on the basis of the putative mutation , C-21350T , upstream of Grhl3 by PCR amplification of genomic DNA with restriction digest of PCR products [9] . Genotyping was confirmed by PCR amplification of polymorphic microsatellite markers , D4Bwg1551e and D4Mit204 , downstream of Grhl3 . The Lmnb1 GAG repeat variant ( Deletion , 18: 56909394 ) was genotyped by PCR amplification of genomic DNA using primers that encompass the repeat ( 5′-GACCACCATACCCGAGGAG and 5′- TCCACAGCCACTCCGATG ) , with separation of products on 5% agarose gels . The C612T SNP ( 18: 56868078 ) creates a HindIII restriction site , allowing genotyping by PCR amplification of exon 1 ( using primer pair 5′-GGCCTGTGGTTTGTACCTTC-3′ and 5′-GGCACCCCTGTTCAGTTCTA-3′ ) , followed by restriction digest of the PCR product . Experimental litters were generated by timed matings . Pregnant females were killed at embryonic day by cervical dislocation and embryos were dissected from the uterus in Dulbecco's Modified Eagle's Medium ( Invitrogen ) containing 10% fetal calf serum ( Sigma ) . At E10 . 5 , the caudal regions of individual embryos at the 30–31 somite stage were excised at the level of somite 15 , rinsed in phosphate buffered saline ( PBS ) and stored at −80°C prior to analysis by 2-DE or Western blot . For in situ hybridisation embryos were fixed in 4% paraformaldehyde ( PFA ) in PBS at 4°C overnight . Animal studies were carried out under regulations of the Animals ( Scientific Procedures ) Act 1986 of the UK Government , and in according with guidance issued by the Medical Research Council , UK in Responsibility in the Use of Animals for Medical Research ( July 1993 ) . Samples , comprising whole embryos ( n = 10 of each genotype ) or individual caudal regions ( n = 10 of each genotype ) , were prepared by sonication in lysis buffer as described previously [55] . Proteins were separated by isoelectric focussing on pH gradients of pH 4–7 or 3–5 . 6 , followed by SDS-PAGE on 12% polyacrylamide gels , as described [56] . Gels were fixed and stained using PlusOne silver stain ( GE Healthcare ) and scanned using a GS-800 calibrated densitometer ( BioRad ) . Gel images were analysed using Progenesis SameSpots ( Non-linear Dynamics ) with separate between-genotype comparisons for whole embryos ( n = 5 pH 4–7 and 5 pH 3–5 . 6 gels for each genotype ) and caudal regions ( n = 5 pH 4–7 and 5 pH 3–5 . 6 gels for each genotype ) . Protein spots were excised manually from a minimum of four different gels , so that each spot was analyzed at least in quadruplicate , subjected to in-gel digestion with trypsin and analyzed by LC-ESI-MS/MS ( QToF-micro; Waters Corp . ) as described previously [55] . Mass spectrometry data were searched against the SwissProt database using the MASCOT search algorithm ( Matrix Science , London , UK ) . One missed cleavage per peptide was allowed . Genomic DNA fragments spanning exons of Lmnb1 were amplified by PCR ( see Table S4 for primer sequences ) . Purified PCR products were sequenced using big dye terminator chemistry ( Applied Biosystems ) and analysed on a MegaBACE 1000 ( Amersham ) . Sequence reads derived from both strands were assembled , aligned and analysed for nucleotide differences using Sequencher ( GeneCodes ) . Protein lysates ( 1 µg per lane ) in RIPA buffer were run on 10% Bis-Tris gels ( NuPage , Invitrogen ) and transferred to PVDF membrane ( XCell II Blot Module , Invitrogen ) . Immunodetection was performed by standard methodology using antibodies to lamin B1 ( S-20 ) and β-tubulin for normalisation ( primary antibodies from Santa Cruz Biotechnology and used at 1∶1000 ) . Proteins were detected using horseradish peroxidise-conjugated secondary antibodies ( DAKO ) , followed by development with ECL plus Western blotting detection system ( GE Healthcare ) . Films were scanned on a GS-800 Densitometer ( Bio-Rad ) for quantification . RNA was purified ( TRIzol Reagent , Invitrogen ) from isolated caudal regions of E10 . 5 embryos or from MEFs , genomic DNA removed by DNase I digestion ( DNA-free , Ambion ) and first strand cDNA synthesis carried out ( SuperScript II , Invitrogen ) . qRT-PCR was performed ( MESA Blue Mastermix for SYBR Assay , Eurogentec ) on a 7500 Fast Real Time PCR system ( Applied Biosystems ) , with each sample analysed in triplicate . Primers for Lmnb1 were designed to amplify a 221 bp product ( nucleotides 1267–1487 of coding sequence ( Ensembl NM 010721 . 1; ENSMUSG00000024590 ) . Additional primer pairs were: cyclin A2 ( Ccna2 ) 5′-CATGTCACTGCTGGTCCTTC and 5′- TGATTCAAAACTGCCATCCA ) ; cyclin B1 ( Ccnb1 ) 5′-GGAAATTCTTGACAACGGTG and 5′-TGCCTTTGTCACGGCCTTAG; Cyclin D1 ( Ccnd1 ) 5′-GCGTACCCTGACACCAATCT and 5′-CTCTTCGCACTTCTGCTCCT; Smc2 5′-AAATAGCCGCCCAGAAAACT and 5′-GAGCGTTCCTTGGTGTCTTC . Primers for p16Ink4a were described previously [27] . Results were normalized to Gapdh as described previously [9] . For microarray , RNA was further purified using the RNeasy Micro Kit ( Qiagen ) , followed by cDNA synthesis , linear amplification and labelling of cRNA using GeneChip 3′IVT Express Kit ( Affymetrix ) . RNA and cRNA quantity and quality were determined by Nanodrop spectrophotometer and Bioanalyser 2100 ( Agilent ) . Affymetrix Mouse 430_2 arrays were hybridised as standard ( www . affymetrix . co . uk ) . Files were processed in GeneSpring GX ( Agilent Technologies ) , with application of GC-RMA normalisation and Benjamimi-Hochberg multiple testing correction . Whole-mount in situ hybridisation , was performed as described previously [9] , using a digoxygenin-labelled 561 bp cRNA probe which was complementary to nucleotides 726–1286 of the Lmnb1 transcript/coding sequence . Embryos were embedded in gelatine-albumin and sectioned at 50 µm thickness on a vibratome . Constructs were generated in pcDNA3 . 1 vector by standard cloning methods , to express fusion proteins composed of a nuclear localisation signal , yellow fluorescent protein and full-length lamin B1 or C-terminal region . Plasmids were transfected into MEFs and FLIP was performed as described previously [51] . In brief , a region of interest ( ROI ) was photobleached at full laser power while scanning at 4% laser power elsewhere . For quantitative analysis , background intensity was subtracted , and intensities of a specific ROI outside the photobleached area were measured over time and normalized using intensities of an ROI in a transfected but non-bleached cell . MEFs , derived from pools of 3–6 embryos at E13 . 5 , were fixed in 4% PFA in PBS for 10 min , permeabilized with 0 . 4% Triton X-100 in PBS for 5 min , and blocked with 0 . 4% fish skin gelatine in PBS for 30 min at room temperature . Incubations with primary and secondary antibodies were for 1 h each at room temperature . Primary antibodies were mouse anti-lamin B1 ( 8D1; [57] and rabbit anti-lamin A ( ab26300: Abcam ) . Secondary antibodies were donkey anti–mouse and anti–rabbit ( Jackson ImmunoResearch Laboratories ) conjugated to Alexa Fluor 488 and Cy5 respectively . Imaging was performed using a confocal microscope ( LSM 510 META; Carl Zeiss , Inc . ) on an Axio Imager . Z1 ( Carl Zeiss , Inc . ) with a 63× NA 1 . 4 oil immersion objective lens . Laser lines used were 405 nm , 488 nm and 633 nm to excite DAPI , Alexa Fluor 488 and Cy5 , respectively . Fluorescence was detected using the following filters: base pairs 420–480 , base pairs 505–530 and long pass 650 . Images were analyzed using MetaMorph ( MDS Analytical Technologies ) or Image Browser ( Carl Zeiss , Inc . ) software . MEFs were plated onto 13 mm cover slips ( passage 3; 1 . 0×105 cells per well in triplicate ) , cultured for 5 hours prior to addition of 10 µM EdU ( Invitrogen ) . After 1 hour cells were fixed and processed for detection of EdU ( Click-It EdU Imaging Kit ) . Cells were then washed in 0 . 1% Triton-X100 in PBS and blocked for 30 min ( 5% heat-inactivated goat serum , PBS-0 . 1% Triton , 0 . 15% glycine , 2 mg/ml BSA ) prior to immunohistochemistry for phospho-histone H3 . Primary and secondary antibodies were anti-phospho histone H3 ( 1∶250 , Millipore ) and Alexa Fluor 488-conjugated anti-rabbit ( 1∶500 , Invitrogen ) . For nuclear staining , cells were incubated with Hoechst ( 1∶2 , 000 in PBS ) . Ten random fields were analysed per cover slip using Image J software ( U . S . National Institutes of Health , Bethesda , Maryland , USA ) . Cells in mitosis were scored by visual inspection of pH 3-positive cells . The experiment was repeated three times , each using an independent cell line . For in vivo proliferation analysis , mice were injected with 150 µg EdU at E10 . 5 . Embryos were collected after 90 minutes , fixed in 4% PFA and processed for embedding in paraffin wax . Transverse 7 µm sections at the axial level of the closing neural folds were used for proliferation analysis ( 5–7 sections per embryo ) , as described previously [12] . Detection of EdU ( Click-It EdU Imaging Kit ) was followed by immunohistochemistry for phospho-histone H3 ( as above ) as described [13] . Fluorescent images were collected on an Axiophot microscope ( Zeiss ) with a DC500 camera ( Leica ) , using FireCam software ( Leica ) . Images were analysed using the Cell Counter plugin in Image J . All statistical analysis was carried out using SigmaStat ( version 3 . 5; Systat Software Inc ) . | Failure of early development of the central nervous system leads to severe malformations termed neural tube defects ( NTDs ) , including spina bifida and anencephaly . Inherited genetic risk factors play a major role in determining susceptibility to NTDs , but causative genes have proven difficult to identify . In this study we investigated genetic factors that could alter the risk of NTDs in an established mouse model , curly tail , in which defects result from partial loss of function of the grainyhead-like-3 ( Grhl3 ) gene . We identified a variant of lamin B1 , a key protein component of the envelope that surrounds the cell nucleus . The protein alteration reduces the structural integrity of the nuclear envelope , causes the nuclei to have altered shape , and reduces the rate of cell division . Curly tail embryos that carry the “abnormal” lamin B1 variant develop NTDs at three times the rate of those that carry the normal version . We conclude that lamin B1 function influences risk of NTDs due to effects on cell proliferation . | [
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... | 2012 | Lamin B1 Polymorphism Influences Morphology of the Nuclear Envelope, Cell Cycle Progression, and Risk of Neural Tube Defects in Mice |
Viruses are known to employ different strategies to manipulate the major histocompatibility ( MHC ) class I antigen presentation pathway to avoid recognition of the infected host cell by the immune system . However , viral control of antigen presentation via the processes that supply and select antigenic peptide precursors is yet relatively unknown . The Epstein-Barr virus ( EBV ) -encoded EBNA1 is expressed in all EBV-infected cells , but the immune system fails to detect and destroy EBV-carrying host cells . This immune evasion has been attributed to the capacity of a Gly-Ala repeat ( GAr ) within EBNA1 to inhibit MHC class I restricted antigen presentation . Here we demonstrate that suppression of mRNA translation initiation by the GAr in cis is sufficient and necessary to prevent presentation of antigenic peptides from mRNAs to which it is fused . Furthermore , we demonstrate a direct correlation between the rate of translation initiation and MHC class I antigen presentation from a certain mRNA . These results support the idea that mRNAs , and not the encoded full length proteins , are used for MHC class I restricted immune surveillance . This offers an additional view on the role of virus-mediated control of mRNA translation initiation and of the mechanisms that control MHC class I restricted antigen presentation in general .
Presentation of antigenic peptides on major histocompatibility ( MHC ) class I molecules is a signal for CD8+ T cells to distinguish between cells that express self or non-self antigens and forms an important part of the immune system's capacity to fight parasite invasion . There are several steps that endogenous peptides pass from their synthesis to the loading onto the MHC class I molecule . On one hand , the digestion of the peptide precursor by the proteasome [1] , [2] , [3] , the affinity of the peptide for the TAP transporter [4] , the trimming of the N-terminus by endopeptidases [5] and the sequence requirements of the peptide to fit the grove on the MHC class I molecules [6] , are all important steps in determining the efficiency of peptide presentation . On the other hand , the steps prior to the digestion of the peptide precursor by the proteasome , the so called pre-proteasomal steps , have to ensure that enough peptide material is produced so that a sufficient amount of the correct peptide epitopes reaches the class I molecules in order to trigger a T cell response . It has been estimated that approximately 104–105 MHC class I molecules are expressed by individual cells at any time to ensure a sufficient antigen presentation . Proteins and polypeptides exhibit a wide range of half-life , with an overall average of 1 to 2 days [7] . As the stability of viral proteins is many times high , it would take many hours for the cells to accumulate a sufficient amount of viral peptides to trigger the most efficient T-cell response if these were derived from the degradation of the full length protein . To explain the rapidity of viral-antigen presentation , a model has been proposed in which a fraction of rapidly degraded mRNA translation products ( RDPs ) [8] or defective ribosomal products ( DRiPs ) [9] with a half-life of less than 10 minutes constitute the main source for antigenic peptides . This model has been supported by the rapid slow down of TAP system by blocking protein synthesis and the equal rapid suppression of antigen presentation when transcription of an mRNA encoding a protein with a long half life is shut off [10] . In addition , cryptic mRNA translation products derived from different reading frames throughout the message can provide substrates for the MHC class I pathway [11] . The use of alternative translation products as a source for antigenic peptides , together with the fact that continues ribosomal activity is required for antigen presentation , implicates mRNA translation as an important pre-proteasomal step in regulating MHC class I restricted antigen presentation . However , the translation mechanisms that govern the synthesis of antigenic peptide products are unknown . Viruses adapt to their environment and manipulate their host cells in order to serve their needs . Controlling the MHC class I antigen presentation pathway is an important target for latent viruses in order to avoid detection of the infected host cell by the immune system . There are many examples of different strategies whereby viral products target the MHC class I pathway on the post-proteasomal level [12] , [13] but there is so far little known about how viruses affect the steps that control the production of antigenic peptides . The Epstein-Barr virus ( EBV ) expresses the nuclear antigen-1 ( EBNA1 ) in all types of infected cells and in its type I latent form , e . g . observed in Burkitt's lymphoma , it is the only viral antigen detected [14] . A Glycine-Alanine repeat sequence ( GAr ) located in the N-terminal part of EBNA1 with no apparent biochemical function has a cis-acting capacity to suppress presentation of antigenic peptides to the MHC class I pathway and plays an important role for the EBV to evade immune detection [15] , [16] . Like EBNA1 , Kaposi's sarcoma-associated herpesvirus LANA1 protein and the MHV-68 gamma herpes virus ORF73 are latent origin binding proteins that act for maintaining viral episomes in infected cells . These two proteins have more recently been suggested to use a similar strategy , but with different sequences , as EBNA1 to escape the MHC class I pathway [17] , [18] , indicating that this might be a more commonly used concept among viruses to evade the immune system . It was recently shown that the nascent GAr peptide targets the initiation step of translation of any mRNA to which it is fused [19] . Here we have used GAr-mediated control of mRNA translation initiation to study its effect on MHC class I restricted antigen presentation . By manipulating the GAr sequence we can control the rate of translation initiation of a reporter mRNA in cis and we can thereby demonstrate that the rate of translation initiation , as opposed to other means of translation control , directly determines the amount of presented peptides derived from the main open reading frame as well as from cryptic translation products of a given mRNA . We discuss how these results fit together with the concept of EBNA1 as an immunologically silent protein and the proposed models for the source of antigenic peptide material for the MHC class I pathway .
The Gly-Ala repeat sequence ( GAr ) of EBNA1 can prevent mRNA translation initiation and MHC class I restricted antigen presentation from open reading frames ( ORF ) to which it is fused [19] , [20] . To test to which degree the GAr is responsible for the suppression of EBNA1 antigen presentation we fused the SIINFEKL encoding antigenic peptide sequence ( SL8 ) derived from chicken Ovalbumin ( Ova ) [21] , [22] into the EBNA1 ( EBNA1-SL8 ) or in an EBNA1 in which the Gly-Ala repeat ( GAr ) was deleted ( EBNA1ΔGA-SL8 ) ( Fig . 1A ) . This allowed us to monitor any effect the GAr has on antigen presentation from these mRNAs using the B3Z CD8+ T hybridoma that is specific for the SL8 in the context of H-2Kb MHC class I molecules [23] . H-2Kb EL4 cells expressing Ova or EBNA1ΔGA-SL8 gave a similar level of presentation of the SL8 epitope , demonstrating that there is no significant difference in how this antigen is processed and presented between these two constructs . However , presentation of SL8 in the context of EBNA1 was dramatically suppressed and comparable to cells expressing an empty vector ( Fig . 1B , left graph ) . Similar results were obtained using the H1299 human cell line in which a vector coding the mouse H-2Kb MHC class I molecule was cotransfected together with the expression vectors for Ova , EBNA1-SL8 or EBNA1ΔGA-SL8 respectively ( Fig . 1B , right graph ) . To test how this difference in antigen presentation correlates with GAr's inhibitory effect on protein synthesis , H1299 cells expressing each construct were pulsed for 1 h in the presence of 35S-methionine and proteasome inhibitor in order to minimize any effects of proteasomal degradation before harvested . This revealed that EBNA1-SL8 is translated with approximately 60% reduced efficiency as compared to the EBNA1ΔGA-SL8 ( Fig . 1C ) . Western blot analysis showed that the steady state protein expressions of the respective proteins correlate with their respective rate of synthesis ( Fig . 1D ) . Similar results in terms of control of synthesis and antigen presentation were also obtained when the GAr sequence was fused to the N-terminus of Ova itself . Fusion of the full length GAr to the N-terminus of ovalbumin ( GAr-Ova ) effectively prevents the presentation of the SL8 peptide over a wide range of mRNA concentrations and eight times the amount of a GAr-Ova cDNA was required to reach the same level of antigen presentation as from cells expressing Ova alone ( Fig . 1E , left panel ) . To ensure that the antigen presentation reporter system was not saturated under these conditions we increased the number of Ova expressing EL4 cells that were exposed to the same fixed number ( 5×104 ) of B3Z cells used in the above experiments ( Fig . 1E , right panel ) . These results , together with previous reports , collectively support the notion that the GAr domain alone inhibits presentation of peptides to the MHC class I pathway from the EBNA1 or from any mRNA to which it is fused , irrespectively of location [19] , [20] . It is known that the GAr in addition to preventing translation initiation also has the capacity to inhibit protein unfolding and proteasome-mediated degradation in a substrate- and position-dependent fashion [24] . In order to investigate if the capacity of the GAr to affect protein stability plays a role in its capacity to provide immune evasion we separated its two functions . The SL8 was inserted in the 3′ untranslated region ( UTR ) of the GAr sequence , either in the same or in a different reading frame ( GAr-1 and GAr-2 , respectively ) where it is expressed as a cryptic minigene [25] , [26] . Thus , any effect the GAr has on antigen presentation from these mRNAs can be separated from its capacity to inhibit proteasomal degradation since the GAr and the SL8 epitope are expressed as separate polypeptides . We also fused the SL8 peptide in frame with the C-terminus of the GAr ( GAr-3 ) ( Fig . 2A ) . In addition , we made the corresponding constructs where we exchanged the GAr sequence for that of the GFP ( GFP-1 , GFP-2 and GFP-3 respectively ) ( Fig . 2A ) . The GFP is a suitable replacement for the GAr as it is also a protein with a low turnover rate , a poor substrate for the proteasomes [27] and , importantly , the levels of mRNAs expressing the SL8 are similar in the context of either ORF ( Fig . 2B ) . These different constructs allowed us to compare the effect of the GAr on suppressing MHC class I antigen presentation independently of its capacity to influence protein degradation . The level of presentation of SL8 from the GFP-3 is similar to that from Ova itself , demonstrating that there is no significant difference in how the antigen is processed in these two settings . However , presentation of the SL8 in the context of all GAr-carrying mRNAs is suppressed as compared with the corresponding GFP constructs , demonstrating that the GAr prevents mRNA antigen presentation throughout the entire mRNA ( Fig . 2C ) . The GFP-1 and GFP-2 constructs give a lower level of presentation of the SL8 compared to when fused to the C-terminus of GFP ( GFP-3 ) ( Fig . 2C ) . This is explained by the fact that the antigenic peptide in GFP-1 and 2 are expressed as cryptic translation products compared with when it is fused to the main reading frame in GFP-3 and Ova . To ensure that the expression of SL8 from the GFP-2 and GAr-2 minigene constructs are indeed derived from an initiation event and not from a read-through from the main ORF we substituted the AUG codon with GGC or GCC . As this completely prevented antigen expression from either constructs it shows that the expression of the SL8 is not due to a read-through event and , thus , that the GAr suppresses a reinitiating event ( Fig . 2D ) . Western blot analysis confirms that the expression levels from the main ORF of the different constructs are similar ( Fig . 2E ) . The notion that SL8 expressed from the 3′UTR is derived from an independent initiation event is further supported by treating cells with IFNγ . IFNγ stimulates the induction of immunoproteasomes and N-terminal trimming peptidases that together give a more efficient processing of peptides longer than 8–10 residues for loading onto MHC class I molecules [28] , [29] . IFNγ treatment does not affect presentation of the SL8 when inserted in the 3′UTR , which is what is expected if it is expressed as a minigene , and only when fused directly to the C-terminus of GFP or GAr ( Fig . 2F , left panel ) . By treating cells with the proteasome inhibitor epoxomicin we observed that that presentation of SL8 is proteasome-dependent when derived from Ova , or fused to GFP , but not when translated as an out-of-frame minigene downstream of GFP ( GFP-1 &-2 ) ( Fig . 2F , right panel ) or GAr ( GAr-1 &-2 ) ( data not shown ) . These results show that the cryptic translated SL8 peptides are derived from independent translation initiation and do not carry additional residues from the main upstream reading frame that could interfere with the processing of the MHC class I peptide . Taken together , these results show that the GAr suppresses the presentation of the SL8 epitope within the same reading frame and out-of-frame epitopes . Hence , the GAr suppresses MHC class I restricted antigen presentation by preventing translation initiation throughout the entire mRNA and its potential capacity to control protein stability is not required to impose immune evasion . The nascent GAr peptide is regulating the synthesis of EBNA1 by directly blocking initiation of the EBNA1 mRNA translation in cis which is caused by a delay in the assembly of the initiation complex [19] . The molecular target of the GAr is not yet known but we have observed that insertion of the c-myc IRES [30] in the 5′UTR of GAr-Ova ( c-myc-GAr-Ova ) overrides GAr-dependent inhibition of protein synthesis and restores the rate of expression to approximately 70% of that of Ova alone ( Figs . 3A and 3B , left panel ) . Similarly , the c-myc IRES also induced the expression of the GAr alone approximately 3-fold , demonstrating that this effect is restricted to the GAr itself ( Fig . 3B , right panel ) . The c-myc IRES has no effect on the rate of Ova synthesis when inserted in an identical way in the 5′UTR ( Fig . 3B , left panel ) , indicating its specific effect on GAr-mediated translation control . Moreover , the c-myc IRES and the GAr domain only affect mRNA translation in cis as we do not see any changes on the rate of translation of actin or of the exogenous GFP ( Fig . 3C ) . Thus , the combination of the GAr and the c-myc IRES provides us with tools with which we can study the relationship between the rate of mRNA translation initiation and the production of antigenic peptides from a single mRNA without targeting protein synthesis or degradation using general chemical inhibitors . When we tested the effect of the c-myc IRES on GAr-dependent control of antigen presentation we observed a 70% presentation of SL8 , as compared to Ova alone or c-myc-Ova ( Fig . 3D ) . Under the same conditions the presentation of SL8 from the GAr-Ova fusion construct was approximately 5-fold less . As the c-myc IRES does not affect the GAr-Ova ORF this result further underlines that the potential effect of the GAr to control the stability of the protein to which it is fused is not sufficient to suppress antigen presentation . Insertion of the c-myc IRES in the 5′UTR of the GAr-2 mRNAs also resulted in a sharp increase in antigen presentation , demonstrating that the same mechanism of translation initiation control that regulates the production of antigenic peptides derived from the main ORF also regulates the production peptides derived from cryptic minigenes . The capacity of the c-myc IRES to neutralise the translation inhibitory effect of the GAr is cell specific and was observed in three out of three human cell lines tested ( Table 1 ) . However , it has been shown that the efficiency of the c-myc IRES-driven translation varies between cell lines from different origins . In murine cell lines the c-myc IRES-driven translation is much lower than in human cell lines and importantly it has been shown to be inactive in murine adult tissue [31] , [32] . This explains the finding that the c-myc IRES was incapable to override the translation inhibitory effect of the GAr in all the murine cell lines tested ( Table 1 ) . The c-myc IRES has been characterised and consists of different domains and predicted ribosome entry window ( Figs . 4A and 4B ) . It has been shown that deletion of the domain 1 reduces its activity with about 60% [33] . In line with this , fusion of a c-myc IRES , that lacks domain 1 ( Δcmyc-IRES ) , in the 5′UTR of Ova-GAr results in a reduced capacity to override suppression of translation and antigen presentation ( Fig . 4C ) . This further links the effect of the c-myc IRES and its capacity to overcome GAr-dependent suppression with its capacity to control mRNA translation initiation ( Fig . 4C ) . These results show that GAr-mediated suppression of translation initiation is sufficient and necessary to prevent antigen presentation from the main ORF as well as from cryptic translation products and that its effect can be neutralised by alternative mechanisms of initiation provided by the c-myc IRES . The observations that the increase in rate of synthesis after insertion of the c-myc-IRES corresponds to antigen presentation indicates a close correlation between the rate of mRNA translation initiation and the capacity of CD8+ T cells to detect and destroy virus-infected host cells . In order to look more closely at this relationship , we wanted to change the rate of Ova synthesis more subtly compared with the “on/off” effect obtained with the c-myc-IRES and we used mutated GAr sequences that have been shown to affect the synthesis of GAr fusion proteins . The lymphocrypto-Papio and the Rhesus viruses infect Old World primates and express EBNA1 homologues that carry shorter GAr-like sequences that have previously been shown not to prevent antigen presentation [34] . The EBV-GAr sequence consists of single alanine residues separated by one , two or three glycines while the Papio-GAr carries single serine residues inserted in every seven residues of the repeat ( Fig . 5A and [19] ) . When we fused a 30 amino acid Papio-GAr sequence ( 30GAr-Papio-Ova ) and a corresponding 30 amino acid EBV-GAr sequence ( 30GAr-EBV-Ova ) to the N-terminus of Ova we observed that the Papio-GAr-like sequence had no effect on mRNA translation or antigen presentation while insertion of the corresponding EBV-GAr sequence resulted in an approximately 4-fold less synthesis and antigen presentation ( Figs . 5B and 5C ) . Similar results were also obtained with the Rhesus GAr-like sequence which also carries serine insertions ( data not shown ) . Interestingly , the Papio-GAr has the capacity to control protein stability and fusion of the Papio-GAr to the p53 protein , which is normally targeted for the ubiquitin-dependent degradation pathway by the MDM2 E3 ligase , resulted in a stabilisation and in an accumulation of polyubiquitinated 30GAr-Papio-p53 products in the presence of MDM2 ( Fig . 5D ) . This indicates that while the Papio sequence retains the effect on proteins stability , the disruption of its GAr sequence is sufficient to render it inefficient in preventing antigen presentation or protein synthesis control [24] . We next tested a construct in which the GAr repeat had been disrupted by inserting two alanines next to each other on three locations ( 32GAr3A-Ova ) ( Fig . 5E ) . This retains the GC rich content of the GAr RNA sequence without introducing new amino acid residues . In this case , the rate of synthesis was approximately 50% less compared with Ova alone but over two-fold more efficient than that of the wild type GAr ( 30GAr-EBV-Ova ) ( Fig . 5F , left panel ) . If two glycine residues were instead replaced by serines ( 31GAr2S-Ova ) we obtained a 75% translation efficiency as compared to Ova alone . When we next compared the effects of these GAr sequences on antigen presentation we observed that the rate of mRNA translation initiation is closely followed by the amount of antigens presented to the MHC class I molecules ( Fig . 5F , right panel ) . Taken together , these results indicate a direct and proportional relationship between endogenous antigen presentation and mRNA translation initiation control .
Our results further underline the notion that the capacity of EBNA1 to evade the MHC class I antigen presentation pathway and the detection by CD8+ T cells relies on the Glycine-Alanine repeat ( GAr ) sequence [15] , [16] , [20] , [35] . Deletion of the GAr sequence from EBNA1-SL8 resulted in the same amount of antigen presentation as when SL8 was presented from the Ova message indicating that no other regions of EBNA1 are needed to evade MHC class I antigen presentation . Dose-response experiments show that this effect is not dependent on the amount of mRNA expressed in the cells and that at least eight times the amount of a GAr-carrying mRNA is required in order to reach a similar level of antigen presentation as that of a corresponding non-GAr carrying mRNA . The GAr has the unique dual capacity to suppress both its own mRNA translation initiation as well as the stability of proteins to which it is fused . By separating these two functions from each other we have shown that the GAr suppresses peptide production from different reading frames of an mRNA to which it is fused and , hence , that control of mRNA translation initiation is both sufficient and necessary for its capacity to suppress MHC class I antigen presentation ( Fig . 6 ) . Previous studies have shown that the GAr can prevent unfolding of substrates targeted for the 26S proteasome by affecting 19S-dependent unfolding in a substrate and position-dependent fashion . However , the GAr has no , or little , effect on the stability of EBNA1 itself , suggesting that fusion of GAr to 26S proteasome substrates gives unspecific effects on protein stability that are unlikely to play any physiological role for the virus [24] . These observations together with our results instead support a model in which the cis-mediated effect of the GAr on EBNA1 mRNA translation initiation is the sole mechanism by which EBNA1-expressing latently EBV-infected cells can evade recognition by the immune system . However , this does not mean that EBNA1 stability is not an important feature in EBV's strategy to evade the immune system for the simple reason that a low rate of EBNA1 synthesis requires a low turnover rate in order to allow a sufficient amount of EBNA1 to be expressed ( Fig . 6 ) . The expression of EBNA1 in the host resting B memory cells , as compared to rapidly proliferating BL cells , is likely less , which could further contribute to help the virus to establish an immune evasive latency . Several results lead us to propose that control of initiation of mRNA translation , and not prevention of elongation , is the key feature for the GAr domain in controlling MHC class I antigen presentation . Firstly , the insertion of the c-myc IRES in the 5′UTR of GAr-carrying mRNAs prevents the GAr from suppressing mRNA translation and antigen presentation . It is unlikely that the insertion of an IRES in the 5′UTR without any changes to the main reading frame could impose differences in GAr-dependent control of synthesis other than via altering the initiation conditions . This is further supported by the observations that deletion of the domain 1 of the c-myc IRES prevents its effect on overcoming the GAr and its cell line-dependent mode of action . This might also indicate that the target factor of the GAr is independently recruited to the polysome by domain I and could further help to elucidate the mechanisms of GAr action on translation initiation . Secondly , the GAr-like sequence derived from the Papio virus , where a single serine residue is inserted at every seven amino acids , has little effect on the rate of protein synthesis or on antigen presentation . Furthermore , by inserting three alanines into the EBV-GAr sequence we retain the GC rich mRNA sequence but increase synthesis and antigen presentation . Finally , the GAr suppresses presentation of antigenic peptides that are derived from independent translation initiation events in the 3′UTR of the GAr-encoding reading frame . The latter type of translation initiation of cryptic minigenes was shown by the group of Shastri to be sufficient to provide antigenic peptides for the MHC class I pathway [25] . It is difficult to see how pre-termination of the translation due to difficulties for the ribosome in reading through the GC rich region could explain suppression of independent down-stream initiation events [36] . In addition , truncated EBNA1 peptides due to failure of elongation are not observed in EBV infected cells . Taken together , neither of the observations presented here are likely to occur if the GAr acts via mechanisms related to elongation , including difficult ribosomal read-through , codon exhaustion , or other more specific mechanisms [36] , [37] . Previous studies have shown that changes to the GAr peptide sequence , but not RNA sequence impair its efficiency to suppress translation [19] , underlining that the effect is mediated by the peptide , and not the RNA sequence . The GAr is predicted to be unstructured and does not included charged residues and , as expected , a 30 amino acid GAr peptide was found not to bind the EBNA1 mRNA ( [20] and data not shown ) . However , a recent report suggests that the Gly-Arg repeat of EBNA1 has RNA binding capacity [38] . Blocking translation initiation offers an explanation to how the GAr can succeed in suppressing production of DRiPs/RDPs and thus antigenic peptides derived from initiation events from all reading frames throughout the mRNA . Based on the model that antigenic peptides are not derived from degradation of full length proteins it should not be possible for the GAr to avoid presentation of peptides derived from EBNA1 by controlling its turnover rate since this would only affect peptides derived from the full length EBNA1 and not DRiPs [39] or RDP products that do not carry the GAr . Our previous work and toeprint analysis carried out by others indicate that the GAr peptide has to be synthesised in order to suppress mRNA translation initiation and that it does not affect the site of initiation [19] , [36] . This is line with the notion that the GAr would not give rise to truncated EBNA1 peptides due to alternative initiation sites or diffuse pre-termination events that would not serve the function of the protein and thereby not support viral replication , nor prevent presentation of upstream antigenic peptides , but to an overall suppression of translation in cis . In fact , using GAr specific polyclonal sera one does not see any massive accumulation of truncated EBNA1 products in normal EBV-infected cells that would have been expected from a pre-termination event derived from within the GAr sequence . One question that arises from this study is if this mechanism of evading the immune system is efficient , it should be adapted by other viruses . It has recently been suggested that the MHV-68 gamma herpes virus ORF73 is using a similar mechanism as EBNA1 to evade MHC class I restricted antigen presentation . In this case , however , the sequence is not identical to the GAr , suggesting that other amino acid sequences can achieve a similar effect [17] . The LANA-1 of Kaposi's sarcoma virus is also believed to use a similar mechanism but with a different repeat sequence [18] . Hence , several viruses might use a similar concept but different sequences . This makes it more difficult to predict how wide spread this type of mRNA translation control is among viruses but it indicates that the strategy to escape the MHC class I pathway by manipulating mRNA translation initiation applies to several viruses and is not restricted to the EBV . The GAr acts in cis and offers a unique opportunity to study the relationship between antigen presentation , protein stability and mRNA translation without the addition of general chemical inhibitors of protein synthesis or degradation that might have indirect or unspecific effects . By making minimal changes to the GAr amino acid sequence we have shown that we can fine tune translation initiation of the mRNAs and , as far as we are aware , there are no other systems described that allow this . The GAr consists of single alanines disrupted by one , two or three glycines . Disruption of the GAr by two alanines next to each other on three locations is sufficient to reduce the translation and antigen presentation inhibitory effect of 30 amino acids GAr sequence by approximately 50% . Introduction of two serines on two locations has a more disruptive effect and reduces its effect with approximately 75% . This demonstrates a close correlation between the rate of mRNA translation initiation and MHC class I restricted antigen presentation that has consequences for understanding the source of antigenic peptides for the MHC class I pathway . These results are in line with other studies suggesting that protein stability does not affect antigen presentation [40] and indicates that a fundamental part of the immune system's capacity to detect virus-infected host cells is reliant on the mechanism of viral mRNA translation , as opposed to any features linked to the actual viral proteins . This supports the notion that MHC class I restricted immune surveillance is in fact directly correlated with the mechanisms that regulate protein synthesis and not protein degradation and supports the model where it is in fact the presence of mRNA , and not the full length proteins , that is surveilled by the MHC class I pathway [41] . This opens up for novel ways of interpreting viral control of mRNA translation and new approaches for therapeutic intervention aimed at virus associated diseases . These results also have broader implications in the understanding of the peptide selection process and will allow the prediction of antigenic peptide production from specific mRNAs that has implications for generating more efficient DNA vaccines and potentially also for better understanding of dysregulated antigen presentation in autoimmune disease and the generation of self tolerance .
The murine lymphoma cell line EL4 ( H-2Kb ) and B3Z cell line were maintained in complete medium , consisting of RPMI-1640 medium supplemented with 10% heat-inactivated fetal calf serum ( FCS ) , 25 mM Hepes-buffer solution ( Gibco-BRL , Santa Clara , CA ) , 100 IU/ml penicillin and streptomycin ( Gibco-BRL ) , 2 mM L-glutamine ( Gibco-BRL ) , 2 mM sodium pyruvate solution ( Gibco-BRL ) , 2 mM non-essential amino acid solution ( Gibco-BRL ) , and 0 . 5 µM of 2-β mercaptoethanol ( 2-βME ) ( Sigma-Aldrich , St . Louis , MO ) . Transient transfections of EL4 cells were performed by electroporation using a BMX pulser Bio-Rad Gene Pulser II ( Bio Rad , Hercules , CA ) at 260 mV in a 0 . 4 cm Bio-Rad electroporation cuvette . EL4 cells were washed once in washing medium , consisting of RPMI medium 1640 supplemented with 2% heat-inactivated fetal calf serum ( FCS ) , 25 mM Hepes-buffer solution ( Gibco-BRL ) , 100 units/ml penicillin , and and 100 µg/ml streptomycin ( Gibco-BRL ) , 2 mM L-glutamine ( Gibco-BRL ) , 2 mM sodium pyruvate solution ( Gibco-BRL ) , 2 mM non-essential amino acid solution ( Gibco-BRL ) , and 0 . 5 µM of 2-βME ( Sigma Chemical ) . The cells were then suspended in complete medium at a concentration of 7 . 5×106/ml . 8 µg of plasmid were inoculated with 3×106 cells in the electroporation cuvette . Immediately after electroporation , the cells were transferred to a 6-well plate with 3 ml of complete media . Human cell lines were cultivated under standard conditions in RPMI medium 1640 ( H1299 and Saos-2 ) , each containing 10% FCS , 2 mM L-glutamine , 100 units/ml penicillin , and 100 µg/ml streptomycin . Cells were seeded in 6-well plates at a density of 1 . 75×105 cells/well . The following day the cells were cotransfected with 1 µg total of expression plasmids along with 3 µl of Genejuice according to the manufacturer's protocol ( Merck Biosciences , Darmstadt , Germany ) . Following separation on 12% SDS-PAGE , proteins were transferred to 0 . 45 µm nitrocellulose membranes , and blots were blocked for 1 hour at room temperature with a 5% skim milk in TBS solution consisting of 20 mM Tris , 500 mM NaCl , 0 . 1% Tween 20 , pH 7 . 5 . Blots were incubated overnight at 4°C with anti-EBNA1 mouse monoclonal antibody ( OT1X ) ( 1∶1000 ) or polyclonal anti-GA antibody ( 1∶500 ) , raised against the Gly-Ala sequence of EBNA1 protein or a monoclonal actin antibody ( 1∶1000 ) Chemicon International ( Temecula , CA ) or anti-p53 rabbit polyclonal antibody ( CM-1 ) . The membranes were washed before incubated with horseradish peroxidase-conjugated rabbit anti-mouse or mouse anti-rabbit immunoglobulin antibody ( 1∶5000 ) for another 1 h and detected using ECL ( Amersham Bioscience ) . The ECL signal was quantified using CCD camera and associated software ( Vilber Lourimat , France ) . Pre-stained molecular markers were from Fermenta ( Ontario , Canada ) . All plasmids were generated using standard procedures . Restriction enzymes , T4 DNA ligase and calf intestinal alkaline phosphatase were obtained from New England Biolabs ( Ipswich , MA ) . Purified synthetic oligonucleotides were obtained either from MWG biotech ( Ebersberg , Germany ) or Eurogentec . Routine plasmid maintenance was carried out in DH5α and TOP10 bacteria strains . The EBNA1 and EBNA1ΔGA were generated using oligonucleotide pairs 5′AGTATAATCAACTTTGAAAAACTCTGAGAAG3′ and 5′CTTCTCAGAGTTTTTCAAAGTTGATTATACT3′ , encoding the SL8 peptide , inserted into the unique Bstx1 site found in EBNA1 sequence , right after the GAr sequence . The GFP-1 construct was prepared using oligonucleotide pairs 5′AATTCTGAATGAGTATAATCAACTTTGAAAAACTCTGAT3′ and 5′CTAGATCAGAGTTTTTCAAAGTTGATTATACTCATTCAG3′ , encoding the SL8 peptide , inserted into the EcoR1/Xba1 sites of EGFP-C2 vector ( BD Biosciences Clontech , Palo Alto , CA ) . The GAr-1 construct was made using the same oligonucleotide pairs inserted in the 3′UTR of the GAr , itself cloned into the pCDNA-3 vector ( Invitrogen , Carlsbad , CA ) . The GFP-2 and GAr-2 constructs were made in the same way using the oligonucleotide pairs 5′AATTCCTGAATGAGTATAATCAACTTTGAAAAACTCTGAT3′ and 5′CTAGATCAGAGTTTTTCAAAGTTGATTATACTCATTCAGG3′ . The different GAr-2 constructs were prepared by mutating the AUG codon in GCC or GGC using standard procedures . The GFP-3 and GAr-3 constructs were prepared using the oligonucleotide pairs 5′AATTCAGTATAATCAACTTTGAAAAACTCTGAT3′and 5′CTAGATCAGAGTTTTTCAAAGTTGATTATACTG3′ and inserted in the same vectors . The c-myc IRES cDNA was obtained from Dr . A . C . Prats ( INSERM U589 , France ) . The pCDNA3-Ova and pCDNA3-GAr-Ova constructs were obtained as described previously [20] . c-myc-Ova , c-myc-GAr-Ova and c-myc-GAr-2 were generated by amplification of full length human c-myc IRES by polymerase chain reaction ( PCR ) , using a 5′ sense primer containing a BamH1 site 5′CGGATCCACTAGAACTCGCTGTAGTAATTC3′ and a 3′ antisense primer 5′TCCGGATCCGCGGGAGGCTGCTGG 3′ containing another BamH1 site . The fragment was cloned into the 5′UTR digested pCDNA3-Ova , pCDNA3-GAr-Ova and pCDNA3-GAr-2 constructs . The 30GAr-EBV-Ova construct was made by replacing the full-length GAr sequence in the Gar-Ova construct with an oligonucleotide sequences corresponding to 30 amino acids of the GAr . The same approach was used to produce 32GAr3A-Ova , 31GAr2S-Ova and 30GAr-Papio-Ova . All mRNA translation assays were carried out in H1299 cells transfected with indicated constructs . Transfected cells were cultured for 36 hours before treated with 20 µM MG132 for one hour in methionine free medium containing 2% dialysed FCS . 0 . 15 mCi/ml of [35S] methionine ( Perkin Elmer , Boston , USA ) was added in the presence of proteasome inhibitor and the cells were harvested at indicated time points using a rubber policeman after 2x washing in cold PBS . Cell pellets were snap frozen at −80°C before lysed in PBS containing 1% NP40 and Complete protease inhibitor cocktail ( Roche Diagnostics GmbH , Mannheim , Germany ) at 4°C . Lysates were centrifuged for 15 minutes at 14 . 000 rpm and pre-cleared by addition of mouse sera and protein G sepharose . An equal amount of total protein was incubated with specific antibodies for 4 hours at 4°C before the immune complexes were recovered using protein G sepharose . The proteins were separated on precast Bis-Tris 4–12% SDS-PAGE ( Invitrogen ) and the amount of labelled protein was visualized by autoradiography and the relative amount of protein synthesis was determined using phosphoimager . EL4-Kb restricted cells ( 5×104 ) expressing the indicated constructs for 48 h were washed in medium and cultured with 5×104 B3Z T cell hybridoma for at least 20 h in 96-well plates . T cell assays in human H1299 cell lines were done by co-transfecting the Kb expression vector together with the reporter construct . The B3Z CD8+ T cell hybridoma expresses LacZ in response to activation of T cell receptors specific for the SIINFEKL peptide ( OVA-immunodominant peptide ) in the context of H-2Kb MHC class I molecules . The cells were then harvested and washed 2 times with 1X cold PBS prior to lysis in 0 . 2% TritonX-100 , 0 . 5M K2HPO4 , 0 . 5M KH2PO4 for 5 min on ice . The lysates were centrifuged for 10 min and 25 µl of supernatant from each well were transferred into 96-well optiplate counting plates ( Packard Bioscience , Randburg , SA ) . The plates were incubated for 1 hour at room temperature , protected from light and tested for β-Galactosidase activity using the Luminescence assay ( BD Biosciences Clontech ) on a FLUOstar OPTIMA ( BMG LABTECH Gmbh , Offenburg , Germany ) . The results were expressed in counts per seconds ( CPS ) or in relative light units ( RLU ) . The peptides SIINFEKL ( corresponding to ovalbumin amino acids 258–276 ) was purchased from Eurogentec ( Seraing , Belgium ) . Total RNA was isolated from EL4 cells . After separation on agarose gels , the RNA was transferred to nylon filter ( Hybond-N+; Amersham Bioscience ) . An oligonucleotide probe corresponding to the SIINFEKL sequence was previously labelled with [32P]ATP using the Ready-to-Go kit ( Amersham Bioscience ) . After baking the membrane at 80°C for 2 h , the RNA was hybridized overnight with the probe at 42°C in PerfectHyb Hybridization Solution ( TOYOBO , Tokyo , Japan ) . The membranes were washed twice for 5 min in 1× sodium chloride/sodium citrate ( SSC : 0 . 15 M NaCl , 15 mM sodium citrate , pH 7 . 0 ) that contained 0 . 1% SDS at room temperature and twice for 1 h in 1×SSC that contained 0 . 1% SDS at 55°C . The RNA was visualized by autoradiography . | The presentation of short peptides on major histocompatibility ( MHC ) class I molecules forms the cornerstone for which the immune system tells apart self from non-self . It is important for viruses such as the Epstein-Barr virus ( EBV ) to avoid this antigen presentation pathway in order to escape recognition and killing of its host cells . All EBV-infected cells , including cancer cells , express EBNA1 without attracting the attention of the immune system . In this report we describe the mechanism by which EBNA1 escapes antigen presentation . This should open up for new approaches to target EBV-associated diseases including cancers and immuno proliferative disorders and for understanding the underlying mechanisms of the source and regulation of antigenic peptide production . | [
"Abstract",
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] | [
"immunology/antigen",
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] | 2010 | Epstein Barr Virus-Encoded EBNA1 Interference with MHC Class I Antigen Presentation Reveals a Close Correlation between mRNA Translation Initiation and Antigen Presentation |
Neural stem cells ( NSCs ) are progenitor cells for brain development , where cellular spatial composition ( cytoarchitecture ) and dynamics are hypothesized to be linked to critical NSC capabilities . However , understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo . Here , we study NSC dynamics within Neural Rosettes—highly organized multicellular structures derived from human pluripotent stem cells . Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration ( INM ) —a hallmark of cortical radial glial cell development . We developed a quantitative live imaging framework to characterize INM dynamics within rosettes . We first show that the tendency of cells to follow the INM orientation—a phenomenon we referred to as radial organization , is associated with rosette size , presumably via mechanical constraints of the confining structure . Second , early forming rosettes , which are abundant with founder NSCs and correspond to the early proliferative developing cortex , show fast motions and enhanced radial organization . In contrast , later derived rosettes , which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons , and thus correspond to neurogenesis mode in the developing cortex , exhibit slower motions and decreased radial organization . Third , later derived rosettes are characterized by temporal instability in INM measures , in agreement with progressive loss in rosette integrity at later developmental stages . Finally , molecular perturbations of INM by inhibition of ACTIN or NON-MUSCLE MYOSIN-II ( NMII ) reduced INM measures . Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies , drug screening , and iPS cell-based platforms for disease modeling .
Neural stem cells ( NSCs ) are neural progenitor cells within the nervous system that are defined by their ability to self-replicate while retaining potential for generating neurons and glia [1–3] . During nervous system development , early emerging NSCs first undergo successive symmetric cell divisions that generate additional progenitor cells , resulting in expansion of the NSC pool . This phase is then followed by asymmetric cell divisions that generate a progenitor cell and a terminally differentiated cell such as a neuron or a glial cell , resulting in decreased NSC ratios [4] ( for review see Ref . [5] ) . Together , these mechanisms are fundamental for the generation of distinct types of NSCs to account for cellular diversity of the nervous system . Much progress has been made towards understanding the factors that regulate the self-replication or differentiation of NSCs both in vivo and in vitro [6 , 7] . One predominantly exciting but less understood aspect of stem cell biology is how the cytoarchitecture of the developing brain is linked to maintenance of NSC number and developmental potential . Particularly interesting is the nuclei dynamics within neuroepithelial cells and radial glial cells—the NSCs that build the cortex . These are elongated cells harboring distant apical and a basal processes that connect the two walls of the developing neural vesicles . Structurally , this layer of NSCs is pseudostratified; i . e . , although several layers of nuclei are apparent between vesicle walls , the cytoplasm of each cell extends to contact both apical and basal surfaces of the wall , resulting in a bipolar cellular morphology that is much longer then the thickness of a single cell . Interkinetic nuclear migration ( INM ) is the process by which nuclei migrate between apical and basal ends of these pseudostratified neuroepithelial cells , in coupling with cell division at the apical surface . INM was first suggested by Sauer [8] , further confirmed experimentally [9–11] and later suggested as a mechanism to ensure maintenance of sufficient NSC pools throughout embryonic neocortical development [12] . Thus , it is hypothesized that INM spatial composition and dynamics reflect critical abilities of NSCs during self-renewal and differentiation . Time-lapse microscopy of mouse and human cortical slices excised from brain and grown in vitro has confirmed INM as a live dynamic process [13] and provided initial clues on mechanisms and functions . Specifically , a correlation between INM and cell cycle was established [14 , 15] and variations between apical vs . basal INM speed as well as motion patterns were shown in vivo [16] . INM dynamics is fascinating also because the pseudostratification of neuroepithelial cells entails high cellular traffic due to accommodation of many moving nuclei within a limited space . It was suggested that unsynchronized INM may serve as a mechanism to maximize probability of cell division at apical sites and consequent exposure to Notch signaling activation within these sites , which in turn promote maintenance of NSC fate following cell division [12] . Yet , very little is known regarding specifics of INM dynamics , reflecting the technical challenge to image and quantify multiple cells in vivo at high resolution and high content . Therefore , two components are needed in order to advance the field: ( 1 ) an in vitro model system that is physiologically relevant and reflects dynamics similar to those observed in vivo , ( 2 ) quantitative readouts for cell dynamics in such a system . Here we used neural rosettes as an in vitro model to explore INM dynamics with relation to NSC maintenance . Neural rosettes are highly organized structures that appear in culture following differentiation of human pluripotent stem cells into cortical lineages . Neural rosettes contain NSCs resembling neuroepithelial and radial glial cells of the developing cortex that are radially organized to create a lumen , resembling the structure of the ventricular zone of the developing cortex . Initial characterization of neural rosettes revealed strong apicobasal cell polarity with the organization of apical ends surrounding a lumen [17] . Joining apical ends at rosette lumens also coincide with mitosis in these luminal regions [17 , 18] , in accordance to INM observations in vivo [19] . We recently dissected the entire cortical differentiation process—from neuroepithelial cells towards distinct radial glial cell types . Specifically , we identified two rosette stages in culture corresponding to two developmentally distinct types of radial glial cells [20] . Early radial glial ( E-RG ) rosettes ( day 14 in culture ) contain highly proliferative NSCs exhibiting broad differentiation potential and minimal differentiation propensity in culture [20] . As cultures proceed in vitro , E-RG rosettes progress into a stage termed Mid radial glial ( M-RG ) rosettes ( day 35 in culture ) , which is characterized by decreased NSC numbers and increased propensity to differentiate into neurons . Further culture of M-RG rosettes ( beyond day 55 ) ultimately results in loss of rosette integrity , a further reduction in NSC numbers , and transition of fate potential from neuronal towards glial bias [20] . We further comprehensively dissected the regulatory networks that drive differentiation from pluripotent stem cells to E-RG and then to M-RG rosettes by employing extensive transcriptional and epigenetic characterization coupled with computational analysis [21] . Together , these findings propose a functional link between cortical development , NSC capacity maintenance and neural rosettes formation and disassembly . Thus , we hypothesized that INM dynamics within neural rosettes may predict NSC capacity of the developing cortex . Here , we developed quantitative live imaging to characterize cellular dynamics within rosette structures , and investigated these kinetic properties during transition across developmentally distinct rosettes and following molecular perturbations . We devised three main readouts associated with INM to capture different aspects of cell dynamics that relate to migration orientation and speed . We further applied these measures to reveal inherent and stage-dependent observations that distinguish E-RG from M-RG rosettes . Finally , we were also able to detect and quantify reduction in cellular organized dynamic performance following specific inhibition of molecular motors involved in INM . Thus , our quantitative approach delineates a model that describes intrinsic dynamic features within rosettes and suggests for the first time a functional link between rosette dynamics and NSC competence . Hence , the presented kinetic quantitative readouts have the potential to serve for functional molecular studies drug screening , and may be implicated to gain novel insights into biology of NSCs in health and disease .
We used the HES5::eGFP Notch activation reporter human embryonic stem cell ( hESC ) line , expressing cytoplasmic GFP in Notch active cells [22] . HES5 is a major and direct downstream target of Notch activation pathway ( for review , see Ref . [23] ) and specifically marks NSCs in vivo . We recently showed that neural rosettes correspond to NSCs of the developing cortex based on their strong apico-basal epithelial polarity and the expression of cortex associated genes such as PAX6 together with the NSC marker HES5::eGFP [20] ( Fig 1A ) . When newly formed E-RG rosettes appear in culture on day 14 , most rosette cells express the cortical marker PAX6 and the NSC marker HES5::eGFP ( Fig 1A , middle panel ) ( >80%; see Ref . [20] ) in accordance with their high proliferative capacity and lack of differentiation in culture . In contrast , continued culture of E-RG rosettes results in their progression towards M-RG rosettes around day 35 , and this is marked by significant loss in the NSC marker HES5::eGFP and the cortical marker PAX6 in rosette cells ( Fig 1A , bottom panel ) ( <30%; see Ref . [20] ) . Importantly , PAX6 expression is now limited only to the regions adjacent to rosette lumens , reflecting the limited area where stem cells reside at that stage . Since the ability of neural progenitors to radially organize in rosettes is correlated with increased ratios of polarized epithelial NSCs [17 , 18 , 20] , we hypothesized that this difference in NSC numbers among early and advanced rosettes would be phenotypically reflected in rosette dynamics , specifically that of INM . Subjective live imaging observations suggested that both E-RG and M-RG rosettes exhibit INM characteristics , and this was even apparent in matching phase contrast images ( S1 and S3 Movies; compare to non-rosettes , S2 Movie; phase contrast time lapses immediately follow GFP time lapses in each movie ) . To quantitatively validate the observed INM motility-patterns , we devised an automated objective framework to assess rosettes dynamics . The analysis was based on manual annotation of rosette contours and centers from the phase-contrast channel , where the cytoarchitecture outlines of the region performing INM become obvious to a human eye based on different texture-patterns in the image ( Figs 1B , right panels and S1A; See Methods ) . Rosette outlines remained stable in the culture dish and did not change throughout the experiment ( S1B Fig ) . Rosette areas were discretized to sub-cellular patches ( S2A Fig; See Methods ) and local cross-correlation was applied to estimate motion for each patch at each time point [24] , similarly to particle image velocimetry ( PIV ) [25 , 26] . This approach was validated as highly correlative to manual single-cell tracking ( S2B Fig ) . Motions were exceptionally fast ranging up to 120μm hr-1 ( S2C Fig ) , and only motions of 15μm hr-1 or faster ( ≥ 2 pixels per time-lapse frame ) were considered for further analysis . We first estimated the average velocity orientation for each of the coordinates within each rosette over the entire time course ( Fig 1C , left panels ) . Indeed , migration pattern followed the expected radial angle , as defined by orientation of each patch’s velocity relatively to the rosette center , i . e . , the expected velocity direction assuming apico-basal radial motion ( See schematics in Fig 1E ) . This pattern was also reflected by the normal distributions observed for motion angles grouped by their expected radial angle ( S2D Fig ) . As expected , this pattern did not occur for cells in non-rosette areas that were adjacent to rosettes ( Fig 1C , right panels ) . More quantitatively , we calculated the distribution of the angular alignment γ between the observed velocities and their respective expected radial angles ( See schematics in Fig 1E ) to validate a dramatic bias of the angular alignment distribution toward structured motion ( Fig 1D , compare E-RG Rosettes , left , to Non-rosettes , right ) . Strikingly , this dynamics was even obvious also when computing motions based on the phase contrast channel , further confirming that rosettes indeed perform radial migration ( Fig 1B–1D , left , compare GFP columns to Phase columns ) . These observations indicate that motion within rosettes resemble in vivo INM [8 , 27] and suggest that radial migration within rosettes in vitro plays a functional role in the maintenance of NSCs . Based on our initial observations we devised three objective measures to study cell dynamics in rosettes to enable functional quantification . Each measure was defined as a scalar readout per rosette that quantifies different aspects in its dynamics throughout time . The first measure , Radial Score ( RS ) , was defined as the average angular alignment ( γ ) of all motions in each rosette over the entire time course ( Fig 2A ) . RS quantifies the mean alignment between observed and expected radial angles . Thus , lower scores correspond to better alignment , reflecting a more organized radial migration ( denoted radial organization henceforth ) . The second measure , Basal to Apical ratio ( B/A ratio ) , was defined as the ratio between the number of basal ( distal ) motions to apical ( luminal ) motions within rosettes along the entire time course ( Fig 2B ) . RS and B/A ratio were designed to quantify INM in vitro , which corresponds to the basal to apical migration observed for the developing neuroepithelium in vivo [16 , 19] . The third measure , Speed was defined as the average magnitude of velocity for all patches across time ( Fig 2C ) , a measure that was quantified in vivo [16 , 19] . When calculated for each time frame over time , these three measures fluctuated around a mean value , validating that the progressive rosette-disassembly in culture is much slower than the four hour imaging course ( S2E Fig ) , thus allowing us to focus on the mean measures as our readouts . Based on our observations ( Fig 1 ) , we hypothesized that these quantitative measures could reveal inherent biophysical properties of neural rosettes and their associations . These measures may also enable to functionally distinguish between INM performance capacity of E-RG and M-RG rosettes , and further test the hypothesis that the INM of M-RG rosettes is compromised and reflects the beginning of rosette disassembly , in line with the increase in cells with non-epithelial character [17 , 18 , 20] . 25 E-RG rosettes and 14 M-RG rosettes were imaged and quantified to test our hypotheses as detailed next . We hypothesized that larger rosettes are characterized by enhanced structured motion , as a response to increased mechanical constraints by the rosette cytoarchitecture . To test this , we examined the association between RS and rosette size . This property was first examined for E-RG rosettes , speculated to have a more structured dynamics compared to the more advanced M-RG rosettes . Indeed , RS of E-RG rosettes was found to be associated with rosette size ( Fig 3A ) , indicating that larger rosettes exhibit enhanced radial migration . Similarly to E-RG rosettes , RS of M-RG rosettes was also found to be associated to rosette size ( Fig 3A ) , suggesting that the association between rosette size and RS is an intrinsic property . This result also implies that the robustness of INM is augmented when larger numbers of nuclei move together towards apical or basal sites , as previously suggested for INM in pseudostratified neuroepithelial cells in vivo [12] . A similar model works also in other studies of collective cell migration showing enhanced group coordinated motility correlated with group size [28–32] . We therefore suggest that the confined structures of larger rosettes lead to more mechanical constraints that explain the increased radial organization of larger rosettes . Next , we tested whether M-RG rosettes differ in their radial migration dynamics compared to E-RG rosettes . We found that RS of M-RG rosettes were larger ( less organized ) than the expected size-dependent values derived from the E-RG’s linear model ( Fig 3A , most M-RG rosettes above the line and Fig 3B , quantitatively ) . We conclude that rosette size plays a prominent role with linear effect on radial migration and that RS can serve as a functional predictive measure for NSC capacity within rosettes . Previous in vivo studies have shown differences in speed between nuclei migrating apically and basally [16 , 33] . We hypothesized that radial organization may also differ between apical and basal motion . To test this hypothesis we classified each motion vector as moving apically ( inward ) or basally ( outward ) with respect to rosette center , reflective of apical and basal nuclei migration during INM , and examined apical and basal motion independently . We partitioned the motion vectors of each rosette into basal and apical groups and calculated each group’s RS . We found that similarly to general RS , basal or apical RS were associated with rosette size ( Fig 4A ) . However , basal motion tends to be more radially organized ( i . e . , lower RS ) than apical motion ( Fig 4B , most points above the y = x line ) , regardless of rosette stage ( Fig 4B ) or size ( Fig 4A , basal RS tends to be lower than apical RS for all rosette sizes ) . This was also judged by the basal RS values for M-RG rosettes , which were higher ( less organized ) than the basal RS values predicted by the linear fit of E-RG rosettes ( Fig 4C ) . These results led to the hypothesis that enhanced radial organization of basal motions contributes to the overall elevated radial organization observed for E-RG rosettes . B/A ratio was hypothesized as a secondary mechanism for the elevated radial organization of E-RG rosettes , by enhancing the contribution of the more radially organized basal motions in a size-independent mechanism ( S3 Fig , S1 Note ) . The measures RS and B/A ratio were calculated based on the orientation of the velocity vectors . Next we considered the speed—the magnitude of these vectors—as a third measure for rosette dynamics ( See Fig 2 ) . We found a two fold increase in the fraction of cells moving at speed of 15 μm hr-1 or faster in E-RG rosettes compared to M-RG rosettes ( Fig 5A ) . This strikingly fits our recent findings according to which there are twice as much NSCs ( i . e . , GFP+ cells ) in E-RG rosettes compared to M-RG rosettes [20] , further drawing a correlation between the actual number of NSCs measured within rosette cultures and the computed quantification of their INM motions . In contrast to RS , rosette speed was not correlated to rosette size ( S4 Fig ) , suggesting that molecular motors driving nuclei motions are less affected by the rosette confining structure . When considering apical and basal motions independently , we found that apical motion was consistently faster than basal motion in a striking linear relation , and with higher speed for E-RG rosettes ( Fig 5B ) . Higher apical ( vs . basal ) nuclear migration speeds were previously reported in time-lapse ex vivo cultured embryonic cortical slices [16] as well as in vivo in zebrafish retina and brain [33] , providing further validation to our quantitative approach as an in vitro platform for investigating INM . Direct comparison further revealed an ordered relation for rosette speed as follows: apical speed of E-RG rosettes > basal speed of E-RG rosettes > apical speed of M-RG rosettes > basal speed of M-RG rosettes ( Fig 5C ) . Inclusively , these data suggest that during early human cortical development , high NSC numbers are accompanied by elevated INM speed towards apical sites , similar to as shown for radial glial cells in cultured cortical slices ex vivo [16] . Our observations indicate that rosettes are generally characterized by basal motions that are slower but more radially organized , while apical motions are relatively faster yet less organized . Also , E-RG rosettes display elevated radial organization and higher speeds in general , for both basal and apical motions , compared to M-RG rosettes ( Fig 5B and 5C ) . These two observations ( fast & less organized versus fast & more organized ) seem , at first , conflicting , but they are reconciled by the notion that E-RG rosettes exhibit high performance for both basal and apical motions to be faster ( Fig 5C ) as well as more organized ( Fig 3B ) than M-RG rosettes . This is while keeping in proportion the inherent hierarchy of basal motions that are generally slower and more organized , compared to apical motions , which are generally faster and less organized , in a rosette stage independent manner . Altogether , these findings also suggest that more than a single mechanism is involved in linking speed to radial organization of INM . We noticed that all measures follow a spatial pattern . It is apparent that inner cells at the center of a rosette exhibit reduced organization , low B/A ratios and slower motion than cells located elsewhere ( Fig 2 ) . To understand the spatial dynamics distribution along the entire rosette area , we defined five circular rings with equal width ( i . e . , width is rosette size-dependent ) for each rosette , starting from rosette center and outwards , and quantified measures for each ring . We found that luminal and peripheral rings exhibited reduced radial organization , B/A ratio and speed , while peak levels were recorded within intermediate rings ( S5 Fig ) . This observation was more prominently expressed for E-RG rosettes . The poor performance of cells in distal rings of M-RG rosettes support a model where distal cells in M-RG rosettes “suffer” from mixed populations comprised of more differentiated cells that have detached the lumen ( apical sites ) towards periphery ( Fig 1A , bottom panel; Ref . [20] ) and thus should reduce organized motion . The reduced dynamics and the broader cellular heterogeneity of M-RG rosettes suggest that these rosettes are mechanically compromised , reflecting the progressive disassembly of rosettes , which culminates around day 55 [20] . We therefore tested whether rosette disassembly is reflected functionally in INM measures also at the shorter range of time , i . e . throughout the time-lapse experiment . This was quantified by calculating each measure for each rosette at every time point independently and then recording its temporal variance ( Methods ) . Importantly , no temporal trend was observed during the 4-hour imaging course of an experiment ( S2E Fig ) . This implies that the variance encodes the fluctuations in a certain rosette measure over the imaging time course , a measure we term functional instability . Indeed , temporal variance of RS , B/A and speed was significantly higher for M-RG rosettes ( Fig 6 ) , suggesting functional instability as an indicator for the stage of progression in rosette disassembly . Importantly , these high temporal variances observed for M-RG rosettes measure their reduced ability in consistently performing INM , arguably due to their compromised structure . They do not measure the actual rosette disassembly process , which occurs in a longer time scale ( from day 14 to day 35 , and culminating towards day 55 ) . Taken together , our results validate functional instability as a reliable readout for rosette organized dynamics . Finally , to further strengthen the validity of our method and to shed some light on mechanisms of INM in vitro , we quantified the effects of pharmacological perturbation on INM . Different molecular motors are thought to mediate nuclei migration [12 , 34] . Such motors are believed to be a part of the cytoskeletal structural machinery such as actin , or motor proteins such as NMII , both shown to be involved in INM movements [35] . We treated rosettes with Blebbistatin or Cytochalasin-B , two agents known to alter INM by inhibiting NMII ATPase activity or depolymerizing actin , respectively . Quantifying INM dynamics in these rosettes following live imaging ( S4–S6 Movies ) showed decrease in INM measures ( Fig 7A ) . This was further supported by demonstrating a loss of the ordered spatial composition of cell cycle components within rosettes . This was judged by immunostaining for mitosis ( PHH3 ) and DNA synthesis ( BrdU ) –two distinct phases in the cell cycle that are spatially distributed to lumen and periphery , respectively ( Fig 7B ) ( See also Ref . [20] ) . These findings further validate the ability of our quantitative approach to distinguish between rosettes under different molecular perturbations and further provide new evidence for possible roles of these molecular motors in driving INM in human radial glial cells .
Neural rosettes are highly organized multi-cellular structures that are formed by NSCs and are a cytoarchitectural hallmark during the transition of pluripotent stem cells into cortical fates in vitro . Here , we provided some initial insights and possible mechanisms for the complex dynamics of these structures , implicating intrinsic size-dependency of radial organization driven by mechanical constraints , inherently elevated radial organization for E-RG rosettes , and enrichment of basal motions as yet another potential contributor to enhanced and more stable INM dynamics of E-RG rosettes . We propose three quantitative measures as means to quantify rosette dynamics: RS , B/A ratio and speed . These measures were used to assess differences in dynamics between early ( E-RG ) and late ( M-RG ) rosettes , revealing that INM of early rosettes is more efficient . This may well reflect the situation in the developing cortex: E-RG rosettes correspond to symmetrically dividing NSCs during early cortical development [20] , which exhibit high self-replication rates and low levels of differentiation , resulting in increased number of cells undergoing INM within the ventricular zone . This implies that radial glial cells during early cortical development hold inherently elevated radial organization that may be required for accommodating the high traffic and orchestrating cell motion and cell division . In this regard , the radial expansion of the ventricular zone , which can be mirrored in vitro by the emergence of larger rosettes , may add greater mechanical constrains that ultimately contribute as well to enhance radial organization . At more advanced stages of cortical development , which are reflected by the M-RG stage in vitro [20] , the production of neurons and intermediate progenitors—both non-polarized cells—is prevalent due to increase in asymmetric cell division of the corresponding radial glial cells . This occurs on the expanse of polarized NSCs adjacent to apical sites , which still perform INM . Thus , the accumulation of differentiated progeny increases non-NSC ratios , which in turn disrupt radial organization performance ( Fig 8 ) . To conclude , our analyses provide a first link between function and dynamics . Literature survey demonstrated notable similarity between speeds measured across different labeling methods , in different species , in vivo and in vitro . Tsai et al ( Ref . [16] ) used cytoplasmic GFP for INM quantification of radial glial cells in mouse cortical slices ex vivo and shows higher speeds for apically directed motions ( up to a 60μm/hour ) compared to basally directed motions ( up to 30 μm/hour ) . An in vivo study in zebra fish ( Ref . [33] ) shows comparable results using the more classic nuclei labeling , with speed of up to 20μm/hour and 3 . 4μm/hour for apical and basal motions , respectively . Similarly , although to a different extent , our in vitro findings show that human E-RG rosettes corresponding to early developing cortical radial glial cells exhibit faster speed for apical motions ( 38 . 8μm/hour ) compared to speed of basal motions ( 35 . 3μm/hour ) , while the more advanced M-RG rosettes corresponding to mid neurogenesis moved apically at 30 . 3μm/hour and basally at 27 . 1μm/hour . This agreement is served as additional means to increase our confidence of using neural rosettes as physiologically relevant in vitro model system for cortical expansion as well as validating the capabilities of our analysis to quantify this process . Our encouraging results suggest that this analytical framework may enable high-content quantification for diagnosis , molecular investigation and drug screening . Recent advancements in the stem cell field allow obtaining skin biopsies from patients and convert them into pluripotent stem cells ( induced pluripotent stem cells ( iPS cells ) ) [36] . Such iPS cells can be derived from patients with cortical diseases and then re-directed from the pluripotent stage into neural rosettes . We envisage that applying these quantitative measures on rosettes derived from patient iPS cells will have the potential to reflect damaged or genetic mutation-affected properties of NSCs . In addition , the effects of a specific drug / molecular perturbation could be predicted based on its alternation on these measures . Thus , this could be the first step toward developing platforms for understanding rosette dynamics in health and disease .
We used the human embryonic stem cell line WA-09 ( H9 ) purchased from WiCell . Tel Aviv University Ethics Committee ( IRB ) approved the usage of existing human embryonic stem cell lines including H9 . Material transfer agreement ( MTS ) was signed between Tel Aviv University ( Vice President for R&D ) and WiCell with regard to the transfer and usage of the human ES cell line WA09 in the Elkabetz lab , and following Agreement Letter between the Principal Investigator and WiCell . The use of human embryonic stem cells for therapeutic research is allowed in Israel . For more details see text on "The Use of Embryonic Stem Cells for Therapeutic Research" , available at http://bioethics . academy . ac . il/english/report1/report1-e . html . The human ES cell ( hESC ) line H9 ( WA-09; Wicell—Wisconsin ) and the H9-derived BAC transgenic HES5::eGFP line [22] were cultured on mitotically inactivated mouse embryonic fibroblasts ( MEFs ) ( Globalstem ) . Undifferentiated hESCs were maintained as described previously [17] in medium containing DMEM/F12 , 20% KSR , 1mM Glutamine , 1% Penicillin/Streptomycin , non-essential amino acids and beta-mercaptoethanol . Experiments were performed as described in Refs . [20 , 21] . For neural induction and generation of neuroepithelial and radial glial cells , hESC colonies were removed from MEFs by Dispase ( 6U/ml , Worthington ) , dissociated with Accutase ( Innovative Cell Technologies , Inc . ) , plated at sub confluent cell density ( 40-50K cells/cm2 , although twice higher density or alternatively small hESC clusters work well and accelerate confluence ) on Matrigel ( 1:20 , BD ) coated dishes , and supplemented with MEF-conditioned media and 10μM ROCK inhibitor ( Y-27632 , Tocris ) with daily fresh FGF2 ( 10 ng/ml , R&D ) . Confluent cultures were subjected to dual SMAD inhibition neural differentiation using Noggin ( R&D , 250 ng/ml ) and SB-431542 ( 10 μM , Tocris ) , and further supplemented with LDN-193189 ( 100 nM , Stemgent ) ( denoted LNSB protocol ) . HES5::eGFP usually appears on day 8 or 9 of neural differentiation . To generate E-RG rosettes and subsequent progenitors , NE cells were scrapped from plates on day 10–12 , pre-incubated with Ca+2/Mg+2 free HBSS followed by collagenase II ( 2 . 5 mg/ml ) , Collagenase IV ( 2 . 5 mg/ml ) and DNAse ( 0 . 5 mg/ml ) solution ( all from Worthington ) ( 37 degrees , 20 minutes ) . Cells were then dissociated and replated at high density ( 500 , 000 cells/cm2 ) on moist matrigel drops , and grown for additional days till rosettes appeared ( E-RG stage ) . Neural induction and direct formation of E-RG stage rosettes could be also formed by co-culture of hESC clusters with MS5 stromal cells as previously described [17] . Briefly , early appearing rosettes on MS5 were harvested mechanically beginning on day 8–10 of differentiation , replated on culture dishes pre-coated with 15 μg/mL polyornithine ( Sigma ) , 1 μg/mL Laminin ( BD Biosciences ) and 1 ug/ml Fibronectin ( BD Biosciences ) ( Po/Lam/FN ) till Day 14 , to obtain E-RG rosettes . Under both protocols , early appearing NE cells were cultured from Day 9 with N2 medium ( composed of DMEM/F12 and N2 supplement containing Insulin , Apo-transferin , Sodium Selenite , Putrecine and Progesterone ) , and further supplemented with low SHH ( 30ng/mL ) , FGF8 ( 100ng/mL ) and BDNF ( 5ng/mL ) . Long-term culture of E-RG rosettes was performed by a weekly mechanical harvesting of rosettes and re-plating on Po/Lam/FN coated dishes with N2 medium , SHH and FGF8 , till Day 28 . These were replaced by FGF2 ( 20ng/mL ) and EGF ( 20ng/mL ) on Day 28 ( all cytokines from R&D Systems ) . At day 35 , E-RG rosettes reached the M-RG rosette stage . Cells were replated as clusters from one passage to another to reach the M-RG stage . Cells were fixed in 4% paraformaldehyde , 0 . 15% picric acid , permeabilized and blocked with PBS , 1% FBS and 0 . 3% Triton solution , and stained with indicated primary antibodies followed by AlexaFluor secondary antibodies ( Invitrogen ) . Cells were imaged in PBSx1 after staining . All cell imaging was carried out in 24 well glass bottom plates ( In Vitro scientific ) . Fluorescence images were obtained using a Nikon Eclipse Ti-E microscope or a confocal LSM710 microscope ( Carl Zeiss MicroImaging , Germany ) . The still or time-lapse images were captured using a 10x and a 20× objectives ( NA = 0 . 3 , 0 . 8 respectively , Plan-Apochromat ) . Fluorescence emissions for eGFP , CY3 , CY5 and DAPI channels were detected using filter sets supplied by the manufacturer . For live imaging , cultured cells were maintained on the microscope stage in a temperature , CO2 , and humidity-controlled environmental chamber . Time-lapse eGFP and phase matched contrast images were acquired using Nikon Eclipse Ti-E microscope every 5 minutes for over 4 hours ( 250 minutes ) . Physical pixel size was 0 . 64 x 0 . 64 μm . Images and movies were generated and analyzed using the NIS elements software ( Nikon ) . All images were exported in TIF and then processed by our quantitative tools . 25 E-RG rosettes and 14 M-RG rosettes were live imaged in N = 2 independent experiments and quantified as detailed below . E-RG rosette cells were treated with either Blebbistatin ( 5μM , Sigma ) or Cytochalasin-B ( 0 . 5μg/ml , Sigma ) and concomitantly recorded for 250 minutes as described above . 10 control E-RG rosettes , 8 E-RG rosettes treated with Blebbistatin and 14 E-RG rosettes treated with Cytochalasin-B were live imaged and analyzed . Rosette centers and contours were manually annotated from the phase contrast channel , where the cytoarchitecture outlines of the region performing INM become obvious to a human eye based on different texture-patterns in the image . Rosette centers and peripheries were marked independently based on subjective identification of regions performing INM as reflected in the image-texture of the phase-contrast channel . Rosette contours were manually validated to remain stable throughout the time-lapse images ( S1B Fig ) , in accordance with the different time scales of rosette imaging and rosette disassembly ( S2E Fig ) . Independent annotations showed highly similar kinetic measures ( S6 Fig ) . The expected radial angle was calculated in relation to the marked center for every location within the region-of-interest defined by the rosette contours . Rosette size was defined as the diameter of the circle that best fits the rosette-annotated contour . Local motion estimation was extracted by maximizing local cross correlation as described in Ref . [24] . Briefly , given two consecutive HES5::eGFP fluorescence images t , t+1 from the time-lapse sequence ( i ) Partition the current image ( at time t ) to a grid of sub-cellular sized local patches , of size 8 . 3μm x 8 . 3μm each ( 13 x 13 pixels ) ; ( ii ) Find maximal cross-correlation to the next frame ( t+1 ) to retrieve the local motion estimations for each patch . The search radius was defined based on maximal speed of 120μm / hour; ( iii ) Extract velocity angles and magnitude ( speed ) from the local motion estimation for each patch; ( iv ) Exclude motions below 15 μm hr-1 from all measures calculations . The quantized motion angles for each patch in the rosette were recorded for 250 minutes ( 50 frames ) . For each patch at every time point the following two angles were defined: Expected radial angle is the orientation of the vector between the rosette center and the patch at hand . The angular alignment γ of a given patch’s motion at a given time is the angle between the local velocity angle and its corresponding expected radial direction ( Fig 2 ) . A measure for radial organization was defined as the average angular alignment across all patches over time . This measure was termed Radial Score ( RS ) , were high values reflected poor radial organization throughout a time-lapse experiment . Only patches that move at speed above 15 μm hour-1 ( ≥ 2 pixel per frame ) were considered for calculating rosette radial organization , because small motions limit the discretization of the velocity angles which cause unreliable high angular deviations . The same minimal motion was considered for the rest of the analysis . The velocity of each patch at every time was classified as apical or basal based on its direction in relation to the rosette center ( Fig 2 ) . Velocity angles pointing toward the rosettes periphery ( +/- 90 degrees ) were classified as basal , while toward the rosette center ( +/- 90 degrees ) as apical . The ratio of all basal to apical motions was termed basal-to-apical ratio ( B/A ratio ) , where value of 1 reflects equal numbers of patches’ motions moving apically and basally , values > 1 corresponds to more motion toward the rosette periphery . RS for basal ( correspondingly , apical ) motions were calculated exactly as described above , only considering basal ( apical ) motions . The measure Speed was defined as the average magnitude of velocity across all patches over time ( Fig 2 ) . Higher values reflect faster average motion throughout a time-lapse experiment . Basal or apical speed was calculated by considering the average of solely the basal or apical motions , respectively . The variance for RS , B/A ratio and speed was calculated over time . Each of the measures was calculated independently for each frame in the time-lapse experiment ( one scalar readout per frame ) , and the variance was recorded . For spatial analysis , 5 different regions , at growing distances-intervals from the rosette center were defined for each rosette . These regions , termed circular rings , were each analyzed independently throughout the time-lapse experiment: all patches in each ring over time were used to calculate RS , B/A ratio and speed . Since rosette geometry was not a perfect circle , the last ring was not always complete , but confined by the rosette contour . Note that the width of a circular ring was rosette specific and changed as function of rosette size . The nonparametric Wilcoxon rank sum test was used to assess statistical significance between E-RG and M-RG rosettes and for the perturbation experiments ( Matlab function ranksum ) . Nonparametric Wilcoxon sign rank test was used to assess statistical significance between two measures calculated independently on the same rosette ( e . g . , apical vs . basal measures , Matlab function signrank ) . Pearson’s linear correlation was used to calculate associations and their corresponding p-values ( Matlab function corr ) . Least square fit was applied to calculate the linear models that best fits the data ( Matlab function polyfit ) . Box plots: solid black line inside the box is the median , bottom and top of the box are the 25% and 75% percentile , respectively . | Brain development is a dynamic and complex process that requires highly orchestrated interaction between neural stem cells . Therefore , investigating these dynamics is fundamental for understanding brain development and disease . However , difficulties to record and quantify neural stem cells behavior inside the brain pose a major limitation . We were recently able to mimic brain development in the Petri dish by generating highly organized multicellular structures containing human neural stem cells termed Neural Rosettes . Here we present a newly developed method to record , quantify and analyze the dynamic movements of neural stem cells within rosettes as reflection of their behavior inside the developing brain . We first confirmed that neural stem cells move radially in rosettes similarly to authentic stem cells residing in the developing brain . We then defined novel measures to assess how well these neural stem cells organize into rosettes in culture and found that organization decreases as stem cells progress in culture . Finally , we demonstrated that disruption of rosette structures by specific drugs impairs organization dynamics of neural stem cells . Our findings offer a first insight into neural stem cell dynamics during brain development , and a potential methodology for functional studies and drug discovery . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development |
Mechanotransduction is a critical function for cells , in terms of cell viability , shaping of tissues , and cellular behavior . In vitro , cellular level forces can stretch adhesion proteins that link extracellular matrix to the actin cytoskeleton exposing hidden binding sites . However , there is no evidence that in vivo forces produce significant in vivo stretching to cause domain unfolding . We now report that the adhesion protein , talin , is repeatedly stretched by 100–350 nm in vivo by myosin contraction of actin filaments . Using a functional EGFP-N-Talin1-C-mCherry to measure the length of single talin molecules , we observed that the C-terminal mCherry was normally displaced in the direction of actin flow by 90 to >250 nm from N-EGFP but only by 50–60 nm ( talin's length in vitro ) after myosin inhibition . Individual talin molecules transiently stretched and relaxed . Peripheral , multimolecular adhesions had green outside and red proximal edges . They also exhibited transient , myosin-dependent stretching of 50–350 nm for 6–16 s; however , expression of the talin-binding head of vinculin increased stretching to about 400 nm and suppressed dynamics . We suggest that rearward moving actin filaments bind , stretch , and release talin in multiple , stochastic stick-slip cycles and that multiple vinculin binding and release cycles integrate pulling on matrices into biochemical signals .
