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555849 | Clotting state after cardioversion of atrial fibrillation: a haemostasis index could detect the relationship with the arrhythmia duration | Background Fibrin D-dimer levels have been advocated as an useful clinical marker of thrombogenesis. Hypothesis We hypothesized that i) there is a hyperclotting state after the return of atrial fibrillation to sinus rhythm, ii) the measurement of plasma D-Dimer levels might be a good screening tool of this clotting status, and iii) the duration of arrhythmia influences the haemostasis measured by plasma D-Dimer levels. Methods Forty-two patients with atrial fibrillation undergoing cardioversion were divided into two groups: in Group A (n = 24,14 male, 56 ± 11 years) the duration of atrial fibrillation was 72 hours or more (142.7 ± 103.8 hours), in Group B (n = 18, 10 male, 61 ± 13 years) the duration of atrial fibrillation was less than 72 hours (25 ± 16 hours). Plasma fibrin D-dimer levels were measured by enzyme immunoassay before, and 36 hours after, cardioversion. The change of plasma D-dimer levels 36 hours after cardioversion was calculated as delta-D-dimer. Results There were no significant differences in demographic, clinical, and echocardiographic data, and the success of cardioversion between the two groups. Compared to the control, the baseline D-dimer levels were significantly higher in both groups. The delta D-dimer levels were significantly higher in Group A than in Group B (p < 0.005). Furthermore, plasma D-dimer levels 36 hours after cardioversion (r = 0.52, p = 0.0016) and delta-D-dimer levels (r = 0.73, p < 0.0001) showed significant correlations with the duration of atrial fibrillation. Conclusion The longer duration of the atrial fibrillation episode could lead to a more prominent cardiovascular hyperclotting state after cardioversion, and the mean changes of plasma D-Dimer levels could be used as an useful clinical marker of the clotting state after atrial systole return. | Introduction Atrial fibrillation is the most common sustained arrhythmia in clinical practice. It is associated with an increased risk of thrombus formation, resulting in substantial morbidity, with the augmented risk of stroke being the most serious. This could be explained by haemostasis conditions favouring thrombosis: previous studies have demonstrated that in most patients, AF is a high risk factor for hypercoagulability, irrespective of underlying structural heart diseases or aetiology [ 1 - 8 ]. In addition, it is well known that the direct current cardioversion of atrial fibrillation, especially if persisting >48 h, carries a great risk of thromboembolism, which extends to 5% of cases not receiving anticoagulant therapy. The mechanism and pathogenesis of thromboembolic episodes after restoration of sinus rhythm in these patients is not completely understood. There is some evidence that the prothrombotic state associated with atrial fibrillation might contribute towards the risk of thromboembolism following cardioversion, but reports are not clear. In this context, having a marker of coagulation activation would be useful in identifying patients at highest thromboembolic risk. Indicators of hypercoagulability, such as D-dimers, which are indicative of a prothrombotic state, might also be indicative of thromboembolic risk [ 9 ]. D-dimers, which originate from the formation and lysis of cross-linked fibrin, are therefore specific markers of coagulation activation. In AF elevated D-dimer levels have been reported to be associated with left atrial appendage dysfunction [ 10 ], and the potential presence of atrial thrombi. Anticoagulation does reduce D-dimer levels, but there were no significant correlations of D-dimer levels with either warfarin dose or the INR [ 11 , 12 ]. D-dimer levels may also increase as a result of comorbidity conditions causing intravascular (i.e. in thrombosis) or extravascular cross-linked fibrin turnover, such as in renal failure, liver impairment, acute or chronic infection, neoplastic disease, hypertension, acute cardiovascular syndromes, bleeding, haematoma and surgery. The interpretation of D-dimer levels can, therefore, be considered as reflecting the prothrombogenic state of patients without these acute clinical conditions, and without overt thrombosis. [ 9 ] However, the age of the patient must be considered: D-dimer levels are reported to increase with age [ 13 - 15 ], which makes the interpretation of D-dimer measurement very difficult and hazardous in older people. Thus, before an evaluation of the predictive role of D-dimer levels for thromboembolic events in AF patients can be made, two conditions must be fulfilled: D-dimer levels should be characteristic of each patient with AF, and the presence of co-morbidity should be excluded. We therefore hypothesized that i) there is still a hyperclotting state after return of sinus rhythm, ii) the measurement of plasma D-dimer levels pre- and post-cardioversion might be a good screening tool of this clotting status, and iii) the duration of arrhythmia could be a good predictor of thromboembolic events after cardioversion, due to the influence on haemostasis measured by plasma D-dimer levels. Methods Over a period of 18 months, we studied 42 consecutive patients, aged between 39–68 years old, with non-valvular atrial fibrillation who underwent successful electrical cardioversion and who remained in sinus rhythm at the one-month visit. Exclusion criteria were other acute causes of atrial fibrillation (for example, thyrotoxicosis, pneumonia or other infections), acute cardiovascular or cerebro-vascular events (myocardial infarction, congestive heart failure, stroke, etc) occurring within five months, valvular heart disease, malignancy, connective tissue disease, infectious or inflammatory conditions and chronic renal/hepatic disease. The patients were divided into two groups. In Group A (24 pts, 14 male, 56 ± 11 years), the duration of atrial fibrillation was 72 hours or more (142.7 ± 103.8 hours). In Group B (18 pts, 10 male, 61 ± 13 years) the arrhythmia had a duration of less than 72 hours (25 ± 16 hours). We included only patients treated with anticoagulant-coumadin for chronic prophylaxis. There was not a statistically significant difference between the mean duration of anticoagulation treatment between the two groups (14 ± 4 months for group A and 12 ± 6 months for Group B). Prothrombin time to an INR (international normalized ratio) of 2.5–3 was considered as a necessary inclusion criterion for all patients. The total population had a history of drug refractory atrial fibrillation, with a serious number of arrhythmia episodes. We only analyzed the documented arrhythmia episodes. The total number of documented episodes of paroxysmal atrial fibrillation in Group A was 33, and in Group B the patients had 36 confirmed arrhythmia episodes. There were no significant differences in age, sex, hematocrit, hemoglobin, plasma fibrinogen level, underlying heart disease, success ratio of electrical cardioversion, echocardiographic data, presence of diabetes mellitus or hypertension between the two groups. The clinical characteristics of the patients are shown in Table 1 . AF was seen at the 12 lead surface electrocardiogram. We compared the D-dimer levels of these two groups at baseline, before cardioversion with a matched control group (n = 19) without atrial fibrillation. Plasma Fibrin D-dimer levels were measured before, and 36 hours after, cardioversion. Anticoagulation reduces D-dimer levels, but as we analyzed the D-dimer levels of the same patients pre- and post-cardioversion, we did not need to use a cut-off value, and all patιents were under coumadin treatment with an INR (international normalized ratio) of 2.5 to 3 at least 3 weeks before cardioversion, and 36 hours post-cardioversion. The study protocol was approved by the local ethics committee (Academic Hospital of Alexandroupolis decision 09/11/2002). All patients received oral and written information concerning the background of the study, and signed informed consent. Table 1 Clinical Characteristics for Total Study Group Group A (n = 24) Group B (n = 18) Control Group (n = 19) Age (years) 56 ± 11 61 ± 13 59 ± 12 Male gender 14(58%) 10(56%) 10(57%) Smokers 15(62.5%) 11(62%) 11(62.5%) Systolic Blood Pressure (mmHg) 145 ± 20 143 ± 22 139 ± 25 Diastolic Blood Pressure (mmHg) 80 ± 10 82 ± 11 80 ± 11 Known hypertension (160/90 mmHg) 8 (33.4%) 6 (34%) 7(35%) Lone AF 11(45.8%) 8 (44.2%) - Coronary artery Disease 5(20.8%) 4(22%) 5(22.8%) Diabetes mellitus 6(25%) 4(22%) 4(22.3%) Hct(%) 45.8 ± 3.9 44.9 ± 4.2 45 ± 3.6 Hb(g/dl) 15.3 ± 1.34 14.8 ± 2.9 15.2 ± 3.1 Fbg (mg/dl) 229.9 ± 27.0 237 ± 37.6 227 ± 26 P value : non significant (NS) Echocardiographic data for Both Groups pre cardioversion Group A Group B Left atrial diameter(cm) 4.2 ± 0.6 4.0 ± 0.8 Left ventricular diastolic dimension (cm) 5.2 ± 1.0 5.0 ± 0.9 Left ventricular systolic dimension (cm) 4.1 ± 0.5 4.0 ± 0.8 P value : non significant (NS) Laboratory An intravenous line was placed and blood samples for D-dimer measurement were taken from the patients immediately before cardioversion, and 36 hours after recovery of sinus rhythm. Citrated plasma was obtained from venous blood by centrifugation at 2,500 rpm for 15 min at 4°C. Aliquots were stored at -70°C to allow batch analysis. The plasma D-dimer levels were measured by the enzyme-linked immunosorbent assay method. The measurements were obtained with the use of a quantitative sandwich immunochromatographic technique (Cardiac D-Dimer; Roche Diagnostics, Mannheim, Germany). For every blood sample, measurements were done twice. The investigators and attending physicians were blinded to the D-dimer test results. Inrta-assay coefficients of variation for assays were <5%, inter-assay variances were 10%. The changes of plasma D-dimer levels 36 hours after cardioversion were calculated as delta- D-dimer. Echocardiography Echocardiographic examinations were performed in all patients, immediately prior to the procedure and 36 hours after successful cardioversion. Transthoracic echocardiographic two-dimensional imaging and guided pulsed wave Doppler recordings were obtained. Transmitral Doppler inflow velocities were recorded from the apical four-chamber view. Peak velocities of early fillings (E) wave and atrial filling (A) wave were determined. The inter- and intra-observer variability was <5% for these measurements. We did not detect the presence of thrombi in the left atrium. However, the absence of thrombus on transthoracic echocardiography does not preclude the real absence of thrombus. Statistical Analysis Clinical variables are expressed as the mean value ± SD. The effects of duration from the onset of atrial fibrillation on the measured indexes were analyzed by two-way repeated measures analysis of variance (ANOVA). Sequential data pre- and post-cardioversion were analyzed by Friedman's repeated measures analysis of variance. Correlations were performed by Spearman's rank correlation method. Stepwise multiple regression analyses were performed to determine independent predictors for plasma D-dimer levels, using age, sex, left-atrial size, left ventricular dimensions (diastole, systole) presence of underlying medical disease, smoking status, and the presence of atrial fibrillation. A p value < 0.05 was considered statistically significant. Analyses were performed with SAS for Windows 8.02 (SAS Institute Inc., Cary, North Carolina) and GraphPad Prism, version 3.00 (GraphPadSoftware, San Diego, California) statistical software packages. Results The baseline D-dimer levels of each group are shown in Table 2 . The D-dimer levels in the control group were significantly lower than both groups (p < 0.05) (Table 2 ). Table 2 Mean D-Dimer levels at baseline before cardioversion in both groups and the relationship with he control group Group A Group B p value Mean D-Dimer 117 ± 74.7 ng/ml 102 ± 53.8 NS Group A Control Group p value Mean D-Dimer 117 ± 74.7 ng/ml 39.7 ± 28.6 0.05 Group B Control Group p value Mean D-Dimer 102 ± 53.8 39.7 ± 28.6 0.05 The patients' sinus rhythm was restored by applying electrical cardioversion in all study patients. Delta D-dimer levels were significantly higher in Group A than in Group B. (p < 0.005). There were no significant differences in plasma D-dimer levels before, and 36 hours after, cardioversion between the two Groups (Table 3 ). Furthermore, plasma D-dimer levels 36 hours after cardioversion, and delta D-dimer levels showed significant correlations with the duration of atrial fibrillaton: D-dimer 36 hours after CV; r = 0.52, p = 0.0016, delta D-dimer; r = 0.73, p < 0.0001. Table 3 D-dimer levels (ng/ml) in both Groups of Patients D-dimer before CV D-dimer after CV delta D-dimer Group A 117.9 ± 74.7 ng/ml 104.1 ± 59.7 ng/ml 34.2 ± 63.6 ng/ml° Group B 102 ± 53.8 ng/ml 84.7 ± 78. 2 ng/ml -17.3 ± 37.8 ng/ml Values are expressed as mean ± SD, °p = 0.005 vs Group B . The echocardiographic data 36 hours after CV have changed. There was a return of atrial contractility using Doppler echocardiography, as shown by the progressive increase in A-wave velocity (Friedman's repeated measures ANOVA, p < 0.0001). Two embolic stroke events were recorded during the six hours after cardioversion in Group A (8,33%) and none in Group B. The embolic events occurred in two women with an INR of 2.6 and 2.9 respectively. At the onset of the event one patient had D-dimer levels of 112.2 ng/ml while the second patient had D-dimer levels of 109.8 ng/ml. Fortunately, these were transient events. The computerized tomography detected non-extentend thromboembolic areas. Discussion In the present study we analyzed D-dimer levels as a screening index of a hyperclotting state after cardioversion of atrial fibrillation. It would be more useful if we used the term abnormal haemostasis, because the fibrin D-dimer is a cross-linked degradation product, resulting from the balance between thrombogenesis and the fibrinolysis process. Fibrin D-dimer levels have been established as a useful clinical marker of thrombogenesis. [ 16 ] The use of D-Dimer levels in the investigation and management pathway of venous thromboembolism is well established. [ 17 ] This marker has a high sensitivity and specificity in excluding thromboembolism, when a well-defined assay is used in the appropriate clinical setting. [ 18 ] In "normal" patients, elevated D-dimer levels have been associated with a higher risk of developing cardiovascular disease. [ 19 ] Also, such cross-linked fibrin degradation products have been shown to be strong and independent predictors of the severity of occlusive peripheral artery disease [ 20 ]. Patients with long-lasting episodes of atrial fibrillation or chronic atrial fibrillation are characterized by increased levels of plasma D-dimers [ 21 , 22 ], platelet activation, and endothelial damage and/or dysfunction, which is consistent with the increased predisposition to thrombus formation in this group of patients [ 23 ]. Some investigators have shown that the cardioversion of atrial fibrillation to sinus rhythm results in a decrease of D-dimer levels [ 24 ]. Our data showed elevated D-dimer levels in individuals who received appropriate anticoagulation therapy at the time of cardioversion. This may suggest the presence of some remaining clot. But we could not estimate this hypothesis because we did not have the profile of D-dimer levels of all patients during a long period before the time of enrolment. In the present study, the plasma D-dimer levels decreased in both groups after successful cardioversion, but the mean change in D-dimer levels pre- and post- cardioversion was significantly lower in Group A than in Group B, and D-dimer levels continued to be high, even 36 hours after the procedure in Group A. There were reported embolic events in 8.33% of Group A patients, with the higher delta D-dimer. These data confirm the existence of an abnormal clotting state after the cardioversion of atrial fibrillation, which could be the cause of the thromboembolic events observed after the return to sinus rhythm, even under anticoagulation. The mechanism of thromboembolism is debatable. The results we found could suggest an embolism might be caused by detachment of a formed thrombus during the phase of passage from AF to sinus rhythm, due to being heavily compromised by stunning the mechanical function of the left atrium and left atrium appendage after sinus rhythm restoration. The stunning of the left atrium and left atrium appendage might attenuate the thrombogenetic activation which our result showed. In the present study we also provided evidence that this hypercoaguable state after successful cardioversion of atrial fibrillation related directly to the duration of the arrhythmia episode. It has been accepted that chronic atrial fibrillation is characterized by increased levels of plasmatic D-dimers, with a wide inter-individual variability, depending on the patients and therapeutic characteristics. However, it has not been established if this level could also be characteristic of paroxysmal or persistent atrial fibrillation in patients, and whether it could be a predictive factor for the risk of thromboembolic events after cardioversion to sinus rhythm. Our results show that longer duration of atrial fibrillation could lead to a more prominent cardiovascular hyperclotting state after cardioversion and that the duration of the arrhythmia episode might be a risk factor for the high incidence of post-cardioversion thromboembolic events. Importantly, this hypercoaguable state does not appear to be subject to any other clinical variables, nor is it related to whether or not the patient had a lone atrial fibrillation or not, suggesting that the duration of the arrhythmia episode confers a constant prothrombotic state per se, after cardioversion to sinus rhythm, which was independent of the etiology but dependent on the duration of the arrhythmia. Interestingly enough, this hyperclotting state after cardioversion exists even under appropriate anticoagulative treatment. The relation of the markers of accelerated coagulation to clinical or echocardiographic risk factors for thromboembolism is controversial. Our results clearly demonstrate a positive correlation of the based on the arrhythmia duration clinically predicted embolic risk to the mean change of plasma D-dimer levels 36 hours after successful cardioversion. We could not detect any relation to the echocardiographic risk factors, probably due to our inability to perform a transesophageal echocardiography. The present study suggests that even in the absence of clinical conditions causing increased embolic risk, patients with signs of accelerated coagulation are at risk of thrombus formation in the future. In conclusion, a longer duration of the atrial fibrillation episode could lead to a more prominent cardiovascular hyperclotting state after cardioversion, and the mean changes of plasma D-Dimer levels could be used as an useful clinical marker of the clotting state after atrial systole return. Clinical implications Our study might have practical implications for the management of patients with an episode of atrial fibrillation, regardless of the anticoagulative treatment they are receiving: the episode must be terminated as soon as possible, because the pathogenesis of thrombus formation in atrial fibrillation is very complex and not yet completely defined. Further investigations with a large population are needed to define all the pathophysiologic mechanisms of thrombus formation. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555849.xml |
512280 | Comparison of the accuracy of methods of computational haplotype inference using a large empirical dataset | Background Analyses of genetic data at the level of haplotypes provide increased accuracy and power to infer genotype-phenotype correlations and evolutionary history of a locus. However, empirical determination of haplotypes is expensive and laborious. Therefore, several methods of inferring haplotypes from unphased genotypic data have been proposed, but it is unclear how accurate each of the methods is or which methods are superior. The accuracy of some of the leading methods of computational haplotype inference (PL-EM, Phase, SNPHAP, Haplotyper) are compared using a large set of 308 empirically determined haplotypes based on 15 SNPs, among which 36 haplotypes were observed to occur. This study presents several advantages over many previous comparisons of haplotype inference methods: a large number of subjects are included, the number of known haplotypes is much smaller than the number of chromosomes surveyed, a range in values of linkage disequilibrium, presence of rare SNP alleles, and considerable dispersion in the frequencies of haplotypes. Results In contrast to some previous comparisons of haplotype inference methods, there was very little difference in the accuracy of the various methods in terms of either assignment of haplotypes to individuals or estimation of haplotype frequencies. Although none of the methods inferred all of the known haplotypes, the assignment of haplotypes to subjects was about 90% correct for individuals heterozygous for up to three SNPs and was about 80% correct for up to five heterozygous sites. All of the methods identified every haplotype with a frequency above 1%, and none assigned a frequency above 1% to an incorrect haplotype. Conclusions All of the methods of haplotype inference have high accuracy and one can have confidence in inferences made by any one of the methods. The ability to identify even rare (≥ 1%) haplotypes is reassuring for efforts to identify haplotypes that contribute to disease in a significant proportion of a population. Assignment of haplotypes is relatively accurate among subjects heterozygous for up to 5 sites, and this might be the largest number of SNPs for which one should define haplotype blocks or have confidence in haplotype assignments. | Background Very rapid and inexpensive methods exist for determining the genotype of diploid organisms at single nucleotide polymorphisms (SNPs). Unfortunately, these high-throughput methods do not provide direct information on which SNP alleles at multiple sites coexist on the same chromosome. Instead, computational methods must be employed to infer the set of SNP alleles that are cosegregating on a single chromosome, referred to as haplotypes. However, the inference of haplotypes from phase-unknown data is computationally difficult, partly due to the fact that the number of possible haplotypes roughly increases as a power of 2 with each additional SNP. Interest in the accurate inference of haplotype structure from unphased genotypic data has increased tremendously in recent years for several reasons. Relative to analysis of single polymorphisms, haplotypes can greatly improve one's ability to infer the evolutionary history of a DNA region [ 1 , 2 ]. Additionally, haplotypes can provide significant increases in statistical power to detect associations between a phenotype and genetic variation [ 3 - 5 ]. Indeed, several disease associations with haplotypes have been detected that were not apparent from single-site analyses [ 6 - 9 ]. There are three principal computational approaches to inferring haplotypes from unphased SNP data. The most commonly used approach is implementation of the expectation-maximization (EM) algorithm [ 10 ]. This method is computationally intensive and is usually combined with various strategies to simplify the task (i.e., by considering only subsets of the sites at a time) or to minimize the number of potential haplotypes that must be considered [ 11 , 12 ]. A more recent alternative is application of Bayesian methods that incorporate prior expectations based upon population genetic principles [ 13 - 15 ]. A third method based on parsimony ("subtraction method"; [ 16 ]) has the limitation that haplotypes are assigned only in unambiguous cases [ 17 ], and the level of ambiguity generally increases with the number of sites considered or the number of sites at which an individual is heterozygous. This limitation is expected to be significant in large-scale analyses of SNP variation, and for this reason the subtraction method is not considered here. Unfortunately, it is unclear how accurate the EM and Bayesian approaches are or whether the EM or Bayesian method is superior in inferring haplotypes, particularly when applied to empirical data. Data simulation [ 18 ] can explore the effect of a wide range of parameters and population dynamics (i.e., linkage disequilibrium, selection, population substructuring) but is unlikely to achieve fully the complex combinations of these effects inherent in empirical data. On the other hand, comparisons using empirical data have been based on as few as six SNPs [ 17 , 19 ] or have employed data sets in which the number of SNPs or known haplotypes equals or greatly exceeds the number of individuals sampled [ 13 , 15 ]. Neither of these situations is likely to be an accurate reflection of the sample sizes or numbers of SNPs that will be assayed with the high-throughput methods available today. To understand the relative performance of the various methods of haplotype inference, there is a need for comparisons that include both larger numbers of polymorphic sites and biologically more complex correlations among the sites. In this study the performance of several leading methods of haplotype inference are compared for a large data set (154 individuals, 15 SNPs) undergoing a combination of mutation, recombination, and gene conversion. The accuracy of computational haplotype inference improves as the magnitude of linkage disequilibrium (LD) among sites increases [ 17 ]. Gene conversion, operating in conjunction with normal recombination, can complicate the normal decay of linkage disequilibrium with distance in a genomic region and can be expected to complicate the computational inference of haplotype structure. This issue has particular relevance to the human growth hormone locus. The five genes of the human growth hormone locus reside within about 45 kb on chromosome 17 [ 20 ]. Pituitary growth hormone (GH1) is by far the most thoroughly studied of the genes and lies at the 5' end of the cluster. The remaining four genes, placental growth hormone (GH2) and three chorionic somatomammotropins (CS1, CS2, and pseudogene CS5 or CSHP1), are expressed only from the placenta. The promoter region of GH1 is unusually polymorphic, with 16 SNPs having been identified in a span of 535 bp [ 21 - 23 ]. Most of these SNPs occur at the comparatively small number of sites that exhibit sequence differences among the five genes of the GH locus, and this has been interpreted as evidence of gene conversion [ 21 , 23 , 24 ]. A survey of 25 SNPs in the entire promoter and coding region of GH1 (Adkins et al. in review) indicates that this bias towards polymorphism at sites of intergenic divergence is quite extreme and supports the hypothesis that gene conversion plays a role in the pattern of variation in the GH1 gene in addition to mutation and recombination. In 154 recruits to the British army, Horan et al. [ 23 ] used cloning and sequencing to empirically determine 36 haplotypes based on 15 of the promoter SNPs previously identified (one site identified by [ 21 ] was invariant). This study takes advantage of the exhaustive work of Horan et al. [ 23 ] to compare the relative accuracy of some of the major implementations of the EM and Bayesian approaches to haplotype inference. Results and Discussion Characteristics of the data set The 15 sites studied by Horan et al. [ 23 ] span 535 nucleotides in the promoter of GH1, with minor allele frequencies ranging from 0.3–41.2%. Six of the sites can be considered "rare" variants with minor allele frequencies below 5% (0.3–3.6%). Standardized linkage disequilibrium (D'; [ 25 ]) among the remaining nine sites ranges from complete linkage disequilibrium (sites -301 and -308; Table 1 ) to effective linkage equilibrium (i.e., sites -1 and +59). Fallin and Schork [ 18 ] identified several characteristics of an unphased set of genotypes that improve the accuracy of haplotype inference, most of which are exhibited by this data set and discussed below. Therefore, this data set probably represents one that is favourable to the accurate inference of haplotypes. Table 1 Linkage disequilibrium (D') among loci with minor allele frequencies ≥ 5% 1 Site Site -278 -75 -57 -31 -6 -1 +59 -308 1.000 0.653 0.892 0.741 0.458 0.192 0.646 -278 0.857 0.845 0.696 0.820 0.666 0.334 -75 1.000 0.358 0.708 0.561 0.172 -57 1.000 0.872 1.000 1.000 -31 0.410 1.000 0.538 -6 1.000 0.194 -1 0.002 1 Numbering relative to the start of transcription for GH1 Increasing sample size improves the accuracy of inferred haplotypes. In Horan's study [ 23 ] 308 chromosomes were surveyed to yield 36 haplotypes, a ratio of 8.6. Three haplotypes can be unambiguously inferred from the 27 fully homozygous individuals, and 11 subjects are heterozygous at only one site, from which an additional 11 haplotypes can be unambiguously inferred. This leaves 116 individuals (232 chromosomes) heterozygous at ≥ 2 sites upon which to attempt to infer the remaining 22 true haplotypes. The distribution of haplotype frequencies also influences the accuracy of haplotype inference in two ways. First, the presence of some haplotypes at comparatively high frequency increases the chances that those haplotypes can be unambiguously inferred from homozygotes, allowing the alternative haplotype to be inferred with high confidence in compound heterozygotes. Second, the presence of some haplotypes at near-zero frequency allows truly nonexistent haplotypes to be accurately estimated as having zero frequency. The empirical haplotype frequencies in this study exhibit considerable dispersion. Two haplotypes are relatively common (33% and 16%; Table 2 ). Thirty-one haplotypes have frequencies below 5%, and 19 have frequencies ≤ 1%. In multiple regression analysis, Fallin and Schork [ 18 ] found dispersion of haplotype frequencies to be the strongest predictor of the accuracy of haplotype inference. Table 2 Inferred frequencies of haplotypes. SNP Haplotype Frequency -476 -339 -308 -301 -278 -168 -75 -57 -31 -6 -1 3 16 25 59 Empirical Phase, no LD Phase, with LD Haplotyper PL-EM SNPHAP Empirical Haplotypes 1 G G G G G T A T G A A G A A T 0.334 0.312 0.321 0.325 0.333 0.326 2 G G G G T T A G G G A G A A T 0.162 0.166 0.162 0.166 0.181 0.171 3 G G T T G T A G G A A G A A T 0.091 0.097 0.097 0.101 0.098 0.102 4 G G T T G T A G - A A G A A T 0.052 0.055 0.055 0.049 0.047 0.050 5 G G G G T T G G G G A G A A T 0.042 0.052 0.052 0.052 0.049 0.050 6 G G T T G T A G - A A G A A G 0.029 0.032 0.032 0.032 0.030 0.030 7 G G G G T T A G G G T G A A T 0.026 0.032 0.032 0.032 0.028 0.029 8 G G T T G T A G G G A G A A T 0.019 0.016 0.016 0.013 0.016 0.018 9 G G G G T T A T G G A G A A T 0.019 0.013 0.013 0.013 0.011 0.011 10 G G T T G T A G - G A G A A T 0.019 0.023 0.026 0.023 0.025 0.025 11 G G G G T T G G G G A G G C T 0.016 0.016 0.016 0.016 0.014 0.014 12 G G G G T T A G G A A G A A T 0.016 0.010 0.006 0.006 0.008 0.008 13 G - G G T T G G G G A G A A T 0.016 0.016 0.016 0.013 0.010 0.013 14 G G G G T C A G G G T G A A T 0.016 0.016 0.016 0.016 0.016 0.016 15 G G T T G T A G G G T G A A T 0.013 0.010 0.010 0.010 0.006 0.009 16 G G G G T T G G G A A G A A T 0.013 0.013 0.013 0.016 0.008 0.008 17 G - G G T T A G G G A G A A T 0.013 0.013 0.013 0.013 0.011 0.011 18 G G G G T T A G - G A G A A T 0.010 - 0.006 0.010 0.007 0.008 19 A G G G T T A G G G A G A A T 0.010 0.013 0.013 0.010 0.005 0.010 20 G G G G G T A G - A A G A A T 0.010 - 0.003 0.010 0.006 0.005 21 G G G G T T G G G G A G A A G 0.010 0.010 0.010 0.010 0.011 0.011 22 G G T T G T A T G A A G A A T 0.010 0.013 0.010 0.013 0.007 0.007 23 G G G G G T A G G A A G A A T 0.006 0.016 0.013 0.006 0.006 0.008 24 G G T T G T G G - A A G A A T 0.006 - - - - - 25 G G T T G T A G G A A G A A G 0.003 - - - 0.004 0.004 26 G G G G T T G G G G T G A A T 0.003 0.006 0.006 0.006 0.007 0.007 27 G G G G T T A T G A A G A A T 0.003 0.003 0.003 - - - 28 G G G G T T A G - A A G A A T 0.003 - - - - - 29 A G G G T T A G G A A G A A T 0.003 - - - - - 30 G - G G T T A G G A A G A A T 0.003 0.003 0.003 0.003 0.003 0.003 31 G G G G T T G G - G A G A A T 0.003 0.010 - - - - 32 G G T T G T G G G G A G A A G 0.003 - - - 0.002 - 33 G G G G T T A G G G A G G C T 0.003 0.003 0.003 0.003 0.004 0.004 34 G - G G T C A G G G T G A A T 0.003 0.003 0.003 0.003 0.003 0.003 35 G G G G G T A G G A C C A A T 0.003 - - 0.003 0.003 0.003 36 G G G G T T A G G G T G A A G 0.003 - - - 0.003 0.003 Incorrect Haplotypes 1 G - G G T T G G G G A G G C T - - - 0.002 0.002 2 G G G G T T G G - A A G A A T - 0.006 - 0.009 0.008 3 G G G G T T G T - G A G A A T - - - - 0.002 4 G - G G T T G T G A A G A A T - - 0.003 - - 5 G - G G T T G T G G A G A A T - - - 0.003 0.002 6 G G G G T T G T G G A G A A T - 0.003 - - - 7 G G G G T T G T G A A G A A T - - - - 0.004 8 A G G G T T A T G A A G A A T - - 0.003 0.003 0.003 9 G G G G T T A G G G C C A A T 0.003 0.003 - - - 10 A G T T G T A G - A A G A A T - - - 0.002 - 11 A G T T G T A G G G T G A A T - - - 0.003 - 12 G G T T T T G G - G A G A A T - - 0.006 0.004 - 13 G G T T T T G G G A A G A A T - - - 0.003 - 14 G G G G G T A T - A A G A A T 0.010 - - - - 15 G G G G G T A T G G A G A A T 0.006 0.006 0.006 0.008 0.008 16 G G G G G T A T G A A G A A G 0.006 0.006 0.006 - - Minor Allele Frequency 0.013 0.036 0.247 0.247 0.399 0.019 0.114 0.367 0.133 0.412 0.065 0.003 0.019 0.019 0.049 Accuracy of haplotype inference The accuracy of computational inferences of haplotype frequencies and assignments to individuals were compared to empirical values for the full set of 15 SNPs in the promoter of GH1. Additionally, analyses were performed on a restricted set of eight SNPs with allele frequencies above 5% (and excluding site -301 which is in complete linkage disequilibrium with -308). The latter analyses were performed to better approximate the characteristics of data sets that are typically collected in genetic epidemiological studies. Although the presence of rare alleles and haplotypes improves the accuracy of haplotype inference, sites with a low frequency minor allele are often ignored due to their reduced usefulness in mapping disease loci and the assumption that such loci will contribute little to population-wide predisposition to disease. Very little difference was observed in the accuracy of haplotype inference between the two data sets. Assignment of haplotypes to individuals was very accurate by all methods (Table 3 ). Approximately 90% of individuals were assigned correct haplotypes. However, this number includes individuals whose haplotypes are unambiguous (heterozygotes at 0 or 1 site). Excluding those individuals, the error rate is closer to 13%. Table 3 Accuracy of computational inferences of haplotype structure of the GH1 gene promoter. 