The transduction of cellular forces and substrate rigidity into a biochemical signal is a critical step in the control of cell viability and differentiation as well as the regulation of tissue and cell morphology [1] , [2] . Several recent studies have shown that stretching of proteins in vitro can produce a biochemical change either by uncovering tryosine phosphorylation sites in p130Cas [3] or vinculin binding sites in talin [1] . Stretching of detergent extracted cytoskeletons increases adhesion protein binding [4] , activates Rap1 GTP formation through a tyrosine phosphorylation pathway [5] , and increases tyrosine phosphorylation levels . While indirect evidence of in vivo stretching in heat-shock responses [6] and the exposure of buried cysteines [7] has been shown and in vivo force measurements have been made on single vinculins [8] , there has been no quantitative measure of the strain of proteins in vivo . The extracellular matrix is under significant stress , and the strain of Fibronectin [9] has been established in a fluorescence resonance energy transfer ( FRET ) assay but there is not a quantitative measure of protein stretching in cells . This raises the question of whether protein stretching ( domain unfolding ) plays a physiological role in the normal sensing of the mechanical microenvironment . The extent of stretch and the length of time in the stretched state provide important constraints on any model of mechanotransduction . Measurement of the N- to C-terminal length of proteins in cells is difficult since there is normally overlap of many molecules in adhesion structures and most of the proteins have molecular lengths that are much greater than can be measured by FRET techniques ( FRET is effective for 5–7 nm ) . Super-resolution techniques like PAL-M and STED do not enable the resolution of the N- and C- terminal positions of individual molecules in dense regions , and STED does not offer the possibility of single molecule and dual tag observation . We postulated that the presence of different fluorophores on the N- and C-termini of proteins could be used to measure the protein length in situ at both the single molecule ( low expression ) and multi-molecular levels ( higher expression in focal adhesions ) with new image processing techniques . In the case of talin , the unstretched molecule has an overall length of 51 nm [10] in vitro , and it contains up to 11 hidden , putative vinculin binding sequences [11] . The 2 , 000 amino acid rod of talin could theoretically stretch to a length of over 800 nm , but it is unknown whether significant stretch occurs in vivo .
A talin1 construct fused to EGFP at the N-terminus and mCherry at the C-terminus was developed and expressed in CV1 cells ( diagram in Figure 1A ) . The distribution of the dually tagged protein was indistinguishable from the distribution of the endogenous talin 1 as determined by antibody staining of both low ( not shown ) and high expressing cells ( Figure 1B ) . Another criterion for the proper behavior of the tagged molecule was that the photobleaching recovery rate of the dually tagged talin was similar to the rate previously measured , i . e . the half-time of photobleaching recovery was greater than 100 s in both cases [12] . Activation of β1 integrin was found to be unaffected by the transfection of dually tagged talin 1 in talin1 knockout cells as shown in Figure S1 . Finally , dually tagged talin was able to restore normal spreading , polarization , and vinculin adhesion formation in talin-depleted cells [13] . Thus , the presence of the two fluorophores did not alter talin binding , function , or its dynamics in adhesion sites and ruffle movement in any detectable way ( Figure S2 ) . As a further test that the chimeric protein was behaving normally , we measured the fluorescence characteristics of individual proteins in low expressing cells . Our criterion for a single talin dimer was that two EGFP molecules were separated by more than 500 nm from other EGFPs ( 10 times the in vitro length of talin ) , and that there were two bleaching steps in the green channel and at least one in the red channel ( previous studies have noted that only about 50% of mCherry molecules will be fluorescent upon expression in mammalian cells [14] ) . In cells with low expression and well-separated fluorophores , we typically observed dimeric EGFP spots ( Figure 2A ) . These were dimeric based upon two criteria: ( 1 ) they normally bleached in two steps and ( 2 ) they were not normally detected by an algorithm to fit a single point spread function ( only 15% of the isolated EGFPs were detected with a circular PSF and in some cases the two fluorophores were well separated ) ( also Figure 2A ) . In the case of the mCherry fluorescence , the fluorophores were normally detected by a circular PSF ( 80% of fluorophores ) , and there were fewer double bleaching events so that we typically linked individual mCherry fluorophores with the dual green fluorophores . When the distance between the green dye pairs and red dye was measured for linked fluorophores , the green-red vector was typically oriented in the direction of the actin movement ( Figure 3A ) and the displacement histogram plot showed a global maximum at 90 with a secondary peak at 150 and shoulders at 50 and 210 nm . As a control , we co-transfected cells with two unlinked focal adhesion proteins , EGFP-FAK ( focal adhesion kinase ) and mCherry-paxillin , and performed the same analysis ( Figure 3B ) . However , the EGFP–mCherry axis did not show strong orientation and the number of observed events increased linearly with displacement as expected for a random distribution ( the sampled area increases linearly with radius ) . When we went back and fit the observed normal histogram for EGFP-talin-mCherry using the known density of fluorophores in the region and the fraction of unfolded mCherry molecules , we found that the random interference of the adjacent molecules contributed significantly to the mis-aligned vectors in the normal talin1 plot and to the histograms at large displacements ( notice that at low expression , the expected number of random events should scale proportionally with area and there is a linear increase in the area sampled with increasing radius ) . Even after correction , these measurements show that talin molecules are stretched in the direction of actin movement in vivo . If the stretching of the talin molecules was due to myosin contraction of the actin filaments , then inhibition of cellular contractile activity might inhibit orientation and displacement [15] , [16] . After blebbistatin addition to inhibit myosin contraction , there were two major changes at the single molecule level: ( 1 ) the orientation of the green-red dipoles was random and ( 2 ) the average displacement was much less , giving a peak at 50–60 nm ( Figure 3C , top ) . If the cells were treated with Y-27632 to inhibit the Rho Kinase , traction forces were dramatically decreased but peripheral contractions persisted ( Figure 3C below ) [17] , [18] . Single talin dimers were still oriented , but the level of displacement decreased giving a major peak at 50–60 nm and a secondary peak at 110 nm . The major peak in both inhibitors was consistent with the length of the in vitro talin molecule , i . e . 51 nm ( assuming that 5–10 nm should be subtracted for the linkers and the fluorescent proteins ) [10] . The longer forms potentially indicated that some of the bound molecules were stretched but correction for random events removed most of the cases above 200 nm . This was consistent with the fact that about 20% of normal force was generated even in the presence of blebbistatin [15] . We wondered if the stretch was static or changed with time . In several cases , we were able to follow isolated EGFP-mCherry pairs over 30 to 60 s at 2 s intervals . Clear changes were observed in the length of single molecules over a time frame of 10–20 s , but there was significant randomness in the stretching events ( Figure 3D ) . We estimated the variance of the position measurements for a single frame to be ±14 nm from a statistical analysis of multiple position measurements of the EGFP fluorophores that did not show any directed movement . Thus , we found that there was significant stretching of single molecules in a transient manner ( see also Figure S3 , which provides the corresponding micrographs and pair locations ) . To be able to better measure the dynamics of the N- to C-terminus displacement of talin in situ , images from cells with higher expression levels were analyzed giving an average displacement . Adhesions with greater fluorescence intensity than 200 fluorophores were chosen . We found that after correcting for chromatic aberration , the mCherry signal was predominantly displaced toward the nucleus from the EGFP signal in peripheral adhesions ( Figure 4A & B , multimolecule analysis ) , whereas in central adhesions , the displacement was usually significantly less . As a control , we analyzed the displacement of mCherry and EGFP in cells expressing both EGFP-paxillin and vinculin-mCherry that should localize randomly in adhesions . In that case there was no preferential direction and no changes were observed over time ( Figure 3B , single molecule analysis ) . To objectively determine the displacement over time , we analyzed each region of interest ( ROI ) with an iterative constraint deconvolution algorithm that created a super-resolved map of the image based upon the PSF of the microscope ( see Materials and Methods ) and a direct , reduced derivative of the Richardson-Lucy Deconvolution [19] , [20] . The intensity of the fluorescence in the adhesion did not require the fluorophores contributing to each point image to be close to the average intensity , but the signal density needed to be high enough such that the point images of the fluorophores overlapped . Within the map , the edge was then found via a conventional Canny edge detector ( Figure 4A ) [21] . When the displacement between the green and red leading edges was measured ( the edges toward the periphery ) , the displacement changed over time , rapidly increasing to as much as 350 nm of separation and dropping to near zero ( Figure 4B ) . Our estimated error of the measurement was ±20 nm and measurements of displacements orthogonal to the axis of actin movement often had fluctuations of ±15 nm over time . In cases where the direction of actin flow was measured , the mCherry fluorescence and presumably the C-terminus of talin were always displaced with the actin flow toward the nucleus . This was true for adhesions on the opposite sides of the same cell or ones oriented at right angles to each other . The average time for the large excursions of the C-termini was of the order of 6–16 s and was much more rapid than the photobleaching recovery rate for talin , indicating that talin was stretched and released multiple times . When two adhesions in the same field were analyzed , they often were uncorrelated in their movements ( Figure 4C ) . The displacements in the round adhesion were relatively slow and had an average lifetime of 13 s , whereas the displacements in the adjacent longer adhesion were more rapid ( also Figure 4C ) . Stress fibers in these cells were normally attached to longer adhesions . The stochastic nature of the displacements was consistent with a transient attachment of the C-terminal to rearward moving actin , displacement , and release , as in a stick-slip coupling . When inhibitors of contraction were added , the displacements in the adhesions decreased dramatically ( Figure 5A ) . Although adhesions persisted in the presence of blebbistatin , the displacements were barely above background levels ( displacements of 0–30 nm ) . In the presence of the Rho kinase inhibitor , the fluctuations decreased dramatically from the normal case ( displacements of 0–50 nm , lower plot , Figure 5A ) . This was consistent with the decreased contractile activity and decreased actin flow rate that should have resulted in smaller displacements before the release and slip . From the steered molecular dynamics analyses of the talin rod , the stretching of talin by 100 to 200 nm could reveal 5–7 vinculin binding sequences [22] , [23] . This is in line with the presumed function of talin stretch to increase the number of bound vinculin molecules . Upon relaxation of talin , the number of bound vinculin molecules should decrease . Thus , the timetable of stretching and relaxation may be related to the exchange rate of vinculin in adhesions . Other studies have shown that vinculin has a much shorter lifetime in the adhesions than talin ( t½ of 16 versus >100 s ) [24] , [25] and the vinculin lifetime is close to the time of the stretch-relaxation cycle that we observe . It is possible , therefore , that the expression of the vinculin head that binds tightly to talin would cause a decrease in adhesion dynamics and promote talin stretching . In cells transiently expressing a vinculin head construct , there was a dramatic increase in the displacement of the C-terminal mCherry from the N-EGFP to levels of 400 to 600 nm and a suppression of the dynamics of the length change ( Figure 5B ) . In normal cells , the level of endogenous vinculin staining in adhesions correlated well with the level of talin , N- and C-terminal displacement ( Figure S4 ) . In the case of activated FAK staining [26] , there was a weak correlation of staining intensity and the level of displacement ( Figure S5 ) . Because the strong binding of activated vinculin head caused increased talin stretching with less dynamics and increased endogenous vinculin staining correlated with increased stretching of EGFP-talin-mCherry , we suggest that talin stretching in vivo results in vinculing binding .
The EGFP-talin-mCherry protein appears to be a good reporter of talin1 function and the stretch of talin in vivo . The measured lengths of the talin molecules of 80 to 350 nm are consistent with the structure of the talin rod ( roughly 2 , 000 aa in the rod that could be stretched to a length of 800 nm ) and the dependence of the stretch upon contraction is consistent with its dependence upon actin flow driven by actomyosin pulling . In the single molecule case , the displacements of the two EGFPs are well within the expected range for the splayed ends of a parallel dimer that is linked at the other end [11] . In the multi-molecular analyses , it is surprising that the N- and C-terminal ends of talin in the adhesions are displaced from each other since it implies that there is a lateral aggregation of the N-termini distinct from the C-termini . Recent analyses of talin using iPALM showed that the talin N-termini were at the membrane surface and C-termini were 30 nm above the membrane [27] , but they were unable to measure simultaneously the N- and C-termini to estimate the average length of the molecule . Based upon those results and the findings here , it appears that the two ends of the talin molecules are located in different complexes that are part of focal adhesions ( as drawn in Figure 6 ) . The fact that the displacement oscillates over time in a myosin-dependent manner rules out many possible artifacts of the measurement system , particularly since myosin-inhibited samples fluctuate 5- to 10-fold less over time . Thus , we suggest that the centripetally moving actin ( moving typically at 40–60 nm/s ) transiently attaches to the C-terminal talin complex that may include other adhesion proteins , stretches talin , and then releases it . The linkage between the actin cytoskeleton and the adhesion complexes generating traction force has been treated as a clutch [28] that generates traction force before slipping in neurons [29] . However , fibroblasts behave differently from growth cones in that there is slower actin flow and greater force on rigid surfaces [30] , [31] . The time scale of force generation at the level of even sub-micrometer adhesions ( Ghassemi , Sheetz , and Hone , personal communication ) is considerably longer than the oscillations in talin length either at the single molecule or adhesion level . Thus , we suggest that talin stretching occurs stochastically through a transient slip bond between inward moving actin filaments ( Figure 6 ) and talin C-terminal complexes that contributes only secondarily to the overall traction force . Logically , a bond between talin and actin cannot be maintained for very long because the velocity of the actin movement rearward is 40–60 nm/s and the lifetime of talin in the adhesions is over 100 s , giving potentially 4 , 000–6 , 000 nm of stretch . In the case of the adhesion complexes , there appears to be a concerted release of the talin C-termini from the actin ( there are several hundred talins in each adhesion and the displacement is rapidly lost ) . Two possible explanations are ( 1 ) enzymatic modification or ( 2 ) a concerted release by a fracture phenomenon such that the breaking of the bond under the highest force passes that force to the next bond causing it to break rapidly resulting in all bonds breaking in rapid succession . In either case , we consistently find a concerted displacement of the talin C-termini in adhesion complexes in the direction of actin flow that is dependent upon myosin contraction . The dramatic oscillations in the length of the talin molecules are inconsistent with the stable nature of forces on pillars that only oscillate on the time scale of minutes and not seconds as does talin stretching . Thus , we postulate that the major role of actin stretching of talin is in signaling and not force generation . The oscillations in talin length appear to affect the binding of vinculin since increased vinculin binding through expression of the active head appears to increase talin length as well as decrease oscillations in length . Recent studies in mice expressing a vinculin mutant that behaves like the active vinculin head find early lethality [32] , which indicates that vinculin dynamics are important for cell function in vivo . These studies are also consistent with developing views of the adhesion sites as signaling complexes with peripheral and core components [33] . Cycles of binding and release could be linked also to enzymatic modifications of the bound proteins such as the phosphorylation of FAK that would enable the cells to accumulate signals from rigid matrices that would support growth and differentiation processes . Much more work is needed to understand the role that the molecular stretching of talin in vivo plays in the functions of adhesion structures and cellular behavior . However , this method for measuring the displacement has demonstrated that stretching-relaxation cycles occur in vivo as a result of myosin contraction by a stick-slip mechanism .
CV1 cells were used for these studies and cells were transfected with lipofectamine 200 , 024 hours prior to resuspension and plating onto fibronectin coated coverslips . Cells were typically imaged after overnight plating . Inhibitors of myosin were added at the time of plating . 10 uM of blebbistatin and 10 uM of Y-27632 were used in the inhibition assay , and care was taken to not expose blebbistatin solutions to light except at the time of image acquisition . Blebbistatin , Y-27632 , and fibronectin were purchased from Sigma . Phospho-FAK antibodies were obtained from Invitrogen . Talin and vinculin antibodies were purchased from Sigma . CV1 cells were fixed in 3% paraformaldehyde in phosphate buffered saline ( PBS ) for 30 min . Fixed cells were washed twice with PBS , twice with PBS containing 50 mM NH4Cl , and twice again with PBS , followed by permeabilization with 0 . 1% Triton-X-100 ( Sigma-Aldrich ) ( room temperature , 15 min ) . Permeabilized cells were incubated at room temperature for 1 h with 30 µl of anti-Talin , anti-Vinculin ( Sigma ) , or anti-phospho-FAK ( Invitrogen ) at 1∶200 dilution ( in 2% fetal bovine serum , 2% bovine serum albumin , and 5% goat serum in PBS ) . Samples were washed three times in 0 . 1% Triton-X-100-containing PBS followed by two times in PBS before incubation with AlexaFluor 647 goat anti-mouse or AlexaFluor 647 goat anti-rabbit ( Molecular Probe , Invitrogen ) at 1∶200 dilution ( in 2% fetal bovine serum , 2% bovine serum albumin , and 5% goat serum in PBS ) for 1 h at room temperature . After the final wash ( three times in 0 . 1% Triton-X-100 containing PBS and two times in PBS ) , coverslips were mounted with FluorSave ( Calbiochem , San Diego , CA ) and examined under a DeltaVision microscope ( all images were captured with a 100× oil objective lens ) . In the stretching experiments , frame-of-reference fiducials , Zeiss 100 nm yellow beads , and 250 nm Invitrogen Tetraspeck beads were used . A stable frame of reference was deduced from fluorescent beads , which settled , stuck to the Fibronectin-coated coverslip , and did not exhibit thermal movement . Tracking relied on dual channel time-alternating TIRF images from an Olympus 1 . 49 100× oil immersion system at a 1 . 5× relay magnification using excitation wavelengths at 488 nm with 27 mW and 561 nm with 15 mW of power , recorded on a 1024×1024 pixel Photometrics Cascade II EMCCD camera at 10 MHz readout speed , 13 mm pixel size , at an operating temperature of −42°C with external forced airflow . The imaging system was calibrated for chromatic aberration , dark current , and read noise using Zeiss 100 nm yellow beads and 250 nm Invitrogen Tetraspeck beads . Single molecule tracking used exposure times of minimally 5 ms at 488 nm and 20 ms at 561 nm , respectively , up to 100 ms for both . The interval between channel pairs was 2 s . Signal molecule tracking was achieved by fast correlation followed by adapted maximum likelihood ( referred to as ML henceforward ) single PSF fit , tuned to the dimer signal for the EGFP signal and mild defocus PSF for the mCherry channel . The ML parameter of choice was how well the photon statistics of a single fluorophore ( forming the point source ) added to a locally constant background of defocused light , and could explain the brightness observed . The center coordinates of the point sources are moved until a local maximum in likelihood is reached . We moved the center in three dimensions , hence allowing for a mild defocus of the center coordinate . Pair occurrences of both fluorophores within a 300 nm radius ( the “catching radius” ) region were recorded as single molecule candidates . Since we used both excitation lines at the same TIRF angle , we had to use averaged and hence relatively tolerant TIRF settings . Also , since the adhesions form areas of elevated refractive index , some widefield leak could not be prevented . The detector and localization software worked well with these settings , since the point-spread functions of the single molecules were very clear and discernible with highest accuracy . The EGFP signals were usually dimers whose components were too close to be resolved by the microscope ( assuming the 250 nm Abbe limit of our oil immersion system ) but generally too far apart to result in the image of a single point . Assuming that the PSFs were dimeric ( Figure 2A ) , the detector tested several dimeric PSFs to determine the best fit of each molecule ( Figure 2B ) . Merely widening the accepting shape of the PSF enabled efficient detection of the dimer signals , but it resulted in accepting significantly more background ( i . e . , random noise constellations ) . Hence , PSF widening was abandoned for our image processing , although it was an order of magnitude more efficient in computing time . The mCherry PSF appeared elevated above the cover slip when the microscope was focused on the GFP fluorophores at the glass surface . The detector was defocused in 10 nm steps for up to 50 nm to test for the defocus of the mCherry monomer . For acceptance , the mCherry signal needed to be within the catching radius of the EGFP signal and to be active for several frames ( usually four or more ) . This temporal co-localization requirement acted as strong noise rejection filter , eliminating about two in three signals that passed the PSF shape criterion . With increasing pull , the mCherry molecules tended to be closer to the coverslip resulting in cleaner PSFs . The observed signal levels of the two fluorophores differed dramatically: mCherry lived far fewer excitation cycles than EGFP ( above 20K cycles versus 40K cycles before average bleaching ) , the mCherry signal was lost due to the defocus blur , and fewer mCherry molecules folded properly ( 35% folded properly rather than 65% for EGFP ) . This limited the observable number of frames but did not impact the detection accuracy in any measurable way . Both the distortion from the dimer and the defocus of the mCherry monomer were learned by the detector through empirical tests . The main challenge regarding the image processing was that it proved virtually impossible to create expression levels that were low enough to be analyzed by photoactivation localization microscopy ( PALM ) software . The lowest meaningful molecular density was a good order of magnitude larger than the density that was acceptable to the fast filters used for the PALM correlation detection . Thus , the PSFs of many molecules partially overlapped or collided . Being able to deal with overlapping PSFs was a prerequisite to design an algorithm with an acceptable yield ( example depicted in Figure 2B ) . To compensate for the problems with the focus and overlap , we used computationally very inefficient matched filters that were trained with our own datasets . The PSFs used for the detection algorithm were harvested from sparse test datasets whose centroid signals were the most radially symmetric we could find and with minimal blur ( i . e . , they needed to be in focus ) . 10–40 such PSFs were centered and then fused into a single PSF suitable for detection . This provided a very selective and reliable first stage filter for the EGFP tags ( even for the dimeric ones ) but—due to large focal range—proved unsuitable for the mCherry monomers . The search was hence executed hierarchically: ( i ) EGFP candidates were identified first; ( ii ) dimers were analyzed; ( iii ) pairs of dimers that collided—i . e . , came too close to other valid EGFP signals within the detection range—were rejected; ( iv ) nearby mCherry signals were analyzed for the proper focus; and ( v ) mCherry collisions were rejected and ( vi ) tested for continuity of the EGFP-mCherry pairing for at least N frames ( we mostly used N = 2 or N = 4 and even N = 2 provided an excellent rejection against noise artifacts ) . The matching itself was done by calculating the logarithmic likelihood that the observed signal was matched to the PSF model . We use a computational model of the PSF to account for all the possible dimers and to implement defocus more easily . No restrictions on the signal amplitude were made , and the matching was limited to a circular region of 300 nm radius in order to still allow for dense signals . A raw micrograph of an unprocessed molecule experiencing stretching and the output of the correlation filter is presented in Figure S6 . A ML method with such restrictions is not any more accurate than a centroid detector ( our localization algorithm performs considerably worse than the PAL-microscopy software in most cases ) , but it performs well in an environment where the signals are denser . The fraction of usable signal was raised considerably ( more than a factor of 3 over the autocorrelation detector ) but often still did not reach 50% of the observable speckle-like signals . We rejected specimens with a very low fraction of analyzable signals ( i . e . , a high number of detected collisions ) due to the danger of admitting statistically non-significant data ( see density “artifacts” in Figures S7 and S8 ) . Motion was not a serious problem for our setup since the PSF signals were reliably clean and motion artifacts would not pass the defocus tolerance . The “speed limit” for exposure times of up to 100 ms was just above the 60 nm/s of the average actin flow . Higher speeds needed a more tolerant detector ( which was computationally unreasonably expensive for the follower-channel ) or shorter exposure times . Oddly enough , the single molecule pair-observation was not limited by the dramatic loss of single molecules detected when the signals become as dense as a PSF diameter . However , if we consider the number of erroneously assigned tags , at high densities , a random tag from another molecule becomes a more plausible “partner” than the true second label ( Figure 3B and Figures S7 and S8 ) . We were forced to monitor the signal density and reject samples with too great a density , since the above error cannot be corrected in our algorithm . The error can be estimated safely but not overcome if present . At high densities , though , proper images were formed whose boundaries were defined and the edge was localized by conventional edge detection theory ( Figure 4A and 4B ) , mainly Canny detectors , which allowed for sub-pixel localization of the boundary . This ensemble detection of dense fluorophore assemblies was further improved by subjecting it to a Richardson-Lucy deconvolved super-resolved ROI . Edge detection was limited orthogonally to the surface , which allowed for the one-dimensional integral across the entire leading edge in order to obtain a more stable readout . This method was applied to fiducial recordings . It showed a tracking accuracy and repeatability better than 25 nm for focal adhesions prior to bleaching . As both localization methods are novel , we derived a t test for paired samples of our measurements versus two powerful negative hypotheses: ( i ) the static measurements were realizations of random , normal , but spatially variant fluctuations and not actual single molecule stretching observations , and ( ii ) our dynamic data were the result of a systematic calibration error superimposed by a locally variable measurement noise . We assumed the worst case for all errors: that the distributions of the noise matched the observed movements optimally and that the calibration error canceled out all observations optimally . Using a powerful and universal error model was necessary to segregate our observation from all possible alternative explanations . Consequently , our confidence intervals were relatively pessimistic . For the static case , any observation shorter than 18 nm and 22 nm , respectively ( the first value for the observed jitter model and the second one for an upper bound of single molecule statistical variance ) , was not significant compared the noise models . That is , measurements shorter than this value were possibly noise . That was about 50% worse than what the observations of our ensemble variance suggested but was a logical consequence of the test limits . The variance was at two-thirds of these values and hence only the average of the observations was truly significant—a single measurement needed to be longer than 36 nm and 45 nm ( again , depending on the underlying model ) , respectively , to be 99% significant . The result for the dynamic tests ( Figure 3D ) was more merciful solely because the distances of motion overshot the latter limit on average . But as the error model here is even more powerful , numerous observations were required to establish significance . For the dynamic measurements , only length changes in excess of 18 nm were significant over the null hypothesis: that is , the quotient of the likelihood of a single observation over the likelihood of a single random process was 1 . 38 for the active normal datasets and 1 . 32 for the active Y-27632 datasets . The dynamic data for blebbistatin was not significant at all ( Figure 5A ) and the dynamic measurements in the presence of blebbistatin constituted a negative result . The observed durations for molecules in our tests were 22–27 frames of 2 s each for the normal case and 22–25 frames for the Y-27632 , raising the previous probability ratios to these powers . The total probability ratio per measurement of a single molecule was ∼6 , 000 for the normal case and ∼500 for the Y-27632 samples . The maximum separation quotient per entire experiment was 1∶1041 for normal versus 1∶1050 for Y-27632 , since the latter showed an average of 18 . 5 long living molecules versus the 10 . 9 in the normal case . The observed movement of molecules over time can hence only be explained by a structured movement over time and not by a random fluctuation . The fiducial beads were identified with a correlation filter and the local maxima above the 30% threshold of the dynamic range , in order to segregate the beads from fluorophore clusters . Beads were localized in two steps via a centroid measurement followed by a maximum likelihood fit . The latter also helped to eliminate beads that were not in contact with the coverslip or showed motion artifacts . The beads that traveled the shortest distances over the observation period were admitted to the pool of the “ensemble . ” This assured that loose beads or beads attached to the cells were not taken into account for the frame of reference . The accuracy of matching was defined as the square root of the variance of a single fiducial relative to the ensemble . We obtained values of 2 . 8 nm for the TetraSpecks and 4 nm for the Zeiss yellow beads . Adding a maximum likelihood detector to the centroid measurements only improved the stability if the beads saturated the detector . When signals were in the linear region , no change or improvement was noticed . Dense fields of beads without biological samples were used to determine the chromatic aberration . The yellow beads emitted broadly in both channels and hence delivered a too optimistic estimate for the lens errors . But the TetraSpecks beads nicely matched our fluorophores and hence were used for all calibrations . The same selection procedure for non-sticking beads was used . Several frames were needed to establish a dense frame of adherent beads , even though the chromatic error was a feature that changed slowly over the field of view . The field of view was tessellated into triangles by the chromatic reference . Within the tessellation , we used tri-linear interpolation to establish the chromatic shift at any given location . We used the green channels as the reference and corrected for the red coordinates . Each red measurement was complemented by the chromatic vector and hence was seen relative to the green channel . No absolute reference was required anywhere in our measurements as all distances were assessed locally . The localization of fluorophore tags—as described above—was photon limited . For both centroid and ML localization , the accuracy increased with the square root of the photon count , but the limits were about 30% narrower for ML matches . ML was also more robust against “collisions”—partially overlapping PSFs—as well as motion and defocus artifacts . The cost was a steep increase in computational effort and an actually much worse performance if wrong PSFs were used . In the best quiet datasets with Blebbistatin , the ensemble of the red fluorochromes was stable within 18 nm for the entire population and 10 nm for the strongest signals . For the brighter green fluorophores , these values were 14 nm and 8 nm , respectively . For the active datasets , the single frame accuracy was as calculated above . However , the green frame was recorded 500 ms after the red one , which introduced a significant uncertainty in the motion prediction . While we extrapolated the frame of reference to the recording time , the terminals of stretching molecules were observed at different stages and hence the distance between the terminals was interpolated . We did this by assuming that the motion was band limited and hence used sin ( t ) /t for the time interpolation . At the speeds of the actin flow , the differences between the sin ( t ) /t interpolation and no interpolation can be as great as 8 nm with no safe way to determine which one was actually more accurate but that is a small fraction of the observed displacements . Assuming that the reference errors , the interpolation , and the localization were independent processes , there was a ∼20 nm error for observation accuracy . If the extrapolation was free of errors , this was reduced to ∼18 nm and ∼15 nm , respectively . This also imposed strict limits of what we regarded as significant stretch , motion , and orientation . Distances must reliably exceed the above limits , motion must either exceed or stay beyond the above limits to be identified as “real , ” and both coordinates which define an orientation must consistently be separated by more than the observation limit . The orientation plots in Figure 3 require observed stretching of 60 nm or more to be quantitatively meaningful under the above limits . | How are mechanical forces that act on the surface of a cell transformed into biochemical signals within the cell ? Studies of isolated proteins suggest that some of them can stretch , but whether this also happens in living cells remains unclear . In this study , we have been able to measure the stretching of single molecules of a cellular adhesion protein called talin in vivo by tagging each end of the protein with a different fluorescent marker and observing changes in the distance between the two markers with a new microscopic method . Talin is a large cellular protein that concentrates at sites where the cell attaches to the substratum and links integrins in the cell membrane to the actin filament network in the cell . In our study , a green tag at the integrin-binding site was close to the cell surface , whereas a red tag at the actin-binding site was displaced inward by actin flow . We observed repeated protein stretching to 5–8 times the native protein length and relaxation linked to the transduction process in living cells in culture . Individual molecules stretched for 6–16 seconds over ranges of 50–350 nm . Cell adhesion sites , where hundreds of talin molecules were displaced in concert , had similar dynamics . These cycles of stretching and relaxation required the contractile protein myosin . The head domain of vinculin—an adhesion site protein that binds strongly to the stretched talin—kept the adhesions stretched and blocked large oscillations in length . These observations indicate that there is repeated stretching of talin , and that adhesion proteins play a role in the transduction of mechanical signals into biochemical signals through binding and release of vinculin and possibly other focal adhesion proteins . | [
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] | 2011 | Mechanotransduction In Vivo by Repeated Talin Stretch-Relaxation Events Depends upon Vinculin |
A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism . To investigate this relationship , we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure . We then constructed an ensemble method to predict environmental and cellular state , including strain , growth phase , medium , oxygen level , antibiotic and carbon source presence . Results show that gene expression is an excellent predictor of environmental structure , with multi-class ensemble models achieving balanced accuracy between 70 . 0% ( ±3 . 5% ) to 98 . 3% ( ±2 . 3% ) for the various characteristics . Interestingly , this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered , as a composite classifier that captures the inter-dependencies of three characteristics ( medium , phase and strain ) achieved 10 . 6% ( ±1 . 0% ) higher performance than any individual models . Contrary to expectations , only 59% of the top informative genes were also identified as differentially expressed under the respective conditions . Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content , including iron transport , transferases , and enterobactin synthesis . Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes . This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent , heterogeneous and seemingly disparate phenotypic and environmental characteristics , with far-reaching applications .
Genome-scale transcriptional profiling has become a standard and relatively inexpensive way to identify the overall cellular state and condition-specific cellular responses to external stimuli . For instance , different sets of genes are known to be active in each growth phase and medium [1] , while strain polymorphisms can result in a remarkably diverse transcriptional repertoire [2 , 3] . Similarly , it is known that bacterial organisms undergoing rapid adaptations to varying environments , such as heat-shock and osmotic stress , produce differential expression profiles that are indicative of the corresponding stress [4–9] . Genome-wide transcriptional profiling can be thought of as a complex representation of all cellular functions and states , with a wealth of multiplexed information that , if decoded efficiently , can provide a fast and quite accurate all-encompassing snapshot of the cell and its environment . Despite its obvious correlation with various physiological and cellular states , we lack a clear understanding of the information content related to the manifold phenotypes that can be extracted from the genome-scale transcription profiles . Until now , a significant obstacle was the absence of sufficient transcriptional data to support the training of multi-feature and multi-label classifiers . Indeed , after aggregating all high-throughput transcriptional data that is currently available for E . coli , the most well-studied model microbe , we are still limited to a few thousands microarray or RNA-Seq experiments that cover more than 30 strains , a dozen different media and a multitude of other genetic ( knock-out , over-expressions , re-wirings ) , or environmental ( carbon limitation , chemicals , abiotic factors ) perturbations . Although this collection has already increased by an order of magnitude from the roughly two hundred genome-wide transcriptional profiles that we had eight years ago , it is still an inadequate sampling of the relevant experimental space . In addition , since these experiments have been performed in different technological platforms ( e . g . Affymetrix E . coli Genome 2 . 0 , Affymetrix E . coli Antisense ) and technologies ( e . g . microarrays vs . RNA-Seq ) , in different labs and under different environmental conditions , appropriate normalization schemes are both of paramount importance and with an added complexity . As such , efficient training of machine learning methods is hindered due to data complexity , compatibility and the curse of dimensionality that plagues datasets with thousands of features ( genes ) but only a few samples ( conditions ) . The application of high-dimensional prediction algorithms has been widespread in biology ranging from gene function prediction [10–12] , disease risk estimation from inherited variants [13] , and network inference [14–18] , but the vast majority of these studies are confined to the use of transcriptional data on pathological , pharmacological and clinical predictions [19–25] . Interestingly , a Saccharomyces cerevisiae study that involved tens of data samples was able to predict growth rates [26] , while a multi-class stressor prediction in rice used five hundred transcription profiles [27] . More recently , a probabilistic human tissue and cell type predictor was built based solely on gene expression profiles [28] . In this work , we investigate how well we can predict cellular and environmental state from genome-wide expression , using known gene expression profiles as our only training data . We report the optimal number of features for each classification task , what these features are , and all relevant pathways . To achieve this , we have extended , normalized and annotated a compendium that was compiled recently [29] to incorporate all published high-quality Affymetrix microarray and RNA-Seq datasets in E . coli ( 2258 samples in total , Fig . 1A ) . This E . coli Gene Expression Compendium ( EcoGEC ) , consists of publicly available data that were curated from online public databases such as GEO [30] , ArrayExpress [31] , SRA [32] , SMD [33] , M3D [34] and PortEco [35] . To increase the compatibility among the various arrays , we adjusted batch-effects across data from different sources and devised a statistical normalization scheme that significantly removed biases ( see Methods; Fig . 1B , Table 1 ) . Concomitantly , we developed an iterative learning procedure to impute unannotated or mis-labeled data and used it to increase the quality of the resulting datasets ( Fig . 2A ) . By applying four different machine-learning algorithms on the EcoGEC compendium ( Fig . 2B ) , we predicted six different organism and environmental variables from gene expression profiles related to medium , growth phase , strain , aerobic conditions , antibiotics and carbon sources present ( Fig . 2C ) . Functional , network and mechanistic analysis of the highly-informative features provide a comprehensive map of the implicated genes and pathways .
We first investigated how many genes are required to achieve optimal performance and the minimum number of genes with near-optimal performance , defined as 2% reduction from the optimal balanced accuracy . As shown in Fig . 3A , in most cases the cumulative information content is asymptotically approaching a maximal value within a few hundred genes . The balanced accuracy profile of the different predictors spans a large spectrum of behaviors , from profiles that are optimal early on , such as in the case of the medium classifier where the 150 first genes are sufficient for accurate classification , to profiles that rise slowly , as in the case of the composite classifier , which is defined as the model that classify classifies 3 characteristics of medium , phase , strain altogether . In general , however , our results show that the subset of genes that is needed to achieve high balanced classification accuracy is neither a handful of biomarkers , nor a large gene set , with all cases achieving near-optimal performance with 100 to 400 genes . In the most extreme case of the composite classifier , a near-optimal balanced accuracy ( 70 . 26% ) can be achieved with less than 400 genes , which is close to its maximum performance ( 71 . 55% ) that is achieved when considering all 4166 genes . To investigate the relationship of data size with classification performance , we systematically reduced the dataset , keeping a balanced class/label distribution . Our results argue that although there is an expected reduction in classification performance , as the dataset is progressively reduced by up to 75% , the method is quite robust with an average reduction of 6% classification performance per quartile reduction in data size ( S1 Table ) . In all cases , the classification performance is significantly higher than the balanced baseline ( Mann-Whitney-Wilkoxon test , P < 2 . 398 × 10−3 ) , with the balanced accuracy of all classifiers ranging between 69 . 95% ( ±3 . 52% ) to 98 . 27% ( ±2 . 32% ) ( Fig . 3B , S2 Table ) . For predicting the growth phase , we first imputed any unannotated phase information , which accounted for 34% of the compendium . We used a learning approach in which missing data is inferred iteratively . This preprocessing step was found to substantially increase the classification performance when evaluated across all classification tasks by an average of 7 . 3% and as much as 22% in some cases ( S1 Fig . , S2A Fig . , S2C Fig . , S3 Table , S4 Table ) . Interestingly , by following this approach , we were able to infer the characteristics from 90 . 6% of the unannotated phase data ( S2B Fig . ) . The iterative learning method does not significantly decrease the MI levels that are observed when compared to those obtained from the original dataset and the gene ranking is mostly preserved ( S5 Table , Kendall tau rank correlation: τ = 0 . 714 , P < 2 . 2 10−16 ) . The simultaneous prediction of all seven characteristics of a sample using seven individual classifiers yields an accuracy of 84 . 21% ( ±1 . 39% ) ( Fig . 3C ) . To create the necessary training set for the simultaneous prediction of three characteristics ( medium , phase and strain ) , we had to reduce the amount of classes to 13 due to insufficient data ( see Methods ) . Interestingly , the composite classifier that simultaneously selects one of the 13 classes , has an increased accuracy ( 71 . 55% ± 3 . 07% ) to that of individual classifiers on the same class types ( 61 . 23% ± 2 . 33% ) and it is significantly higher than the baseline ( 37% and 7 . 14% for balanced and imbalanced baseline accuracy , respectively ) . Altogether , the results suggest that multiple environmental and cellular features of an organism can be precisely predicted from a set of individual classifiers , by using a small , targeted gene set . Table 2 and S6 Table contain the contingency tables of each classifier and Fig . 3D depicts the corresponding ROC and PR curves [36] . The overall AUC of the ROC curves exceeds 0 . 82 , except in the case of stationary phase ( 0 . 71 ) . This result is likely due to the high noise level and low sampling size for that class , which dilutes discriminatory features between the mid/late exponential and stationary phases . In the contingency table of the composite classifier ( Table 2 ) , the lowest classification case was observed in the case of “Others” ( 58/179 samples ) . This is expected , since that class corresponds to samples that either are missing data or represent classes that have low sample sizes and are grouped together . Next , we investigated which genes have the highest information content and the respective pathways they belong to . The decrease of mutual information in ranked genes follows an inverse logarithmic relationship ( Fig . 4A and S5 Table ) . For each classifier , we selected the gene subset that accounts for the top 10% of the mutual information content of all genes , yielding feature sets that range from 49 to 136 genes . The overlap among classifiers is substantial: 141 out of a total 715 informative genes ( 19 . 7% ) are present in two or more different classifiers ( Fig . 4B ) . Functional enrichment analysis of the most informative genes reveals a rich repertoire of biological processes where their differential enrichment is discriminative of each specific class ( Fig . 5 , S7 Table ) . Not surprisingly , in the case of the aerobic respiration classifier enriched functional categories include cellular respiration ( P < 3 . 1 × 10−4 ) . Similarly , for phase and strain classifier , organic acid biosynthesis ( P < 2 . 7 × 10−4 ) and nitrogen biosynthesis ( P < 1 . 2 × 10−3 ) are up-regulated , respectively . Genes that are related to carbohydrate metabolism ( P < 6 . 1 × 10−7 ) are noticeably most informative to classify different carbon sources as well as strains . Some functional characteristics were statistically significant across multiple classifiers , including cell wall/peptidoglycan ( P < 2 . 7 × 10−7 ) and ATP-binding ( P < 1 . 5 × 10−8 ) , hydrolases ( P < 9 . 1 × 10−6 ) , membrane ( P < 4 . 1 × 10−6 ) , ribosome ( P < 2 . 2 × 10−7 ) and transport ( P < 4 . 2 × 10−6 ) ( Fig . 4C ) . The global pathway map in Fig . 5 depicts that most informative genes that were found to belong in five pathway groups: biosynthesis , signal transduction , degradation , transporter and central metabolism . For the composite classification of medium , strain and phase , relevant pathways are implicated with signal transduction , degradation , and transport ( Fig . 5A ) . Moreover , genes for phase classification are enriched in biosynthesis ( P < 4 . 3 × 10−7 ) which is in agreement with previous studies that report the prevalence of phase-dependent transcriptional regulation in a variety of biosynthetic processes [37–39] . Fig . 5B provides a more detailed view of the regional network involved in biosynthesis and transport , highlighting the pathways that would be most informative to classify various bacterial characteristics . Highly informative genes involved in specific pathways ( e . g . glutamate biosynthesis I , histidine , purine , and pyrimidine biosynthesis and glycerol-3-phophate/glycerol phophodiester ABC transporter ) have a crucial role from a functional network perspective , either by being a hub or their first-order neighbors in an identical pathway group . The analysis of the most informative genes for the media classifier reveals 14 genes encoding for membrane transporters and 7 involved in nitrogen metabolism ( Fig . 4 , S7A Table , S1 Text ) . From this set , five are implicated in amino acid transportation and synthesis ( gltK , gltJ , gltL , dppF , glnD ) . Different media contain different amounts of amino acids and nutrients required for bacterial growth so the activation of their biosynthesis is expected to be an informative feature about the media where bacteria are growing . Another 3 genes are involved in the enterobactin synthesis ( entA , entE , fepA ) , a siderophore that has been very recently revealed to be related to the growth of E . coli in M9 [40] . Over the course of the growth curve , the metabolic pathways change in order to optimize the use of the available nutrients and to ensure survival under stress conditions . The major transcriptional regulator for the entry into stationary phase is RpoS and , as expected , it is present in the set of genes informative for growth phase , along with several genes belonging to its regulon like dnaK , clpx , hemL , dps , rpsK , hfq , rplA , crr , rpsE and gapA [41] . In this set of genes , there are also genes already described to be differentially expressed in stationary phase , like hpf , crr and sspA [42–44] . In addition , ribosomal proteins ( rpsL , rpsQ , rpsE , rplA , rplT , rpmJ , rrsG ) are also implicated to be phase-dependent , which is in agreement with previous reports [45] . In the case of the strain classifier , the analysis displays a wide variety of genes involved in different pathways and cellular processes . Different strains have evolved differentially from their common ancestor and , hence , have developed different regulatory pathways for various processes including carbon assimilation , degradation , and membrane formation . All informative genes for the medium classifier ( S7A Table ) are included at the top 10% informative genes of the composite classifier with all remaining genes being part of metabolic processes ( S7D Table ) . Environmental perturbations , such as carbon source and oxygen abundance , give rise to informative genes that are specific to those cellular processes ( S7F Table and S7G Table , respectively ) . In the case of oxygen , GO analysis reveals 8 genes involved in the respiratory process , 4 in aerobic respiration ( sucA , acnB , nuoJ , cyoE ) and another 4 in fermentation ( hycC , hycE , hycF , fhlA ) . For carbon source prediction , we can find 15 proteins associated with membrane formation , with 6 of them described transporters ( atpC , kgtP , rhtB , lptG , malF , malG ) . In addition , 5 differentially expressed genes involved in carbohydrate metabolism also stand out ( malS , kgtP , malF , malG , pta ) . Regarding antibiotics , we have tested Norfloxacin , which functions by inhibiting DNA gyrase . Unexpectedly , in its informative gene list we cannot find any gene related to DNA repair or SOS response ( S7E Table ) , possibly because these genes are involved also in other environmental conditions and are not antibiotic-specific . Most of the genes that reveal the presence of Ampicillin are membrane proteins and cell wall proteins which is in agreement with its function as cell membrane inhibitor ( S7H Table ) , including the membrane protein porin ( ompF ) that is known to bind ampicillin [46] . Interestingly , a substantial subset of the informative genes that were selected as features were not differentially expressed in the respective samples ( S2 Table ) . A closer look at those genes , which range from 70% to 18% of the corresponding feature set , reveals that they indeed take part in processes that are characteristic of the respective environmental conditions . For instance , the oxygen classifier contains as features genes that are involved in both aerobic ( cyoD , nuoK , sucD , sucC and cyoB ) and anaerobic respiration ( hycB , menF , nuoK , nfsA , hypA ) , although these genes would not be selected if we ranked based on differential expression . Similarly , in carbon source classification this set includes 11 genes involved in carbohydrate catabolic processes ( dkgB , araG , gatZ , fbaA , malE , murQ , ascF ) and 6 in cellular polysaccharide metabolic processes ( kdsA , kdsD , waaC , waaP , rfaZ , rfa ) . The 24 transporters used for the medium classification , the 5 genes involved in translation for phase classification and 72 membrane proteins that are contained in the antibiotic feature set are indeed expected to be informative in the respective classification task , despite not being in the top differentially expressed genes . The results obtained in this study can be used to decipher novel , condition-specific gene functions . To assess whether biological function can be predicted by targeted experimentation of classifier-specific informative features , we selected one gene with high MI for carbon source classification ( ppiD ) and another gene that is highly ranked for classification between aerobic and anaerobic respiration ( ldcC ) . The MI of each gene is only high in the classifier of interest and not in the rest ( S8 Table ) . We then tested knock-out mutants [47] in their respective conditions . As such , both the ppiD and ldcC mutants and the wild type strain were grown in M9 supplemented with three different carbon sources: glucose , glycerol and lactate . The ldcC mutant functions as a negative control in the case of carbon source classification since this mutation is expected to have no effect on medium determination . Indeed , the results ( S3 Fig . , S12 Table ) show that ΔppiD growth is impaired in the presence of the three sugars ( t – test , P < 0 . 03 ) while growth with the ldcC mutant remains similar to the WT demonstrating the involvement of ppiD in the use of different carbon sources ( t – test , P > 0 . 07 ) . ppiD has been described as a membrane-anchored chaperone [48] but its specific function has not been discovered . Our result suggest that this protein is involved in sugar metabolism , possibly related to folding activity of membrane sugar transporters . Growth curves for knockout replicates of the top five informative genes for different carbon sources , as well as the growth curves for the genes related to aerobic growth genes ( as negative control ) , are shown in S4 Fig . . As expected , growth deficits were more pronounced in the first set in both glycerol and lactate ( t – test , P < 0 . 006 and P < 0 . 008 , respectively ) . We performed a similar experiment where the three strains ( WT , ΔppiD and ΔldcC ) were grown in M9 with glucose in aerobic and anaerobic conditions , in order to assess the influence of the ldcC mutation in these conditions . Here , the ppiD mutant serves as the negative control and the ldcC mutation is indeed informative of the aerobic conditions , although the difference is not as pronounced as in the case of carbon source classification ( P < 0 . 029 for ppiD; P > 0 . 080 for ldcC ) . A closer look at the MI values show that the informative genes for aerobic respiration are two orders of magnitude lower than those for medium , which suggests that information content is dispersed among a number of genes .
How much information regarding the life and the present environmental context can be inferred from the global transcription profile of an organism ? To address this question , we constructed an extensive , annotated gene expression compendium , where we trained Bayesian models for seven distinct classification tasks . Our models achieved high classification performance that was robust on the number of genes that were used as informative features . Our work demonstrates that bacterial transcriptomes embody rich information regarding the organism and the environment that it inhabits . Recent work demonstrates the power of such datasets to identify data-driven ontologies and rethink the definition of biological processes within them [49] . More importantly , multiple characteristics of an organism can be accurately predicted using a set of character-specific classifiers , suggesting practical advantages of this approach over limited datasets . Transcriptional activity is not the sole feature type that conveys predictive information regarding environmental conditions and an organism’s characteristics . Like eukaryotes , epigenetic signals regulate transcriptional activity in bacteria , for example , by altering DNA methylation states to control the binding of proteins to DNA [50] . Single-molecule real-time ( SMRT ) sequencing technology has been recently applied to reading of genome-scale methylation states in a pathogenic E . coli [51] and the technology would provide higher-resolution of molecular information of bacteria , enabling fine-scale predictive characterization based on it . Other features related to the genome-scale metabolic state , proteomic biomarkers and cell morphology can be incorporated to increase the predictive capacity of any given classifier . Similarly , while the six characteristics that we evaluated here are fundamental in their role and indicative of global processes , there are several other environmental and organismal characteristics , such as other abiotic factors or other microbial species in the same environment , which can be predicted from these features . Multiple characteristics of an organism are interrelated , implying its heterologous transcriptional landscapes in different combinations of phenotypic conditions . These complex dependencies in phenome are not readily analyzable even in the compilation of thousands of publicly available transcriptome profiles as the experimental conditions in published data are often disproportionate , typically skewed in favorable settings ( e . g . MG1655 strain over LB medium ) , which produces small sample sets or even empty sets in combinatorial conditions . Indeed , the results on composite classification argues that with the current omics dataset compilation , it is not feasible to explore many of the strain , phase , medium combinations , as we have sufficient data for only 13 classes , out of a total of 48 possible classes ( 4 for each of medium , phase , strain ) . Interestingly , the performance of the composite multi-class classifier performs significantly better for the overall classification of these characteristics , than an aggregate of individual classifiers for phenotypes , demonstrating large interdependencies across different conditions . By looking at the top informative genes in two classifiers , we demonstrated the involvement of the ppiD in the utilization of different carbon sources . Further analysis involves the use of over/under-expressed copies and protein-protein assays to discover quantitative associations and interaction partners . By analyzing the expression levels of the genes in the phase classifier that are not predictable using RT-PCR and transcriptional fusions we can find out novel regulation when growth phase changes from exponential to stationary . Another potential application is in the case of the antibiotics Ampicillin and Norfloxacin where this analysis can be used to identify implicated pathways in lethal and non-lethal concentrations . In recent years , the capacity of microorganisms to sense and act upon environmental stimuli [52] has sparked renewed interest due to its diverse applications in preventive medicine and synthetic biology [53 , 54] . These studies shed light on the adaptive behavior of cells under environmental temporal stimuli [55–57] and on the decomposition of promoter activity in complex conditions [58] . Our work here is the first that attempts to identify and comprehensively interpret the capacity of the transcriptome for characterizing a manifold of environmental conditions using the consensus of multiple statistical learning algorithms . Aside from its intellectual merit , the presented work can help building classifiers and selecting features in a number of practical applications . Detection and characterization of microbes are of great importance in many clinical , environmental , industrial , and agricultural application [59] . Data are increasingly become available for the adoption of such classification techniques since high-throughput methods have been recently applied at low cost . From battlefields to agricultural crop management , inexpensive sequencing transforms the landscape of what is possible in a timely , inexpensive manner . Our work paves the way towards the use of high-throughput expression datasets to a broad range of applications including detection and characterization of the environmental conditions and bacterial population that are important for clinical , environmental , industrial , and agricultural applications . Without loss of generality , this work can be described as a data-driven approach to “bacterial forensics” , i . e . the extraction of environmental knowledge from large-scale phenotypic bacterial data , and it can have far-reaching applications in environments that would be challenging to investigate otherwise .
We downloaded 83 RNA-Seq E . coli transcriptional profiles from 17 different GEO entries [30] that correspond to 8 strains , LB and MOPS media in wild-type ( WT ) , gene knock-outs ( KOs ) , double KOs and environmental perturbations . When bedGraph format was used in the data , gene expression level was measured in RPKM using the bgrQuantifier program that is part of the RSEQ tool [60] . For other formats such as wig , we first converted them into bedGraph . We filtered out samples where the environmental information was not known , which led to 64 samples for further analysis . Data were converted to log2 scale and performed quantile-normalization using MATLAB . The resulting RNA-Seq dataset was composed of 64 samples of 4725 genes . We integrated the RNA-Seq dataset ( 64 samples ) to the E . coli Microarray Compendium ( EcoMAC ) that consists of 2198 microarrays of 4189 genes for which raw files were downloaded and normalized by RMA ( robust multichip average ) method [29] . The integrated EcoGEC dataset consists of 2262 samples and 4166 genes ( Fig . 1A , S13 Table , S14 Table ) . Although integrative analysis of multiple microarray gene expression ( MAGE ) datasets allows to distill the maximum relevant biological information from genomic datasets , the unwanted variation , so-called batch-effects arising from data merged from difference sources has been a major challenge to impede such effort [61] . To adjust the non-biological experimental variation with the consideration of large number of datasets with a few samples , we used ComBat that is developed under Bayesian framework and is known to be robust to outliers in small sample sizes [62] . In the process of adjustment , we took into account experimental conditions as covariates to prevent loss of biological variations . Prior to building a prediction model , we transformed the adjusted gene expression data into categorical values ( under-expressed , UE; wild-type , WT; over-expressed , OE ) in order to deal with biases arising from combining different platforms and improve the classification accuracy [63] . We first measured the log2 Fold Change ( FC ) of gene expression with respect to the WT expression for each gene . WT samples were identified from experiments that didn’t undergo genetic and environmental perturbations from the three platforms ( 7 for Affymetrix E . coli Antisense Genome Array , 6 for Affymetrix E . coli Genome 2 . 0 Array , and 6 for RNA-Seq ) . log2 Fold Change ( FC ) was separately measured for each platform by comparing the mean of WT data . Using transformed data , we estimated a normal distribution N ( μ , σ2 ) for each gene and finally converted each log2 FC gene value into one of the 3 categorical values by measuring deviation from the mean ( UE when gij < μi – σi; WT when μi – σi ≤ gij ≤ μi + σi; OE when μi + σi < gij; gij is the log2 FC for gene i in sample j , μi is mean of gene i and σi is standard deviation of gene i ) . The platform-specific categorization of gene expression effectively removes platform biases ( Fig . 1B ) . The large fraction of unannotated phase data in the compendium hinders the maximum utilization of such resource . Missing phase information was imputed by iterative learning approach in which prediction model for growth phase is trained using the annotated phase data and inferred data in previous iteration until prediction of unknown data finally reaches at convergence ( S1 Fig . ) . In each iteration , the experiments that were unannotated ab initio were repeatedly inferred . Inference is based on consensus-based approach of four machine learning methods described above . Re-labeled phase information accompanying with annotated data is used for training the consensus model in next iteration . This procedure is halted once the similarity of phase labels between consecutive iterations is convergent when the similarity of phase labels between consecutive iterations converges ( change in fraction < ξ , where ξ = 0 . 01 here ) . Although the use of inferred labels through iterative learning demonstrates an increased performance , compared with the prediction using known labels only ( S2 Table ) , we report the performance for phase prediction using annotated labels only throughout the manuscript . To investigate the accuracy ( balanced ) of inference of unannotated data , we performed the simulation study for each classifier by randomly masking 30% of total labels of each class . First , the accuracy of inferred annotation after iterative learning is measured by comparing with real labels before and after iterative learning ( S2 Table ) . Then we further evaluate iterative learning for by changing the percentage of unannotated labels ( 2% , 5% , 10% , 20% ) in the total data ( S2 Fig . and S4 Table ) . A label is assigned for each of the seven classification characteristics ( two for antibiotics; Ampicillin and Norfloxacin ) . We have identified 4 classes for medium ( LB , M9 , MOPS , others ) , 3 classes for phase ( early-exponential , mid/late-exponential , stationary ) having both annotated and predicted data , and 4 classes for strain ( MG1655 , BW25113 , EMG2 , others ) . A class of “others” was added that corresponds to conditions that are unclear or scare in quantity . Classification of the strain , medium , and growth conditions can be integrated also as a multi-class problem . We synthesized a new predictor variable called composite by combining values of 3 characteristics . From the 48 possible classes ( combination of 4 labels for medium , 3 labels for phase , 4 labels for strain ) , only 13 combinations have enough data ( more than 5 samples ) for training , hence we have encompass all other labels with insufficient data under the label “others” , resulting in a total of 13 classes ( Table 2 ) . We use Naïve Bayes ( NB; [64] , Decision Trees ( DT , [65] ) , K-nearest-neighbors ( KNN , [66] ) and Support Vector Machines ( SVM , [67] ) to construct a consensus classification scheme [68] . The class label assigned is the one with the highest number of votes . The predictive power is assessed through Receiver-Operator Characteristic ( ROC ) and Precision-Recall ( PR ) curves [36] . For multi-class problems , such as in the case of medium , phase and strain classification , we built ROC/PR curves in a one-versus-rest ( OVR ) approach . The leave one batch out cross validation was conducted to verify model performance while removing batch effects . For this , each batch is left out for testing and the rest of data is then used for training . This procedure is iterated until all batches in the dataset are tested . For carbon source , phase , and composite classifier , the profiles having early-exponential phase or acetate are studied in a single project so inevitably , we had to rely on the batch-uncontrolled cross-validation . The classifier performances with and without batch control are compared in S11 Table . As the high imbalance of class distribution is observable in the dataset as shown in Table 1 , creating inflated baseline , we show the classifier performance for the original dataset as well as for the dataset with balanced class distribution . Mutual information is a stochastic measure of dependence [69] and it has been widely applied in feature selection in order to find an informative subset for model training [70] . In our work , each of the eight models were trained with the top k-ranked genes based on their mutual information ( MI ) to the label where MI is measured by I ( X;Y ) =∑∑p ( x , y ) log ( p ( x , y ) /p ( x ) p ( y ) ) Where x is the gene selected and y is the predictor variable . This process is iteratively repeated by increasing k with an interval of 10 and the exception of start ( 10 ) and end points ( all genes ) . Basically , the selection procedure of k features are performed in training data only and k showing the highest performance is selected for testing . All the analyses in this study other than the cross-validation of model used the features selected from the complete data . The most informative genes are selected by measuring the mutual information ( in bits ) for each of the characteristic variables and then selecting the top 10% genes based on their information content . These top informative genes are then used for finding shared genes across different classifiers ( Fig . 4B ) and for network analysis ( Fig . 5 ) . For functional enrichment analysis , we use all selected genes that optimize the classifier performance . Associated functional annotations for the set of selected genes for each of the classifiers are found by DAVID [71] . Various annotations including Gene Ontology terms , KEGG pathways , and InterPro protein domains are investigated . Among them , the 6 most statistically significant terms ( P < 3 . 7 10−4 ) for each classifier are displayed in Fig . 4 . Global map of genetic interactions for E . coli is reconstructed from [72] with pathway modules that functionally cluster genes based on the Pathway Ontology and transporter complexes curated in EcoCyc [73] . Pathway diagrams were re-plotted from the KEGG database [74] . In addition to DAVID , we have performed a GSEA analysis [75] where each gene is ranked by its mutual information ( S9 Table ) . We have also compared the results to those obtained by DAVID and provide this comparison in S10 Table . On average , 80 . 5% of DAVID results that correspond to the feature set at optimal classification performance are in the GSEA enriched terms . Growth curves of the WT , ΔppiD and ΔldcC were performed in M9 complemented with 0 . 4% of glucose , glycerol and sodium lactate . For growth curves , the starter cultures of all strains were grown and therefore adapted ( B7–9 generations ) to M9 glucose for 12 hours at 37C . Cultures were started at OD600 of 0 . 004 . OD600 was measured every 10 minutes on a Tecan Plate Reader . Two independent replicate growth tests were performed for each strain . For the anaerobic and aerobic growth curves bacteria were grown in M9 supplemented with glucose at 37C without shaking . The anaerobic growth was made in an anaerobic chamber where media was inserted 2 days prior to the experiment to extract all the oxygen present in the media . Samples were taken at 2 , 8 and 24 hours through a spectrophotometer ( S12 Table ) . For consensus-based prediction using four different classifiers , we used the Statistics Toolbox in MATLAB . For the multi-class SVM , one-versus-rest ( OVR ) approach was used in which for each class , a binary classifier is built for the class label and the rest . Each binary SVM was built using Gaussian Radial Basis Function ( RBF ) kernel and the default sigma factor of 1 was used . For soft margin , C parameter showing best performance was selected in the range of 0 . 5 to 4 in the training phase . For KNN , K was set to one in knnsearch . For decision tree and naïve Bayes , the default settings in ClassificationTree and NaiveBayes were used , respectively . The code used in this study including the imputation by iterative learning and the consensus-based prediction that allows users to reproduce the results is freely available on gitHub ( https://github . com/minseven/mForensics . git ) . | The transcriptional profile of an organism contains clues about the environmental context in which it has evolved and currently lives , its behavior and cellular state . It is yet unclear , however , how much information can be efficiently extracted and how it can be used to classify new samples with respect to their environmental and genetic characteristics . Here , we have constructed an extensive transcriptome compendium of Escherichia coli that we have further enriched via an iterative learning approach . We then apply an ensemble of various machine learning algorithms to infer environmental and cellular information such as strain , growth phase , medium , oxygen level , antibiotic and carbon source . Functional analysis of the most informative genes provides mechanistic insights and palpable hypotheses regarding their role in each environmental or genetic context . Our work argues that genome-scale gene expression can be a multi-purpose marker for identifying latent , heterogeneous cellular and environmental states and that optimal classification can be achieved with a feature set of a couple hundred genes that might not necessarily have the most pronounced differential expression in the respective conditions . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Microbial Forensics: Predicting Phenotypic Characteristics and Environmental Conditions from Large-Scale Gene Expression Profiles |
Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health . Although several strains of these viruses had been isolated in Iran in the late 1970's , there was no recent data about the present situation at the outset of this study . Entomological investigations performed in 2009 and 2011 in Iran collected 4 , 770 sandflies from 10 different regions . Based on morphological identification , they were sorted into 315 pools according to species , sex , trapping station and date of capture . A phlebovirus , provisionally named Dashli virus ( DASHV ) , was isolated from one pool of Sergentomyia spp , and subsequently DASHV RNA was detected in a second pool of Phlebotomus papatasi . Genetic and phylogenetic analyses based on complete coding genomic sequences indicated that ( i ) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV] , ( ii ) there is a common ancestor to DASHV , Sandfly fever Sicilian- ( SFS ) and SFS-like viruses isolated in Italy , India , Turkey , and Cyprus ( lineage I ) , ( iii ) DASHV is more distantly related with Corfou and Toros viruses ( lineage II ) although common ancestry is supported with 100% bootstrap , ( iii ) lineage I can be subdivided into sublineage Ia including all SFSV , SFCV and SFTV except those isolated in Iran which forms sublineage Ib ( DASHV ) . Accordingly , we suggest to approve Sandfly fever Sicilian virus species consisting of the all aforementioned viruses . Owing that most of these viruses have been identified in human patients with febrile illness , DASHV should be considered as a potential human pathogen in Iran .
The genus Phlebovirus , family Phenuiviridae currently contains 9 recognised virus species ( grouping 37 viruses ) , and 33 tentative species [1] . At least 9 new viruses ( Adana , Alcube , Arrabida , Fermo , Granada , Medjerda Valley , Punique , Toros , Zerdali ) have also been isolated and appear to belong to the three groups primarily transmitted by phlebotomines in the Old World [2–9] . In the Old World , sandfly-borne phleboviruses are distributed in the Mediterranean region , Africa , the Indian subcontinent , the Middle East and central Asia , where they are transmitted by sandflies belonging to the genera Phlebotomus and Sergentomyia . In contrast , New World sandfly-borne phleboviruses are transmitted by phlebotomines of the genus Lutzomyia . There is a strict discrimination between Old World and New World phleboviruses due to the exclusive distribution of their respective vectors . Current , phleboviruses pathogenic for humans include: ( i ) Alenquer ( ALEV ) , Candiru ( CDUV ) , Escharte ( ESCV ) , Serra Norte ( SRNV ) , Morumbi ( MRBV ) , Maldonado ( MLOV ) , Chagres ( CHGV ) , Adria ( ADRV ) , Naples ( SFNV ) , Sicilian ( SFSV ) and Toscana viruses ( TOSV ) , all of which are transmitted by sandflies , ( ii ) Punta Toro ( PTV ) and Rift Valley fever ( RVFV ) viruses which are transmitted by mosquitoes , ( iii ) Bhanja ( BHAV ) , Severe fever thrombocytopenia syndrome ( SFTSV ) , and Heartland ( HRTV ) viruses which are transmitted by ticks [10–15] Amongst the Old World sandfly-borne phleboviruses , two species ( Sandfly fever Naples and Salehabad ) and two tentative species ( Sandfly fever Sicilian [SFSV] and Corfou [CFUV] ) are listed in the IXth report of the International Classification for Taxonomy of Viruses ( ICTV ) [1] . SFSV and SFNV are associated with self-limiting febrile illness , whereas Toscana virus ( TOSV ) is often associated with neurological manifestations either central or peripheral [16]; TOSV is the most prevalent sandfly-borne arbovirus in Europe , particularly in countries bordering the Mediterranean [17] . Although SFNV , discovered in 1942 during World War II ( WWII ) , was for a long time considered to be a prominent cause of incapacitating fever in the Mediterranean region , the last reported case was confirmed in 1990 [18] . It is not impossible that SFNV would have gone extinct since . In contrast , SFSV remains endemic in the Mediterranean basin , the Middle East , Central Asia and Europe [17] . SFSV was first isolated from the sera of a sick US soldier in Egypt in 1943 during WWII , and later was isolated again in Sicily during an outbreak of febrile illness among US-army troops [19] . There is accumulating direct ( virus isolation or molecular detection ) and indirect ( seroprevalence studies ) evidence that viruses closely related to but clearly distinct from SFSV are widespread in the Mediterranean region and the Middle East . Outbreaks and sporadic human cases occurred in Cyprus ( Sandfly fever Cyprus virus [SFCV] ) , in Turkey ( Sandfly fever Turkey virus [SFTV] ) , in Ethiopia ( SFSV-Ethiopia ) [20–23] . Corfou virus [CFUV] , discovered in 1985 in Phlebotomus neglectus on the eponymous Greek island , was never associated with human infection [24]; however , viral RNA was detected in the CSF of a patient and the corresponding virus was provisionally named Chios-A virus; sequences of CFUV and Chios-A virus were very similar [3 , 25] . It is also important to underline that neutralisation test can easily distinguish SFSV from CFUV , despite less discriminative serological methods ( ELISA , HI , IIF , CF ) cannot [24] . Several pheboviruses have been isolated from sandflies in Iran: SALV , KARV , and THEV in 1959 , and SFSV in 1975 [26] . Active circulation of these viruses and SFNV was also supported by finding neutralizing antibodies in human sera [27 , 28] . To investigate whether these viruses or new ones are currently circulating in sandflies in Iran , field campaigns were organized in different localities during the summers of 2009 and 2011 . This article presents the molecular detection , virus isolation , complete genome sequencing and subsequent genetic and phylogenetic analysis of a novel SFSV-like virus , provisionally named Dashli virus ( DASHV ) from the village of Dashliborun where infected sandflies were collected .