15 Promoter SNPs Error Rate Based on # of Heterozygous Sites (N) Error Rate Algorithm MSE I H # correct/# wrong I F Overall Ambiguous Individuals 2 (13) 3 (32) 4 (24) 5 (28) 6 (11) Phase v2, no LD 3.6 × 10 -5 0.81 27/4 0.91 0.11 0.15 0.08 0.09 0.25 0.11 0.27 Phase v2, with LD 2.2 × 10 -5 0.81 28/5 0.93 0.10 0.13 0 0.09 0.17 0.14 0.27 Haplotyper 1.0 2.0 × 10 -5 0.81 28/5 0.93 0.09 0.13 0 0.06 0.13 0.18 0.27 PL-EM 1.0 2.5 × 10 -5 0.82 31/9 0.92 0.11 0.15 0 0.09 0.13 0.21 0.36 SNPHAP 1.0 2.0 × 10 -5 0.82 30/7 0.93 0.09 0.13 0 0.09 0.13 0.14 0.27 8 SNPs with Minor Allele Frequency ≥ 5% Phase v2, no LD 4.8 × 10 -5 0.79 19/3 0.92 0.11 0.15 Phase v2, with LD 4.1 × 10 -5 0.80 20/4 0.92 0.11 0.15 Haplotyper 1.0 3.8 × 10 -5 0.81 19/2 0.93 0.10 0.14 PL-EM 1.0 2.3 × 10 -5 0.85 22/4 0.94 0.08 0.11 SNPHAP 1.0 3.3 × 10 -5 0.85 22/4 0.93 0.08 0.11 Estimation of haplotype frequencies was also highly accurate, and there was no meaningful difference in accuracy among the methods as measured by the similarity index, I F . As measured by the mean squared error (MSE) the implementation of the program Phase that ignored linkage disequilibrium among sites gave marginally lower accuracy for the full data set and for the data set composed of higher frequency alleles, but the magnitude of the MSE was small for all methods and spanned only about a two-fold difference between the best and worst value. PL-EM successfully identified the largest number of correct haplotypes, but this success rate was accompanied by the burden of the highest number of incorrect haplotypes inferred. Indeed, the aggregate frequency of incorrect haplotypes inferred by PL-EM was about 1% higher than for the other methods. This observation may have practical value for the analysis of unphased genotypic data. PL-EM may be slightly advantageous if the analytical goal of identify the largest number of correct haplotypes is much more important than minimization of the number of incorrect haplotypes inferred, which may be the case in studies of functional genetics. However, if minimization of the number of incorrect low-frequency haplotypes is more important, as will usually be the case in genetic epidemiological studies, PL-EM may not be the optimal method. Unfortunately, none of the methods is clearly superior in minimizing the number of incorrect haplotypes inferred. Importantly, none of the methods failed to identify haplotypes with frequencies above 1%. Conversely, no incorrect haplotype was assigned a frequency greater than 1%. Indeed, the aggregate frequency of incorrect haplotypes was ≤ 3.7% by all methods. These results are reassuring in two respects. First, it appears unlikely that any of the methods will fail to identify a haplotype that is a major contributor to disease risk within a study population. Second, it also is unlikely that an incorrect haplotype will be implicated as a significant disease risk. It has been noted previously [ 17 , 18 ] that computational methods tend to over-estimate slightly the frequency of the more common haplotypes. The four most common haplotypes in this data set have an aggregate frequency of 64%. The aggregate frequency inferred for these haplotypes ranged from 63% to 65.9% among the methods. The magnitude of error in the estimation of the frequency of the common haplotypes is very small and indicates that this should not be a significant source of error in studies of population genetics or genetic epidemiology if the present results can be generalized. Effect of number of heterozygous sites The number of possible haplotypes compatible with an individual's unphased genotype is 2 k , where k is the number of heterozygous sites. For this reason, the difficulty of correctly assigning haplotypes to subjects increases dramatically as those subjects become heterozygous at more sites. Therefore, the error rate for assigning haplotypes was evaluated based on the number of sites at which subjects were heterozygous. Up to 3 heterozygous sites, the error rate is below 10%. For 4 heterozygous sites the error rate is about 15% and exceeds 20% only when 6 sites are heterozygous. Phase was an odd exception to this pattern due to an unusually high error rate for four heterozygous sites, despite the lowest error rates for five and six heterozygous sites. On the assumption that an error rate not much larger than 10% is desirable for a genetic study, it appears that computationally assigned haplotypes for subjects heterozygous at more than four SNPs should be viewed with extreme caution. Similarly, there is a current effort to define haplotype blocks in the human genome to facilitate genome-wide scans for disease loci with a minimum number of sites that must be genotyped. If the results for this gene can be generalized, it would appear unwise to define haplotype blocks based on more than 4–5 SNPs. Conclusions All of the implementations of the EM and Bayesian methods of haplotype inference had high accuracy. Therefore, if this data set is representative of other SNP genotyping studies one can have high confidence in the assignment of haplotypes and estimation of haplotype frequencies produced by any one of the programs. Each method identified every haplotype with a frequency greater than 1%. Therefore, it is unlikely that any of the methods would fail to identify a haplotype contributing to disease risk in a significant proportion of a population. Conversely, no incorrect haplotype was assigned a frequency greater than 1%, indicating a low probability of an incorrect haplotype being identified as a significant disease risk factor. Assignment of haplotypes was very accurate for subjects heterozygous for up to three SNPs, and was at least 80% accurate for up to five heterozygous sites. This suggests that haplotype blocks should perhaps be defined based on no more than five sites and that this might be the practical limit at which one can have confidence in the assignment of haplotypes to subjects. Methods Genetic analyses The empirically determined set of haplotypes from Horan et al. [ 23 ] were kindly provided by Drs. David Cooper and David Millar. To examine the accuracy of computational haplotype inference, five different algorithms (Table 3 ) were used to infer haplotypes based on the 15 SNPs scored by Horan et al. (2003), and the accuracy of these haplotypes was compared to their empirical determinations. The program HAPLOTYPER [ 13 ] takes a Bayesian approach to haplotype inference and a partition-ligation strategy for improving speed and accuracy that divides the data into small segments of consecutive loci during haplotype inference that are later combined. We used the default settings of the htyperv2 program, except that 50 iterations of prediction were requested before the results were reported. Like HAPLOTYPER, Phase 2.0.2 [ 15 ] employs a Bayesian approach and partition-ligation. Phase was run both with and without the assumption of decay of linkage disequilibrium (option M) with distance in order to evaluate the effect of this assumption. Phase was run with the default options with these exceptions: five restarting points (-x option), the triallelic site -1 was treated as multiallelic but without the stepwise mutation model (-d option), ten steps through the Markov chain per iteration ("thinning intervals"), and the length of the final run with all loci increased by tenfold (option -X). According to Stephens and Donnelly (2003) HAPLOTYPER and Phase differ primarily in the prior distribution that is used. Phase uses an approximate coalescent that will give greater weight to haplotype resolutions of multilocus genotypes that are most similar to previously resolved haplotypes, while HAPLOTYPER uses a Dirichlet prior that chooses randomly among possible haplotype resolutions if the genotypes can not be made to correspond to previously inferred haplotypes. The program PL-EM [ 12 ] combines partition-ligation with the EM algorithm to infer haplotypes. PL-EM was run with these settings: haplotypes with probability of appearance >0.1 reported, 3–4 loci per partition, 154 partial haplotypes passed on in each ligation step, 50 independent runs in each implementation of the EM algorithm. The program SNPHAP [ 11 ] by David Clayton also employs the EM algorithm to infer haplotypes, but differs from many implementations by adding one locus at a time and removing from consideration low probability haplotypes after each addition until all loci are added. The default settings for SNPHAP were used. Another popular implementation of the EM algorithm, EM-DeCODER [ 13 ], is limited to 100 genotypes and could not be applied to the full set of 154 subjects of Horan et al. (2003). The full data set of Horan et al. [ 23 ] includes six sites with a minor allele frequency below 5%. Sites with allele frequencies this low are often ignored in genetic studies. Therefore, haplotypes were also inferred based upon a restricted set of sites that excluded six sites (-476, -339, -168, +3, +16, and +25) with minor allele frequencies below 5% and excluded site -301 which is in complete linkage disequilibium with site -308. Additionally, the single individual bearing a C allele at sites +1 and +3 was excluded due to the extremely low frequency of that allele. This left eight sites upon which to perform haplotype inference. Pairwise D' [ 25 ], the linkage disequilibium statistic D standardized by its maximum value, was calculated for loci with minor allele frequencies above 5% using the program Arlequin v2.000 [ 26 ] based on the empirical haplotypes provided by Drs. Cooper and Millar. Measures of accuracy of haplotype inference The accuracy of haplotype inference was examined by several metrics. The mean squared error (MSE) [ 18 ] is defined as where p ek and p tk are the inferred and empirically determined frequencies for the k th haplotype, and h is the number of haplotypes. I F and I H were proposed by Excoffier and Slatkin [ 10 ]. I F is another measure of how closely the inferred and empirical haplotype frequencies correspond and is given by where the variables are defined as above. I F ranges from 0 to a maximum value of 1 when the frequencies match perfectly. I H compares the number of haplotypes inferred to the number actually known to occur and ranges from 0 to 1 (complete correspondence between inferred and true). I H is defined as where m true is the number of haplotypes known to occur, m est is the number of inferred haplotypes with frequency ≥ 1/(2 n ), and m missed is the number of known haplotypes that were not inferred. The error rate [ 13 ] is the proportion of subjects whose inferred haplotypes are not completely accurate. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC512280.xml |
544950 | Thumb force deficit after lower median nerve block | Purpose The purpose of this study was to characterize thumb motor dysfunction resulting from simulated lower median nerve lesions at the wrist. Methods Bupivacaine hydrochloride was injected into the carpal tunnel of six healthy subjects to locally anesthetize the median nerve. Motor function was subsequently evaluated by measuring maximal force production in all directions within the transverse plane perpendicular to the longitudinal axis of the thumb. Force envelopes were constructed using these measured multidirectional forces. Results Blockage of the median nerve resulted in decreased force magnitudes and thus smaller force envelopes. The average force decrease around the force envelope was 27.9%. A maximum decrease of 42.4% occurred in a direction combining abduction and slight flexion, while a minimum decrease of 10.5% occurred in a direction combining adduction and slight flexion. Relative decreases in adduction, extension, abduction, and flexion were 17.3%, 21.2%, 41.2% and 33.5%, respectively. Areas enclosed by pre- and post-block force envelopes were 20628 ± 7747 N.N, and 10700 ± 4474 N.N, respectively, representing an average decrease of 48.1%. Relative decreases in the adduction, extension, abduction, and flexion quadrant areas were 31.5%, 42.3%, 60.9%, and 52.3%, respectively. Conclusion Lower median nerve lesion, simulated by a nerve block at the wrist, compromise normal motor function of the thumb. A median nerve block results in force deficits in all directions, with the most severe impairment in abduction and flexion. From our results, such a means of motor function assessment can potentially be applied to functionally evaluate peripheral neuropathies. | Introduction The thumb has unique anatomical and biomechanical characteristics that are required to perform many manipulative tasks. Thumb motor dysfunction resulting from neuromuscular and musculoskeletal pathologies severely hinders the performance of these daily tasks. Clinical treatment, prevention protocols, and rehabilitation efficacy requires a thorough understanding of thumb motor capabilities, as well as its associated functional deficit. Investigations of underlying pathological mechanism of the thumb help advance clinical treatments such as tendon transfers [ 1 ], functional electrical stimulation [ 2 ] and plasticity suppression [ 3 ]. Measurement of strength during maximum voluntary contraction is a simple and direct means of assessing neuromuscular function. Popular instruments used for quantitative assessment of thumb strength are pinch dynamometers. The pinch output, however, provides limited information about thumb motor function in that it offers a single generic force in one specific direction. Each muscle/tendon within the thumb has a distinct anatomical origin and insertion, suggesting its external force potential in a particular direction [ 4 - 6 ]. Hence, evaluation of strengths in multiple directions offers insight concerning the motor capacity of individual muscles. Force production of a digit has been measured in various directions such as flexion/extension [ 7 , 8 ], abduction/adduction [ 9 - 14 ], or in combined directions [ 15 , 16 ]. Bourbonnais et al. developed an apparatus to measure thumb force production in eight directions in the transverse plane of the thumb and investigated force dependence on the direction of effort [ 15 ]. Yokogawa and Hara measured index fingertip forces in various directions within the flexion/extension plane [ 8 ]. Recently, we developed experimental apparatuses to measure multi-directional forces of a digit in its transverse plane [ 17 - 19 ]. From these multi-directional forces we constructed force envelopes representative of the characteristic force output pattern of a digit [ 17 - 19 ]. Disorders resulting from traumatic injuries to and various diseases of these nerves are common in clinical practice. Clinical manifestations of hand dysfunction are distinctive depending on the nerve involved. For example, thenar atrophy is a major clinical observation affecting thumb function at the later stages of compression neuropathy of the median nerve. Several studies have been conducted to investigate the effects of simulated peripheral neuropathies using local anesthetization [ 5 , 16 , 20 , 21 ]. Kozin et al. [ 21 ] studied the effects of median and ulnar nerve blocks on grip and pinch strength and showed significant decreases following nerve blockage [ 21 ]. Boatright and Kiebzak [ 20 ] investigated the effects of median nerve block on thumb abduction strength. Kaufman et al. [ 5 ] measured isometric thumb forces in eight directions together with electromyographic signals of thumb muscles after block of the median nerve. Labosky and Waggy [ 22 ] studied the strength related to grip, pinch, thumb adduction, thumb abduction, and finger flexion after radial nerve block [ 22 ]. Kuxhaus studied the three dimensional feasible force set at the thumb-tip before and after ulnar nerve block and reported this to be a reproducible and sensitive means to detect impairment. The purpose of this study was to utilize our developed apparatus and protocols to investigate the effects of lower median nerve lesion on thumb motor function. The lesion was simulated by blocking the median nerve at the wrist using an anesthetic. We hypothesized that a median nerve block would cause (1) a decrease in force production, which would be direction-dependent with the most severe reduction in the abduction direction, and (2) a decrease in the force envelope area and force quadrant area, with the greatest decrease in the abduction quadrant. Methods Subjects Six healthy male subjects (mean age: 26.9 ± 5.1 years) participated in this study. The subjects had no previous history of neuromuscular or musculoskeletal disorders of the upper extremities. Each subject signed an informed consent form approved by the Institutional Review Board prior to participating in the experiment. Median nerve block Injections were performed under aseptic conditions while the subjects sat with the forearm supinated and the wrist slightly extended. After the skin at the palmer area of the wrist was cleaned with alcohol, 4 mL of 0.5% bupivacaine hydrochloride (Astra Pharmaceuticals, Westborough, MA, USA) was injected into the carpal tunnel with a sterile 25-gauge short-bevel needle. The needle was inserted through the transverse carpal ligament in line with the radial border of the fourth digit slightly ulnar to the palmaris longus tendon at the level of the distal wrist crease. Forty minutes was allowed for the median nerve block to reach complete effectiveness [ 23 ] and was verified using the Semmes-Weinstein monofilament test. The average monofilament score was 2.85 across the five digits before nerve block. About 40 minutes after nerve injection, little sensory impairment occurred in the ulnar distribution (score = 3.22), while the sensory score in the median distribution was greater than 6.15. The effects of nerve block lasted more than 6 hours with all subjects regaining normal hand function within 12 hours. Testing apparatus The experimental apparatus was designed and constructed to measure maximum voluntary contraction forces of any digit at any point along the digit. Force application was possible in any direction within the transverse plane of the longitudinal axis of the digit. The apparatus consisted of position control accessories, a force transducer, and a custom fitted aluminum ring attached to the transducer (Figure 1A,1B ). The transducer (Mini40, ATI Industrial Automation, NC, USA), capable of measuring 6 degrees of freedom forces and moments, was attached to a mounting clamp via an aluminum adapter plate while the aluminum ring was secured to the tool side of the transducer using a custom adapter. The ring served as a connection anchor for the transducer and the digit. The force transducer and ring attachment were positioned in a desired orientation using an aluminum slide rail, tubing, and lockable mounting clamps (80/20 Inc., Columbia City, IN, USA). The slide rail was secured to an aluminum base plate. Foam padded wooden blocks with two locking straps secured the arm to the base plate. Figure 1 Schematic of experimental setup to measure thumb force production in the transverse plane. (A) 3D view. (B) Side view with hand and thumb in place. Thumb extension and flexion occur in parallel with the palm, and abduction and adduction occur in a plane perpendicular to the palm with abduction moves away from the palm. (C) Visual guide for circumferential force production. The analog outputs from the transducer were digitized using a 16-bit analog-to-digital converter (PCI-6031, National Instruments, TX, USA). The X (abduction/adduction) and Y (flexion/extension) force components in the transverse plane were displayed on the screen while the subject performed a force production task. The resolutions of the force transducer in its axial (flexion/extension) and horizontal (abduction/adduction) directions were 0.16 N and 0.08 N, respectively. A personal computer equipped with LabVIEW (National Instrument, TX, USA) was used for force data acquisition, display, and processing. Experimental procedures Each subject was tested before and after median nerve block. The nerve block procedures were performed immediately after the completion of the first testing session. Post-block testing started after the verification of complete median nerve block, approximately 40 minutes after the injection. During each test, the subject was seated in a chair adjacent to the testing station modified with a wooden board to align their back vertically throughout the trials. The subjects rested their forearm on padded wooden blocks positioning their shoulder in approximately 60° of frontal plane abduction. Nylon straps fitted with plastic snap locking mechanisms secured the forearm and minimized the intervention of the elbow and shoulder during thumb force application. Subjects grasped a vertical dowel secured to the distal end of the wooden blocks in a midprone position. Formable thermoplastic braces were used to fix the elbow in 90° of flexion, and the wrist in 20° of extension and 0° of ulnar deviation. A metallic brace was used to fix the interphalangeal joint of the thumb in full extension. The aluminum ring was placed around the middle of the proximal phalanx and oriented to accommodate comfortable thumb position with the metacarpophalangeal joint flexed approximately 15°. Prior to testing, a line was drawn on the proximal phalange at the midpoint between the interphalangeal and metacarpophalangeal joints. The alignment of the ring with the circumferential line standardized the location of force application within and between subjects. As force application was at the middle of the proximal phalanx, mechanical action pertains to both the metacarpophalangeal and carpometacarpal joints. We chose the terminology of flexion/extension and adduction/adduction based on the mechanical action with respect to the metacarpophalangeal joint. With the thumb in the ring (Figure 1B ), extension and flexion occurred in parallel with the palm, and abduction and adduction occurred in a plane perpendicular to the palm. Each subject performed 15 circumferential MVC trials with randomized starting directions (Figure 1C ). The subject was allotted 15 seconds to complete each circumferential trial, and was instructed to use the entire time allotted to traverse the perimeter of the ring once. A dot generated on the computer screen was programmed to traverse a circle within 15 seconds to provide the subject with directional feedback of their force application. Subjects were given 60 seconds of rest between each circumferential trial. Each subject was familiarized with the task with a few practice trials. Data were collected from each subject at 100 samples per second producing a total of 22,500 pairs of force components from the 15 circumferential trials. Our previous study [ 19 ] indicated that the testing protocol did not cause noticeable fatigue. Force envelope and quadrants Data from multiple circumferential trials were accumulated to construct a force envelope. The procedures to generate a force envelope were as follows: Cartesian force coordinates ( X i , Y i ) were transformed into polar coordinates ( R α , α), where R α was the force magnitude at an angular position α. Each α was rounded to the nearest integer ranging from 0 to 359 degrees. The maximum, F α , was determined from a string of N data points along each radial line defined by α. At the completion of the 15 trials, there were, on average, N = 63 data points on each radial line of α based on the distribution off the 22,500 data points around 360°. A moving average with an interval of 10° was applied to the maximal series data F α (α = 0, 1, 2,..., 359) to obtain filtered maximal forces. These forces formed a force envelope . The area formed by a force envelope was divided into adduction-extension, extension-abduction, abduction-flexion, and flexion-adduction quadrants by radial lines oriented at 0°, 90°, 180°, and 270° A quadrant force was represented using the mean magnitude of the forces in that quadrant. The areas of the entire envelope and each quadrant were calculated by summing the areas of individual arc sections formed by the polar coordinates of the force envelope. (Figure 2 ). Figure 2 Division of force envelope into extension, abduction, flexion, and adduction quadrants. Statistical Analyses One- and two-factor repeated measures analyses of variance (ANOVA) were used to analyze outcome measures. The independent variables were testing SESSION (n = 2, i.e., pre- and post-block), force DIRECTION (n = 16), and force QUADRANT (n = 4), with SESSION as a repeated variable. Dependent variables were directional force, individual quadrant area and force envelope area. Statistical analyses were performed using SPSS 11 (SPSS Inc., Illinois) with statistical significance set at α = 0.05. Results Force envelope and directional forces Figure 3 shows the force envelopes produced by each subject (A to F) before and after median nerve block. The post-block force envelope was inside the pre-block envelope for each subject, indicating a decrease in force magnitude in all directions after nerve block. Figure 4 shows the average pre- and post-block force envelope across all subjects. Force magnitudes were significantly reduced after nerve block (p < 0.001) resulting in significantly smaller force envelopes. The average decrease across all directions was 27.9%. A maximum decrease of 42.4% occurred at 199°, corresponding to a combined direction of abduction and slight flexion, while a minimum decrease of 10.5% occurred at 328° corresponding to a combined direction of adduction and slight flexion. Relative decreases at 0° (adduction), 90° (extension), 180° (abduction), and 270° (flexion) directions were 17.3%, 21.2%, 41.2% and 33.5%, respectively. Figure 3 Force envelopes before and after median nerve block of subjects A, B, C, D, E, and F. For each subject, the inner envelope represents post-block results. Figure 4 Average force envelopes produced by the thumb before and after median nerve block. A single force in each quadrant was represented using the mean magnitude of the forces in that quadrant (see description in the Methods). The average quadrant forces were significantly decreased after nerve block (p < 0.001; Figure 5 ). The amount of decrease was also different between quadrants (p < 0.005). Relative decreases in mean quadrant forces were 24.5%, 38.7%, 32.1%, and 18.1% for extension, abduction, flexion, and adduction, respectively. The maximal decreases in mean quadrant force, 38.7%, occurred in the abduction quadrant. Figure 5 Average force magnitude, N, in individual quadrants. The percentage values denote the percent decreases of post-block forces relative to pre-block forces. Force envelope areas and quadrant areas Areas enclosed by the post-block envelopes were significantly smaller than the pre-block envelopes (p < 0.001; Figure 4 ). Post-block force envelope area, 10700 ± 4474 N.N, was 51.9% of pre-block force envelope area, 20628 ± 7747 N.N. Quadrant area decreased significantly (p < 0.001; Figure 6 ). The maximal percentage decrease in area after nerve block was 60.9% in the abduction quadrant, followed by a 52.3% area decrease in the flexion quadrant. Figure 6 Area (N-N) of individual force quadrants, and percentage decrease after nerve block. The percentage values denote the percent decrease of post-block quadrant areas. Discussion In this study we simulated a lower median nerve lesion and evaluated the resultant thumb motor function deficit. Our internal control via pre- and post-block design offered a particular advantage of investigating the mechanical role of muscles innervated by a targeted nerve. The testing and analytical methods employed have provided advanced quantification of thumb motor function. The results have confirmed our initial hypotheses that greatest force decreases occurred in directions related to abduction, and that the post-block thumb force envelope area was smaller than the pre-block force envelope area. Preferential force attenuation in the quadrants of abduction and flexion after median nerve block are in agreement with anatomical and neuromuscular features of the thumb. The median nerve innervates the abductor pollicis brevis, the opponens pollicis and superficial head of the flexor pollicis brevis, all of which contribute to the abduction and flexion of the thumb [ 4 ]; therefore, denervation of these muscles after median nerve block would cause the greatest force deficit related to median nerve function [ 5 ]. Additionally, as force application moved towards adduction, the force deficit decreased as neuromuscular control shifted from the median nerve to the ulnar nerve via the first dorsal interosseous and adductor pollicis brevis. Force deficit in extension was also comparably small as extension forces are mainly produced by the extensors pollicis brevis and longus originating in the forearm. Our reported force decreases following a median nerve block (40.9% in abduction, 34.1% in flexion) were smaller than those reported in the literature. Kozin et al. [ 21 ] reported a 60% decrease in pinch strength after a median nerve block using mepivicaine hydrochloride [ 21 ]. Boatright and Kiebzak [ 20 ] reported an approximate 70% decrease in thumb abduction strength after median nerve block using Lidocaine [ 20 ]. Kaufman et al. [ 5 ] stated that a median nerve block with Lidocaine almost completely diminished force production in the abduction direction [ 5 ]. The discrepancy may be due to the anesthetic used and strength testing method. Although the sensory block appeared to be complete for each method, the motor capabilities of the muscles associated with the median nerve might or might not be completely eliminated. Such a result is largely dependent on a particular anesthetic, its concentration and dosage, as well as the efficacy of the injection technique at immersing the nerve. The methods of strength testing may also help explain the different magnitudes of strength deficit after the nerve block. All previous results were based on forces obtained in discrete direction(s), and focused exertions, while the current study utilized a method of force production in a continuous, circumferential and dynamic manner. Furthermore, thumb motor performance can be maintained despite the absence of certain individual muscles. For example, Britto and Elliot reported that the loss of abductor pollicis longus and extensor pollicis brevis in their two patients did not show functional compromise of strength and grip strength [ 24 ]. In a broader sense, the neuromuscular system has remarkable capabilities to accomplish the same motor function goal using different effectors and different goals using the same effectors, a phenomenon so called "motor equivalence" [ 25 ]. An unexpected finding from this study was that the force deficit occurred in all directions (Figure 4 ). In other words, the median nerve block caused reduced force production by those muscles not associated with the median nerve. Several potential explanations exist to describe such a phenomenon. First, the injection into the carpal tunnel at the wrist, although localized, potentially diffused into the intrinsic fascia of the hand partially compromising function of the ulnar nerve, which innervates the adductor pollicis. Although Semmes-Weinstein monofilament testing confirmed the continued sensation of the digits within the ulnar nerve distribution, it is not inconceivable that the injection could have contaminated the ulnar innervated muscles, the first dorsal interosseous and deep head of the flexor pollicis brevis [ 20 ]. Secondly, thumb force in any direction is produced by synergistic activation of the many intrinsic muscles, and as a result, the muscular deficiency associated with one direction may hinder the force production in other directions by other muscles [ 5 , 22 ]. For example, Kaufman et al. demonstrated that thumb muscles not innervated by the median nerve displayed lower electromyographical activation and shifted the direction of maximum activation after a median nerve block [ 5 ]. Labosky and Waggy showed that a radial nerve block caused a 53% decrease in thumb abduction strength because of the lack of stabilization of the radial innervated extensor muscles [ 22 ]. Consequently, deficiency of median innervated muscles inherently limits force production in other directions as neuromuscular switching is necessary to produce force in changing directions. The median innervated muscles are the dominant abductors of the thumb metacarpophalangeal and carpometacarpal joint. The more than 50% residual abduction force found in this study suggests that the injection did not totally block the motor function of these muscles, even though a complete sensory loss was verified. This concurs with clinical observations of median compression neuropathy. Individuals with carpal tunnel syndrome complain of sensory dysfunction early in the disease process (at the beginning), while motor signs of thenar wasting and thumb weakness occur as the disease advances. The concept that the motor deficit is more resistant to peripheral median neuropathy than sensory loss has been well documented [ 23 , 26 , 27 ]. Butterworth et al. studied the temporal effects on sensory and motor blockade after injection of bupivacaine or mepivacaine, and found that sensory loss was complete but about a 20% compound motor action potential remained after 40 minutes [ 23 ]. In conclusion, we have incorporated a method for assessing thumb motor deficit based on strength measurement with a standard local anesthetic to investigate the effects of a simulated median neuropathy on thumb motor function. Median nerve block results in force deficits in all directions, with the most severe impairment in abduction and flexion. Future endeavors using this methodology can potentially further elucidate underlying pathomechanisms of peripheral neuropathies in all digits of the hand. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544950.xml |
515302 | Cluster randomised trials in the medical literature: two bibliometric surveys | Background Several reviews of published cluster randomised trials have reported that about half did not take clustering into account in the analysis, which was thus incorrect and potentially misleading. In this paper I ask whether cluster randomised trials are increasing in both number and quality of reporting. Methods Computer search for papers on cluster randomised trials since 1980, hand search of trial reports published in selected volumes of the British Medical Journal over 20 years. Results There has been a large increase in the numbers of methodological papers and of trial reports using the term 'cluster random' in recent years, with about equal numbers of each type of paper. The British Medical Journal contained more such reports than any other journal. In this journal there was a corresponding increase over time in the number of trials where subjects were randomised in clusters. In 2003 all reports showed awareness of the need to allow for clustering in the analysis. In 1993 and before clustering was ignored in most such trials. Conclusion Cluster trials are becoming more frequent and reporting is of higher quality. Perhaps statistician pressure works. | Background Cluster randomised trials are those where research subjects are not allocated to treatments independently, but as a group. For example, in a study of counselling patients on physical activity in general practice, practices were allocated to counselling or control and patients aged 40–79 years who attended during a five day period and who did not take regular exercise were invited to take part. Patients in the same practice received the same treatment, counselling or usual care, depending on how the practice was allocated. [ 1 ] The group of patients within the general practice formed a cluster. Members of a cluster will be more like one another than they are like members of other clusters and we need to take this into account in the analysis, and preferably the design, of the study. Methods which ignore clustering may mislead, because they assume that all subjects provide independent observations. Applying simple statistical methods to such data, without taking the clustering into account, can lead to confidence intervals which are too narrow and P values which are too small. There has been an increasing interest in cluster randomised trials over the past 20 years. For example, by the end of 2003 the British Medical Journal Statistics Notes on this topic [ 2 - 7 ] had been cited 121 times. There have been several reviews of published cluster randomised trials [ 8 - 13 ] (Table 1 ). All but Puffer et al. [ 10 ] reported that very few trials had sample size calculations which included clustering and about half took clustering into account in the analysis, fewer in the African studies reported by Isaakidis and Ioannidis. [ 11 ] Puffer et al. [ 10 ] did not mention whether trials failed to take clustering into account in the analysis. My own review of their trials as listed on the British Medical Journal website found that only 3 out of 36 ignored clustering. The review of the American Journal of Public Health and Preventive Medicine in 1998 – 2002 [ 13 ] is especially interesting because it attempted to replicate an earlier study [ 9 ] in the same journals. There was an increase in the number of reports of cluster randomised trials: 12.3 studies were reported per year in 1998 – 2002 compared to 5.3 studies per year in 1990 – 1993. [ 9 ] The quality of the analysis may have improved, but such assessments are subjective and very difficult to compare between reviews. Table 1 Some reviews of published cluster randomised trials Authors Source of trials Years Clustering allowed for in sample size Clustering allowed for in analysis Donner et al. [8] 16 non-therapeutic intervention trials 1979 – 1989 <20% <50% Simpson et al. [9] 21 trials from American Journal of Public Health and Preventive Medicine 1990 – 1993 19% 57% Isaakidis and Ioannidis [11] 51 trials in Sub-Saharan Africa 1973 – 2001 (half post 1995) 20% 37% Puffer et al. [10] 36 trials in British Medical Journal , Lancet , and New England Journal of Medicine 1997 – 2002 56% 92% a Eldridge et al. [12] 152 trials in primary health care 1997 – 2000 9% 59% Varnell et al. [13] 60 trials in American Journal of Public Health and Preventive Medicine 1998 – 2002 20% 54% (all analyses) + 25% (some analyses only) a My review of trials identified by Puffer et al. [10] It is understandable that papers do not report sample size calculations, as often these are omitted from papers entirely, sometimes by the request of the journal to save space. It can be argued (though I would not do so) that once we have carried out a study, the sample size calculations are not particularly informative. Analysis which ignores the clustering, however, can be highly misleading, finding significant differences where there are none. We may have incorrect conclusions in the literature, which are then uncritically repeated and become false knowledge. We should not be surprised that clustering is ignored. In the past, few textbooks have cautioned against this and the assumption of independence of observations is seldom stressed. Many statisticians will admit to having incorrectly ignored clustering in the analysis of clustered designs, including myself when I was younger and more ignorant than today. However, it can be very important. In this paper I attempt to chart the changes in both the number of cluster randomised trials reported and the proportion of these reports where clustering has been taken into account in the analysis. Methods I first carried out a search on the ISI Web of Science, looking for papers on cluster randomisation and reports of trials. I classified these by type (trial report or methodological article), year of publication, and journal. To identify cluster randomised trials we have to read the papers. We cannot tell whether a trial is cluster randomised from title, keywords, or abstract. Many authors are not aware of the importance of clustering and do not mention it. In this paper I report the results of a hand search of the British Medical Journal . I identified and scanned all papers reporting trials for the years 1983, 1988, 1993, 1998, and 2003, recording any where subjects were allocated in clusters. I excluded any studies where subjects were not allocated to groups by the investigator, for example several comparisons of fund-holding and non-fund-holding general practices. For each trial identified, I noted whether clustering had been taken into account in the analysis. There are several approaches which can be used to allow for clustering. The easiest is to calculate a summary statistic for each cluster. [ 4 ] This is usually a mean for a continuous outcome or a proportion for a dichotomous outcome. We can also use robust variance estimates, general estimating equation models (GEEs), multilevel modelling, Bayesian hierarchical models, and several other techniques. Any method which takes into account the clustering should be an improvement compared to methods which do not. I also noted whether ignoring the possible effects of clustering might have an important effect on the conclusions. Clustering may result in P values and confidence intervals which are sufficiently biased to have a major effect if any of the following are true: the cluster size is large, the number of clusters is small, or the intra-cluster correlation coefficient is large. Whether any of these applies in a trial which ignores clustering is a matter of judgement. Results A computer search for cluster randomised trials Figure 1 shows the result of a search on the ISI Web of Science, looking for papers on cluster randomisation and reports of trials. I found that other terms, such as 'group randomised' did not work, as I got hundreds of abstracts with 'patients were in two groups, randomised to active or control treatments'. Figure 1 Results of a Web of Science search. Results of a Web of Science search on: randomi* in clusters OR cluster randomi*, up to the end of 2003. There are many potential biases. In the first part of the period, the Web of Science database did not include abstracts, so there was less opportunity to pick up the search terms. More recently, several journals began to include a description of the trial design in the title of the paper, for example 'Effect on hip fractures of increased use of hip protectors in nursing homes: cluster randomised controlled trial'. [ 14 ] This will increase the detection rate. These design descriptions are not always correct, nor does the cluster randomised nature of the trial necessarily appear in the description. Also, many authors will not be aware of the importance of clustering and will not mention it. These factors will reduce detection. Hence this is not a thorough search and will have missed many studies, but it might give an idea of the increase in activity. I divided the papers into those which were methodological, either educating researchers into the appropriate design and analysis of cluster randomised trials or developing new methods of analysing such trials, and those reporting actual trials. The data for 2000 and 2001 includes special issues of Statistics in Medicine and Statistical Methods in Medical Research on cluster randomisation, so there were a larger number of methodological papers than might be expected in those years. The numbers of papers found in the two categories were similar in each year before 2001: as many papers were about how to do such trials as were reports of actual trials. It is hard to believe that there are so few such trials being reported and it is likely that many have been reported without any acknowledgement of the importance of clustering. All the papers up to 1990 are due to Donner and his colleagues. [ 8 , 15 , 16 ] However, it was impossible to identify papers which used older terminology. A paper by Cornfield [ 17 ] 'Randomisation by group: a formal analysis' includes the following statement 'Randomization by cluster accompanied by an analysis appropriate to randomization by individual is an exercise in self-deception, however, and should be discouraged.' This would not be found by the search. The book on cluster randomization by Murray [ 18 ] is called The Design and Analysis of Group-Randomized Trials . The British Medical Journal was the journal most frequently represented in the survey, no fewer than 43 of the 332 publications found, 13%, appearing there. The next was Statistics in Medicine with 39 publications (12%), all methodological, then the British Journal of General Practice with 17 (5%), Controlled Clinical Trials with 16 (5%), and Family Practice with 10 (3%). Figure 1 shows that papers in the British Medical Journal reflect the literature as a whole. The first paper in the BMJ was a report of a trial, [ 19 ] which was followed four years later by a series of short educational articles. [ 3 , 4 , 6 , 7 ] When I first did the search reported in Figure 1 , I was surprised by how few trials were reported. My subjective impression was that there were many more cluster randomised trials than I had found. I therefore decided to carry out a small survey of journals to find out whether the dramatic increase shown in Figure 1 was real. As the British Medical Journal had most reports and had been published for many years, this was the obvious journal with which to begin. A survey of papers in the British Medical Journal The results of the search are shown in Table 2 . As Table 2 shows only reports of trials, it does not include all the BMJ papers in Figure 1 , which also includes methodological papers. A list of all papers reviewed is given in the additional file: papers in the survey. Only one of the trials in survey [ 1 ] cited any of the BMJ Statistics Notes on clustering. [ 2 - 7 ] Table 2 Result of a hand search for cluster randomised trials in the British Medical Journal Year Vol Trials Clustering ignored Ignoring clustering judged as important Found in Web of Science search 2003 326-7 9 0 0 5 1998 316-7 4 1(?) 1 0 1993 306-7 4 3 2 0 1988 296-7 0 0 0 0 1983 286-7 1 1 1 0 ? doubtful whether clustering taken into account The noted query relates to a paper in which the authors stated that 'Univariate comparisons were calculated by t test and χ 2 analysis. The role of potential covariates was explored using linear regression specified as a two level model (practice and individual) using the software package MLn'. [ 20 ] I could find no multilevel modelling in this paper, but a lot of t and χ 2 tests. This was a trial of community based management in failure to thrive by babies. Thirty eight primary care teams were randomly allocated to intervention or control and all children identified in the practice were offered the same intervention, so clearly clustering should be taken into account. The trials which I regarded as failing to take the clustering into account were as follows. Russell et al. [ 21 ] investigated the effect of nicotine chewing gum as an adjunct to general-practitioners advice against smoking. Subjects were 'assigned by week of attendance (in a balanced design) to one of three groups (a) non-intervention controls (b) advice and booklet (c) advice and booklet plus the offer of nicotine gum.' There were 6 practices, with recruitment over 3 weeks, one week to each regime. The study was analysed by chi-squared tests. As the clusters were large, with 1938 subjects in 18 clusters, clustering should have been taken into account. Rink et al. [ 22 ] investigated the impact of introducing near patient testing for standard investigations in general practice. Twelve practices were used, and some given the equipment and some not in a cross-over design. Analysis used paired t tests, unpaired t tests, odds ratios, ratios of proportions with confidence intervals, and chi squared tests, none of which took clustering into account. In a trial of clinical guidelines to improve general-practice management and referral of infertile couples, Emslie et al. [ 23 ] randomised 82 general practices in Grampian region and studied 100 couples in each group. However, the main outcome measure was whether the general practitioner had taken a full sexual history and examined and investigated both partners appropriately. The cluster size may be small but the cluster effect may be large. The GP should be the unit of analysis here as opposed to the couple, as done in the paper. The trial where I judged ignoring clustering to be unimportant had many very small clusters. Wetsteyn and Degeus [ 24 ] compared 3 regimens for malaria prophylaxis in travellers to Africa. Members of one family were allocated to one regimen and the results analysed using a chi-squared test. Only five of the 18 trials had been found in the Web of Science search, showing that that was indeed an underestimate. However, the growth in numbers of trials is indicated by both electronic and hand searches. Discussion A bibliometric survey has suggested a rapid increase in the number of cluster randomised trials, many of which appeared in the British Medical Journal . A hand search of the British Medical Journal has confirmed this increase, at least in this journal. Although the effects of clustering have often been ignored in trials, producing potentially misleading conclusions, the situation has certainly improved in the British Medical Journal . This has followed many articles on the topic in the Journal. Perhaps statistician pressure works. Identification of cluster allocation is subjective. I included one year, 1998, also searched by Puffer et al. [ 10 ] and identified four trials where Puffer et al. [ 10 ] identified only one. My assessments of whether clustering has been taken into account and whether ignoring it might be important are also subjective. Nevertheless, I think that the general conclusion of increasing activity and better reporting of trials, at least in the British Medical Journal , is valid. Whether we would find a similar improvement in other journals is less certain. It is likely that reporting of cluster randomised trials in the British Medical Journal is especially good, as the journal reports many such trials, has carried many articles on their correct analysis and reporting, has a fairly rigorous statistical refereeing system, [ 25 - 27 ] and is generally of a relatively high methodological standard. The BMJ 's current statistical checklist [ 28 ] does not mention clusters, however. It would be possible to extend the survey to other journals where such trials are frequently reported, but these, too, might be more likely to adhere to sound principles of analysis and reporting than would journals where few such studies appear. The thought of hand-searching journals where no trials might be found does not appeal. There are still many other aspects of trial reporting where improvement is possible [ 10 , 12 ] but the picture drawn by this survey is encouraging. Methodologists need to keep up the pressure and to extend it to specialist journals. The recently published extension of the CONSORT statement to cluster randomised trials is to be welcomed. [ 29 ] We should also pursue other types of study where the unit of analysis is doubtful, such as those involving observations of multiple body parts in the same patient or multiple measurements on the same tissue treated as independent. Conclusions Cluster trials have become much more frequent since the mid 1990s. Reporting of these trials has improved and in the journal which publishes more than any other the quality had improved greatly. This improvement has followed a large number of articles advocating methods of analysis which take clustering into account, Perhaps statistician pressure works. Competing interests The author has been published frequently in the British Medical Journal , including articles written for payment. Authors' contributions J. M. Bland is the sole contributor. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Papers in the survey List of papers in the survey of the BMJ, Word file. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC515302.xml |
538290 | Ectopic paraesophageal mediastinal parathyroid adenoma, a rare cause of acute pancreatitis | Background The manifestation of primary hyperparathyroidism with acute pancreatitis is a rare event. Ectopic paraesophageal parathyroid adenomas account for about 5%–10% of primary hyperparathyroidism and surgical resection results in cure of the disease. Case presentation A 71-year-old woman was presented with acute pancreatitis and hypercalcaemia. During the investigation of hypercalcemia, a paraesophageal ectopic parathyroid mass was detected by computerized tomography (CT) scan and 99m Tc sestamibi scintigraphy. The tumor was resected via a cervical collar incision and calcium and parathormone tumor levels returned to normal within 48 hours. Conclusions Acute pancreatitis associated with hypercalcaemia should pose the suspicion of primary hyperparathyroidism. Accurate preoperative localization of an ectopic parathyroid adenoma, by using the combination of 99m Tc sestamibi scintigraphy and CT scan of the neck and chest allows successful surgical treatment. | Background Acute pancreatitis occurring secondary to hypercalcemia is rare. Most of the time adenomas are located in the neck. However, in 10–20% cases the parathyroid adenomas are found to be located within the mediastinum [ 1 , 2 ]. The lower parathyroid glands develop from the third pharyngeal pouch in close association with the thymus and they may migrate along with the thymus during development. As a result they may be found commonly within the anterosuperior mediastinum. On the other hand, the superior parathyroid glands are not associated with the thymus and may even be located in the posterior mediastinum [ 1 - 3 ]. Paraesophageal or retroesophageal parathyroid tumors arise from superior parathyroid glands, have normal blood supply from a branch of the inferior thyroid artery and are not embryologically considered ectopic [ 1 - 3 ]. We present a case of paraesophageal parathyroid adenoma clinically presenting as acute pancreatitis and successfully managed surgically by the collaboration of thoracic and general surgeons, via a cervical incision. Case presentation A 71-year-old female was admitted with epigastric pain and vomiting lasting for more than 12 hours. She had a history of arterial hypertension and cholecystectomy two years previously. On examination she had tenderness of the upper abdomen. Blood tests showed leucocytosis (14,500 / mm 3 ), increased serum levels of amylase (1,100 IU/L), LDH (550 IU/L) and calcium (14.8 mg/dl). On ultrasonography of the upper abdomen a non homogeneous appearance of the head of the pancreas was noted with a common bile duct diameter of 8.5 mm. CT scan of the abdomen confirmed the diagnosis of acute exudative pancreatitis. Acute pancreatitis subsided within 72 hours after conservative treatment. Further laboratory investigation of the hypercalcaemia revealed increased 24-hours urine calcium (465 mg), decreased serum phosphorus levels at 1.3 mg/dl, increased serum parathyroid hormone levels (771 pg/ml), normal levels of serum free T3 (FT3), free T4 (FT4), thyroid stimulating hormone (TSH), calcitonine, carcino embryonic antigen (CEA), carcinoma antigen (CA) 15-9, CA 125, alpha feto protein (AFP). Ultrasonography of the thyroid gland and the neck showed a suspicious prevertebral mass. CT scan of the thorax and neck detected a paraesophageal mediastinal mass close to the thoracic inlet. (Figure 1 ) 99m Tc sestamibi scintigraphy confirmed the diagnosis of parathyroid adenoma. (Figure 2 ). Figure 1 CT scan showing a paraesophageal, retrotracheal mass, close to the thoracic inlet Figure 2 Imaging of the parathyroid paraesophageal adenoma by Tc-99m scintigraphy After the complete subsidence of acute pancreatitis and the return of calcium serum levels at values less than 12 g/dl by hydration, the patient underwent endoscopic retrograde cholangiopancreaticography (ERCP) which failed to show bile duct lithiasis. With a diagnosis of parathyroid adenoma, resection of the parathyroid adenoma via a collar cervical incision was carried out. The tumor was easily separated from the surrounded structures (vertebra, trachea, and esophagus) by blunt dissection and the feeding vessels were found and ligated anteriorly. (Figure 3 ) The patient had a 6 days uneventful hospital stay. Calcium and parathyroid hormone serum levels returned to normal within 48 hours from the end of operation. A slight serum hypocalcaemia was observed over the following days and the patient received oral therapy with calcium and vitamin D to restore serum calcium levels within normal range values. Figure 3 The parathyroid adenoma after resection, measuring 40 mm in its maximal dimension. The silk suture ligating the feeding vessels is shown. Discussion Recurrent episodes of acute pancreatitis secondary to hypercalcemia are an uncommon presentation of primary hyperparathyroidism [ 4 - 7 ]. Acute pancreatitis is reported to be associated with primary hyperparathyroidism in 1% – 8% of cases in some large published series [ 4 - 7 ]. Sporadically reported cases of acute pancreatitis induced by primary hyperparathyroidism, in both the recent and past medical literature, suggest that the relationship between the two clinical conditions is not incidental [ 8 - 15 ]. Carnaille et al found significantly elevated serum calcium levels to be of major importance in the development of pancreatitis in patients with primary hyperparathyroidism [ 7 ]. Increased levels of serum calcium at the first episode of acute pancreatitis should pose the suspicion of primary hyperparathyroidism. In patients with a history of cholecystectomy (as in the presented case), where the main cause of an episode of acute pancreatitis is bile duct lithiasis, the diagnosis could be missed if serum calcium levels ranged within normal values. The main causes of primary hyperparathyroidism are single or double parathyroid adenoma (80%), hyperplasia of all four or more existing parathyroid glands (15–20%) and rarely cancer of the parathyroid gland (2%) [ 1 , 2 , 16 ]. Richards et al reported 5%–10% of the parathyroid glands to be located in the posterior mediastinum, 20% are found substernally within the thymic tissue in the anterior mediastinum (1–2%) while 1% of the glands are located in the carotid sheath and 5% into the thyroid gland. [ 2 ] Other rare sites of ectopic parathyroid tissue are the vagus nerve sheath, the thyrothymic ligament and the pericardium [ 3 ]. By reviewing 112 patients who underwent re-operation for primary hyperparathyroidism, Wang found 39% of missing adenomas to be located in the retrotracheal space [ 17 ]. Parathyroid glands, are now found with increasing frequency in the visceral compartment of the mediastinum (aortopulmonary window and right pulmonary artery, close to the tracheal bifurcation), because of the improvement of the imaging techniques ( 99m Tc sestamibi scintigraphy). The frequency of this occurrence at the moment is uncertain [ 2 ]. Many investigators advocate the need for the concordance of at least two diagnostic modalities before surgical excision. The combination of 99m Tc sestamibi scintigraphy and CT scan of the chest and neck gives important information to proceed with surgery and to minimize the risk of re-operation for recurrent hyperparathyroidism in the future [ 3 , 16 , 18 , 19 ]. The combination of both techniques had 100% sensitivity and 97.4% positive predictive value for the detection of the cause of primary hyperparathyroidism [ 18 ]. The spectrum of diseases demonstrated with 99m Tc scintigraphy includes eutopic parathyroid disease, ectopic parathyroid disease, solitary, double or multiple parathyroid adenoma, cystic adenoma, lipoadenoma, multiple endocrine neoplasia, entities with atypical washout and non-parathyroid entities that take up 99m Tc sestamibi (normal and pathologic cervical, supraclavicular, axillary lymph nodes, hyperplastic thymus, focal soft tissue uptake from a sarcoid or carcinoid tumor) [ 3 ]. The addition of early lateral views to the conventional 99m Tc sestamibi scintigraphy gives more information to the surgeon, concerning the depth of the lesion in atypical sites [ 20 ]. CT scan with intravenously injected contrast material has a low overall sensitivity of 45%–55% in primary hyperparathyroidism, but it is helpful mainly in the detection of ectopic mediastinal parathyroid adenomas [ 2 , 3 ]. Magnetic resonance imaging (MRI) of the neck and chest has a sensitivity of about 80%. The sensitivity of MRI is higher for the detection of ectopic mediastinal parathyroid adenomas (88%) [ 3 ]. Selective angiography combined with venous parathyroid hormone sampling has sensitivity between 60% and 85%. However, selective angiography is an aggressive and complicated approach and it is not advised as the initial approach in primary hyperaparathyroidism [ 2 , 3 ]. Single photon-emission computed tomographic (SPECT) sestamibi scintigraphy of the neck and thorax has the capability of three-dimensional assessment and it is considered to be the optimal method for the evaluation of parathyroid disease, especially that of mediastinum for ectopic parathyroid glands [ 21 - 24 ]. Fusion of sestamibi SPECT images onto the CT images using a software package, as described by Patrick et al, gives excellent information on the exact localization of ectopic parathyroid tissue [ 19 ]. FDG-PET was found to have higher sensitivity than the sestamibi-SPECT in a prospective study by Neumann et al for preoperative detection and localization of parathyroid adenomas; high cost and limited availability of the scanners restrict its use as first-line examination in primary hyperparathyroidism [ 25 ]. Paraesophageal mediastinal adenomas are resected via a cervical incision in the majority of cases [ 1 , 2 , 16 , 26 ]. By retracting the thyroid gland and trachea to the opposite side, a finger can be inserted into the pretracheal space, even down to the mediastinum, to palpate the tumor. If the tumor is localized by finger palpation, it is easy to mobilize by blunt (finger) dissection and to expose it into the operating field. The vascular pedicle is the only structure that needs to be ligated. When an ectopic cervical or paraesophageal parathyroid adenoma is detected preoperatively by imaging studies, intraoperative frozen section of the adenoma and of a homolateral parathyroid gland, on which normal parathyroid tissue will be confirmed, precludes diffuse parathyroid hyperplasia. A targeted operation can then be chosen, which has the advantage of minimizing the time of operation and avoiding serious hypocalcemia in the immediate postoperative period. [ 26 ] Conclusions An ectopic paraesophageal parathyroid adenoma may be manifested with an episode of acute pancreatitis. Preoperative investigation for exact localization of an adenoma should include two imaging studies, preferably Tc-99m sestamibi scintigraphy or sestamibi-SPECT scintigraphy of the neck and chest and CT scan of the neck and chest. Resection of an ectopic paraesophageal adenoma is easily accomplished via a cervical incision and blunt mobilization of the tumor. Competing interests The author(s) declare that they have no competing interests. Authors contributions CNF has made contribution to the conception, design and drafting of the article, was involved in the critical revision of the article. S R has made contribution to the conception, design and drafting of the article. C L has made contribution to the conception and design of the article. D K has made contribution to the conception and design of the article. G K has made contribution to the conception and design of the article, was involved in the critical revision of the article. AL has made contribution to the conception and design of the article, was involved in the critical revision of the article. All the authors have read and approved the final version of the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538290.xml |