A total of 4 , 770 ( 3 , 158 females and 1 , 162 males ) sandflies were collected and identified morphologically . They were allocated to 315 pools ( 198 female and 117 male pools ) . The number of sandflies and pools originating from individual villages are shown in Table 1 and Fig 1 . The most abundant species were P . papatasi ( 57 . 57% ) and Sergentomyia spp . ( 31 . 05% ) . The less abundant species were; P . alexandri , P . mascitti , P . tobbi , P . mongolensis , P . sergenti , P . caucasicus , P . major , P . bergeroti , and P . kandelakii . Pool #131 that consisted of 30 non-engorged female Sergentomyia spp . trapped in the Shordakesh in Dasliboroun village , in July 2011 was positive with primers pair N-Phlebo1S/ 1R [29] . The resulting 502-nt sequence in the polymerase gene was most closely related to Sandfly fever Turkey virus ( SFTV—GenBank acc no: GQ847513 ) with sequence identities of 94% and 81% at the AA and nt levels , respectively . Using the rt-RT-PCR assay designed for the specific detection of DASHV , pool #131 was confirmed as positive and pool#94 was also found positive ( Ct values < 28 ) . Four-fold dilutions of the total nucleic acids derived from these 2 pools were tested using DASHV rt-RT-PCR , and dilutions up to 1:1 , 024 were positive ( 1:4 , 096 dilution was negative ) with Ct values ranging from 25 . 78 to 34 . 65 ( S1 Fig ) . Pool # 94 consisted of 30 non-engorged females of P . papatasi which were also collected at the same location as pool #131 on the same day ( 06 July 2011 ) . The rt-RT-PCR positive product of pool#94 was sequenced and the obtained 128 nucleotides were 100% identical with the homologous sequence corresponding to pool#131 . Assuming that only one sandfly was infected in each of the pools #94 and #131 , the global sandfly infection rate for the DASHV in this study was estimated to be 0 . 04% . When considering only Phlebotomus spp ( not Sergentomyia spp ) in the Golestan region , the infection rate raised to 0 . 22% ( 2/904 ) . The 12 . 5 cm2 flask of Vero cells inoculated directly with pool #131 showed a clear cytopathic effect ( CPE ) at day 4 after inoculation . The supernatant was used to seed one passage into 12 . 5 cm2 flask and this was done again until passage 4 . Freeze-dried vials of infectious supernatant medium were prepared and included in the collection of the European Virus Archive ( www . european-virus-archive . com/ ) where they are publicly available for academic research . Pool#94 was also inoculated onto Vero cells but neither CPE nor viral RNA could be detected after 4 consecutive passages . The complete genomic sequence of DASHV consisted of 6 , 444nts , 4 , 413 nts and 1 , 802 nts for the L , M and S segments , respectively ( GenBank acc . no KP771821 , KP771822 , and KP771823 ) . The polymerase gene encoded a 6 , 270-nt long ORF ( 2 , 090 AA ) , whereas the glycoprotein gene encoded a 1 , 342-nt long ORF ( 4 , 026 AA , further cleaved into a 531-AA long Gn and a 478-AA long Gc ) . The small segment encoded a 738-nt and an 801-nt long ORF which were translated to nucleocapsid protein ( 246 AA ) and nonstructural protein 267 AA ) , respectively . Pairwise distances of the nt- and AA-sequences are presented in S1 Table . Amino acid distances between DASHV compared with SFSV , SFTV and SFCV were ≤19 , 8% ( L ) , ≤39 , 7% ( Gn ) , ≤31 , 6% ( Gc ) , ≤15 , 0% ( N ) , and ≤36 , 2% ( NS ) . Amino acid distances between DASHV and other phleboviruses were much higher: ≥43 , 2% ( L ) , ≥61 , 5% ( Gn ) , ≥45 , 4% ( Gc ) and , ≥ 46 , 9% ( N ) , ≥73 , 5% ( NS ) . Gene by gene comparative distance analysis showed that pairwise distances of DASHV vs SFSV and SFS-like viruses were consistently lower than the lowest distances observed between DASHV and phleboviruses other than SFSV / SFS-like viruses . The distances between DASHV and SFS-like viruses from outside Iran were between 4 . 5–19 . 8% and 18 . 3–29 . 6% for the AA and nt sequences of the L , M , and S proteins ( S1 Table ) . However these distances dropped to 0 . 0% and 9 . 3% for the N protein and 4 . 2% and 12 . 6% for the Ns protein , for AA and nt , respectively . In addition , the lowest interspecific distances; 40 . 0% ( L ) , 46 . 2% ( Gn ) , 33 . 6% ( Gc ) , 35 . 8% ( N ) , and 54 . 8% ( Ns ) among ICTV-recognized phlebovirus species [2] were higher than the lowest distances observed between DASHV and SFSV / SFS-like viruses . In addition , the lowest interspecific distances; 40 . 0% ( L ) , 46 . 2% ( Gn ) , 33 . 6% ( Gc ) , 35 . 8% ( N ) , and 54 . 8% ( Ns ) among ICTV-recognized phleboviruses [2] were higher than the highest distances observed between DASHV and SFSV / SFS-like viruses . ICTV recognized species are clearly segregated in the phylogenies where they are supported by high bootstraps ( 100% ) except for RVFV; thus our results are congruent with the previously reported topologies [14 , 15 , 30 , 31] . Regardless of the gene used , DASHV clustered with following viruses: SFSV from Iran , Italy , Ethiopia , SFCV , SFTV , CFUV and TORV , as supported by 100% bootstrap ( Figs 2–7 ) . Within this group , two lineages consisting of DASHV , SFSV strains , SFCV and SFTV on one hand ( I ) , and of CFUV and TORV strains one the other hand ( II ) were also consistently observed and supported by 100% bootstrap values ( Figs 2–7 ) . Complete coding sequences of N and Ns genes were available for the aforementioned strains , but also for 6 additional strains consisting of 3 strains from Cyprus , 2 from Iran , 1 from India ( Fig 5 & Fig 6 ) ; here , DASHV was consistently grouped with the two other Iranian strains ( sublineage Ib ) which are clearly distinct from other SFS-like viruses from Italy , Cyprus , Turkey , and Ethiopia ( sublineage Ia ) . Characteristics of these sequences are presented in S2 Table . The corresponding phylogenetic tree is presented in S2 Fig . As shown in the complete sequence phylograms , DASHV is clearly distinct from other viruses , which were split into 3 groups supported by bootstrap value >70%: ( i ) lineage I ( 99% bootstrap support ) consisted of 11 sequences ( lineage Ia ) representing SFSV-Italy , SFSV-Ethiopia , SFSV-Tunisia , SFSV-Algeria , SFCV , and SFTV and of DASHV sequence ( lineage Ib ) ; ( ii ) lineage II was splitted into 3 sublineages , lineage IIa consisted of CFUV and the unique sequence of Chios-A virus ( Greece ) [32] , lineage IIb consisted of 7 sequences of Utique virus [9] , lineage IIc consisted of Toros virus together with two sequences of Girne 2 virus ( Northern Cyprus ) [32] . Regardless the protein used for analysis ( L , N , Ns , Gn , Gc ) , distances observed between among DASHV , SFSV , TORV and CFUV were lower than the highest intraspecific distances . Of the 5 genes studied , L and N were the most suitable to determine cut-off values amenable to all phleboviruses . Using the complete polymerase gene AA sequences ( Fig 8A ) , the cut-off value can be set at 0 . 35 for defining existing species: regarding SFSV , the highest genetic diversity is 0 . 206 supporting that DASHV , SFSV variants , Corfou and Toros viruses should be considered as members of the same species . The lowest genetic distance between these viruses and other phleboviruses are ≥0 . 435 ( with mosquito- and sandfly-borne viruses ) and ≥0 . 638 ( with tick-borne phleboviruses ) Using the complete Nucleoprotein gene AA sequences ( Fig 8B ) , the cut-off value can be set at 0 . 35 for defining existing species: regarding SFSV the highest genetic diversity is 0 . 16 supporting that DASHV , SFSV variants , Corfou and Toros viruses should be considered to belong to the same species . The lowest genetic distance between these viruses and other phleboviruses are ≥0 . 429 ( with mosquito- and sandfly-borne viruses ) and ≥0 . 616 ( with tick-borne phleboviruses )
Genetic and phylogenetic analysis based on the complete coding sequence of the 5 viral genes together with homologous sequences of other phleboviruses indicates that DASHV belongs to a monophyletic group ( 100% bootstrap ) consisting of several sandfly-borne phleboviruses: SFSV strains isolated in Italy and Ethiopia , SFTV ( Turkey ) , SFCV ( Cyprus ) , Corfou virus isolated in the eponymous Greek island , and Toros virus isolated in southern Anatolia ( Turkey ) . Phylograms ( Fig 7 ) show that DASHV is consistently more closely related with SFSV , SFTV and SFCV ( lineage I ) compared with Corfou and Toros viruses which form a distinct lineage ( lineage II ) . The dichotomy of DASHV and SFSV ( lineage I ) vs Toros and CFU ( lineage II ) is consistently observed regardless the gene used for analysis ( Fig 7 ) . In the S segment protein analysis DASHV grouped with two SFSV viruses isolated in Iran in 1975 from Phlebotomus spp . ( Fig 5 & Fig 6 , Genbank acc no EF201823 and EF201824 ) [33] . Currently , there are no sequences available for the L and M segment proteins of these viruses . The distances between DASHV and other lineage I sequences corresponding to viruses circulating outside of Iran ranged 4 . 5–19 . 8% and 18 . 3–29 . 6% for the AA and nt sequences of the L , M , and S proteins ( S1 Table ) . In contrast , distances observed between DASHV and SFSV strains originating from Iran were lower than 0 . 0% and 9 . 3% for the N protein and 4 . 2% and 12 . 6% for the Ns protein , for AA and nt , respectively . Since the 3 Iranian strains are most closely related to each other than to any other phlebovirus , we propose to consider them as variant strains of DASHV which will be considered as a separate sublineage ( Ib ) within lineage I . Sublineage Ib is supported by 100% bootstrap values in N and Ns gene ( sublineage Ib ) . Sublineage Ia includes all other SFSV and SFS-like viruses ( SFTV , SFCV ) ( Figs 2–7 ) . Obviously , during the past 40 years DASHV has evolved relatively slowly as showed by low sequence diversity ( Fig 5 & Fig 6 , S1 Table ) . Fig 8 correspond to the phylogenetic tree obtained with all publicly available sequences ( partial and complete ) of the polymerase gene; most of these sequences were obtained by using the RT-PCR assay designed by Sanchez-Seco et al . [29] ( 2003 ) . The topology of the lineage I was unchanged although additional sequences obtained from Tunisia , and Algeria were included ( S2 Fig ) . In contrast , 9 additional sequences clusterized within the lineage II which corresponded to Utique virus RNA ( 6 sequences; all detected in Tunisia ) [34] , Girne-2 virus RNA ( 2 sequences detected in north-eastern Turkey ) [32] , and Phlebovirus Chios-A RNA ( 1 sequence detected in the CSF of a Greek patient ) . When looking at Fig 8 , it appears that lineage II may be divided into 3 sublineages although they are based on a 160-nt based analysis . Whether or not lineage II can be subdivided into at least 3 sublineages has to be confirmed when complete genomes will be sequenced . Although discovered seventy years ago , SFSV remains a tentative species within the genus Phlebovirus . Corfou virus , discovered in 1981 , is in the same situation . Taking advantage of the recent increased number of complete sequences , we propose to consider that SFSV together with SFCV , SFTV and DASHV can represent a single species that could be named Sandfly fever Sicilian virus by analogy with the Sandfly fever Naples species . Whether CFUV and Toros viruses should be included in the Sandfly fever Sicilian virus species can be discussed; in our opinion , we would be inclined to merge all of these viruses in the same species , and to act as lumpers rather than splitters . However , it would be wise to wait for additional complete genome sequences of viruses included in the lineage II such as Chios , Utique and Girne 2 ( S2 Fig ) . In Iran SFSV was isolated from P . papatasi and Phlebotomus spp . [28 , 33] . In our study , the positive pools consisted of unengorged female P . papatasi and Sergentomyia spp . Sandfly-borne phleboviruses do not appear to possess a very restricted vector association: ( i ) SFTV and Corfou viruses were isolated from P . major complex sandflies in Turkey [35] and in Greece [24]; ( ii ) Sicilian-like virus sequences were detected in P . ariasi in Algeria [36] and also in P . longicuspis , P . perniciosus and S . minuta in Tunisia [9] . Sergentomyia spp . sandflies have long been considered unimportant vectors since they were not believed to feed on humans and mammals , but on reptiles . Recent results are increasingly questioning this point with cumulating evidence that Sergentomyia spp . could play a role in leishmaniasis in certain regions of the world [37–39] . Similarly for viruses , Sergentomyia spp . has been reported to be infected by a variety of different human pathogenic RNA viruses , such as Chandipura virus [40] , Saboya virus [41] , sandfly Sicilian-like virus [9] , Toscana virus , Tete virus , and 2 unclassified viruses ( ArD95737 and ArD 111740 ) [42] . It was recently demonstrated that some Sergentomyia species also feed on humans and/or mammals [43] . Indeed , there are recent direct studies which indicate that Sergentomyia species may be vectors of human and canine pathogens [37–39 , 44 , 45] . Whether future studies demonstrate that DASHV causes disease in humans , then further investigations will be necessary to identify unambiguously the vector . The sandfly infection rate for DASHV ( 0 . 042% ) is comparable with previous studies [8 , 46–50] . However , since the trapping of sandflies in our study was performed in regions where the ecological and environmental conditions are very different , in Golestan the rate of infection in Phlebotomus spp . and Sergentomyia spp . is 1/904 ( 0 . 11% ) and 1/1455 ( 0 . 068% ) , respectively; this suggests important circulation and possibly important exposure for human and non human vertebrates [34 , 50] . This pleads for continuing investigation in this region through seroprevalence studies targeting vertebrates as recently in Europe and Africa . There are persistent evidence that SFSV and SFS-like viruses are occupying a large geographic area from South-western Europe to Middle east including northern Africa [51–53] . The majority of these viruses ( Fig 9 ) cause epidemic or sporadic cases of infection in humans [22 , 23 , 25] . This should be incentive to perform studies in order to determine whether or not DASHV is involved in fever of unknown origin in the region . DASHV is genetically very close with SFSV . Although there is no data supporting that Corfou and Toros virus are human pathogens , there is considerable evidence of SFSV human cases of infection in Italy , Cyprus , Turkey , Ethiopia [18 , 20 , 23] . There is strong evidence that the different variants of SFSV cause febrile illness in humans either in sporadic or in epidemic cases [54] . Therefore , it is likely that DASHV can cause the same type of febrile illness . Seroprevalence studies have shown the presence of specific neutralising antibodies in humans in France , Italy , Cyprus and Israel [55–58] . It is therefore likely that Dashli virus can cause human infections and that these humans infection are probably febrile illness . Cohorts of patients presenting with unexplained fever in regions where sandfly vector are present should be tested for SFSV using PCR or serological techniques . In Iraq , during an outbreak among US Army troops in 2007 , 13 of 14 convalescent sera contained IgM antibodies specific for SFSV [59] . Specific IgG was also detected in Marine soldiers after self-reported febrile illness cases [60] . A variant strain of SFSV was also isolated from a human serum during an important outbreak in Ethiopia [23] . Accordingly , DASHV has the potential to cause human disease , which should be investigated through seroprevalence studies in Iran , specifically in Golestan . In addition , it would be worthwhile to develop a diagnostic test based on real-time RT-PCR to screen acute cases of febrile illness in the region where the virus has been isolated . The system that is described here was designed exclusively for DASHV . Because of several mismatches in the primers and probe sequences , it is likely to be of limited interest for the detection of the other viruses of the species . However , a real-time RT-PCR assay ( detecting DASHV , SFSV , TORV and CFUV ) has recently been described and could greatly help to better understand the medical impact of these viruses [51 , 52] . In summary , a sandfly Sicilian-like phlebovirus was isolated from a non-engorged female pool of Sergentomyia spp and was detected in a non-engorged female pool of P . papatasi trapped in the Shordakesh in Dasliboroun village , in Iran . Its genetic characterization through complete sequencing of the three gene segments revealed that DASHV is closely related to other members of the Sandfly fever Sicilian virus species group . Further sandfly collections are required to strengthen our understanding of the circulation of DASHV and to update our knowledge of the distribution of sandfly-borne phleboviruses in Iran . Serological studies among animal and human populations are also required to investigate the pathogenicity of DASHV and its capacity to infect humans and other vertebrates since all the SFS-complex viruses with which it is closely related are pathogenic for humans .
Sandflies were trapped in several cities and villages from 10 provinces in Iran ( Fig 1 ) using CDC Miniature Light Traps as previously reported [35] from June to September in 2009 and in 2011 . Individual sandflies were identified using a stereomicroscope according to morphological characteristics [61 , 62] . After identification , they were pooled based on species , sex , and location with up to 30 individuals per pool and placed in 1 . 5 ml tubes before storage at -80°C . When trapping was done in private areas , owners/residents were informed an gave oral permission for the study to be conducted on their land/in their residences . Pools of sandflies were homogenized in a final volume of 600μL as previously described [30] and 200-μL of the aliquot was used for viral nucleic acid ( NA ) extraction using the BioRobot EZ1-XL Advanced system ( Virus Extraction Mini Kit , Qiagen ) . Five μL of NA was used for RT-PCR and nested-PCR assays with primers and protocols previously described [29 , 48] . PCR products of the expected size were column-purified ( Amicon Ultra Centrifugal filters , Millipore ) and directly sequenced . A real-time ( rt ) RT-PCR was designed in the nucleoprotein gene to detect specifically DASHV RNA . Sense ( DASHV -N-FW [GATTGTAGAGGGCAGACCCG] ) and reverse primers ( DASHV -N-REV [TCCATTGCACTCCCAGGAAC] ) were combined with the fluorogenic TaqMan probe ( DASHV -N-Probe [6FAM-TGGACTGTCCAAGCTGTGGAGG-TAMRA] ) , and used with the Go Taq Probe 1-Step RT-qPCR ( Promega ) as previously reported [2] . Sandfly homogenates of 50μL were inoculated onto 12 . 5 cm2-tissue culture flasks containing Vero cell monolayers in EMEM , enriched with 1% Penicilin Streptomycin , 1% L-Glutamine 200 mM , 1% Kanamycin , and 3% Fungizone and 5mL of fresh EMEM containing 5% fetal bovine serum ( FBS ) was added after incubation at room temperature for 1 hr . To monitor the development of cytopathic effects the flasks were incubated at 37°C in 5% CO2 atmosphere and examined daily using an inverted microscope . Supernatant corresponding to passage 2 of DASHV infected Vero cells was used for complete genome characterization using Next Generation Sequencing ( NGS ) as previously described [2]; viral sequences were identified from the contigs based on the best BLAST similarity against reference databases using the CLC Genomics Workbench 7 . 0 . 4 . Reads > 30 nucleotides long were trimmed using CLC Genomic Workbench 6 . 5 , with a minimum of 99% quality per base and mapped to reference sequences on Genbank . Parameters were set such that each accepted read had to map to the reference sequence for at least 50% of its length , with a minimum of 80% identity to the reference . Sequence gaps were completed by PCR , designing specific primers based on NGS results and for the extremities using the primers previously defined [14] , and PCR fragments were sequenced either by Sanger sequencing or by NGS . Once the complete genome was revealed , Sanger sequencing was performed through specific primers designed for the confirmation of the complete sequence . Complete coding regions of the S , M and L segments of phleboviruses were collected from Genbank ( http://www . ncbi . nlm . nih . gov/genbank ) and were aligned together with DASHV using the CLUSTAL algorithm of the MEGA 6 software [63] . Nucleotide ( nt ) and amino acid ( AA ) distances were calculated with the p-distance method . Neighbour-joining ( NJ ) analysis ( Kimura 2-parameter model ) was carried out using AA alignments , with 1000 bootstrap pseudoreplications . ML analysis was also performed using the best model defined for each gene . Since there was no obvious difference in the topology of the trees for viruses closely related with DASHV using either NJ or ML , final analysis including a larger set of sequences was performed using NJ . A total of 24 homologous sequences most closely related with DASHV were aligned using Clustal W in MEGA6 [63] . The evolutionary history was inferred either by using the Maximum Likelihood method based on the Tamura 3-parameter model gamma distributed with invariant sites [63] or by the neighbour-joining method using the Kimura-2 parameter model . All positions with less than 95% site coverage were eliminated , so that they were a total of 160 positions in the final dataset . Evolutionary analysis was conducted in MEGA6 . Distribution of evolutionary distances upon amino acid pairwise comparison of the complete open reading frame were studied using complete coding sequences of the 5 ORFs . The genetic distance was reported on the x-axis . Frequency of genetic distances was recorded on the y-axis . Ranges were assessed for intraspecific and interspecific distances as previously described [64 , 65] . The DASHV sequence has been deposited into the GenBank database with the corresponding accession numbers for L , M and S genomic segments KP771821 , KP771822 , and KP771823 , respectively . | Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health . Although several strains of these viruses had been isolated in Iran in the late 1970's , there was no recent data about the present situation at the outset of this study . Entomological investigations performed in 2009 and 2011 in Iran collected 4 , 770 sandflies from 10 different regions . A phlebovirus , provisionally named Dashli virus ( DASHV ) , was isolated / detected in two pools . DASHV strain was isolated in cell culture and complete genome sequence was determined . Sequence analysis indicated that ( i ) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV] , a virus that is known to cause self-resolutive incapacitating febrile illness in humans , ( ii ) there is a common ancestor to DASHV and all other variants of SFSV isolated in Italy , India , Turkey , and Cyprus ( lineage I ) , ( iii ) DASHV is more distantly related with Corfou and Toros viruses ( lineage II ) although common ancestry is supported with 100% bootstrap , ( iii ) lineage I can be subdivided into sublineage Ia including all SFSV strains , whereas Iranian viruses are most closely related and should be individualized as DASHV ( sublineage Ib ) . Although discovered first in the 1940's , SFSV is still listed as "tentative species" by the International Committee for Taxonomy of Viruses . Based on the results described in this study , we propose to approve Sandfly fever Sicilian virus species . Owing that most of these viruses have been identified in human patients with febrile illness , DASHV should be considered as a potential human pathogen in Iran . | [
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"an... | 2017 | Isolation and sequencing of Dashli virus, a novel Sicilian-like virus in sandflies from Iran; genetic and phylogenetic evidence for the creation of one novel species within the Phlebovirus genus in the Phenuiviridae family |
Aberrant viral RNAs produced in infected plant cells serve as templates for the synthesis of dsRNAs . The derived virus-related small interfering RNAs ( siRNA ) mediate cleavage of viral RNAs by post-transcriptional gene silencing ( PTGS ) , thus blocking virus multiplication . Here , we identified ASYMMETRIC LEAVES2 ( AS2 ) as a new component of plant P body complex which mediates mRNA decapping and degradation . We found that AS2 promotes DCP2 decapping activity , accelerates mRNA turnover rate , inhibits siRNA accumulation and functions as an endogenous suppressor of PTGS . Consistent with these findings , as2 mutant plants are resistant to virus infection whereas AS2 over-expression plants are hypersensitive . The geminivirus nuclear shuttle protein BV1 protein , which shuttles between nuclei and cytoplasm , induces AS2 expression , causes nuclear exit of AS2 to activate DCP2 decapping activity and renders infected plants more sensitive to viruses . These principles of gene induction and shuttling of induced proteins to promote mRNA decapping in the cytosol may be used by viral pathogens to weaken antiviral defenses in host plants .
Host-virus interactions entail susceptibility and resistance mechanisms embedded in anti-pathogen strategies of hosts and anti-host resistance strategies mounted by successful viral pathogens . As obligate intracellular parasites viruses have evolved various strategies to hijack host components for their own survival and multiplication in hosts [1] . In higher plants , post-transcriptional gene silencing ( PTGS ) is an important native antiviral resistance machinery that suppresses viral gene expression through ( si ) RNA-directed viral RNA cleavage . Aberrant viral RNAs synthesized during replication of RNA viruses or transcribed from DNA viruses serve as a template for RNA-DEPENDENT RNA POLYMERASE6 ( RDR6 ) to synthesize complementary RNAs [1] . The double stranded RNAs ( dsRNAs ) produced are processed by the plant’s small RNA pathway to generate siRNAs which mediate viral mRNA cleavage and silencing viral gene expression . The importance of the PTGS pathway in plant viral defense has elicited counter defense measures from the viral pathogens to overcome it . Plant viruses have evolved various viral RNA silencing repressors ( VSR ) to target different PTGS pathway components . For example , the Tomato bushy stunt virus P19 protein binds to siRNAs directly whereas the Cucumber mosaic virus 2b protein blocks the RNA cleavage activity of Argonaute1 ( AGO1 ) in the RNA-induced Silencing Complex [2 , 3] . In addition to the VSRs , plants also encode endogenous silencing repressor such as the RDR1 from Nicotiana tabacum to target the dsRNA biogenesis step [4] . Aberrant viral RNAs serve as templates for synthesis of dsRNAs by RDR6 , and like cellular mRNAs they can be cleared by the host RNA degradation machinery [1] . The clearance of aberrant viral RNAs will deplete substrates for dsRNA synthesis and siRNA production thus attenuating PTGS . Degradation of cytoplasmic RNAs occurs in P-bodies which are conserved and dynamic protein-RNA aggregates . Among protein subunits of the P-body complex investigated so far , DCP2 is the only protein subunit that possesses enzymatic activity for removing 5' cap structure ( m7GpppX- ) in vitro [5] . The 5' cap structure is an essential feature of eukaryotic mRNA required for mRNA stability and efficient translation [6] . Plant mutants deficient in P-body components display severe postembryonic developmental defects , suggesting that these cytoplasmic bodies play important roles in regulating gene expression in plant developmental process [7] . Furthermore , plant DCP1 and DCP5 have been shown to be translation suppressors [7 , 8] . Other than DCP1 , DCP2 and DCP5 , similar phenotypic and functional co-localization analyses suggest that 3 additional factors VARICOSE ( VCS ) , XRN4 , and DHH1 are also key components of plant P-bodies [7] . Genetic and biochemical analysis have shown that mutations in XRN4 [9] or DCP2 [10] enhance PTGS presumably by increasing aberrant RNA levels . In contrast to higher plants , the role of mRNA decapping in animal host defense against viruses is unclear . RNA viruses , including negative stranded RNA viruses and ambiviruses ( the Orthomyxoviridae , Bunyaviridae , and Arenaviridae families ) , and dsRNA virus totivirus L-A , which infects Saccharomyces cerevisiae , provide their mRNAs with a 5′ cap structure via a cap-snatching mechanism . In this mechanism , the viral polymerase cleaves host mRNAs 10–13 nucleotides from the 5′ end and utilizes the capped fragment as a primer to synthesize viral transcripts [11] . Therefore , the decapping machinery of animal cells may act as an important immune system to accelerate turning over of viral mRNAs thereby limiting virus multiplication for this subgroup RNA viral pathogens [11 , 12] . On the contrary , the decapping machinery in higher plants is used to suppress PTGS thereby promoting virus replication [10] . Little is known about the roles of plant mRNA decapping on virus-plant interaction and virus pathogenesis , possibly because deficiencies in most of the genes encoding mRNA decapping machinery cause postembryonic lethality [7] . Geminiviruses are the largest group of plant DNA viruses whose compact genomes consist of small single-stranded DNA circles of 2–3 kb . Despite their small size , these viruses inflict big damages on many commercially important crops [13] . Owing to their small genome size the encoded genetic information is extremely compact . Among geminiviruses , members of the genus Begomovirus , such as India cassava mosaic virus ( ICMV ) , possess two genomic components , DNA-A and DNA-B [14] . The DNA-A which encodes 5 gene products is involved in virus replication , transcriptional activation of viral genes and encapsulation of the viral genome . The DNA-B component encodes two proteins that are expressed at the late stage of virus infection , the nuclear shuttle protein BV1 ( NSP ) and the movement protein BC1 ( MP ) , both being required for viral systemic movement . It is known that BV1 facilitates the intracellular trafficking of viral DNA between nuclei and cytoplasm , whereas BC1 potentiates cell-to-cell movement of viral DNA . BV1 is a virulence factor , found to suppress trans-membrane receptor kinase activity in vitro [15] . AC2 which is encoded by the DNA-A component has been reported as a VSR and it trans-activates host and viral genes [16] . We have previously identified a pathogenesis factor βC1 of the monopartite geminivirus TYLCCNV ( Tomato yellow leaf curl China virus ) that interacts with Arabidopsis ASYMMETRIC LEAVES 1 ( AS1 ) to cause alterations in leaf development resulting in the manifestation of disease symptoms [17] . AS1 is needed for βC1 function as changes in leaf morphology elicited by this viral factor is largely attenuated in as1 mutant . Unexpectedly , βC1 is able to partially complement as2 mutation suggesting that βC1 is a molecular mimic of ASYMMETRIC LEAVES 2 ( AS2 ) [17] . What roles does AS2 play in viral pathogenicity and/or virulence remains to be investigated . Here , we show that BV1 , a geminivirus virulence factor that is expressed late in the virus life cycle , can induce AS2 expression by binding to its promoter region . Over-expression of AS2 both in Arabidopsis thaliana and Nicotiana benthamiana rendered plants more sensitive to geminivirus infection whereas as2 mutant plants were resistant . Moreover , BV1 can induce nuclear export of AS2 to the cytosol where the latter interacted with DCP2 to promote decapping activity , reduce siRNA accumulation and weaken RNA silencing . This viral counter-defense strategy makes plants more sensitive to virus infection and replication . Finally , we provide evidence that cytoplasmic localization of AS2 was necessary for it to function as a negative regulator of host resistance against virus infection .
Arabidopsis thaliana Wild type ( WT ) and as1-1 , as2-1 , and sgs3-1mutants ( all in Col-0 background ) were used [18–21] . After vernalization for 2 days at 4°C in darkness , seeds were germinated on Murashing and Skoog ( MS ) medium at 22°C with 16 h light . Plasmids were introduced into Agrobacterium tumefaciens strain AGL1 or EHA105 by electrotransformation . Arabidopsis transformations were performed using the floral-dip method [22] . Nicotiana benthamiana GFP transgene line 16c was kindly provided by Dr . David Baulcombe . Agrobacterium-mediated transient expression in N . benthamiana leaves was performed by pressure infiltration [23] . Arabidopsis thaliana L1 line with silenced 35S-GUS transgene was from Dr HervéVaucheret [24] . Plants were infected with CaLCuV by either micro-particle bombardment or agroinfiltration . Plasmids pCPCbLCVA . 007 ( GenBank accession no . AY279345 ) and pCPCbLCVB . 002 ( GenBank accession no . AY279344 ) were kindly provided by Dr Dominique Robertson ( Turnage et al . , 2002 ) . Biolistic PDS-1000/HE System ( Biorad ) was used for particle delivery and Arabidopsis plants were inoculated at 1 , 100 psi Capture Disks ( Biorad ) . Inoculated plants were kept in darkness for 12h and then returned to a growth chamber under normal condition . Symptoms of the inoculated plants were recorded 7 days later . For quantitative analysis of viral titer , leaf samples were collected from plants 3–4 weeks after inoculation . Total gDNA and viral DNAs were extracted by CTAB method and quantitative PCR ( Q-PCR ) was performed by using Actin2 as an internal genomic DNA control [25] . CaLCuV infectious clones ( DNA-A and DNA-B ) suitable for agroinfiltration [25] were used to infect Arabidopsis plants with 6–8 true leaves . Full-length cDNAs were amplified by PCR using Phusion High-Fidelity DNA Polymerase ( FINNZYMES ) and subcloned into binary vectors pCAMBIA1300-2X35-3HA , pBA002-3HA or pBA002-6Myc to generate HA-tagged and Myc-tagged constructs under the control of a 35S promoter . Point mutation in specific amino acids of AS2 were generated with Stratagene's QuikChange II Site Directed Mutagenesis Kit ( Stratagene , USA ) with primers listed in S1 Table . pCAMBIA1300 vector was used to construct AS2-EGFPfusion gene expressed from a native AS2 promoter ( from -2 . 8kb to +2 . 0 kb , just before the initiation codon ) to generate the plasmid 1300-AS2p ( -2 . 8K ) :AS2-EGFP for stable transformation . NES from HIV Tat protein ( LQLPPLERLTLD ) and for NLS from SV40 virus ( PKKKRKVKD ) were used to make AS2-NES and AS2-NLSfusion genes . AS2 variants ( AS2-NES and AS2-NLS ) were replaced WT AS2 in the plasmid of 1300-AS2p ( -2 . 8K ) :AS2-EGFP and used for AS2 native promoter driven AS2 variants expression vector . BV1 of CaLCuV was cloned into the pBA002-CFP to form pBA002-BV1-CFP . GFP imaging was as described [23] . To prepare protein samples , a leaf section ( 50mg ) was ground in liquid N2 and extracted with 200 μl of 8M urea . The extract was mixed with 2 x SDS loading buffer and boiled for 10 min . Ten microliters of protein extract was separated by SDS-PAGE . Antibodies against GFP and protein gel blot analysis were as described in [23] . Transient silencing suppressor activity assays in N . benthamiana was performed as described [23] . For co-infiltrations , the OD600 of GFP-carrying agrobacterial strain was 0 . 8 and that of AS2 was 1 . 2 . Total RNA was extracted from 12-day-old seedlings using Trizol reagent ( Invitrogen ) according to the manufacturer’s instructions . Fifteen μg total RNA were fractionated on a 1 . 2% ( w/v ) agarose gel and then transferred to a Hybond-XL membrane ( GE Biosciences ) . Hybridization was performed overnight at 65°C in hybridization buffer ( 0 . 3 M sodium phosphate at pH 7 . 0 , 10 mM EDTA , 5% SDS , 10% dextran sulfate , 0 . 15 mg/mL salmon sperm DNA ) , and signals were detected by autoradiography . For small RNA analysis , 15 μg of total RNA were fractionated on a 15% polyacrylamide gel containing 8 M urea and then transferred to a Hybond-N+ membrane ( GE Biosciences ) . DNA oligonucleotides were end-labeled with [γ-32P] ATP using T4 polynucleotide kinase ( New England Biolabs ) . Hybridization was performed overnight at 42°C using the ULTRAHyb-Oligo hybridization buffer ( Ambion ) and signals were detected by autoradiography . Southern blot was performed as described previously [26] . Membrane was hybridized with a probe encoding the AC1 ( Rep ) of CaLCuV DNA-A . The probe was DIG-dUTP-labeled by PCR using a PCR DIG probe synthesis kit ( Roche Shanghai , China ) and hybridization signals were detected by autoradiography . RNAs were isolated from leaf and stem samples using Qiagen RNeasy Plant mini kits ( Qiagen ) with on-column DNase treatment . Plant RNA purification reagent ( Invitrogen ) was also used for total RNA extraction followed with DNase treatment [27] . RNA concentration was measured by Nanodrop ( Thermo , USA ) . M-MLV reverse transcriptase ( Promega , USA ) was used for reverse transcription reactions . Real-time PCR was performed with Power SYBR Green PCR Master ( Applied Biosystems , USA ) and run in ABI7900HT . All samples were run in triplicates and data was analyzed with RQ manager at a pre-set Ct value ( Applied Biosystems , USA ) . PCR primers were listed in S1 Table . Cordycepin treatments and mRNA stability analysis were performed as described before [7] . Twelve-day-old seedlings were incubated in MS medium with cordycepin ( 3′-deoxyadenosine; Sigma-Aldrich ) and DMSO treatment was used as a mock control . Data derived from the mock control was used for normalization for mRNA stability assays . Total RNA was extracted from samples harvested at various time points using Plant RNA extraction reagent ( Invitrogen ) . Actin2 was used as an internal mRNA control . cDNAs encoding full-length CaLCuV BV1 , AS1 , AS2 , DCP1 , DCP2 , DCP5 and VCS-C terminal were amplified by PCR using Phusion High-Fidelity DNA Polymerase ( FINNZYMES ) and subcloned to generate GST fusion , MBP fusion and 6His , 6His-SUMO fusion constructs . The yeast SUMO protein tag was used to improve AS2 protein solubility . All constructs were transformed into E . coli BL21 ( DE3 ) cells and cultured at 37°C . After the OD600 had reached ∼0 . 6 , isopropyl β-D-thiogalactopyranoside was added to a final concentration of 0 . 4 mM and the culture incubated overnight at 20°C . Bacterial cells were collected by centrifugation and suspended in a lysis buffer containing proteinase inhibitor cocktail ( Roche ) . After French press treatment , recombinant proteins were purified with specific affinity columns and AKTA FPLC system ( GE Biosciences ) followed by size-exclusion columns . The eluted proteins were concentrated by Ultracel YM-30 ( Millipore ) . In vitro pull-down assays were performed with 2 μg of GST/MBP/His/His-SUMO fusion proteins . Proteins were incubated in a binding buffer ( 50 mM Tris-HCl at pH 7 . 5 , 100 mM NaCl , 0 . 25% Triton X-100 , 35 mM β-mercaptoethanol ) for 2 h at 4°C , and 30 μl of glutathione sepharose 4B ( GE Biosciences ) were added and the mix incubated for overnight . After washing with binding buffer for 6 times , pulled-down proteins were separated on 12% SDS–polyacrylamide gel and detected by Western blotting using anti-His , anti-GST or anti-MBP antibody . About 3 g of 14-day old Arabidopsis seedlings expressing35S:BV1-ECFP or AS2p ( -2 . 8K ) :AS2-EGFP was used for ChIP assays . Seedlings were incubated with 50 μM MG132 ( Calbiochem ) for 12 hr before harvesting . Proteins were extracted in extraction buffer ( 50 mM Tris-HCl at pH 7 . 5 , 150 mM NaCl , 2 mM MgCl2 , 1 mM DTT , 20% glycerol , 0 . 5% nonident P-40 ) containing protease inhibitor cocktail ( Roche ) and protease inhibitor mixture ( Sigma ) . Cell debris was pelleted by centrifugation at 14 , 000g for 30 min . The supernatant was incubated with GFP-agrose beads ( GFPtrack ) overnight at 4°C . Beads collected by centrifugation were washed 6 times with washing buffer ( 50 mM Tris-HCl at pH 7 . 5 , 150 mM NaCl , 2 mM MgCl2 , 1 mM DTT , 10% glycerol , 0 . 5% nonident P-40 ) . Proteins were eluted by 50 μL of 2 . 5× sample buffer and analyzed by Western blotting using anti-DCP2 rabbit antibody [7] . About 2 g of 14-day old Arabidopsis seedlings expressing 35S:BV1-ECFP was used . Seedlings treated with 50 μM MG132 overnight were used for chromatin preparation and immunoprecipitation . Immunoprecipitation was performed by adding GFP-agrose beads ( GFPtrack ) . After washing , immune complexes were eluted from protein A beads and reverse cross-linked by incubation for at least 6 h at 65°C . Samples were treated with proteinase K for 1 h at 65°C . DNA was extracted in a final volume of 80 μL using the QIAquick PCR purification kit ( Qiagen ) . ChIP assay was repeated with 3 biological replicates . One microliter of DNA was used for each real-time quantitative PCR with SYBR Premix Ex Taq ( Applied Biosystems , USA ) in the ABI7900 real-time system ( Applied Biosystems , USA ) . Each sample was assayed in triplicate by PCR . Error bars in each graph indicate standard deviation ( SD ) of three biological replicates . We used ACTIN2 as an internal control . Primers used for ChIP assays are listed in S1 Table BiFC was performed using vectors and methods described in [25] . Full length cDNAs encoding BV1 ( CaLCuV ) , AS1 , AS2 , DCP1 , DCP2 , DCP5 and VCS-C terminal were cloned into corresponding restriction enzyme sites of BiFC vectors . The resulting cassettes including fusion genes and constitutive promoters were cloned into pGreen binary vector HY105 and transformed into Agrobacterium . For BiFC experiments , leaves of 3-week-old N . benthamiana plants were co-infiltrated with Agrobacterium as previously described . A nuclear protein Aux/IAA from Jatropha curcas was used as a nuclear marker [28] . IAA-ECFP was produced by PCR cloning into the pBA002-ECFP vector . The agrobacterium strain carrying IAA-ECFP was co-inflitrated with strains carrying BiFC vectors into N . benthamiana leaf cells . Images were taken from cells 48 hours post-infiltration using a confocal laser scanning microscope . RNAs ( 121nt-G16 ) containing a 16-guanine track at the 3′ end were transcribed with the MAXIscript T7 kit ( Ambion ) from a DNA fragment of At2g38280 corresponding to the 5′ untranslated region ( 123 nucleotides ) of the transcribed mRNA . To generate cap-labeled RNAs , the ScriptCap m7G Capping system ( Epicentre ) was sequentially used . Decapping assays were performed at 37°C for 30 min with cap-labeled RNA and the indicated amounts of purified proteins . Reaction products were resolved by thin layer chromatography as described by Xu J . et al . [7] . The reactions were performed in in vitro decapping assay buffer ( 10 mM Tris-Cl , pH 7 . 5 , 100 mMKAc , 2 mM MgAc2 , 0 . 5 mM MnCl2 , 2 mM DTT , 0 . 1 mM spermine , and 25 μg/mL yeast tRNA ) . TLS PEI cellulose F plates ( Merck ) were used to resolve products of decapping assays .
We infected Arabidopsis WT ( Col-0 ) plants with Cabbage leaf curl Virus ( CaLCuV ) , a model for bipartite geminivirus , and examined the symptoms of infected plants . CaLCuV infects Arabidopsis leaf tissues with high efficiency , inducing symptoms of severe stunting and leaf epinasty , suggesting inference with leaf development ( Fig 1A , 1B and 1C , control plant shown in Fig 1D and 1E ) . To explore the molecular basis of the developmental abnormality , we determined transcript levels of a number of genes implicated in leaf development . Of the 5 genes tested only AS2 transcript levels were obviously induced by more than 4 fold in infected plants ( Fig 1F ) . By contrast , there was no AS1 expression changes in the infected plants , although AS1 shares overlapping function with AS2 in leaf development . These results suggest that AS2 may play a role in geminivirus pathogenesis and/or virulence , in addition to its known functions in leaf stem cell determination . Expression levels of KNOTTED1-like homeobox ( KNOX ) genes , BREVIPEDICELLUS ( BP ) and KNAT2 , all of which are targets of AS2 , were not visibly altered upon virus infection ( Fig 1F ) . The considerable increase in AS2 transcript levels led us to hypothesize that AS2 may play a role in virus-host interaction . To see which viral component is responsible for the increased AS2 expression , we generated transgenic Arabidopsis plants expressing several individual CaLCuV proteins . Preliminary analysis of transgenic plants identified the virulence factor BV1 as the candidate . Fig 1G and S1 Fig show a positive correlation between BV1 expression and AS2 expression in several independent transgenic lines . This result shows that BV1 alone may induce AS2 expression , independent of any other viral factors . The effect of BV1 on AS2 expression may be direct or indirect . To test for possible direct binding of BV1 to the AS2 genomic locus we performed Chromatin Immunoprecipitation ( ChIP ) assays using transgenic 35S:BV1-CFP seedlings . Fig 1H and 1I show the- 2 . 2 Kb to -1 . 6Kb ( 600-bp ) of the AS2 promoter was more efficiently precipitated by BV1-CFP demonstrating possible binding of BV1 to this region of the AS2 promoter . To ascertain the importance of this AS2 genomic region in BV1 interaction we constructed an AS promoter:GUS reporter gene ( AS2p:GUS ) . Owing to the long intron in the 5'UTR of AS2 ( Fig 1H ) the reporter gene consisted of 4 . 8Kb AS2 genomic sequences ( from -2 . 8kb to +2 . 0 kb , just before the initiation codon ) fused to a GUS coding sequence downstream ( AS2p:GUS ) . We transformed Arabidopsis plants of different genotypes with the AS2p:GUS fusion gene . GUS activity was high in WT ( Col-0 ) young seedlings ( S2A Fig ) but weaker in mature leaves and inflorescence stems confirming previous results [20] . Infection experiment verified the AS2p:GUS activity was virus-inducible in a BV1-dependent manner ( compare right and left plants in S2C Fig ) . By contrast , AS2p:GUS activity was low in as2-1 mutant ( S2B Fig ) suggesting positive auto-regulation by AS2 ( Compare uninfected plants shown in S2A and S2B Fig , also infected plants shown in S2D and S2E Fig ) , in addition to its activation by BV1 . BV1-dependent AS2p:GUS activity was much reduced when a 1 . 6 Kb sequence ( -2 . 8 to -1 . 2Kb ) of AS2 5′ upstream region was deleted from the promoter of the reporter gene ( S2F Fig ) . This result is consistent with the chromatin immunoprecipitation data that BV1 associated with this 1 . 6 Kb region to activate AS2 promoter activity . Two opposing hypothesis may be proposed to explain the activation of AS2 by BV1 . One possibility is that the host protein may be induced as part of the host defense system to counter and block virus infection . The other possibility is that the AS2 induction may underpin a subversive mechanism used by the virus to compromise host defense . To discriminate between these two possibilities , we infected Arabidopsis WT and mutant plants of different genotypes: as2-1 , as1-1 , two related leaf developmental mutants ( phenotypes shown in S3A Fig ) [19] and sgs3-1 , an enhanced susceptibility mutant [29] . Fig 2 shows viral infection symptoms were pronounced on WT plants as well as plants of as1-1 and sgs3-1 . Moreover , consistent with published results [29] the viral symptomatic onset on sgs3-1 plants was 2–3 days earlier compared with WT control and as1-1 . There was no obvious difference in viral symptomatic onset between WT and as1-1 plants . In contrast to sgs3-1 , the onset of viral symptoms on as2-1 was 2–3 days later than in WT and as1-1 ( Fig 2A , 12 dpi ) . At the late stage ( 28 dpi ) , there was no obvious symptomatic difference between WT and sgs3-1 , whereas as1-1 displayed a slightly weaker symptom ( Fig 2B ) . Much milder symptoms including curling of leaves , flowers and siliques and dwarfing of plant stature were found with infected as2-1 plants ( Fig 2B and 2C ) . These results indicate AS2 deficiency attenuates virus replication . To obtain quantitative data on viral titers we determined viral genomic DNA accumulation levels in CaLCuV-infected plants of different genotypes . Plants of as2-1 were more resistant to the geminivirus as compared to as1-1 and WT plants . The virus titer was much lower in systemic leaf of as2-1 either by Southern blot or quantitative PCR ( Q-PCR ) analysis , suggesting AS2 interferes with virus replication ( S3B Fig and Fig 2D ) . The results so far suggested that AS2 may function as a negative regulator of host defense mechanisms and its deficiency would lead to virus resistance . If this hypothesis was correct , then AS2 overexpression should produce the opposite results . Fig 2F and S4 Fig show that this was indeed the case both in Arabidopsis and N . benthamiana . 35S:AS2 over-expression Arabidopsis and N . benthamiana plants were much more sensitive to bipartite geminiviruses , CaLCuV and Indian Cassava Mosaic virus ( ICMV ) respectively , with high viral DNA-A and B levels . To directly confirm AS2 suppressor activity , we expressed 35S:AS2 in the L1 line of Arabidopsis thaliana which harbors a silenced GUS gene owing to PTGS . Fig 3A shows that AS2 overepxression reactivated the silenced 35S:GUS transgene in the L1line . In reactivated plants , the increased GUS mRNA levels were accompanied by decreased GUS-related siRNA levels as compared to the parental L1 line ( Fig 3B ) . Similar results were obtained by over-expression of a 35S:AS2-YFP fusion gene ( Fig 3A and 3B ) . We also tested AS2 suppressor activity by transient expression in N . benthamiana using the strong viral suppressor P19 of Tomato bushy stunt virus as a control . S5 Fig confirms the suppressor activity of AS2 and less small interfering RNA ( siRNA ) accumulation by co-expression of AS2 also shows that its activity was weaker compared to P19 . Together , these results indicate that AS2 can function as an endogenous PTGS suppressor in two different assay systems . AS2 was first characterized as a transcription factor which interacts with AS1 to regulate a number of downstream genes involved in leaf development [19] . This observation implies that the AS2 protein should be nuclear localized in order to execute its transcriptional function . On the other hand , our results above indicate that AS2 can function as a suppressor of PTGS , which is known to occur in the cytosol . This discrepancy can be resolved if AS2 can shuttle between the two cellular compartments to execute different functions . In fact , when expressed from its native promoter the AS2 protein was found in both the nuclear and the cytosolic compartment in transgenic Arabidopsis roots ( Fig 4A and S6 Fig ) . Nuclear localization of AS2 has been previously reported [20] . Similar dual subcellular localization of the AS2 protein was seen by transient expression in tobacco leaves ( S7 Fig ) To identify the cellular compartment in which AS2 carries out its suppressor activity , we fused AS2 with either a Nuclear Localization Signal ( NLS , Simian vacuolating virus 40 , SV40 ) or a Nuclear Exporting Signal ( NES , human immunodeficiency virus , HIV ) . The two AS2 localization mutants were tested for their suppressor activity . Fusion of NES did not interfere with AS2 suppressor activity ( Compare Fig 5A and 5B , also 5F ) but NLS fusion greatly attenuated AS2 suppressor activity ( Compare Fig 5A and 5C , also 5H ) . Furthermore , protein level analysis indicated that AS2 and AS2 variants have comparable stability ( Fig 5I ) . These results provide evidence that cytosolic localization of AS2 is required for its PTGS suppressor activity . Furthermore , a mutation that converts a conserved amino acid Ile 88 to Ala blocked local and systemic silencing suppressor activity ( S8 Fig and Fig 5D to 5I ) . Because BV1 is a nuclear-cytosol shuttle protein we asked whether BV1 was able to bind AS2 in addition to activating its encoding gene . Fig 4B shows BV1 interacted strongly with AS2 but much less with AS1 in pull-down assays in vitro . AS2 was capable of self-interaction forming dimers or even higher-order protein complexes . This self-association property was compromised by the I88A mutation ( Fig 4C ) . To determine the mechanism of AS2 action in PTGS we screened for possible protein-protein interaction with proteins in the PTGS pathway and also proteins involved in RNA quality control machinery . Arabidopsis DCP2 has been recently reported as a negative regulator for PTGS [10] . This observation prompted us to examine whether BV1 and AS2 may interact with protein subunits of the decapping complex [7] . Using either BV1 or AS2 as a bait we found that AS2 strongly interacted with DCP2 and weakly with DCP1 in vitro ( Fig 4D ) . Moreover BV1 also weakly interacted with the COOH- terminal fragment of VARICOSE ( VCS ) . The strong interaction between either BV1 or AS2 with DCP2 was further confirmed by co-immunoprecipitation experiments ( Fig 4E and 4F ) . To confirm the observed protein-protein interactions in vivo , we performed Bimolecular Fluorescence Complementation ( BiFC ) using yellow fluorescent protein ( YFP ) . We generated constructs to express AS2 , BV1 or DCP2 fused at their N- or C- termini with the N- or C- terminal portions of YFP ( nYFP and cYFP ) . Expression constructs were introduced into N . benthamiana leaf cells by agroinfiltration , and those with complementary YFP fusions ( i . e . nYFP + cYFP ) were analyzed by confocal microscopy 48 hours post-infiltration . Test proteins were examined in all possible combinations . No signal was detected in control experiments in which only one fusion protein was expressed . Co-expression of the paired BV1/AS2 and BV1/DCP2 proteins resulted in YFP fluorescence in nuclei foci indicating complex accumulation in these subcellular locations . AS2/AS2 paired protein signals were found in both nuclear and cytosolic regions ( Fig 4G ) . By contrast , the fluorescence signal of AS2/DCP2 pair was exclusively localized in cytosolic speckles , corresponding most likely to P bodies . No signal was found in the nucleus ( Fig 4H ) . Next , we examined the effect of the I88A mutation on interaction with DCP2 . BiFC analysis showed that amino acid I88 was important for AS2/DCP2 association in N . benthamiana cells ( Fig 4H ) . Since BV1 is a shuttling protein and interacts with AS2 it is possible that this viral protein may shuttle nuclear AS2 to the cytosol to function as a silencing suppressor . To this end , we co-expressed BV1-CFP in the presence of the AS2/DCP2 BiFC combination . Many cytosol P-bodies like structures with CFP/YFP co-localization were observed ( Fig 4I ) and the results were confirmed by statistical analysis ( Fig 4J ) . Taken together , our results suggest that the formation of multiple protein bodies ( BV1-AS2-DCP2 ) may play important roles in BV1 and AS2 silencing suppressor activity . Among the various P body components only DCP2 has been shown to possess decapping activity [13] . Therefore , we examined the effect of AS2 on DCP2 decapping activity in vitro . Fig 6A shows that DCP2 decapping activity was stimulated by the addition of AS2 and this stimulating effect was abolished by the I88A mutation . There was no obvious difference in the stimulating effect on DCP2 decapping activity between WT AS2 and its localization mutant derivatives ( AS2-NLS and AS2-NES ) ( S9 Fig ) , which still retained the ability to physically interact with DCP2 . Taken together , these results indicate that the cytoplasmic localization of AS2 in vivo is indispensable for its silencing suppressor activity . BV1 also showed a moderate stimulating effect on DCP2 decapping activity in vitro ( Fig 6A ) . We performed qRT-PCR analysis to test whether mRNA turnover was altered in as2-1 and in plants expressing AS2 and derivatives . To this end , we used the native AS2 promoter to express coding sequences for AS2-EGFP , AS2-I88A-EGFP , AS2-NLS-EGFP and AS2-NES-EGFP in the as2-1 mutant background and the resulting transgenic plants were tested for mRNA stability in vivo . Expansin-Like1 ( EXPL1 ) transcript levels were 4-fold in as2-1 mutant than that of in the WT control ( S10 Fig ) . Moreover , Fig 6B shows the estimated half-life of EXPL1 transcripts was about 80 min in as2-1 , >120 min in AS2-NLS-EGFP and in AS2-I88A-EGFP plants . These values were at least two times higher than the half-life of 40 min found in WT control samples ( Fig 6B ) . We also observed that the half-life of EXPL1 transcripts was about 40 min for AS2-EGFP and AS2-NES-EGFP plants . These in vivo results support the notion that AS2 increases the decapping capacity of DCP2 in the cytosol to accelerate mRNA decay in vivo . If the ability of AS2 to suppress PTGS is executed mainly in the cytosol then an AS2 mutant that is exclusively localized in the nucleus should be ineffective whereas a mutant that is localized to the cytosol should remain active . To test this hypothesis we used the transgenic lines generated above with appended NLS and NES sequences to direct the AS2 protein to specific subcellular localization . Fig 6C shows that whereas as2-1 mutant was resistant to CaLCuV the complemented line ( AS2/as2-1 ) was as sensitive to the virus as WT . Addition of the NLS sequence to retain AS2 protein in the nucleus resulted in transgenic plants that were as sensitive as as2-1 mutant plants indicating a lack of complementation for PTGS suppression . On the other hand , addition of NES sequence to AS2 produced the same result as WT AS2 indicating that PTGS function was mediated by cytosolic AS2 . Quantitative analysis on virus titer in infected plants further confirmed these results ( Fig 6C )
Host decapping system plays important roles in host/viral pathogen interaction in several systems but whether increased decapping activity is a host anti-viral defense or a viral strategy to weaken host defense depends on individual cases . For some animal and human viral pathogens , e . g . positive-stranded or negative-stranded RNA viruses , the mRNA decapping machinery is an important host immune system to counter virus infection [11] . On the other hand , mRNA decapping in cytoplasmic P-bodies is also essential for virus to complete their life cycle in animal or human cells , e . g . FHV [30] and therefore , in this case , increased decapping activity would presumably aid the pathogen . So far , the only viral encoded decapping enzyme , the vaccinia D10 , is synthesized at a later stage of the virus life cycle , after viral DNA replication . D10 synthesis correlates well with the shutdown of host gene expression , and deletion of this gene has been shown to cause persistence of host and viral mRNAs in infected cells [31] . The vaccina D10 decapping enzyme may help restrict host antiviral responses by accelerating host mRNA degradation during poxvirus infection . The Kaposi's sarcoma-associated herpesvirus encodes a host shutoff factor SOX which commandeers cellular mRNA turnover pathways to destroy host mRNAs following digestion by cellular exonuclease Xrn1 . This result suggests that Xrn1 is poised to deplete mRNAs undergoing translation in mammalian cells [32] . Based on these observations , a very likely scenario is that viral component ( s ) may hijack host cellular mRNA turnover machinery to efficiently destroy or enhance host mRNAs or aberrant viral RNAs transcribed from DNA or RNA viruses . Our data here presents a new mechanism by which plant pathogens mis-regulates host cellular mRNA turnover machinery to attenuate host anti-virus defense . This finding may aid in advancing knowledge on molecular mechanisms of host-virus interaction in animal pathogens . Meanwhile , DCP2 and decapping machinery may also contribute to innate immune response by a negative feedback mechanism to restore normal homeostasis following viral infection [33] . Compromising cytoplasmic or nuclear 5'-3' exoribonuclease function enhances transgene PTGS in Arabidopsis , suggesting that these pathways compete for similar RNA substrates . The Arabidopsis DCP2 is a negative regulator for RNA silencing in Arabidopsis [10] and N . benthamiana ( this study , S5 Fig ) indicating its inhibitory role on PTGS . Competition between single-stranded RNA substrates between RNA quality control and PTGS ensures appropriate partitioning of RNA substrates among these RNA degradation pathways [34] . Mutants of UPF1 , a gene in Nonsense-Mediated Decay pathway , showed hypersensitivity to ( + ) RNA virus PVX infection , further highlighting the complexity of RNA substrates partitioning for virus immune response [35] . In higher plants , more recently also in mammals , PTGS has emerged as a vital antiviral resistance machinery that competes with the decapping system for RNA substrates . PTGS suppresses viral gene expression through the production of dsRNAs and siRNA-directed viral RNA cleavage , mainly in the cytoplasm . On the other hand , aberrant RNA substrates are depleted by decapping system inhibiting PTGS . This substrate competition implies that increased decapping activity would block PTGS and is expected to aid virus virulence . AS2 has been well-characterized as a nuclear factor that transcriptionally regulates several downstream genes involved in leaf development . Here , we identified AS2 as a new regulatory component of Arabidopsis cytosolic P body , which activates DCP2 decapping activity in vitro ( Fig 6A ) and probably in vivo as reflected by the EXPL1 mRNA stability in planta ( Fig 6B ) . We provide evidence that AS2 also functions as an endogenous PTGS suppressor: 1 ) AS2 is able to restore expression of a silenced transgene ( Fig 3 ) ; 2 ) as2 mutant shows resistance to virus infection ( Fig 2 and Fig 6 ) ; 3 ) AS2 overexpression blocks PTGS and promotes virus infection ( S5 Fig and S4 Fig ) ; 4 ) Cytosolic but not nuclear AS2 inhibits PTGS and siRNA accumulation ( Fig 5 and S5 Fig ) ; 5 ) Nuclear-localized AS2 variant is not able to rescue the virus sensitivity phenotype of as2 mutant ( Fig 6C ) ; 6 ) Nuclear-localized AS2 variant is not able to rescue the mRNA turnover defect of as2 ( Fig 6B ) although this variant retains similar capacity as WT AS2 in promoting decapping activity in vitro ( S9 Fig ) . The biological activity of the AS2/DCP2 complex is further reflected in similar morphological phenotype of monogenic mutants . The venetion pattern of as2-1 cotyledons was disrupted similar to that found in dcp2-1 suggesting that the two genes , AS2 and DCP2 , operate in the same pathway . Furthermore , we found that the AS2 mRNA itself is feed-back regulated by the decapping complex , since AS2 transcript levels are elevated by approximately two-fold in decapping mutants [7] . This feed-back mechanism is also found in dcp1 , dcp2 and vcs mutants [7] . In addition to AS2 a few endogenous silencing suppressor for PTGS in plants have been previously identified , including the cytoplasmic exoribonucleases , XRN2 , XRN3 and XRN4 and DCP2 [9 , 10 , 18 , 36] . Given the importance of the decapping system in inhibiting PTGS we would expect any potential cellular activators of DCP2 activity to work as endogenous suppressors of PTGS as well . Likely candidates include DCP1 and DCP5 [7 , 8] . The begomovirus DNA-B component encodes two proteins , the BV1 ( nuclear shuttle protein , NSP ) and the BC1 ( movement protein , MP ) , both being required for systemic infection . BV1 which shuttles between the nucleus and the cytoplasm is believed to mediate the intracellular trafficking of viral DNA . BV1 also interacts with jasmonate singalling regulator MYC2 and plant immune receptor NIK1 to counter host resistance to pest and disease [15 , 25] . Here , we identified the geminivirus BV1 protein as a virulence factor that promotes mRNA decapping efficacy in P bodies so as to indirectly attenuate PTGS . BV1 is a nuclear-cytoplasmic shuttle protein and can bind single or double stranded DNA or RNA with no known sequence preference . The effects of BV1 on decapping activity are both direct and indirect . BV1 can induce expression of the nuclear gene AS2 but the AS2 induction by BV1 or virus does not lead to increased expression levels of downstream genes , e . g . KNAT etc ( Fig 1F ) . This observation suggests that most of the induced and newly-synthesized AS2 are escorted by BV1 into the cytosol to enhance degradation of aberrant RNAs , therefore reducing the RNA substrate for siRNA biogenesis . In addition to this indirect effect , BV1 also weakly activates the activity of RNA decapping , through which some plant transcripts involved in antiviral immunity may be reduced faster . A recent report showed that BV1 may interfere with host antiviral immunity by translation suppression of host proteins [37] . Meanwhile , based on the fact that BV1 mainly interacts with AS2 in the nucleus ( Fig 4G ) , it is also possible that DCP2 drags part of BV1 out of the nucleus Beside of its involvement in activating decapping we cannot exclude other functions of BV1 on begomovirus pathogenesis , e . g . direct siRNA sequestration , which is dependent or independent of AS2 induction of decapping . Because of the fundamental roles of dsRNA in initiating and maintenance of PTGS , it is not surprising that SGS3/RDR6 bodies have been identified as a common target for VSRs to suppress PTGS , e . g . the VPg of a ( + ) RNA virus Potyvirus [38] , TRIPLE GENE BLOCK PROTEIN1 ( TGBp1 ) of potexviruses [39] , P6 of ( - ) RNA virus Rhabdovirus [40] , p2 of Tenuivirus rice stripe virus ( RSV ) [41] and V2 protein of tomato yellow leaf curl virus [42] . In addition to the VSRs , plants also encode endogenous silencing repressor such as the RDR1 from Nicotiana tabacum to target the dsRNA biogenesis step [4] . The RNA decapping process could be hijacked and activated by viruses to reduce the template for synthesis of dsRNAs thereby escaping the host PTGS immune surveillance . We expect future work to uncover VSRs from other DNA and RNA viruses that may act directly on other P body components to activate its decapping activity and downregulate PTGS for the benefit of the virus . The results in this study can be best summarized by the working model presented in Fig 7 . In this model , BV1 of geminivirus translocates into the nucleus to bind and activate AS2 expression ( Frame 1 ) . The induced AS2 protein binds to BV1 ( Frame 2 ) which shuttles it into cytoplasmic P bodies where AS2 also promotes decapping efficiency ( Frame 3 ) . BV1 can also interact with AS2 and DCP2 to enhance RNA decapping and mRNA turnover . The accelerated aberrant RNA turnover suppresses host PTGS and make plants more sensitive to geminivirus infection and replication ( Frame 3 ) . | In higher plants , aberrant RNAs generated during virus replication serve as templates to make small interfering RNAs . These small RNAs are used by host as a defense mechanism to cleave viral RNAs thereby blocking virus replication . The anti-virus defense is attenuated by the host cellular mRNA turnover machinery which clears aberrant RNAs . Viruses may use encoded component ( s ) to activate host cellular mRNA turnover for their own benefits . In this study , we identified ASYMMETRIC LEAVES2 ( AS2 ) as an activator of mRNA decapping and degradation and an endogenous suppressor of virus silencing . We showed that the geminivirus BV1 protein induces AS2 expression , causes nuclear exit of AS2 to activate mRNA decapping activity and renders infected plants more sensitive to viruses . Similar mechanisms may be used by other viral pathogens to weaken antiviral defenses in host plants and also mammals . | [
"Abstract",
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] | [] | 2015 | Geminivirus Activates ASYMMETRIC LEAVES 2 to Accelerate Cytoplasmic DCP2-Mediated mRNA Turnover and Weakens RNA Silencing in Arabidopsis |
Prions cause neurodegeneration in vivo , yet prion-infected cultured cells do not show cytotoxicity . This has hampered mechanistic studies of prion-induced neurodegeneration . Here we report that prion-infected cultured organotypic cerebellar slices ( COCS ) experienced progressive spongiform neurodegeneration closely reproducing prion disease , with three different prion strains giving rise to three distinct patterns of prion protein deposition . Neurodegeneration did not occur when PrP was genetically removed from neurons , and a comprehensive pharmacological screen indicated that neurodegeneration was abrogated by compounds known to antagonize prion replication . Prion infection of COCS and mice led to enhanced fodrin cleavage , suggesting the involvement of calpains or caspases in pathogenesis . Accordingly , neurotoxicity and fodrin cleavage were prevented by calpain inhibitors but not by caspase inhibitors , whereas prion replication proceeded unimpeded . Hence calpain inhibition can uncouple prion replication from its neurotoxic sequelae . These data validate COCS as a powerful model system that faithfully reproduces most morphological hallmarks of prion infections . The exquisite accessibility of COCS to pharmacological manipulations was instrumental in recognizing the role of calpains in neurotoxicity , and significantly extends the collection of tools necessary for rigorously dissecting prion pathogenesis .
Transmissible spongiform encephalopathies ( TSE ) are inexorably fatal neurodegenerative disorders caused by prions [1] which consist of PrPSc , a protease-resistant isoform of the normal cellular prion protein PrPC . Accordingly , Prnpo/o mice lack PrPC , cannot generate PrPSc , and withstand prion inoculation [2] . PrPSc forms aggregates that grow by recruiting PrPC and whose breakage underlies prion replication [3] . The hallmarks of TSEs include PrPSc deposition and progressive brain damage . Prnpo/o mice show mild phenotypes and no TSE [4]–[7] , indicating that TSEs are not caused by loss of PrPC function . Several observations suggest that extracellular deposition of PrPSc is intrinsically innocuous [8]–[10] , whereas neurotoxicity is driven by unknown secondary triggers . A mechanistic dissection of prion neurotoxicity necessitates faithful , experimentally versatile in vitro models – yet such models have proven difficult to generate [11] , [12] . COCS can be infected with various prion strains [13] , with prion titers peaking within 4 weeks . We reported that COCS retain their normal cerebellar architecture and do not experience prion-induced damage within a 1-month observational period . We have now maintained intact organotypic morphology for several months . Under these conditions we observed progressive neurodegeneration starting 5 weeks post-inoculation in prion-infected COCS .
All mouse experiments for generation of prion isolates conformed to Swiss law , were performed according to Swiss federal guidelines ( ‘Ethical Principles and Guidelines for Experiments on Animals’ 3rd edition , 2005 ) and were approved by the Animal Experimentation Committee of the Canton of Zurich ( permit 200/2007 ) . The specific experiments reported in this study were mostly performed in primary cultures and cell lines and for the most part substituted in vivo experiments with ex vivo experiments . All compounds were purchased from Sigma-Aldrich unless otherwise stated . GABAA-α6-cre mice were generated on a C57BL/6xCBA background and intercrossed with Prnpo/o mice [5] , [14] . Tg37 mice allowing for conditional PrP deletion was generated on a Prnpo/o FVB background [15] . GABA-Aα6-CRE-;loxPrP-tg37 littermates were used as negative controls ( PrPCGC+ ) . Prnpo/o and Prnpo/o;tga20+/+ ( tga20 ) , were on a mixed 129Sv/BL6 background [5] , [16] . Rocky Mountain Laboratory strain ( RML; passage #6 ) and 22L prions were amplified in CD1 mice , and 139A prions were amplified in C57BL/6 mice , by intracerebral inoculation into the lateral forebrain of 30 µl 1% ( wt/vol ) brain homogenate . Organotypic cerebellar slice cultures , 350 µm thick , were prepared from 10–11 day-old pups according to a previously published protocol [17] . Cultures were inoculated with 100 µg brain homogenate per 10 slices . Brain homogenate was diluted in 2 ml physiological Gey's balanced salt solution ( GBSS ) ( NaCl 8 g l−1 , KCl 0 . 37 g l−1 , Na2HPO4 0 . 12 g l−1 , CaCl2 2H2O 0 . 22 g l−1 , KH2PO4 0 . 09 g l−1 , MgSO4 7H2O 0 . 07 g l−1 , MgCl2 6H2O 0 . 210 g l−1 , NaHCO3 0 . 227 g l−1 ) supplemented with the glutamate receptor antagonist kynurenic acid ( 1 mM ) ( GBSSK ) . Slices were incubated with infectious brain homogenates as free-floating sections for 1 h at 4°C . Slices were then washed twice in 6 ml GBSSK , and 5–10 slices were placed on a 6-well Millicell-CM Biopore PTFE membrane insert ( Millipore ) . After removing any residual buffer , inserts were transferred to a cell culture plate and cultured in “slice-culture medium” ( 50% vol/vol MEM , 25% vol/vol basal medium Eagle and 25% vol/vol horse serum supplemented with 0 . 65% glucose ( wt/vol ) , penicillin/streptomycin and glutamax ( Invitrogen ) ) . Cultures were kept in a standard cell incubator ( 37°C , 5% CO2 , 95% humidity ) and the culture medium was exchanged three times weekly . Slices were harvested for protein analyses or fixed for immunocytochemical analysis at various time points . Drug treatment was initiated 21 days post-inoculation ( dpi ) in all cases . Drugs were re-added at every medium change . Appropriate drug concentrations were determined by literature search , and we assumed that slice culture uptake of compounds were similar to other cell culture systems . The toxicity of each compound was assessed by measuring NeuN immunoreactivity in parallel on infected and non-infected slices; if toxicity occurred , drugs were retested at a lower concentration . Drug and concentration used were ( 2S , 3S ) -trans-epoxysuccinyl-L-leucylamido-3-methylbutane ethyl ester ( E64d , 15 µM , Bachem ) , z-Val-Phe-CHO ( MDL-28170 , 50 µM ) , N-benzyloxycarbonyl-L-leucylnorleucinal ( calpeptin , 100 µM ) , benzyloxycarbonyl-Asp-Glu-Val-Asp ( OMe ) fluoromethylketone ( zDEVD-fmk , 20 µM ) , N-acetyl-L-α-aspartyl-L-α-glutamyl-N- ( 2-carboxyl-1-formylethyl ) -L-valinamide ( Ac-DEVD-CHO , 20 µM , Promega ) , benzyloxycarbonyl-Val-Ala-Asp ( OMe ) fluoromethylketone ( zVAD-fmk , 40 µM , R & D Systems ) . Drug and concentration used for antiprion compounds were: pentosan polysulphate ( PPS , 300 ng ml−1 , kindly provided by Bene pharmachem ) , quinacrine ( 1 µM ) , Congo red ( 1 µg ml−1 ) , amphotericin B ( 4 . 5 µg ml−1 ) , suramin ( 50 µM ) , curcumin ( 1 µM ) , cannabidiol ( 5 µM , Tocris ) , imatinib mesylate ( 10 µM , LC Laboratories ) and 2 , 6-dichlorobenzylideneaminoguanidine acetate ( guanabenz , 5 µM ) . Aggregated PrP was assessed using the Misfolded Protein Assay [18] , [19] . Brain homogenate containing 5 µg protein was diluted in 1 ml TBS-T and subjected to affinity-based PrPSc enrichment using magnetic beads coupled to the peptoid ASR-1 ( KKKFKF ) . Samples were incubated for 1 h at 37°C under permanent agitation ( 750 rpm ) , washed , and digested with trypsin ( 50 µg ml−1 in 0 . 01 M CaCl2 ) for 30 min at 37°C ( 750 rpm ) [20] . Captured PrP was released and disaggregated by adding 75 µl of 0 . 1 N NaOH ( 10 min; 750 rpm ) . After neutralization ( 30 µl 0 . 3 M Na2H2PO4 , 5 min , 750 rpm ) , samples were placed on a magnet to remove the beads , and 150 µl supernatant was analyzed by a PrP ELISA by transferring the samples to POM19-coated ELISA plates [21] . After 1 h incubation at 37°C ( 30 rpm ) , plates were washed and POM2-AP was added ( 1 h , 37°C ) . After 3 washes , Lumiphos plus substrate ( ECL , Amersham ) was added , incubated for 30 minutes at 37°C , and plates were read using a chemiluminescence reader . All samples were analyzed at dilutions falling within the logarithmic dose-response range of the calibration curves . A FRET based assay was established for the purpose of quantifying FL-PrP expression in cerebellar slices . Europium ( Eu3+ ) donor and allophycocyanin ( APC ) acceptor fluorophores were coupled to anti-PrP holoantibodies POM1 and POM2 recognizing the globular domain and the octarepeats , respectively . The donor POM1-Eu3+ conjugate is excited at wavelength 340 nm and transfers energy to the acceptor conjugate POM2-APC when the distance between acceptor and donor is <10 nm . POM2-APC then emits light at wavelength 665 nm , which can be measured with a suitable time-resolving spectrofluorimeter . To detect PrP level in homogenates , COCS were lysed; the Eu2+-POM1 and APC-POM2 antibody pair was added , measured immediately using a FRET reader and normalized to total protein . Cerebellar slices were lysed in buffer containing 50 mM Tris-HCl pH 8 , 0 . 5% Na deoxycholate , and 0 . 5% Triton X-100 . COCS were washed twice in PBS . Cerebellar tissue was then scraped off the membrane using 10 µl PBS per slice , and homogenized by trituration using a 30 G syringe , followed by 2×30 s pulses in a sonicator bath . Protein concentration was determined using the bicinchoninic acid assay ( Pierce ) . Samples were adjusted to 20 µg protein in 20 µl and digested with 25 µg ml−1 proteinase K in digestion buffer ( 0 . 5% wt/vol sodium deoxycholate and 0 . 5% vol/vol Nonidet P-40 in PBS ) for 30 min at 37°C . This protocol allowed specific detection of PrPSc as shown previously [13] . PK digestion was stopped by adding loading buffer ( NuPAGE , Invitrogen ) and boiling samples at 95°C for 5 min . Proteins were separated on a 12% Bis-Tris polyacrylamide gel or for higher molecular weight proteins on a 4–12% gradient gel ( NuPAGE , Invitrogen ) and blotted onto a nitrocellulose membrane . Membranes were blocked with 5% wt/vol Topblock ( Fluka ) in Tris-buffered saline supplemented with Tween ( 150 mM NaCl , 10 mM Tris HCl , 0 . 05% Tween 20 ( vol/vol ) ) and incubated with primary antibodies in 1% Topblock . Primary mouse monoclonal antibodies used were: POM1 mouse IgG1 antibody raised against PrPC ( anti-PrPC ) ( 200 ng ml−1 ) , anti-α-fodrin ( AA6 , 100 ng ml−1 , Millipore ) , anti-GAPDH ( 200 ng ml−1 , Millipore ) , and anti-actin ( 200 ng ml−1 , Chemicon ) . Secondary antibody used was horseradish peroxidase ( HRP ) -conjugated rabbit anti–mouse IgG1 ( 1∶10 , 000 , Zymed ) . Blots were developed using SuperSignal West Pico chemiluminescent substrate ( Pierce ) and visualized using the VersaDoc system ( model 3000 , Bio-Rad ) . COCS samples for fodrin blots were harvested in PBS with 0 . 5% DOC , 0 . 5% NP-40 supplemented with 1 mM AEBSF and complete mini protease inhibitor cocktail ( Roche ) . Because of inefficiencies intrinsic to the tissue slice homogenization procedure , some variation in loading occurred and as a consequence all samples were normalized to GAPDH as a loading control . In vivo samples for fodrin blots were homogenized in PBS with 0 . 32 M sucrose supplemented with 1 mM AEBSF and ‘Complete mini’ protease-inhibitor mix . All samples were normalized to alpha-tubulin . PNGase treatment was performed using a commercially available kit , according to the manufacturer's protocol ( New England Biolabs ) . In brief , 10 µg protein was treated with 2 µl denaturation buffer in a 20 µl reaction and incubated for 15 min at 95°C . A reaction mixture of 2 . 6 µl G7 , 2 . 6 µl NP-40 ( 10% ) , as well as 0 . 5 µl PNGase was added and samples were incubated for 4 h at 37°C . Samples were then mixed with loading dye , cooked and analyzed by western blotting . Histoblot analysis was performed according to a standard protocol using 50–100 µg ml−1 PK ( 30 min , 37°C ) [22] . Fresh tissue sections were incubated on PVDF membranes soaked in lysis buffer . After protein transfer , membranes were digested with PK for 4 hours and PrPSc was detected with antibody POM1 to PrP . The fluorescence Apoptag TUNEL assay was performed on formalin fixed tissue sections according to the manufacturers protocol ( Millipore ) . For immunocytochemistry , the organotypic slices were washed twice in PBS and fixed in 4% formalin overnight at 4°C . Membrane inserts were washed and incubated for 1 h in blocking buffer ( 0 . 05% vol/vol Triton X-100 and 3% vol/vol goat serum dissolved in PBS ) and incubated with primary antibodies diluted in blocking buffer at 4°C for 3 d . Primary antibodies and concentrations used were ascites fluid of mouse anti–chicken calbindin IgG1 antibody ( 1∶2 , 000 , Swant ) , rabbit anti-activated caspase 3 ( 1∶300 , BD Biosciences ) , rabbit anti-human synaptophysin ( 1∶300 , Zymed ) , rat anti-MBP IgG2a ( 1∶700 , Serotec ) and mouse anti-Neuronal Nuclei ( NeuN , 1 µg ml−1 , Millipore ) . The primary antibodies were detected using Alexa-conjugated secondary antibodies ( 3 µg ml−1 , Molecular Probes ) and counterstained with 4 , 6-diamidino-2-phenylindole ( dapi ) ( 1 µg ml−1 ) . For NeuN morphometry images were recorded at 4× magnifications on a fluorescence microscope ( BX-61 , Olympus ) equipped with a cooled black/white CCD camera and for caspase-3 stains on a Leica SP5 confocal laser scanning microscope using a 63× oil immersion lens . NeuN images were acquired at identical exposure times , and the area of immunoreactivity was determined by morphometry with image analysis software analySIS vs5 . 0 using identical grey-scale threshold settings for identifying positive pixels . Histology was performed on formalin-fixed , formic-acid decontaminated COCS . Specifically , COCS were dehydrated and embedded in paraffin with their membrane support . The paraffin blocks were then turned by 90 degrees , re-embedded , and cut for conventional histology . For caspase-3 activity determinations , slices were harvested in pools ( n = 20 ) in PBS , 0 . 5% DOC , 0 . 5% NP-40 with 2% β-mercaptoethanol and homogenized by trituration . Homogenates were analyzed immediately for DEVDase activity using caspase 3 fluorometric detection kit ( Assay design ) and normalized to protein concentration determined by Bradford assay . Organotypic slice cultures were prepared and incubated as previously stated . Cultures were washed once with PBS and total RNA was extracted using TRIzol reagent ( Invitrogen Life Technologies ) according to the manufacturer's protocol . Before cDNA synthesis , residual genomic DNA was removed using the DNA-free kit ( Ambion ) ; cDNA was synthesized from 1 mg total RNA with the QuantiTect reverse transcription kit ( Qiagen ) using random hexamers according to the manufacturer's protocol . We tested for successful cDNA synthesis ( +reverse transcriptase ) and contamination of total RNA with genomic DNA ( −reverse transcriptase ) by PCR with primers specific for β-actin ( Actb ) . Quantitative real-time PCR was performed using the SYBR Green PCR Master Mix ( Applied Biosystems ) on an ABI PRISM 7700 Sequence detector ( PerkinElmer ) . Regulation was calculated relative to untreated wildtype slices after normalization to the Actb signal . The following primer pairs were used: Actb sense , 5′-GAC GGC CAG GTC ATC ACT AT-3′; antisense , 5′-ACA TCT GCT GGA AGG TGG AC-3′ . TNF sense , 5′-CAT CTT CTC AAA ATT CGA GTG ACA A-3′; antisense , 5′-TGG GAG TAG ACA AGG TAC AAC CC-3′ . MCP-1 sense , 5′-TTA AAA AAC CTG GAT CGG AAC CAA-3′; antisense , 5′-GCA TTA GCT TCA GAT TTA CGG GT-3′ . Rantes sense , 5′-ATG CCG ATT TTC CCA GGA CC-3′; antisense , 5′-TTT GCC TAC CTC TCC CTA CTG-3′ . Slices were washed in Na-phosphate buffer , fixed in freshly prepared 2% PFA+2 . 5% GA in 0 . 1 M Na-phosphate buffer 0 . 1 M pH 7 . 4 , postfixed in osmium tetroxide , embedded in epon and examined with transmission electron microscopes Jeol JEM 1011 and 100CX . Each sample grid was divided into 20 equally sized “grid squares” and the number of objects of interest ( vacuoles , dystrophic neurites and tubulovesicular structures ) was determined for each “grid square” covered by tissue . For propidium iodide ( PI ) incorporation , slices were incubated for 30 min with PI ( 5 µg ml−1 ) and images were recorded in living tissue using a fluorescent microscope ( Axiovert 200 ) equipped with a cooled CCD camera using a 5× objective . Images were analyzed by morphometry . Prion-susceptible neuroblastoma cells ( subclone N2aPK1 ) [23] were exposed to 300-µl brain homogenates using 6–12 replicas per dilution in 96-well plates for 3 d . Cells were subsequently split three times 1∶3 every 2 days , and three times 1∶10 every 3 d . After the cells reached confluence , 25’000 cells from each well were filtered onto the membrane of ELISPOT plates , treated with PK ( 0 . 5 µg ml−1 for 90 min at 37°C ) , denatured , and infected ( PrPSc+ ) cells were detected by immunocytochemistry using alkaline phosphatase-conjugated POM1 mouse anti-PrP and an alkaline phosphatase-conjugated substrate kit ( Bio-Rad ) . We performed serial tenfold dilutions of experimental samples in cell culture medium containing healthy mouse brain homogenate . Scrapie-susceptible PK1 cells were then exposed to dilutions of experimental samples ranging from 10−4 to 10−6 ( corresponding to homogenate with a protein concentration of 10 µg ml−1 to 0 . 1 µg ml−1 ) , or to a 10-fold dilution of RML or healthy mouse brain homogenate . Samples were quantified in endpoint format by counting positive wells according to established methods [23] . One-way ANOVA with Tukey's post-test for multi-column comparison or a Dunnet's post-test for comparison of all columns to a control column were used for statistical analysis of experiments involving the comparison of three or more samples . Paired Student's t-test was used for comparing two samples . Results are displayed as the average of replicas ± s . d . UniprotKB Reference Sequence: Beta-actin - P60710 , Caspase-3 - P70677 , CD68 - P31996 , Fodrin ( αII-spectrin ) - P16546 , GABAAα6 - P16305 , GFAP - P03995 , MBP - P04370 , MCP-1 - P10148 , NeuN - Q8BIF2 , PrP27-30 - P04925 , Rantes - P30882 , TNF - P06804 .