550662 | Proteolytic cleavage of pertussis toxin S1 subunit is not essential for its activity in mammalian cells | Background Pertussis toxin (PT) is an exotoxin virulence factor produced by Bordetella pertussis , the causative agent of whooping cough. PT consists of an active subunit (S1) that ADP-ribosylates the alpha subunit of several mammalian G proteins, and a B oligomer (S2–S5) that binds glycoconjugate receptors on cells. PT appears to enter cells by endocytosis, and retrograde transport through the Golgi apparatus may be important for its cytotoxicity. A previous study demonstrated that proteolytic processing of S1 occurs after PT enters mammalian cells. We sought to determine whether this proteolytic processing of S1 is necessary for PT cytotoxicity. Results Protease inhibitor studies suggested that S1 processing may involve a metalloprotease, and processing does not involve furin, a mammalian cell protease that cleaves several other bacterial toxins. However, inhibitor studies showed a general lack of correlation of S1 processing with PT cellular activity. A combination of replacement, insertion and deletion mutations in the C-terminal region of S1, as well as mass spectrometry data, suggested that the cleavage site is located around residue 203–204, but that cleavage is not strongly sequence-dependent. Processing of S1 was abolished by each of 3 overlapping 8 residue deletions just downstream of the putative cleavage site, but not by smaller deletions in the same region. Processing of the various mutant forms of PT did not correlate with cellular activity of the toxin, nor with the ability of the bacteria producing them to infect the mouse respiratory tract. In addition, S1 processing was not detected in transfected cells expressing S1, even though S1 was fully active in these cells. Conclusions S1 processing is not essential for the cellular activity of PT. This distinguishes it from the processing of various other bacterial toxins, which has been shown to be important for their cytotoxicity. S1 processing may be mediated primarily by a metalloprotease, but the cleavage site on S1 is not sequence-dependent and processing appears to depend on the general topology of the protein in that region, indicating that multiple proteases may contribute to this cleavage. | Background Pertussis toxin (PT) is a complex exotoxin and an important virulence factor produced by Bordetella pertussis , a bacterial pathogen of the human respiratory tract that causes the disease whooping cough. PT holotoxin is a multi-subunit complex with an AB 5 structure [ 1 , 2 ]: the enzymatically active A subunit (S1) is an ADP-ribosyltransferase that modifies the alpha subunit of several heterotrimeric G proteins (primarily G i proteins) in mammalian cells [ 3 , 4 ], and the B oligomer (S2, S3, 2 copies of S4, and S5) binds unidentified glycoconjugate receptors on cells [ 5 , 6 ]. The events in the intracellular trafficking of PT between surface binding and ADP-ribosylation of target G proteins on the cytoplasmic side of cellular membranes are relatively obscure. Electron microscopy studies and experiments with inhibitors suggest that the holotoxin is internalized by endocytosis [ 7 - 9 ]. Subcellular fractionation experiments and inhibition of cytotoxicity by Brefeldin A (BFA), which disrupts the Golgi apparatus [ 10 ], provide evidence for subsequent retrograde transport of PT to the Golgi apparatus [ 7 - 9 ]. Trafficking of PT beyond the Golgi apparatus is relatively uncharacterized, though it has been hypothesized that further retrograde transport of PT through the secretory pathway to the endoplasmic reticulum (ER) occurs [ 11 - 13 ]. After dissociation of S1 from the holotoxin, the liberated S1 subunit is then proposed to traverse the ER membrane to gain access to its target G proteins in the cytosol [ 13 ]. Evidence supporting this ER-to-cytosol translocation was obtained from transfection studies with constructs expressing S1 with a signal peptide for ER localization [ 12 ]. Another observation that may bear on the cell biology and cytotoxicity of PT is that the S1 subunit appears to be proteolytically processed to a lower molecular weight form upon interaction of PT with mammalian cells [ 14 ]. This processing was shown to be dependent upon entry of PT into cells and seemed to involve an early endosome function. The size of the processed form of S1 (approximately 22 kDa versus 26 kDa for the full-length S1) suggested that processing may be targeted at a protease-sensitive loop near the C-terminus of S1 that contains primary sites for trypsin and chymotrypsin cleavage [ 15 ]. However, evidence for the location of the cellular cleavage site on S1 was not presented. In addition, a link between processing of S1 and activity of PT in cells was not established. Proteolytic processing is a common theme in the activation of bacterial toxins upon interaction with mammalian cells. For example, anthrax toxin, diphtheria toxin, Pseudomonas exotoxin A and shiga toxin are all activated after cleavage by the endogenous eukaryotic protease furin [ 16 ], a subtilisin-like protease residing in the secretory pathway of eukaryotic cells [ 17 ], or by closely-related proteases [ 18 ]. Cholera toxin (CT) and Escherichia coli heat-labile toxin (LT) A subunits are cleaved at a protease-sensitive loop to promote maximal activity [ 19 , 20 ], and CT A subunit was found to be cleaved upon interaction of CT with T84 epithelial cells, by an unidentified protease [ 21 ]. In this study we extend the analysis of proteolytic processing of cell-associated S1 and conclude that S1 processing is not essential for the cellular activity of PT. Results and discussion Processing and fractionation of S1 in PT-treated CHO cells In a previous study, 125 I-labelled PT was used for analysis of S1 processing in mammalian cells [ 14 ]. As an alternative to radiolabeled toxin, we analyzed detergent lysates of cells treated with unlabeled PT to determine whether we could detect S1 processing. Near-confluent Chinese hamster ovary (CHO) cells were treated with PT (20 nM) for 4 h at 37°C, and then cells were washed, recovered by trypsinization and lysed on ice with either Triton X-100 lysis buffer or RIPA lysis buffer. The detergent-soluble and -insoluble fractions were then analyzed by sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE) and western blotting. As shown in Fig. 1A , we were able to detect processing of S1 by this method, with the majority of cell-associated S1 present as the lower molecular weight form (S1p, approximately 22 kDa, versus 26 kDa for full length S1). This processing event was independent of PT enzymatic activity, since the enzymatically inactive PT-9K/129G (PT*) was similarly processed by CHO cells (Fig. 1B ). The kinetics of S1 processing (data not shown) were very similar to those previously reported [ 14 ], which, along with the similar size of the processed form, strongly suggested that we were observing the same event as previously studied. Surprisingly, however, the great majority (>80%) of S1 fractionated with the detergent-insoluble pellet material in this assay. Triton lysis at 25°C rather than on ice increased the proportion of S1 that was solubilized, but at least half of the processed form remained in the insoluble pellet material (Fig. 1A ). To determine whether S1 fractionation with the detergent-insoluble material represented a potentially interesting feature of its intracellular transport, or merely an artifact of the lysis procedure, we added 500 ng PT to a Triton lysate of untreated CHO cells, incubated this on ice 30 min, centrifuged to separate the mix into soluble and insoluble fractions and analyzed these by SDS-PAGE and western blotting. Almost all (>95%) of the S1 fractionated to the insoluble pellet (Fig. 1C ), demonstrating that S1 association with detergent-insoluble material occurs in the lysate and is independent of PT transport within cells. The Triton-insoluble fraction typically contains nuclei and cytoskeletal components [ 22 ], so it is possible that PT, or at least S1, has an affinity for one or more of these components. Effects of protease and cell trafficking inhibitors on S1 processing in CHO cells We first ruled out the possibility that furin, a protease that cleaves several other bacterial toxins in mammalian cells, is responsible for S1 cleavage, by finding that S1 processing occurs normally in furin-deficient FD11 cells [ 23 ] (data not shown). This observation was not surprising since there are no consensus furin cleavage sites in the S1 sequence. In order to determine the catalytic type of protease responsible for S1 processing in CHO cells, we preincubated CHO cells with serine, cysteine, aspartic and metalloprotease inhibitors (following the suggestions of Barrett [ 24 ]) before addition of PT, and studied S1 processing by these cells as before (Fig. 2 ). The broad specificity serine protease inhibitor 3,4-DCI did not significantly inhibit processing (though the inhibitor was somewhat toxic to the CHO cells and reduced the amount of S1 recovered), and neither did the serine protease inhibitor aprotinin (Fig. 2A ). The serine protease inhibitor pefabloc SC (BMB/Roche) did have a consistent inhibitory effect on S1 processing, with approximately 45% of the cell-associated S1 in the unprocessed form (versus approximately 10% on average in the absence of inhibitor). Since the other serine protease inhibitors had no effect on S1 processing, the reason for the inhibitory effect of pefabloc SC is unclear, but may be related to its ability to bind covalently to proteins (BMB/Roche). Neither the aspartic protease inhibitor pepstatin nor the cysteine protease inhibitor E-64 had any significant inhibitory effect on S1 processing (Fig. 2A ) (nor did the cysteine/serine protease inhibitor leupeptin – data not shown). However, EDTA had a strong inhibitory effect on S1 processing by CHO cells (Fig. 2A,B ), with 56% and 74% of cell-associated S1 in the unprocessed form in the presence of 0.5 mM and 1 mM EDTA, respectively. Since the inhibitory effect of a non-specific metal chelator such as EDTA could be due to the cation-dependence of activity of other proteases [ 24 ], we also used the metalloprotease inhibitor 1,10-phenanthroline, which has a high affinity for zinc and is considered the most useful inhibitor for metalloproteases [ 24 ]. This inhibitor also had a strong inhibitory effect on S1 processing by CHO cells (Fig. 2B ), with 61% and 63% of cell-associated S1 in the unprocessed form in the presence of 0.5 mM and 1 mM phenanthroline, respectively. Therefore, we conclude that the cellular protease responsible for S1 processing in CHO cells is most likely a metalloprotease, which presumably resides in the secretory (endocytic) pathway and the identity of which remains to be determined. This is a novel observation in the sense that other bacterial toxins are cleaved by cellular proteases of the subtilisin family (such as furin) [ 16 , 23 ] or by other serine proteases [ 21 ], although one report demonstrated that CT activity on several different cell types was blocked by a competitive substrate for metalloproteases [ 25 ], suggesting that metalloproteases may also be involved in the cellular activity of other bacterial toxins. However, the possibility remains that multiple proteases, possibly of different classes, are involved in this S1 processing event. We also determined the inhibitory activity on S1 processing by CHO cells of two inhibitors of cellular trafficking and secretion, bafilomycin A 1 , which inhibits vacuolar proton ATPase and therefore prevents endosome acidification [ 26 ], and BFA, which disrupts the Golgi apparatus [ 10 ]. Bafilomycin A 1 had a significant inhibitory effect on S1 processing, with 51% of cell-associated S1 in the unprocessed form (Fig. 2B ), consistent with the hypothesis that S1 processing occurs in the endosomal compartment of CHO cells and demonstrating a role for endosome acidification in this processing event. However, BFA had no inhibitory effect on S1 processing (Fig. 2B ), consistent with previously reported results [ 14 ] and with the hypothesis that S1 processing occurs prior to the Golgi apparatus in the putative retrograde trafficking pathway. Effects of S1 processing inhibitors on cellular activity of PT Proteolytic processing of bacterial toxins is a common theme in their activation within mammalian cells [ 16 ], but whether cellular processing of S1 plays a role in the activity of PT had not been previously addressed. As a preliminary investigation of this question, we sought to determine whether the inhibitors of S1 processing by CHO cells had any effect on the ability of PT to ADP-ribosylate target G proteins in CHO cells. CHO cells were preincubated with inhibitors before addition of PT (1 nM) as before. Controls were cells to which either PT or PT* (which has no ADP-ribosylation activity) was added in the absence of inhibitor. Cells were recovered after 3 h, and lysates were prepared and tested in the ADP-ribosylation assay. In this assay, active PT within cells will ADP-ribosylate available G proteins, so that when a lysate is prepared from these cells and used in an in vitro ADP-ribosylation assay with PT and 32 P-labelled NAD, there is no labeling of G proteins in the lysate, since they were already modified by the PT added to the cells. If PT activity within cells is inhibited, then a proportion of the G proteins in the lysate from these cells will be unmodified and therefore labeled in the in vitro reaction with PT. The assay was repeated twice and the result of one experiment is shown in Fig. 2C . The mean percent inhibition for the various inhibitors (in decreasing order of their inhibitory effect) was as follows: pefabloc SC – 95%, BFA – 79%, bafilomycin A 1 – 49%, EDTA – 44%, phenanthroline – 28%, 3,4-DCI – 9%, pepstatin – 8%. Therefore there was no strong correlation between the extent of inhibition of S1 processing by the inhibitors and their inhibitory activity on ADP-ribosylation of G proteins by PT in CHO cells. The cell trafficking/secretion inhibitors had a significant inhibitory effect (BFA has previously been shown to inhibit cellular activity of PT [ 7 - 9 ], presumably due to its disruption of PT trafficking in cells, despite its lack of inhibition of S1 processing), but the metalloprotease inhibitors had only a mild inhibitory effect. Of the other protease inhibitors, pefabloc SC had the greatest inhibitory effect, as it did on S1 processing, whereas pepstatin had no significant inhibitory effect on ADP-ribosylation (or S1 processing). To rule out an effect of the inhibitors on the enzymatic activity of PT (independent of its cellular activity), we also performed in vitro ADP-ribosylation assays with PT in the presence of the various inhibitors at the concentrations used on the CHO cells. No significant inhibitory effect was seen with any of the inhibitors (data not shown) with the exception of 3,4-DCI, which was also somewhat toxic to the CHO cells but did not significantly inhibit processing of S1. Altogether, these data are inconclusive with regard to the hypothesis that cellular processing of S1 plays a role in the ADP-ribosylation of G proteins in CHO cells by PT. Location of processing site on S1 We reasoned that if we could identify the precise processing cleavage site on S1, then we would be able to mutagenize this site, obtain a mutant form of S1 that was resistant to cellular processing, and then determine whether processing was required for cellular activity of PT. The size of S1p compared to unprocessed S1 (approximately 22 kDa versus 26 kDa) suggested a cleavage site close to either the N-terminus or the C-terminus of S1, although processing at both termini was also a possibility. Processing at the N-terminus of S1 seems unlikely in view of the fact that the