We exposed COCS prepared from tga20 and Prnpo/o mice to the three distinct prion strains , RML , 22L , and 139A . At 42 dpi , PrPSc was detected in tga20 COCS exposed to each strain ( Figure 1C ) , but neither in Prnpo/o COCS nor in NBH-exposed tga20 COCS , confirming that COCS are infectible with many different prion strains , and that PrPSc reflected de novo synthesis rather than residual inoculum . Similar results were obtained for wt COCS at 56 dpi ( Figure 1C ) , although the lower PrPC expression resulted in lower PrPSc levels ( Figure S2F ) . Different prion strains induce distinct patterns of PrPSc deposition and lesion profiles , and can differentially target distinct neuronal subpopulations . Histoblots of COCS revealed strikingly strain-specific PrPSc deposition patterns . RML induced a diffuse signal akin to the “synaptic” pattern seen in vivo; 22L induced a plaque-like pattern with dense , multifocal deposits; and 139A induced ubiquitous PrPSc patches except in the central white matter ( Figure 1D ) . Prion-infected wt COCS at 42 dpi displayed patterns equivalent to those found in tga20 COCS at 35 dpi . No signal was seen in histoblots of prion-challenged Prnpo/o and NBH-challenged tga20 COCS ( Figure 1D ) . RML infected tga20 COCS showed a selective loss of NeuN+ cells at 42 dpi ( Figure 2A ) . NeuN+ cell loss was undetectable at 28 dpi , and was absent from Prnpo/o COCS at 42 dpi , but was conspicuous and significant in RML-infected COCS at 42 dpi ( Figure 2B ) . Therefore neurodegeneration was driven by prion replication rather than by toxic inoculum constituents . The severity of the spongiform changes was similar to that of cell loss: RML , 22L , and 139A-infected wt COCS ( 56 dpi ) displayed vacuoles in 20 , 30 , and 33% of all EM grid squares respectively , whereas no vacuolation occurred after NBH challenge ( Table 1 ) . Many of these vacuoles were myelinated , consistent with intraaxonal localization . RML , 22L , and 139A infected wt COCS ( 56 dpi ) displayed dystrophic neurites in 23 , 12 and 21% of all grid squares respectively , with no degenerating neurites observed in NBH samples ( Table 1 ) . Tubulovesicular structures were sporadically observed in all strains , but never in NBH samples ( Table 1 ) . Selective ablation of PrP on cerebellar granule neurons ( CGCs ) using GABAAα6-cre mice [14] intercrossed to PrP tg37 mice [15] ( PrPΔCGC ) resulted in abrogation of RML-induced loss of NeuN+ cells , showing that neuronal PrP confers neurotoxic signaling ( Figure 2C , S3B ) . Concomitantly with cell loss , a strong induction of inflammatory cytokines TNFα , MCP-1 , and Rantes was observed at 6 weeks post-inoculation in RML tga20 cultures , but not in RML-treated Prnpo/o COCS [5] ( Figure 2D–E ) . Samples in Figure 2D were normalized to tga20 NBH samples at 14 dpi and samples in Figure 2E were normalized to NBH treated Prnpo/o samples using the ΔΔCt method . The inflammatory mediators were found to be upregulated over NBH-exposed slices across 4 independent sets of samples analyzed by real-time PCR or microarray analysis , each with 4 biological replicas per group ( data not shown ) . Several compounds reported to abrogate prions from infected cell lines were tested on wt COCS for their ability to suppress prion deposition . In order to study their potential to ameliorate prion neurotoxicity , instead , we opted to use tga20 COCS because they showed accelerated cell loss and smaller interslice variability . In order to distinguish between interference with prion replication and prevention of initial infection , drug treatment was initiated at 21 dpi ( Figure 3A ) when PrPSc accumulation was already conspicuous [13] . At 35 dpi , before the appearance of neurotoxicity , PrPC and PrPSc were measured in wt samples by Western blotting ( Figure 3B–C , S4A , n = 2–3 ) . In addition , we measured protein aggregation by the misfolded protein assay ( MPA ) , which selectively captures PrP aggregates and upon a limited trypsin digestion returns quantitative responses over a 4-log range [19] ( Figure 3D , S4B; n = 4 ) . Prion titers were determined by the scrapie cell assay in end-point format ( SCEPA; Figure 3D; n = 3 ) [23] . Finally , drug-treated tga20 COCS were maintained until 42 dpi and analyzed by NeuN morphometry ( Figure 3E–F; n = 10 ) . Neurotoxicity was defined as significant NeuN+ CGC loss over NBH treatment , and neuroprotection was defined as significant NeuN+ CGC rescue ( p<0 . 05 ) over infected , untreated COCS . By these criteria , pentosan polysulphate ( PPS ) , amphotericin B , Congo red , porphyrin , suramin , imatinib , and E64d were neuroprotective , with several compounds completely preventing cell loss ( Figure 3E ) . No compounds were toxic to non-infected cultures at the concentration used ( Figure S4C ) . We then studied the effects of each compound onto PrPSc accumulation , PrP aggregation , and prion infectivity by quantitative Western blotting after PK digestion , MPA , and SCEPA , respectively . PPS , suramin , amphotericin B , guanabenz and imatinib showed a strongest suppression of infectivity , PrP aggregation , and PK resistance , whereas curcumin , cannabidiol and quinacrine were ineffective ( Figure 3C–D ) . In RML infected drug treated COCS total PrP ( PrPC+PrPSc ) was only marginally affected ( Figure S4A ) . In uninfected cultures the amount of total PrP was unaffected by drug treatment ( Figure S4D; n = 3 ) . By western blotting , suramin samples showed decreased FL-PrP and E64d samples showed increased FL-PrP , suggesting that E64d affects lysosomal degradation of PrP ( Figure S4D ) . A significant reduction in FL-PrP was observed only for suramin and quinacrine treated cultures by FRET assay ( Figure S4E; n = 4 ) , suggesting that the anti-prion drug effects affected predominantly PrPSc ( Figure S4A ) . Surprisingly , Congo red increased PK resistance while suppressing infectivity and aggregation ( Figure 3C–D ) . The dissociation of aggregation and PK resistance from infectivity suggests that Congo red acts differentially on the stability and frangibility of PrP aggregates , as previously described for other amyloidotropic compounds in prion-infected COCS [3] , [24] . In agreement with this notion , incubation of RML brain homogenate with Congo red sufficed to confer increased PK-resistance ( Figure S4F ) , while relative aggregation was not significantly affected ( Figure S4G ) . Quinacrine , but no other compound , also afforded partial neuroprotection against 3 mM H2O2 ( Figure S4H ) . Prion-infected COCS displayed TUNEL+ ( 136±53 vs . 19±13 cells/mm2; p = 0 . 0014; n = 10 , Figure S5A–B ) and propidium-iodide retaining ( PI+ ) cells ( Figure 4A–B; n = 10 ) , although to a much smaller extent than staurosporine treated COCS ( 48 h; >2000 TUNEL+ cells/field , Figure S5A–B ) . The progressive increase in PI+ cells between 35–42 dpi correlated temporally with NeuN+ cell loss ( Figure 4A; n = 10 ) . Although there was some variability between individual brain slices , all infected cultures showed severe damage at later incubation times ( Figure S6A–B ) . PI+ cells were mostly confined to the CGL ( asterisk ) , whereas staurosporine induced rapid and widespread cell death also affecting the CGL ( Figure 4B ) . Hence prion-induced cell death was mostly apoptotic , chronic-progressive rather than acute , and preferentially targeting the CGL . Whilst PPS , Congo red , and amphotericin B counteracted neurotoxicity by inhibiting prion replication , E64d prevented neurotoxicity , yet it did not reduce MPA readings , and enhanced prion titers and PrPSc deposition ( Figure 3E ) , suggesting that it interfered with neurotoxic events downstream of prion replication . Accordingly , E64d did not affect PrPSc glycosylation ( Figure 4C ) , total PrP expression and running pattern ( Figure 4D ) , and PrP processing into C1 and C2 fragments in prion-infected COCS , although a reduction in full-length PrP was observed ( Figure 4E , S7 ) . Because E64d inhibits cystein proteases including calpains , we investigated a possible involvement of calpains in neurotoxicity . Both calpains and caspases can cleave α-fodrin into a 150 kDa fragment . In addition , calpains selectively generate a diagnostic 145 kDa fragment whereas caspases give rise to a 120 kDa fragment [25] . Faint 145 kDa α-fodrin bands were barely apparent in uninfected COCS , but displayed increased intensity upon prion infection ( n = 3; p<0 . 01 at 37 dpi ) , peaking at 37–42 dpi on a timescale consistent with increased PI incorporation ( Figure 4A , F , G ) . Therefore , enhanced α-fodrin cleavage generating the 145 kDa fragment accompanies prion-induced neurodegeneration , suggesting calpain activation . Fodrin cleavage was counteracted by inhibiting prion replication with anti-prion compounds PPS , congo red , and amphotericin B ( Figure 4H–I; n = 3; p<0 . 001 ) and was also induced by a second prion strain , 22L ( Figure 4J–K; n = 4 , p<0 . 05–0 . 01 ) . The 145 kDa fodrin cleavage product was also increased in brains of terminally sick 22L infected tga20 mice and RML infected wt mice , suggesting prion-induced calpain activation in vivo ( Figure 4L–M; n = 3–5 , p<0 . 01 ) . We then sought to dissect the relative contribution of calpain and caspases to COCS neurotoxicity . Two further calpain inhibitors , MDL-28170 and calpeptin , also significantly reduced prion neurotoxicity ( Figure 5A , S8A; n = 9 ) . Conversely , the prevalence of cells containing activated caspase 3 ( aC3 ) was similar in uninfected vs . prion-infected COCS ( 79±53 vs 139±53 cells/mm2; n = 8; p>0 . 05 ) , and enhanced by staurosporine treatment ( 24 h; 660±295 cells/mm2; p<0 . 01; Figure 5B–C ) . Also , DEVDase activity in COCS homogenates did not increase significantly upon prion infection ( Figure 5B; n = 4 , p>0 . 05 ) . Crucially , the caspase inhibitors z-DEVD-fmk and z-VAD-fmk antagonized staurosporine-induced toxicity ( Figure S8B ) , yet neither compound conferred antiprion neuroprotection ( Figure 5D; n = 10 ) . We then treated prion-infected COCS with protease inhibitors starting at 21 dpi , and harvested samples at 41 dpi . The prion-dependent increase in α-fodrin cleavage was reduced by E64d ( n = 7 , p<0 . 01 ) , calpeptin and MDL-28170 treatment ( n = 3 , p<0 . 05–0 . 01 ) , but not by caspase inhibition by z-DEVD-fmk ( Figure 5E–H; n = 6 , p>0 . 05 ) . The above results imply that calpains , rather than caspases , are causally involved in prion-induced α-fodrin cleavage and neurotoxicity .
Prion infection of COCS faithfully reproduced all salient features of the pathogenesis of prion diseases: ( 1 ) progressive , profound neuronal loss after a protracted asymptomatic incubation time ( 42 dpi in tga20 COCS ) , ( 2 ) a proinflammatory glial response with vigorous upregulation of Rantes , MCP-1 and TNFα , ( 3 ) typical neuropathological changes such as spongiform changes , tubulovesicular structures , and neuroaxonal dystrophy , and ( 4 ) an excessive meshwork of astrocytic processes exceeding that observed in controls and reminiscent of gliosis . Conversely , CGC loss in COCS was faster and stronger than in prion-infected animals [26] , suggesting that prion clearance may be less efficient in COCS than in vivo . Compounds suppressing prion replication and/or interacting with PrPSc ( PPS , CR , porphyrin , amphotericin B , imatinib and suramin ) were neuroprotective in the COCS-based screen , whereas compounds previously reported to be effective in prion-infected cell lines but not in vivo ( quinacrine [27] , [28] , curcumin [29] , and cannabidiol [30] ) were ineffective despite the report of a direct interaction of curcumin with PrPC ( Table S1 in Text S1 ) . Hence inhibition of prion replication was neuroprotective to COCS , and the COCS neurodegeneration assay predicted in vivo efficacy more accurately than cell-based assays . Not all drugs acted in a perfectly consistent manner in all assays – a fact which reflects the biophysical and biological differences between the variables measured by each assay . In particular , Guanabenz treatment decreased prion infectivity , but failed to show neuroprotection . This may reflect subliminal drug toxicity , which indeed became evident after treatment of COCS with higher concentrations of guanabenz ( data not shown ) . Congo red increased the protease resistance of PrP , yet it decreased the capture of protein aggregates and prion infectivity . This is consistent with results from cultures treated with other amyloid-binding compounds [3] , [24] and probably indicates that these compounds hinder prion replication by hyperstabilizing protein aggregates . Indeed , congo red was reported to regulate the stability of PrPSc aggregates [31] and we found that PK resistance of PrPSc was enhanced by Congo red treatment . Suramin yielded slightly higher MPA readings than what might have been expected from PrPSc and infectivity determination , suggesting that it might partially unfold prion fibrils and make them more available for MPA capture . Porphyrin reduced PrPSc and MPA readings , and was neuroprotective , yet it did not affect prion titers . These discordant findings suggest that porphyrin may render PrPSc less toxic without appreciably reducing prion replication . E64d was neuroprotective to COCS despite slightly enhanced PrPSc and infectivity accumulation , suggesting blockade of neurotoxic pathways downstream of prion replication . E64d inhibits preferentially cathepsins B , H , and L as well as calpains , which participate to cell death [32] in excitotoxicity [33] , brain ischemia [34] and Alzheimer's disease [35] . Further calpain inhibitors ( calpeptin and MDL-28170 ) were also neuroprotective in vitro and all blocked the calpain-specific cleavage fragments of the substrate fodrin . Instead of reducing prion replication or C2 cleavage [36] , E64d enhanced prion accumulation in COCS , possibly by inhibiting their lysosomal degradation . Caspases can be cleaved by calpains [37] , and prion-infected brains can contain scattered caspase-3+ and TUNEL+ cells [38] . Although prion-infected COCS also harbored TUNEL+ cells , we failed to detect any caspase activity , any activated caspase-3 , and any caspase-dependent α-fodrin cleavage . Crucially , two distinct caspase inhibitors failed to confer neuroprotection . These data suggest that prion neurotoxicity is calpain-dependent but caspase-independent in CGCs . The prevalence of PI+ cells rose rapidly at the time of onset of enhanced α-fodrin cleavage and was closely followed by neuronal loss , suggesting that calpain-driven cell death was quickly followed by lysis and removal . Calpain activation strongly suggests that exaggerated calcium influx may represent an important upstream event in pathogenesis . We have attempted to test the latter hypothesis directly , but the slow progression of prion pathology in COCS ( which is similar to that observed in vivo ) posed significant obstacles . In particular , we found that chronic treatment of COCS with Ca2+ chelators or protracted culture in low-calcium medium was too toxic to allow for any firm conclusion ( data not shown ) . We here identify calpain inhibition as an experimental paradigm that uncouples prion replication from neurotoxicity . While a few other examples of retarded neuropathogenesis despite florid prion replication where reported earlier by us and others [39] , [40] , the molecular mechanism of such uncoupling had remained unclear . The data presented here suggest that uncoupling occurs because calpain is a crucial link between prion-induced intracellular hypercalcemia and cell death . It will be exciting to test whether the chain of event hypothesized above may be manipulated in order to control prion-induced damage rather than prion replication . Beyond the biological phenomena described above , a significant advance provided by this study consists - in our view - of providing a convenient experimental paradigm that combines the exquisite accessibility of in vitro systems with the rich palette of neurotoxic and neurodegenerative events characteristic of prion diseases , such as spongiform changes , neuronal loss , and astrogliosis . The latter features could hitherto only be studied in prion-infected experimental animals , since prion-infected cell lines do not exhibit significant cytotoxicity . The successful transposition of prion-specific neurodegenerative features to cultured tissues does away with many issues of pharmacokinetics , bioavailability , and animal welfare , thereby enabling a broad range of pharmacological experiments that had been hitherto impractical or impossible . It is to be hoped that many laboratories will make use of the technologies described here , and that neurodegenerative prion science will consequently progress at a faster pace . | Transmissible spongiform encephalopathies ( TSEs ) are a group of fatal protein misfolding diseases causing neurodegeneration in vivo . TSEs are unique in that the infectious agent termed ‘prion’ consists of a misfolded protein lacking sequence specific nucleic acids . Prion-infected cultured cells do not develop visible pathological changes , and this has hampered mechanistic studies of prion-induced neurodegeneration . Here , we have developed a prion-induced neurodegeneration model that uses cultured slices of living brain tissue . Such slices display all the classical hallmark of prion disease , namely prion replication , inflammation , spongiform changes and neurodegeneration . Neurotoxicity is blocked by anti-prion drugs by reducing prion replication . We demonstrate for the first time an involvement of calcium-regulated cysteine proteases called calpains in driving neurotoxicity . We find that the proteolytic processing of the calpain substrate is induced by prion infection and blocked by calpain inhibitors without prion replication being affected . The assay system developed here allows for precise dissection of the mechanisms of prion-induced degeneration with pharmacological means . | [
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] | 2012 | Prion Pathogenesis Is Faithfully Reproduced in Cerebellar Organotypic Slice Cultures |
Hairpin telomeres of bacterial linear chromosomes are generated by a DNA cutting–rejoining enzyme protelomerase . Protelomerase resolves a concatenated dimer of chromosomes as the last step of chromosome replication , converting a palindromic DNA sequence at the junctions between chromosomes into covalently closed hairpins . The mechanism by which protelomerase transforms a duplex DNA substrate into the hairpin telomeres remains largely unknown . We report here a series of crystal structures of the protelomerase TelA bound to DNA that represent distinct stages along the reaction pathway . The structures suggest that TelA converts a linear duplex substrate into hairpin turns via a transient strand-refolding intermediate that involves DNA-base flipping and wobble base-pairs . The extremely compact di-nucleotide hairpin structure of the product is fully stabilized by TelA prior to strand ligation , which drives the reaction to completion . The enzyme-catalyzed , multistep strand refolding is a novel mechanism in DNA rearrangement reactions .
Telomeres at the termini of linear chromosomes protect the DNA ends from degradation or aberrant repair reactions including end-fusion , while allowing complete replication of the terminal sequences [1] . The simplest form of telomere is a covalently closed hairpin loop found in bacteria carrying linear chromosomes , including Borrelia spirochetes—the causative agents of Lyme disease and relapsing fever [2] , [3] , Agrobacterium [4] , [5] , and cyanobacteria . Replication of such bacterial linear chromosomes with hairpin telomeres starts from an internal origin and proceeds bi-directionally , yielding a circular intermediate composed of a head-to-head , tail-to-tail dimer of chromosomes ( Figure 1A ) [6] , [7] . The circular dimeric chromosome is then resolved at the two inverted-repeat junctions , formed as replication traverses through the telomeres , by a dedicated DNA cleavage-rejoining enzyme called protelomerase ( also known as telomere resolvase ) to regenerate unit-length chromosomes with hairpin telomeres [8]–[11] . The protelomerase enzymes function as a dimer , making staggered cleavages of both strands of DNA to form covalent 3′-phosphotyrosine linkages , then exchanging the released 5′-ends while holding onto the 3′-ends , and finally sealing the broken DNA strands to generate two hairpin ends ( Figure 1B ) [12] , [13] . The phosphotyrosine-mediated DNA cleavage-rejoining reaction is chemically isoenergetic with no intrinsic directional bias , in a similar fashion to the reactions catalyzed by topoisomerases [14] and tyrosine-recombinases [15] that interconvert between linear double-helical DNA substrates and products . However , protelomerase is unique in that it converts the canonical duplex conformation of DNA into strained hairpin structures . Although the crystal structure of a bacteriophage-derived protelomerase TelK bound to a linear duplex substrate DNA was reported ( Figure S3 , top panel ) [16] , the TelK–DNA complex structure provided little information regarding events following the strand cleavages or structure of the hairpin telomere products . Thus , mechanisms by which protelomerase drives the hairpin formation reaction forward without an exogenous input of energy or getting trapped in a DNA cleavage–religation equilibrium are not well understood . We describe here a series of crystal structures of a bacterial protelomerase bound to reaction intermediates and hairpin products , which reveal that the enzyme dimer actively stabilizes both the tightly folded hairpin products and a transition state of DNA refolding pathway following the DNA strand cleavages . Furthermore , we show that the hairpin telomere formation by protelomerase is highly sequence-dependent , in line with the multistep strand-refolding mechanism suggested by the crystal structures . Thus , our collective results suggest that protelomerase catalyzes not only the chemical reactions of DNA strand cutting and rejoining but also the ordered transition between different DNA conformations to guide refolding of a DNA strand . Since DNA hairpins are formed as key intermediates in transposition [17]–[20] and the use of transposon-type motif by the Borrelia protelomerase/telomere resolvase ResT has been reported [21] , our findings on protelomerase could provide insights into the mechanisms of transposon-related DNA remodeling reactions , including the V ( D ) J recombination responsible for diversifying antigen-receptor genes in higher vertebrates [22]–[24] .
To better understand how protelomerase functions , we have crystallized the full-length protelomerase from the plant pathogen Agrobacterium tumefaciens C58 ( TelA ) in complex with DNA substrates containing the terminal sequences of the Agrobacterium linear chromosome . We used several types of DNA substrates ( Figure S1 ) resulting in crystal structures of TelA–DNA complexes that differ in the DNA conformation for the region ultimately forming the hairpin turn ( shown by red letters in Figure S1 ) . Phases for a parental TelA–DNA complex were obtained by the selenomethionine SAD phasing method , and all crystal structures have been refined to 2 . 2∼2 . 4 Å resolution . Due to strongly anisotropic diffraction , the resolution limits for the refinement were set differently along the three principal axes ( Table 1 ) . In the crystals , the asymmetric unit contains a single TelA molecule bound to a hairpin telomere sequence , and the crystallographic dyad generates the TelA homodimer responsible for resolution of a replicated hairpin telomere ( Figure 2 ) . Our models consist of residues 102 to 421 of the full-length 442 residues TelA protein bound to a half-site DNA substrate consisting of a 13 or 14 bp double-stranded stem and a 5′-overhang ( Figure S1 ) . The electron density for the N-terminal ∼100 residues was very weak , likely reflecting high flexibility . This region is not required for in vitro hairpin formation by TelA [5] . The TelA monomer consists of two structural domains , the catalytic domain and an α-helical bundle domain , that together clamp down the DNA substrate ( Figure 2 ) . While TelA shows significant sequence homology to the bacteriophage-derived protelomerase TelK [16] , [25] only in the ∼190-residue region of the catalytic domain including the active site residues ( ∼25% identity ) , the three-dimensional structure of TelA closely resembles that of the core part of the larger TelK protein ( Figure S2 ) . Each of the two domains of TelA interacts with DNA in both the major and minor grooves , with a total of 43 residues positioned in close proximity to DNA ( <3 . 6 Å ) . Six base-pairs of the binding site are recognized by direct hydrogen bonding interactions , with additional base-pairs involved in water-mediated hydrogen bonds or van der Waals contacts ( Figures 3 , S4 , and S5 ) . The α-helical linker ( Ala198–Gly217 ) connecting the two domains harbors several residues that make DNA contacts . Among these residues , Tyr201 and Arg205 play key roles in refolding the duplex DNA substrate into hairpin products as discussed later . The catalytic domains in the TelA dimer interact extensively with one another , burying 1 , 147 Å2 of surface area per subunit . The two protein molecules in the TelA dimer bound to DNA are positioned such that there is a large ( >10 Å ) offset in the DNA helical axes across the dimer interface , similar to the arrangement observed in the TelK–DNA complex ( Figures 2B and S3 ) [16] . By crystallizing the wild-type TelA bound to a palindromic target DNA nicked at the scissile positions 6 bp apart ( DNAa in Figure S1 ) in the presence of orthovanadate , we obtained a TelA dimer bound to the covalently closed hairpin products . The self-complementary six-base overhangs ( T1C2A3T4G5A6 ) with the native sequence of the Agrobacterium chromosome terminus form sharp hairpin turns in two alternating conformations , and are packed tightly between the two active sites in the TelA dimer ( Figure 4 ) . The vanadate moiety links the 5′-and 3′-OH groups across the DNA nick as well as the Tyr405 nucleophile in the active site , mimicking the pentavalent transition state of the DNA ligation reaction ( Figure 5 ) . The DNA strands take an extremely compact hairpin conformation in which all bases except two at the apex form the canonical Watson–Crick base-pairing . The two unpaired bases ( Ade3 and Thy4 ) remain intrahelical and stack on the base-paired stem of the hairpin DNA , with rises per base steps comparable to that in the B-form DNA ( ∼3 . 4 Å ) ( Figure 4A , B ) . The compact di-nucleotide hairpin structure is stabilized by TelA through a number of interactions . The guanidinium group of Arg205 makes a cation-π stacking interaction on the thymine base ( Thy4 ) at the tip of the hairpin turn ( Figure 4A , E ) . The stacking interaction by Arg205 is made in trans—that is , the interdomain linker contributing Arg205 to cap a hairpin DNA product connects the catalytic and DNA-binding domains clamping down the other hairpin half-site in the TelA dimer . The α-helical interdomain linker segment completely blocks the helical path of each DNA half-site , suggesting that the linear duplex substrate DNA would have to be severely distorted to fit in the DNA-binding path of the TelA dimer . The backbone phosphate group of Cyt2 , Ade3 , and Ade6 in the hairpin turn each forms both direct and water-mediated hydrogen bonds/salt bridges with TelA ( Figure 3 ) . Sequence-specific contacts are made by the carboxyl group of Glu400 that interacts with the unpaired Ade3 base in both of its two alternate sidechain conformers ( Figure 4A ) , Lys208 that hydrogen bonds with the O4 atom of Thy1 in the major groove , and Lys288 that interacts with the O2 atoms of Thy1 and Cyt2 in the minor groove ( Figure 6 ) . Refinement of the atomic model of the TelA-hairpin DNA–vanadate complex at 2 . 2 Å resolution allowed two alternate conformations of DNA strand in the hairpin turn to be resolved ( indicated by the red arrows in Figure 4A and 4C ) . The backbone phosphate group of Gua5 at the apex of the hairpin turn as well as the flanking bases Thy4 and Gua5 take two distinct positions with approximately equal partial occupancies . The terminal base Thy4 is stacked more closely with Arg205 in trans in one conformer , while the backbone phosphate of Gua5 in the other conformer forms a salt bridge with the same Arg205 in cis . Thus , Arg205 plays dual roles in stabilizing the tight hairpin turn bound to the TelA dimer . For steric reasons , the two juxtaposed hairpin ends in a TelA dimer must be in alternative conformations , which introduces asymmetry into the otherwise 2-fold symmetric TelA–DNA complex ( Figure 4E ) . The two hairpin ends have backbone phosphorus atoms positioned only 5 . 9 Å apart across the 2-fold axis ( intrastrand phosphorus distance in the B-form DNA is ∼6 . 8 Å ) , highlighting the tight packing of hairpin turns in the TelA dimer . Having revealed the structure of the hairpin telomere , we then asked whether stabilization of the extremely compact DNA hairpin conformation by TelA is dependent on covalent closure of the DNA strand . To address this question , we used TelA with a point mutation in one of the active site residues Arg255 that plays an essential role in coordinating the scissile phosphate ( Figure 4C and Figure 5 ) . TelA•R255A was crystallized in complex with the palindromic target DNA sequence nicked at the scissile positions ( DNAa in Figure S1 ) . The resulting 2 . 3 Å resolution crystal structure of the TelA•R255A–DNA complex shows the exact same hairpin DNA conformation as observed in the wild-type TelA–hairpin DNA–vanadate complex described above ( r . m . s . d . of 0 . 41 Å for the six nucleotides in the hairpin ) , except that the scissile phosphate-binding site is empty and nothing bridges the 5′ and 3′-OH groups of DNA ( Figure 4D ) . As the DNA hairpin region is free from crystal lattice contacts ( Figure S6 ) , the result suggests that the hairpin conformation observed in our crystal structures is the most thermodynamically preferred conformation of the telomere DNA sequence when bound to TelA , even in the absence of a covalent phosphodiester linkage . This argues against a model in which strand ligation captures the hairpin conformation of an otherwise flexible DNA strand during hairpin telomere formation by TelA . The crystal structures of the hairpin–DNA–TelA complexes suggest that a linear duplex substrate bound to the TelA dimer would be in a severely distorted conformation ( Figure S3 ) , as observed for the structure of TelK bound to a duplex substrate DNA [16] , and is thus transformed into the thermodynamically more favorable hairpin form once the DNA strands are cleaved . Despite the overall favorable reaction energetics , refolding of a duplex substrate into two hairpin products within the TelA dimer may not readily proceed due to steric and/or electrostatic interferences . To gain insights into how the 5′-ends are exchanged , refolded , and packed tightly within the partially buried interior of the stable TelA dimer , we determined crystal structures of the covalent phosphotyrosine TelA–DNA intermediate trapped using suicide DNA substrates . The first type of suicide DNA substrate used in our studies has nicks one base 3′ to the scissile positions ( DNAb or DNAc in Figure S1 ) [26] . Strand cleavage by TelA releases a single nucleotide ( Thy1 ) between the nick and the newly formed phosphotyrosine bond , removing the 5′-OH group necessary for strand ligation . The resulting DNA has five-base 5′-overhangs , one base short of the natural six-base 5′-overhang . Crystal structure of this phosphotyrosine complex refined at 2 . 2 Å resolution ( Figure 7A–C ) shows a unique “open” conformation of the DNA strand distinct from that observed for the compact hairpin telomere product ( Figure 7E ) . In this open conformation , the first base into the overhang region to be refolded ( Ade6 ) completely swings out into an extrahelical position and stacks against the Tyr201 sidechain . The positioning of Tyr201 is determined by water-mediated hydrogen bonds with the main chain carbonyl group of Ile170 , Thr174 sidechain , and a DNA backbone phosphate , whereas the swung-out conformation of Ade6 is stabilized by those involving Asp202 and Arg205 ( Figure 7A ) . The base plane of Ade6 has a ∼45° tilt with respect to the base planes in the duplex region . The second base , Gua5 , is also flipped out and is stacked on Ade6 . The third base , Thy4 , is positioned similarly to how it is positioned in the hairpin product structure ( Figure 7E ) where the Arg205 guanidinium group makes a cation-π stacking on its nucleobase moiety , while the other face of the Thy4 base stacks on its symmetry-mate across the 2-fold axis of the TelA complex . The sugar moiety of Thy4 stacks on the Gua5 base . In addition to these stacking interactions , the positioning of Gua5 and Thy4 is further stabilized by G-T wobble base-pairs ( Figure 7A , C ) . The syn conformation of the Gua5 base is well supported by simulated annealing omit difference electron density ( Figure 7C ) . While clear electron density was observed for the bases Thy4 , Gua5 , and Ade6 , the density was weaker and less continuous for the bases Cyt2 and Ade3 , suggesting higher flexibility near the 5′-terminus of the DNA strand ( Figure S7 ) . In the open DNA conformation observed in the phosphotyrosine complex , the trajectory of the linearly stacked Tyr201 sidechain , Ade6 , Gua5 , and Thy4 bases is completely blocked by the interdomain α-helix harboring Arg205 , and the DNA backbone makes a sharp turn to reverse the chain direction ( Figure 7A , B and Figure S7 ) . The irregular conformation of DNA with flipped-out bases , sharply bent backbone , and the flexible 5′-terminus suggests that it is an intermediate step in the DNA strand refolding pathway ( Figure 1B ) . Stabilization of the flipped-out bases Ade6 and Gua5 in extrahelical positions would help disrupt the original base-pairing in the duplex substrate , as well as clear space for exchanging the 5′-ends . The path of the DNA strand is set by the stacking interaction made by Tyr201 that orients the first base Ade6 and the capping interaction made by Arg205 that shapes the nascent hairpin loop structure . Point mutants TelA•Y201A and TelA•R205A are capable of cleaving DNA to form the phosphotyrosine complex , but they are completely inactive in producing hairpin products in vitro ( Figure 8A and Figure S8 ) . This underscores the important roles of Tyr201 and Arg205 in refolding DNA into a hairpin telomere . Consistent with the critical role of Tyr201 in orienting the tri-nucleotide stretch Ade6 , Gua5 , and Thy4 , a crystal structure of TelA•Y201A-DNA complex shows that Ade6 has swung out further toward the protein to partially occupy the space taken by Tyr201 in the wild-type enzyme , leaving other bases in the 5′-overhang flexible ( Figure 8B ) . Similarly , a crystal structure of TelA•R205A complexed with DNA carrying the natural self-complementary six-base 5′-overhang ( DNAb6 in Figure S1 ) shows an extended DNA conformation without hairpin loop formation or flipping of the Gua5 base into the syn conformation ( Figure 8B ) . Interestingly , Tyr319 and Arg322 of Tn5 transposase are part of a conserved “YREK” sequence motif found in the IS4 family of transposases and are involved in stabilizing the hairpin DNA conformation [18] . However , the precise roles of the Tyr and Arg sidechains appear to be different between Tyr319/Arg322 of Tn5 and Tyr201/Arg205 of TelA . Tyr201 of TelA rather plays an analogous role to Trp298 of Tn5 that stacks against a flipped-out DNA base in an extrahelical position [18] , [27] . In any case , a critical difference between the transposon and the hairpin telomere systems is that while base-flipping occurs in the transposase-bound hairpin DNA [18] , [28] , it is observed only in the refolding intermediate ( Figure 7A , B ) and not in the hairpin telomere product ( Figure 4A , B ) bound to TelA . The putative strand refolding intermediate with the open DNA conformation described above was obtained with a DNA substrate missing the terminal nucleotide Thy1 of the 5′-overhang ( DNAb or DNAc in Figure S1 ) . We reasoned that if it is indeed a transition state structure , the DNA strand could be trapped in the same conformation by introducing a mismatch in the natural palindromic six-base 5′-overhang to inhibit formation of the fully base-paired hairpin loop . Thus a second type of suicide DNA substrate was designed , in which the six-base overhang has cytosine in place of Thy1 to block base-pairing ( DNAd in Figure S1 ) . The Thy to Cyt substitution should also prevent the major groove interaction by Lys208 ( Figure 6 ) . Wild-type TelA mixed with this mismatched DNA substrate was trapped in a phosphotyrosine complex as expected . The crystal structure refined at 2 . 4 Å resolution shows that the six-base overhang adopts a conformation very similar to that observed for the nicked suicide substrate , with an r . m . s . d . of 0 . 78 Å for atoms in the tri-nucleotide stretch ( Figure 7D ) . We therefore concluded that the open DNA conformation observed in the trapped phosphotyrosine complexes represents a metastable state of the 5′-overhang , which precedes stable capturing of the 5′-end into the fully base-paired hairpin form . We propose that this “refolding intermediate” conformation allows TelA to overcome steric and/or electrostatic interferences between the DNA strands during refolding of a duplex substrate into the compact hairpin products ( Figure 1B ) . The mechanism is reminiscent of how enzymes in general catalyze chemical reactions by stabilizing intermediates , lowering energy barriers along reaction pathways [29] . To further validate our model on the mechanism of hairpin telomere formation , we examined effects of sequence variation in the DNA substrate . Based on the observed sequence-specific interactions that stabilize the hairpin product or the refolding intermediate including the G-T wobble pair , one would expect a strict requirement in hairpin telomere formation for the specific 6 bp DNA sequence between the two scissile positions . We therefore tested in vitro hairpin formation by TelA on a series of duplex DNA substrates with various palindromic sequences in the central 6 bp ( Figure 8C ) . Most of the nonnatural target sequences yielded no hairpin products , including 5′-TGATCA-3′ that corresponds to a natural target site after swapping Gua5 and Cyt2 ( Figure 8C , Lanes 3 and 12 ) . Nonetheless , these nonnative substrates were cleaved by TelA ( unpublished data ) . The results are consistent with our model that the DNA strands are refolded into hairpins guided by a set of specific protein–DNA and DNA–DNA interactions . It would be fair to note , however , that there are nonnative sequences that still support in vitro hairpin formation ( e . g . , Figure 8C , Lane 6 ) , and we found sequence changes at the tip of the hairpin turn ( Ade3 and Thy4 ) to be more tolerated in general [5] . Alternative base-pairing schemes , a G–G base-pair for instance [30] , may allow for formation of a refolding intermediate similar to that formed by the natural target sequence in such cases . The fairly elaborate mechanism of strand refolding by TelA described in this work raises a question as to how well it is conserved among protelomerase enzymes from different organisms . The basic architecture of the protelomerase dimer with a sharp disjunction in the DNA-binding path has been observed for both TelA and the bacteriophage-derived TelK systems ( Figure S3 ) [16] and is likely a common feature for this family of proteins . In addition , all known protelomerase enzymes make staggered DNA cleavages 6 bp apart [12] , [25] , [31] , where the conserved spacing between the scissile phosphates may reflect similarities in general mechanisms of hairpin telomere formation . On the other hand , the amino acid residues of TelA outside its catalytic domain , including those important in DNA refolding ( Tyr201 and Arg205 ) , do not appear to be particularly well conserved among protelomerase enzymes from different systems [32] . Moreover , DNA sequences of the hairpin telomeres from different organisms do not show strong similarities and each protelomerase system has unique target sequences . We have shown that a modified palindromic DNA substrate with 5′-CGCGCG-3′ between the scissile positions , as found in the native target sequence for TelK [25] , is not processed into hairpin products by TelA ( Figure 8C , Lane 9 ) . Similarly , TelK cleaves efficiently but does not produce hairpin products on a modified DNA substrate with 5′-GTATAC-3′ , as found in the presumed target sequence for the protelomerase from phage VHML [16] , [33] . The strict but distinct sequence requirements imply that stabilization of DNA refolding intermediates may be a common strategy employed by protelomerase enzymes , while the detailed refolding mechanisms , including specific protein–DNA and DNA–DNA interactions , likely differ among different organisms . Enzymes that rearrange/recombine DNA play important roles in diverse biological contexts [34] . A common strategy employed by these enzymes is to bind tightly to and stabilize the final products , thereby driving the reactions forward by virtue of DNA-binding free energies [35]–[37] . We have shown that this is indeed the case for the protelomerase TelA , a DNA rearrangement enzyme involved in the maintenance of Agrobacterium linear chromosome . Unexpectedly , however , we found that TelA facilitates the duplex-to-hairpin conversion by stabilizing not only the hairpin telomere product but also a transient strand-refolding intermediate to guide the DNA strand refolding process . We believe that the enzyme-catalyzed , multistep DNA refolding described in this study is a novel mechanism , and we suspect that similar strategies may be employed by other protein machineries that facilitate conformational changes/refolding of DNA or other macromolecules in various biological contexts .
The TelA protein and its mutants used in the present study have a 20-residue N-terminal His-tag attached to the full-length Agrobacterium tumefaciens protelomerase protein ( gene locus: Atu_2523 ) . The His-tagged TelA was overexpressed in E . coli strain BL21 under the control of the arabinose-inducible pBAD promoter and purified using the Ni-NTA and Heparin-Sepharose columns . Selenomethionine-labeled TelA was overexpressed in the methionine auxotroph strain B834 ( DE3 ) . All oligonucleotides were purchased from IDT in the standard desalting grade and used without further purification . The sequences of the oligonucleotides used in the crystallization experiments are available in Figure S1 . The target sequence for TelA was derived from either the left terminus ( for DNAa , DNAb , DNAd , and DNAb6 in Figure S1 ) or the right terminus ( for DNAc used to grow SeMet crystals ) of the Agrobacterium tumefaciens C58 linear chromosome ( Genbank #AE007870 . 2 ) . TelA–DNA complexes used in crystallization were prepared by mixing equal moles of protein monomer and DNA half-site at an approximate protein concentration of 0 . 2 mM and a NaCl concentration of ∼0 . 5 M . The hairpin DNA–TelA–vanadate complex was assembled in the presence of 10 mM sodium orthovanadate using a DNA substrate containing the six-base TCATGA overhang ( DNAa in Figure S1 ) . The R255A TelA–hairpin DNA complex was prepared using the same DNA in the absence of sodium orthovanadate . To prepare the phosphotyrosine complexes with cleaved DNA , the purified protein was mixed with either the CATGA ( nicked: DNAb , DNAc in Figure S1 ) or CCATGA ( mismatched: DNAd in Figure S1 ) suicide DNA substrate . Crystals of the TelA–DNA complexes were obtained by the hanging drop vapor diffusion method at 20°C . The well solution consisted of 5% ( w/v ) PEG 4000 , 10 mM Tris-HCl ( pH 7 . 4 ) , and 300 mM NaCl , and the hanging drops were formed by mixing the TelA–DNA complex with the well solution at a 1∶1 volume ratio . All TelA–DNA complexes were crystallized in the same crystal form under similar conditions , though the time it took for the crystals to appear varied depending on the DNA substrates used . The crystals were cryoprotected by gradually introducing glycerol to a final concentration to 25% , then flash frozen in liquid nitrogen . X-ray diffraction data were collected at the beamlines 14ID-B , 14BM-C , and 24ID-C of the Advanced Photon Source ( Argonne , IL ) . The structure of the TelA phosphotyrosine complex formed with a 1 bp longer suicide DNA substrate than the other DNA substrates ( 15 mer+19 mer: DNAc in Figure S1 ) was determined by the single-wavelength anomalous dispersion ( SAD ) method using the selenomethionine drivative . Two single-path scan datasets were collected at the selenium K-edge , one at a lower resolution ( 3 . 0 Å ) and one to a higher resolution ( 2 . 4 Å ) . Indexing , integration , and scaling of the collected diffraction frames were done using HKL2000 [38] or XDS [39] . Eleven selenium sites per TelA monomer were located with the lower resolution dataset ( 3 . 0 Å ) using SOLVE [40] . Resolution of the experimental phases was then improved by combining the two datasets , and density modification by RESOLVE generated an interpretable map . Automated model building by RESOLVE built ∼50% of the protein residues . Iteration of phase-restrained refinement using REFMAC5 [41] and manual model building using COOT [42] eventually generated a model consisting of 320 amino acids covering the TelA residues 102∼421 , and all DNA residues . The 121 N-terminal amino acids including the 20-residue His-tag , and the 21 C-terminal amino acids are disordered . Structures of all other complexes were determined by molecular replacement using PHASER [43] . All crystallographic models were finally refined using PHENIX [44] with the TLS refinement . X-ray diffraction data , phasing , and model refinement statistics are summarized in Table 1 . Severely anisotropic data were subjected to ellipsoidal truncation and anisotropic scaling [45] prior to structure refinements . Figures were produced using PYMOL ( www . pymol . org ) . Buried protein surface area was calculated using CNS [46] . Curves [47] and 3DNA [48] were used for DNA geometry analyses . A 50 bp region from Agrobacterium chromosome terminus centered on the target sequence of TelA , or its variant sequences , was cloned into the pSK plasmid to generate pAgSK54 . pAgSK54 linearized with the restriction enzyme AlwNI was purified using a Qiagen spin-column and was employed as the substrate in the in vitro resolution assay . The resolution reaction was performed with 10 nM linearized plasmid DNA and 6 . 7 µM TelA at 22°C for 2 h in 50 mM Tris-HCl ( pH 7 . 4 ) , 150 mM NaCl , and 1 mM DTT ( Figure 8A ) or at 30°C for 30 min in 20 mM Tris-HCl ( pH 7 . 5 ) , 50 mM potassium glutamate , and 1 mM DTT ( Figure 8C ) . The reactions were quenched by addition of proteinase K or SDS . The DNA products extracted by phenol extraction were separated on 1% argarose gel and visualized by ethidium bromide staining . The phosphotyrosine complex formation of the wild-type and mutant TelA proteins ( Figure S8 ) was monitored on a 44 bp nicked suicide substrate assembled from 24 mer and 20 mer oligonucleotides containing the 5′-CATG-3′ overhang . Protein at 10 µM was incubated with 2× molar excess of the suicide substrate DNA in the same buffer condition used for the resolution reaction . The reaction was quenched at each time point ( 1 h , 2 h , 1 d , 2 d , 3 d , and 1 wk ) by addition of SDS and the samples were analyzed by SDS-PAGE . The atomic coordinates and the structure factors for all crystal structures reported here have been deposited in the Protein Data Bank with accession codes 4E0G , 4E0J , 4E0P , 4DWP , 4E10 , 4E0Z , and 4E0Y . | Linear chromosomes capped by hairpin telomeres are widespread in prokaryotes and are found in important bacterial pathogens . However , three-dimensional structure of the hairpin telomere , as well as the molecular mechanisms underlying its generation , has remained poorly understood . In this work , we investigated how the enzyme responsible for generating the bacterial hairpin telomeres ( protelomerase , also known as telomere resolvase ) transforms a linear double-stranded DNA molecule into sharp hairpin turns . Our X-ray crystallographic and biochemical data collectively suggest that protelomerase employs a multistep DNA strand-refolding mechanism as described below . Protelomerase first cleaves both strands of a double-helical DNA substrate and reshapes the DNA strands into a transition state conformation ( refolding intermediate ) stabilized by specific protein–DNA and DNA–DNA interactions including noncanonical ( non-Watson–Crick ) base-pairs . The DNA strands are then refolded into extremely compact hairpin products , stabilized by a set of interactions distinct from those stabilizing the refolding intermediate . We believe that an enzyme “catalyzing” not only the chemical reactions of DNA strand cutting/rejoining but also the ordered transition between different DNA conformations to guide refolding of the DNA strand is a novel concept , and we suspect that similar mechanisms may be employed by other enzymes involved in conformational changes/refolding of biological macromolecules . | [
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] | 2013 | An Enzyme-Catalyzed Multistep DNA Refolding Mechanism in Hairpin Telomere Formation |
Zinc is an essential trace element that is required for the function of a large number of proteins . As these zinc-binding proteins are found within the cytosol and organelles , all eukaryotes require mechanisms to ensure that zinc is delivered to organelles , even under conditions of zinc deficiency . Although many zinc transporters belonging to the Cation Diffusion Facilitator ( CDF ) families have well characterized roles in transporting zinc into the lumens of intracellular compartments , relatively little is known about the mechanisms that maintain organelle zinc homeostasis . The fission yeast Schizosaccharomyces pombe is a useful model system to study organelle zinc homeostasis as it expresses three CDF family members that transport zinc out of the cytosol into intracellular compartments: Zhf1 , Cis4 , and Zrg17 . Zhf1 transports zinc into the endoplasmic reticulum , and Cis4 and Zrg17 form a heterodimeric complex that transports zinc into the cis-Golgi . Here we have used the high and low affinity ZapCY zinc-responsive FRET sensors to examine cytosolic zinc levels in yeast mutants that lack each of these CDF proteins . We find that deletion of cis4 or zrg17 leads to higher levels of zinc accumulating in the cytosol under conditions of zinc deficiency , whereas deletion of zhf1 results in zinc accumulating in the cytosol when zinc is not limiting . We also show that the expression of cis4 , zrg17 , and zhf1 is independent of cellular zinc status . Taken together our results suggest that the Cis4/Zrg17 complex is necessary for zinc transport out of the cytosol under conditions of zinc-deficiency , while Zhf1 plays the dominant role in removing zinc from the cytosol when labile zinc is present . We propose that the properties and/or activities of individual CDF family members are fine-tuned to enable cells to control the flux of zinc out of the cytosol over a broad range of environmental zinc stress .
Zinc is an essential trace metal that is required for the structure and activity of a large number of proteins . In eukaryotes these proteins include transcription factors containing structural domains stabilized by zinc ions , such as the C2H2-type and C4-type zinc fingers [1] . Zinc is also a cofactor for many enzymes that are located in the cytosol ( e . g . alcohol dehydrogenase 1 ) , and in subcellular compartments such as the nucleus ( e . g . RNA polymerases ) , mitochondria ( e . g . cytochrome c oxidase ) , and endoplasmic reticulum ( e . g . calreticulin ) [2–4] . Due to the essential nature of some of these proteins , all organisms are challenged with obtaining sufficient levels of zinc for incorporation into newly synthesized proteins . A further complicating factor is that excessive levels of zinc are toxic to cells . As a consequence , zinc acquisition , compartmentalization , storage , and efflux need to be tightly regulated to maintain zinc at a level that is sufficient , but not toxic to cell metabolism . In many organisms zinc-responsive transcription factors maintain zinc homeostasis by controlling the expression of genes that are required for the transport of zinc into and out of the cytosol . In eukaryotes these zinc transport proteins commonly belong to either the Zrt- Irt- like protein family ( ZIP ) or CDF family . Members of the ZIP family typically facilitate zinc uptake or the release of zinc from intracellular stores , whereas the CDF family members usually transport zinc into the lumens of intracellular compartments or out of a cell [5] . As zinc transport by a ZIP family member typically results in an increase in cytosol zinc levels , the expression of genes encoding ZIP family members is often up-regulated when zinc is limiting [6] . As an example , in Saccharomyces cerevisiae the transcriptional activator Zap1 controls the expression of genes encoding ZIP family members required for zinc uptake ( Zrt1 and Zrt2 ) and release of zinc from the vacuolar stores ( Zrt3 ) [7] . As Zap1 is active in zinc-limited cells and is inactive when zinc is in excess , the expression of ZRT1-3 increases when cells need zinc . Importantly , as zinc transport into the cytosol by the ZIP proteins inactivates Zap1 , a negative feedback loop is created that prevents zinc from reaching toxic levels . Negative feedback circuits also control the expression of CDF family members . In humans , the metal-responsive transcription factor 1 ( MTF-1 ) regulates the expression of ZnT1 , an essential CDF family member that is required for zinc efflux from cells [8] . MTF-1 is activated by excess zinc in the cytosol , which in turn transcriptionally induces ZnT1 expression when zinc is high . Similarly , when dietary zinc levels are high in the nematode Caenorhabditis elegans , the high zinc-responsive factor 1 ( HIZR-1 ) induces the expression of CDF family members required for the excretion of zinc from intestinal cells ( ttm-1b ) and storage of zinc in intestinal gut granules ( cdf-2 ) [9] . As the end result of these transcriptional changes is a reduction in cytosolic zinc levels , thereby inactivating MTF-1 and HIZR-1 , a negative feedback loop is created that prevents the cytosol from being depleted of zinc . Although a number of genes encoding transporters required for zinc uptake , storage , and efflux are subject to negative feedback control , the expression of some CDF family members increases in zinc-limited cells . For example , Zrg17 and Msc2 are two CDF family members from S . cerevisiae that form a heterodimeric complex that transports zinc into the endoplasmic reticulum [10] . Although this complex transports zinc out of the cytosol , ZRG17 is a Zap1-target gene that is expressed at higher levels in zinc-deficient cells [11] . While this regulation at first seems counterintuitive , as it would further deplete zinc from the cytosol , the induction of ZRG17 by Zap1 is critical for preventing the unfolding of proteins in the endoplasmic reticulum under this condition [11] . As zinc transport by the Zrg17/Msc2 complex would also further increase Zap1 activity , the zinc-dependent regulation of ZRG17 presumably results in a positive feedback circuit to supply zinc to compartmentalized proteins when the cytosol is limited for zinc . The regulation of ZRG17 by Zap1 illustrates a mechanism of how zinc can be supplied to an intracellular compartment in a zinc-limited environment . As few other studies have examined the regulatory circuits that maintain zinc levels in organelles during periods of zinc starvation , the goal of this work was to determine if related mechanisms were present in the distantly related yeast S . pombe . We chose to use S . pombe because multiple aspects of zinc homeostasis differ between fission and budding yeast . These differences include the transcription factor used to control zinc homeostasis ( Loz1 vs . Zap1 ) , the primary site for the storage of excess zinc ( endoplasmic reticulum vs . vacuole ) , and the presence of metallothioneins that preferentially bind divalent metal ions such as zinc ( Zym1 from S . pombe ) or monovalent ions such as copper ( Cup1 from S . cerevisiae ) [12–16] . Another difference between fission and budding yeasts is the subcellular localization of zinc transporters within the secretory pathway . In S . cerevisiae two CDF family members , Zrc1 and Cot1 , transport zinc into the vacuole [17] . In S . pombe , the homolog of Zrc1 , named Zhf1 , transports zinc into the endoplasmic reticulum , and the homologs of Msc2 and Zrg17 ( named Cis4 and Zrg17 respectively ) form a complex that localizes to the cis-Golgi [18 , 19] . The biological significance of these differences in subcellular localization of the CDF family members between budding and fission yeasts is currently unclear . To gain a better understanding of the mechanisms that control the supply of zinc to organelles , we used multiple genetic approaches to determine the extent to which three CDF family members from S . pombe ( Zhf1 , Zrg17 , and Cis4 ) facilitate zinc transport out of the cytosol under conditions of zinc deficiency and zinc excess . We found that deletion of zhf1 results in a strong growth defect when zinc is in excess and that deletion of zrg17 or cis4 leads to a mild growth defect in the presence of the zinc chelator EDTA . These latter results suggest that the Cis4/Zrg17 complex may play an important role under zinc deficiency conditions . To further investigate whether transport via Cis4 and Zrg17 is affected by cellular zinc status we developed methods to monitor changes in cytosolic zinc availability in fission yeast . These analyses revealed that that cis4Δ and zrg17Δ cells accumulate higher levels of zinc in the cytosol under conditions of zinc deficiency , while zhf1Δ cells accumulate higher levels of zinc in the cytosol when zinc is not limiting . We also show that the transcription of zhf1 , cis4 , and zrg17 genes is not dependent upon zinc . These results reveal that different CDF family members have complementary roles in transporting zinc out of the cytosol . They also suggest that either the activities or the properties of different CDF family members are fine-tuned to transport zinc out of the cytosol under different environmental zinc stresses .
Three members of the CDF family transport zinc into the secretory pathway in fission yeast: Zhf1 , Cis4 , and Zrg17 [13 , 15 , 18 , 19] . Although previous studies have shown that Zhf1 is required for growth in the presence of high zinc , relatively little was known about the roles of Cis4 and Zrg17 in zinc homeostasis . To determine if Cis4 and Zrg17 were necessary for growth under low or high zinc conditions , serial dilutions of cis4Δ and zrg17Δ cells were plated onto zinc-limiting ( EMM + 100 μM EDTA ) or zinc-replete medium ( EMM + 0–200 μM zinc ) ( Fig 1 ) . Cells lacking the Zrt1 or Zhf1 , which are required for survival during zinc deficiency or zinc toxicity respectively [18] , were also plated as controls . In the presence of 100 μM EDTA , cis4Δ cells exhibited a slight growth defect relative to the wild-type . zrg17Δ cells had a modest growth defect under all conditions , but grew more slowly in the presence of EDTA relative to cis4Δ . As Cis4 and Zrg17 form a heteromeric complex , these results are consistent with Cis4 and Zrg17 playing an important role in supplying zinc to the secretory pathway when zinc is limiting . The slower growth of zrg17Δ relative to cis4Δ also suggests that Zrg17 may have additional functions that are independent of Cis4 and zinc . To determine if Cis4 and Zrg17 were required for zinc transport out of the cytosol of zinc-limited cells , we developed constructs to express the genetically encoded ZapCY1 and ZapCY2 zinc-responsive FRET sensors in the cytosol of fission yeast . The ZapCY1/2 sensors have been widely used to monitor dynamic changes in intracellular zinc levels [20] . Both sensors contain the regulatory zinc fingers 1 and 2 from the transcription factor Zap1 , flanked by citrine YFP , hereafter referred to as YFP , and eCFP ( Fig 2A ) . In zinc-limited environments , the Zap1 zinc finger domain 1 and 2 are largely unstructured . However , in the presence of zinc , the zinc finger domains fold together to form a single structural unit [21] . As this closed conformation brings together YFP and eCFP increasing FRET , the FRET signal in cells expressing ZapCY1 and ZapCY2 is directly coupled to intracellular zinc availability . Previous studies have shown that ZapCY1 binds zinc in vitro with an apparent dissociation constant of ~ 2 . 5 pM , while ZapCY2 contains substitutions within the zinc finger domains , which result in it binding zinc with an ~ 300 fold lower affinity [20] . To determine if the ZapCY1 and ZapCY2 FRET reporters were stably produced in S . pombe , strains expressing ZapCY1 and ZapCY2 from the constitutive pgk1 promoter were grown overnight in ZL-EMM , and the levels of each sensor examined by immunoblotting . Both reporters accumulated to similar levels in zinc-limited and zinc-replete cells indicating that their stability was not affected by zinc ( Fig 2B ) . We also assessed the subcellular localization of each reporter in response to cellular zinc status using fluorescent microscopy . As shown in Fig 2C , there was strong fluorescence in cells expressing ZapCY1 or ZapCY2 , which was absent from cells transformed with the empty vector . The ZapCY1 and ZapCY2 proteins were both localized to the cytosol and nucleus , and were excluded from the vacuole . For unknown reasons , higher levels of the ZapCY2 reporter accumulated in the nucleus of zinc-replete cells . A potential concern with using ZapCY1 and ZapCY2 to assess alterations in the labile pools of zinc in yeast is that both sensors bind zinc ions , which in turn might reduce the levels of zinc that are normally available for cellular metabolism . In previous studies we have shown that the expression of the Loz1 target genes zrt1 and zym1 is dependent upon intracellular zinc levels [22] . Specifically , zrt1 is expressed in zinc-limited cells and zym1 is expressed in zinc-replete cells . We therefore predicted that zrt1 and zym1 expression would be altered if the ZapCY1/2 FRET sensors interfere with zinc homeostasis . As shown in Fig 2D , the introduction of the ZapCY1/2 FRET sensors had no major effect on zym1 and zrt1 mRNA levels . In addition , when the FRET reporters were co-expressed with a zrt1-lacZ reporter , there were no differences in β-galactosidase activity when compared to cells expressing the vector ( Fig 2E ) . Taken together the above results show that the ZapCY1/2 FRET sensors accumulate within the cytosol and nucleus of cells without any substantial effect on zinc homeostasis . To determine if the ZapCY1 and ZapCY2 FRET sensors are able to detect dynamic changes in the labile pool of zinc in fission yeast , we measured the activity of each reporter in vivo following a ‘zinc shock’ . In a zinc shock experiment cells are initially depleted of zinc by growing overnight in ZL-EMM , which leads to increased expression of zrt1 and high levels of Zrt1 on the plasma membrane . As zinc-limited cells are primed and ready to uptake zinc , zinc rapidly enters cells in a dose-dependent manner when it is added to the growth medium ( Fig 3A ) . To examine the response of the high affinity FRET sensor to zinc shock , wild-type cells expressing ZapCY1 were grown overnight in ZL-EMM before being transferred to temperature-controlled microplate wells . Cells were excited at 434 nm and a FRET ratio calculated by dividing the intensity of the emission at 535 nm by the emission at 475 nm . The growth overnight in ZL-EMM resulted in a FRET ratio of 2 . 29 +/- 0 . 20 ( Fig 3B and 3C , t = -5 min ) . This ratio remained constant until the addition of zinc , which led to a rapid increase in FRET in a dose-dependent manner ( Fig 3B , 0 . 01–1 μM zinc ) . These changes in FRET occurred without affecting the stability of ZapCY1 ( Fig 3D ) , consistent with the ZapCY1 sensor binding zinc and forming the closed conformation which brings YFP and CFP closer together . Zinc shocks with higher levels of zinc ( 10–1000 μM Zn2+ ) also led to a rapid increase in the FRET ratio ( Fig 3B and 3C ) . However , the magnitude of the response was similar to that seen following a zinc shock with 1 μM zinc . We conclude from these results that a zinc shock with 1 μM Zn2+ results in sufficient levels of zinc accumulating within the cytosol and nucleus of cells to saturate the high affinity ZapCY1 sensor . To assess the effects of a zinc shock on the low affinity reporter , similar experiments were performed with wild-type cells expressing ZapCY2 . In these cells , growth overnight in ZL-EMM resulted in an initial FRET ratio of 1 . 57 +/- 0 . 05 ( Fig 3E and 3F , t = 0 min ) . As ZapCY2 binds zinc with a lower affinity than ZapCY1 , we predicted that higher levels of zinc would be needed to saturate ZapCY2 . Consistent with this hypothesis , no significant increase in FRET was observed following a zinc shock with 0 . 1 μM Zn2+ and a modest response was seen with 1 μM Zn2+ . A rapid increase in the FRET ratio to 1 . 92 +/- 0 . 03 was detected following a zinc shock with 10 μM Zn2+ ( Fig 3E , t = 2 min ) . However , this FRET signal subsequently decreased until it reached a more constant ratio of ~ 1 . 75 after 15 minutes ( Fig 3E , t = 15–90 min ) . As the zinc shock did not affect the stability of ZapCY2 ( Fig 3G ) , these results are consistent with ZapCY2 rapidly binding zinc , and then zinc being lost to higher affinity zinc binding sites in the surrounding environment . Zinc shocks with higher levels of zinc ( Fig 3E and 3F , 100 μM zinc ) were sufficient to saturate the FRET sensor , but in contrast to ZapCY1 , the FRET ratio slowly decreased with time . Thus , the ZapCY1 and ZapCY2 sensors are both able to detect changes in cytosolic zinc levels . However , higher levels of zinc are necessary to saturate ZapCY2 and the zinc bound to ZapCY2 is more readily lost to the surrounding environment . To gain further evidence that the sensors were measuring changes in cytosolic zinc levels , ZapCY1 and ZapCY2 were introduced into cells lacking zrt1 . In the absence of Zrt1 , higher levels of zinc are needed during a zinc shock experiment to see an increase in total cellular zinc because cells rely on low affinity systems for zinc uptake ( compare Fig 3A to Fig 4A ) . We therefore predicted that higher levels of zinc would be necessary to saturate ZapCY1 and ZapCY2 in zrt1Δ . Consistent with this prediction , higher levels of zinc were required to obtain a maximal FRET ratio change in zrt1Δ cells compared to the wild-type ( Fig 4B–4E ) . As an example , a zinc shock with 1 μM zinc was sufficient to saturate ZapCY1 in the wild-type , but did not affect the activity of the ZapCY1 reporter in zrt1Δ ( Fig 4F ) . The differences in FRET response were a result of loss of zrt1 , as both reporters were expressed at similar levels to the wild-type , and a zinc shock had no effect on the stability of either reporter ( Fig 4G–4I ) . Together , these results indicate that the FRET signal in cells is dependent upon the expression of zrt1 and also is consistent with the activity of both reporters being directly regulated by cytosolic zinc levels . In our previous studies we found that genetic mutations that disrupt Loz1 function result in the constitutive de-repression of zrt1 transcription , leading to increased expression levels . Therefore , to assess the effects of overexpression of zrt1 on cytosolic zinc levels , ZapCY1 and ZapCY2 were introduced in loz1Δ cells and the FRET response was measured during a zinc shock experiment . Following the growth of loz1Δ ZapCY1 cells overnight in ZL-EMM , an initial FRET ratio of 3 . 3 +/- 0 . 5 was detected ( Fig 5A and 5B ) , which is higher than the initial FRET ratio in cells expressing Loz1 . Further , only a minor increase in FRET was seen following a zinc shock with 0 . 1–1000 μM zinc . As loz1Δ cells constitutively express zrt1 , one explanation for the high initial FRET ratio in this mutant is that they have higher levels of zinc uptake leading to the saturation of ZapCY1 . It was also possible that the ZapCY1 reporter was unable to respond to zinc in this genetic background . To distinguish between these possibilities , we used sodium pyrithione ( NaPT ) to artificially lower cytosolic zinc levels . Pyrithione is a membrane permeable ionophore that readily forms complex with zinc [23] . When 50 μM NaPT was added to wild-type ZapCY1 cells grown overnight in ZL-EMM , a small decrease in the FRET ratio consistent with this molecule binding or releasing accessible zinc within the cytosol ( Fig 5C ) . Importantly , a rapid increase in FRET was seen when zinc was added to the NaPT treated cells . When a similar experiment was performed with loz1Δ cells , a large decrease in the FRET ratio was seen upon the addition of NaPT , which could be reversed by the addition of zinc ( Fig 5D ) . These results indicate that the ZapCY1 reporter is functional in loz1Δ cells , and suggest that in the absence of strong chelators and ionophores it is saturated with zinc under all conditions . To test whether the saturation of the ZapCY1 reporter in loz1Δ cells was a result of high zrt1 expression , we examined the activity of the ZapCY1 reporter in double mutants lacking loz1 and zrt1 . In these cells a low FRET ratio of 1 . 8 +/- 0 . 2 was detected following growth overnight in ZL-EMM ( Fig 5E ) . These results suggest that the high expression of zrt1 significantly contributes to the saturation of ZapCY1 in loz1Δ cells . We also noted that higher levels of total zinc accumulated in loz1Δ zrt1Δ when compared to zrt1Δ following a zinc shock ( Fig 5F ) . These results suggest that Loz1 controls the expression of a second lower affinity zinc uptake system and/or regulates the expression of other genes that affect cytosolic zinc availability . Consistent with this hypothesis , a zinc shock with 1 μM zinc did not result in an increased FRET ratio in zrt1Δ , but did lead to a slow increase in FRET in loz1Δ zrt1Δ ( compare Figs 4B and 5E ) . Similarly , the ZapCY1 reporter was close to saturation after a 30 min zinc shock with 10 μM Zn in loz1Δ zrt1Δ cells , and yet in zrt1Δ , a zinc shock with 10 μM Zn zinc only led to a slow gradual increase in FRET over 60 min . As loz1Δ cells accumulate higher levels of zinc within the cytosol , we also assessed the effects of this allele on the response of the low affinity ZapCY2 reporter . In contrast to the response of ZapCY1 , the basal FRET ratio in zinc-limited loz1Δ ZapCY2 cells was similar to the wild-type ( compare Figs 3F to 5H ) . The responses of the ZapCY2 reporter to zinc also resembled those of the wild-type ( Fig 5G and 5H ) . Thus , under conditions of zinc deficiency , loz1Δ cells accumulate higher levels of zinc in the cytosol/nucleus relative to the wild-type . However , when zinc is not limiting in these cells it is effectively buffered and/or transported out of the cytosol . The above results show that the ZapCY1 and ZapCY2 sensors can be used in S . pombe to measure dynamic changes in the levels of labile zinc in the cytosol and nucleus . As deletion of cis4 or zrg17 resulted in a growth defect on low zinc medium , we used these sensors to test whether Cis4 and Zrg17 were necessary for zinc transport out of the cell under this condition . When a zinc shock experiment was performed with cis4Δ ZapCY1 cells , the starting FRET ratio was higher than that observed in the wild-type . Additionally , only a small increase in the FRET ratio was seen with 0 . 1 μM zinc ( from 2 . 8 +/- 0 . 23 to 4 . 0 +/-0 . 2 ) and also when cells were shocked with higher levels of zinc ( 1–1000 μM ) ( Fig 6A–6C ) . In contrast , the addition of NaPT resulted in a large decrease in the FRET ratio , which could be reversed by the addition of zinc ( Fig 6D ) . For the most part , similar trends were seen with zrg17Δ ZapCY1 and cis4Δ zrg17Δ ZapCY1 . However , for zrg17Δ cells the maximum FRET ratio was slightly higher than that observed with cis4Δ cells; and a zinc shock with 0 . 1 μM zinc was not sufficient to totally saturate ZapCY1 ( Fig 6E–6G and S1 Fig ) . As ZapCY1 was largely saturated in cis4Δ and zrg17Δ cells following growth overnight in ZL-EMM , these results are consistent with Cis4 and Zrg17 being required for the transport of zinc out of the cytosol under conditions of zinc deficiency . To determine if the higher levels of zinc that accumulated in cis4Δ and zrg17Δ also affected zinc binding to low affinity sites , similar experiments were performed with cells expressing ZapCY2 . A zinc shock with 10 or 1000 μM zinc resulted in smaller increase in FRET compared to the wild-type ( Fig 6H and 6I and S1 Fig ) . The signal also decreased over time . While it is possible that Cis4 and Zrg17 transport zinc out of the cytosol following a zinc shock , the decrease in FRET response in these mutants suggests that other mechanisms that are independent of Cis4 and Zrg17 protect the cytosol from accumulating high levels of labile zinc . As Zhf1 is predicted to play the primary role in protecting cells from zinc toxicity , we next examined the activity of ZapCY1 and ZapCY2 in strains lacking zhf1 . In zhf1Δ ZapCY1 cells grown overnight in ZL-EMM , the basal FRET ratio and response of this sensor to zinc shocks with 0 . 1 and 1 μM zinc were similar to those seen in wild-type cells ( Fig 7A and 7B ) . In contrast , a zinc shock with 10 μM zinc led to a rapid increase in the FRET ratio , followed by an immediate decrease . After these rapid changes the FRET ratio slowly increased for the remainder of the experiment . A similar response was seen with zinc shocks with higher levels of zinc , with the exception that it took longer ( ~30 min ) to see the increase in FRET ratio . To test whether this atypical response was a result of the instability of the ZapCY1 reporter in zhf1Δ cells , immunoblot analysis was used to examine the stability of ZapCY1 during a zinc shock with 100 μM Zn2+ . As shown in Fig 7C and 7D , elevated levels of a lower molecular weight band accumulated in this strain ( see asterisk ) , suggesting that ZapCY1 was more prone to degradation in this strain relative to others . Despite this higher level of degradation , there were no changes in the levels of the full-length reporter and experiments using the zinc chelator NaPT resulted in FRET profiles that resembled those observed in the wild-type ( Fig 7E ) . Although we do yet understand the zinc-dependent changes in the FRET response in zhf1Δ cells , the observation that they are not observed in the presence of NaPT suggests that they result from zinc accumulating in the cytosol of this strain . To gain further evidence that Zhf1 protects the cytosol from excess zinc , similar experiments were performed with zhf1Δ ZapCY2 . In these cells , zinc had no effect on the stability of the full length reporter and a zinc shock with 1 μM zinc was sufficient to saturate ZapCY2 ( Fig 7F–7I ) . The FRET ratio after a zinc shock with 1 μM zinc also remained high for the duration of the experiment . These results reveal that higher levels of zinc accumulate in the cytosol of zhf1Δ following a zinc shock and indicate that Zhf1 has a central role in removing labile zinc from the cytosol . The above results suggest that the Cis4/Zrg17 complex plays a primary role in the transport of zinc out of a zinc-limited cytosol , while Zhf1 has the dominant role in transporting labile zinc from the cytosol . In S . cerevisiae the expression ZRG17 increases under conditions of zinc deficiency and this increase is critical for normal endoplasmic reticulum function under this condition [11] . To determine if the expression of cis4 and zrg17 was dependent on zinc in fission yeast we used S1 nuclease analysis to examine mRNA levels in wild-type and loz1Δ cells grown under zinc-limiting and zinc-replete conditions . As shown in Fig 8A , cis4 and zrg17 transcripts accumulated under all conditions indicating that their expression is not affected by zinc or Loz1 . The levels of zhf1 mRNAs were also not regulated by zinc and Loz1 , consistent with previous studies that have demonstrated experimentally that the expression of zhf1 is not affected by cellular zinc status [13 , 24] . As deletion of cis4 or zrg17 resulted in increased saturation of the high affinity ZapCY1 reporter , we also used S1 nuclease analysis to test whether these mutants accumulated sufficient levels of zinc in the cytosol to trigger increased Loz1-mediated gene repression . The rationale for these experiments is that Loz1 represses target gene expression when zinc levels are high . As a consequence , if higher levels of zinc accumulate in the cytosol of cis4Δ and zrg17Δ , this could result in increased repression of Loz1 target genes . When cells were grown under zinc-limiting conditions , lower levels of zrt1 transcripts accumulated in cis4Δ and zrg17Δ cells relative to the wild-type control ( Fig 8B ) . These results are consistent with the Cis4/Zrg17 complex transporting zinc out of cytosol of zinc-limited cells .
Yeast are useful model systems to study zinc homeostasis , as they are able to survive in low zinc environments and rapidly adapt to conditions of zinc excess . In this work we took advantage of these properties by examining the activity of the zinc-responsive ZapCY FRET reporters following overnight growth in a zinc-limited medium and during a zinc shock . We show that ZapCY1 and ZapCY2 are both able to measure dynamic changes in cytosolic zinc levels in fission yeast and that higher levels of zinc are necessary to saturate ZapCY2 . We also show that there is a transient increase in FRET following a zinc shock in wild-type cells expressing ZapCY2 , suggesting that zinc bound to this sensor exchanges with other ligands within the cytosol that can bind or buffer zinc . As ZapCY1 is able to detect zinc ions binding to high affinity sites within proteins , and ZapCY2 detects binding to low affinity sites , these sensors create useful tools for monitoring the factors that influence cytosolic zinc ion availability and zinc ion binding within the cytosol . To identify additional factors that affect the levels and availability of zinc within the cytosol , we used ZapCY1/2 to test whether Cis4 , Zrg17 , and Zhf1 have redundant or complementary roles in zinc transport out of the cytosol . We found that deletion of cis4 or zrg17 resulted in higher levels of saturation of ZapCY1 under conditions of zinc deficiency , whereas deletion of zhf1 had little effect on the saturation of ZapCY1 under this condition . In contrast , significantly lower levels of zinc were necessary to saturate ZapCY2 in zhf1Δ cells compared to cis4Δ or zrg17Δ following a zinc shock . We propose that the Cis4/Zrg17 heterodimer preferentially transports zinc out of the cytosol into the secretory pathway under zinc-limiting conditions , whereas Zhf1 has the dominant role in transporting labile zinc out of the cytosol when zinc is not limiting ( Fig 9 ) . In this model , the transport activity of the Cis4/Zrg17 heterodimer ensures that zinc is supplied to the secretory pathway under zinc-limiting conditions . As a reduction in cytosolic zinc levels also triggers the inactivation of Loz1 and increased expression of the zrt1 zinc uptake system , cells are able to balance the levels of zinc uptake with zinc flux out of the cytosol . Cells face a different challenge when zinc is in excess , as too much zinc is toxic to cell metabolism . Under these conditions , the dominant role of Zhf1 results in excess zinc being directed to intracellular stores , protecting the cytosol and other organelles from the toxic effects of too much zinc . A key question that our studies raise is what is the mechanism by which individual CDF family members preferentially transport zinc under zinc-limiting or zinc-replete conditions ? Studies with S . cerevisiae have revealed much of what we know about the ability of CDF proteins to transport zinc under varying conditions of zinc stress . In this yeast , the Msc2/Zrg17 complex facilitates the transport of zinc into the endoplasmic reticulum , whereas Zrc1 and Cot transport zinc into the vacuole [10 , 14] . One factor that affects zinc transport via the Msc2/Zrg17 complex is ZRG17 expression . ZRG17 is a Zap1 target gene that is expressed at higher levels in zinc-deficient cells [7 , 11] . Importantly , in the absence of the Zap1-dependent induction of ZRG17 , zinc-deficient cells experience greater levels of ER stress [11] . These results suggest that the levels of Zrg17 protein limit zinc transport by the Msc2/Zrg17 complex and that the increase in ZRG17 expression is critical for normal ER function under conditions of zinc-deficiency . Recent studies have also revealed that higher levels of MSC2 mRNAs accumulate in zinc-deficient cells [25] . The levels of Msc2 may also be an important factor that limits zinc transport by the Msc2/Zrg17 complex . While changes in gene expression are an integral part of zinc transport into the ER under zinc-deficient conditions , it is also important to note that ZRC1 is a Zap1 target gene , and yet overexpression of ZRC1 does not affect cytosolic zinc availability in zinc-deficient cells [26] . These results suggest that Zrc1 does not play a significant role in transporting zinc out of the cytosol under this condition . They also reveal that increased expression of a zinc transport gene does not necessarily result in more zinc being transported out of the cytosol , and that other factors likely affect zinc transporter function . As the expression of cis4 , zrg17 , and zhf1 is not dependent upon zinc , what other factors could affect their ability to transport zinc out of the cytosol ? One possibility is that there are intrinsic differences in the ability of Zhf1 and Cis4/Zrg17 to transport zinc . For example , if the affinities of the zinc binding sites on the cytosolic face of Zhf1 were weaker than those of the Cis4/Zrg17 heterodimer , this latter complex may only be able to acquire zinc when the cytosolic zinc pools are less saturated . An alternative possibility is that the labile pool of zinc that is accessible to Zhf1 under zinc-limiting conditions is dependent on the presence of an active Cis4/Zrg17 heterodimer . Potential mechanisms that could lead to a pool of labile zinc that is inaccessible to Zhf1 include an increase in the total number of buffering components in the cytosol ( i . e . the total amount of zinc remains the same and the buffering capacity increases ) and/or tighter buffering of cytosolic zinc ( preventing zinc from being available to the weaker binding sites of Zhf1 ) . While future experiments are necessary to determine the precise nature of the buffering components of the cytosol , and the affinity of different CDF transporters for zinc , it is noteworthy that Cis4/Zrg17 and Msc2/Zrg17 complexes both appear to have a primary role in transporting zinc out of the cytosol into the secretory pathway under zinc-limiting conditions . In addition , Zhf1 and Zrc1 both facilitate the transport of zinc from the cytosol when zinc availability is not limited . These similar functions suggest that at least some features of these transporters are conserved in fission and budding yeast . In addition to the potential differences above , multiple other factors could affect the function of the Cis4/Zrg17 heterodimer and Zhf1 . For example , in yeast and humans , zinc transporters from the ZIP family are targeted for degradation in response to high zinc [27 , 28] . Although it is currently not known if the stability or activity of each of the S . pombe CDF proteins are regulated at a post-translational level in response to cellular zinc levels , proteomic studies that compared the copy numbers of proteins in fission yeast during vegetative growth in minimal medium revealed the presence of ~12 , 000–14 , 000 Zhf1 molecules/cell , ~3000–6000 Zrg17 molecules/cell , and ~ 1300–5500 Cis4 molecules/cell [29 , 30] . The higher levels of Zhf1 relative to Zrg17 and Cis4 may therefore be one factor that contributes to Zhf1 having the principal role in transporting zinc out of the cytosol in a zinc-replete environment . In addition to factors that directly affect the function of zinc transport proteins , it is unclear if the subcellular localization of zinc transporters or their local environment affects their function . Moreover , relatively little is known about the molecules that buffer zinc within organelles and the cytosol , and whether the buffering capacity of an organelle for zinc , and/or the number and affinity of zinc-binding proteins within a compartment influences zinc transport . Thus , future studies with CDF proteins from S . pombe and other organisms are warranted to identify additional factors that alter zinc transport function . We also examined the effects of the loz1Δ allele on cytosol zinc availability . We had previously found that loz1Δ cells constitutively express zrt1 and hyperaccumulate zinc when excess zinc is present in the growth medium [22] . Although loz1Δ cells hyperaccumulate zinc , paradoxically they have a more severe growth defect under zinc-deficient conditions compared to zinc replete ( Fig 1 ) . Here we find that the loz1Δ allele results in the saturation of the high affinity ZapCY1 sensor following growth overnight in ZL-EMM , indicating that this mutant accumulates higher levels of zinc in the cytosol relative to the wild-type . We also find that the response of the ZapCY2 reporter was similar to that of the wild-type , revealing that labile zinc entering loz1Δ cells is rapidly removed into stores and/or is effectively buffered . These latter results reveal that other mechanisms that are independent of Loz1 help S . pombe to maintain zinc homeostasis . They also provide an explanation for the viability of the loz1 mutant in high zinc . Another observation that we made was that ZapCY1 was not saturated in double mutants lacking zrt1 and loz1 , and that this double mutant accumulated higher levels of zinc in the cytosol relative to zrt1 . These results indicate that the constitutive derepression of zrt1 is the primary reason for the saturation of ZapCY1 in loz1Δ cells . They also suggest that Loz1 regulates other genes that affect cytosolic zinc availability . Known Loz1 target genes include zrt1 , as well as adh4 ( alcohol dehydrogenase 4 ) , gcd1 ( glucose dehydrogenase 1 ) , and SPBC1348 . 06c , which encodes a small fungal protein of unknown function [22 , 31] . Loz1 also represses the expression of non-protein coding RNAs that interfere with the expression of the adh1 ( alcohol dehydrogenase 1 ) and zym1 ( zinc metallothionein 1 ) genes [22 , 32] . The expression of adh1 and zym1 is therefore inverse to that of other Loz1 targets , in that they are repressed under conditions of zinc deficiency . Although no known Loz1 target gene other than zrt1 has a role in transporting zinc , altered expression of some of its targets could affect intracellular zinc availability . For example , as the loz1Δ allele results in the constitutive repression of adh1 , which encodes the abundant zinc binding protein Adh1 , the lower levels of this protein could result in higher levels of zinc being available for other proteins . Thus , future studies to identify new Loz1 target genes and to examine the roles of existing target genes in controlling intracellular zinc availability may provide additional insight into factors affecting zinc homeostasis . The ability of some CDF proteins to transport zinc is a manner that is dependent upon the levels of ‘labile’ or ‘readily available’ zinc in the cytosol could be of particular importance in organisms that express large numbers of CDF family members . For example , humans express 10 CDF family members ( named ZnT1-10 ) , while Arabidopsis thaliana and C . elegans each express 14 family members [33] . Potential reasons for why these organisms have so many CDF proteins include that they have unique subcellular localizations , different metal ion specificities , and/or that they have more specialized roles in supplying zinc to smaller subsets of proteins [5 , 34–38] . Some genes encoding CDF proteins also show tissue- or developmental- specific expression patterns , while others are regulated by zinc and/or by hormonal or stress-responsive signaling pathways [5 , 39 , 40] . Although it is currently unclear in other organisms if the activity of specific CDF proteins is dependent upon cellular zinc status , the conserved role of this family in supplying zinc to organelles and storage compartments raises the possibility that the activity of other CDF proteins may also be fined tuned according to cytosolic zinc ion availability .
To generate the strains used for the FRET analysis , the plasmids pZapCY1 and pZapCY2 were linearized with NruI and were integrated into the leu1-32 locus of the wild-type strain JW81 ( h- ade6-M210 leu1-32 ura4-D18 ) [41] . All other strains expressing ZapCY1 or ZapCY2 were generated from genetic crosses with the wild-type ZapCY1 ( ABY795 ) or WT ZapCY2 ( ABY797 ) with the respective mutant . The strains co-expressing the ZapCY1 and ZapCY2 with the zrt1-lacZ reporter were generated from genetic crosses with JW81 containing the integrated reporter TN-zrt1-lacZ [24] . To generate zinc-deficient and zinc-replete cells , yeast strains were initially grown to exponential phase in the nutrient rich YES medium . Cells were then spun down and washed twice in ZL-EMM , a derivative of Edinburgh minimal medium that lacks zinc ( ZL-EMM ) . Washed cells were then diluted to 0 . 02 OD600 with fresh ZL-EMM and were grown for 16 hrs at 31°C in ZL-EMM or in this medium supplemented with 1 , 10 , or 100 μM ZnCl2 . For all zinc shock experiments , cells were grown as described above in ZL-EMM without zinc . The indicated amount of zinc ( 0 . 01–1000 μM ZnCl2 ) was then added to induce the zinc shock . The plasmids pZapCY1 and pZapCY2 were generated by PCR amplifying the coding regions for ZapCY1 and ZapCY2 from the vectors pcDNA3 . 1-ZapCY1 and pcDNA3 . 1-ZapCY2 respectively , with primers containing EcoRI and BamHI restriction sites . The ZapCY1/2 PCR products were then digested with EcoRI and BamHI and cloned into similar sites into the vector JK-pgk1-adh4T . The vector JK-pgk1-adh4T is a derivative of JK148 that contains 840 bp of the pgk1 promoter inclusive of its 5’UTR and 726 bp of the adh4 terminator . It was generated by initially PCR amplifying the pgk1 promoter with primers containing KpnI and EcoRI restriction sites . KpnI- and EcoRI- digested PCR products were then cloned into the vector JK148 to generate JK-pgk1 . The adh4 terminator was cloned using a similar approach with the exception that primers were designed to introduce the adh4 PCR product into the BamHI/SacI sites of JK-pgk1 . β-Galactosidase assays were performed as described previously [42] . Activity units were calculated as follows: ( ΔA420 x 1000 ) / ( min x ml of culture x culture absorbance at 600 nm ) . For AAS 10 ml of cells were grown in ZL-EMM as described above . After the OD600 was measured , the indicate amount of zinc was added at t = 0 min . Cells were then grown at 31°C with shaking and 1 . 5 ml aliquots removed at the indicated time point . To remove extracellular zinc , cells were washed twice with 0 . 5 M EDTA and twice with ddH2O . Cell pellets were then digested by boiling in 150 μl of metal free nitric acid for 45 min and the zinc content measured using a SpectrAA 220FS Atomic Absorption Spectrometer . The final zinc concentration/cell was calculated by comparing the readings to a standard curve generated using a zinc standard ( Sigma 18827 ) . All values are the average from three independent experiments and error bars represent standard deviations . For FRET experiments , cells were grown for 16 hrs in ZL-EMM as described above . ~2 . 5 x 106 cells were directly transferred to temperature controlled 96 well plates and the FRET emission intensities measured using spectrofluorometry using the following excitation and emission wavelengths: eCFP excitation 434 nm / emission 474 nm , and FRET excitation 434 nm / emission 535 nm . The FRET ratio was calculated by dividing the FRET emission intensity by the eCFP emission intensity . All average values show the mean FRET ratio from three independent experiments that were performed on independent days . Error bars show standard deviations . For immunoblotting , total protein extracts were prepared by a trichloroacetic acid precipitation . Proteins were separated by SDS/PAGE analysis using a 10% resolving gel before transfer to nitrocellulose membranes . Proteins were detected using anti-GFP ( Sigma G1544 ) or anti-Actin ( Abcam ab3280 ) , and secondary antibodies IR-Dye800CW conjugated anti-mouse IgG ( LICOR ) and IRDye680 conjugated anti-rabbit IgG ( LICOR ) . Signal intensities were measured using an Odyssey infrared imaging system . For RNA analysis , total RNA was purified using hot acidic phenol method . RNA blots and S1 nuclease analyses were performed as described previously [32 , 43] . Probes for the RNA blot analyses were generated using the MAXISCRIPT T7 kit ( Ambion ) according to manufacturers instructions , whereas probes for the S1 nuclease analyses were generated by 5’ end labeling the following oligonucleotides: zrg17 5’-GATCACTAATAGTTACAGAGACATTATTATTTATAGGGTTTTGAATCTGAATAGCAGTCGGGATG- 3’ , cis4 5’- CGAACGCAGAAGAATTAACATTCATTTTTGTCGTCAGGAACACCCAAAAGCTGTGGTTGAC-3’ , zhf1 5’-GTTGCCAGCCATATGTGTATTTTGGTTCGTGAGATGTTGAATGTGCTAGACGAGTAGCCCA-3’ , zrt1 5’- CCATATTCGTTGAATTCATTGGCATCACCTCCACAAGTCACAGTAGCAGAGCTATCATCGTC-3’ , and act1 5’-GTCCCATACCTACCATAATACCATGGTGACGGGGTCTACCGAC-3’ . Act1 probes were diluted with unlabeled probe where indicated . Fluorescent microscopy of live cells was performed with an Olympus FV 1000 Filter Confocal system , using filter sets for GFP . Data are presented as the mean ± standard deviation ( SD ) . Statistical analyses were performed using GraphPad Prism 5 software ( GraphPad Software , La Jolla , CA , USA ) . Where appropriate , data were analyzed by a Student unpaired t-test . A p value of <0 . 05 was considered statistically significant . | All organisms require homeostasis mechanisms to maintain sufficient levels of zinc for normal cell metabolism and to avoid toxicity . As zinc-binding proteins are located in the cytosol and within intracellular compartments , all cells have to balance intracellular zinc ion distribution so that there are sufficient , but non toxic levels of zinc in the cytosol as well as organelles . Although much is known about the mechanisms that control cytosolic zinc levels , relatively little is known about the mechanisms that maintain organelle zinc homeostasis . As proteins belonging to the CDF family transport zinc into organelles , here we used a fission yeast model system to determine if the expression or function of zinc transporters belonging to this family was regulated by zinc . We find that two CDF family members , Cis4 and Zrg17 , facilitate the transport of zinc out of the cytosol of zinc-deficient cells , whereas the CDF family member Zhf1 preferentially transports zinc out of the cytosol when zinc is not limiting . As the expression of the genes encoding these transport proteins is not regulated by zinc , the results suggest that different CDF family members have complementary roles in transporting zinc out of the cytosol that are independent of changes in transcription . These results provide new insights into the regulatory mechanisms that control cytosolic and organelle zinc homeostasis . | [
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"an... | 2018 | Zinc transporters belonging to the Cation Diffusion Facilitator (CDF) family have complementary roles in transporting zinc out of the cytosol |
Interactions among multiple infectious agents are increasingly recognized as a fundamental issue in the understanding of key questions in public health regarding pathogen emergence , maintenance , and evolution . The full description of host-multipathogen systems is , however , challenged by the multiplicity of factors affecting the interaction dynamics and the resulting competition that may occur at different scales , from the within-host scale to the spatial structure and mobility of the host population . Here we study the dynamics of two competing pathogens in a structured host population and assess the impact of the mobility pattern of hosts on the pathogen competition . We model the spatial structure of the host population in terms of a metapopulation network and focus on two strains imported locally in the system and having the same transmission potential but different infectious periods . We find different scenarios leading to competitive success of either one of the strain or to the codominance of both strains in the system . The dominance of the strain characterized by the shorter or longer infectious period depends exclusively on the structure of the population and on the the mobility of hosts across patches . The proposed modeling framework allows the integration of other relevant epidemiological , environmental and demographic factors , opening the path to further mathematical and computational studies of the dynamics of multipathogen systems .
While the dynamic of infectious diseases has been traditionally studied focusing on single pathogens one at a time , increasing attention is currently being devoted to the interactions among multiple infectious agents [1] . Interaction mechanisms can indeed alter the pathogen ecology and have important evolutionary , immunological and epidemiological implications [2]–[5] . A clear example of pathogen cocirculation is given by viruses that may have different genetic and antigenic variants , such as human influenza A virus with different subtypes and associated strains ( i . e . phenotypically different variants ) [6] and dengue virus with four serotypes circulating in affected tropical regions [7] . Among other examples we find many sexually transmitted diseases ( like human immunodeficiency virus ( HIV ) , human papilloma virus , herpes simplex virus ) , but also infections affecting animals , such as avian influenza [6] or the foot-and-mouth disease causing rapid acute infections in livestock [8] . The interaction among pathogens are mostly driven by immune-mediated [2] or ecological [3] mechanisms , generally resulting into competition among the infectious agents [4] , [5] , even though cooperation may be observed in some specific settings [9] . Among strain-polymorphic pathogens , for example , immune-mediated interaction occur when infection by a strain confers long-lasting protection against the particular strain , with partial cross-immunity against viral variants , depending on the level of similarity of their genetic and antigenic profiles . Cocirculating strains are therefore not independent [10] , as it happens in the case of influenza A virus , with strain-dependent prolonged immunity following infection [6] and epidemiological evidence for partial cross-immunity among strains [11] , [12] . Interaction in terms of ecological interference is due to the temporary or permanent removal of a host from the population of susceptible hosts , because of infection from another strain . This may occur during the illness period and associated recovery ( e . g . an individual staying at home or being admitted to the hospital ) or because of deadly outcomes , generating complex competition dynamics for the exploitation of the remaining hosts . The spatial and social structure of a host population , as well as the migration of hosts , is recognized to represent a crucial element affecting the geographical propagation of directly transmitted infectious diseases [13] . Infectious hosts moving from one location to another may seed the disease in previously unaffected locations , whereas susceptible hosts may contract the disease by entering in close contact with members of already infected subpopulations [14]–[18] . Recently available massive datasets on host spatial structure and mobility patterns [19]–[25] have enabled the development of a large quantity of modeling approaches that assess the relevance and impact of hosts' mobility features on epidemic spreading processes caused by a single pathogen [13] , [19] , [26]–[42] . Given its importance for dispersal mechanisms , the spatial structuring of the host population and the coupling among different subpopulations may also be important to multipathogen dispersal mechanisms , and to epidemiological and ecological interactions [43] . Space and host mobility may indeed act as an additional mechanism of ecological interference for host exploitation between different pathogens cocirculating in a population of susceptible hosts where the approximation of homogeneous mixing among hosts does not hold . Multistrain epidemics in the absence of homogeneous mixing have been studied assuming static networks or lattices , without considering host mobility [44]–[46] , and in the context of pathogen evolution , often providing detailed approaches regarding biological and epidemiological mechanisms ( e . g . they properly account for pathogen mutation , physiological trade-off , cross-immunity and other relevant immunological and biological aspects ) but lacking explicit modeling of host behavioral ecology regarding mobility [47]–[51] . In view of all the elements at play in the study of host-multipathogen systems , a key question is therefore to assess to what extent patterns of coexistence or dominance of parasites are shaped by competition among infectious agents induced by specific mechanisms of interaction , as opposed to other biological factors characterizing individually the pathogens or the host population . In this paper we focus on the competition mechanisms induced by hosts mobility in a spatially structured population in the case of two strains with full cross-immunity ( an exploration of the partial cross-immunity case is reported in the Text S1 ) . In order to single out the effect of mobility and population structure on the competition dynamic , we do not consider pathogen evolution processes . Furthermore we consider rapid acute infections , and ignore within-host interactions and within-host coexistence , which may instead be more relevant for persistent infections . This modeling framework represents a plausible setting for the analysis of a multistrain model for human influenza A in the framework of a single epidemic season . In this case the immune-driven antigenic drift has been rarely observed in a geographically restricted region [52] , [53] , suggesting that virus diversity is largely generated through importations instead of evolutionary mechanisms [52]–[54] . By introducing a general modeling framework in terms of a metapopulation approach , we find that changes in the host mobility rate alter the ecological conditions of the host-multipathogen system , which in turn changes the competitive balance between strains , resulting in a shift in their relative abundance and/or dominance . Given the importation of two strains with the same basic reproductive number ( i . e . equal advantage at the population level within each patch ) but different timescales characterizing the infectious period , an increase in the host mobility selects the fast strain ( i . e . the strain with the shorter infectious period ) that becomes dominant in the system . On the contrary , fragmented population with low host mobility selects the slow strain ( i . e . the strain with the longer infectious period ) as it diffuses more efficiently from one patch to another reaching the highest prevalence in the population . An intermediate mobility regime exists where the two strains codominate in the system . Computational results are further supported by theoretical arguments . The simplifying assumptions considered in the model make it applicable to a large variety of host-multipathogen systems , as competition may arise in the interactions between strains but also of unrelated pathogens; within this general framework we therefore use pathogen , parasite type , strain , or variant as synonymous hereafter .
We consider a two-pathogen compartmental model that tracks hosts according to their pathogen-specific infection status . The infection by each strain is described by a susceptible-infectious-recovered ( SIR ) dynamics [55] . We assume full cross-immunity , so that after infection by one strain the host is found to be fully immune to the other strain . We also assume that no other interaction among strains occurs besides full cross-immunity , therefore neglecting coinfection or superinfection events , a plausible assumption for rapid acute infections such as influenza . The case of partial cross-immunity among strains is also presented in the Text S1 , however the full exploration of this case and of the resulting phase space of the system will be the object of further studies . The SIR dynamics for strain , with , is ruled by the transition rates , and , representing the disease transmissibility rate ( for the transition from susceptible to infectious ) and the recovery rate ( for the transition from infectious to recovered ) , respectively . The dynamics is characterized by the basic reproductive number , defined as the expected number of secondary infections that one infectious host can produce during its lifetime as an infectious host placed in an entirely susceptible population , leading to the threshold condition for an epidemic outbreak in the population , [55] . In our study , we assume that the two strains have the same basic reproductive number , , but different infectious periods . This represents a case in which the pathogens have the same transmission potential and generate outbreaks characterized by the same impact on the population expressed in terms of attack rates . The epidemic waves are however different , unfolding with different timescales , the faster being the one characterized by the shorter generation time . In our case the generation time is uniquely determined by the infectious period [55] ( see Figure 1 ) and without loss of generality we consider a fast strain with infectious period and a slow strain with infectious period . The parameter quantifies the timescale separation . The infection transmission is modeled by dividing the population of individuals into four compartments: susceptible , infected by the fast strain , infected by the slow strain and recovered , i . e . immune to both strains . Each susceptible individual can contract either strain with the corresponding force of infection , or , where is imposed by the equivalence of the basic reproductive numbers of the two strains . The two infection events are independent and mutually exclusive because of the assumptions considered . The multipathogen disease dynamics affects a spatially structured population of hosts modeled through a metapopulation system . This theoretical framework was first used in population ecology , genetics and adaptive evolution to describe population dynamics whenever the spatial structure of populations is known to play a key role in the system's evolution [56]–[59] and later applied to understand the epidemic dynamics on such substrates [60]–[64] . For the case of epidemic modelling , the infectious disease spreads in an environment characterized by a non-continuous spatial distribution of susceptible hosts and the pathogen diffusion depends on the ability of hosts to move from one region of the system to another one , connecting otherwise isolated communities [58] , [59] . Hosts mix homogeneously within the local communities ( also called subpopulations or patches or nodes of the metapopulation network ) , whereas at the global , system-wide level , patches are coupled through the migration of hosts ( represented in terms of mobility connections between patches ) , as schematically shown in Figure 1 . Here we consider a metapopulation network with subpopulations . To each node , we assign an initial number of individuals , , and a degree denoting the number of connections the node has with other subpopulations in terms of mobility processes . The degrees of the nodes are distributed according to a given probability distribution , which we choose to represent the two most abundant situations in real systems – namely , a Poisson distribution accounting for homogeneous networks of contacts and a power-law functional form which represents the case in which mobility patterns are highly heterogeneous . To compare the effects of changes in the structural pattern of the subpopulations with no variations of the corresponding average values , we set the average degree of both networks , , to be the same . Homogeneous networks are generated following the Erdős-Rényi algorithm [65] , which consists of assigning a link between each pair of nodes with probability . It models a fairly homogenous system with low degree fluctuations . On the other hand , heterogeneous networks characterized by a power-law degree distribution , where we consider , are generated using an uncorrelated configuration model [66] , [67] . In this second case , the probability distribution is characterized by a second moment that is much larger than the first , which makes it critical to explicitly take into account degree fluctuations . This feature is distinctive of a vast majority of social and demographic systems that have been empirically characterized [19]–[25] , [68] . In case of homogenous traveling probability , mobility fluxes are modeled by assigning to each individual in subpopulation a probability per unit of time to travel to another neighboring subpopulation . We assume that such probability is constant across nodes , namely , and that individuals leaving a subpopulation choose at random one of the available links [36] , so that the probability of traveling from to is given by . According to the value of , different mobility scenarios emerge: high values of yield large mobility fluxes resulting in a well mixed metapopulation system where individuals easily move from one patch to another; on the contrary small probability values result in a dynamically fragmented scenario in which patches are fairly isolated . The mobility process is described by the following diffusion equation: ( 1 ) where the sum runs over the set of the nearest neighbors . According to this equation the population distribution at equilibrium is given by ( 2 ) where is the average population size . The main variables used in the model and the corresponding ranges of values considered are reported in Table 1 . We also tested in the Text S1 more realistic definitions of host mobility , following empirical findings . To simulate the spread of the two strains on the metapopulation system of susceptible hosts , we initialize the number of individuals of each subpopulation at the equilibrium value given by Eq . ( 2 ) . We then seed randomly chosen subpopulations for each strain by setting a proportion equal to of the local population size in the corresponding infectious class . These conditions ensure the start of the outbreak for each strain for the values of the basic reproductive number considered , and at the same time they aim to avoid competition at the initial stage of the multistrain epidemic . Values of the number of initially infected nodes different from 50 where tested in order to check that this does not alter the simulation results . Once the system is initialized , the transmission dynamics of the two strains is reproduced by means of Monte Carlo numerical simulations at the discrete individual level . We consider hosts as integer units and we explicitly simulate both their mobility among different subpopulations and the infection transmission within each subpopulation as discrete-time stochastic processes , with fixed time step representing the unitary time scale of the process . To this end , at each time step , the number of hosts traveling along any connection of the system belonging to any compartment and the number of new infectious and recovered hosts for each subpopulation are extracted randomly from binomial and multinomial distributions to consider all possible outcomes of these events . Further details on the algorithm used for the simulations , as well as initial conditions and parameters , are described in Section 1 of the Text S1 . For each set of parameters we simulate 2 , 000 stochastic realizations of the spatial epidemic spreading averaging over different initial conditions , and over different instances of the metapopulation network that defines the spatial structure of the system population . For each scenario , we collect statistics of epidemiological quantities , including the number of subpopulations affected by each strain , the outbreak probability , and the incidence and attack rates of each strain , both at the global level and within each subpopulation . This allows to monitor the evolution of the two epidemics , their impact on the system , and the result of the competition process . Several works have recently studied the global spreading of a single strain SIR-like epidemic in metapopulation models [34]–[41] , [69] , [70] . The threshold condition is sufficient for an epidemic outbreak to occur in a given subpopulation , but it does not guarantee the disease is able to spread globally . Low diffusion rates may indeed hinder a pathogen to disperse to other patches before it goes extinct locally , thus preventing the persistence of the virus and its spatial spread in the host population . The global spreading of an infectious disease in a metapopulation model is captured by the definition of an additional predictor of the disease dynamics , , regulating the number of subpopulations that become infected from a single initially infected subpopulation , analogously to the reproductive number at the individual level [71]–[73] . The parameter defines a global invasion threshold: the condition guarantees that the epidemic taking place in the seeding subpopulation is able to spread at the global scale reaching a non-infinitesimal fraction of the metapopulation system . depends on several factors , including disease parameters , demography , metapopulation network structure , travel fluxes and mobility timescales . Theoretical studies in [34]–[41] , [69] , [70] have addressed the impact of empirically observed features on , thus providing a better understanding about how mobility patterns and demography affect the invasion threshold of an infection . The current analytical framework allows to get an expression for , in which the impact of several sources of heterogeneities in the topology of the metapopulation system , traffic fluxes [34]–[39] , [69] , [70] and time scales [40] can be quantitatively assessed . In order to provide an understanding of the mechanisms shaping the global invasion condition of a multistrain epidemic , we review here the derivation of for the simplest case , of a single strain on a homogeneous metapopulation network with uniform mobility pattern . In a homogenous system , in which topological fluctuations can be neglected , all nodes can be assumed to have the same degree . If the mobility dynamics is described by Eq . ( 1 ) , an expression for can be obtained by formalizing the seeding process of infected hosts through their migration from one patch to another . The probability that an infected patch will seed the epidemic in a disease-free patch is given by [74] , where is the number of infectious hosts who traveled from to during the entire duration of the outbreak , while infectious . The latter quantity can be estimated as follows . The total number of individuals that experience the disease during the epidemic unfolding within the subpopulation will be , where is the attack rate given by the SIR equations and is equal to for all nodes – as recovered by Eq . ( 2 ) in the case . Each infected individual stays in the infectious state for an average time equal to the inverse of the recovery rate , during which it can travel to the neighboring subpopulation at rate . To a first approximation we can therefore consider that the number of seeds sent from to during the duration of the outbreak is given by . If we model the invasion from one patch to another in terms of a branching process , we obtain that an infected subpopulation infects on average subpopulations , where is the number of connections along which the disease can spread . This leads to the following expression for in the homogeneous assumption ( 3 ) As discussed , the global invasion threshold quantifies the spreading potential of an epidemic at the global level . For any set of parameters values characterizing the infection dynamics , the threshold condition defines a critical value of the host mobility below which the epidemic is not able to spread globally . It is worth remarking that this transition cannot be uncovered by continuous deterministic models because of the stochastic features of the contagion process and the discrete nature of circulating hosts . Let us now consider the case of two competing strains – one slow and another fast . Even if both strains have the same transmission potential at the local level , namely the same , their large scale spreading potential , encoded in , would be different . As shown by Eq . ( 3 ) , is indeed an increasing function of the infectious period , therefore . This indicates that , in a metapopulation system of fully susceptible hosts , the slow strain would be able to infect on average a larger number of subpopulations than the fast strain , although at a much slower pace . As we will see in the following section the trade-off between transmission potential and spreading time-scale crucially impacts the population level competition among the two epidemics .
We consider two strains with relatively high transmission potential , i . e . , and infectious rates given by and . As an indicator of the outcome of the competition between the two strains we consider the final number of subpopulations and affected by each strain during the outbreak . We say that a patch has been affected by a strain if at least a fraction of the population within the patch has contracted the disease . We set equal to and we checked that the results are not sensitive to the value of this parameter . By looking at the average of and when varies , we inspect several competition scenarios that are determined by mobility regimes . Figure 2A shows the results of the multistrain epidemic simulations assuming a homogeneous metapopulation structure . Different mobility regimes give rise to different coexistence and dominance patterns . For large values of the fast strain dominates affecting the vast majority of subpopulations infected in the system , the slow strain being constrained to roughly of the patches . As the value of decreases , the system-wide spreading potential of the slow strain progressively grows at the expense of the fast one , until a cross-over takes place at diffusion rate . This intermediate regime is characterized by the codominance of the two strains [75] , each one affecting approximately the same portion ( ) of infected subpopulations . Below this point , the slow strain becomes dominant , whereas the fast one only induces local outbreaks propagating through a small number of subpopulations . Eventually , for very small values of none of the strains is able to spread geographically and no global outbreak occurs . Figure 2b further illustrates this phenomenology by plotting the average value of the ratio as a function of . Values of the ratio much larger than 1 indicate the dominance of the slow strain , and values corresponding to to the opposite scenario in which the fast strain dominates . The codominance phase is obtained for values of the ratio close to 1 , with the cross-over diffusion rate given by the intersect of the curve with the horizontal line . The figure also compares heterogeneous and homogeneous metapopulation systems . The results show that the behavior is qualitatively the same for both network structures , the main quantitative difference being given by a lower value in the heterogeneous case . Similar results are also recovered with a different model for the mobility fluxes as detailed in Section 2 of the . The observed behavior can be understood according to the following intuitive explanation . After the two epidemics are seeded in their initial locations they evolve independently at the beginning , until one of the two strains reaches a subpopulation that has already been infected by the other strain , thus finding part of the population immune , i . e . a reduced pool of susceptible hosts to infect . This may prevent the strain to widely spread within the patch and diffuse further along the mobility connections towards other neighboring nodes . This competing mechanism favors the strain that spreads more rapidly and more efficiently from one patch to another , features that change depending on the mobility regime . When the traveling rate is high , the whole system is at risk of a major epidemic because of the large rate of mixing across different patches . Both and are much greater than 1 , implying that the two epidemics would successfully reach the global invasion of the system , in absence of competition . When the two strains are competing on the same metapopulation system , the relevant factor for dominating the spread is given by the spreading speed; the shorter the infectious period and the more rapidly the strain reaches a large fraction of the system patches that will thus not be invaded by the slow strain . However by decreasing the value of , of each strain also decreases . In the proximity of the invasion threshold the condition becomes relevant for the spreading dynamics and favours the slow strain which percolates more efficiently through the network . Indeed , the global epidemic time scale is not anymore dominated by the local velocity of transmission but rather by the mobility time scale of individuals . Hosts contracting the slow strain remain infectious for a longer time and thus have more chances to migrate while infectious . The low mobility rate , coupled with a short infectious period , hinders the movement of infectious hosts , resulting in a lower probability of infecting a neighboring patch . We provide a more quantitative understanding of the crossover behavior in the section dedicated to the analytical discussion of the results . The same argument applies to explain the difference between the two network topologies observed in Figure 2B . The topological fluctuations that characterize the heterogeneous topology induce larger values of the parameter with respect to the corresponding homogeneous network ( provided that the rest of parameters is kept the same ) [34]–[36] . Therefore the invasion threshold becomes larger than one for the two strains for smaller values of the mobility rate in the heterogenous case , which results in a shift of the cross-over diffusion rate towards lower values . In the case of partial cross-immunity presented in the Text S1 , we find that the main results reported for the full cross-immunity scenario still hold . Specifically , we have simulated situations in which recovered individuals from one strain may have up to cross-immunity to the other strain , which roughly correspond to estimates for diverse degrees of antigenic drift of influenza [76] . We now focus on characterizing the coexistence of both strains at the within-patch level and their spread at the global spatial level . We define the coexistence probability as the probability that within the same subpopulation both strains produce at least 1% of the population infected . For both heterogeneous and homogeneous mobility networks is an increasing function of the traveling rate ( Figure 3 ) , therefore mobility favors the coexistence of the two strains within the same subpopulation . Coexistence is however generally unlikely to occur in a vast fraction of subpopulations , given the relatively small values of the probability obtained , showing that the two strains rarely coexist within the same subpopulation and the competition takes place at the metapopulation level . To further characterize the two strain coexistence within a patch , we measure for each patch the attack rate at the end of the outbreak , defined by a two-dimensional variable , where is the fraction of hosts affected by the fast ( slow ) strain within the patch during the outbreak . In all mobility regimes explored , the interaction between the two strains can be mapped to a small region of the space . Specifically , the strains always produce attack rates with a strictly linear dependence ( Figure 4 , panels A , B , C ) , characterized by probability distributions centered around and and with different proportions in the three diffusion regimes considered ( Figure 4 , panels D , E , F ) . Moreover configurations in which only one strain is present in a subpopulation have a frequency of occurrence much higher than configurations where the two strains co-exist , further confirming the results of Figure 3 . We explore whether the coexistence of the two strains at the local level may carry a spatial signature . In absence of georeferenced data in our model that is based on an abstract spatial network , we consider the topological properties of the patches as possible spatial indicators . Noticeable differences arise when the probability of within-patch coexistence is measures by degree classes ( Figure 5 ) . In both homogenous ( panel A ) and heterogenous ( panel B ) cases , is an increasing function of and it can vary over more than two orders of magnitude from poorly connected subpopulations to most connected ones . This behavior , although expected because highly connected patches are more likely to collect individuals from other subpopulations , highlights two different levels for strains competition in the system . On one side , in highly connected nodes the two strains compete at the single subpopulation level and the predominance of one of the two strains is dictated only by their epidemic parameters . Such behavior is mostly due to the fact that highly connected nodes are almost surely reached by infected individuals of both strains at the early stage of the spreading process . Thus , both strains are likely to infect a non-vanishing fraction of the node population at the same time , leading to higher probability of coexistence . On the other hand , as low connected nodes are harder to reach , the competition is mostly driven by the time at which one strain reaches the subpopulation . The first strain to disseminate to the low connected patch has likely enough time to infect a large fraction of the susceptible hosts before the arrival of the other strain . In this case the competition between the two strains acts at the metapopulation level as coexistence between the strains is almost zero . To conclude our analysis of the system at the patches' degree level in Figure 6 we present the fraction of infected subpopulations with degree for the two strains as a function of the degree in the cross-over mobility region . In both homogenous and heterogenous networks the slow strain shows a higher incidence for low-degree nodes , whereas for intermediate and higher connectivities , the fast strain dominates the spreading process . Finally , we focus on the two parameters that mainly affect the spreading of the strains and their interaction – namely , the reproductive number of both strains and the ratio between the infectious periods of the two strains . Variations of from 1 . 1 to 4 induce a variation of the cross-over mobility rate of more than two orders of magnitude ( Figure 7A ) , with higher values of the basic reproductive number leading to smaller values of . The decrease observed in the cross-over rate is very rapid for , followed then by an almost constant value for larger values of in both network types , indicating the presence of a critical beyond which the interaction dynamics of the two strains is dominated only by the disease parameters and not by the mobility rate . Differently from , variations of do not strongly alter the value of the cross-over mobility rate , with a change of of one order of magnitude inducing variations in of less than ( Figure 7B ) . Moreover , the initial fall off observed for at fixed ( panel a ) is not seen anymore . In both plots we note that the critical diffusion rate is smaller in the heterogeneous networks with respect to the homogenous ones for the whole range of parameters explored , confirming a favoring effect in the spatial spread of both strains as previously discussed . To provide a specific example , we applied this framework to the case of two influenza-like strains spatially circulating on the real worldwide aviation network ( assuming full cross-immunity and epidemiological parameters as in Figure 7B ) , we obtain that the air-transportation mobility scenario falls in the regime in which the fast strain is dominant for all the values of tested ( more details are reported in the Text S1 ) . Here we focus on the case of homogeneous networks and propose a simplified analytical description of the dynamics to gain theoretical insights to further support the observed numerical behavior . We consider a continuous time approximation and assume that two strains do not interact at the early stage of the spreading process , in order to provide an estimation of the critical diffusion rate below which we have the dominance of the slow strain and above which we have the dominance of the fast strain . The basic approach is to treat the dynamics at the system level in terms of the usual SIR model in a well mixed population , considering the subpopulations as the elementary ingredients of the spreading process . Under this assumption , the number of infected subpopulations grows exponentially in time , and we can write ( 4 ) where is the duration of the outbreak in a single population and is the estimator of the invasion potential , as described in the Methods section , i . e . is the analogous of the basic reproductive number at the metapopulation level . If we consider the case of two epidemics starting at different seeded subpopulations , by neglecting possible interactions among the two strains , we obtain that the ratio between the number of subpopulations infected by the slow strain and the number infected by the fast one is given by: ( 5 ) Our goal is to derive the cross-over diffusion rate at which we have that both strains cocirculate , which is given by the condition . Hence , from Eq . ( 5 ) , we get ( 6 ) In the case of equal size populations , and for the same , it is possible to show that the timescale defining the epidemic unfolding , for instance the maximum of the removal rate , is well approximated by a linear dependence on [74] , [77] . We can therefore assume that and substituting Eq . ( 3 ) into Eq . ( 6 ) we explicitly arrive to the crossover condition as ( 7 ) where simplifies and disappears from the equation . Finally , denoting: ( 8 ) we have: ( 9 ) Eq . ( 9 ) can always be solved for numerically and , in some cases , analytically . The comparison between theoretical predictions and numerical simulation results shows a good agreement in the behavior of the cross-over diffusion rate as a function of ( Figure 8 ) , confirming that the analytical approximation is able to capture the fundamental mechanisms for competition between the two strains .
We studied a two-pathogen interaction in a spatially structured population of susceptible hosts mediated by immunological mechanisms ( full cross-immunity ) and ecological ones ( hosts mobility ) , where other biological and epidemiological features are kept equal across pathogens ( basic reproductive number ) . Assuming the two diseases to be imported locally in different patches , we find that a variety of scenarios emerge as a result of the competition between pathogens , driven by the host mobility rate . Either both infectious agents cocirculate and codominate in the system , each of them reaching a substantial fraction of the patches , or one of the two dominates constraining the other to a rapid extinction . The spatial structure enables the selection for a given trait depending on the hosts behavioral ecology regarding mobility . A longer infectious period constitutes a disadvantage for a rapidly mixing population across different patches as it generates a slower epidemic at the local level and therefore a slower invasion at the spatial scale . If the typical timescale for host mobility increases , the longer period during which hosts remain infectious make the invasion process more efficient with respect to the faster strain . We found that in all cases the two strains rarely coexist within the same patch . Therefore , the competition occurs at the metapopulation level and it is determined by the spreading pattern at large spatial scales which in turn depends on the structure of the mobility network . Several works have recently shown the crucial role of host dispersal in mediating multi-strain interaction and in canalizing the evolution of pathogens traits [47]–[51] . Our model contributes to this research efforts by focusing on the specific aspect of infectious duration and providing a clear understanding of how the interplay between the time scales of the dynamical processes involved – the unfolding dynamics of the two epidemics and host mobility dynamics – affects multi-strain competition . Therefore it highlights a mechanism that plays a potentially relevant role on the process of pathogen evolution . Moreover , given that strains can only interact when they coexist , our results are of further interest as they show under what mobility conditions this interaction at the subpopulation level is feasible . Our results show that there exist a codominance regime around the cross-over host diffusion rate , where each infectious agent accounts for a proportion approximately equal to of the subpopulations of the system . However dominance of a single strain is more likely to occur than codominance as an outcome of competition , as measured by the larger interval in the phase space corresponding to a strain invading the majority of the patches . This result is consistent with the laboratory confirmed influenza surveillance data in the Northern and Southern hemisphere showing that H1 and H3 subtypes are rarely found in the same season in a given country ( 1 out of 171 country influenza seasons analyzed ) [75] . In the model we considered full cross-immunity among the circulating strains , a situation applicable , e . g . , to measles infections , characterized by complex recurrent epidemics arising from cyclic exhaustion of susceptible hosts in the population [78] . This assumption is also often considered as a simplification when modeling multiple strains of influenza , though immunity after infection is strain-dependent and only partial cross-immunity against viral variants is found [6] . We have explored situations of partial cross-immunity showing that our findings are stable for relatively high degrees of cross-immunity between the two strains considered . These results thus show that our framework may be applicable to two strains having a high level of similarity in their genetic and antigenic profiles , as this provides large cross-immunity across influenza strains . A full exploration of the spectrum of cross-immunity values is needed to further investigate to what extent they may affect the findings of this work . The model may also be extended to more than two interacting pathogens . While straightforward from a design point of view , increasing the number of pathogens rapidly increases the complexity of the system and the corresponding computational time of its numerical simulations , so that targeted methods need to be developed to reduce the exponentially large state spaces [79] . Furthermore our model considered an infection dynamics acting on timescales much shorter than the host lifetime , and no demographic processes were therefore taken into account . In order to study outbreaks on longer timescales or that occur in recurrent cycles , mechanisms for susceptible hosts replenishments in the population need to be considered , as for instance birth and death processes in the case of measles epidemics or loss of immunity in the case of influenza infection . This latter case would correspond to a two-strain SIRS compartmental approach and it could be used within our framework to study the role of host mobility on strain replacement events , as it may occur after influenza pandemics , where we need to assume that the other strain is already present and at equilibrium when an additional strain emerges in the system . While an application to human influenza A seems plausible with the limitations discussed above , a more comprehensive understanding of the general evolutionary dynamics of influenza viruses , central to its surveillance and control , would need to include punctuated antigenic change [80] , reassortment events [53] , [81] , [82] , multiple circulating lineages [81] , among other factors . The simplicity of the approach , on the other hand , allows us to provide analytical insights and theoretical predictions that further support the numerical results obtained with mechanistic discrete stochastic simulations . Such predictions are obtained with a very simplified mathematical reasoning , and here we discuss the main assumptions considered . We assumed that the two epidemics do not interact at the early stage , which is strictly verified only in the limit of infinite network size . Moreover , in using SIR-like equations for the dynamics of the number of infected patches , treated as a continuous variable in the continuous time approximation , we supposed that the infectivity of a node decays exponentially over time . However , in general , the infectivity of a subpopulation is proportional to the number of infectious individuals present in that subpopulation , which has a more complex functional dependence on . Notwithstanding these approximations , the theoretical estimates for the cross-over diffusion rate are in good agreement with the values recovered numerically , for a large range of values . It is also worth remarking that the presented framework is valid not only for human mobility and human multistrain epidemics , but it also applies to farmed or wild animals for which data on movements are available or can be partially mapped , along with the corresponding virological and serological data . The model could be for instance considered to investigate the role of bovine displacements among premises in a given country [19] , [20] and for import/export across countries in the competition among foot-and-mouth disease strains [8] following episodic invasion events [17] , [83] , or in the cocirculation of new serotypes of bluetongue virus following importation in Europe in 2006 and 2007 [84] . Changing dynamics of dominant serotypes of rabies viral infections may be also related to changes in hosts movements ( induced e . g . by changes in the local environment or ecosystem disturbances ) , in addition to other mechanisms [85] . Variations in hosts behavioral ecology may be tested to further investigate the interactions among multiple subtypes of avian influenza virus in specific settings , given their importance in the possible occurrence of reassortment events leading to the emergence of novel viruses [86] . Here we focused specifically on directly transmitted diseases that can be well described by the homogeneous mixing assumption within each local community of hosts coupled by spatial propagation due to host migrations among communities . | When multiple infectious agents circulate in a given population of hosts , they interact for the exploitation of susceptible hosts aimed at pathogen survival and maintenance . Such interaction is ruled by the combination of different mechanisms related to the biology of host-pathogen interaction , environmental conditions and host demography and behavior . We focus on pathogen competition and we investigate whether the mobility of hosts in a spatially structured environment can act as a selective driver for pathogen circulation . We use mathematical and computational models for disease transmission between hosts and for the mobility of hosts to study the competition between two pathogens providing each other full cross-immunity after infection . Depending on the rate of migration of hosts , competition results in the dominance of either one of the pathogens at the spatial level – though the two infectious agents are characterized by the same invasion potential at the single population scale – or cocirculation of both . These results highlight the importance of explicitly accounting for the spatial scale and for the different time scales involved ( i . e . host mobility and spreading dynamics of the two pathogens ) in the study of host-multipathogen systems . | [
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"mathe... | 2013 | Host Mobility Drives Pathogen Competition in Spatially Structured Populations |
Canine rabies was endemic pre-urbanisation , yet little is known about how it persists in small populations of dogs typically seen in rural and remote regions . By simulating rabies outbreaks in such populations ( 50–90 dogs ) using a network-based model , our objective was to determine if rabies-induced behavioural changes influence disease persistence . Behavioural changes–increased bite frequency and increased number or duration of contacts ( disease-induced roaming or paralysis , respectively ) –were found to be essential for disease propagation . Spread occurred in approximately 50% of model simulations and in these , very low case rates ( 2 . 0–2 . 6 cases/month ) over long durations ( 95% range 20–473 days ) were observed . Consequently , disease detection is a challenge , risking human infection and spread to other communities via dog movements . Even with 70% pre-emptive vaccination , spread occurred in >30% of model simulations ( in these , median case rate was 1 . 5/month with 95% range of 15–275 days duration ) . We conclude that the social disruption caused by rabies-induced behavioural change is the key to explaining how rabies persists in small populations of dogs . Results suggest that vaccination of substantially greater than the recommended 70% of dog populations is required to prevent rabies emergence in currently free rural areas .
Canine rabies is an ancient disease that has persisted in dog populations for millennia–well before urbanisation [1] . Increased understanding of rabies spread in communities with relatively small populations of dogs–such as those in rural and remote areas–could give insights about rabies persistence in non-urban areas , as well as inform prevention and control strategies in such regions . Rabies virus is neurotropic and clinical manifestations of canine rabies can be broadly classified as the dumb form ( characterised by progressive paralysis ) and the furious form ( characterised by agitated and aggressive behaviour; [2–4] ) . Although the mechanisms of rabies-induced behavioural signs are poorly understood [5] , pathogen-influenced changes in host behaviour can optimise pathogen survival or transmission [6] . We hypothesise that rabies-induced behavioural changes promote rabies transmission in dog populations by influencing social network structure to increase the probability of effective contact . If so , this would enable rabies to spread in rural and remote regions . Since 2008 , rabies has spread to previously free areas of southeast Asia . Islands in the eastern archipelago of Indonesia , as well as Malaysia are now infected [7–10] . Much of this regional spread of canine rabies has occurred in rural and remote areas . Oceania is one of the few regions in the world in which all countries are rabies free . Recent risk assessments demonstrate that Western Province , Papua New Guinea ( PNG ) and northern Australia , are at relatively high risk of a rabies incursion [11 , 12] . Dogs in communities in these regions are owned and roam freely . Population estimates in such communities are often low; for example , median 41 dogs ( range 10–127 ) in Torres Strait communities ( pers comm: annual surveys conducted by Queensland Health , and Brookes et al . [13] ) and median 100 dogs ( range 30–1000 ) in Western Province Treaty Villages ( pers comm: annual surveys conducted by the Australian Commonwealth Department of Agriculture ) . Canine rabies might have a low probability of maintenance in domestic dogs in these communities due to their small population sizes , but if continued transmission occurs–particularly over a long duration–then spread to other communities or regional centres and regional endemicity might occur . GPS telemetry data from small populations of dogs ( < 50 dogs ) in the Torres Strait have recently been collected [13] . Such data has been used to describe contact heterogeneity in animal populations , and has been used in models to provide insights about disease spread and potential control strategies [14–16] . The effect of contact heterogeneity on disease spread is well-researched and models can provide useful insights about disease control strategies in heterogeneously mixing populations [17–19] . Most recently in the context of rabies , Laager et al . [20] developed a network-based model of rabies spread using GPS telemetry data from dogs in urban N’Djamena , Chad . Other models of rabies-spread in which parameters that describe contact heterogeneity were derived from telemetry data include canine [21] and raccoon models [22 , 23] . Patterns of contacts are likely to be altered by the behavioural effects of clinical rabies . Although Hirsch et al . [22] demonstrated that seasonal patterns of rabies incidence in raccoons could be explained by changes in social structure due to normal seasonal behavioural change of the hosts , the influence of rabies-induced behavioural changes on social structure has neither been researched nor explicitly incorporated in simulation models in any species . Here , our objective was to investigate the probability , size and duration of rabies outbreaks and the influence of rabies-induced behavioural changes on rabies persistence in small populations of free-roaming dogs , such as those found in rural communities in PNG and northern Australia . We also investigate the effect of pre-emptive vaccination on rabies spread in such populations .
We developed an agent-based , stochastic , mechanistic model to simulate social networks of free-roaming domestic dogs and the subsequent transmission of rabies between individual dogs within these networks following the latent infection of a single , randomly-assigned dog ( Fig 1 ) . The structure of the social networks was based on three empirically-derived networks of spatio-temporal associations between free-roaming domestic dogs in three Torres Strait Island communities ( Table 1 ) ; Kubin , Warraber and Saibai [13] . The progression of rabies infection in a susceptible dog was simulated in daily time-steps and followed an SEI1I2R process ( rabies infection status: susceptible [S] , latent [E] , pre-clinical infectious [I1] , clinical [I2] and dead [R] ) . Rabies virus transmission from an individual infectious ( j ) to an individual susceptible ( i ) dog is described by Eq 1 , in which the daily probability of contact between a pair of such dogs was calculated based on the edge-weight between the pair ( Eij ) , which is the proportion of a 24 hour period during which that pair of dogs is spatio-temporally associated ( in the event of no network connection , Eij = 0 ) . Transmission of rabies further depends on the probability of a bite ( Pj ) by the infected dog conditional on its infection status ( I1 or I2 ) , and the probability of subsequent infection of the susceptible dog ( Tj ) . Generation of the social network and estimation of the parameters associated with the dog population dynamics and rabies epidemiology are described below , and parameter values are shown in Table 2 . Maximum iteration duration was 3 years . Model outputs included distributions of the predicted duration of outbreaks ( defined as the number of days from the introduction of one latently infected dog to the day on which infected dogs were no longer present ) , the total number of rabies-infected dogs during the outbreak and the effective reproductive number , Re , during the first month following incursion ( mean number of dogs infected by all dogs that were infected during the first month ) . Initially , rabies was simulated in each of the three community networks and the predicted outputs from each model were compared between each other . Statistical tests were used to determine the number of iterations required to achieve convergence of output summary statistics ( described below ) . Global sensitivity analysis using the Sobol’ method ( described below ) was used to investigate the relative influence of all input parameters on model outputs . To observe the influence of rabies-induced behavioural changes , model outputs from simulations of rabies spread in each of the three community networks with and without parameters associated with rabies-induced behavioural changes were compared . Finally , the impact of pre-emptive vaccination was investigated by randomly assigning rabies immunity to a proportion of the population ( 10–90%; tested in 10% increments ) prior to incursion of the rabies-infected dog in each iteration . Prior to each iteration , a modified Watts Strogatz algorithm generated a connected , undirected small-world network of 50–90 dogs with network characteristics that reflected the empirical networks of the dog populations in Saibai , Warraber and Kubin communities , as follows [13 , 24–26] . Consistent with the terminology used in our previous description of these networks [13] , dogs are nodes , connections between dogs are edges , the proportion of spatio-temporal association ( within 5m for at least 30s ) between a pair of connected dogs in each 24 hour period is represented as edge-weight , and degree refers to the number of network connections for an individual dog . Re-wiring refers to re-assignment of an individual dogs connections in the network . A regular ring lattice was constructed with N nodes in which N was randomly selected from a uniform distribution of 50–90 . Each node was assigned K degrees , which was randomly selected from the respective empirical degree distribution of the community represented by the simulation . Each node ( ni ) was connected to Ki/2 ( rounded to the nearest integer ) nearest neighbours in the ring lattice in a forward direction , then all nearest neighbours in a backward direction until Ki was achieved . Existing edges were then re-wired ( the edge was disconnected from the nearest neighbour and reconnected to a randomly selected node ) following a Bernoulli process ( probability ρ ) to achieve an average shortest path-length expected in an equivalent-sized Erdõs-Réyni graph in which nodes are connected randomly , whilst maintaining the empirical degree distribution of the community represented by the simulation [27] . Edges were then weighted according to the mean expected duration of association between pairs of dogs as a proportion of daily time , and were randomly selected from the respective empirical edge-weight distribution of the community represented by the simulation . Parameters that describe the empirical networks and their derivation are presented in Brookes et al . [13] . Networks simulated with the modified Watts Strogatz algorithm were tested for similarity to the empirical networks prior to use of the algorithm in the model ( Table 1 ) . Degree and edge-weight distributions were compared to those of the empirical networks using the Mann-Whitney U and Kolmogorov-Smirnoff tests , to assess similarity of median and shape of simulated distributions , respectively . Mean small-world indices were calculated according to Eq 2 in which C is the global clustering coefficient , L is the average shortest path length , s denotes a simulated network and r denotes an Erdos-Reyni random network of equivalent mean degree [28] . A small-world index >1 indicates local clustering , consistent with the empirical network structures . Network similarity tests were conducted on 1000 simulated networks for each community . Parameters that were used to describe the dog populations and rabies epidemiology in the model are listed in Table 2 . Variance-based GSA using the Saltelli method was used to determine which parameters most influenced the variance of outputs and was implemented in this study using the SALib module in Python [41] . The sequence of events were: parameter sampling to create a matrix of parameter sets for each iteration ( parameter ranges are listed in Table 2 ) , simulation using the parameter sets to obtain model output ( duration of outbreaks , the total number of rabies-infected dogs and the mean monthly effective reproductive number , Re ) , and estimation of sensitivity indices ( SIs ) to apportion output variance to each parameter . Mean monthly Re was used as the output of interest in relation to R for Sobol analysis , to remove the strong influence of incubation period on Re in the first month . To separate the influence of stochasticity from the variation associated with each parameter , the random seed was also included in the Sobol’ analysis [42] . The seed value for each iteration was selected from the parameter set ( uniform distribution , 1–100 ) . First-order and total-effect SIs were estimated for each parameter , representing predicted output variance attributable to each parameter without and with considering interactions with other inputs , respectively . SIs were normalised by total output variance and plotted as centipede plots with intervals representing SI variance . Model output variance is most sensitive to inputs with the highest indices . The number of iterations required to achieve sufficient convergence of summary measures was estimated using the following method . Key output measures–the number of rabid dogs and the duration of outbreaks ( days ) –were recorded from 9 , 999 iterations of the model divided equally between all three communities . Ten sets of simulated outputs of an increasing number of iterations ( 1–5000 ) were sampled; for example , ten sets of outputs from 1 iteration , 10 sets of outputs from 2 iterations , 10 sets of outputs from 3 iterations , and so on . The mean number of rabies-infected dogs and outbreak duration was calculated for samples in each set . The coefficient of variation ( CV; standard deviation/mean ) of these sample means was then calculated for each set . With increasing iterations , the variation in sample mean between sets decreases and the CV approaches zero . The number of iterations was considered sufficient to indicate model output stability when 95% of the previous 100 iteration sizes CV was < 0 . 025 .
Each community simulation comprised 10 , 000 iterations ( more than sufficient to achieve convergence of summary output statistics without limiting computational time [S1 Fig] ) . Predicted outputs are shown in Table 3 . The proportion of iterations in which a second dog became infected was greater than 50% in Kubin and Warraber communities , and 43% in Saibai . In these iterations , predicted median and upper 95% duration of outbreaks were longest in Warraber and shortest in Saibai ( median: 140 and 78 days; 95% upper range 473 and 360 days , respectively ) . In the Warraber simulations , 0 . 001% of iterations reached the model duration limit of 1095 days . The number of infected dogs was reflected in the Re estimates in the first month: 1 . 73 ( 95% range 0–6 . 0 ) , 2 . 50 ( 95% range 1 . 0–7 . 0 ) and 3 . 23 ( 95% range 1 . 0–8 . 0 ) in Saibai , Kubin and Warraber communities , respectively . The rate of cases during these outbreaks was 2 . 4 cases/month ( 95% range 0 . 6–7 . 6 ) , 2 . 0 cases/month ( 95% range 0 . 4–6 . 5 ) and 2 . 6 cases/month ( 95% range 0 . 5–8 . 0 ) in Saibai , Kubin and Warraber communities , respectively . Fig 2 shows plots of the Sobol’ total-effect sensitivity indices ( SI ) of parameters for outbreak duration , number of infected dogs and the monthly effective reproductive ratio Re . S2 Fig shows Sobol’ first-order effect SIs , which are low relative to the total-effect SIs for all outcomes . This indicates that interactions between parameters are highly influential on output variance in this model and therefore , we focus on the influence of parameters through their total effects . As expected , the total-effect SI of the seed was highest–it was associated with > 50% of the variance for all outcomes–because it determines the random value selected in the Bernoulli processes that provide stochasticity to all parameters . The influence of the seed is not presented further in these results . Incubation period , the size of the dog population and the degree of connectivity were highly influential on outbreak duration ( total-effect SI 0 . 51 , 0 . 55 and 0 . 51 , respectively ) . All parameters were influential on the predicted number of rabid dogs ( total effect SIs > 0 . 1 ) . The size of the dog population , incubation and clinical periods , and degree had greatest influence ( total effect SIs > 0 . 5 ) . Dog population size and degree of association were most influential on predicted mean monthly Re ( total effect SI 0 . 74 and 0 . 40 , respectively ) . Of the community-specific parameters ( population size , degree and edge-weight distributions , birth and death rates , and initial probability of re-wiring ) , dog population size and the degree consistently had the greatest influence on each predicted output’s variance . Of network parameters other than degree , the probability of wandering ( ‘re-wiring’ ) during the clinical phase ( furious form ) was markedly less influential on predicted mean monthly Re than initial ‘re-wiring’ ( total effect SIs 0 . 051 and 0 . 19 , respectively ) or either parameter associated with spatio-temporal association ( edge-weight; both total effect SIs > 0 . 15 ) . The influence of the increased probability of a bite by a dog in the clinical period ( furious form ) on predicted mean monthly Re was greater compared to the pre-clinical or clinical ( dumb-form ) bite probability ( total-effect SI 0 . 19 relative to 0 . 11 ) . The size of the relative influence of these parameters on outbreak duration or number of rabies-infected dogs was reversed and less marked . Birth and death rate consistently had a moderate influence on all outputs ( total-effect SI 0 . 20–0 . 24 ) . The proportion of outbreaks in which > 1 dog became infected , and the duration , number of infected dogs and Re in the first month following incursion in simulations without all or with combinations of parameters for rabies-induced behavioural changes , are shown in Fig 3 . Outputs from the simulation in each community with all parameters ( increased bite probability [furious form] , increased spatio-temporal association [edge-weight; dumb form] , wandering [‘re-wiring’; furious form] ) are included for comparison . The simulation without parameters for rabies-induced behavioural changes ( Fig 3; ‘None’ ) propagated following < 10% of incursions in all communities . In 95% of these predicted outbreaks , rabies spread to ≤ 3 other dogs during a median of ≤ 60 days . This was reflected in the low Re estimate in the first month of these incursions ( ≤ 0 . 75 ) . Inclusion of one parameter associated with rabies-induced behavioural changes was still insufficient for sustained predicted outbreaks . Overall , < 20% incursions in these simulations resulted in rabies spread to ≤ 6 other dogs over a median duration of ≤ 56 days . Re in the first month of these incursions indicated that increased spatio-temporal association , followed by an increased probability of bite were more likely to result in rabies spread than ‘re-wiring’ to increase network contacts in these simulations . This pattern was reflected in the upper 95% range of dogs infected , which was greatest when increased spatio-temporal association was included , and least when ‘re-wiring’ was included . When combinations of rabies-induced behavioural changes were included , increased bite probability and spatio-temporal association together were sufficient to achieve similar proportions of predicted outbreaks in which > 1 dog was infected ( 40–60% of incursions ) as the simulation with all parameters included ( Fig 3 ‘Full’ ) . Predicted impacts and Re in the first month following incursion were also similar . Re was greater than the sum of Re from scenarios with increased bite probability and spatio-temporal association alone . With combined spatio-temporal association and ‘re-wiring’ , the 95% range of the number of infected dogs was greater than simulations in which only one parameter was included ( up to 11 other dogs ) but Re in the first month following incursion was close to 1 in all communities , reflecting overall limited rabies spread . In the combined increased bite probability and ‘re-wiring’ simulation , propagation did not occur to > 4 dogs , reflecting the Re of ≤ 0 . 8 . Due to the similarity between median outputs from each community and greatest variation in outputs from Warraber , only vaccination simulations using the Warraber network were included in this section . Initially , all parameters were included in these vaccination simulations ( births and deaths were included ) . Vaccination simulations were then run without population turnover ( births and deaths were excluded ) . Fig 4 shows all outputs . In all simulations , the proportion of outbreaks in which > 1 dog was infected fell as the proportion of pre-emptively vaccinated dogs increased–a greater reduction was observed in the simulations without population turnover–and was < 40% when at least 70% of the population were vaccinated . The proportion of outbreaks in which more than one dog was infected was still 17% and 12% when 90% of the population were vaccinated in simulations with and without births and deaths , respectively . In outbreaks in which > 1 dog was infected , the duration of outbreaks decreased as vaccination proportion increased ( although the 95% range was always predicted > 195 days in all simulations ) . The median number of infected dogs was ≤ 3 once at least 60% of dogs were vaccinated in all simulations , but the 95% range was not consistently < 10 dogs until 80% and 70% of the population was vaccinated in simulations with and without births and deaths , respectively . The median case rate was 1 . 6 cases/month ( 95% range 0 . 4–4 . 6 cases/month ) when 70% of the population was vaccinated in simulations with births and deaths , with a median duration of 68 days ( 95% range 16–276 days ) . In simulations without births and deaths , the case rate was 1 . 4 cases/month ( 95% range 0 . 4–4 . 3 cases/month ) when 70% of the population was vaccinated , with a median duration of 64 days ( 95% range 16–248 days ) . Re estimated in the first month following incursion reflected these outputs . At ≥ 70% pre-emptive vaccination , Re was approximately 1 or less when births and deaths were excluded . However , in the simulations with births and deaths Re did not fall below 1 until > 80% of the population were pre-emptively vaccinated .
Our study is unique in that we modelled rabies spread in small populations of free-roaming dogs and incorporated the effect of rabies-induced behavioural changes . Key findings included the long duration of rabies persistence at low incidence in these populations , and the potential for outbreaks even with high levels of pre-emptive vaccination . This has implications for canine rabies surveillance , elimination and incursion prevention strategies , not only in rural areas with small communities , but also for elimination programs in urban areas . We discuss our findings and their implications below . Without behavioural change , we could not achieve rabies propagation in the social networks in the current study; disruption of social contacts appears to be key for rabies maintenance in small populations of dogs . Social network studies have shown that dogs form contact-dense clusters [13 , 20] . Increased bite probability and spatio-temporal association between contacts ( edge-weight in the model ) were most influential on rabies propagation in our model , but it is possible that ‘re-wiring’ of dogs is also influential in larger populations in which there is a greater probability that a dog would ‘re-wire’ to a completely new set of dogs in another cluster , thus increasing total contacts and enhancing spread ( degree was also found to be highly influential on rabies spread ) . Ranges for these parameters were wide to reflect uncertainty which in turn reflects the difficulty of acquiring accurate field information about the behaviour of rabies-infected dogs . It is not ethical to allow dogs that have been identified in the clinical stages of rabies infection to continue to pose a threat to other animals and humans so that field data about contact behaviour can be collected . However , whilst these parameters were important for spread to occur , their wide range was not as influential on output variance relative to other parameters for which data were more certain . In the model , limiting types of behavioural change to each rabies form was a simplification that allowed us to differentiate the effects of types of network disruption . In reality , the association between rabies forms and behavioural changes is likely to be less distinct [33] and thus , rabies spread in small populations could be further enhanced if dogs display a range of behavioural changes . Incubation period strongly influenced outbreak size and duration , and together with rabies-induced behavioural changes that enabled transmission , is likely to have resulted in the ‘slow-burn’ style of outbreaks ( low incidence over long duration ) that were predicted by this model . Within iterations in which propagation occurred , case rate was generally < 3 cases/month without vaccination , and 1 . 5 cases/month when 70% of dogs were pre-emptively vaccinated . At such low incidence , we believe that canine rabies is likely to have a low probability of detection in communities where there is high population turnover and aggressive free-roaming dogs can be normal [29 , 43] . In these populations , dog deaths and fights between dogs are common . Undetected , slow-burn outbreaks in previously free regions are a great risk to humans because rabies awareness is likely to be low . They also provide more opportunity for latently infected dogs to travel between communities either by themselves , or with people , which could result in regional endemicity . Townsend et al ( 34 ) suggest a case detection rate of at least 5% ( preferably 10% ) is required to assess rabies freedom following control measures; surveillance capacity in rabies-free regions such as Oceania should be evaluated and enhanced if required . Pre-emptive vaccination is another option to protect rabies-free regions; for example , an ‘immune-belt , ’ an area in which dogs must be vaccinated , was established in the 1950s in northern Malaysia along the Thai border [44] . The World Health Organization recommends repeated mass parenteral vaccination of 70% of dog populations to achieve herd immunity [45] . Whilst the origin of this recommendation is unclear , it has been accepted for decades–for example , legislation allowed free-roaming of dogs in designated areas if at least 70% of the dog population was vaccinated in New York State in the 1940s [46]–and previous modelling studies of pre-emptive vaccination support this threshold [20 , 47–49] . We found that vaccination with 70% coverage is expected result in outbreaks are self-limiting . Therefore , if inter-community dog movements are unlikely , the probability of regional spread is unlikely . However , given predicted upper 95% ranges of 8–14 rabies infected dogs for at least 8 months at 70% coverage , we recommend at least 90% coverage to reduce the effective monthly reproductive ratio < 1 , limit human exposure , and provide a more certain barrier to regional spread , particularly in regions where dogs are socially and culturally connected to people and consequently , movement of dogs is likely . In places in which movements are not easily restricted–such as urban centres in which dog populations are contiguous–our study indicates that comprehensive vaccination coverage is crucial and that reducing population turnover ( for example , by increasing veterinary care to improve dog health ) might not have a substantial effect on reducing the vaccination coverage required . The political and operational challenges of rabies elimination are well-documented [50] , and lack of elimination or subsequent re-emergence is attributed to insufficient vaccination coverage ( < 70% dog population overall , patchy coverage or insufficient duration [49 , 51 , 52] ) and re-introduction of infected dogs [48 , 53] . Pockets of unvaccinated dogs within well-vaccinated , urban areas could maintain rabies at a low incidence sufficient to re-introduce rabies as surrounding herd immunity wanes . It is also possible that with comprehensive , homogenous 70% coverage , a low incidence of rabies–such as appears possible at 70% vaccination in our study–is sufficient for endemicity in larger populations but is practically undetectable , giving the appearance of elimination . A higher proportion of vaccinated dogs might be required for elimination , and further modelling studies incorporating behavioural change in larger empirical networks are required to test this hypothesis . Validation of a canine-rabies spread model is challenging , not only because variation between model outputs and observed data can arise from many sources , but because rabies surveillance is passive and case ascertainment is notoriously challenging [52] , thus limiting the fitting of mathematical models and undermining comparison of predicted outputs to observed data . Mechanistic models are therefore a valuable tool to describe possible spread and develop hypotheses about rabies persistence , surveillance and control by using plausible , generalisable disease data ( in the current study , the epidemiology of rabies ) and context specific , ecological data ( in the current study , empirical network data from small populations of dogs to provide contact rates ) . Although opportunity for validation is limited because outbreak data from small populations of dogs is scarce ( and non-existent in our study area ) , observed patterns of disease spread ( low incidence and long duration of outbreaks ) are consistent with those predicted by the current study [37 , 54] . Global sensitivity analysis indicated that population size ( a parameter of reasonable certainty ) and degree of connectivity had the greatest influence on duration , size and initial spread; this makes intuitive sense , and as expected , the largest and longest outbreaks were predicted in the Warraber network which had the highest median degree . Of the parameters that most influenced model outputs , parameterisation of the degree of connectivity was most likely to influence generalisability of our study findings because data are limited and social connectivity might vary between populations of free-roaming dogs . However , a study in N’Djaména , Chad , found that the average degree was 9 and 15 ( maximum 20 and 64 , respectively ) in two populations of size 272 and 237 dogs , respectively [20] , which is not dissimilar to the degree distribution of the small Torres Strait dog populations . Reassuringly , input parameters about which there was more uncertainty–for example , bite probabilities–were less influential on variation in outputs . By exploring rabies epidemiology in small populations of free-roaming dogs–in which contact heterogeneity was determined in part by their social networks and in part by the disease–our study provides insights into how rabies-induced behavioural changes are important for endemicity of rabies in rural and remote areas . We found that rabies induced behavioural change is crucial for the disease to spread in these populations and enables a low incidence of rabies cases over a long duration . Without movement restrictions , we predict that substantially greater than the recommended 70% vaccination coverage is required to prevent rabies emergence in currently free areas . | We investigated rabies spread in populations of 50–90 dogs using a simulation model in which dogs’ contacts were based on the social networks of three populations of free-roaming domestic dogs in the Torres Strait , Australia . Rabies spread would not occur unless we included rabies-induced behavioural changes ( increased bite frequency and either roaming or paralysis that increased the number or duration of contacts , respectively ) . The model predicted very low case rates over long durations which would make detection challenging in regions in which there is already a high population turnover , increasing the risk of human infection and spread to other communities via dog movements . Spread also occurred in >30% of model simulations at low incidence for up to 200 days when 70% of the population was pre-emptively vaccinated , suggesting that higher vaccination coverage will be required to prevent rabies emergence in currently free rural areas , especially those in which dogs readily travel between communities . | [
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"med... | 2019 | Rabies-induced behavioural changes are key to rabies persistence in dog populations: Investigation using a network-based model |
Approximately 35 million people are infected with Clonorchis sinensis ( C . sinensis ) globally , of whom 15 million are in China . Glycolytic enzymes are recognized as crucial molecules for trematode survival and have been targeted for vaccine and drug development . Hexokinase of C . sinensis ( CsHK ) , as the first key regulatory enzyme of the glycolytic pathway , was investigated in the current study . There were differences in spatial structure and affinities for hexoses and phosphate donors between CsHK and HKs from humans or rats , the definitive hosts of C . sinensis . Effectors ( AMP , PEP , and citrate ) and a small molecular inhibitor regulated the enzymatic activity of rCsHK , and various allosteric systems were detected . CsHK was distributed in the worm extensively as well as in liver tissue and serum from C . sinensis infected rats . Furthermore , high-level specific IgG1 and IgG2a were induced in rats by immunization with rCsHK . The enzymatic activity of CsHK was suppressed by the antibody in vitro . Additionally , the survival of C . sinensis was inhibited by the antibody in vivo and in vitro . Due to differences in putative spatial structure and enzymology between CsHK and HK from the host , its extensive distribution in adult worms , and its expression profile as a component of excretory/secretory products , together with its good immunogenicity and immunoreactivity , as a key glycolytic enzyme , CsHK shows potential as a vaccine and as a promising drug target for Clonorchiasis .
Clonorchiasis , induced by Clonorchis sinensis ( C . sinensis ) infection , is a major public health problem in Southeast Asian countries including China , Korea , Taiwan , and Vietnam . Approximately 35 million people are infected with this neglected fluke globally , of whom 15 millions are in China [1] . The World Health Organization ( WHO ) announced in 2009 that C . sinensis infection is one of the biological agents that can induce cholangiocarcinoma [2] . In spite of its public health threat , there are still few effective measures to prevent this neglected tropical disease . Humans can be infected with C . sinensis by ingestion of raw or undercooked freshwater fish with metacercariae . The metacercariae of C . sinensis excyst in the duodenum , then migrate into hepatic bile ducts where the flukes mature into adult worms [3] . During the long term of parasitism , the worms continuously release excretory/secretory products ( ESPs ) , a cocktail of hundreds to thousands of bioactive proteins . As molecules involved in the interaction between the parasite and host , ESPs have been well characterized to be targets for vaccine and drug development [4–7] . Glycolytic enzymes such as enolase [4 , 8] and phosphoglycerate kinase [9 , 10] are recognized as crucial molecules for trematode survival , and they have been targeted for vaccine and drug development . Hexokinase ( HK ) ( ATP: D-hexose-6-phosphotransferase , EC 2 . 7 . 1 . 1 ) is the first key regulatory enzyme of the glycolytic pathway [11] . In other helminthes such as Brugia malayi ( B . malayi ) [12] , Haemonchus contortus [13] , and Schistosoma mansoni ( S . mansoni ) [14–16] HKs have been well characterized as potential targets for vaccine and drug development . In our previous study , the sequence , structure , and enzymatic properties of HK from C . sinensis ( CsHK ) were confirmed , and its molecular characteristics including molecular mass , mRNA and protein levels during different life stages of C . sinensis were determined [17] . These studies are cornerstones for our current study . In the present study , we compared the putative spatial structure of CsHK with HKs from definitive hosts of C . sinensis . The effects of a small molecule inhibitor on the enzyme kinetics of recombinant CsHK ( rCsHK ) and the immunological characteristics and immune protective efficacy of rCsHK were investigated in detail . Our results indicate that CsHK may be a promising candidate for development of vaccines and drugs against C . sinensis infection .
All animals used in the present study were purchased from the animal center of Sun Yat-sen University and raised carefully in accordance with National Institutes of Health animal care and ethical guidelines . All experimental procedures were approved by the Animal Care and Use Committee of Sun Yat-sen University ( Permit Numbers: SCXK ( Guangdong ) 2009–0011 ) . The ethical approval for human sera was granted from the Centers for Disease Control and Prevention of Guangxi Zhuang Autonomous Region , China . All human serum samples used in this study were anonymized . Metacercariae of C . sinensis were isolated from experimentally infected freshwater Ctenopharyngodon idellus fish in our laboratory pool [18] . Each Sprague-Dawley ( SD ) rat was orally infected with 50 metacercariae . At 8 weeks after infection , the rats were sacrificed and C . sinensis adults were recovered from the livers . CsESPs and rat anti-CsESPs serum were obtained as described before [4] . Purified rCsHK was obtained in our previous study [17] . Purified rCsHK ( 200 μg ) emulsified with an equal volume of complete Freund’s adjuvant ( Sigma , USA ) was injected subcutaneously into SD rats . Two boosters of 100 μg rCsHK with an equal volume of incomplete Freund’s adjuvant ( Sigma , USA ) were given at 2-week intervals . The pre-immune sera were collected prior to the first injection . The immune sera were collected at 2-week intervals from 0 to 12 weeks . As the amino acid sequence of CsHK shares 69% identical residues with the S . mansoni sequence [17] , the putative tertiary structure of CsHK was constructed based on that of HK from S . mansoni ( SmHK , Protein Data Bank , PDB: 1BDG_A ) using SWISS-MODEL and viewed by Swiss-Pdb Viewer [17 , 19] . Structural models of CsHK were superposed with closed-form human glucokinase ( hHK-IV , PDB: 1V4S_A ) [20] and the N-terminal half of closed-form rat hexokinase-1 ( rHK-In , PDB: 1BG3_B ) [21] . The allosteric sites in closed-form hHK-IV [20] and CsHK were compared . The glucose 6-phosphate ( G6P ) binding sites in CsHK were compared to that of rHK-In [21] . The accession numbers/ID numbers for genes and proteins mentioned in the text are listed in S1 Table . The enzymatic activity of HK was assayed as described using a coupled reaction [17 , 22] . A 200-μL aliquot of reaction mixture included 3 mM glucose , 3 mM ATP , 15 mM MgCl2 , 0 . 5 mM nicotinamide adenine dinucleotide phosphate ( NADP ) , 0 . 3 U of yeast glucose 6-phosphate dehydrogenase ( G6PD ) Type VII , and 100 mM Tris-HCl ( pH 8 . 5 ) . Reduced NADP ( NADPH ) formation by G6P dehydrogenation was monitored at 340 nm in a microplate reader ( SpectraMax M5 , Molecular Devices , USA ) . All enzymatic reagents were purchased from Sigma-Aldrich ( USA ) . To determine the kinetic parameters of rCsHK , the substrate ( ATP , CTP , GTP , ITP , TTP , UTP , or glucose ) concentrations were varied from 0 . 05 to 3 mM . Effectors such as AMP ( 0–5 mM ) , phosphoenolpyruvate ( PEP , 0–10 mM ) , and citrate ( 0–10 mM ) were added to the reaction mixture to investigate their effects on enzymatic activity of rCsHK , as was 2-phenyl-1 , 2-benzisoselenazol-3 ( 2H ) -one ( EbSe , a small molecular inhibitor , 0–100 μM ) . Note that EbSe was found to be ineffective in a counterscreen for inhibition of G6PD [23] . Purified rCsHK protein ( 2 μg ) or CsESPs ( 30 μg ) was subjected to 12% SDS-PAGE and then electrotransferred onto a polyvinylidene difluoride ( PVDF ) membrane ( Whatman , UK ) at 100 V for 60 min in a Trans-Blot transfer cell ( Bio-Rad , USA ) . The PVDF membranes were blocked with 5% ( w/v ) skimmed milk in phosphate buffer saline ( PBS , pH 7 . 4 ) overnight at 4°C and then probed with serum from C . sinensis infected humans/rats , healthy people , rCsHK immunized rats or pre-immune rats for 2 h at room temperature ( RT ) . All the sera were at the same dilution of 1:200 . After washing with PBS three times , the membranes were then incubated in horseradish peroxidase ( HRP ) -conjugated goat anti-human/rat IgG ( 1:2 , 000 dilution , Protein tech . , USA ) for 1 h at RT . Both the primary and secondary antibodies were diluted with 0 . 1% BSA in PBS ( pH 7 . 4 ) . After washing five times , the membranes were developed with diaminobenzidine ( DAB , Boster , China ) reagent according to the manufacturer’s instructions . Adult worms and metacercariae of C . sinensis and liver tissue from infected rats were fixed with formalin , embedded with paraffin wax and sliced into 4 μm-thick sections . The sections of adult worms and metacercariae were deparaffinized in xylene , hydrated in gradient alcohol and then blocked with normal goat serum for 2 h at RT . The sections were incubated in mouse anti-rCsHK serum ( 1:100 dilution ) previously obtained [17] in a humid chamber at 4°C overnight . Serum from a pre-immune mouse was employed as a negative control . After successively washing three times with PBS containing 0 . 05% Tween-20 ( PBST , pH 7 . 4 ) and two times with PBS , the sections were incubated with Cy3-conjugated goat anti-mouse IgG ( 1:400 dilution , Molecular Probe , USA ) for 1 h at RT in the dark . BSA ( 0 . 1% ) in PBS was employed as dilution buffer . The sections were subsequently imaged under a fluorescence microscope ( Leica , DMI3000B , Germany ) followed by washing . After being successively deparaffinized in xylene and hydrated in a series of ethanol , the sections of liver tissue from infected rats were blocked in 3% ( v/v ) H2O2 in PBS for 15 min to exhaust endogenous peroxidase . The sections were blocked with normal goat serum for 2 h at RT followed by antigen retrieval in 10 mM citrate buffer ( pH 9 . 6 ) at 95°C for 30 min using a water bath . The sections were incubated with mouse anti-rCsHK serum ( 1:100 dilution ) or serum from a pre-immune mouse . After washing , the sections were probed with HRP-conjugated goat anti-mouse IgG ( 1:400 dilution , Protein tech . , USA ) for 1 h at RT . The immunoreactive signal was developed by DAB reagent . At last , the sections were counterstained with Mayer’s hematoxylin , dehydrated , cleared in xylene and imaged under a light microscope ( Carl Zeiss , Germany ) . Microplates were coated with 2 μg/well purified rCsHK in coating buffer ( 0 . 1 M carbonate-bicarbonate , pH 9 . 6 ) and incubated at 4°C overnight . Subsequently , the plates were blocked with 5% skimmed milk in PBST for 2 h at 37°C . After washing , the wells were incubated with different dilutions of the immune serum ( 6 weeks after the first immunization ) raised by rCsHK . Serum from rats immunized with PBS was measured as a negative control . HRP-conjugated goat anti-rat IgG ( 1:20 , 000 dilution in 0 . 1% BSA-PBST , Protein tech . , USA ) was used as the secondary antibody . After incubation for 1 h and washing three times with PBST , the reactions were developed by adding 100 μl of substrate solution ( TMB , BD biosciences , San Diego , USA ) followed by 10 min in darkness . The absorbance was measured at 450 nm after adding 2 M H2SO4 to stop the reaction . The levels of total IgG and IgG isotype in serum collected at different time points ( 0 , 2 , 4 , 6 , 8 , 10 , 12 weeks after the first immunization ) were determined by the aforementioned process . The dilutions of the serum were 1:400 . HRP-conjugated goat anti-rat IgG ( 1:20 , 000 dilution ) /IgG1/IgG2a ( 1:10 , 000 dilution , Bethyl , Texas , USA ) were employed as secondary antibodies . Adult worms newly recovered from infected rats were washed three to four times with sterilized PBS with 1% antibiotics ( penicillin 100 μg/ml and streptomycin 100 U/ml ) . They were then transferred to 12-well plates with 20 adults per well and incubated in 2 ml of low glucose DMEM with 1% antibiotics . Serum from rCsHK immunized rats or pre-immune rats was added to the medium at dilutions of 1:160–1:40 . Low glucose DMEM was used as a blank control . The worms were monitored under a microscope ( Leica , Germany ) for 5 min , and intact alive worms were counted at 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 15 , 18 , 20 , 22 , 24 , 26 , and 28 days after the incubation . Worms with no muscle contraction or no pumping after 5 consecutive shots were considered to be dead [24] . Parasites incubated in medium with diluted rat anti-rCsHK serum for 1 , 3 , 5 , and 6 days were collected . The worms were suspended and then homogenized in RIPA lysis buffer ( containing 1 mM proteinase inhibitor PMSF , Bioteke , China ) . The supernatant was collected after centrifugation for 15 min at 10 , 000 × g at 4°C and the concentration of total protein was determined using a BCA protein assay kit ( Novagen , USA ) . The enzymatic activity of native CsHK in the samples was assayed as described above . The enzymatic activity of secreted phospholipase A2 from C . sinensis ( CsPLA2 ) was assayed as a control with the sPLA2 assay kit ( Cayman Chemical , USA ) according to the manufacturer’s instructions . Thirty-two 6-week-old SD rats were randomly divided into four equal groups: infection group , adjuvant group , PBS group , and rCsHK group . rCsHK ( 200 μg ) or an equivalent volume of PBS was emulsified with complete Freund’s adjuvant and subcutaneously injected into SD rats in the rCsHK group and PBS group . rCsHK ( 100 μg ) emulsified with incomplete Freund’s adjuvant was given for the next two boosters at 2-week intervals . An equivalent volume of adjuvant was injected subcutaneously into SD rats in the adjuvant group . After the measurement of antibody titers at week 6 post immunization , the rats ( n = 8 in each group ) were anesthetized with ether and intragastrically challenged with 80 live metacercariae of C . sinensis . The eggs per gram feces ( EPG ) was counted with a previous method [25] at 6 weeks after the infection . All rats were sacrificed at week 8 post infection to recover adult worms from their livers for worm burden evaluation . All rats were kept under the same conditions until sacrifice . EPG and worm burden were counted blindly . Reduction rates in parasite burden were calculated as follows . Worm reduction rate ( % ) = [ ( average worm burden of control group—average worm burden of experimental group ) / average worm burden of control group] × 100% . Egg reduction rate ( % ) = [ ( average EPG of control group—average EPG of experimental group ) / average EPG of control group] × 100% . All of the experiments were repeated at least three times in triplicate . SPSS version 13 . 0 software was used for statistical analysis . Student’s t test was used to analyze IgG isotypes and immune protective efficacy among the groups . The survival rates of cultured worms were determined using the Kaplan-Meier method , and differences between the groups were identified through log-rank analysis . The results are presented as mean ± SD , and p < 0 . 05 was classified as statistically significant .
CsHK is composed of a large domain ( green ) and a small domain ( light green ) . The two domains are linked by connecting regions I-III ( light green ) . In closed-form CsHK , the α 13 helix is included in the small domain . The lengths and amino acid residues of α 13 helix ( magenta and light green ) and connecting region I ( brown and light green ) of CsHK are different from those of hHK-IV and rHK-In ( Fig . 1A-1B ) . The allosteric sites in closed-form hHK-IV are ARG63 , MET210 , TYR214 , TYR215 , VAL452 , VAL455 , and ALA456 . In CsHK , the corresponding sites are SER59 , LEU202 , ALA206 , LEU207 , ILE443 , ALA446 , and SER447 ( Fig . 1C ) . As for G6P binding sites of rHK-In , SER88 , ARG174 , and THR449 are replaced by THR78 , GLY163 , and SER436 in CsHK ( Fig . 1D ) . rCsHK catalyzed the phosphorylation of a series of hexoses at the following relative velocity ( Table 1 ) : D ( + ) -glucose ( 100% ) congruent to D ( + ) -mannose ( 97 . 13% ) greater than D ( - ) -fructose ( 16 . 60% ) greater than D ( + ) -galactose ( 0 . 23% ) . With respect to phosphate donors , rCsHK could use ATP , CTP , GTP , ITP , TTP , and UTP , and rCsHK was less specific for ATP . Very little or no dephosphorylating activity was found for ADP , AMP , and inorganic pyrophosphate ( PPi ) . ATP was able to be replaced by other nucleotides with moderate relative velocity . ATP , GTP , ITP and TTP homotropically and allosterically activated the enzyme ( Hill coefficients , h > 1 ) , whereas CTP homotropically and allosterically inhibited the enzyme ( h < 1 ) . UTP has no allosteric effect on the enzyme ( h = 1 ) ( Fig . 2A , S2 Table ) . rCsHK was inhibited by high concentrations of ATP . At physiological concentration ( 5 mM ) [14 , 26] , ATP showed 8% inhibition of rCsHK , whereas other nucleotides showed no inhibition of rCsHK . ATP , CTP , and TTP showed 13 . 8 , 8 . 6 , and 14 . 3% inhibition of rCsHK at 10 mM concentration , respectively , whereas other nucleotides showed no inhibition of rCsHK . AMP exhibited a mixed allosteric K+V+ effect [27] on rCsHK by decreasing its K0 . 5 and increasing Vmax with respect to ATP ( Fig . 2B , S2 Table ) . PEP displayed allosteric activation of rCsHK with respect to ATP with mixed K+V+ allosteric effects in a dose-independent manner ( Fig . 2C , S2 Table ) . Citrate exhibited an unusual mixed allosteric effect on rCsHK with respect to ATP . At 5 mM and 10 mM citrate behaved as a mixed K+V+ activator , whereas at 2 mM citrate behaved as a V activator and a K inhibitor ( antiergistic or crossed mixed K−V+ effect ) [28] ( Fig . 2D , S2 Table ) . Under these conditions , V activation contributed less to the effective reaction rate compared to K inhibition . The resulting effect was a net inhibition by 2 mM citrate with a reduction of h from 1 . 935 ± 0 . 271 to 1 . 267 ± 0 . 242 . At 0 . 5 μM EbSe behaved as a mixed K+V+ allosteric activator of rCsHK with respect to ATP and glucose , whereas at 5 μM , 25 μM or 100 μM EbSe displayed net allosteric inhibition of rCsHK with mixed K−V+ effects with respect to ATP and glucose in a dose-independent manner ( Fig . 2E-2F , S2 Table ) . rCsHK was not inhibited by 2 mM of D-fructose 6-phosphate or D-fructose 1 , 6-diphosphate . Purified rCsHK was probed with serum from C . sinensis infected humans/rats and rat anti-CsESPs serum yielding a cross-reactive band of approximately 54 . 8 kDa ( including molecular mass of a His-tag ) [17] , but it was not recognized by serum from healthy people or from a pre-immune rat . In addition , CsESPs blotted with rat anti-rCsHK serum , but not with serum from a pre-immune rat , yielded a band at approximately 50 . 0 kDa ( Fig . 3 ) . In adult worms ( Fig . 4 ) , strong fluorescence of CsHK was detected in the vitellarium , tegument , intestine , spermatheca , testicle , pharynx , uterus and egg in uterus , but not in the negative control . In metacercariae , strong fluorescence was distributed in the tegument and vitellarium . In slides of liver from infected rats incubated with mouse anti-rCsHK serum , strong fluorescence was detected in the vitellarium , tegument , intestine , spermatheca , testicle , ovary , ventral sucker , uterus and egg in uterus of the worms inside the bile duct . In addition , specific fluorescence was also observed in the intrahepatic biliary epithelium and lumen of the biliary tract near the parasites . No specific fluorescence was detected in the negative control incubated with serum from a pre-immune mouse . In slides of infected liver developed for color by DAB reagent , specific brown staining was detected in the intrahepatic bile ducts with adenomatoid hyperplasia , but it was not observed in the negative control incubated with serum from a pre-immune mouse or in liver slides from normal rats incubated with mouse anti-rCsHK serum . The titer of anti-rCsHK IgG was up to 1:409 , 600 at 6 weeks after the immunization , showing the high immunogenicity of rCsHK ( Fig . 5A ) . In serum from rCsHK immunized rats , IgG1 and IgG2a levels increased at 2 weeks and reached their peak at 6 and 8 weeks , respectively . From 2 to 8 weeks , the IgG1 level was statistically higher than IgG2a , but it was lower at 10 and 12 weeks ( Fig . 5B ) . The median survival time of C . sinensis adults in the blank control group , 1:40 pre-immune serum group , 1:80 pre-immune serum group , 1:160 pre-immune serum group , 1:40 anti-rCsHK serum group , 1:80 anti-rCsHK serum group , and 1:160 anti-rCsHK serum group was 15 , 8 , 8 , 9 , 2 , 3 , and 3 days , respectively ( Fig . 6A ) . There was no significant difference in survival rate among the pre-immune serum groups at any dilution ( p > 0 . 05 ) . Significant differences were observed in the survival rates among all other groups ( p < 0 . 05 ) . The enzymatic activity of CsHK in adult worms incubated in medium with different dilutions of anti-rCsHK serum declined significantly in a dose- and time-dependent manner ( Fig . 6B ) . As a control , there was no obvious change in the enzymatic activity of CsPLA2 in the worms ( Fig . 6C ) . The number of worms recovered in the PBS group , infection group , adjuvant group , and rCsHK group was 25 . 1 ± 4 . 8 , 26 . 1 ± 5 . 1 , 24 . 8 ± 5 . 3 , and 12 . 5 ± 2 . 4 , respectively . The EPG values in the four groups were 3983 . 3 ± 386 . 7 , 3895 . 8 ± 424 . 1 , 4075 . 0 ± 473 . 0 , and 1991 . 7 ± 245 . 4 , respectively ( Table 2 ) . The worm burden and EPG were significantly lower in the rCsHK group compared to the control groups ( p < 0 . 01 ) . The worm reduction rate and egg reduction rate were 50 . 20% and 50 . 00% , respectively . There was no significant difference in worm burden or EPG among the infection , adjuvant , and PBS groups .
In the current study , we identified differences in spatial structure between CsHK and HKs from the definitive hosts of C . sinensis , humans and rats . We also characterized the substrate specificity and allosteric regulation of rCsHK in detail . The distribution of CsHK in worms and in liver tissue and serum from C . sinensis infected rats was confirmed . Furthermore , a high-level specific antibody was induced in rats by immunization with rCsHK . The enzymatic activity of CsHK was suppressed by the antibody in vitro . Additionally , the survival of C . sinensis was inhibited by the antibody in vivo and in vitro . The length and amino acid composition of the α 13 helix and of connecting region I were found to differ among CsHK , hHK-IV and rHK-In . ATP-binding sites , allosteric sites , G6P binding sites and B-cell epitopes are included in these regions [17 , 20 , 29] . Taken together , these data suggest that the subtle structural differences between CsHK and HKs from definitive hosts of C . sinensis , humans and rats , may result in remarkable changes in their enzymatic behavior . The 100-kDa HK-I , HK-II , and HK-III of mammalian hosts have high affinity for glucose ( Km = 7–200 μM ) and are strongly inhibited by G6P . The 50-kDa HK-IV , also called glucokinase , has low affinity for glucose ( Km = 5–12 mM ) and is not regulated by G6P [30–32] . HK-IV , which phosphorylates glucose in liver and pancreatic islets , plays a critical role as a glucose-sensing device due to its specific regulatory properties , mainly low affinity for glucose , a sigmoidal saturation curve for this substrate , and a lack of inhibition by G6P [33–36] . Our present and previous studies [17] confirmed that rCsHK is a 50-kDa G6P-sensitive allosterically modulated HK , sharing some characteristics with HKs from mammals . Vertebrate HKs , including HK-IV , typically act on mannose , fructose and 2-deoxyglucose as well as glucose , the preferred substrate . In the rat , the four isoenzymes have essentially the same relative specificity for glucose and fructose [37] . Our results demonstrated that rCsHK could use glucose , fructose , and mannose as substrates , although it preferred to use glucose and mannose . Galactose was a much poorer substrate than glucose , mannose , or fructose , in accordance with observations of HK from Toxoplasma gondii ( TgHK , a 50-kDa HK ) [22] . Similarly to TgHK [22] , the kcat values of rCsHK for glucose ( 4 . 639 ± 0 . 174 ) and ATP ( 4 . 113 ± 0 . 076 ) were almost the same . This suggests that consumption of glucose and ATP are stoichiometrically even . However , TgHK is not an allosteric enzyme [22] . Eukaryotic HKs prefer ATP as the nucleotide substrate , and TgHK is no exception . rCsHK showed less specificity and other nucleotides were relatively good substrates . For example , rCsHK had K0 . 5 values of 0 . 315 ± 0 . 026 mM for ATP and 1 . 335 ± 0 . 253 mM for ITP with similar Vmax values . ITP yielded 35 . 28% velocity relative to ATP . As for TgHK , ITP yields 2 . 6% velocity relative to ATP [22] . By contrast , rat HK-IV , despite its much broader sugar specificity , has Km 24-fold higher and Vmax 8-fold lower for ITP than for ATP [38] . With the other isoenzymes ITP also appears to be a poor substrate [32] . When ATP , the normal phosphate donor for rat HK-IV , is replaced by ITP , the positive cooperativity with respect to glucose disappears [38] . However , both ATP ( h = 1 . 935 ± 0 . 271 ) and ITP ( h = 1 . 191 ± 0 . 109 ) homotropically and allosterically activated rCsHK . Fructose 6-phosphate , which is an inhibitor of yeast HK [39] , does not affect the enzymatic activity of rCsHK or TgHK [22] . AMP exhibited a mixed allosteric K+V+ effect on rCsHK by decreasing its K0 . 5 and increasing Vmax with respect to ATP . AMP at 2 mM reduced the Vmax value of TgHK by 15%; however , no change in the Km value of TgHK for either glucose or ATP was observed [22] . Glycolysis is essential to C . sinensis , suggesting that enzymes involved in the pathway could be targets for drug and vaccine development [10 , 40] . EbSe was identified in a screen as a potent inhibitor of Trypanosoma brucei HK1 ( TbHK1 ) and Plasmodium falciparum HK ( PfHK ) by interrogating a selected small-molecule library of HK inhibitors [41 , 42] . EbSe can promiscuously modify cysteine residues , and this nonspecific interaction is known to be the mechanism of its inhibition of some enzymes such as human indoleamine 2 , 3-dioxygenase [43] . However , site-directed mutagenesis of cysteines in TbHK1 and PfHK did not alter their sensitivity to EbSe inhibition , indicating that either cysteine residues are not involved in EbSe inhibition or multiple cysteines must be bound in order for inhibition to occur [41 , 42] . CsHK shares limited sequence identity with TbHK1 ( 36% ) and PfHK ( 31% ) . At 0 . 5 μM , 2 μM and 5 μM EbSe acts as a mixed inhibitor of TbHK1 with respect to ATP [41] . However , at 0 . 5 μM EbSe behaved as a mixed K+V+ allosteric activator of rCsHK with respect to ATP and glucose . At 5 μM , 25 μM or 100 μM EbSe displayed net allosteric inhibition of rCsHK with mixed K−V+ effects with respect to ATP and glucose in a dose-independent manner . The results suggest that EbSe interacts with the two enzymes differently . EbSe has no effect on mammalian cells [41] , suggesting that it may hold promise for the development of new anti-clonorchiasis compounds . Comparison of the putative spatial structure between CsHK and its human and rat counterparts supports possible explanations for the significant differences in the enzymes' allosteric behavior observed in the presence of the effectors and the small molecular inhibitor , which could be exploited in drug design . rCsHK was recognized by rat anti-rCsHK serum in western blotting , showing the immunoreactivity of rCsHK . rCsHK recognition by serum from C . sinensis infected humans/rats suggests that CsHK might be a component of circulating antigens from C . sinensis [44 , 45] . In addition , CsESPs were blotted with rat anti-rCsHK serum , yielding a band at approximately 50 kDa . Moreover , rCsHK could be recognized by rat anti-rCsESPs serum . In liver tissue from C . sinensis infected rats , immunofluorescence and immunohistochemistry showed that CsHK was distributed in the intrahepatic biliary epithelium and lumen of the biliary tract near the parasites . These results indicated that CsHK was also an ingredient of CsESPs . In adult slides , CsHK was extensively distributed . The locations included tegument , intestine and pharynx , where ESPs usually discharge from . The wide distribution hints that as a key enzyme involved in glycolysis , CsHK is important for the worm . CsHK was observed to be expressed in the tegument . The trematode tegument is a dynamic organ involved in host-parasite interactions in addition to participating in nutrition , immune evasion and modulation , excretion , osmoregulation and signal transduction [46] . The presence of CsHK in CsESPs was probably due to renewal and shedding of the tegument [47] . In trematodes , the intestine is not only a major source of secretory proteins but also a place for nutritive digestion and absorption [48] . Coupled with its localization in the tegument as a feeding structure , CsHK might participate in the absorption and digestion of glucose from the host for energy supply . Moreover , the distribution of CsHK in muscular tissues such as the ventral sucker and pharynx might be associated with the energy requirement for muscle contraction and adhesion behavior . Its distribution in reproductive organs such as the vitellarium , testis , spermatheca , ovary , and uterus suggests that continuous catalytic activity of CsHK for glucose metabolism might take place in these organs to meet the energy demands for growth and reproduction of the parasite . The trematode vitellarium plays a key role in egg production by supplying eggshell material , relevant enzymatic activity and nutrients to the fertilized ovum [49] . The localization of CsHK in eggs is consistent with the highest mRNA and protein levels of CsHK occurring in the egg life stage [17] . It has been speculated that CsHK plays a crucial role in maintaining glucose metabolism for the development of eggs and formation of the eggshell . The distribution of CsHK in liver tissue from C . sinensis infected rats demonstrated the abundant excretory expression profile of CsHK in intrahepatic bile ducts of the host . This suggests that CsHK might mediate direct interactions with host cells as a component of CsESPs , and it may derive from the excoriation of parasites and excretion through the intestine or glands [4] when C . sinensis inhabits the host . The localization of CsHK on bile duct epithelial cells close to the resident worms and the surface of hyperplastic adenoma suggests that CsHK might be internalized , taken up and/or translocated from the parasite by host cells . The rapid increase of specific antibody and titers up to 1:409 , 600 at 6 weeks after immunization with rCsHK by ELISA shows the strong immunogenicity of rCsHK . Bioinformatics tools indicate an abundance of putative B-cell and T-cell epitopes in CsHK [17] . The high levels of specific antibody elicited by rCsHK might result from its multiple B-cell epitopes . In serum from rCsHK immunized rats , IgG1 and IgG2a levels increased . It is well known that IgG2a and IgG1 are , respectively , induced by T helper cells ( Th ) 1 and Th2 . Our results suggest that rCsHK induced a combined Th1/Th2 immune response . During long-term C . sinensis infections , there is a Th1 to Th2 shift , resulting in chronic liver fluke disease and long-term survival of the worm [50] . In rCsHK immunized rats , the levels of IgG1 were statistically higher than those of IgG2a from 2 to 8 weeks , but lower at 10 and 12 weeks . The rats were challenged 6 weeks after the first immunization . The worm burden and EPG in the rCsHK immunized group significantly decreased compared to the control groups at 12 weeks after the first immunization . The role of Th1 cells is to orchestrate protective proinflammatory immune responses [51] . It has been documented that protected animals elicit high levels of both IgG1 and IgG2 antibodies , whereas the magnitude of these are 10-and 100-fold lower in non-protected animals . Protection is tightly correlated with the level and avidity of the IgG2 antibodies induced [52–54] . Moreover , for successful vaccination against most bacterial and viral diseases , an efficient Th1 response is required [55] . The decrease of worm burden and EPG in the rCsHK immunized group might be related to the up-regulated immune responses , especially Th1 , evoked by rCsHK at 10 weeks post immunization . The survival rates of C . sinensis adults incubated in medium with different concentrations of rat anti-rCsHK serum statistically decreased compared to those of worms incubated in medium with pre-immune serum . The enzymatic activity of CsHK in adult worms incubated in medium with different dilutions of anti-rCsHK serum declined significantly in a dose- and time-dependent manner . The inhibition of CsHK enzymatic activity by anti-rCsHK serum might contribute to the decrease of worm burden and EPG in the rCsHK immunized group . Collectively , we confirmed that differences exist in spatial structure and affinity for hexoses and phosphate donors between CsHK and HKs from humans or rats , the definitive hosts of C . sinensis . We found that effectors ( AMP , PEP , and citrate ) and a small molecular inhibitor regulate the enzymatic activity of rCsHK with various allosteric systems . CsHK was found to be extensively distributed in adult worms . It was confirmed to be a component of ESPs . rCsHK showed relatively good immunogenicity and immunoreactivity . Subcutaneous immunization with rCsHK decreased worm burden and EPG in challenged rats , which might be related to the up-regulated immune responses , especially Th1 , evoked by rCsHK and to the inhibition of CsHK enzymatic activity by anti-rCsHK serum . Our study showed that CsHK has vaccine potential and is a promising drug target for Clonorchiasis , making it worthy of further investigation . | Clonorchiasis , caused by Clonorchis sinensis ( C . sinensis ) infection , is a kind of neglected tropical disease . There are still few effective measures to prevent clonorchiasis . As in other helminthes , hexokinase ( HK ) has been well characterized as a target for vaccine and drug development . In the current study , we identified differences in spatial structure between CsHK and HKs from the definitive C . sinensis hosts , humans and rats . We also characterized the substrate specificity and allosteric regulation of rCsHK in detail . The distribution of CsHK in the worm and in the liver tissue and serum from C . sinensis infected rats were confirmed . Furthermore , a high-level specific antibody in rat was induced by immunization with rCsHK . The enzymatic activity of CsHK was suppressed by the antibody in vitro . Additionally , the survival of C . sinensis was inhibited by the antibody in vivo and in vitro . Our study shows that CsHK has vaccine potential and is a promising drug target for Clonorchiasis . | [
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] | [] | 2015 | Advanced Enzymology, Expression Profile and Immune Response of Clonorchis sinensis Hexokinase Show Its Application Potential for Prevention and Control of Clonorchiasis |
The human gut microbiota is impacted by host nutrition and health status and therefore represents a potentially adaptive phenotype influenced by metabolic and immune constraints . Previous studies contrasting rural populations in developing countries to urban industrialized ones have shown that industrialization is strongly correlated with patterns in human gut microbiota; however , we know little about the relative contribution of factors such as climate , diet , medicine , hygiene practices , host genetics , and parasitism . Here , we focus on fine-scale comparisons of African rural populations in order to ( i ) contrast the gut microbiota of populations inhabiting similar environments but having different traditional subsistence modes and either shared or distinct genetic ancestry , and ( ii ) examine the relationship between gut parasites and bacterial communities . Characterizing the fecal microbiota of Pygmy hunter-gatherers as well as Bantu individuals from both farming and fishing populations in Southwest Cameroon , we found that the gut parasite Entamoeba is significantly correlated with microbiome composition and diversity . We show that across populations , colonization by this protozoa can be predicted with 79% accuracy based on the composition of an individual's gut microbiota , and that several of the taxa most important for distinguishing Entamoeba absence or presence are signature taxa for autoimmune disorders . We also found gut communities to vary significantly with subsistence mode , notably with some taxa previously shown to be enriched in other hunter-gatherers groups ( in Tanzania and Peru ) also discriminating hunter-gatherers from neighboring farming or fishing populations in Cameroon .
Humans and gut microbiota , the community of microorganisms inhabiting the gastrointestinal tract , have evolved in close association with each other for millions of years . As a result , humans depend on these microbes for acquisition of key nutrients from food , shaping the immune system , and providing protection from opportunistic pathogens [1–3] . Despite considerable plasticity in the structure and composition of an individual’s gut microbiota [4] , significant correlations between characteristics of the microbiome and host genotype [5–8] , exposure to maternal microbiota [9] , and patterns of disease [10 , 11] suggest that the human microbiome represents a potentially adaptive phenotype with important implications for human health . Since the Neolithic revolution about 12 , 000 years ago , human populations have started to diversify their dietary regimes , resulting in the contrasted subsistence modes known today . This major cultural transition has created metabolic constraints as well as novel pressures by pathogens due to the proximity of livestock and the increased density of populations . Such cultural and environmental differences among populations have resulted in physiological adaptations that can be detected in our genome [12–14] and have likely affected the community dynamics of our gut microbial ecosystem . Dietary changes have been shown to facilitate rapid changes in gut microbiota [4]; however , the roles of habituation ( over a lifetime ) versus host adaptation ( across generations ) in these broader patterns are unclear . Understanding the long-term interaction that took place between the dietary specialization of populations and their gut microbiomes is therefore of great interest , notably to understand and predict the effect of recent and rapid changes in lifestyle and food on human health . Nevertheless , to date , microbiome studies have mostly focused on industrialized populations . Of the few studies that have included a more diverse array of populations , most have contrasted urban populations in highly industrialized countries to populations in developing countries [15–19] , or populations having both contrasted diet and occupying distinct climates [20 , 21] . Such designs do not allow the respective influences of the many factors coupled to geography such as diet , climate , hygiene , parasitism , and host genetics on microbiome variation to be disentangled . While some specific changes in microbial communities have been linked to components of human dietary regimes [4 , 19 , 22] , urbanization levels [23 , 24] , hygiene practices [15] , and the use of antibiotics [23 , 25] , the effect of other environmental or host-related factors is not clear . Notably , we do not know the extent to which the observed loss of microbial diversity of the human gut microbiome in urban industrialized populations [15–18 , 20 , 23] is attributable to their dietary specialization , differences in pathogen/parasite exposure , or other environmental factors [26] . This loss of microbial biodiversity is a public health concern , as it may reflect a perturbed ecosystem associated with multiple diseases [27 , 28] . In addition to the loss of microbial diversity , developed countries nearly ubiquitously present a marked decrease in the prevalence of human gut parasites [29] . Although it is estimated that 3 . 5 billion people worldwide are infected with some parasite ( protozoan or helminth ) [30] , studies assessing their role in shaping gut microbiota are limited [31] . Yet throughout evolution , gut microbes and gut-dwelling parasites have co-inhabited the human gastrointestinal tract [32] , and community dynamics are likely determined by current and past interactions ( both during an individual’s lifespan and throughout evolutionary history ) between microbiota , protozoa , helminths , and the host immune response [33] . For example , it has been shown that direct competition by commensal microbes can provide protection from invading pathogens , and a disturbance to the natural microbiota can effectively result in increased susceptibility to pathogens and/or parasites [34 , 35] . There is also substantial evidence that these interactions are essential for the development of a healthy immune system , and that the underlying cause of the increased incidence of autoimmune disorders in industrialized countries is the absence of exposure to pathogens and parasites early in life ( the “hygiene hypothesis” ) [36 , 37] . In this context , it is important to evaluate the potential role of protozoa and helminths in shaping gut microbiota composition and structure . Here , we focus on fine-scale comparisons of African rural populations with contrasting modes of subsistence but similar local environment and urbanization levels , and either shared or distinct genetic ancestry . Our objective is to better understand the relative influence of diet , host genetics , and parasitism on human gut microbiota composition and structure . We focus on populations from Cameroon for which a diversity of subsistence modes coexist in a restricted geographical area and a shared ecosystem ( i . e . , the tropical rainforest ) . We include individuals from hunter-gatherer populations ( which are referred to in this manuscript as Pygmy to distinguish their genetic ancestry ) , Bantu farming populations and Bantu fishing populations , all living in a rural environment . These populations are almost entirely self-sufficient in food; their primary source of energy comes from cassava ( Manihot esculenta ) , and fish or meat provides the main source of protein . Animal food production for these populations has been estimated to be high compared to elsewhere in Cameroon or Africa [38] . To account for recent changes in diet , we evaluated current dietary regimes using dietary surveys . We also assessed parasitism status by direct observations of fecal samples under the microscope . The focus on populations living in the tropical rainforest is complementary to previous African populations sampled: the Hadza hunter-gatherers and a population from Burkina Faso , living in the East and West African tropical savanna , respectively [15 , 18] and a population from Malawi living in a relatively dry subtropical area of East Africa [16] . Here , in addition to comparing the gut microbiota of human populations with limited geographic separation and contrasting subsistence modes , we aimed to characterize the relationship between gut microbial communities and various intestinal parasites .
We analyzed 64 individuals in seven different villages in Southwest Cameroon , corresponding to 20 hunter-gatherers , 24 farmers , and 20 individuals from a fishing population ( see Fig 1 and S1 Table ) . The average age of study participants ranges between 26 and 78 years , with an average age of 50 years . The Pygmy hunter-gatherers diverged from the other Bantu populations about 60 , 000 years ago [39 , 40] and the farming subsistence mode likely started over the last 5 , 000 years [41] . The sampled populations therefore not only have contrasted subsistence modes , but also have different genetic backgrounds . We chose these populations because previous work done in 1984–1985 , based on nutritional questionnaires and isotopes analyses , showed they had distinct diets [38 , 42] . We performed new nutritional frequency surveys to assess how diet had changed during the past 30 years ( see S1 Table ) . Interestingly , the amount of meat in the hunter-gatherers’ diet has substantially decreased , reflecting the lower abundance of wild game in the forest reserve and the hunting ban applied for some species . In contrast , the consumption of fish has increased in inland populations ( especially in farmers ) , due to the construction of new roads connecting the coastal and inland populations . Similar to the results from 1984–1985 , the farmers eat less starchy foods ( cassava ) than hunter-gatherers and individuals from the fishing population ( p = 0 . 005 and 0 . 017 , respectively; Mann-Whitney U test ) . A principal component analysis on all dietary components revealed roughly three clusters corresponding to the three dietary regimes , with the first axis distinguishing hunter-gatherers from the others , and the second axis separating the farming and fishing populations ( see Fig 1b ) . The one exception to this pattern concerns the farmers from the North ( living along the same road as the hunter-gatherers ) , who cluster with the hunter-gatherers . Based on a permutation test ( 10 , 000 permutations ) , the Euclidean distance between the hunter-gatherers ( grouped with the North farmers ) and the South farmers and fishers , respectively , is significant ( p < 0 . 0001 in both cases ) , whereas between South farmers and fishers it is not ( p = 0 . 3 ) . Therefore , in our analyses of subsistence we consider the North and South farmer populations separately . In addition to dietary questionnaires , we assessed the nutritional status of individuals by measuring their BMI ( Body Mass Index ) ( see S1 Table ) . Twenty percent of the Pygmy hunter-gatherers were underweight ( BMI < 18 ) whereas 12% , 0% , and 4% of the South farmers , North farmers , and individuals from the fishing population were , respectively . Conversely , 0% of hunter-gatherers were overweight ( BMI > 25 ) while 12% , 14% and 26% of individuals in the other groups were , respectively . This likely reflects the difference in socio-economical status and access to medicine between these populations . Subsistence ( as defined by the four following groups: hunter-gatherers , farmers from the North , from the South and fishers ) was significantly correlated with BMI in a linear regression model ( p = 0 . 026 ) , but not using a Pearson Chi-square test ( p = 0 . 25 ) . We assessed the intestinal parasitism of individuals by direct observation of their fecal samples under the microscope and detected the presence of Entamoeba cysts , as well as eggs of Ascaris , Trichuris , and Ancylostoma ( see S1 Table and S1 Fig ) . Overall , 89% of hunter-gatherers , 76% of farmers from the South , 100% of farmers from the North , and 58% of individuals from the fishing population were infected by at least one of these organisms . Regarding Entamoeba , 37% , 41% , 57% and 16% of individuals were infected in each population , respectively . Although the presence of Entamoeba was not significantly correlated with subsistence ( p = 0 . 18; linear regression model ) , the reduced rate of parasitism in the fishing population most likely reflects their higher level of hygiene and increased access to medicine . However , further studies are needed to examine the effects of medication on parasitism in these populations . Based on Pearson’s Chi-squared tests , we found that there were no statistically significant relationships between Entamoeba and any of the covariates tested ( including sex , age , BMI , subsistence , genetic ancestry , location , or dietary components; p > 0 . 1 ) . However , a linear regression analysis found a correlation between Entamoeba and age ( p = 0 . 019 ) , but not with the other factors ( S10 Fig ) . The fecal microbiota of 69 samples ( including 5 biological replicates ) were characterized by sequencing of the V5–V6 region of the bacterial 16S ribosomal RNA with the Illumina MiSeq technology . The dataset was rarefied to 50 , 000 reads/sample ( see S2 Fig ) , and reads were clustered into 5039 operational taxonomic units ( OTU ) at 97% identity . The five biological replicates ( sampling of the same individual few days apart , see S1 Table ) allowed us to compare the microbial differences within individuals to those between individuals . We assessed differences in gut communities by calculating UniFrac distances , a phylogenetic based distance metric , which when weighted , accounts for relative abundance of taxa [43] . Because both weighted and unweighted metrics capture different aspects of microbial diversity [43] , we included both types of analyses in the manuscript . We found that the average UniFrac distance between replicates of the same individual was lower than between individuals ( although only statistically significant for the unweighted distances: p = 0 . 003; one-sided Mann-Whitney U test; see S3 Fig ) . We used PERMANOVA analysis to separately test for associations between microbiome composition ( OTU abundances ) and age , sex , BMI , parasitism , location , subsistence , and ancestry , the latter three being nested ( see S2 Table ) . We found that the presence of Entamoeba , location , subsistence , and ancestry were each significantly associated with variation in microbiome composition ( p = 0 . 0001 , 0 . 01 , 0 . 003 and 0 . 01 , respectively; S2 Table ) , whereas the other factors were not . To further characterize patterns of variation that account for phylogenetic relationships of community taxa , we also performed a PERMANOVA analysis on both weighted and unweighted UniFrac distance matrices . Congruent with our previous results , we found that the presence of Entamoeba was the most significant variable for both weighted and unweighted UniFrac distances ( p = 0 . 007 and 0 . 0001 , respectively; S2 Table ) . Entamoeba infection also provided the strongest separation along the primary axis of variation of the multidimensional scaling plots ( Fig 2a and S4a Fig ) . Subsistence and location were both determined to be significant based on unweighted UniFrac distances ( p = 0 . 0003 and p = 0 . 002 , respectively ) , but not weighted ( p = 0 . 14 and p = 0 . 29 , respectively ) . Because unweighted UniFrac distances assign increased weight to rare taxa , this suggests that less abundant taxa are more important in describing differences between the microbiomes across subsistence modes and locations . Furthermore , subsistence provided only weak visual separation along the first two axes of variation for both metrics ( S4b and S4c Fig ) . Because of the significant relationship between the presence of Entamoeba with patterns in variation in the gut microbial communities found in all populations , we further investigated the relationship between its presence and microbiota composition ( Fig 2 ) . As it is difficult to distinguish between the opportunistic pathogenic species ( E . histolytica ) and the strict commensal ( E . dispar ) by microscopy alone , we were unable to characterize this organism at the species level . However , only two of the sampled individuals self-reported to be suffering from diarrhea ( one positive with Entamoeba , the other negative ) , suggesting that individuals with Entamoeba were not experiencing symptomatic amoebiasis . Previous studies showed that when both species are common in a population , there is a higher prevalence of E . dispar than E . histolytica and the majority of infections by E . histolytica are asymptomatic [44] . We first verified that the presence of Entamoeba was significantly associated with the gut microbiome including age , sex , BMI , and subsistence , ancestry , or location as covariates ( p = 0 . 0005 , p = 0 . 0003 , and p = 0 . 0001 , respectively; PERMANOVA for unmerged OTUs ) . At the phylum level , we found that 7 of the 13 phyla represented are significantly different between individuals that harbored Entamoeba and those that did not ( Ent+ and Ent- , respectively ) , with most phyla ( except Bacteroidetes ) occurring at a higher relative abundance in Ent+ individuals ( see Table 1 ) . When looking at individual taxa , based on an ANOVA , we also identified a number of notable differences between Ent+ and Ent- individuals ( Fig 2b and 2c , S3 and S4 Tables ) , and we found that eighteen of the 93 most abundant taxa ( present at ≥ 0 . 1% in at least 4 individuals ) differed significantly in their relative abundance between Ent+ and Ent- individuals ( FDR q < 0 . 05 , after Benjamini-Hochberg correction for the number of taxa analyzed [45] ) . To ensure that these relationships were not due to other factors , we included age , sex , BMI , and either subsistence , location , or ancestry as covariates in the model and found that although the q-values changed slightly , all were still significant ( q < 0 . 05 ) . These taxonomic signatures for Entamoeba status are so strong that its presence can be predicted with 79% accuracy using a Random Forest Classifier ( RFC ) model based on gut microbiome composition ( p < 0 . 001; See Methods section S5 Fig ) . Of the ten taxa identified as being the most important in their predictive power , all but Prevotella stercorea were significant in our ANOVA model ( of which all are in higher abundance in Ent+ individuals except Prevotella copri ) . The reason for the association between Entamoeba and these microbes have yet to be identified , but it is noteworthy that the two most important taxa identified in the RFC model , Elusimicrobiaceae unclassified ( uncl ) and Ruminococcaceae uncl , include established endosymbionts of protists and common inhabitants of the termite gut [46] . Furthermore , Ruminococcaceae uncl was shown to be enriched in Hadza as compared to Italians [18] . Spirochaetaceae Treponema , the third most important taxon , include species that have been reported to inhabit the cow rumen , the pig gastrointestinal tract , and the guts of termites [47] and have been proposed as symbionts in the human “ancestral microbiome” [18 , 20 , 48] . Christensenellaceae , the fourth most important taxon , was recently identified as being the most heritable taxon in an analysis of twins from the UK , and was shown to impact host metabolism [5] . Two taxa in the order Bacteroidales , Prevotella stercorea and Prevotella copri , the seventh and eighth most important taxa , are the only ones occurring at significantly reduced abundance in infected individuals; Prevotella is an important genus of gut bacteria and is systematically underrepresented in Western microbiomes [15–18 , 20 , 26] . While members of the Clostridia and Gammaproteobacteria are more abundant in infected individuals , the pattern for Bacteroidales is the opposite ( see Fig 2b ) . Oscillospira uncl and Parabacteroides uncl , the ninth and tenth most important taxa , are associated with the rumen and human intestine , respectively . Furthermore , when looking at the microbial diversity of Ent+ versus Ent- individuals , we found that the presence of Entamoeba is associated with a significant increase in alpha ( intra-host ) diversity using the Phylogenetic Distance Whole Tree metric ( p = 1 . 03E-06; Welch’s t-test; Fig 3a ) , as well as using the Shannon and Simpson indices ( p = 0 . 001 and p = 0 . 025 , respectively; Welch’s t-test; S6 Fig ) . Interestingly , although the alpha ( intra-host ) diversity of Ent+ individuals is significantly higher than Ent- individuals , the beta ( inter-host ) diversity ( as estimated by both UniFrac distance metrics ) reveals that gut communities across Ent+ individuals are more similar than across Ent- individuals ( weighted and unweighted , p = 2 . 23E-06 and p < 2 . 2E-16; Welch’s t-test; Fig 3b and S7 Fig ) . This could suggest that , as alpha diversity increases , there are fewer potential stable states for individual gut communities , or that the presence of Entamoeba drives changes in the microbiome ( directly or indirectly through effects on the immune system ) that are dominant over other factors .
The importance of gastrointestinal parasites in human disease is well established , both as infectious agents and in shaping immunity [30 , 32 , 54] . This relationship is the basis of the hypothesis that the underlying cause of the high incidence of autoimmune diseases , unique to industrialized countries , is the absence of childhood exposure to infectious agents [36] . Recent research supporting this hypothesis shows that mild and controlled infection by internal parasites can activate an immune response and reduce symptoms of a range of autoimmune diseases [55] . Likewise , the relationship between gastrointestinal microbiota and host immune response has been well established [56–58] . Despite evidence for direct host-parasite and host-microbiome interactions , and the fact that gut parasites and microbes share the same gut environment , studies are limited which assess the relationship between these organisms [31] . Here we show significant correlations between gut microbiota ( composition and diversity ) and the presence of the intestinal amoeba Entamoeba ( dispar , histolytica , or both ) . Notably , individuals harboring these protozoa exhibit significantly higher alpha diversity in their bacterial gut communities , coupled with a significant reduction in inter-individual variation . This pattern could be a reflection of either direct or indirect interactions between Entamoeba , gut bacteria , and/or host immune factors . For example , Entamoeba could feed on certain species of bacteria , allowing others to proliferate or induce a host immune response that differentially affects the success of different microbes . Alternatively , it’s possible that a specific gut microbiota predisposes an individual to Entamoeba colonization . This relationship could also be the result of other correlating factors , not included in this study ( e . g . exposure to anthelmintics and/or infection by other pathogens or parasites ) . This pattern of lower alpha and higher beta diversity seen in Entamoeba-negative individuals has been repeatedly identified as a signature of gut microbiota in non-industrialized societies [15–18 , 26] . There are a number of hypotheses that have been proposed as explanations for this pervasive pattern including increased microbial dispersal [26] , higher complexity of dietary carbohydrates [19 , 22] , and diminished or lack of exposure to antibiotics [59 , 60] . An additional explanation for the inverse relationship between alpha and beta diversity is that in these populations , a more diverse gut microbiota is less sensitive to perturbations , or exhibits a limited number of potential stable states . It has been repeatedly demonstrated that biodiversity is often stabilizing , resulting in increased community resilience [61–63] . However , there are exceptions to this common trend as exemplified in the people of Tunapuco , a traditional agricultural community from the Andean Highlands , who exhibit gut microbiota with both higher alpha and beta diversity compared to the Western community analyzed in the study [20] . The explanation for this atypical pattern is not known , but it could be due to variables associated with the cooler climate of the region such as a distinct source community of microbes with more possible equilibrium states at higher levels of diversity and/or differences in parasite prevalence . It is still unclear what mechanism is responsible for the observed differences in the gut microbiota of Entamoeba positive and negative individuals . We note that our study is only able to describe correlations between Entamoeba and the microbiome , and causality cannot be inferred . We expect further studies , perhaps using model organisms , to shed light on the causal factors underlying this relationship . However , these patterns are consistent across rural populations that vary in terms of geographic location , genetic ancestry , diet , and access to medicine , suggesting that the pervasiveness of intestinal parasites like Entamoeba in non-industrialized societies might partially contribute to the explanation for the higher alpha diversity and lower beta diversity commonly observed in developing vs . industrialized populations . Alternatively , the relative differences in diversity between traditional vs . Western societies could be due to distinct and unrelated factors . Interestingly , we found that the majority of specific taxa for which abundance significantly correlated with the presence of Entamoeba share the common feature that they have been highlighted for their potential role as signatures of inflammation-related diseases . For example , Clostridiales Ruminococcaceae , the second most important taxon in the RFC model , significantly more abundant in Ent+ individuals , has been found to be underrepresented in individuals suffering from Crohn’s Disease and Ulcerative Colitis [27] . Likewise , a decreased prevalence of Prevotella copri and Fusobacteria , as observed in Ent+ individuals , was recently shown to be negatively correlated with Rheumatoid arthritis [64] and incidence of colorectal cancer [65 , 66] , respectively . Although speculative , these relationships suggest a potential link between gut parasites , gut bacteria , and host inflammation . Additional studies are needed to elucidate the mechanisms driving these observed patterns , specifically how exposure to anthelmintics in developing countries might drive changes in gut microbiota that mirror patterns observed in industrialized societies . In addition to identifying the presence of Entamoeba as an important predictor of gut microbiome composition and structure across populations , we were also able to examine the relative influence of other factors . First , we compared the gut microbiome composition of individuals from the same subsistence mode and genetic ancestry , but coming from different villages . Within the hunter-gatherers , we saw clear differences in composition as well as in diversity between individuals living in Bandevouri versus those living in Makouré and Bidou , although this difference was only significant using the Shannon Index for alpha diversity ( p < 0 . 05; Welch’s t-test ) . Based on the data we have available , we found that these groups do not differ in terms of diet or parasitism , suggesting a role for other unexplored very localized environmental factors ( e . g . , water source ) . In terms of genetic ancestry , we found that , despite a genetic divergence as old as 60 , 000 years , the gut microbiome of the Pygmy hunter-gatherers is not strikingly different from that of the Bantu populations . The UniFrac distances and the number of significant taxa are indeed even lower between hunter-gatherers and farmers than between the farmers and the fishing population , two Bantu groups that share the same genetic ancestry . This suggests that in these populations , genetic background might play a smaller role in microbiome variation compared to the effect of diet and environment . However , we found key differences distinguishing the microbiota of hunter-gatherers from those of the farming and fishing populations , likely reflecting the influence of their long-term diet . The hunter-gatherers were correctly assigned to their subsistence mode with higher accuracy ( 85% ) relative to the other populations . Furthermore , some of our findings mirror patterns previously observed in comparisons of traditional vs . industrialized societies [18 , 20 , 26 , 48] ( see Table 1 ) , suggesting this ancestral subsistence mode might carry a specific microbial signature . Notably , we found a higher frequency of Proteobacteria in hunter-gatherers compared to the other Cameroonian populations , similar to the relationship between the Hadza and Italians [18] and that between traditional populations in Peru ( hunter-gathers and farmers ) and US individuals [20] . Lachnospiraceae uncl , identified as the third important in the RFC model with the tendency to be lower in the Pygmy hunter-gatherers ( 5 . 7% versus 7 . 7–11 . 3% in other populations , q = 0 . 075 ) , was also found to be in lower frequency in the Hadza compared to Italians [18] . Finally , Succinivibrio and Ruminobacter species , enriched in the Hadza , were also identified as important taxa in the RFC model , and occur at higher frequencies in the Pygmy hunter-gatherers ( see Table 1 ) . Thus , all these taxa seem to be a specificity of hunter-gatherer populations , rather than reflecting a difference between industrialized European and rural African populations . Succinivibrio is considered to be an opportunistic pathogen , which could mean that hunter-gatherer populations have more opportunistic pathogens than other populations , as proposed by Schnorr et al [18] . However , while Treponema was also found enriched in the Hadza , Matses , and Tunapuco populations [18 , 20] , we found it at a very low frequency in all the populations studied here ( < 3 . 5% , Table 1 ) . Moreover , we found Treponema abundance to differ significantly based on Entamoeba infection status rather than subsistence . When looking at other opportunistic genera in the Enterobacteriaceae family , we found that Shigella and Escherichia , both previously found only in Italian children and not in children from Burkina Faso [15] , occur at extremely low abundances in all four subsistence groups ( < 0 . 1% , see Table 1 ) . As for Klebsiella and Salmonella , neither taxon differed significantly amongst our groups ( Table 1 ) . Thus , there does not seem to be any clear trend for opportunistic pathogens in hunter-gatherers populations compared to others . However , our results highlight the importance of including parasite analysis in comparative studies of the gut microbiome of rural populations . Amongst the four populations included in this study , the fishing population is the most urbanized due to increased consumption of processed food and access to medicine . As such , the characteristics distinguishing the gut microbiomes of the fishing population from the farmers and hunter-gatherers that also differ between rural populations in developing countries and urban populations in industrialized countries [16 , 18 , 26] might correspond to signature patterns of a more industrialized lifestyle . In particular , within the phylum Bacteroidetes , we found a lower overall abundance of Bacteroidales uncl in the fishing population relative to the other three populations ( Table 1 ) , an order also depleted in Italians compared to Hadza [18] . High abundance of Prevotella and Bacteroides have also been shown to represent signatures of the microbiomes for people in developing and industrialized countries , respectively [15 , 16 , 18 , 20 , 26] . Higher abundances of Prevotella are often correlated with increased consumption of carbohydrates and simple sugars , whereas an elevated proportion of Bacteroides is associated with a diet richer in protein and fat . Although differences between the populations studied here were not statistically significant , the fishing population harbored the highest abundance of Prevotella sp . ( 30 . 8% ) , while the farmers from the North and the hunter-gatherers harbored the lowest ( 19 . 2% and 20 . 2% , respectively ) , congruent with decreased consumption of simple sugars in these populations . Notably , the abundance of Prevotella sp . is high relative to other genera in this order across all populations ( Table 1 ) and species of Prevotella were the most reduced in individuals infected with Entamoeba . This study suggests an important role for eukaryotic gut inhabitants and the potential for feedbacks between helminths , protozoa , microbes , and the host immune response , one that has been largely overlooked in studies of the microbiome . Prior analyses of the African gut microbiome have found an enrichment of Treponema , Bacteriodetes and Prevotella compared to European populations , an enrichment that has been proposed to be related to diet . However , our observations suggest that some of these trends could be related to the presence of Entamoeba ( or other commensals and parasites ) . Furthermore , we found that many of the taxa for which abundance was significantly correlated with Entamoeba infection exhibit opposite patterns of abundance to those demonstrated to be correlated with a variety of autoimmune disorders . In addition , our results highlight the substantial variability in gut microbiome composition among closely related populations . Thus , using a single population as a representative of a lifestyle or geographical region may be overlooking important fine-scale patterns in microbiome diversity . Hence , comparative population studies of the human microbiome stand to benefit tremendously from considering variation within a geographic region and the role of parasitism and disease .
The research permits , including all necessary ethical approvals , were obtained for this study by the “Institut de Recherche pour le Développement” ( IRD ) in agreement with the "Ministère de la Recherche Scientifique et de l’Innovation" ( MINRESI ) of Cameroon . We sampled 64 adult volunteers ( 26 females and 38 males ) in seven rural villages ( Bidou , Makouré , Bandevouri , Ndtoua , Afan Essokié , Akak and Ebodié ) in Southern Cameroon , after obtaining their informed consent for this research project . The research permits , including all necessary ethical approvals , were obtained for this study by the “Institut de Recherche pour le Développement” ( IRD ) in agreement with the "Ministère de la Recherche Scientifique et de l’Innovation" ( MINRESI ) of Cameroon . For each participant , we collected information about his or her age , gender , anthropometric traits , health status , ethno-linguistic and quantitative nutritional questionnaires . We also collected saliva and fecal samples . The fecal sample was self-collected in the morning and stored in a plastic bag at most 3–4h before further handling . It was then split in two separate samples; one was used to perform the parasitological analysis at a local hospital ( fresh or covered with formol ) and the other was stored to run the sequencing analyses . This latter sample was handled following previous methods [67]: the sample was first submerged with pure ethanol for about 24h at room temperature , then the ethanol was poured out of the container and the sample was wrapped in a sterile gauze and deposited on silica gel [18] . The silica gel was then replaced by new gel when it changed colors from orange to yellow , i . e . when it could not absorb further humidity . The samples were then transported back to France and stored at -80°C until they were shipped to Minnesota , USA , on dry ice , and stored there at -80°C until further use . For five individuals , we were able to collect replicate fecal samples at two different time points: four individuals 7 days apart , and one individual 1 day apart . Intestinal parasitism of individuals was assessed by direct observation of fecal samples under the microscope . For each individual , a small amount of fecal matter was diluted in formol and homogenized to be liquid . A drop of liquid was then visualized under the microscope . If no known parasites were detected in this sample , another drop was closely inspected . If nothing was visible , the individual was characterized as negative . Parasite characterization was carried out by the same individual using the same method every time . Total DNA was extracted by bead beating from approximately 50 mg of each fecal sample using the MOBIO PowerFecal DNA Isolation Kit ( MOBIO Laboratories , Carlsbad , CA , USA ) according to the manufacturer's protocol . DNA isolated from fecal samples was quantified using a NanoDrop ( ThermoScienctific ) , and the V5–V6 regions of the 16S rRNA gene were PCR amplified using Accura High Fidelity Polymerase , with the addition of barcodes for multiplexing . The forward and reverse primers were the V5F and V6R sets [68] , chosen in part to allow dual coverage of the entire region . The barcoded amplicons were pooled and Illumina adapters were ligated to the reads . A single lane on an Illumina MiSeq instrument was used ( 250 cycles , 300 bp , paired-end ) to generate 16S rRNA gene sequences yielding 175 , 784 Pass Filter ( PF ) reads per fecal sample ( SD = 72 , 822 ) and ~12 . 65 million total PF reads ( 4 . 9Gb of data ) . Raw sequencing data ( fastq files ) are available through MG-RAST [Project ID: mgp15238] . We obtained a total of 12 . 65 million high-quality reads , resulting in an average of 175 , 784 reads per sample ( +/- 72 , 822 ) . Raw Illumina sequences were demultiplexed and filtered using Cutadapt 1 . 7 . 1 [69] to remove adaptor sequences ( Read 1:CTGTCTCTTATACACATCTCCGAGCCCACGAGAC , Read 2:CTCTCTCTTATACACATCTGCCGCTGCCGACGA ) , chimeras , sequences containing ambiguous bases , and low quality reads ( Phred quality scores < 20 ) . Read pairs were resynced using RISS-UTIL and matching paired-end sequences were merged using FLASH [70] . Merged sequences over 250 bp in length ( the maximum length of the V5–V6 region ) were removed . The remaining merged sequences were analyzed using the open-source software package QIIME 1 . 7 . 0 ( Quantitative Insights Into Microbial Ecology ) [71] . We performed both open- and closed-reference Operational Taxonomic Unit ( OTU ) picking at 97% identity against the May 2013 Greengenes database [72] such that OTUs were assigned taxonomy based on 97% similarity to the reference sequence . Non-bacterial 16S rRNA sequences removed and those that did not align were clustered to each other prior to taxonomic assignment . The average percent of mapped reads per individual was 83% ( SD = 7 . 5% ) and did not vary significantly between populations ( Welch’s t-test , p > 0 . 2 ) . All summaries of the taxonomic distributions ranging from phylum to species were generated from the non-rarefied OTU table generated from this analysis . To characterize diversity across individuals , rarefaction plots were generated for each sample using the phylogenetic distance metric for diversity [73] . Samples were rarefied to 50 , 000 reads , the maximum depth permitted to retain all samples in the dataset . All diversity analyses were conducted on rarefied OTU tables containing 50 , 000 sequences per sample . Measurements are based on the mean values calculated from 100 iterations using a rarefaction of 10 , 000 sequences per sample ( 20% of the total 50 , 000 ) . Alpha-diversity was calculated for each sample based on phylogenetic diversity , Shannon’s index [74] and the Simpson index [75] . Beta-diversity was assessed based on both unweighted and weighted UniFrac distance metrics [43] using the Greengenes phylogenetic tree [72] . Principal Coordinate Analysis ( PCoA ) was carried out on the distance matrices . P-values were calculated using the Welch’s or Wilcoxon t-tests , depending on normality of the distribution . To determine if the UniFrac distances were on average significantly different for groups of samples , we conducted Principal Coordinates Analysis ( PCoA ) to reduce raw gastrointestinal microbial community data into axes of variation . We assessed the significance of each covariate by performing a permutational multivariate analysis of variance ( PERMANOVA ) [76] , a non-parametric test , on both weighted and unweighted UniFrac distance matrices using the “adonis” function from the vegan package in R [77] . This test compares the intragroup and intergroup distances using a permutation scheme to calculates a p-value . For all PERMANOVA tests we used 10 , 000 randomizations . Intergroup differences in microbiome composition for subsistence , location , population , BMI , sex , ancestry , age , dietary factors , and parasitism were assessed by PERMANOVA [76] using non-rarefied OTU abundance data and implemented using the “adonis” function of the vegan package in R [77] . To identify taxa significantly associated with each covariate of interest , we normalized the distribution of each OTU and used an ANOVA , FDR corrected for the number of OTUs in our dataset . For the ANOVA , OTUs with identical taxonomic identifiers were combined . In parallel , we also restricted the merging only to OTUs names defined at the family , genus or species level . Both results are reported in Supplementary Material ( “merged OTUs” versus “partially merged OTUs” ) . For analyses of both merged and partially merged OTUs , the resulting taxa were filtered to include only those that occurred at least 0 . 1% in at least 4 individuals . A random forest classifier with 2000 decision trees was trained on the taxa abundance table consisting of 93 OTUs with 5-fold cross-validation using scikit-learn [78] . Mean accuracy ( the ration of the number of correct predictions relative to the total number of predictions ) over the 5 folds was 0 . 79 ( standard deviation 0 . 09 ) with p < 0 . 001 ( estimated using 1000 permutation tests with 5-fold cross-validation ) . The most discriminating taxa were identified by random forest importance values ( in scikit-learn random forest importance values are calculated as mean decrease in node impurity ) . We report the top ten median importance values and 95% confidence intervals from 1000 random forests . We used PICRUSt v1 . 0 . 0 ( Phylogenetic Investigation of Communities by Reconstruction of Unobserved States ) to generate taxonomy-based predicted metagenomes for each sample [50] . Counts from the rarefied OTU Table ( 50 , 000 OTUs per sample ) were normalized by the predicted 16S rRNA gene abundances and functional predictions of Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [49] pathways were determined using pre-computed files for the May 2013 Greengenes database [72] . Relative abundances of the functional predictions were calculated . We also compared the predicted metagenomes of individuals to determine which functions were enriched or depleted across covariates ( subsistence , population , location , ancestry , BMI , age , sex , dietary components , and parasitism phenotypes ) for abundant ( ≥ 0 . 1% in at least 4 individuals ) and rare ( < 0 . 1% in at least 4 individuals ) pathways . An ANOVA was used to determine which predicted pathways were significant ( q < 0 . 05 ) for each covariate . | The community of microorganisms inhabiting the gastrointestinal tract plays a critical role in determining human health . It’s been hypothesized that the industrialized lifestyle , marked by a diet rich in processed foods , higher use of antibiotics , increased hygiene , and exposure to various chemicals , has altered microbiota in ways that are harmful . Studies have addressed this by comparing rural and industrialized populations , and have found that they systematically vary in their gut microbiome composition . Nevertheless , the relative influence of host genetics , diet , climate , medication , hygiene practices , and parasitism is still not clear . In addition , microbial variation between nearby human populations has not been explored in depth . Moreover , The World Health Organization estimates that 24% of the world’s population , concentrated in developing countries , is infected with gut parasites . Despite this , and evidence for direct interactions between the immune system and both gut parasites and bacteria , we know relatively little about the relationship between gut helminths , protozoa , and bacteria . In our study , we aimed to address some of this complexity . To do so , we characterized the gut microbial communities and parasites from Pygmy hunter-gatherer and Bantu farming and fishing populations from seven locations in the rainforest of Southwest Cameroon . We found that both subsistence mode and the presence of the gut protozoa , Entamoeba , were significantly correlated with microbiome composition . These findings support previous studies demonstrating diet is an important determinant of gut microbiota , and further show that this pattern holds true at a local scale , in traditional societies inhabiting a similar environment . Additionally , we show a significant relationship between a common human parasite ( Entamoeba ) and gut bacterial community composition , suggesting potential important interactions between the immune system , gut bacteria , and gut parasites , highlighting the need for more hierarchical cross population studies that include parasitism as potential factor influencing gut microbiota dynamics . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [] | 2015 | Variation in Rural African Gut Microbiota Is Strongly Correlated with Colonization by Entamoeba and Subsistence |
Biological networks have evolved to be highly functional within uncertain environments while remaining extremely adaptable . One of the main contributors to the robustness and evolvability of biological networks is believed to be their modularity of function , with modules defined as sets of genes that are strongly interconnected but whose function is separable from those of other modules . Here , we investigate the in silico evolution of modularity and robustness in complex artificial metabolic networks that encode an increasing amount of information about their environment while acquiring ubiquitous features of biological , social , and engineering networks , such as scale-free edge distribution , small-world property , and fault-tolerance . These networks evolve in environments that differ in their predictability , and allow us to study modularity from topological , information-theoretic , and gene-epistatic points of view using new tools that do not depend on any preconceived notion of modularity . We find that for our evolved complex networks as well as for the yeast protein–protein interaction network , synthetic lethal gene pairs consist mostly of redundant genes that lie close to each other and therefore within modules , while knockdown suppressor gene pairs are farther apart and often straddle modules , suggesting that knockdown rescue is mediated by alternative pathways or modules . The combination of network modularity tools together with genetic interaction data constitutes a powerful approach to study and dissect the role of modularity in the evolution and function of biological networks .
Biological function is an extremely complicated consequence of the action of a large number of different molecules that interact in many different ways . Elucidating the contribution of each molecule to a particular function would seem hopeless , had evolution not shaped the interaction of molecules in such a way that they participate in functional units , or building blocks , of the organism's function [1–4] . These building blocks can be called modules , whose interactions , interconnections , and fault-tolerance can be investigated from a higher-level point of view , thus allowing for a synthetic rather than analytic view of biological systems [5 , 6] . The recognition of modules as discrete entities whose function is separable from those of other modules [7] introduces a critical level of biological organization that enables in silico studies . Here , we evolve large metabolic networks based on an artificial chemistry of precursors and metabolites , and examine topological and information-theoretical modularity measures in the light of simulated genetic interaction experiments . Intuitively , modularity must be a consequence of the evolutionary process , because modularity implies the possibility of change with minimal disruption of function [1] , a feature that is directly selected for [3 , 8] . Yet , if a module is essential , its independence from other modules is irrelevant unless , when disrupted , its function can be restored either by a redundant gene or by an alternative pathway or module . Furthermore , modularity must affect the evolutionary mechanisms themselves , so that both robustness and evolvability can be optimized simultaneously [1 , 9 , 10] . A thorough analysis of these concepts requires both an understanding of what constitutes a module in biological systems and tools to recognize modules among groups of genes . In particular , a systems view of biological function requires that we develop a vocabulary that not only classifies modules according to the role they play within a network of modules and motifs , but also how these modules and their interconnections are changed by evolution , i . e . , how they constitute units of evolution targeted directly by the selection process [4] . The identification of biological modules is usually based either on functional , evolutionary , or topological criteria . For example , genes that are co-expressed and/or coregulated can be classified into modules by identifying their common transcription factors [11 , 12] , while genes that are highly connected by edges in a network form clusters that are only weakly connected to other clusters [13] . From an evolutionary point of view , genes that are inherited together but not with others often form modules [14–16] . Yet , the concept of modularity is not at all well defined . For example , the fraction of proteins that constitutes the core of a module and that is inherited together is small [14] , implying that modules are fuzzy but also flexible so that they can be rewired quickly , allowing an organism to adapt to novel circumstances [17] . Progress in our understanding of the modular nature of biological networks must come from new functional data that allow us to study different groups of genes both together and apart , and compare this data to our topological , information-theoretic , and evolutionary concepts . A promising set of data is provided by genetic interactions [18] , such as synthetic lethal pairs of genes ( pairs of mutations that show no phenotype on their own but that are lethal when combined ) , or dosage rescue pairs , in which a knockout or mutation of a gene ( in general , a loss of function ) is suppressed by overexpressing another gene . Such pairs are interesting because they provide a window on cellular robustness and modularity brought about by the conditional expression of genes . Indeed , the interaction between genes—gene epistasis [19]—has been used to successfully identify modules in yeast metabolic genes [20] . However , often interacting pairs of genes lie in alternate pathways rather than cluster in functional modules , do not interact directly , and thus are expected to straddle modules more often than lie within one [21] . In silico evolution is a powerful tool if complex networks can be generated that share the pervasive characteristics of biological networks , such as error tolerance , small-world connectivity , and scale-free degree distribution [22] . If furthermore each node in the network represents a simulated chemical or a protein catalyzing reactions involving these molecules , then it is possible to conduct a detailed functional analysis of the network by simulating knockdown or overexpression experiments . This functional datum can then be combined with evolutionary and topological information to arrive at a more sharpened concept of modularity that can be tested in vitro when more genetic data become available . Previous work on the in silico evolution of metabolic [23] , signaling [24 , 25] , biochemical [26 , 27] , regulatory [28] , as well as Boolean [29] , electronic [30] , and neural [30–32] networks has begun to reveal how network properties such as hubness , scaling , mutational robustness as well as short pathway length can emerge in a purely Darwinian setting . In particular , in silico experiments testing the evolution of modularity both in abstract [33] and in simulated electronic networks [30] suggest that environmental variation is key to a modular organization of function . In the experiments we describe below , we evolve large metabolic networks of many hundreds of nodes with over a thousand edges for up to 5 , 000 generations from simple networks with only five genes . These networks are complex—in the sense of information-rich [34 , 35]—are topologically interesting , and function within simulated environments with different variability that can be arbitrarily controlled . We analyze these networks using new tools that allow us to see genetically interacting pairs in the light of different concepts of modules , and compare our results to an application of those tools to the yeast protein–protein interaction network .
Networks evolve to be highly complex , increase in size and develop complex pathways to metabolize the precursors . Typically , pathways evolve first via duplication and divergence of the existing genes , but later pathways are combined and new pathways emerge by evolving import proteins for precursors that leak into cells and for which catalytic proteins had evolved . Reaction networks are complicated , involving loops and multiple interconnections .
Evolution shapes our artificial metabolic networks into complex tightly connected pathways that are modular in nature , and that share many of the well-known properties of biological networks , such as scale-free edge distribution , small-world connectivity , and hubness . We can use these networks to study how established concepts of modularity—such as betweenness centrality clustering and information-theoretic modularity—compare to the rate at which genetically interacting pairs are disrupted by either removing nodes with high BC , or merging nodes that have been assigned to the same information-theoretical cluster . By evolving networks in different environments that are expected to yield different modularities , we can dissect the impact of genetically interacting pairs on modularity notions . When we compare the behavior of genetically interacting pairs in our evolved networks to those in the yeast protein–protein interaction network , we find commonalities and some discrepancies . One of our main findings is that synthetic lethal pairs usually lie within modules , no matter how modules are defined , and that compensatory ( suppressor ) pairs preferentially straddle modules . We also find that in our metabolic networks , many nodes that are assigned the same module in fact have high betweenness centrality themselves , a property that does not appear to be shared with the yeast protein–protein interaction graph , where random pairs separate faster than compensatory pairs . A number of differences between the networks can explain these findings . First , the functional graphs ( Figure 1B ) we use to determine nodes of a network have a different connectivity pattern than protein–protein interaction networks as shown in Figure 3 , and are sparser . Second , the multi-copy suppressor pairs we use to mark genetic compensation in our metabolic networks are different in nature from the dosage rescue pairs listed in Reguly et al . [18] . Also , synthetic lethality for metabolic networks refers almost exclusively to functional redundancy , whereas synthetic lethality in yeast can involve complex and indirect interactions . While in principle we could have restricted the comparison of our evolved networks to only the metabolic component of the yeast interaction network , the number of genetically interacting pairs of genes affecting metabolic genes in Reguly et al . is not sufficient to establish significance . Experimental work in progress by several groups to obtain a large number of multi-copy suppressor pairs in yeast will change this situation dramatically . We find no evidence that dynamic environments are required for the evolution of functional modules [30 , 33] . Rather , it appears that genes segregate into functional modules as long as there are a large number of different ways to achieve functionality . Indeed , on the contrary , metabolic networks evolved in dynamic environments appear to be less modular . We can understand this finding by noting that our dynamic environments change randomly by omitting the availability of a random fraction of precursors , as opposed to the modular changes implemented in Ref . [30] . To deal with the unpredictability of the environment , our metabolic networks first evolve reactions that produce precursors from other precursors and metabolites ( see Figure S8 ) such that several different genes produce the same precursor from different precursors and metabolites at any point in time . In that way , the evolved redundancy ensures the presence of any particular precursor . Because this redundancy creates connections between pathways , the modularity score of such networks is lower . We also find that networks evolve more slowly in dynamic environments , but they are more robust to environmental fluctuations in return . Thus , at least for metabolic networks , robustness and modularity do not necessarily go hand-in-hand . The in silico evolution of functional networks based on artificial genetics and chemistry presents an opportunity to study how complex networks , their structure and organization , evolve over time to cope with environments with varying degrees of predictability . We believe that such networks can provide a formidable benchmark for experiments with biochemical networks , and allow predictions with hitherto unavailable accuracy . The type of functional interaction experiments that we performed on our large evolved networks anticipates high-throughput efforts currently under way using temperature-sensitive yeast deletion mutants and their multi-copy suppressors , and suggests that dosage rescue ( or multi-copy suppressor ) pairs of genes represent an appropriate and sensitive tool to study modularity in biological networks .
Molecular interactions occur through proteins that catalyze the reactions between the molecules of our artificial chemistry and transport them in and out of cells . These proteins are encoded by an artificial genetics using the four “nucleotides” 0 , 1 , 2 , and 3 and determine the rate at which the reactions proceed . An open reading frame on a chromosome starts with four zeros ( see Table S1 ) , followed by a code indicating the expression level , followed by a tag designating the protein type , followed by the specificity and the affinity . The specificity is a 12 nucleotide stretch that determines the target molecule or reaction ( e . g . , if the tag is “import” , 123321000000 specifies that molecule 1-2-3=2-1 is transported into the cell ) . Reactions are specified by mapping the 5 , 020 , 279 legal reactions to the 412 = 16 , 777 , 216 possible 12-mer specificities , in such a manner that any mutation in the specificity region is guaranteed to catalyze a legal reaction . A protein's affinity is determined by an “active site” that has four domains; one each for the four molecules involved in the reaction A + B → A′ + B′ . The binding affinity of a transport protein to the specified target is obtained by averaging the affinity of all four domains . Each domain has twelve entries that are matched to particular molecules ( of maximally twelve atoms ) in the following manner . First , a molecule is translated into its binary equivalent , for example , 1-2-3=3-2-1 is 01-10-11-11-10-01-00-00-00-00-00-00 ( zeros are used to pad molecules smaller than 12 atoms ) . The 24 bit domain of the protein P is compared with the binary equivalent of the target molecule M , resulting in an affinity score D ( M , P ) that is highest if the protein domain is precisely complementary to the molecule . So , for example the perfect domain for molecule 1-2-3=3-2-1 is 10-01-00-00-01-10-11-11-11-11-11-11 . Numerically , D ( M , P ) is obtained as 1 − S ( M , P ) , where S ( M , P ) is a similarity score where is the base-10 translation of the logical bitwise EQUAL of the molecule's and protein's ith site . The base-10 translation of the equivalent of a perfect match ( ‘11' ) is 3 , so that the maximal is 12 × 32 = 108 , ensuring that 0 ≤ A ( M , P ) ≤ 1 . The complementarity scheme is chosen to minimize the occurrence of domains of the type 00-00-00–00 , as they would be decoded as start codons . The maximal genome size in this model is 120 , 000 bits , or 60 , 000 nucleotides , on 2 circular chromosomes . Genes are allowed to overlap . Note that because of the absence of recombination , one of the two chromosomes consistently degenerates during evolution so that all of the complexity ends up contained in a single circular genome . Cells live in a two-dimensional space where precursor molecules are produced at defined locations and diffuse out , so that the concentration of molecule M at distance d from the source , [M] ( d ) , depends on the concentration at the source via which is the solution of the diffusion equation with a diffusion coefficient D = 1/2 , at time t = 1 . Molecule concentrations [Mi] are updated according to a discretized version of the standard metabolic rate equations [46] for molecules i = 0…607 , where the sum runs over reactions j = 1 to r , and the matrix cij is the connectivity matrix of the network defined as and vj is the metabolic flux In Equation 3 , is the number of edges leaving molecule l , and we defined the reaction matrix for reaction j as well as the affinity A ( j ) by where D ( Mp , Pp ) are the affinities of protein domain Pp to the molecules Mp as defined above . The fitness of an organism is determined by the amount and complexity of the molecules it can metabolize from the precursors . The 608 possible molecules of the artificial chemistry are numbered according to their complexity ( length and type of atoms ) : and the first 53 molecules are arbitrarily termed precursors . The remaining 555 molecules are metabolites of increasing complexity ( the most complex one being M607 ) . Each different molecule metabolized by the cell contributes to the total fitness . If Δ ( Mi ) is the total amount of molecule i synthesized by the cell , the total fitness is calculated using the fitness value of each the molecules Mi , which depends on its index i via as In Equation 6 , the product extends only across metabolites that have achieved non-vanishing abundance during a cell's lifetime . Because of the explicit dependence of a cell's fitness on the concentration of precursors in the cell's vicinity , fitness is context dependent , and in principle depends on the frequency of other cells in a population . Due to the multiplicative nature of the fitness function , the discovery of new pathways is always beneficial with the same percentage , and the fitness increases exponentially during evolution . We usually plot the logarithm of the fitness , which is additive . A Genetic Algorithm [47] is used to evolve circular genomes encoding genes using the nucleotide alphabet [0 , 1 , 2 , 3] . Mutations are Poisson-random with a mean of one mutation per genome ( and a maximum of six mutations per genome ) . With a probability of 1/16 per genome , a stretch of 4–512 base pairs is duplicated and inserted directly adjacent to the duplicated stretch . With the same probability , a stretch of the same size is deleted from the genome . No recombination takes place between genomes . The probability for a genome to be replicated is proportional to the fitness calculated in Equation 6 ( Wright-Fisher selection ) . Organisms must be at least 8 updates old before they can replicate , and they are protected from death during those first 8 updates . We designed the ancestral genome to have 3 genes on the first 1 , 000 bp chromosome , with the 2nd chromosome of 1 , 000 bps filled with poly-‘3′s in order to be as distant as possible to start codons . However , it turned out that the third gene has a start codon ( 0000 ) within its specificity domain as well as in the sequence specifying the expression level , both of which give rise to two additional proteins in overlapping reading frames ( see Figure 11 ) . Those proteins , because they are useless to the organism , quickly disappear within the first tens of generations . The spaces between the first three genes are filled with random sequence , and the 880 bp genome is padded with 120 poly-‘3′s , to make up the 1 , 000 bp of the ancestral genome as sketched in Figure 11 . The complexity of an organism can be estimated by the amount of information its genome encodes about the environment within which it thrives [34 , 35 , 48] . We can estimate the information content I of a sequence s of length L encoding the bases 0 , 1 , 2 , 3 by I = L − H ( s ) , where the entropy of the sequence H ( s ) is approximated by the sum of the per-site entropies , with a per-site entropy In Equation 7 , the pi are the probabilities to find base i at position x , which can be obtained from an alignment of genomes in mutation-selection balance . For small populations and long genomes , this balance is not achieved , and the substitution probabilities pi must be estimated using the fitness effect of each substitution wi according to the implicit equation [49] where is the mean fitness of the possible alleles at that position and μ is the mutation rate per site . We obtain the fitness wi of each allele at each position by constructing the genotype and evaluating the fitness of the cell it gives rise to in the appropriate environment . ( Mutations that appear to be beneficial are counted as wild-type fitness . ) Using the four values wi , the probabilities pi can be obtained by iterating Equation 8 10 , 000 times or until the variance of all pi drops below 10−12 . To assign a modularity score to our networks , we use the information bottleneck method [50] , as applied to biological networks by Ziv et al . [40] . Briefly , the method assigns clusters to the nodes of a network described by a random variable X using an assignment random variable Z and a relevance variable Y ( the bottleneck ) by maximizing both the simplicity of the description ( maximizing the mutual entropy between the graph and its description I ( X : Z ) ) and its relevance or fidelity ( maximizing I ( Y : Z ) ) . This is achieved via a hard clustering method that starts with a description Z with one fewer nodes than X , then calculates the conditional probability p ( z | y ) from a diffusion process and selects those nodes of X to merge in the description Z that result in the highest I ( Y : Z ) . This process iterates until all the nodes have been joined and the size of Z is one . This procedure results in a list of nodes ( from highest cluster probability to lowest ) that can be used to study how synthetic lethal and knockdown suppressor pairs are merged as an alternative to the topological clustering via betweenness centrality . A modularity score for each network is obtained as the area under the information curve obtained by plotting the normalized quantities I ( Z : X ) /H ( X ) and I ( Z : Y ) /I ( X:Y ) against each other [40] . Because random graphs give rise to an information curve with area 0 . 5 , any modularity score above 0 . 5 signals a modular organization of the network . To obtain the modularity score in Figure 6 , we averaged the modularity score of the largest , second largest , etc . connected components of the network μi weighted by their relative size . Thus , if the ith largest connected component of the network of size N is ni , then the average modularity score is ( note that ni ≥ 5 is required as the modularity of smaller networks cannot be obtained ) The average distance D of each node to any other defines the average geodesic distance of a graph where n is the total number of nodes , d ( i , j ) is the shortest path distance between i and j , and m is the total number of edges . We measure the robustness of evolved networks with respect to node deletions and to changes in the precursor concentrations . Even though these perturbations are unrelated prima facie , there is evidence that mutational robustness and robustness to noise are correlated [28] . We measure mutational robustness by removing n random nodes and determining the ( scaled ) fitness of the remaining graph , where is the mean of 1 , 000 independent fitness measurements of a network where n random nodes have been removed . The fitness decreases exponentially as long as less than 30% of the nodes are removed , suggesting a ( “knock-out” ) robustness parameter ρKO defined via Environmental robustness is determined by evaluating the fitness of an organism as more and more of the 53 precursor molecules are removed . Fitness declines exponentially with the number of deleted nodes or chemicals removed , and robustness can be quantified by the slope of the decrease of log fitness , defining ρENV in a similar manner . The betweenness centrality of a node in a network topology measures how many shortest paths go through that node . If bi is the ratio of the number of shortest paths between a pair of nodes in the network that pass through node i and the total number of shortest paths between those two nodes , then the unscaled betweenness of node i is , and the ( scaled ) betweenness centrality is [45] where n is the number of nodes in the network . The betweenness centrality is positive and always less than or equal to 1 for any network . The software to implement the artificial chemistry and genetics , as well as the evolution experiments described in this manuscript , is available at http://public . kgi . edu/~ahintze . | The modular organization of cells is not immediately obvious from the network of interacting genes , proteins , and molecules . A new window into cellular modularity is opened up by genetic data that identifies pairs of genes that interact either directly or indirectly to provide robustness to cellular function . Such pairs can map out the modular nature of a network if we understand how they relate to established mathematical clustering methods applied to networks to identify putative modules . We can test the relationship between genetically interacting pairs and modules on artificial data: large networks of interacting proteins and molecules that were evolved within an artificial chemistry and genetics , and that pass the standard tests for biological networks . Modularity evolves in these networks in order to deal with a multitude of functional goals , with a degree depending on environmental variability . Relationships between genetically interacting pairs and modules similar to those displayed by the artificial gene networks are found in the protein–protein interaction network of baker's yeast . The evolution of complex functional biological networks in silico provides an opportunity to develop and test new methods and tools to understand the complexity of biological systems at the network level . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] | [
"none",
"computational",
"biology"
] | 2008 | Evolution of Complex Modular Biological Networks |
Animal development requires the execution of specific transcriptional programs in different sets of cells to build tissues and functional organs . Transcripts are exported from the nucleus to the cytoplasm where they are translated into proteins that , ultimately , carry out the cellular functions . Here we show that in Caenorhabditis elegans , reduction of mRNA export strongly affects epithelial morphogenesis and germline proliferation while other tissues remain relatively unaffected . Epithelialization and gamete formation demand a large number of transcripts in the cytoplasm for the duration of these processes . In addition , our findings highlight the existence of a regulatory feedback mechanism that activates gene expression in response to low levels of cytoplasmic mRNA . We expand the genetic characterization of nuclear export factor NXF-1 to other members of the mRNA export pathway to model mRNA export and recycling of NXF-1 back to the nucleus . Our model explains how mutations in genes involved in general processes , such as mRNA export , may result in tissue-specific developmental phenotypes .
Cell differentiation and morphogenesis rely on the expression of specific genes that are translated into proteins in specific sets of cells to ensure the correct formation of the organs and body plan . The physical separation between genomic DNA and the cytoplasm in eukaryotic cells makes it necessary to export RNA through the nuclear envelope ( NE ) [1 , 2 , 3 , 4 , 5] . This nucleo-cytoplasmic transport is highly conserved [6] and our understanding of its mechanism comes from a variety of model organisms including yeast , nematodes , fruit flies and vertebrates [4 , 5 , 7 , 8] . mRNA biogenesis and export are tightly coordinated by sequential assembly of appropriate ribonucleoprotein complexes named the THO complex ( named after the yeast tho2 subunit was identified as a suppressor of the Transcriptional defect of Hpr1 by Overexpression ) , the TREX ( TRanscription EXport ) complex and the THSC/TREX-2 ( Transport/export complex 2 ) complex [4 , 5 , 9 , 10 , 11] . Briefly , during transcription , a group of proteins called the THO complex is recruited to chromatin . This complex is needed for transcription elongation , mRNA export and genome integrity [12 , 13] . The metazoan THO complex contains THOC1/2/3/5/6/7 ( THO complex in yeast: Hpr1 , Tho2 , Mtf1 and Thp2 ) [14] . Next , additional proteins UAP65 , Aly/REF and CIP29 ( Sub2p , Yra1p and Nab2 in yeast ) bind the THO subunits to build the transcription-export complex ( TREX complex ) which couples transcription with mRNA export [15] . After the messenger ribonucleoprotein ( mRNP ) has been generated , the conserved nuclear RNA export factor 1 ( NXF1/TAP ) is recruited through direct interaction with several TREX components [2 , 16] . NXF1 family export factors are composed of multiple domains . At the N terminus is the RNA recognition motif ( RRM ) [17] . Next , a leucine-rich repeat domain ( LRR ) is required for NXF1-mediated export [18] . This domain is followed by a nuclear transport factor 2 , NTF2-like domain , that heterodimerizes with a protein known as p15 or NXT [19 , 20 , 21 , 22] . Efficient mRNA export from the nucleus to the cytoplasm requires the formation of this complex . The remaining C-terminal domain , TAP , also known as the NXF1 ubiquitin-associated domain ( UBA ) , permits translocation through the central channel of the nuclear pore complex ( NPC ) by interacting with FG-Nups ( phenylalanine-glycine ( FG ) reach nucleoporins ) [6 , 20 , 21 , 23 , 24] . Finally , the THSC/TREX-2 ( transport/export complex 2 ) , binds the mRNP to the nucleoplasmic side of the NPC . The transit of mRNP through the nuclear pore is mediated by direct interaction of NXF1-p15 with the nucleoporins that line the pore [25] . Once in the cytoplasm , mRNA can be stored in large ribonucleotide protein particles ( RNP ) , as happens in the so-called germ granules ( known as P granules in C . elegans ) or it can be directly translated into proteins [26 , 27 , 28] ( Fig 1 ) . Over the last decades , C . elegans has emerged as a powerful model for studying cell differentiation and morphogenesis . C . elegans has a simple body plan . Schematically , it can be divided into two cylindrical layers of tissues and organs separated by a fluid-filled space ( pseudocoelom ) . From outside to inside , the outer layer constitutes the body wall , which consists of the cuticle and an epithelium called the epidermis ( also known as the hypodermis ) [29] , the excretory system , neurons and muscles . The inner system is comprised of the gonad and another epithelial tube composed of the pharynx and intestine [30] . The anterior portion of the pharynx and the external epidermis remain linked by nine cells called the arcade cells . Absence of this arcade cell epithelium leads to a Pun ( pharynx unattached ) phenotype where the pharynx detaches from the mouth during development and forms a confined cell cluster in the interior of the animal [30 , 31 , 32 , 33] . Several pathways contribute to cell fate specification and epithelialization of arcade cells . It occurs after the epidermis and pharynx have epithelialized . The process is very fast ( less than 10 minutes ) , during mid-embryogenesis after the embryonic cell divisions are complete [33] . Recent studies show that PAR-6/PARD6A is required for polarizing the arcade cells to define typical apical and basolateral domains [34 , 35 , 36] . In C . elegans epithelial cells , both domains are separated by the adherens junctions ( CeAJ ) . Thus , the CeAJ contains proteins that mediate adhesion such as HMR-1/cadherin , HMP-1/-catenin , HMP-2/-catenin , and VAB-9/claudin [37 , 38] . In addition , DLG-1/Discs large and the coiled-coil protein AJM-1 , are also part of the CeAJ although they are located slightly more basally [39 , 40] . In this study we show that reducing mRNA export strongly affects epithelial formation and germline proliferation in C . elegans . Previous studies revealed that both processes require specific gene expression programs . Our findings indicate the existence of feedback mechanisms that activate expression of specific genes to compensate for the lack of mRNAs in the cytoplasm such as those involved in mRNA export or cytoskeletal rearrangements . Finally , we suggest a model to explain the mRNA export pathway and recycling of the export factor NXF-1 back to the nucleus in C . elegans to close the export cycle .
To discover genes involved in embryonic morphogenesis , we performed a genetic screen for embryonic lethal worms with the pharynxes unattached to the mouth ( Pun phenotype ) . Thus , we identified a thermo-sensitive ( ts ) mutant allele , t2160 , whose embryos arrested at late stages with a highly penetrant Pun phenotype ( 87 . 5% ( n = 176 ) ) and body elongation defects ( 81% ( n = 60 ) ) ( Fig 2A and 2B , Table 1 ) . Three experimental lines demonstrated that t2160ts is an allele of the C . elegans nuclear export factor 1 ( nxf-1 ) [41] . First , using the whole genome sequencing approach ( WGS ) and CloudMap/Hawaiian Variant Mapping ( http://usegalaxy . org/cloudmap ) [42] , we identified a homozygous A-to-G transition at the 14414501 position of chromosome V , in the C15H11 . 3/nxf-1 gene that caused a VAL to ALA substitution . The t2160ts mutation was located in the RRM ( RNA recognition motif ) domain of NXF-1 ( Fig 2C ) . Second , t2160ts failed to complement a knockout deletion of the nxf-1 ( ok1281 ) gene . Third , the t2160ts embryonic lethality was successfully rescued with a plasmid containing 1096 bp of the gene promoter , the nxf-1 genomic region and 1313 bp of the 3' UTR ( S1 Fig ) . To determine whether the ts effect of the VAL to ALA substitution was likely due to synthesis or to folding [43] we performed a ts curve assay during embryo development ( S2 Fig ) . In an up-shift curve , worms grown to adulthood at 15°C ( permissive temperature ) were allowed to lay eggs which were sequentially shifted to 25°C ( restrictive temperature ) . In those embryos , the maternal product was therefore synthesized at the permissive temperature . However , 100% of those embryos died when shifted to 25°C at the two-cell stage , and the lethality did not fall under 50% until mid-embryogenesis when most cell divisions and epithelialization are completed . The maternal product is enough to complete the development of a maternally rescued homozygous embryo at 25°C from a heterozygous nxf-1 ( t2160ts ) ( +/- ) hermaphrodite mother . Together with the down-shift curve , these results show the NXF-1 requirement during embryonic cell proliferation , differentiation and morphogenesis and strongly indicate that t2160ts mutation alters the protein conformation when exposed to 25°C . Since the t2160ts mutation affects the nxf-1 gene , we decided to check intracellular mRNA distribution . To examine the polyadenylated RNA localization , we performed FISH ( fluorescent in situ hybridization ) analysis . Hybridization with an oligo-dT probe against poly ( A ) showed mRNA preferentially accumulated in the nucleus rather than the cytoplasm of nxf-1 ( t2160ts ) mutants . In contrast , the signal was mostly dispersed in the cytoplasm of wild-type ( WT ) embryo cells ( Fig 2D ) . This indicates that t2160ts is a loss-of-function mutation in the nxf-1 gene that impairs mRNA export . A phenotypic analysis of the available alleles and nxf-1 RNAi reveals that the t2160ts mutation leads to reduced activity but is not a null allele of nxf-1 . nxf-1 ( ok1281 ) knockout maternally rescued or nxf-1 RNAi-fed L1 larvae led to larval arrest , whereas nxf-1 ( t2160ts ) or RNAi performed under mild conditions ( RNAi diluted with L4440 bacterial RNAi empty vector at a 1:1 ratio ) led both to the same embryonic Pun phenotype and body elongation defects in the F1 embryos . Heterozygous worms ok1281/ t2160ts exhibited an intermediate phenotype: they reached adulthood but were sterile ( Table 1 ) . To check NXF-1 localization in vivo and throughout development , we created transgenic lines expressing NXF-1 fused to 3xFLAG and eGFP ( enhanced green fluorescent protein ) ( S1B Fig ) . The transgene successfully rescued the nxf-1 ( t2160ts ) mutation indicating that the construct was functional and did not change the function of NXF-1 . eGFP expression was detected in all stages of the C . elegans life cycle . As expected for a nuclear export factor , NXF-1::3xFLAG::eGFP showed nuclear localization during embryogenesis , larval and adult stages . NXF-1 showed dynamic localization during cell division: it was detected as nuclear but diffused to the cytoplasm during mitosis ( S1 Movie ) . In addition , NXF-1::3xFLAG::eGFP was detected in granules in the oocyte cytoplasm ( Fig 3 ) . To assess the developmental defects of nxf-1 ( t2160ts ) embryos , we performed 4D microscopy and compared it to that of WT N2 embryos ( S2 Movie ) . Since the nxf-1 ( t2160ts ) mutant is temperature sensitive , worms ( WT and mutant ) were grown at 15°C . Then , the worms where transferred to 25°C degrees and allowed to grow overnight ( O/N ) prior to selecting the embryos . The Pun pharynxes of the nxf-1 ( t2160ts ) mutant embryos displayed several characteristics that are consistent with normal tissue differentiation , such as the presence of a distinct pharyngeal lumen and sustained rhythmic pumping . In further support of these results , we observed strong expression of several GFP markers indicating the presence of differentiated muscle ( Pmyo-2::GFP ) [44] , and neurons ( Pric-19::GFP ) [45] in the Pun pharynxes ( Fig 4A and 4B ) . In addition to these transgenes , we tested the expression of the pha-4 gene . The pha-4 transcription factor is the central selector regulator gene for the C . elegans pharynx and its activity is essential for all pharyngeal development [46] . PHA-4 determines the identity and morphogenetic program of all the pharyngeal precursors by directly regulating many genes expressed in the pharynx and arcade cells at different time intervals [36 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54] . pha-4 expression was detected in the nuclei of the intestine , pharynx and arcade cells , both in the nxf-1 ( t2160ts ) mutant and WT . All nine arcade nuclei could be identified and were located approximately between the pharyngeal and epidermal cells ( Fig 4C ) , indicating that developmental programs properly differentiate pharyngeal cells in the nxf-1 ( t2160ts ) mutant . Furthermore , normally expressed CDH-3::GFP [55] in the developing arcade cells , lateral epidermal cells and seam cells suggested proper differentiation of epithelial cells ( Fig 4D ) . In contrast , expression of the pxIs10 [Ppha-4::GFP::CAAX + ( pRF4 ) rol-6 ( su1006 ) ] transgene that generates a GFP fused to the isoprenylation sequence ( CAAX ) of mig-2 [56] , under control of the pha-4 promoter to drive GFP to the plasma membrane of the same cells [30 , 53] , revealed that although the intestinal and pharyngeal cell membranes glowed in both WT and mutant embryos , fluorescence was not detected in the arcade cell membrane of the mutant ( Fig 4E ) . This indicated the existence of membrane or cortex defects specifically in the arcade cells of the nxf-1 ( t2160ts ) mutant . To further assess whether epithelialization defects in arcade cells caused the Pun phenotype in nxf-1 ( t2160ts ) mutants , we monitored the localization of the fluorescent reporter for the C . elegans apical surface polarization protein PAR-6/Par-6 and the expression and localization of C . elegans apical junction ( CeAJ ) components ( Fig 4F , S3A Fig ) : the classical cadherin-catenin complex ( HMR-1/E-cadherin , JAC-1/p120-catenin , HMP-1/alpha-catenin ) and the more basal AJM-1 , DLG-1/disk large complex and SAX-7/L1CAM that has been proposed to function as a transmembrane component of this complex ( S3 and S4 Figs ) [57] . Partial loss of NXF-1 activity affected normal expression of CeAJ proteins . We detected a strong increase in DLG-1::dsRed expression and a moderate decrease of AJM-1::GFP , SAX-7::GFP and HMR-1::GFP expression in both the epidermis and the gut , that may be a direct consequence of the less efficient export of transgenic mRNA in the nxf-1 ( t2160ts ) mutant . However , the more dramatic change in nxf-1 ( t2160ts ) mutants was the absence of apical junctions in the arcade cells and the mislocalization of the PAR-6 polarity protein that shows an ectopic and non-polarized localization in arcade cells and also , to a lesser degree , in pharyngeal and intestinal cells as occurs in WT ( Fig 4F , S5 Fig ) , indicating that NXF-1 is essential for arcade cells to form a polarized epithelium . In addition , proper epidermal morphogenesis was disrupted , and some cells failed to adopt their normal elongated form ( Fig 4 , S3 Fig , S4 Fig ) . Finally , to determine whether other epithelia , such as intestine , could also be affected to a lesser extent , we analyzed WT and nxf-1 ( t2160ts ) L1 larvae intestinal morphology . Although the mutants showed a fully developed intestine , their morphology was not completely normal and showed a wider lumen than in the WT , all along the gut duct . This defect was already detectable during embryogenesis ( S6 Fig ) , indicating that although less sensitive than arcade and hypodermal cells , intestinal epithelia is also affected by limited mRNA export . In summary , a partial loss of activity in the nxf-1 ( t2160ts ) mutant predominantly affects epithelial tissues ( mainly arcade cells ) causing pharynx attachment defects and body elongation arrest by affecting cell-cell membrane contacts but not cell differentiation . To discern whether the unattached pharynx and body elongation defects observed in nxf-1 ( t2160ts ) mutants were due to a specific function in morphogenesis or to impaired mRNA export in tissues with a high demand of mRNA , we knocked down other mRNA export machinery components and evaluated both phenotypes . Thus , we depleted NXT-1/p15 and the DEAD-box helicase , HEL-1/UAP56 by RNAi . NXT-1/p15 is an ortholog of the Ran-GDP-binding nuclear transport factors NXT1 and NXT2 , that heterodimerize with NXF-1 to bind to nucleoporins and facilitate export of poly ( A ) RNA [2 , 58 , 59] . HEL-1/UAP56 is a DEAD-box helicase , essential for mRNA export in C . elegans [59 , 60] ( Fig 5 ) . L1 larvae of the strain ST65 ( ncIs13[ajm-1::GFP] ) [61] , expressing AJM-1::GFP , fed with RNAi clones of the nxf-1 and hel-1 genes , arrested at the L2 stage . L1 animals depleted of NXT-1 reached adulthood but were sterile and 50% of them showed protruding vulva ( S7 Fig ) . When the RNAi experiment started at the L4 stage , all the worms progressed to adulthood and laid eggs that arrested at early embryonic stages [41 , 59] . To obtain a partial reduction of the mRNA export activity , we performed RNAi experiments by feeding L4 stage worms with bacterial nxf-1 and nxt-1 RNAi diluted with L4440 ( bacterial RNAi empty vector ) at a 1:1 ratio for a “milder” RNAi effect . F1 embryos developed further and died at later stages . 71% ( n = 28 ) of the nxf-1 RNAi embryos , 62% ( n = 29 ) of the nxt-1 RNAi embryos and 27% of the hel-1 RNAi ( L4 normal conditions ) embryos showed unattached pharynxes with missing expression of AJM-1::GFP in arcade cells and body elongation defects ( Fig 5 , Table 1 ) . Thus , we concluded that inhibition of the mRNA export machinery by RNAi depletion of its individual components leads to a catastrophic arrest during development . In contrast , a partial reduction in mRNA export predominantly affects epithelial tissues , mainly arcade cells , causing pharynx attachment defects and body elongation arrest . To assess whether other proteins involved in mRNA biogenesis and processing also affect embryonic morphogenesis in C . elegans , we knocked down components of the exon junction complex ( EJC ) and scored the unattached pharynx and body elongation defects . The EJC complex remains stably bound within mRNPs and serves as a binding platform for factors involved in mRNA packaging , export , translation and nonsense-mediated decay ( NMD ) . Depletion of C . elegans EJC has a partial effect on mRNA splicing fidelity [62] . This complex provides a link between several steps of the mRNA life cycle [reviewed in: 63 , 64 , 65] . L1 larvae of the transgenic strain ST65 ( ncIs13[ajm-1::GFP] ) [61] , expressing AJM-1::GFP , were fed with RNAi clones of the genes mag-1/Mago-nashi and its binding partner rnp-4/Y14 ( components of the C . elegans EJC ) [66] . Depletion of these two genes caused lethality of the F1 embryos which arrested with elongation defects [this study , 59 , 66] . Depletion of RNP-4/Y14 did not cause nuclear accumulation of poly ( A ) RNAs , suggesting that C . elegans Y14 orthologue plays an essential role in C . elegans development , but is not directly associated with mRNA export [59] . The AJM::GFP reporter showed that the hypodermis was disorganized in these embryos . In contrast , pharyngeal and intestinal tissues were evident in those arrested embryos . The CeAJ in the foregut was properly formed and the pharynx was completely elongated ( Fig 5 ) . Our results indicate that whereas the epidermis is highly sensitive to different processes affecting mRNA metabolism , such as biogenesis , processing or export , arcade cells are specifically more sensitive to mRNA export defects . This suggests the existence of different mechanisms for epithelialization or different levels of mRNA requirements for the different types of epithelia during morphogenesis . To further explore the consequences of reducing the activity of nxf-1 in other tissues , we expanded the analysis to the C . elegans germline . Oocyte production requires high levels of transcription and translation to accumulate enough maternal product for embryonic development [67 , 68] . DAPI staining of gonads at the one-day adult stage shows that the number of mitotic germ cells was strongly reduced in the nxf-1 ( t2160ts ) mutant ( Fig 6 ) . N2 and nxf-1 ( t2160ts ) worms were grown at 15°C until the L4 larval stage and then moved overnight to 25°C before scoring the gonad nuclei . The mitotic region of nxf-1 ( t2160ts ) gonads had 105 . 9±3 . 4 nuclei ( mean±standard error/SE ) ( n = 20 ) , which is half the number of nuclei in the mitotic region of WT worms 205 . 36±2 . 9 ( mean±SE ) ( n = 11 ) grown under the same conditions . In C . elegans , germline proliferation is governed by GLP-1/Notch-receptor and other effectors that mediate the transition from mitosis to meiosis [69 , 70] . Although , we did not find significant differences between gene expression of those factors in nxf-1 ( t2160ts ) vs WT nematodes ( S8 Fig ) , the inefficient transport of their mRNAs to the cytoplasm could affect the extension of the mitotic region . The number of nuclei in mitosis was determined by counting phosphorylated histone H3 ( pH3 ) -positive nuclei in dissected gonads . Immunostaining with an anti-pH3 antibody marks cells in the late M phase [71] . This reduction in phosphorylated histone H3 is not caused by a lower level of histone expression ( S9 Fig ) but likely reflects the less proliferative state of the nxf-1 ( t2160ts ) mutant gonad . The reduction of the average number of mitotic cells observed in nxf-1 ( t2160ts ) ( 3 . 58±0 . 36 ( mean±SE ) ( n = 29 ) ) versus the WT ( 8 . 88±0 . 69 ( mean±SE ) ( n = 18 ) ) further confirmed the diminished germline proliferation in the nxf-1 ( t2160ts ) mutant ( Fig 6 ) . As a canonical cell cycle progression mechanism , CDC25 dephosphorylates CDK1 to allow entry into mitosis . In C . elegans , CDK-1 is phosphorylated at the Tyr15 inhibitory residue upon DNA damage [72 , 73] . Phosphorylation of tyrosine ( Tyr15 ) and threonine ( Thr14 ) in the ATP-binding loop of CDK-1 prevents activation of the CDK/cyclin complex hindering entry into mitosis . To understand how loss of function of nxf-1 disrupts the mitotic cell cycle , we performed immunostaining of adult gonads with antibodies against phosphorylated Tyr15 CDK-1 . Our results showed an increase in Tyr15 phosphorylation of CDK-1 in the nuclei of the gonadal proliferative region of nxf-1 ( t2160ts ) mutant animals ( S10 Fig ) . This increase was higher than that caused by irradiation with ionizing radiation ( IR ) in WT animals . The absence of significant changes in the expression of cdc-25 or cdk-1 ( S9 Fig ) in nxf-1 ( t2160ts ) vs WT and immunostaining with antibodies specific to phosphorylated proteins suggests that the reduction in germline proliferation is achieved by control of the cell cycle machinery by phosphorylation . To further check whether cell cycle impairment was an nxf-1 ( t2160ts ) -specific phenotype or a consequence of reduced RNA export , we assayed other genes involved in RNA export . RNAi depletion of the DEAD-box helicase HEL-1/UAP56 also increased Tyr15 phosphorylation of CDK-1 in the gonadal proliferative region ( S10 Fig ) . We next extended the analysis of cell proliferation to the cell cycle progression in the developing embryo . Consistent with the results observed in the gonad , 4D microscopic analysis shows that embryonic cell division is significantly slower in nxf-1 ( t2160ts ) mutants compared to WT embryos under the same conditions ( Fig 7 ) . Taken together , these results suggest that RNA export reduction impairs mitotic cell cycle progression in C . elegans . Since the germline mitotic rate was reduced upon RNA export impairment , we further investigated its role in maintenance of meiosis . The RAD-51 protein is involved in DNA repair by homologous recombination and it is a marker of double-strand breaks ( DSBs ) undergoing processing [74 , 75] . Although the expression of rad-51 was not affected by nxf-1 ( t2160ts ) mutation ( S9 Fig ) , we observed a massive accumulation of RAD-51 in the pachytene/diplotene region of nxf-1 ( t2160ts ) mutant gonads ( S11 Fig ) . However , depletion of hel-1 by RNAi did not produce similar RAD-51 foci ( S11 Fig ) . This result suggests that this phenotype is not directly caused by the reduction of RNA export , but instead may reveal an additional function of nxf-1 in genome stability . Once nuclei enter the meiotic pathway and complete the premeiotic S-phase , physiological double-strand breaks ( DSBs ) are generated through the action of a specialized topoisomerase enzyme SPO-11 [76] . Chromosomes align and synapse , and recombination is largely completed by late pachytene . This mechanism for initiation of meiotic recombination is conserved throughout eukaryotes . As a consequence , RAD-51 foci fail to form in spo-11 mutants , indicative of an absence of DSBs [76] . To assay whether the increased levels of RAD-51 in nxf-1 ( t2160ts ) mutants were due to a deregulation of SPO-11 activity , we knocked down spo-11 by RNAi in an nxf-1 ( t2160ts ) mutant background . Depletion of spo-11 did not suppress the formation of RAD-51 foci in the nxf-1 ( t2160ts ) mutant , indicating that they are independent of SPO- 11 activity ( S11 Fig ) . To gain insight into the transcriptional consequences of reducing mRNA export , we performed RNA-seq analysis of nxf-1 ( t2160ts ) mutant worms and compared the gene expression profile to that of N2 WT worms . Since nxf-1 ( t2160ts ) is a temperature sensitive mutant , synchronized one-day old adult-stage WT and nxf-1 ( t2160ts ) worms grown at 15°C were shifted to 25°C for 12–16 hours before RNA extraction . Three biological replicas of each analysis were performed . RNA extraction , deep sequencing and quantitative differential expression analysis were performed as described in Material and Methods . Raw sequence data generated in this study are available at the Gene Expression Omnibus ( GEO ) data repository ( Accession number GSE116737 ) . Statistical analysis with the DeSeq and Edger bioinformatics algorithms showed 1117 statistically significant downregulated genes and 834 statistically significant upregulated genes in nxf-1 ( t2160ts ) mutants vs WT ( S12 Fig ) . Our KEGG pathway analysis [77] of these sets of genes revealed that mRNA export reduction in the nxf-1 ( t2160ts ) mutant led to activation of RNA transport and mRNA surveillance pathways . nxf-1 expression itself , its binding partner nxt-1/p15 and other genes involved in RNA transport are significantly upregulated when nxf-1 ( t2160ts ) is mutated . This result likely suggests the existence of a transcriptional feedback mechanism that activates mRNA export in response to low levels of cytoplasmic RNA . Similar transcription-translation feedback loops ( TTFL ) in which genes are transcribed until their protein products accumulate and are transported into the nucleus , thus inhibiting positive elements from the promoter region of the gene so that transcription is halted , have been described from yeast to mammals [78 , 79 , 80 , 81 , 82] . Consistently , genes involved in other aspects of the RNA life cycle such as ribosome biogenesis pathways appear as significantly downregulated , which again suggests a regulatory transcriptional response to adapt the number of ribosomes to the few transcripts available in the cytoplasm ( Table 2 , S1 Table , S2 Table , S12 Fig ) . In addition , a Gene Ontology analysis [77] of the same sets of differentially expressed genes revealed that they do not randomly fall within different molecular function categories . Instead , the significantly upregulated set in the nxf-1 mutant is highly enriched for GTPase binding , RasGTPase binding , small GTPase binding , actin binding and cytoskeleton protein binding genes . On the other hand , the set of significantly downregulated genes is enriched in genes involved in oxidative phosphorylation and mitochondrial ATP synthesis ( Table 2 , S12 Fig ) . These results suggest that reduction of mRNA export has a deep impact on cytoskeletal dynamics that could underlie the nxf-1 ( t2160ts ) epidermal and mitochondrial defects . These results prompted us to specifically study the cytoskeleton and mitochondrial network in the nxf-1 ( t2160ts ) mutant . Cytoskeletal growth and rearrangement require the translation of specific mRNAs that code for structural components and regulatory proteins connected to the cytoskeleton [83] . To examine the actin filament network in WT and nxf-1 ( t2160ts ) embryos , we used phalloidin staining . Whereas WT embryos accumulated actin at the nascent apical surface at the onset of epithelialization , we observed a decrease in filamentous actin ( F-actin ) staining in the mutant . In addition , actin remained dispersed in the arcade cells of nxf-1 ( t2160ts ) embryos compared to WT ( Fig 8 ) . Next , we evaluated the mitochondrial network morphology by discriminating between four types of mitochondrial shapes: connected , intermediate , fragmented and very fragmented [84] . C . elegans WT embryonic cells show a connected mitochondrial network in their cytoplasm ( S13 Fig ) . In contrast , nxf-1 ( t2160ts ) embryos grown at 25°C showed a general dotted pattern of Mitotracker staining in their cytoplasm , indicating the additional presence of fragmented-type mitochondria ( S13 Fig ) . To further validate this observation , we analyzed mitochondrial morphology in adult muscle cells , a tissue where mitochondria are highly abundant and evident . To do so , animals were grown for 8 days at 25°C and scored at day 1 post L4 , day 4 and day 8 . 64% ( n = 47 ) of the nxf-1 ( t2160ts ) body wall muscle cells already showed a fragmented pattern of mitochondrial network at day 1 ( S14 Fig ) . A higher percentage ( 76% ) ( n = 46 ) of nxf-1 ( t2160ts ) muscle cells still had the fragmented phenotype at day 8 , whereas in WT worms , only 14% ( n = 21 ) of muscle cells showed this mitochondrial morphology ( S14 Fig ) . This fragmented mitochondrial network observed in nxf-1 ( t2160ts ) is detectable in different types of embryonic cells and not restricted to epithelia . Therefore , it does not seem to be the cause of morphogenetic defects but rather a result of cytoskeletal defects [85] . These data , as a whole , point to a model in which the decrease in cytoplasmic mRNA available for actin rearrangement could explain the reduction and disorganization of the actin cytoskeletal network in nxf-1 ( t2160ts ) mutant embryos , leading to cell attachment and elongation defects [86 , 87] . The transcriptional activation of genes coding for small GTPase , actin and cytoskeleton binding proteins further supports the existence of a transcriptional feedback mechanism that activates the expression of those genes in response to the cellular requirements of cytoskeletal rearrangements . To get deeper insight into the molecular mechanism by which NXF-1 acts in the cell , we identified C . elegans NXF-1 co-immunoprecipitated protein partners using LC-MS/MS ( liquid chromatography-mass spectrometry/mass spectrometry ) . We expressed NXF-1::3xFLAG::eGFP to immunoprecipitate NXF-1 along with its protein partners and used the N2 WT strain as the negative control . Immunoprecipitations ( IPs ) from three replicate JCP519 and N2 worm extracts were eluted from the beads by competitive elution with the 3xFLAG peptide . Next , immunoprecipitates were resolved by SDS-PAGE , and stained with Coomassie Blue . Proteins were identified by LC-MS/MS ( Table 3 ) . Co-immunoprecipitated proteins fall into the following two main categories:
The formation and maintenance of specialized organs depend on developmental signaling pathways that regulate cell proliferation and differentiation , as well as establishment of the correct architecture by regulating cell-cell adhesion , cytoskeletal organization and apical-basal polarity within the constituent cells . For this to happen , gene expression has to be tightly regulated in all the steps; from transcription to mRNA export and translation [1 , 3] . Three levels of regulation control formation of the arcade cell epithelium: first , the transcriptional level; second , the level of protein expression; and third , the protein localization to nascent adherens junctions [36] . Nuclear export factor 1 ( NXF-1 ) , but not its ortholog , NXF-2 , has been shown to play an essential role in mRNA export in C . elegans [41 , 59 , 60] . However , the consequence of NXF-1 partial loss-of-function was not examined previously . Isolation of the nxf-1 ( t2160ts ) thermo-sensitive mutant provides an invaluable tool for analyzing the spatial and temporal in vivo role of mRNA transport during development . nxf-1 ( t2160ts ) mutation results in mRNA accumulation in all cell nuclei . This inability to export mRNA primarily disrupts epidermal and pharyngeal morphogenesis during embryonic development . Mutant embryos do not elongate properly and show problems with epidermal cell organization . In addition , although the pharynx was evident and the pharyngeal lumen was visible , in most of the cases ( 87 . 5% , n = 176 ) it was unattached to the mouth . Our genetic analysis revealed that the observed phenotypes were not the result of cell fate mis-specification , but rather cell morphogenetic defects . Expression of pha-4 , a transcription factor that regulates pharyngeal development [46 , 100]; myo-2/Myosin-3 , pharyngeal muscle myosin [44] and ric-19/ICA1 , which is expressed in nervous system [45] , revealed that the fate of major pharyngeal components was properly specified . In contrast , expression of membrane-tagged GFP [32 , 56] and the apical junction markers: PAR-6/PARD6A; DLG-1/Discs large [101 , 102]; AJM-1 [62] and HMR-1/E-cadherin [103] indicated that Pun pharynxes of nxf-1 ( t2160ts ) animals are possibly a result of lost cell polarity and failed epithelialization of arcade cells . Similar expression patterns of apical markers have been observed in pha-1 mutants [104] . These developmental defects do not reflect a specific function of NXF-1 , but rather the consequence of the reduction of mRNA export . Disruption of other nuclear export factors such as NXT-1/p15 and HEL-1/UAP56 also led to similar embryonic lethality , epidermal defects and the Pun phenotype . Thus , although it affects all cells , hypodermal and especially pharyngeal development seem to be particularly sensitive to a reduction in the efficiency of mRNA export . The arcade cell epithelium forms extremely rapidly , in less than 10 min , while epidermal epithelialization takes over 30 min [32 , 33] . Therefore , pharyngeal morphogenesis probably requires extremely tight temporal control over the differentiation process . As a consequence of the low amount of cytoplasmic mRNA , nxf-1 mutation causes upregulation of genes involved in mRNA export and downregulation of ribosomal RNAs . aly-1/ALYREF , eef-1A . 2/EEF1A1 , npp-14/NUP214 , npp-21/TPR , nxt-1/p15 and nxf-1 itself , among others , appear significantly upregulated in nxf-1 ( t2160ts ) worms compared to WT N2 animals ( S1 Table , S2 Table ) . Such a feedback mechanism has also been described in Drosophila Schneider cells ( S2 cells ) in which blocking the NXF1-mediated mRNA export pathway results in upregulation of export factors [105] . A similar feedback regulatory mechanism also seems to operate for genes involved in cytoskeletal rearrangement . nxf-1 loss of function causes the lack of an apical junction in arcade cells ( Fig 5 , S3 Fig , S4 Fig ) and a dramatic reduction in filamentous actin in nxf-1 mutant embryos ( Fig 8 ) . Our transcriptomic analysis shows a significant upregulation of genes involved in cytoskeletal maintenance: GTPase binding , Ras GTPase binding , small GTPase binding , Rho GTPase binding , actin binding , and cytoskeletal binding proteins . This overexpression likely occurs as a feedback mechanism due to an insufficiency of cytoplasmic mRNAs necessary for cytoskeletal maintenance and rearrangement . Transcriptional activation of these genes is indeed a critical step during epithelial polarization and cytoskeletal reorganization [87] . Studies in Drosophila suggest a functional connection between SBR/NXF1 and the cytoskeleton [106] . In early D . melanogaster embryos , SBR/NXF1 marks the spindles of dividing nuclei [107] . We found the HCP-1/CAGE1 protein among the NXF-1 interactors in the immuno-precipitation experiments . HCP-1 is a centromere-associated protein involved in the fidelity of chromosome segregation [108] . The key role of HCP-1 is to target CLS-2/CLASP to kinetochores which promote the polymerization of kinetochore-bound microtubules [109] . Detection of HCP-1 suggests that NXF-1 may play a role in mitotic spindle assembly independently of mRNA transport . This functional connection between NXF1 and the embryonic mitotic spindle may underlie the slow cell division rate and the DNA breaks observed in C . elegans nxf-1 ( t2160ts ) mutants . D . melanogaster sbr10 and sbr5 mutants have morphological spindle defects in their first meiotic division [110] . Moreover , the sterile males of sbr12 mutant flies display immobile spermatozoa which exhibit disturbances in mitochondrial morphology and cytokinesis similar to those described here [106 , 107] . In addition to the defects in epidermal and pharyngeal morphogenesis , nxf-1 loss of function reduces the gonadal mitotic regions in C . elegans . The reduced number of mitotic germ cells in nxf-1 ( t2160ts ) animals and the small number of cells in M-phase could be explained by mitotic delay of cells entering into the M-phase , which leads to mitotic defects and increased CDK-1 phosphorylation levels ( Fig 6 , S10 Fig ) . C . elegans germline proliferation is governed by GLP-1/Notch-receptor and other regulators [69 , 70] . Our results suggest that efficient mRNA export of those and/or other factors is key to proper mitotic progression in the C . elegans gonad . Thus , knockdown of HEL-1/UAP56 also leads to increased CDK-1 phosphorylation levels ( S10 Fig ) . Interestingly , UAP56/HEL-1 associates with the mitotic apparatus in HeLa cells . When UAP56/HEL-1 was knocked down , chromosome misalignment and mitotic delay at prometaphase were frequently observed in mitotic cells . Chromosome misalignment causes activation of the spindle assembly checkpoint ( SAC ) which arrests mitotic progression at prometaphase [111] . Interestingly , not only mitosis but also meiosis is affected in nxf-1 ( t2160ts ) animals . The massive accumulation of RAD-51 foci in the meiotic region suggests the existence of multiple DNA breaks . Importantly , knockdown of other mRNA export factors such as HEL-1/UAP56 does not lead to the same accumulation of RAD-51 foci , suggesting that they are not caused by the lack of mRNA export ( S11 Fig ) . These breaks could form as a consequence of the impaired cytoskeleton dynamics during chromosome pairing or could reflect the existence of torsional stress at the DNA fiber level upon NXF-1 downregulation . This mechanical stress activates ATR which seems to modulate nuclear envelope plasticity and to promote chromatin detachment from the nuclear envelope [112 , 113] . Unexpectedly , high levels of mRNA from a transgene containing the hsp-16 . 2 promoter , GFP , and the unc-54 3’UTR ( hsp-16 . 2::gfp::unc-54 ( 3’UTR ) ) , has been detected in the so-called “expression zone” [26] that overlaps with the region where we see the meiotic RAD-51 accumulation in the nxf-1 ( t2160ts ) mutant . Additional studies in C . elegans show that the heat shock hsp-16 . 2 gene promoter relocates to the nuclear periphery after heat shock [114] . These findings suggest the existence of a yet unknown stress response mechanism in the late pachytene/diplotene germ cells . In summary , mRNA export is required in all tissues and organs . However epithelial cells that undergo a rapid morphogenetic transformation during development ( such as arcade cells and epidermis ) and the germline ( the only proliferative tissue in adult nematodes ) appear to be highly sensitive to reductions in the mRNA export rate in C . elegans . Many proteins involved in mRNA export have been implicated in cancer , developmental and neural diseases [1 , 115 , 116 , 117 , 118 , 119] . It has been shown that NPC can be reprogrammed as part of the oncogenic transformation process , the result of a viral infection or during oxidative and metabolic stress [1 , 8] . Interestingly , bioinformatic research predicts NXF1 to be a probable tumor suppressor gene ( TSG ) [120] . A deeper understanding of the processes involved in mRNA export from nucleus to cytoplasm is required . Basic aspects of their relationship to stress and DNA damage response remain an open question . This knowledge will shed light on many aspects of biology ranging from cell differentiation to morphogenesis and disease .
Standard methods were used to culture and manipulate C . elegans strains [121] . Worms were grown on NGM ( nematode growth media ) agar plates . Plates were previously seeded with an LB ( Luria-Bertani ) liquid culture of the Escherichia coli strain OP50 ( Uracil auxotroph , E . coli B . , ampicillin resistant from CGC ) overnight at 37°C ( ampicillin ( 100 mg/ml ) and nystatin ( 0 . 004% ) ) , and air-dried . When larger amounts of worms were needed ( for IP experiments ) , egg-seeded plates were used . Egg plates were prepared as described [122] . Normal NGM plates were seeded with 5ml egg mix and air-dried . In this study , worms were grown at 15°C and 25°C . The nxf-1 ( t2160ts ) mutant is temperature sensitive so it was maintained at 15°C . Before all experiments , worms were shifted to the non-permissive temperature of 25°C . The C . elegans strains used in this study are listed in S3 Table . Their genotypes , characteristics and sources are shown . 3D FISH protocol [123] was followed . Embryos were fixed on slides using the freeze-crack procedure . For hybridization , the probe against the poly-A sequence of mRNA ( 40T ) labeled with Cy3 fluorochrome ( Sigma ) was added to the hybridization buffer and slides were incubated for 2–3 days at 37°C . Phalloidin staining [124] was performed . Embryos were fixed on slides using the freeze-crack procedure . After cracking , eggs were fixed for 20 minutes in fix/permeabilization solution ( 4% PFA; 0 . 2% Triton X-100; 50mM PIPES pH 6 . 8; 25mM HEPES pH 6 . 8; 10 . 2mM EGTA; 2mM MgCl2 ) , then slides were rehydrated/permeabilized by three 5-minute washes in 1X PBS in a Coplin jar , followed by 90 minutes of incubation with CytoPainter Phallooidin-iFluor 488 solution ( Abcam ) . Slides were washed 2 times in 1X PBS and mounted by adding a drop of ProLongTM Diamond Antifade Mountant with DAPI ( Invitrogen ) . Young adult worms were dissected in dissection buffer ( 1X egg buffer , 0 . 02% Tween-20 , 0 . 2mM Levamisole and Milli-Q H2O ) . Dissected gonads on slides were fixed in fixation buffer ( 1X egg buffer , 0 . 02% Tween-20 , 4% formaldehyde and Milli-Q H2O ) covered with a coverslip ( 24x24 mm ) , incubated for 5 minutes and dipped in liquid nitrogen . Coverslips were flipped away and slides were incubated in Coplin jars in precooled ( -20°C ) 1:1 acetone: methanol solution for 10 minutes . Next , slides were washed three times ( 10 minutes each ) in 1% Triton PBS buffer followed by another 5-minute wash with 0 . 1% Tween-20 PBS . Samples were blocked for 20–30 minutes in a Coplin jar with 10% fetal bovine serum diluted in 0 . 1% Tween PBS . Slides were pre-blocked for 20–30 minutes using Image- iT FX Signal Enhancer ( Invitrogen ) . Slides were incubated with the desired first antibody , washed three times ( 10 minutes each ) in 1% Triton PBS buffer , stained with the appropriate secondary antibody , and mounted by adding a drop of ProLongTM Diamond Antifade Mountant with DAPI ( Invitrogen ) . The following antibodies were used: anti-RAD-51 ( 1:10000 , SDIX 2948 . 00 . 02 ) ; anti-pH3 ( detects pSer 10 H3 , 1:400 , Santa Cruz Biotechnology sc-8656R ) ; anti-pTyr15 CDK-1 ( 1:10000 , CALBIOCHEM 213940 ) ; goat anti-rabbit IgG ( H+L ) , Alexa Fluor 555 ( 1:1000 , Thermo Fisher Scientific ) ; goat anti-rabbit IgG ( H+L ) , Alexa Fluor 488 ( 1:1000 , Thermo Fisher Scientific ) . In order to immunoprecipitate NXF-1 and Co-IP their interactors , protein extracts from JCP519 ( nxf-1 ( t2160ts ) V; jcpEx6[pAZ09 ( Pnxf-1::nxf-1::3xFLAG::eGFP::nxf-1UTR ) ] ) , were used . Extracts from WT worms were used as the negative control . A large amount of protein extract was needed , and thus 8 to 10 NGM egg plates were used . Protein extracts were measured using the BCA Protein Assay Kit ( Fisher Scientific ) according to the manufacturer’s instructions . IP/Co-IPs were performed with Anti-FLAG M2 Magnetic Beads ( Sigma ) composed of the murine derived ANTI-FLAG M2 monoclonal antibodies attached to superparamagnetic iron impregnated 4% agarose beads . The eluted IPs were run on Mini-PROTEAN TGX Precast Gels by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) and proteins were separated according to their molecular weights [125] . Next , the gels were stained with Coomassie Blue and bands were excised . Proteomic analysis was performed at the CIC Biogune proteomics platform ( https://www . cicbiogune . es/org/plataformas/Proteomics ) . C . elegans biolistic bombardment was performed as described [121] , with few modifications . We used the Biolistic PDS-1000/He Particle Delivery System ( Bio-Rad ) . This system uses high-pressure helium , released by a rupture disk and a partial vacuum , to propel a macrocarrier sheet with millions of microscopic DNA-coated gold particles toward target worms at a high velocity . In this work , JCP495 ( nxf-1 ( t2160ts ) V ) was successfully rescued by bombardment with plasmids pAZ07 ( Pnxf-1::nxf-1::nxf-1UTR ) and pAZ09 ( Pnxf-1::nxf-1::3xFLAG::eGFP::nxf-1UTR ) ( S1 Fig ) . The JCP519 ( nxf-1 ( t2160ts ) V; jcpEx6[pAZ09 ( Pnxf-1::nxf-1::3xFLAG::eGFP::nxf-1UTR ) ] ) strain expressing NXF-1::3XFLAG::eGFP was generated by gene bombardment using the plasmid pAZ09 . In this study , RNAi was achieved by feeding worms with the bacteria that produced the desired dsRNA . RNAi clones of nxf-1 , hel-1 and rnp-4 ( our lab ) , as well as nxt-1 and mag-1 [126] were used in this study . The empty L4440 vector in HT115 cells was used as a control . For a “mild” RNAi effect , bacterial RNAi clones of nxf-1 and nxt-1 were diluted with L4440 at a 1:1 concentration . For microscope preparations , worms were monitored on NGM plates under a Leica Stereo microscope ( MZ16FA ) . DIC was performed on a fluorescent Leica microscope ( DM600B ) equipped with a Hamamatsu Orca-ER C10600 camera fitted with DIC optics . C . elegans embryos , larvae and adults were mounted on 4 . 5% agar pads and observed under DIC optics [127] . Images were captured with Micro-manager software ( https://micro-manager . org/ ) and processed with XnView software and ImajeJ or Fiji software . Confocal microscopy imaging was performed with a Zeiss 780 confocal microscope ( immunofluorescence and phalloidin staining experiments ) . Images were acquired and processed using ZEN lite open software from Zeiss and ImageJ/Fiji . Relative fluorescence image data obtained from ImageJ/Fiji was statistically analyzed with IBM SPSS Statistic 21 , and the representative graphs were created with GraphPad Prism 6 software . In this study , the nxf-1 ( t2160ts ) strain was backcrossed with the Hawaiian ( CB4856 ) strain . Around 3000 F2 recombinants ( t2160ts ) / ( Hawaiian-CB4856 ) were singled out . 560 thermo-sensitive F2 t2160ts/Hawaiian recombinants were obtained . Total DNA extraction of 560 C . elegans worms ( 560 recombinants ( t2160ts ) / ( Hawaiian-CB4856 ) ) was performed using the Plant/Fungi DNA Isolation Kit ( Norgen Biotek Corp . ) following the manufacturer’s instructions . This kit enabled us to isolate total DNA from a small number of worms . Using the Hawaiian single-nucleotide polymorphism ( SNP ) mapping method , we backcrossed the nxf-1 ( t2160ts ) mutant with the polymorphic Hawaiian strain [128] . Next , we isolated the newly generated F2 recombinants homozygous for the nxf-1 ( t2160ts ) mutation , ( Hawaiian-CB4856 ) /nxf-1 ( t2160ts ) . Using 205 ng genomic DNA obtained as described , sequencing libraries were constructed using the NEXTflex Rapid DNA-Seq Kit according to the manufacturer’s instructions ( Bioo Scientific ) . DNA quality and integrity were evaluated by Experion Automated Electrophoresis System ( Bio-Rad ) and the concentration was calculated using qPCR . Libraries were prepared at the genomic platform of the CIBIR ( http://cibir . es/es/plataformas-tecnologicas-y-servicios/genomica-y-bioinformatica ) and sequenced on an Illumina HiSeq 15000 . The quality of DNAseq results was assessed using FastQC ( http://www . bioinformatics . babraham . ac . uk/projects/fastqc/ ) . Paired-end 100-bp sequencing yielded a theoretical mean coverage of 245X of the C . elegans genome . The FastQ files were analyzed using a Cloud-Based Pipeline for Analysis of Mutant Genome Sequences ( Cloudmap tool , https://usegalaxy . org/u/gm2123/p/cloudmap ) with standard parameters following Cloudmap workflow [42] . Total RNA extraction from C . elegans worms was performed using the RNeasy Mini Kit ( Qiagen ) following the manufacturer’s instructions . Four 99x16 . 2 mm worm plates of nxf-1 ( t2160ts ) and WT worms were used . RNA deep sequencing was performed at the genomic platform of the CIBIR ( http://cibir . es/es/plataformas-tecnologicas-y-servicios/genomica-y-bioinformatica ) . Expression analysis was performed by DESeq2 [129] and edgeR [130] as described [131 , 132] . | The Central Dogma of Biology schematically highlights the transmission of genetic information stored in DNA , through RNA , to the formation of proteins . This general flow implicates RNA export from the nucleus to the cytoplasm and proper protein localization within the eukaryotic cell . Ultimately , proteins are the cell’s structural and catalytic functional units . As a result , cells differentiate into one cell type or another ( such as epithelial , muscle , neuron… ) and exhibit specific shape and functionality . Here we describe , in a C . elegans model , how mutations in genes involved in a general and ubiquitous mechanism , such as mRNA export , may result in tissue-specific developmental phenotypes that show up in processes that are highly demanding of cytoplasmic transcripts like epithelialization and gamete formation . A deep understanding of the mechanisms underlying the "connectors" shown in the Central Dogma of Biology is key both to unravel the general genetic control of an organism’s development and , at the same time , contribute to a better understanding of tissue-specific diseases . | [
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... | 2019 | Reduction of mRNA export unmasks different tissue sensitivities to low mRNA levels during Caenorhabditis elegans development |
Human endogenous retroviruses ( HERVs ) and other long terminal repeat ( LTR ) -type retrotransposons ( HERV/LTRs ) have regulatory elements that possibly influence the transcription of host genes . We systematically identified and characterized these regulatory elements based on publicly available datasets of ChIP-Seq of 97 transcription factors ( TFs ) provided by ENCODE and Roadmap Epigenomics projects . We determined transcription factor-binding sites ( TFBSs ) using the ChIP-Seq datasets and identified TFBSs observed on HERV/LTR sequences ( HERV-TFBSs ) . Overall , 794 , 972 HERV-TFBSs were identified . Subsequently , we identified “HERV/LTR-shared regulatory element ( HSRE ) , ” defined as a TF-binding motif in HERV-TFBSs , shared within a substantial fraction of a HERV/LTR type . HSREs could be an indication that the regulatory elements of HERV/LTRs are present before their insertions . We identified 2 , 201 HSREs , comprising specific associations of 354 HERV/LTRs and 84 TFs . Clustering analysis showed that HERV/LTRs can be grouped according to the TF binding patterns; HERV/LTR groups bounded to pluripotent TFs ( e . g . , SOX2 , POU5F1 , and NANOG ) , embryonic endoderm/mesendoderm TFs ( e . g . , GATA4/6 , SOX17 , and FOXA1/2 ) , hematopoietic TFs ( e . g . , SPI1 ( PU1 ) , GATA1/2 , and TAL1 ) , and CTCF were identified . Regulatory elements of HERV/LTRs tended to locate nearby and/or interact three-dimensionally with the genes involved in immune responses , indicating that the regulatory elements play an important role in controlling the immune regulatory network . Further , we demonstrated subgroup-specific TF binding within LTR7 , LTR5B , and LTR5_Hs , indicating that gains or losses of the regulatory elements occurred during genomic invasions of the HERV/LTRs . Finally , we constructed dbHERV-REs , an interactive database of HERV/LTR regulatory elements ( http://herv-tfbs . com/ ) . This study provides fundamental information in understanding the impact of HERV/LTRs on host transcription , and offers insights into the transcriptional modulation systems of HERV/LTRs and ancestral HERVs .
Transposable elements ( TEs ) are mobile genomic DNA sequences that occupy approximately half of the human genome and are capable of autonomous or non-autonomous replication [1] . TEs were initially thought to be parasitic , selfish , and junk DNA [2] . Decades of research accumulated evidences that some TEs are co-opted by the host and acquire new physiological functions as protein-coding/-non-coding genes and regulatory elements for host genes [3–15] . TEs have their own regulatory elements for transcription and replication [9–24] . Such TE-derived regulatory elements are abundant in the human genome and have various effects on transcriptional modulations of host genes as promoters , enhancers , and insulators [9–15 , 25–34] . Notably , numerous TE insertions sharing the same regulatory elements can affect multiple genes in a coordinate manner . Several studies have suggested that TE insertions have contributed to the rewiring and evolution of regulatory networks by recruiting multiple genes into the same regulatory circuit [10–15 , 33–37] . Human endogenous retroviruses ( HERVs ) and other long terminal repeat ( LTR ) -type retrotransposons ( HERV/LTRs ) are a class of TEs that developed through the infection of host germ cells by ancient retroviruses , followed by their transmission to the offspring ( referred to as endogenization ) [38] . HERV/LTRs ( and other retroviruses ) are composed of 5′- and 3′-LTR sequences , which modulate viral transcription and internal sequences containing viral genes [38] . In the host chromosome , HERV/LTRs are present either as a complete structure ( referred to as provirus ) or as a single LTR structure ( referred to as solo LTR ) [38] . HERV/LTRs occupy approximately 8% of the human genome [1] . HERVs have lost their replication and transposition activities in germ cells owing to the accumulation of mutations [38] . According to RepeatMasker ( 20-Mar-2009 ) ( http://www . repeatmasker . org/ ) , 375 and 130 types of LTRs and internal sequences of HERV/LTRs , respectively , have been discovered in the human genome . This indicates that HERV/LTRs show the greatest diversity for all classes of human TEs . HERV/LTRs are transcribed by the host machinery , including RNA polymerase II ( Pol II ) , and many regulatory elements bounded to Pol II-associated transcription factors ( TFs ) are present in LTR sequences [38] . HERV/LTRs show the highest enrichment in regulatory sequences such as open chromatin regions among all classes of human TEs [9 , 37] . Reflecting the considerable diversity of HERV/LTRs , each type of HERV/LTRs has various regulatory elements involved in regulating diverse host genes [9–15 , 20–24] . For instance , LTR7 insertions provide POU5F1- ( OCT4- ) , SOX2- , KLF4- , and NANOG-binding sites for protein-coding/non-coding genes , which are essential for maintaining pluripotency in embryonic stem ( ES ) and induced pluripotent stem ( iPS ) cells [10–13 , 39] . As a further example , MER41 insertions harboring STAT1- and IRF1-binding sites in several genes contribute to primate-specific interferon responses [14] . Clarifying the properties of HERV/LTRs regulatory elements provides a better understanding of their impact on host transcriptional regulation . We systematically identified and characterized regulatory elements derived from HERV/LTRs based on publicly available datasets of chromatin immunoprecipitation followed by sequencing ( ChIP-Seq ) of sequence-specific TFs . The ChIP-Seq datasets were provided by ENCODE [40] and Roadmap Epigenomics ( Roadmap ) ( Tsankov et al . [41] ) projects . Previous studies have comprehensively investigated regulatory elements of TEs ( including HERV/LTRs ) based on the ENCODE dataset [9 , 37 , 40] . Jacques et al . demonstrated that the majority of primate-specific regulatory sequences are derived from TEs [9] . Because this particular study was mainly focused on the dataset of DNase I hypersensitive sites ( DHSs ) , it provided limited insight into the specific associations of TEs and TFs [9] . Sundaram et al . showed specific associations of TEs and TFs using a dataset of ChIP-Seq for TFs [37] . However , the number of sequence-specific TFs investigated in that study was restricted ( 15 sequence-specific TFs ) owing to the focus on TFs for which ChIP-Seq was performed in both human and mouse cells to compare the binding profiles [37] . In the present study , we performed a more comprehensive study than earlier of regulatory elements on HERV/LTRs by evaluating 519 ChIP-Seq datasets of 97 sequence-specific TFs ( S1 and S8 Tables ) . Furthermore , we constructed dbHERV-REs , a database of HERV/LTR regulatory elements with an interactive interface ( http://herv-tfbs . com/ ) . This study provides fundamental information to understand the impact of HERV/LTRs on host transcription .
We analyzed 519 ChIP-Seq datasets provided by ENCODE and Roadmap ( S8 Table ) . The datasets included ChIP-Seq analysis of 97 sequence-specific and Pol II-associated TFs ( S1 Table ) . The ChIP-Seq experiments were performed using 94 cell types . Although ENCODE and Roadmap provided datasets of pre-determined ChIP-Seq peaks ( pre-determined TFBSs ) , there are substantial differences in analytical pipelines between the two projects ( S2 Table ) . Therefore , we determined ChIP-Seq peaks using a uniform analytical pipeline ( S1B Fig ) . When focusing on repetitive elements such as HERV/LTRs , it is important to check whether multiple mapped reads ( reads can be mapped to multiple genomic regions ) are excluded in data analysis of next generation sequencing [37 , 42] . If multiple mapped reads are not excluded , false positive peaks may be detected at regions that have sequences similar to those authentically bounded by the TF . If they are excluded , it is unfeasible to identify ChIP-Seq peaks on recently integrated HERV/LTRs that show low sequence divergence among the copies . Some studies on TEs excluded multiple mapped reads [9] , while others did not [10] . Therefore , we generated two types of ChIP-Seq peak datasets: all-read and unique-read TFBSs ( S1B Fig ) . All-read TFBSs are ChIP-Seq peaks that were determined with all reads mapped to the human reference genome . The unique-read TFBSs are ChIP-Seq peaks that were determined with only the reads uniquely mapped to the reference genome; in other words , multiple mapped reads were excluded before the peak calling of ChIP-Seq . Consequently , we identified 7 , 262 , 985 and 6 , 833 , 767 of all- and unique-read TFBSs , respectively ( S2A Fig ) ; for estimating the numbers , overlapped TFBSs of the same TF were merged among cell types . Detailed information on ChIP-Seq is summarized in S8 and S9 Tables . We identified TFBSs observed on HERV/LTR sequences ( HERV-TFBS overlaps ( HERV-TFBSs ) ) belonging to the all- and unique-read TFBSs ( Fig 1A ) . We first identified HERV-TFBSs in each cell type , and then merged HERV-TFBSs of the same TF in all cell types ( merged HERV-TFBSs ) . Thus , we identified 866 , 649 merged HERV-TFBSs from all-read TFBSs and 794 , 972 from unique-read TFBSs ( S2A Fig ) . HERV-TFBSs respectively occupied 11 . 9% and 11 . 6% of entire TFBSs in all- and unique-read TFBSs ( S2A Fig ) . To evaluate the differences between all- and unique-read TFBSs , we compared the number of HERV-TFBSs for both the TFBS datasets . In most HERV/LTR types , the numbers of HERV-TFBSs were approximately the same for all- and unique-read TFBSs; however , the difference was quite large for some HERV/LTR types such as LTR7 and LTR5_Hs ( S3A , S3C and S3D Fig ) . These HERV/LTR types were recently inserted [see dbHERV-REs ( http://herv-tfbs . com ) ] and showed low ‘genomic mappability’ ( sequence uniqueness ) ( S3B and S3E Fig ) . Therefore , a substantial number of sequence reads was not uniquely mapped on the HERV/LTRs and was discarded . Based on these results , we generally used unique-read TFBSs for further analyses . When we individually focused on HERV/LTR types with low genomic mappability , such as LTR7 and LTR5_Hs , we used all-read TFBSs . We compared HERV/LTRs with other classes of TEs with respect to the TF binding profiles . In the unique-read TFBSs , LINE , SINE , and DNA transposons were respectively overlapped to 15% , 16% , and 6% of the entire TFBSs ( S4A Fig ) . It is important to check whether a TF binds to a type of TE significantly more than expected , because TEs occupy a large fraction of the genome , and therefore , TF binding would be partially observed on the TEs regardless of the absence of a special association between the TEs and TFs . Therefore , we evaluated statistical enrichment of binding of a TF in respective types of TEs to random expectation . The enrichment of TF binding was measured using a randomization test shuffling genomic positions of TFBSs ( see Materials and Methods ) . Subsequently , we counted the number of TFs bounded significantly to a type of TE , and then the distribution was compared among the TE classes ( S4B Fig ) . We demonstrated that the number of TFs binding significantly to a TE type tended to be substantially higher in the HERV/LTR class than the other TE classes ( S4B Fig ) . In the other TE classes , a few TEs were bounded by a large number of TFs ( S4C Fig ) . Thus , HERV/LTRs were distinguished from the other TEs with respect to numbers of TF bindings . Previous studies reported the same tendency that HERV/LTRs have more regulatory sequences ( e . g . , DHSs and TFBSs ) than the other TEs [9 , 37] . To understand the characteristic patterns of TF binding to HERV/LTRs , we performed hierarchical clustering analysis based on statistical enrichments of TF binding to random expectation ( Fig 2A ) . Enrichment significance was measured for each combination between HERV/LTRs and TFBSs in respective cell types to consider the cell type-specific binding of TFs to HERV/LTRs . Fourteen HERV/LTR and TFBS clusters were identified ( Fig 2A ) , of which , we characterized 8 TFBS clusters ( TF_1–8 ) ( Fig 2B ) [40 , 41 , 43–45]: TF_1 contained TFBSs for FOXA1/2 , GATA4/6 , and SOX17 , which are critical for the differentiation of embryonic mesendoderm or endoderm . TF_2 contained TFBSs for POU5F1 , SOX2 , and NANOG , essential for pluripotency of ES and iPS cells . TF_3 contained TFBSs for GATA1/2 and TAL1 , essential in hematopoietic and leukemia cells . TF_4 contained SPI1 , which is critical for the differentiation of hematopoietic cells . TF_5 and TF_6 contained TFBSs for NFYA/B , USF1/2 , and other TFs expressed in a broad-range of cell types . TF_8 contained TFBSs for PAX5 and PBX3 , essential for the differentiation of B lymphocytes . TF_7 contained CTCF-binding sites found in all the cell types , which function as insulators and regulate chromatin architecture . We also characterized 9 HERV/LTR clusters ( HERV_1–9 ) ( Fig 2A–2C ) . HERV_1 was enriched in TF_1 ( endoderm TF cluster ) and TF_2 ( pluripotent TF cluster ) . HERV_2 was enriched in TF_2 ( pluripotent TF cluster ) . HERV_3 was enriched in TF_8 ( B-lymphocyte TF cluster ) . HERV_4 cluster was enriched in TF_5 cluster . HERV_5 and HERV_7 were enriched in TF_7 ( CTCF cluster ) . HERV_6 was enriched in TF_5 and TF_6 clusters . HERV_8 was enriched in TF_3 and TF_4 ( hematopoietic TF clusters ) . Lastly , HERV_9 was not enriched in most TFBSs . Taken together , we identified the characteristic clusters of HERV/LTRs by the hierarchical clustering analysis , indicating that HERV/LTR types can be classified based on their TFBSs . Each HERV/LTR cluster typically contained several HERV/LTR types belonging to different HERV/LTR families ( Fig 2C ) . This indicates that the pattern of HERV/LTR regulatory elements do not match their phylogenic classifications . TFBSs for FOXA1/2 , GATA4/6 , NANOG , POU5F1 , SP1 , GATA2 , TAL1 , MAX , USF1 , SPI1 , ZNF143 , and YY1 were enriched in various types of HERV/LTRs ( Fig 2A right ) . HERV/LTR-shared regulatory element ( HSRE ) was defined as a TF-binding motif identified in a substantial fraction of HERV-TFBSs at the same consensus position ( Fig 1 ) . HSREs can indicate that the regulatory elements of HERV/LTRs are present before their insertions into the respective genomic loci [46] . We identified HSREs according to a scheme shown in Fig 1 . HSREs were identified separately from ENCODE and Roadmap dataset . In total , 2 , 525 and 2 , 201 types of HSREs were respectively identified from all- and unique-read TFBSs . Regarding all-read TFBSs , HSREs comprised specific associations of 370 HERV/LTRs and 85 TFs . These HSREs were composed of 255 , 225 genomic loci and present in 21% of the total HERV-TFBSs and in 2 . 5% of the entire TFBSs ( S2A Fig ) . For unique-read TFBSs , HSREs comprised specific associations between 354 HERV/LTRs and 84 TFs . These HSREs were composed of 178 , 121 genomic loci and present in 17% of the total HERV-TFBSs and in 2 . 0% of the entire TFBSs ( S2A Fig ) . In most HERV/LTR types , the numbers of identified HSREs were approximately the same between unique- and all-read TFBSs; however , in HERV/LTR types with low genomic mappability ( e . g . , LTR7 and LTR5_Hs ) , more HSREs were identified from all-read TFBSs than unique-read TFBSs ( S2B and S2C Fig ) . This was consistent with the comparison of the number of HERV-TFBSs between the two datasets ( S3 Fig ) . Concerning HERV-TFBSs harboring HSREs , approximately half of HERV-TFBSs had more than one of TF-binding motif corresponding to HSRE ( S5A Fig ) . Most of the HSREs were identified in LTR sequences ( 87%; 1 , 935/2 , 201 combinations in unique-read TFBSs ) , and the others were identified in the internal sequences of HERV/LTRs ( 13%; 266/2 , 201 combinations ) . Large proportions of copies of LTR12 , LTR22 , LTR13 groups and LTR6B contained HSREs ( with respect to proportions of copies harboring HSREs , top 15 of HERV/LTRs are shown in Table 1 ) . Regarding TFs , MER41B , LTR13/13A , LTR8/8A , LTR10A/10F , LTR9/9B , and LTR5B/5_Hs contained various HSREs ( S5B Fig ) . HSREs were identified in both recently and anciently inserted HERV/LTRs , the latter of which was inserted into the genome of the common ancestor of the clade Eutheria ( S5C , S5D and S5E Fig ) . As degrees of divergences ( or ‘ages’ ) of HERV/LTRs increased , proportions of copies harboring HSREs decreased ( S5D Fig ) , indicating regulatory elements of ancient HERV/LTRs were more divergent than those of young HERV/LTRs . As in the case of HERV-TFBSs , HSREs bounded by TFs essential for pluripotent , embryonic endoderm , and hematopoietic cells were frequently identified in addition to CTCF ( S5F and S5G Fig ) . HSREs bounded by CTCF were frequently observed in internal sequences rather than LTR sequences ( S5H and S5I Fig ) . Regarding LTR2B , LTR5B , MER41B , and MLT1J , HSREs identified from unique-read TFBSs are shown in S6 Fig . Characteristics of HSREs in LTR7 identified from the Roadmap dataset are shown in Fig 3 . LTR7 showed low genomic mappability ( S3B Fig ) , and , therefore , the results of all-read TFBSs were considered ( those of unique-read TFBSs are shown in S7 Fig ) . LTR7 is an LTR sequence of the HERVH provirus belonging to the ERV1 family . In our clustering analysis , LTR7 belonged to the HERV_2 cluster , whose members were highly bounded by SOX2 , POU5F1 , and NANOG ( Fig 2 ) . These TFBSs were observed at approximately the same consensus positions of LTR7 among those copies ( Fig 3A and 3B ) . For example , a peak of SOX2 binding was observed at around the 150th nucleotide position on the consensus sequence of LTR7 ( Fig 3B ) . Splits of HERV-TFBS peaks were observed in NANOG , EOMES , and FOXA1/2 due to an insertion/deletion in multiple sequence alignment of LTR7 ( S8 Fig ) . TF-binding motifs in HERV-TFBSs were observed at approximately the same consensus position of LTR7 among those copies ( Fig 3C and 3D ) . We identified HSREs according to the scheme described in Fig 1 ( and Materials and Methods ) . To identify HSREs , we compared heights of the peaks between HERV-TFBSs and TF-binding motifs ( S9 Fig ) . If the peak of TF-binding motifs ( Fig 3C and 3D ) was higher than 60% of that of HERV-TFBSs ( Fig 3A and 3B ) , the set of TF-binding motifs was regarded as HSRE . We identified novel HSREs in LTR7 , such as EOMES , FOXA1/2 , and GATA6 , and confirmed the previous reports showing that NANOG- , SOX2- , and POU5F1-binding sites were shared across the LTR7 copies [10–13] . Although the HSREs of NANOG , EOMES , FOXA1 , and SOX2 were recaptured from unique-read TFBSs , the peaks of HERV-TFBSs in unique-read TFBSs were substantially lower than those in all-read TFBSs ( S7 Fig ) . Chromatin accessibilities evaluated by DHSs and chromatin states [47–49] showed that the regulatory elements of LTR7 were specifically active in ES cells ( Fig 3E and 3F ) , consistent with the results of previous studies [9–12 , 50] . To approach the evolutionary dynamics of HERV/LTR regulatory elements , we investigated heterogeneity of the regulatory elements . We focused on HSREs that was disproportionately present in a specific subgroup of a HERV/LTR type . LTR7 copies were classified into three main subgroups ( subgroups I , II , and III ) by phylogenetic analysis based on the sequences ( Fig 3G ) . Examining orthologous copies of LTR7 in primates indicated that these subgroups were inserted at different time points ( Fig 3H ) . NANOG- and EOMES-binding sites were uniformly present among the three subgroups ( Fig 3I ) . SOX2- and POU5F1-binding sites were found to be enriched in subgroup III , and FOXA1-binding sites ( and , to a certain extent , FOXA2- and GATA6-binding sites ) were enriched in subgroup II ( Fig 3I ) . We referred to the ChIP-Seq dataset provided by Ohnuki et al . [10] ( S10 Fig ) because this dataset contained ChIP-Seq of SOX2 , POU5F1 , and KLF4 in iPS cells , and the sequence read lengths ( 75-bp ) were much longer than those of ENCODE/Roadmap dataset ( 25- or 36-bp ) . We also referred to the ChIP-Seq data of NANOG in ES cells provided by Durruthy-Durruthy et al . [15] , performing 100-bp pair-ended sequencing ( S10 Fig ) . Genomic mappability of LTR7 substantially improved in the 75-bp sequencing compared with 36-bp ( S10A Fig ) . In this dataset , we demonstrated that binding of SOX2 , KLF4 , and POU5F1 were enriched in subgroup III ( S10D Fig ) . In particular , the enrichments were observed in both all- and unique-read TFBSs . POU5F1-binding motifs at positions corresponding to HSREs were enriched in subgroup III , while FOXA1/A2-binding motifs were excluded ( Fig 3J ) . To quantitatively compare TF binding among the subgroups , we counted the number of reads mapped on LTR7 copies and summed them in respective subgroups , and then we estimated the enrichment of the reads to input control in respective subgroups ( Fig 3K ) . In NANOG and EOMES , the enrichment was relatively higher in subgroup III although the reads were enriched in all the three subgroups . In SOX2 and POU5F1 , the reads were enriched in subgroup III . In FOXA1 ( and , to a certain extent , in FOXA2- and GATA6-binding sites ) , the reads were enriched in subgroup II . Thus , we demonstrated subgroup-specific TF binding in LTR7 . In a previous study , LTR7 copies were divided into transcriptionally active and inactive groups based on RNA-Seq using pluripotent cells [11] . We further demonstrated that the active LTR7 copies were enriched in the subgroup III ( S11 Fig ) . Some LTR7 copies fuse with host coding/noncoding genes and play an essential role in maintenance of cell pluripotency [10–12 , 39] . We demonstrated that most of the LTR7 copies comprising the chimeric transcripts belonged to the subgroup III ( S11 Fig ) . Finally , we attempted to estimate insertion dates ( i . e . , ages ) of proviruses of HERVH/LTR7 based on sequence comparison between 5′- and 3′-LTRs ( see Materials and Methods ) . As shown in Fig 3L , majority of the subgroup I , II , and , III seem to have been inserted in branch of the genera Catarrhini and Hominoidea and the span from the end of Hominoidea to the beginning of Homininae ( interquartile range of insertion dates; 29 . 7–42 . 0 , 19 . 4–31 . 1 , and 13 . 5–22 . 7 million years ago ( Mya ) , respectively ) . This is consistent with the insertion dates estimated by presence of orthologous copies in primates ( Fig 3H ) . We showed that regulatory elements of HERV/LTRs were different within the same HERV/LTR type ( Fig 3G–3K ) . In order to approach evolutionary dynamics of regulatory elements in HERV/LTRs , we examined changes in the regulatory elements in the LTR5 ( HERV-K/HML-2 ) group . LTR5 is composed of LTR5A , LTR5B , and LTR5_Hs . LTR5_Hs is the youngest HERV/LTR type , and a previous study reported that LTR5_Hs has regulatory elements for POU5F1 , SOX2 , and NANOG [21] . Also consistent with the results of a previous study [51] , phylogenetic analysis and examination of orthologous copies indicated that LTR5B was the oldest ancestral type , and LTR5A and LTR5_Hs were independently generated from LTR5B-like viruses ( Fig 4A and 4B ) . Here , we divided LTR5 into five groups ( groups I–V ) based on their phylogenetic relationship and the TFs binding to them ( Fig 4A , 4C and 4E ) . Group I was rarely bounded by TFs ( Fig 4C and 4E ) . Group II was bounded by SPI1 , TAL1 , and GATA1/2 , which are vital in hematopoietic cells . Group III was bounded by GATA4/6 , SOX17 , and FOXA1/2 , essential in embryonic endoderm cells , together with the hematopoietic TFs . Group IV was bounded by NANOG , MYC , POU5F1 , and SOX2 , which are critical in pluripotent cells , in addition to the hematopoietic and the endoderm TFs . In group V , which is the youngest group , binding levels of some hematopoietic TFs ( SPI1 and GATA1/2 ) and endoderm TFs ( GATA4/6 and SOX17 ) were low . These differences in TF binding correlated with the differences in TF-binding motifs at positions corresponding to the HSREs ( Fig 4D ) . Chromatin accessibilities evaluated by DHSs indicate that the cell specificity of LTR5 members shifted along with their gain/loss of TFBSs ( Fig 4F ) . Group I was not active in any cell types , as expected owing to the absence of the regulatory elements . Group II was active in K562 ( leukemia ) cells . Group III was active in HepG2 ( hepatoblastoma ) and A549 ( lung epithelial cancer ) cells , in addition to K562 cells . Group IV was active in H1-hESC ( ES ) cells , in addition to the above cells; group V was not active in K562 cells . We examined chromatin states [47–49] of HERV/LTRs with and without TFBSs/HSREs . Compared with the entire population of HERV/LTRs , HERV/LTRs harboring HERV-TFBSs or HSREs were enriched in promoter [transcription start site ( TSS ) and promoter flanking regions ( PF ) ] , enhancer ( E ) , weak enhancer ( WE ) , and CTCF-binding regions ( CTCF ) , but not in transcribed ( T ) and repressed ( R ) regions ( S12A Fig ) . The HERV/LTR types enriched in enhancer regions were different across different cell types ( S12B Fig ) . These differences seem to reflect the differences of their HSREs; LTR2B [9] , LTR7 [9 , 11 , 50] , MER41B , and LTR5B , which were respectively enriched in the enhancer regions of GM12878 , H1-hESC , K562/HeLa-S3 , and HepG2 cells , had HSREs bounded by TFs essential in the corresponding cell types ( S6A Fig , Fig 3A and 3B , S6C Fig and S6B Fig , respectively ) . Unlike enhancers , HERV/LTRs enriched in CTCF-binding regions remained unchanged among the cell types ( S12C Fig ) , which is consistent with previous findings [41] . We examined TFs in which large fractions of TFBSs were occupied by HERV-TFBSs ( S3 Table ) . Binding sites of NFYA/B , USF1/2 , GATA4/6 , TAL1 , SOX2 , SOX17 , and TCF4 were highly overlapped with HERV/LTRs . Nearly half of NFYB-binding sites were observed on HERV/LTRs [52] . NFYA/B frequently bound to members of the HERV_4 cluster in Fig 2 ( e . g . , LTR12 , MER51 , and MER57 groups ) and members of the HERV_6 cluster ( MLT1 group ) ( Fig 2 ) . These HERV/LTRs contained HSREs for NFYA/B [see dbHERV-REs ( http://herv-tfbs . com/ ) ] . Then , we investigated specific associations between the insertion dates of HERV/LTRs and TFs that bound to the HERV/LTRs ( S13 Fig ) . HERV/LTRs integrated after the divergence of primates were highly bounded by members of TF_2 ( pluripotent cluster ) shown in Fig 2 , such as POU5F1 , SOX2 , SMAD1 , TCF4 , and NANOG ( S13 Fig and Fig 2 ) . This is consistent with the results of a previous study showing that SOX2- and POU5F1-binding sites were amplified after the divergence of primates by insertions of HERV/LTRs harboring the binding sites [13] . HERV/LTRs integrated before the divergence of primates were highly bounded by members of the TF_6 cluster , such as SIX5 , USF1/2 , and ATF3 ( S13 Fig and Fig 2 ) . This is because these TFs frequently bound to the MLT1 group ( Fig 2 ) , which inserted before the divergence of primates . HERV/LTRs that inserted at the span from Catarrhini to Hominoidea were highly bounded by NFYA/B and LEF1 ( S13 Fig ) . This is because these TFs bound to the LTR12 group , which inserted at the span from Catarrhini to Hominoidea [see dbHERV-REs ( http://herv-tfbs . com/ ) ] . It is important to clarify whether HERV-TFBSs contribute to the regulation of host genes , especially in a cell type-specific manner . We examined the association between HERV-TFBSs and genes specifically expressed in a particular cell type . In six cell types ( GM12878 , H1-hESC , K562 , HepG2 , HeLa-S3 , and HUVEC cells ) , we identified 200 genes that specifically expressed in each cell type . Subsequently , we examined the enrichment of HERV-TFBSs according to the cell types in regions nearby the genes that were specifically expressed . We demonstrated that HERV-TFBSs in each cell type were enriched in region nearby the specifically expressed genes in the corresponding cell type ( Fig 5A ) . This indicates that HERV-TFBSs are involved in cell type-specific regulation of host genes . To ascertain which biological functions are associated with HERV-TFBSs/HSREs , we performed Gene Ontology ( GO ) enrichment analysis with GREAT [53] . First , we performed the analysis using a set of all HERV-TFBSs in one cell type ( Fig 5B ) . HERV-TFBSs in cells such as GM12878 and K562 were highly enriched in regions nearby the genes associated with innate immunity-related pathways such as “response to interferon-gamma” and “type I interferon signal pathway” ( Fig 5B ) . The MER41 and MLT1 groups occupied significant fractions of HERV-TFBSs nearby the genes associated with the above biological processes ( S14 Fig; left panel ) . Regarding TFBSs , binding sites of SPI1 , POU2F2 , ZNF263 , and USF1 were found to be enriched ( S14 Fig right panel ) . Next , we ascertained biological processes in GO term with which HERV-TFBSs were more enriched compared to the other TFBSs ( i . e . , TFBSs did not overlap with HERV/LTRs ) . HERV-TFBSs showed significantly stronger associations with biological processes relevant to immune responses compared to the other TFBSs ( S4 Table ) . We also performed GO enrichment analysis to examine biological functions in which HERV-TFBSs were enriched compared to the entire population of HERV/LTRs , and we obtained similar results ( S5 Table ) . Finally , we performed the GO enrichment analyses to infer biological functions with which each type of HSRE is associated . In this analysis , we used sets of HERV-TFBSs harboring each type of HSRE in respective cell types . In total , 39 , 946 significant associations for combinations of cell types , HSREs , and GO terms were identified [summary data is deposited in dbHERV-REs ( http://herv-tfbs . com/ ) ] . Consistent with the above analyses , GO terms associated with the immune response were frequently observed ( S6 Table ) , and the associations between HSREs and various biological processes were identified [see dbHERV-REs ( http://herv-tfbs . com/ ) ] . Some regulatory elements affect the remote genes via three-dimensional ( 3D ) interactions by forming chromatin loops [45] . We attempted to extract such 3D interactions between HERV-TFBSs/HSREs and promoters of host genes from the data on promoter-captured Hi-C ( pcHi-C ) in GM12878 cells [54 , 55] . pcHi-C is a modified “chromosome conformation capture” method for a comprehensive identification of the 3D interaction between promoters and other genomic regions [54] . We first examined HERV-TFBSs or HSREs present in promoter-interacting regions ( interacting regions ) . In total , 26 , 194 and 3 , 860 of HERV-TFBSs and HSREs-containing HERV-TFBSs , respectively , were present in the interacting regions . Some interacting regions were associated with several genes , and 81 , 536 or 12 , 452 of interactions between promoters of genes and HERV-TFBSs or HSREs-containing HERV-TFBSs were identified , respectively . The average interval of interactions between promoters and interacting regions containing HERV-TFBSs was 392 kb ( average interval of interactions between promoters and all interacting regions was 411 kb in this dataset ) . HERV/LTRs harboring TFBSs or HSREs were enriched two-fold in interacting regions compared with the population of the entire HERV/LTRs ( Fig 6A ) . Transcription levels ( reads per kilobase per million mapped reads; RPKM ) of genes tended to be higher as the number of HERV-TFBSs interacting with the genes increased ( Fig 6B ) . Thus , the HERV/LTR regulatory elements in interacting regions seem to work as transcriptional modulators of host genes via long-range interactions . Members of the MLT1 , MER21 , and MER41 groups were enriched in interacting regions , together with LTR8 , LTR54 , and LTR13 ( Fig 6C ) . Next , we developed and performed a “Hi-C-based” GO enrichment analysis by modifying a statistical method used in GREAT [53] ( see Materials and Methods ) . As shown in Fig 6D , HERV-TFBSs were highly enriched in GO terms associated with immune response such as “positive regulation of interleukin-2 production” and “dendritic cell chemotaxis , ” consistent with the result of “distance-based” GO enrichment analysis as shown in Fig 5B . Furthermore , using the Hi-C-based GO enrichment analysis , we ascertained biological processes in GO term with which HERV-TFBSs were more enriched compared to the other TFBSs . Consistent with the above results , HERV-TFBSs showed significantly stronger associations with biological processes relevant to immune responses compared to the other TFBSs ( S7 Table ) . We constructed dbHERV-REs , a database of HERV/LTR regulatory elements with an interactive user interface ( http://herv-tfbs . com/ ) ( S19 Fig ) . The database provides ( i ) general information on HERV/LTRs such as family classification , copy number , and insertion date judged by distribution of orthologous copies among mammalian genome; ( ii ) positions of HERV-TFBSs , HSREs , and HERV-DHSs in the consensus sequence of HERV/LTRs and in the human reference genome; and ( iii ) results of GO enrichment analyses with GREAT [53] using sets of respective HSREs . The database also can compare phylogenetic relationship of HERV/LTR copies with the presence of orthologous copies across the mammalian genome , TFBSs , and TF-binding motifs . Results of all- and unique-read TFBSs are available in the database . Additionally , the database provides results on pre-determined TFBSs provided by ENCODE and Roadmap , which were based on their analytical pipelines of ChIP-Seq peak calling ( S2 Table ) . As of May 2017 , TFBSs for 97 TFs and DHSs for 125 cell types were deposited . A user can focus on significant associations between HERV/LTRs and TFs by setting statistical and other thresholds .
We showed that HERV/LTRs frequently contained HERV-TFBSs/HSREs for TFs essential in hematopoietic ( e . g . , SPI1 , TAL1 , and GATA1/2 ) , pluripotent ( e . g . , SOX2 , POU5F1 , and NANOG ) , and embryonic endoderm/mesendoderm cells ( e . g . , GATA4/6 , SOX17 , and FOXA1/2 ) . Hematopoietic regulatory elements of HERV/LTRs seem to descend from ancestral exogenous retroviruses , which would have replicated in the hematopoietic ( or blood ) cells , considering that modern exogenous retroviruses frequently contain such regulatory elements [38] . Pluripotent regulatory elements seem to have been crucial for efficient replication of HERV/LTRs in germ cells , as with other TEs such as LINE1 , because transcriptional environments are similar between pluripotent and early embryonic cells [21 , 56] . Endoderm/mesendoderm regulatory elements also seem to be important for HERV/LTRs , possibly for their replication in the host germ cells immediately after the endogenization , as these TFs highly expressed in both somatic and germ cells [41] . A previous study showed that the regulatory elements of HERV/LTRs are active in various cells and tissues by evaluating enrichment of active histone modifications on HERV/LTRs [50] . Therefore , as the number of available ChIP-Seq datasets increase , a greater number of regulatory elements of HERV/LTRs will be identified . Although the role of retroviral internal sequences in transcription remains unclear , it is known that an internal sequence in Human T-cell Leukemia Virus Type 1 ( HTLV-1 ) contains a CTCF-binding site functioning as an insulator [57] . In the present study , we found that a substantial fraction of HSREs was present in the internal sequences , and the most frequently observed HSRE in the internal sequences was the CTCF-binding site ( S5I Fig ) . These findings suggest that regulatory elements , particularly CTCF-binding sites , would be present in the internal sequences of retroviruses , including HERVs , more than previously considered [38 , 57] . Further investigation is needed for clarifying the role of retroviral internal sequences in transcriptional modulation . Pluripotent regulatory elements seem to be essential for HERVs and other TEs to replicate efficiently in the host germ cells and to expand in the host genome . However , the pluripotent regulatory elements are rarely observed in exogenous retroviruses , even though HERVs descended from ancient exogenous retroviruses [38] . In this study , we demonstrated the heterogeneity of regulatory elements among subgroups in LTR7 ( Fig 3G–3K ) , LTR5 group ( Fig 4 ) , LTR6A ( S15 Fig ) , LTR9 ( S16 Fig ) , MER11C ( S17 Fig ) , and MER11B ( S18 Fig ) . Such heterogeneity of regulatory elements was also observed in endogenous retroviruses ( ERVs ) of other mammals [58 , 59] . These indicate that gains or losses of the regulatory elements occurred during genomic expansions of the HERV/LTRs ( or the ERVs ) . We observed a tendency that younger subgroup of HERVs had more regulatory elements for pluripotent TFs ( e . g . , NANOG , POU5F1 , and SOX2 ) in LTR7 , LTR5_Hs , LTR6A , and MER11C ( Fig 3G–3K , Fig 4 , S15 Fig , and S17 Fig , respectively ) although we observed an opposite tendency in MER11B ( S18 Fig ) . Thus , HERVs seem to have frequently acquired pluripotent regulatory elements . We hypothesize that these HERVs acquired the pluripotent regulatory elements after endogenization for efficient replication and genomic expansion in the host germ cells . Thus , investigation of heterogeneity of regulatory elements of HERV/LTRs can illuminate the evolutionary dynamics of transcriptional modulation system of HERVs . LTR7 is essential for the maintenance of pluripotency in ES and iPS cells , and it has been hypothesized that LTR7 insertions rewired the core regulatory network of the pluripotent cells [10–12] . We further clarified the heterogeneity among subgroups of LTR7 with respect to insertion dates , TF binding profiles , and transcriptional activities . Subgroup III , the youngest subgroup of LTR7 , was most frequently bounded by SOX2 , POU5F1 , and KLF4 ( Fig 3G–3K and S10D Fig ) . Subgroup III also showed the highest enrichment of ChIP-Seq reads of NANOG ( Fig 3K ) . Subgroup III showed the highest transcriptional activity in pluripotent cells ( S11 Fig ) . Most LTR7-chimeric transcripts , which are vital in maintaining pluripotency [10–12 , 39] , were composed of LTR7 belonging to the subgroup III ( S11 Fig ) . These findings suggest that the evolutionary rewiring of the core regulatory network of pluripotent cells was caused by a specific population of LTR7 , i . e . , members of the subgroup III , rather than by the entire population of LTR7 ( Fig 3L ) . Moreover , this rewiring seems to have occurred more recently than previously thought [60] , the branch from the end of Hominoidea to Homininae . This is because the rewiring should have occurred during the period when subgroup III was inserted ( Fig 3G , 3H and 3L ) . Further investigation is needed to elucidate the evolution of pluripotent cells due to LTR7 insertions . The GO enrichment analysis based on genomic positions of HERV-TFBSs/HSREs demonstrated that HERV-TFBSs/HSREs tend to be located near the genes involved in innate immune responses such as cytokine-mediated signaling ( Fig 5B and S4 , S5 and S6 Tables ) . This tendency was recaptured by Hi-C-based GO analysis , which used information on 3D interactions between HERV-TFBSs and promoters of host genes in B-lymphocytes ( GM12878 cells ) ( Fig 6D ) . In those GO enrichment analyses , HERV-TFBSs showed significantly stronger associations with biological processes relevant to innate immune responses compared to the other TFBSs ( S4 and S7 Tables ) . This suggests that HERV/LTR regulatory elements were likely to be associated with regulatory networks controlling innate immune responses . Furthermore , this tendency seems to be more attributable to natural selection of HERV/LTRs after the insertions than preferential insertions in specific genomic regions , because HERV/LTR copies with TFBSs were more enriched in regions near the genes related to innate immune response than HERV/LTRs without TFBSs ( S5 Table ) . The tendency of regulatory elements of HERV/LTRs being associated with innate immune response seemed to be affected by cell types ( e . g . , B-lymphocytes ) in which ChIP-Seq was performed . Therefore , as the number of cell types in which ChIP-Seq are performed increase , more associations between HERV/LTRs with TFBSs and specific biological functions will be identified . Finally , GO enrichment analyses showed that each type of HSRE was statistically associated with various biological processes in addition to the immune response [deposited in dbHERV-REs ( http://herv-tfbs . com ) ] . Further research , especially knockout-based studies such as the one by Chong et al . [14] , is necessary to prove the causal relationship between regulatory elements of HERV/LTRs and regulatory networks controlling specific biological processes . To summarize , we identified various HERV/LTR regulatory elements involved in several host regulatory networks . Our study provides the foundation to understand the impact of HERV/LTRs on host transcription , and provides insights into transcriptional modulation systems that HERV/LTRs and ancestral retroviruses of HERVs originally used .
Information on the ChIP-Seq dataset is summarized in the “peak calling of ChIP-Seq” section . RepeatMasker output file ( http://hgdownload . soe . ucsc . edu/goldenPath/hg19/bigZips/chromOut . tar . gz ) was downloaded from the UCSC genome browser ( https://genome . ucsc . edu/ ) . This is an annotation file of repetitive elements on the human reference genome ( GRCh37/hg19 ) used in RepeatMasker track in the genome browser . Consensus sequences of HERV/LTRs were obtained from the RepeatMasker library ( 20140131 release ) and Repbase Update ( 1 . 1 . 3 release ) in Repbase ( http://www . girinst . org/server/RepBase/ ) . DHS datasets were obtained from ENCODE ( S10 Table ) . Genome segmentations in six cell types ( combined between ChromHMM and Segway ) [47–49] were obtained from ENCODE ( S11 Table ) . Datasets of Cold Spring Harbor Laboratory ( CSHL ) LongPolyA RNA-Seq were obtained from ENCODE in the GTF format ( S12 Table ) . Ontology file ( go-basic . obo , date; 3/16/2016 ) and GO association file ( gene_association . goa_human , submission date; 3/16/2016 ) were downloaded from the GO Consortium ( http://geneontology . org/ ) . The UCSC known genes were downloaded from UCSC ( http://hgdownload . cse . ucsc . edu/goldenPath/hg19/database/knownGene . txt . gz ) . pcHi-C dataset in GM12878 cells [54 , 55] ( GSE81503_GM12878_PCHiC_merge_final_seqmonk . txt . gz and GSE81503_GM12878_PCHiC_merge_final_washU_text . txt . gz , accession GSE81503 ) were obtained from the Gene Expression Omnibus ( http://www . ncbi . nlm . nih . gov/geo/ ) . An analytical pipeline used in this study is summarized in S1B Fig . For the Roadmap dataset , we obtained a sequence read file ( fastq format ) from the Sequence Read Archive ( SRA ) using the SRA Toolkit fastq-dump ( http://www . ncbi . nlm . nih . gov/books/NBK158900/ ) . For the ENCODE dataset , we downloaded an unfiltered alignment file , if available , for GRCh37/hg19 ( bam format ) from the ENCODE database ( http://www . encodeproject . org/ ) . The unfiltered alignment file was generated using the ENCODE Processing Pipeline with BWA 0 . 7 . 10 ( aln and samse ) . If the unfiltered alignment file was not available , we downloaded a fastq file from the ENCODE database . Fastq or bam files of biological replicates were then concatenated . Sequence reads in the fastq files were mapped to human reference genome ( GRCh37/hg19 ) using BWA 0 . 7 . 12 ( aln and samse/sampe ) . In the default setting of BWA aln , a multiple mapped read is randomly assigned to a particular genomic position chosen from candidate positions . For the all-read TFBSs , ChIP-Seq peaks were called using MACS2 with default setting . For unique-read TFBSs , multiple mapped reads or reads with low mapping quality ( reads with MAPQ score of <10 ) were removed using samtools view [61] , and then ChIP-Seq peaks were called . In peak calling , input control file was used with ChIP-treated file . Information on the ChIP-Seq data is summarized in S8 and S9 Tables . HERV-TFBSs and HSREs were identified separately in ENCODE and Roadmap datasets . HERV-TFBSs and HSREs were identified both in all- and unique-read TFBSs . We identified HERV-TFBSs in respective cell types by examining the overlaps between HERV/LTRs and TFBSs with bedtools intersect [62] . In the respective TFs , TFBSs or HERV-TFBSs among all cell types or conditions were merged with bedtools merge [62] ( referred to as the merged TFBSs or HERV-TFBSs ) . For counting TFBSs and HERV-TFBSs , the merged TFBSs and HERV-TFBSs were used . For the identification of HSREs , the merged HERV-TFBSs were used . First , sequences of HERV/LTR copies were extracted from human reference genome ( GRCh37/hg19 ) using bedtools getfasta [62] . Multiple sequence alignment ( MSA ) of HERV/LTR copies was constructed with a consensus sequence of the corresponding HERV/LTR type . MAFFT v7 . 239 [63] was used for the construction of MSA with the options—addfragments , —keeplength , and—retree 2 . In this setting , the consensus sequence was used as input , and sequences of HERV/LTR copies were used as fragment sequence . In MSA , the position of HERV-TFBSs was mapped on each HERV/LTR sequence , and then the number of the mapped HERV-TFBSs was counted at every consensus position ( referred to as “depth” of HERV-TFBSs ) . For setting the threshold to identify peaks of HERV-TFBSs , randomized ( shuffled ) TFBS datasets were generated with bedtools shuffle [62] for 500 times . In the respective randomized datasets , the depth of HERV-TFBSs was counted for each consensus position with the above-mentioned procedures . For every consensus position , average and standard deviation of the depth of HERV-TFBSs among randomized datasets was calculated . Standardized score ( z score ) of HERV-TFBS depth was calculated for every consensus position with the average and standard deviation in randomized datasets ( termed as base-wise z score ) . If base-wise z score of a given region ( >50-bp ) in the consensus sequence was higher than four , the region was defined as a peak of HERV-TFBSs . Finally , known TF-binding motifs of the corresponding TF were scanned in original HERV-TFBS sequences . For motif scanning , FIMO [64] and known TF-binding motifs recorded in JASPAR [65] and HOCOMOCO [66] were used . The threshold ( p value ) of the motif scanning was set at 0 . 001 . In MSA , position of the TF-binding motif was mapped on each HERV/LTR sequence , and then the number of the mapped motifs was counted at every consensus position ( referred to as “depth” of TF-binding motifs ) . To identify HSREs , heights of peaks of depths were compared between HERV-TFBSs and TF-binding motifs . If the height of the TF-binding motif peak is ( i ) greater than or equal 10 and ( ii ) greater than 60% of the height of the HERV-TFBS peak , we regard the set of TF-binding motifs as HSRE ( S9 Fig ) . For counting the number of genomic positions of HSREs , overlapping HSREs of the same TF were merged for avoiding double counts . This is because some TF-binding motifs were present in both strands at approximately the same positions due to their palindrome signatures . After identifying HSREs , overlaps between HSREs and HERV-TFBSs in respective cell types were examined , and the cell specificities of HSREs were determined . HERV-TFBS overlaps were counted for all combinations . In each dataset of TFBS , we generated 100 times of randomized TFBS datasets using bedtools shuffle [62] and counted the number of HERV-TFBS overlaps in the randomized datasets . Among the randomized datasets , average and standard deviation of numbers of HERV-TFBS overlaps were calculated . In each HERV-TFBS combination , we calculated z score ( count-based z score ) using the number of HERV-TFBS overlaps in an observed dataset and the average and standard deviation among randomized datasets . For TEs other than HERV/LTRs , z scores for all combinations of respective TE types and the merged TFBSs were calculated using the same procedures . We used unique-read TFBSs , and separately dealt with TFBSs of the same TF in distinct cell types . If there were several TFBS files for the same ChIP-Seq condition , the TFBS files were merged using bedtools merge [62] . All TFBSs ( e . g . , SOX2-binding sites in HUES64 cells from Roadmap ) were used for the analysis , except for CTCF-binding sites; we used CTCF-binding sites that were determined in tier 1 and 2 cells of ENCODE ( GM12878 , H1-hESC , K562 , HepG2 , HeLa-S3 , and HUVEC ) , HUES64 cells , and germ layer ( ectoderm , endoderm , mesoderm , and mesendoderm ) cells that were differentiated from the HUES64 cells . Z scores were calculated using the method in the “randomization test shuffling genomic positions of TFBSs” section . A matrix containing the z scores was created . HERV/LTR type whose copy number was less than 100 was excluded from the matrix . Rows ( TFBSs ) and columns ( HERV/LTRs ) were excluded if they did not contain any elements whose z scores were greater than or equal to 10 . Distance matrix was constructed using the Euclid method based on the z score matrix . We performed hierarchical clustering with the distance matrix using Ward’s method . All analyses were performed by packages of amap and ReorderCluster implemented in R . As listed in S13 Table , phylogenetic trees were constructed for HERV/LTR types satisfying the following criteria: ( i ) after removal of the fragmented copies ( described below ) , the number of copies fell within the range of 10–2 , 500; and ( ii ) greater than 30% of their copies remained after the removal of fragmented copies . Fragmented and outlier copies were excluded from the analysis . For defining the fragmented copies , we constructed preliminary MSA of HERV/LTR copies with the consensus sequence using MAFFT v7 . 239 [63] with options of—addfragments , —keeplength , and—retree 2 ( in this setting , the consensus sequence was used as input , and sequences of HERV/LTR copies were used as fragment sequence ) . HERV/LTR copies were defined as fragmented if less than 80% of their sequences were only aligned to the consensus sequences in the preliminary MSA . After the removal of fragmented copies , we constructed MSA of HERV/LTR copies using MAFFT v7 . 239 with—auto options . Sites in the MSA containing gaps were excluded if site coverages of those positions were less than 30% . For defining the outlier copies , a preliminary tree was reconstructed with RAxML v8 . 2 . 0 [67] . GTRCAT was used as a nucleotide substitution model . Z score of the length of external branch was calculated for the preliminary tree . Outlier copy , whose z score of the branch length was greater than three , was excluded from the MSA . We constructed the final tree using the same procedures with the preliminary tree . Supporting values were calculated using the SH-like test [68] . In addition to the SH-like test , rapid bootstrap analysis [67] ( 100 times ) was performed for the phylogenetic tree of the LTR5 group . The age of a provirus of ERVs can be estimated by sequence comparison between 5′- and 3′-LTRs of the ERVs , as sequences of both LTRs were identical at the time of insertion , and after the insertion , both LTRs independently accumulated mutations as a part of the host genome [69] . In this analysis , we used the annotation of a provirus of HERVH/LTR7 as reported previously [11] . We only analyzed proviruses of HERVH/LTR7 harboring two LTR7 sequences that were categorized in the same subgroup in the tree ( Fig 3G ) . For each provirus , a pairwise sequence alignment of 5′- and 3′-LTRs was constructed using the EMBOSS Stretcher program [70] . After removal of all gapped sites in the alignment , p-distance of the paired LTRs was calculated , and then the genetic distance of the paired LTRs was computed using the Jukes-Cantor 69 model . A substitution rate of HERVs of 1 . 0 × 10−9 per site per year was used as described previously [71] . Insertion date of the provirus was calculated with the formula , D/2R ( D , genetic distance of the paired LTRs; R , substitution rate of HERVs ) . For judging whether an orthologous copy of a HERV/LTR copy was present in a certain reference genome , liftOver ( http://hgdownload . soe . ucsc . edu/admin/exe/linux . x86_64/liftOver ) was used . If liftOver successfully converted the genomic position of a particular HERV/LTR copy in human reference genome to that of a reference genome of other species , we judged an orthologous copy of the HERV/LTR copy was present in the genome of the corresponding species . A minimum match parameter was set at 0 . 5 . Reference genomes of PanTro4 ( chimpanzee ) , GorGor3 ( gorilla ) , PonAbe2 ( orangutan ) , Nomleu3 ( gibbon ) , RheMac3 ( rhesus macaque ) , CalJac3 ( marmoset ) , TarSyr1 ( tarsier ) , MicMur1 ( mouse lemur ) , Mm9 ( mouse ) , Bostau7 ( cow ) , and CanFam3 ( dog ) were used . Classification of insertion date of HERV/LTRs was defined as follows: ~Hominoidea; greater than 10% of orthologous copies of the HERV/LTR type present in any of the chimpanzee , gorilla , orangutan , and gibbon genomes but absent in that of the rhesus macaque . Catarrhini; greater than 10% of orthologous copies of the HERV/LTR type present in the chimpanzee , gorilla , orangutan , gibbon , and rhesus macaque genomes but absent in that of the marmoset . Simiiformes; greater than 10% of orthologous copies of the HERV/LTR type present in the chimpanzee , gorilla , orangutan , gibbon , rhesus , and marmoset genomes but absent in those of the tarsier and mouse lemur . Primates; greater than 10% of orthologous copies of the HERV/LTR type present in the chimpanzee , gorilla , orangutan , gibbon , rhesus , marmoset , tarsier , and mouse lemur genomes but absent in those of the mouse , cow , and dog . Eutheria~; greater than 10% of orthologous copies of the HERV/LTR type present in the chimpanzee , gorilla , orangutan , gibbon , rhesus , marmoset , tarsier , mouse lemur , mouse , cow , and dog genomes . We only analyzed HERV/LTR types whose copy numbers were greater than or equal to 100 . Unique-read TFBSs were used in GO enrichment analyses . GO associations described in gene_association . goa_human were used . GO term associated with greater than or equal to five genes was used in the analyses . In distance-based GO enrichment analysis , the createRegulatoryDomains command in the local version of GREAT [53] was used for defining regulatory domains of respective GO terms with the option of basal ( five kb upstream and one kb downstream of the TSS ) plus extension ( up to one Mb ) . We used the TSS annotation based on the UCSC known genes . Enrichment score and p values with binomial test were calculated by the original R script . To determine the GO term in which TFBSs with HERV/LTRs were more enriched than the other TFBSs ( TFBSs not on HERV/LTRs ) , we counted the number of TFBSs with HERV/LTRs and the entire TFBSs in regulatory domains associated with a certain GO term . Then , the enrichment significance was calculated by Fisher’s exact test . In order to examine the GO term in which HERV/LTRs harboring TFBSs were more enriched than the entire HERV/LTRs ( all HERV/LTRs regardless of overlaps with TFBSs ) , we estimated the number of HERV/LTRs harboring TFBSs and the entire HERV/LTRs overlapped to regulatory domains associated with a certain GO term . The enrichment significance was calculated by Fisher’s exact test . To ascertain the GO term in which each type of HSRE was enriched , we performed the GREAT analysis [53] using a set of HERV-TFBSs harboring a HSRE in each cell type . The threshold for statistical significance was set at 0 . 1 , with false discovery rates calculated using the Benjamini–Hochberg ( BH ) method . We thus developed the “Hi-C-based” GO enrichment analysis by modifying the GREAT algorithm [53] . Interacting regions in pcHi-C [54 , 55] of all genes were merged using bedtools merge [62] and were defined as “total region” . Interacting regions of genes associated with a particular GO term were merged and were defined as “regulatory domain” for the corresponding GO term . The lengths of the total region and regulatory domain were calculated ( termed total_length and regdom_length , respectively ) . HERV-TFBSs overlapping with the total region and regulatory domain were also counted ( termed total_count and regdom_count , respectively ) . For calculating the enrichment significance , we performed a binomial test using the above total_count and regdom_count in addition to the ratio of regdom_length and total_length ( regdom_length/total_length ) . In Hi-C-based GO enrichment analysis , we performed GO enrichment analysis to determine the GO term in which TFBSs with HERV/LTRs were more enriched than the other TFBSs . We counted the number of TFBSs with HERV/LTRs and the other TFBSs in regulatory domains associated with a certain GO term . Then , the enrichment significance was calculated by Fisher’s exact test . In CSHL LongPolyA RNA-Seq , protein-coding genes with RPKM >3 in any cell type were included in the analysis . For every gene , z score of RPKM was calculated for each cell type by using the average and standard deviation of the six cell types ( GM12878 , H1-hESC , K562 , HepG2 , HeLa-S3 , and HUVEC cells ) . Regarding the z scores , top 200 genes in each cell type were defined as those expressed specifically in the corresponding cell type . Regulatory domain for genes specifically expressed in a certain cell type was created by using the createRegulatoryDomains command in GREAT [53] with a setting of basal ( 5 kb upstream and 1kb downstream of TSS ) plus extension ( up to 1 Mb ) . Enrichment scores and p values with binomial test were calculated by original R scripts . The system is running on Amazon Web Service ( http://aws . amazon . com/ ) . The relational database was constructed with MySQL . The server program was written in Python using Twisted ( http://twistedmatrix . com/ ) , an event-driven networking framework . The user interface was designed upon AJAX ( Asynchronous JavaScript + XML ) philosophy . plotly . js ( http://plot . ly/javascript/ ) is used for data visualizations . jQuery ( http://jquery . com/ ) was used for the browser scripting . | Human endogenous retroviruses ( HERVs ) are genomic “fossils” of ancient exogenous retroviruses and their descendants that were replicated in host germ cells . The traits and evolutionary dynamics of ancient retroviruses and their descendants can be inferred by scrutinizing present-day HERVs . We systematically identified regulatory elements of HERVs based on publicly available datasets of ChIP-Seq of 97 TFs . Clustering analysis showed that HERV/LTRs can be grouped by the TF-binding patterns; HERV/LTR groups bounded by pluripotent TFs ( e . g . , SOX2 , POU5F1 , and NANOG ) , embryonic endoderm/mesendoderm TFs ( e . g . , GATA4/6 , SOX17 , and FOXA1/2 ) , and hematopoietic TFs ( e . g . , SPI1 ( PU1 ) , GATA1/2 , and TAL1 ) were identified . By analyzing the three-dimensional chromosomal interactions , we demonstrated that regulatory elements of HERVs tend to interact with host immune-response genes . We further demonstrated heterogeneities of regulatory elements within LTR7; SOX2 , POU5F1 , and KLF4-binding sites were highly enriched in the youngest subgroup of LTR7 , which had the highest transcriptional activity in pluripotent cells . This suggests that the subgroup acquired those regulatory activities for efficient replication in the host germ cells . Finally , we constructed dbHERV-REs , an interactive database of HERV/LTR regulatory elements ( http://herv-tfbs . com/ ) . This study provides insights into regulatory elements of HERVs and transcriptional modulations of host genes by HERVs . | [
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"... | 2017 | Systematic identification and characterization of regulatory elements derived from human endogenous retroviruses |
The vapor phase of the volatile pyrethroid transfluthrin incapacitates mosquitoes and prevents them from feeding . Although existing emanator products for delivering volatile pyrethroids protect against outdoor mosquito bites , they are too short-lived to be practical or affordable for routine use in low-income settings . New transfluthrin emanators , comprised simply of treated hessian fabric strips , have recently proven highly protective against outdoor-biting vectors of lymphatic filariasis , arboviruses and malaria , but their full protective lifespan , minimum dose requirements , and range of protection have not previously been assessed . The effects of transfluthrin-treated hessian strips upon mosquito biting exposure of users and nearby non-users , as well as dependence of protection upon treatment dose , were measured outdoors in rural Tanzania using human landing catches ( HLC ) . Strips treated with 10ml of transfluthrin prevented at least three quarters ( p < 0 . 001 ) of outdoor bites by Anopheles arabiensis , Culex spp . and Mansonia spp . mosquitoes , and >90% protection against bites on warmer nights with higher evaporation rates , for at least one year . Strips treated with this high dose also reduced biting exposure of non-users at a distance of up to 5m from the strips for An . arabiensis ( p < 0 . 001 ) and up to 2m for Mansonia spp . ( p = 0 . 008 ) , but provided no protection to non-users against Culex spp . No evidence of increased risk for non-users , caused by diversion of mosquitoes to unprotected individuals , was found at any distance within an 80m radius . A dose of only 1ml provided equivalent protection to the 10ml dose against An . arabiensis , Culex spp . and Mansonia spp . mosquitoes over 6 months ( p < 0 . 001 ) . Transfluthrin-treated hessian emanators provide safe , affordable , long-term protection against several different pathogen-transmitting mosquito taxa that attack humans outdoors , where they are usually active and cannot be protected by bed nets or residual sprays with conventional , solid-phase insecticides .
Long lasting insecticidal nets ( LLINs ) and indoor residual spraying ( IRS ) are used extensively to control transmission of malaria , lymphatic filariasis , and several arboviruses by indoor-biting mosquitoes . Across much of the tropics , two or more mosquito-borne pathogens are co-endemic and are often transmitted by the same vectors [1] . These tools are effective against anthropophilic ( prefer feeding on humans ) , endophagic ( feed indoors ) and endophilic ( rest indoors ) mosquitoes [2 , 3] but are less effective against exophagic ( feed outdoors ) and exophilic ( rest outdoors ) mosquitoes [4] . A wide diversity of outdoor-biting mosquitoes mediate transmission of pathogens that cause filariasis , dengue , yellow fever and malaria , frustrating efforts to eliminate them with LLINs and IRS [5] . Additional vector control tools are therefore clearly required to simultaneously target the many different species of vector mosquitoes that bite humans outdoors and mediate transmission of several neglected tropical diseases . The most effective pyrethroid insecticides are applied to solid surfaces , such as house walls and ceilings ( IRS ) or bed nets ( LLINs ) , where mosquitoes may be exposed to them when they make physical contact with those surfaces . However , some less polar insecticides , such as the fluorinated pyrethroids , like metofluthrin and transfluthrin , have lower melting points hence can melt into liquids at ambient temperatures in the tropical areas and are slightly volatile so they release vapor into the air . Low doses of airborne pyrethroids induce sub-lethal responses such as: repellency , deterrence , feeding inhibition and reduce fecundity as opposed to higher doses of contact insecticides that induce knock down and mortality of mosquitoes . Nevertheless , these sub-lethal responses are likely to decrease vectorial capacity of mosquitoes and consequently reduce disease transmission that could be equivalent to toxic contact insecticides [6] . Vapor-phase insecticides are typically formulated as coils , emanators or candles [7] . Transfluthrin [8] and metofluthrin [9] mosquito coils have been shown to prevent malaria infection , notably in combination with LLINs [8] . However , the effectiveness of these products is attenuated by the need for regular compliance by users , reapplication or retreatment of treated clothing or other substrates [10 , 11] , or active electrical energy input , which may be impractical in many rural tropical settings [12] . Passive emanators for releasing such vapor-phase active ingredients have been evaluated against outdoor-biting mosquitoes [13 , 14 , 15 , 16] . These tools do not require heating or electricity and may require minimal compliance by users if the active ingredient is released into the surrounding air , to protect a space around the user . Cost-effectiveness of existing gold standard personal protection measures against mosquitoes is typically limited by product durability . The longest-lasting passive metofluthrin emanator products we are aware of reduced outdoor biting rates of Culex quinquefasciatus mosquitoes for up to 8 weeks , after which protection declined rapidly [14] . No evidence has been published that any of these factory-formulated , disposable products can provide high levels of outdoor protection for longer periods , whereas LLINs can protect sleeping spaces for years at a time . A simple low-technology emanator has been developed , which consists of a strip of hessian sacking hand-treated with transfluthrin possibly allowing repeated retreatment . This emanator is shown to have high efficacy for reducing exposure to mosquito bites for up to six months [17 , 18] . However , neither of these exploratory studies was conducted long enough to determine the full durability of the prototype , the minimum dose required , or rigorously assessed potential for diversion to nearby non-users . In order to more convincingly assess the full potential of transfluthrin-treated hessian strips as a protection measure against outdoor-biting mosquitoes , this study was undertaken to measure their full long-term protective efficacy over more than two years and assess the protective efficacy of different doses of transfluthrin . The spatial activity of transfluthrin-treated strips was also quantified by measuring the distance over which protection extended and determine whether or not nearby non-users were at a higher risk of being bitten by mosquitoes diverted from users . The effect of changes in temperature on efficacy of strips was also investigated .
The field study described herein was conducted in the Kilombero Valley of southern Tanzania . Several species of Culex , Anopheles , and Mansonia mosquitoes including several known vectors of not only malaria [6 , 19 , 20 , 21] , but also filariasis , and five different arboviruses [22] have been reported in this locality . Since scale up of LLINs in 2008 , Anopheles gambiae sensu stricto population densities have declined , leaving exophagic An . arabiensis mosquitoes as the most abundant human-biting Anopheles species [23 , 24] , alongside substantial populations of Ma . africana , Ma . uniformis , Cx . quinquefasciatus , Cx . univittatus and Cx . theileri . While the physiological resistance status of these various culicines is unknown , local populations of An . arabiensis have become resistant to pyrethroids ( permethrin , lambda-cyhalothrin and deltamethrin ) by 2014 [20] when the final year of long-term efficacy testing and the dose-response evaluations described below were conducted ( Fig 1 , Experiments 1 and 2 , respectively ) . This area typically experiences two rainy seasons every year: intermittent , sporadic rains from November to January and steadier , more consistent rainfall from March to May . Annual rainfall ranges between 1200 and 1800 mm and annual mean temperature ranges between 20°C and 32°C . Rectangular strips of hessian fabric , measuring 4 m by 30 cm were cut out of jute ( Corchorus capsularis ) gunny bags that had been imported from India . Strips were treated with different doses of 97% technical grade transfluthrin ( Shenzhen Sunrising Industry Company , China ) as previously described [17 , 18] . Each strip was soaked in an emulsion of 0 . 1 , 0 . 2 , 0 . 5 , 1 , 2 , 5 or 10 ml of transfluthrin , 90 ml of Axion liquid detergent ( Orbit Chemical Industries Ltd , Nairobi and Colgate-Palmolive East Africa Ltd ) and 400 ml of water and then left to dry indoors overnight at room temperature . Control strips were soaked in an equivalent mixture of water and Axion liquid detergent . The study comprised three distinct experiments to ( 1 ) determine the long-term protective efficacy of transfluthrin-treated Hessian strips , ( 2 ) determine how their efficacy varies with application dose , and ( 3 ) determine the maximum transfluthrin vapor concentration a human user of such treated strips could be exposed to ( Fig 1 ) . This study was conducted in two phases . The first phase lasted almost one full year post-treatment , from 25th of July 2012 until the 6th of June 2013 . The second phase spanned the period from the last quarter of the second year post-treatment , to slightly beyond two and a half years post treatment , from the 30th of April 2014 until the 1st of January 2015 . In the first phase , ( Fig 1 ) five strips treated with 10ml of technical grade transfluthrin ( first emulsified by mixing with 90 ml of water and 10ml of liquid detergent as described above ) and five untreated control strips were simultaneously assessed by rotation through four separate open-field sites ( Fig 2A ) within the village of Lupiro ( 8 . 385°S and 36 . 670°E ) . In this first phase , treated and untreated strips were moved in pairs between field sites and the semi-field tunnel every 3 consecutive experimental nights ( See below for details of the three-night randomization cycle for strip treatments ) following a 5×5 Latin square design , spanning 15 nights of experimentation for each round of experimental replication . In order to allow volunteers and supervisors four nights per working week to sleep normally , each 3-night cycle of treatment randomizations was allocated to a single working week , so each full round of experimentation was distributed across 5 working weeks . Overall , 5 rounds of experimental replication were completed over the course of phase 1 , comprising over 75 nights of experimentation , 600 person-nights of outdoor human landing catches ( HLC ) measurements , and the same number of person-nights of outdoor mosquito catches measured by human-baited M-trap . The M-trap consisted of netting material wrapped around a wooden frame . The M-trap has two compartments , one occupied by a seated male volunteer protected by a netting panel door and another with an entry slit into which mosquitoes can fly , so that they are captured without being able to make contact with the human occupant . Also , by the time the second phase ( Fig 1 ) was initiated , one of the strips had degraded due to fungal growth and was disposed of . Therefore , the four remaining strips were rotated through the same four field sites in Lupiro . Treated and untreated strips were moved in pairs between the four field sites every 3 nights ( See below for details of the three-night randomization cycle for strip treatments ) following a 4×4 Latin square design , spanning 12 nights of experimentation for each round of experimental replication . For same practical logistical reasons described for phase 1 , each treatment randomization cycle of 3 nights was completed within a working week , allowing volunteers four free nights off , so each round of experimental replication was completed over the course of a four-week period . The first round of experimental replication was conducted . The first round of experimental replication was conducted between the 30th of April and 21st of May 2014 . While a second round was initiated soon afterwards in early June 2014 , it was immediately observed that the stock transfluthrin froze into a solid , and that the strips provided little if any protection , following onset of the cool season . Experiments were therefore terminated before this attempt to conduct a second round of replication was complete , and suspended until the exceptionally long cool season that followed finally abated . Complete second and third rounds of experimentation were therefore conducted between the 27th of October 2014 and the 13th of November , and then between the 15th of December and the 1st of January 2015 , respectively . Overall , the three rounds of experimental replication that were completed over the course of phase 2 comprised of 36 nights of experimentation , 144 person-nights of outdoor HLC measurements , and the same number of person-nights of outdoor mosquito catches measured by human-baited M-trap . Each field site consisted of a cleared , open , rectangular field , measured out as 180m by 120m with the long axis pointing north and south ( Fig 2A ) , located ≥100 meters away from the nearest human residence . The two stations at each particular site , where users sat inside the perimeter of a strip ( Fig 2B ) , were positioned 80m apart and 80m away from the perimeters of the site ( Fig 2A ) . These field sites were located ≥300m from each other , so that they could be considered as separate experimental units . In each site , two strips , treated ( T ) or untreated control ( C ) were attached to frames of four wooden poles ( Fig 2A ) forming an area of 4m2 [17] . Over every three sequential nights of experimentation , each of the following three arrangements of strips were randomly allocated to each night , where the treatment status of the strip of the user at a given station is denoted as either untreated controls ( C ) or transfluthrin-treated ( T ) , with the status of the nearby strip at the other station denoted with a subscript , and the status of the catcher north denoted to the left of the hyphen while that of the south station is to the right: ( 1 ) An untreated control strip at the northern station and a treated strip in the southern station ( CT-TC ) , ( 2 ) Untreated control strips at both the northern and southern station ( CC-CC ) , and ( 3 ) A treated control strip at the northern station and an untreated control strip at the southern station ( TC-CT ) . The treatment arrangement selected was the same across all 4 sites on each night of experimentation . The effects of strip treatment status upon human user exposure to mosquito bites was determined by outdoor HLC , conducted by a single adult male volunteer sitting in a chair within the perimeter of the strip . HLC for this set of experiments were conducted from 18 . 30 hours each evening until 06:30 hours each morning , broken into 6 sequential periods of 2 hours with ten minute breaks for tea , coffee and light snacks in between . All strips were color-coded by stitching colored cotton ribbons along the hem in order to blind mosquito collectors and field supervisors to their treatment status . In order to measure the effect of user-occupied treated strips upon nearby non-users , an M-trap was placed at different distances away from a HLC mosquito collector ( Fig 2B ) . Potentially hazardous HLC [25] was only considered justified to apply to the users because it is known that alternative trapping methods can misrepresent the protective effects of repellents for human users [25 , 26] . One of six predefined distances ( 2m , 5m , 10m , 20m , 30m and 40m ) away from the station where HLC was conducted by the strip user were randomly allocated , without replacement within each one-night randomization cycle , to each of the six two-hour intervals between 18:30 hours and 06:30 hours each night ( 18:30 to 20:30 , 20:30 to 22:30 , 22:30 to 00:30 , 00:30 to 02:30 , 02:30 to 04:30 and 04:30 to 06:30 ) . At the start of each new two-hour period , the M-trap was moved to that allocated distance , along one of 12 pre-defined directions , which was fixed for each night of experimentation . In order to account for balance out , and account for , the highly variable effects of wind speed and direction , these 12 pre-defined directions were evenly distributed 30° apart around the full compass ( 0° , 30° , 60° , 90° , 120° . 150° , 180° . 210° , 240° . 270° , 300° and 330° , relative to north ) and were allocated randomly , without replacement , to each of 12 sequential nights within a 12-night randomization cycle . Pairs of volunteers at each station crossed over between conducting HLC and acting as mosquito baits in the M-traps after every day . However , the allocation of pairs of volunteers to stations within a site remained fixed throughout the study , so that these two causes of variation could be combined into a single-variable source of variance in the statistical analysis . The protective efficacy of different doses of technical grade transfluthrin ( all first emulsified by mixing with 90 ml of water and 10ml of liquid detergent as described above ) used to treat Hessian strips was determined following a very similar procedure to the one described above for the assessment of long-term efficacy ( Fig 1 ) . The first substantive modification was that these studies were limited to the first half of the night , from 19:00 to 01:00 , when An . arabiensis densities were noticed to be highest . This six-hour period was divided into six one-hour periods ( 19:00 to 20:00 , 20:00 to 21:00 , 21:00 to 22:00 , 22:00 to 23:00 , 23:00 to 00:00 and 00:00 to 01:00 ) , to which was the various distances from the strip and user allocated . Also the treatment randomization scheme was modified as follows . Two replicate treated strips at each of 8 different doses of transfluthrin , including zero ( 0 , 0 . 1 , 0 . 2 , 0 . 5 1 . 0 , 2 . 0 , 5 . 0 and 10ml , with even the zero dosage treatment designated as T for the purposes of relating it to the experimental design description above and the statistical analysis described below ) , constituting a total of 16 distinct strips . An additional eight replicate control strips , treated with an equivalent mixture of water and detergent only , were selected at random to act as untreated controls ( designated as C in the experimental design description above and in the statistical analysis described below ) for each site and station on each night . These 16 treated ( T ) strips and matching untreated control ( C ) strips were randomly allocated to one of the four sites for a single randomized treatment rotation of three experimental nights , exactly as described above for the efficacy durability assessment . These 48 site-nights of experimentation distributed across 4 sites therefore took 12 nights of experimentation to complete per round of experimental replication . Four rounds of replication were conducted during gaps between the experimental rounds described for the long term evaluation above: The first round was split into two periods because of the extended cool season as described above between the 16th and 26th of July and then the 29th of September until the 11th of October 2014 . The second , third and fourth rounds were conducted from the 4th to the 24th of October 2014 , from the 17th of November 2014 to the 13th of December 2014 , and the 5th to the 24th of January 2015 , respectively . During experiments , both HLC and M-trap volunteers sat under a shelter made of plastic supported by metal or wooden poles ( Fig 2 ) , so that both volunteers and strips were protected from rainfall . During the day , all strips were left hanging on the four poles , in the shade of these shelters where they were protected from rainfall and direct sunlight . During extended breaks in experimental use , strips were left hanging outdoors on wooden poles under a tree at the Ifakara Health Institute ( IHI ) facilities , under conditions expected to be representative of normal use and storage . Volunteers conducting HLC caught mosquitoes that landed on their legs using a mouth aspirator and a head lamp while those assigned to M-Traps collected mosquitoes from traps , also with a mouth aspirator and head lamp . All mosquito capture by either HLC or M-trap was conducted for either 45 minutes ( Dose-response experiments ) or 1 hour and 45 minutes ( Long term efficacy experiments ) and volunteers took 15 minutes break and helped themselves to coffee or tea . All mosquitoes collected in each 1 hour ( Dose-response experiments ) or 2 hour ( Long term efficacy experiments ) collection period , at each HLC station or nearby M-trap , were placed in separate labelled paper cups . On each morning after the field experiments , the content of each cup was sorted separately into distinct morphologically-identified mosquito taxa , at genus ( Culex spp . and Mansonia spp . ) , species group ( An . funestus sensu lato ) or species complex ( An . gambiae sensu lato ) level . A sub-sample of specimens identified as members of the An . gambiae s . l . complex was taken to the laboratory where identification to sibling species level was carried out by polymerase chain reaction [27] . All data describing the details of the field experimental design , numbers of mosquitoes caught from each sorted taxon , and identified as members of various An . gambiae s . l . sibling species in the laboratory were recorded using the ED1 , SS1 and SO1 paper forms recently described for informatically-robust , standardized collection of mosquito data in entomological experiments or surveys [28] . Experiments to measure concentrations of transfluthrin in air were conducted by BioGenius and Dräger Safety AG & Co . KGaA , two independent analytical services companies in Germany ( See S1 Supporting Information for the detailed report ) . A hessian strip exactly like those described above was treated with 1ml of transfluthrin ( 98 . 9% , Bayer CropScience AG , Germany ) , by first suspending in water and detergent in exactly the same way as above , and then cut into four equal pieces . Only one of these pieces was placed in an enclosed room , to avoid overloading the sorbent capacity of the collection tubes used . The rooms each had an internal volume of 30m3 ( length = 4 . 69m , width = 2 . 56m and height = 2 . 50m ) with internal air temperature varying between 21 . 9 and 24 . 0°C . These rooms were completely sealed , leaving the keyhole as the only point of air flow , in which two tubes containing 13 . 6g of Tenax TA adsorbent ( Dräger Safety AG & Co . KGaA , Germany ) were placed . Air from inside the test-rooms were sucked through the tubes using suction pumps set at an airflow rate of 1 . 5 l·min-1 , so that hydrophobic molecules like transfluthrin were adsorbed onto the Tenax TA matrix . The key hole was 96cm above the floor and the strip was placed 1 . 9m from the floor . The rooms were fitted with an electric fan to improve air circulation , but the fan was faced away from the treated strip . The first set of tubes in the keyhole of each room was collected after 1 hour and the second after 24 hours . The quantity of transfluthrin retained within the tubes was determined by thermal desorption followed by gas chromatography using mass spectrometry detection , in accordance with guideline DIN/ISO 16000–6 . Data was entered in Microsoft Excel and analysed using R statistical software version 3 . 1 . 3 , augmented with the lme4 package for fitting generalized linear mixed models ( GLMMs ) . Separate statistical analyses were conducted for each mosquito taxon that was common in the study area , specifically An . arabiensis , Culex spp . , and Mansonia spp . As ≥75% protection against mosquito bites was only observed in the first phase of long-term efficacy studies , lasting 48 weeks since the strips were treated , analysis was restricted to this subset of data , over which period the properties of the strips at least approached the target product profile requirements of outlined for spatial repellents [29] . In order to determine the influence of treated strips upon mosquito biting rates experienced by the user and the non-user at a range of distances from the user , GLMMs of mosquito catch count data for each one or two hour period of the night were fitted for each distinct distance , with the users of treated strips conducting HLC in TC-CT or CT-TC arrangements considered to be at 0m distance , while users of untreated controlled strips conducting HLC at the opposite station in these same arrangement representing non-users at 80m distance . To estimate the effect of treatment at each distance , the treatment status of the strip in which the user sat in that particular station on that particular night ( TC in any TC-CT or CT-TC arrangement ) was treated as a categorical factor in the model , with the catches on users of untreated strips in arrangements with no treated strips ( both CC observations in CC-CC arrangements ) as the reference group and catches on users of untreated strips opposite users of treated strips in the same station on the same night ( CT in any TC-CT or CT-TC arrangement ) excluded from the analysis in case any diversion of mosquitoes might increase their exposure so that they do not represent true normal individuals in the absence of any intervention . This possibility of mosquito diversion from the users of treated strips to the users of untreated strips , considered as non-users at 80m distance , was similarly accomplished by changing the contrast and reference groups , treating catches on users of untreated strips opposite users of treated strips in the same station on the same night ( CT in any TC-CT or CT-TC arrangement ) as the test group , while the catches on users of untreated strips in arrangements with no treated strips ( both CC observations in CC-CC arrangements ) as the reference group were treated as the reference group . The GLMMs fitted to these mosquito catch data applied a Poisson distribution to these count observations , with observation treated as random effect so that the logarithmic transformation of the Poisson function could normalize these otherwise over-dispersed data . Other random effects included in the models were site , date , and period of the night . Note that the collection method was not included as a variable in any of these models because it was consistently either one or the other for all the data subsets each different model for each different distance ( HLC for 0m and 80m or M-trap for 2 , 5 , 10 , 20 , 30 and 40m ) was fitted to . No prospective measurements of temperature were recorded at the field site so , after it was noticed in the field that transfluthrin-treated strips were less efficacious at lower temperatures , satellite-derived mean daily air temperature estimates for the study area ( longitude 34 . 688° to 36 . 563° by latitude -9 . 524° to -7 . 619° ) were obtained from National Center for Environmental Prediction/National Center for Atmospheric Research with halfway grid points included from mean daily reanalysis since 1948 ( http://www . esrl . noaa . gov/psd/data/gridded/data . ncep . reanalysis . html ) . In order to test for the effect of temperature upon protective efficacy , this variable ( Expressed in units as degrees Centigrade ) was added as an independent variable to the model described for strip users ( considered to be at 0m distance ) . Similarly testing for the effect of time since treatment upon protective efficacy , was achieved by adding the number of weeks since the strip had been treated to the same model . The effect of different doses upon the protective efficacy of transfluthrin-treated strips was tested exactly as described above for the primary evaluation of their impact for users and for non-users at various distances , except that non-user data collected with M-traps was excluded from the analysis and different models were fitted for each different dose evaluated .
Strips treated with 10ml of transfluthrin prevented at least three quarters of outdoor bites by An . arabiensis , Culex spp . and Mansonia spp . mosquitoes for at least one year ( Relative protection ( RP ) [95% confidence interval ( CI ) ] = 0 . 85 [0 . 71 , 0 . 91] , 0 . 92 [0 . 78 , 0 . 97] and 0 . 94 [0 . 80 , 0 . 98] , respectively , P<0 . 001 in all cases ) , and conferred significant protection for the entire 2 . 5 year study duration ( Fig 3 ) . Treated strips significantly reduced relative biting exposure to mosquitoes ( An . arabiensis: p < 0 . 004; Culex spp . : p < 0 . 001 and Mansonia spp . : p < 0 . 001 ) , particularly when preceding mean daily temperatures were greater than 23°C ( Fig 4 ) . During the first year , strips prevented more than 90% of bites by all three major mosquito taxa whenever preceding mean daily temperature reached 23°C or more: ( RP [95% CI] = 0 . 91 [0 . 80; 0 . 96] , p < 0 . 001 ) for An . arabiensis , 0 . 98 [0 . 93; 0 . 99] , p < 0 . 001 for Culex spp . , and 0 . 99 , [0 . 99; 0 . 99] , p < 0 . 001 for Mansonia spp . ) When data was pooled for all nights over the first year with preceding daily mean temperatures below 21°C , mean protection was nevertheless reasonably satisfactory , at approximately 80% for An . arabiensis ( RP [95% CI] = 0 . 80 [0 . 63; 0 . 90] , p < 0 . 001 ) and Culex spp . ( RP = 0 . 80 [0 . 48; 0 . 93] , p < 0 . 0001 ) , and closer to 90% for Mansonia spp . ( RP [95% CI] = 0 . 89 [0 . 89; 0 . 89] , p < 0 . 001 ) . In addition to protecting the actual users sitting within their perimeter ( Fig 2A ) , strips treated with the same 10ml dose evaluated in previous studies [17 , 18] even provided almost 50% protection against An . arabiensis ( RP [95%CI] = 0 . 42 , [0 . 34 , 0 . 49] , p < 0 . 001 ) to non-users ( humans acting as baits in M-traps ) located within 5m of them ( Fig 5 ) . However , no significant protection of non-users , even at only 2m distance , was observed for Culex spp . or Mansonia spp . ( Fig 5 ) . Reassuringly , no evidence of diversion of mosquitoes from any major taxa from users to non-users was observed at any distance evaluated up to 80m radii ( Fig 5 ) . As little as 1ml of transfluthrin provided equivalent protective efficacy to strips treated with the 10-fold higher dose previously evaluated , and no increase in protective efficacy was observed as dosage was increased beyond that minimum required level ( Fig 6 ) . For instance 1ml transfluthrin treated strips reduced biting exposure to An . arabiensis ( RP [95%CI] = 0 . 71 [0 . 62 , 0 . 78] , p < 0 . 001 ) to the same degree as the 10ml dose ( RP [95%CI] = 0 . 66 [0 . 58 , 0 . 73] , p < 0 . 001 ) . The quantity of transfluthrin collected within 1 hour from the rooms with treated strips inside was below the detection threshold of 2ng per tube . After 24 hours the quantities of transfluthrin recovered from tubes were 623ng , 1370ng and 863ng from each room , corresponding to a mean ( ± standard error ) concentration in air of only 0 . 13 ± 0 . 06 μg·m-3 , which is >1000 times lower than the maximum acceptable exposure concentration for long-term inhalation exposure of human beings of 500 μg·m-3 , as defined by the regulatory authorities of the European Union ( EU ) [30] .
Despite these study limitations , the experiments reported here clearly demonstrate how transfluthrin-treated hessian emanators can provide safe , affordable , long-term protection against three of the most medically important mosquito taxa in the world , one of which was known to be resistant to conventional , solid-phase pyrethroids at the time [20] . Crucially , all the protective efficacy measurements reported in Figs 3 to 6 were conducted outdoors , where active humans cannot be protected by bed nets or residual sprays with conventional , solid-phase insecticides . In addition to the long-standing problems of outdoor transmission of a range of mosquito-borne pathogens through multiple vectors [1] , the recent rapid spread of pandemic urban Zika virus transmission from human to human [50] via several potential vectors that often bite outdoors now merits urgent attention [51 , 52 , 53] . Further studies to adapt this prototype to formats suitable for programmatic scale-up , and to assess their impacts and mechanisms of action when applied at high coverage across entire populations , should therefore be immediately prioritized . | Many vector-borne parasites and arboviruses are transmitted by outdoor-biting mosquitoes , especially in the evenings and mornings , often despite high coverage of houses with insecticidal nets and residual sprays . The goal of the study was to measure the long-term durability of protection provided by a new , low-technology , passive emanator for the volatile pyrethroid transfluthrin against outdoor-biting mosquitoes . Treated hessian strips reduced exposure of users to three different types of vector mosquitoes by more than three quarters over the first year after treatment , and prevented more than 90% of bites on warmer nights when the active ingredient evaporated faster . Treated strips protected non-users against some vector mosquito species , as far away as 5m from the strip . Reassuringly , mosquitoes were not diverted to nearby unprotected individuals anywhere within an 80m radius . Transfluthrin-treated hessian strips may have considerable potential for integrated control of multiple vectors of filariasis , arboviruses and malaria , which are co-endemic in many tropical areas . | [
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"surfactants",... | 2017 | A low technology emanator treated with the volatile pyrethroid transfluthrin confers long term protection against outdoor biting vectors of lymphatic filariasis, arboviruses and malaria |
The fidelity of DNA replication requires an appropriate balance of dNTPs , yet the nascent leading and lagging strands of the nuclear genome are primarily synthesized by replicases that differ in subunit composition , protein partnerships and biochemical properties , including fidelity . These facts pose the question of whether imbalanced dNTP pools differentially influence leading and lagging strand replication fidelity . Here we test this possibility by examining strand-specific replication infidelity driven by a mutation in yeast ribonucleotide reductase , rnr1-Y285A , that leads to elevated dTTP and dCTP concentrations . The results for the CAN1 mutational reporter gene present in opposite orientations in the genome reveal that the rates , and surprisingly even the sequence contexts , of replication errors are remarkably similar for leading and lagging strand synthesis . Moreover , while many mismatches driven by the dNTP pool imbalance are efficiently corrected by mismatch repair , others are repaired less efficiently , especially those in sequence contexts suggesting reduced proofreading due to increased mismatch extension driven by the high dTTP and dCTP concentrations . Thus the two DNA strands of the nuclear genome are at similar risk of mutations resulting from this dNTP pool imbalance , and this risk is not completely suppressed even when both major replication error correction mechanisms are genetically intact .
The integrity of an organism's genome is vital to its continued survival , whether unicellular microbe or complex large mammal [1] . Therefore , there are highly conserved mechanisms involved in regulating and protecting genetic material both during and post DNA replication . One of the first safety systems for DNA replication is the stringent control of dNTP synthesis by ribonucleotide reductase ( RNR ) , which maintains concentrations of the individual dNTPs at different levels [1] , [2] . RNR catalyses the rate-limiting step in the production of all four dNTPs for the synthesis of nuclear and mitochondrial DNA [3] , [4] . In yeast , RNR is a multi-subunit complex comprised of a large subunit , which exist as a homodimer of Rnr1 proteins or a heterodimer of Rnr1/Rnr3 proteins , and a small subunit comprised of Rnr2/Rnr4 proteins . The large subunits contain allosteric specificity sites that modulate enzyme activity and control the balance of the four dNTPs by influencing the specific ribonucleoside diphosphate reduction reaction within the catalytic sites [5] . A highly conserved loop of 13 amino acid residues ( Loop 2 ) connects the allosteric specificity and catalytic sites and is crucial for the correct allosteric regulation of the enzyme [6] , [7] . The DNA polymerase selectivity , proofreading and mismatch repair are subsequent safety systems that determine the fidelity of DNA replication . The DNA polymerase selectivity ensures insertion of the correct nucleotide during DNA synthesis . Although the major replicative polymerases alpha ( Pol α ) , delta ( Pol δ ) , and epsilon ( Pol ε ) are high fidelity enzymes , their accuracy is dependent upon the supply of dNTPs [8] . The second mechanism is proofreading in which errors are removed from primer termini during replication by a 3′–5′ exonuclease activity . Errors that escape proofreading can still be repaired post-replication , through the mismatch repair system ( MMR ) ( reviewed in [9] ) . The major components of MMR are the homologs of the bacterial MutS proteins , a heterodimer of either Msh2-Msh6 or Msh2-Msh3 that recognise and bind to the mismatch . Msh2-Msh6 is mainly responsible for repairing single base-base mismatches , short insertions and deletions ( indels ) and small loops , whereas Msh2-Msh3 is involved in larger loop repair . Therefore , Msh2 is essential for MMR [10] and loss of this activity elevates mutation rates [11] . Mutation or loss of Msh2 in humans is associated with microsatellite instability and hereditary nonpolyposis colorectal cancer ( HNPCC ) [12] and gall bladder cancer [13] . The current model of the eukaryotic replication fork involves DNA polymerase complexes with very different subunit composition , enzymatic properties and fidelity . The leading strand is synthesized primarily by Pol ε , while the lagging strand is synthesized primarily by Pol α and Pol δ [14] , [15] . Here we asked whether an imbalanced dNTP pool can force the leading and lagging strand polymerases to produce different errors . It is possible to answer this question by using a gene that is located close to an origin of replication and switching the leading and lagging strand synthesis . We previously created a panel of yeast strains with defined dNTP pool imbalances . The imbalances , in which none of dNTP levels was below normal , did not activate the genome integrity checkpoint and were highly mutagenic despite the availability of functional proofreading and MMR [16] . Utilizing a strain with elevated dTTP and dCTP concentrations and normal dATP and dGTP concentrations , we previously determined the rate and specificity of replication errors generated at the CAN1 locus [17] . As the CAN1 reporter gene is located close to a replication origin , by reversing the orientation of CAN1 and thereby switching the leading and lagging strand synthesis at this locus , we can analyse potential mutational strand bias . To determine the efficiency of DNA mismatch repair in the presence of this dNTP pool imbalance , we also created an rnr1-Y285A mutant strain that was MMR deficient . Our data demonstrate that the mutational potential of this dNTP pool imbalance overpowers the intrinsic differences in error specificity of the leading and lagging strand polymerases and reveals that MMR works with highly variable efficiency .
To examine potential differences in mutational specificity between the major replicative polymerases in the presence of the imbalanced dNTP pools , we reversed the orientation of the CAN1 gene ( CAN1-OR2 ) . To investigate the effect of this dNTP pool imbalance in the absence of MMR , we deleted MSH2 in the rnr1-Y285A CAN-OR1 strain . The msh2Δ single mutant strain had normal dNTP pools ( Fig . 1 ) . The dNTP pools in the double mutant had the same imbalance as in the single rnr1-Y285A [17] , with approximately 26- and 14-fold higher concentrations of dCTP and dTTP , respectively , compared to wild type ( wt ) whilst the concentration of dATP was about double and dGTP was normal ( Fig . 1 ) . The spontaneous CAN1 mutation rate in the rnr1-Y285A CAN1-OR2 was 13-fold higher than wt ( Table 1 ) , which was similar to the CAN1-OR1 previously published OR1 [17] . The msh2Δ mutant had a 15-fold higher mutation rate compared to wt , however , the rnr1-Y285A msh2Δ strain mutation rate was over 500-fold greater than that of wt and over 30-fold either of the relative single mutants . Indels were the major mutation type observed in all four mutant strains whereas it was single base substitutions in wt ( Fig . 2 ) . The rnr1-Y285A , with CAN1 in both orientations , and msh2Δ strains had an average increase in the indel rate of more than 60-fold the wt strain ( 0 . 5×107 for wt versus 33×107 for OR1 [17] , 37× for OR2 , and 42×107 for msh2Δ ) . However , the double mutant indel rate was increased the most at more than 2000-fold over wt . In addition to single base indels , base substitutions were also significantly increased in the mutants to over 8-fold higher in the single mutants and 350-fold higher in rnr1-Y285A msh2Δ compared to wt . Complex mutations , defined as mutations involving insertions or deletions of multiple bases , were much more common in the double mutant , occurring at a rate over 30 times higher than that in wild type . Replication of the CAN1 gene originates from ARS507 and travels through the gene towards the telomere [18]–[20] ( Fig . 3A ) . Therefore , in rnr1-Y285A CAN1-OR1 the leading strand polymerase , presumed to be Pol ε [21] , uses the non-coding strand as the template while the coding strand is the template for lagging strand replication primarily by Pol δ or Pol α [14] . In CAN1-OR2 , Pol ε now copies the coding strand and Pol δ/Pol α copy the non-coding strand ( see Fig . 3A ) . An example is given in Fig . 3B , for the single base substitution at 648 bp . During leading strand synthesis in OR1 , no mistake is made when copying template G due to high concentration of dCTP . However , during lagging strand replication dTTP is inserted opposite template C , as dTTP is at a much higher concentration than the dGTP required for correct pairing . As the succeeding incoming nucleotides are also at an increased concentration , rapid extension then follows stabilizing the C: dT mismatch . In the next round of replication , a C to A mutation arises . When the gene is reversed in rnr1-Y285A CAN1-OR2 , Pol ε now copies the template C with low fidelity by misinserting dTTP , which ultimately results in a C to A mutation , and Pol δ/Pol α replication is error-free . Hotspots , mutation sites where the rates were ≥10-fold greater than wt , were assigned to have occurred during leading or lagging strand synthesis by the nature of the mutation observed and dNTP pool imbalance . Simplified mutational spectra illustrating the hotspots in the CAN1 gene for each strain are shown in Fig . 4 with the full spectra in Figure S1-S3 . The hotspot mutation rate was calculated by the equation [ ( frequency/total no . of samples ) x CAN1 mutation rate] . The majority of hotspots in rnr1-Y285A CAN1-OR1 and OR2 show no leading – lagging strand bias and have similar mutation rates in both strains ( Fig . 5 ) . However , the major hotspot at position 425–427 bp was only seen in OR2 and had a mutation rate of 48×10−8 which was 15-fold higher than in OR1 . The rnr1-Y285A and msh2Δ strains had several shared major hotspots . Three single base deletions occurred in G: C homopolymeric runs at 757–760 bp , 795–797 bp , and 857–859 bp and two single base substitutions at 313 bp and 1379 bp ( Fig . 4 and Table S1 ) . Whilst the double mutant shared these five hotspots with both single mutants , there was a more than 100-fold increase in rates for base substitutions at 313 bp and 13791 bp ( Fig . 6A and Table S1 ) . The major hotspots in rnr1-Y285A msh2Δ were those seen in msh2Δ at 1118–1121 bp , 1392 bp , and especially the dominant deletion hotspots at 620–625 bp , 964–969 bp , and 1381–1386 bp . The site-specific mutation rates in the double mutant ranged from 4- to 800-fold the single mutants . Analysis of the mutation spectra in the rnr1-Y285A and rnr1-Y285A msh2Δ strains showed that MMR had different efficiency at distinct mismatches . The ratio of mutation rates in the msh2Δ and MMR-proficient strains gave site-specific MMR correction efficiency ( Fig . 6B and Table S1 ) . The five hotspots ( 314 , 718 , 757 , 795 and 857 bp ) , which include those with the highest mutation rates in the single rnr1-Y285A mutant , were the same sites that MMR was the least efficient at repairing errors . The correction factors were less than 30 and only around 10 in four of these sites ( i . e . , around 10% of errors at these sites will remain uncorrected by MMR ) . The majority of sites with the highest mutation rates in the double mutant ( 620 , 964 , 1118 , 1381 , and 1392 bp ) were those that MMR was best at repairing , namely at T: A mononucleotide repeats . Loss of MSH2 increased the mutation rate at these sites by 260- to 800-fold .
Despite the inherent differences in complexity of continuous ( leading strand ) and non-continuous ( lagging strand ) synthesis , the increased dCTP and dTTP drive the same kind of mutations at identical sequences regardless of the replicative DNA polymerase . Most of the mutations occurred at a G: C base pair in which the cytosine served as the template for synthesis and was often flanked by a 5′-A or a tract of purines as exemplified in Fig . 3 . With the concentration of dGTP being the lowest and dCTP and dTTP the highest , the deletion of a G: C base pair in a mononucleotide repeat is stabilized by the rapid incorporation of the next incoming nucleotide ( dTTP opposite the template A ) , as described in detail in our previous report [17] . This dNTP imbalance and sequence context also explains the G: C to T: A base substitutions where dTTP is misinserted opposite template C and mismatch extension proceeds with the rapid incorporation of the pyrimidines opposite the flanking tract of purines . Thus , the mismatch remains at the expense of polymerase proofreading . However , an exception was found at 425 bp ( where there is a hotspot found only when the CAN1 gene is reversed to OR2 ) . Although similar sequences ( AT runs ) show no variation in mutation rates between orientations it appears that polymerase δ or α could be making a mistake at this point but not Pol ε . There were also several minor hotspots that suggest polymerase specificity ( positions 538 , 937 , and 971 were unique to OR1 whereas 387 and 1353 were seen only in OR2 ) which could be indicative of the differences in polymerase efficiency in certain sequence contexts . Whole genome sequencing may give insight into other sites and contexts that affect polymerase specificity and establish the patterns of mutations arising in the presence of this dNTP pool imbalance . Given that the concentration of dATP was also lower than dCTP and dTTP , T: A to G: C transversions could also be expected in the base substitution hotspots where dCTP is misinserted opposite template T during replication . The nucleotide ratio of dCTP: dATP increased from ∼1∶1 in the wt strain to ∼6∶1 in the rnr1-Y285A strains . However , the increase in the nucleotide ratio of dTTP: dGTP was larger , from ∼4∶1 in the wt strain to ∼38∶1 in the rnr1-Y285A strains , which may explain the prevalence of the G: C to T: A transversions . Furthermore , the lack of T: A to G: C transversions may be due to the intrinsic difference in the rates at which the two errors are generated . Recent genome-wide studies in S . cerevisiae have reported that G: C to T: A transversions were observed at a higher rate than T: A to G: C in strains with normal dNTP pools [22] , [23] . The three major replicative polymerases were more prone to generate G: C to T: A transversions but very rarely generated T: A to G: C transversions [23] . In addition , tumours with somatic mutations in the exonuclease domain of Pol ε have a higher prevalence of C to A mutations [24]–[28] . MMR efficiency was dependent upon the site and mismatch generated from the dNTP pool imbalance . The increase in indels in the msh2Δ strains was not surprising as MMR is known to be highly active at repairing mistakes at mononucleotide repeats [29] , [30] . The indels were almost entirely unique to sequences with ≥3 mononucleotide repeats in the double mutant ( 99 . 2% , 127 of 128 ) compared to 91% in the msh2Δ mutant and most frequently occurred in A: T runs . This can be predicted as A-T mononucleotide repeats are often the site of indels in MMR deficient strains [31] and are by far the most common in the CAN1 gene sequence ( Figure S4 ) . Indeed , it appears that the relationship between mutation rate and mononucleotide repeat length is exponential as others have found across the whole yeast genome [22] . The MMR correction factor for all indels in the rnr1-Y285A background was 32 , which means that on average , 31 of 32 indels are corrected by MMR ( compare Fig . 2 rates ) . Nevertheless , this is ∼3-fold lower than that in the wt RNR background suggesting that some indels driven by this dNTP pool imbalance escape MMR . In addition , there were several major indel hotspots , mainly at G: C base pairs in mononucleotide repeats , with correction factors of 10 compared to the indels at A: T repeats which ranged from 200 to 800 . This is a huge variation in the vital post-replication repair machinery that supports the notion of MMR efficiency being dependent on the dNTP pool imbalance , sequence context , and identity of the mismatch . There are several possibilities as to why MMR is not efficient at these sites in the rnr1-Y285A strain . First , there could be a saturation of MMR due to the volume of errors induced by the pool imbalance that are not corrected by proofreading [32] . Consider the hotspots at 795 and 857 bp which dominated the spectra in rnr1-Y285A . The correction factor for the wt RNR strain was more than 2- and 5-fold higher than for the rnr1-Y285A mutant at the 795 and 857 hotspots , respectively ( S1 Table ) . Therefore , MMR was more accurate at repairing deletions at these sites in the wt RNR strain with normal dNTP pools . Second , MMR itself may require a natural dNTP pool balance in order to correctly repair mistakes . If MMR complexes recognise the mismatches generated but recruit an error-prone or even high fidelity polymerase , the imbalanced dNTP concentration may result in the same mismatch; thus , the mutation is maintained . Finally , some mismatches may not be subjected to MMR if they are damaged or generated outside of DNA replication [33]–[37] .
The CAN1 gene was replaced with URA3 from the pUG72 plasmid [38] ( primers “CAN1 Del Ura3” in Materials and Methods S1 ) in the RNR mutated strain ( rnr1-Y285A ) previously described [16] . PCR amplified WT CAN1 in reversed orientation ( primers “CAN1 orientation” in Materials and Methods S1 ) was then transformed into the can1:: URA3 strain to give rnr1-Y285A CAN1 OR2 . 5-FOA selection allowed the elimination of any can1:: URA3 cells and the CAN1 reverse orientation was confirmed by sequencing ( “can1ori scr” primers in Materials and Methods S1 ) . An MMR deficient strain was created by deleting MSH2 in the AC402 wt ( to give msh2Δ ) using the pAG32 plasmid and transfection technique [39] and the primers msh2_hphMX4 , shown in Materials and Methods S1 . The deletion was confirmed using primers flanking MSH2 . This strain was then crossed with rnr1-Y285A [16] , sporulated and dissected spores selected on Hygromycin and –Trp plates for the double mutant rnr1-Y285A msh2Δ . All culturing was carried out at 30°C in YPAD ( 1% yeast extract , 2% bacto-peptone , 20 mg/l adenine , 2% agar for plates ) liquid cultures in a shaking incubator at 160rpm . The Canavanine resistance assay was used to calculate mutation rates as previously described [17] , [40] , [41] . The Canr colonies were picked and the CAN1 gene amplified and sequenced ( MWG Eurofins ) using published primers [17] to produce the mutation spectra . dNTP pools were measured in asynchronous cultures as described previously [16] with minor changes as described in [42] . Briefly , cells were harvested by filtration at a density of 0 . 4×107 to 0 . 5×107 cells/ml and NTPs and dNTPs were extracted in trichloroacetic acid and MgCl2 followed by a Freon-trioctylamine mix . dNTPs were separated using boronate columns ( Affigel 601 , Biorad ) and analysed by HPLC on a LaChrom Elite UV detector ( Hitachi ) with a Partisphere SAX column ( Hichrom , UK ) . | The building blocks of DNA , dNTPs , are vital to life , and thus their production is carefully controlled within each cell . Under certain conditions , such as cancer , infection , or drugs , the overall dNTP level or dNTP balance can change . Using yeast genetics we manipulated the dNTP pool balance in unicellular baker's yeast and analysed the effects upon fidelity of DNA replication . We also disrupted mismatch repair , an internal safety system that corrects replication errors and is mutated in many cancers . By sequencing DNA from yeast cells with these alterations we gain insights into the mechanisms of mutation formation that contribute to genome instability . We find that the leading and lagging strand replication fidelity is affected similarly by the dNTP pool imbalance and that the mismatch repair machinery corrects replication errors driven by a dNTP pool imbalance with highly variable efficiencies . | [
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] | [
"biochemistry",
"dna",
"metabolism",
"dna",
"replication",
"genetics",
"biology",
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] | 2014 | Increased and Imbalanced dNTP Pools Symmetrically Promote Both Leading and Lagging Strand Replication Infidelity |
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