arginine at amino acid 9 (R9) is crucial to enzymatic activity [ 27 ]. A protease-sensitive loop that has primary sites for trypsin and chymotrypsin cleavage [ 15 ] is located towards the C-terminus of S1 (amino acids 211–220; Fig. 3 ) [ 1 ]. To help define the location on S1 of processing by CHO cells, we compared the cellular processing of a modified form of PT containing an extension of 9 amino acids at the N-terminus of S1 (PT*-CSP/N) to that of native PT. As shown in Fig. 4A , the processed form of S1 in cells incubated with PT*-CSP/N was slightly larger (approximately 1 kDa) than that of cells incubated with PT, leading to the conclusion that processing occurs towards the C-terminus of S1. The presence of 2 processed forms of S1 in cells incubated with PT*-CSP/N presumably reflects some additional processing of the N-terminal extension, but since each of these forms is larger than that of S1p from native PT, the conclusion is the same. Fig. 4B shows that the major trypsin-digested fragment of S1 is slightly larger than S1p from cellular processing of PT, suggesting that the site on S1 of cellular processing is close to the protease-sensitive loop, but is N-terminal to the trypsin cleavage site (at R218). However, we cannot rule out the possibility of intracellular modification of S1 that would alter its migration on SDS-PAGE gels and complicate the interpretation of this experiment. We performed extensive site-specific mutagenesis in the region between M202 and R218 of S1 in an attempt to obtain a mutant form of PT that was no longer processed in mammalian cells. However, we were unable to obtain such a mutant by this approach – almost all PT mutants were processed normally, including those with changes at the primary cleavage sites for trypsin (R218A) and chymotrypsin (W215A) (Fig. 5A ). Certain changes at residue A203 (A203D, A203R) resulted in very low levels (<1%) of PT secretion by B. pertussis (data not shown) so that we were unable to determine whether processing was affected. However, other changes at this residue (A203G, A203S, A203V) had no effect on PT secretion, processing or activity (data not shown). In an attempt to locate the processing site, we constructed mutant forms of PT with deletions of various stretches of residues in this region. Each of 2 adjacent deletions of 8 residues (Δ203–210, Δ211–218; Fig. 3 ) resulted in the complete loss of S1 processing in CHO cells (as far as could be determined by western blotting – Fig. 5A ), and the same was true of the overlapping 8 residue deletion Δ207–214 (data not shown), strongly suggesting that the processing site is located in this region. However, smaller overlapping deletions of 4 or 5 residues in this region did not disrupt S1 processing (Fig. 5 and data not shown), indicating that no particular sequence in this region served as a specific cleavage site for the processing event. In further support of this idea, 2 PT constructs in which residues 210–218 of S1 were replaced by random amino acid sequence (210–218/R1 and 210–218/R2) were both processed normally (Fig. 5B ). Equivalent replacement of residues 203–210 abrogated assembly and secretion of PT by B. pertussis , so we could not make the same assessment for this region. However, two lines of evidence suggested that the processing site may be located in the region of residue A203. First, a PT construct (I-205–206) with an insertion of 8 amino acids between residues Q205 and A206 in S1 was processed to the same size S1p as wild type PT (Fig. 5A ), indicating that the processing site was upstream of the insertion (although it may have been within the insertion). Second, mass spectrometry analysis of the processed and unprocessed forms of S1 in lysates from PT-treated CHO cells identified a difference in mass between S1 and S1p (3577.4) most closely corresponding to the theoretical mass of a peptide from R204 to the C-terminus of S1 (3603.9) (data not shown). However, as mentioned above, substitutions at A203 either did not affect processing of S1 or greatly reduced secretion of PT, and substitutions at M202 and R204 also did not affect S1 processing (data not shown), so we were unable to verify this putative cleavage site by mutagenesis. It is also possible that the major processing site is further downstream (within the 211–220 loop region for example) with subsequent additional cleavage occurring during cell lysis, resulting in the apparent size of S1p. Effect of processing site mutations on PT activity We determined the effect of several of these deletion and replacement mutations on PT activity using the ADP-ribosylation assay. Cells were incubated with the purified PT construct (2 nM) for 3 h to determine cellular activity. As shown in Fig. 6A , all mutant constructs retained significant activity, relative to the inactive mutant PT*. The two deletion mutants that were not processed in cells were analyzed further and were found to possess 88.5% (Δ203–210) and 78.1% (Δ211–218) of wild type PT cellular activity (Fig. 6B ). The in vitro activity of these constructs was also assayed, using a fusion of GST with the C-terminal 20 amino acids of human Giα3 (GST-αC20) as the substrate, with the finding that the Δ203–210 mutant possessed 100% of wild type PT activity while the Δ211–218 mutant had a 26.5% reduction in activity (Fig. 6B ). We also found that the 210–218 replacement mutants retained full cellular activity (Fig. 6C ). Together these data demonstrate that S1 processing is not essential for PT cellular activity, since the mutants in which processing was apparently abolished retained significant activity. However, this conclusion must remain tentative in the absence of a single substitution mutant that is unprocessed, which would be the best reagent to answer this question. A large deletion of eight amino acid residues may affect other PT-associated properties or may mask the effects of the loss of processing. The stability of these mutant forms of PT may have been altered, though apparently not significantly reduced from the processing assay data (Fig. 5 ). It is also possible that the number of PT molecules necessary for full activity is low enough to be undetectable in the processing western blot assay. In previous studies, limited trypsin cleavage of PT increased its activation in vitro [ 15 ], indicating that S1 processing may play a role in activity, and domains on S1 for interaction with target proteins and enzymatic activity were found to lie within the N-terminal 204 amino acids [ 28 ], so the processed form of S1 should retain these functions. We also tested several strains expressing mutant PT constructs in our mouse infection model of B. pertussis virulence [ 29 ], and none of these strains was significantly defective in colonization compared to the parental wild type strain (data not shown). Although these data suggest that S1 processing is not essential for the virulence of B. pertussis , it is possible that S1 could be processed in vivo by alternative proteases absent from CHO cells. Processing in stable CHO cell transfectants expressing S1 Previously we constructed stable CHO cell transfectants expressing S1 either with a signal peptide (for ER localization) or without one (for cytoplasmic localization), and showed that S1 fully ADP-ribosylated target G proteins in each transfectant [ 12 ]. In that study we did not observe significant processing of S1 in whole cell lysates of these transfectants, but we re-examined this issue using Triton X-100 lysis of transfectants and western blotting of the insoluble pellet material. As seen in Fig. 7A , there was no detectable processing of S1 to S1p in either transfectant. Exogenous addition of PT to these cells resulted in EDTA-inhibitable processing of S1 to S1p (Fig. 7B ), demonstrating that S1 expression and activity in the transfectants did not prevent S1 processing of exogenously added PT, though the level of processing in the S1+SP transfectant was apparently quite low. The data from these transfectants do not rule out the possibility that S1 processing may contribute to the trafficking of PT to the ER. However, the data are consistent with the idea that S1 processing is not essential for its activity in mammalian cells, and therefore that translocation of the full-length S1 across the ER membrane occurs. This would distinguish PT from several other bacterial toxins of similar subunit structure, such as cholera toxin, heat-labile toxin and shiga toxin, for which processing of the A subunit is apparently important for cellular activity [ 16 ]. The difference may be in the association of the A subunit with the B oligomer. The other toxin A subunits have a relatively long helix that protrudes through a central pore in the B oligomer [ 30 ], and cleavage of the A subunit is required to release the enzymatic domain from this complex. S1 has a relatively short helix associated with the B oligomer [ 1 ], and therefore cleavage may be unnecessary for its release from the holotoxin complex in the ER, or whichever compartment translocation occurs from. Conclusions In this study we have further characterized the cellular processing of the S1 subunit after PT interacts with mammalian cells. Our major conclusion is that this processing event is not essential for PT activity in mammalian cells, based on several lines of evidence: (1) protease inhibitor studies showed a general lack of correlation between S1 processing and PT cellular activity; (2) mutant forms of PT in which S1 processing was apparently abolished retained significant (>75% of wild type) cellular activity; and (3) no S1 processing was apparent in transfected cells expressing active S1. Although we have not definitively ruled out a contribution of S1 processing to the cellular activity of PT due to the imperfect nature of our unprocessed mutants, it is possible that the processing event is completely unrelated to PT cytotoxicity and instead is an irrelevant activity occurring, possibly in lysosomes, on the large majority of the intracellular pool of PT molecules that do not enter the putative retrograde transport pathway to the ER and then on to the cytosolic target proteins. Methods Bacterial strains and growth conditions The B. pertussis strain used in this study was a streptomycin- and nalidixic acid-resistant derivative of W28 (Wellcome). The PT9K/129G (PT*) derivative of this strain was constructed as previously described [ 27 ]. The other PT mutant derivatives used in this study were constructed as described below. B. pertussis was grown on Bordet-Gengou agar (Difco) plates containing 15% defibrinated sheep blood and the following antibiotics at the indicated concentrations where necessary: streptomycin 400 μg ml -1 , nalidixic acid 20 μg ml -1 , gentamicin 10 μg ml -1 ; or in Stainer-Scholte liquid medium [ 31 ] containing heptakis-dimethylcyclodextrin (Sigma). Escherichia coli strains used were DH10B [ 32 ] for standard cloning experiments and S17.1 [ 33 ] for conjugation with B. pertussis , and these were grown on LB agar plates containing 10 μg ml -1 gentamicin where necessary or in LB broth containing 100 μg ml -1 ampicillin. Plasmid and strain construction Plasmid pJ-PT was obtained by subcloning a 2.3 kb Eco RI- Bsr GI fragment (containing the PT S1 and S2 genes) into Eco RI/ Acc 65I-digested allelic exchange vector plasmid pJHC1 [ 34 ]. Mutations were engineered into the S1 sequence of this plasmid, which was confirmed by DNA sequencing, transformed into E. coli S17.1 and introduced into the B. pertussis chromosome by conjugation and allelic exchange as described previously [ 35 ]. Deletion, insertion and substitution mutations were constructed by overlap extension PCR [ 36 ], and the 210–218/R1 and R2 replacement mutations were constructed by using a degenerate oligonucleotide (CARBON 1097; 5'-GATAAGAGCTCCVNNVNNVNNVNNVNNVNNVNNVNNVNNGCCGGCGAGGCCTCGCC-3' where V = G, A, or C and N = any nucleotide) which was allowed to anneal, extended with DNA polymerase Klenow fragment, digested with SacI and BglI and inserted into SacI- and BglI-digested pJ-PT. The GST-αC20 construct was obtained by inserting annealed complementary oligonucleotides (encoding the C-terminal 20 amino acids of human Giα3) into the plasmid pGEX-2T (Pharmacia) to derive pGEX-αC20. The PT*-CSP/N construct was obtained as previously described [ 11 ]. Western blotting Samples were run on 12% SDS-PAGE gels and transferred to nitrocellulose filters. To detect S1, blocked filters were incubated with S1-specific monoclonal antibody X2X5 or 1C7, followed by peroxidase conjugated anti-mouse IgG secondary antibody (Amersham). Blots were developed using ECL Plus (Amersham) and exposed to X-ray film. Protein purification PT and mutant derivatives were prepared from B. pertussis culture supernatants by the fetuin affinity method of Kimura et al. [ 37 ], resuspended in PBS and stored at -80°C until use. The protein concentration was determined by BCA assay (Pierce). GST-αC20 protein was purified from a culture of E. coli DH10B containing the plasmid pGEX-αC20. For induction of the fusion protein, the strain was grown in LB to A600 1.0 and then IPTG was added to a concentration of 0.5 mM. 2 h after IPTG addition, cells were centrifuged, lysed in BPER lysis reagent (Pierce), cleared by centrifugation, and passed through a GSTrap column (Amersham-Pharmacia). Fusion protein was eluted in reduced glutathione buffer, dialyzed against PBS and analyzed by SDS-PAGE and BCA assay (Pierce) to determine protein concentration. Cell lysis and fractionation CHO cells were grown in 6-well plates to near confluency and then PT was added and incubated for the indicated times at 37°C. Cells were then collected by trypsinization, washed in PBS, resuspended in 50–100 μl of either NET/Triton lysis buffer (150 mM NaCl, 5 mM EDTA, 50 mM Tris, pH 7.4, 0.01% NaN 3 , and 0.5% Triton X-100) or RIPA buffer (10 mM Tris, pH 7.4, 0.1% SDS, 1% sodium deoxycholate, 1% NP-40, 150 mM NaCl) and incubated 30 min on ice. The lysate was then centrifuged 15 min at 13,000 rpm at 4°C in a microfuge, the supernatant was removed to a fresh tube and the pellet was resuspended in sample buffer. Samples were boiled 5 min and loaded onto an SDS-PAGE gel. Inhibitors Inhibitors were added to CHO cells 30 min prior to the addition of PT. For protease inhibitors we followed the suggestions of Barrett [ 24 ] to determine the catalytic type of protease involved. Protease inhibitors (BMB/Roche) and concentrations used were: aprotinin (0.15 μM), 3,4-dichloroisocoumarin (3,4-DCI, 1 mM) and 4-(2-aminoethyl)-benzenesulfonyl-fluoride, hydrochloride (pefabloc SC, 1 mM) for inhibition of serine proteases; trans-epoxysuccinyl-L-leucylamido(4-guanidino)butane (E-64, 1 mM) and leupeptin (1 μM) for inhibition of cysteine proteases; pepstatin (1 μM) for inhibition of aspartic proteases; and EDTA (0.5–1 mM) and 1,10-phenanthroline (0.5–1 mM) for inhibition of metalloproteases. Other inhibitors used were BFA (Sigma, 5 μg/ml) and bafilomycin A 1 (ICN, 0.5 μM). After SDS-PAGE and western blotting of samples, band intensities were measured by densitometry and used to calculate the extent of inhibition of S1 processing. Trypsin digestion of PT PT (100 or 200 ng) was digested with trypsin (Sigma) in a volume of 20 μl at room temperature for 1 h in 50 mM Tris, pH 8, and 2 mM CaCl 2 . Trypsin was present at 70 μg/ml. Sample buffer was added and the samples were then boiled 5 min before loading onto an SDS-PAGE gel. Western blotting Samples were run on 12% SDS-PAGE gels and transferred to nitrocellulose filters. To detect S1, blocked filters were incubated with S1-specific monoclonal antibody X2X5 (3) (a generous gift from Drusilla Burns) or 3CX4, followed by peroxidase conjugated anti-mouse IgG secondary antibody (Amersham). Blots were developed using ECL Plus (Amersham) and exposed to X-ray film. ADP-ribosyltransferase assays To determine the cellular activity of PT samples, PT (0.5–2 nM) was added to near confluent CHO cells in 12-well culture plates, and after 3 h at 37°C cells were recovered from plates, washed in PBS and lysed in NET/Triton lysis buffer 30 min on ice. The lysate was then centrifuged 15 min at 13,000 rpm at 4°C and the supernatant was stored at -20°C until the assay. The ADP-ribosylation assay contained, in 25 μl, 0.1 M Tris, pH 7.5, 20 mM dithiothreitol (DTT), 0.5 mM ATP, 1 μM 32 P-NAD (specific activity 30 Ci/mmol; NEN), 10 ng PT, and an aliquot of the lysate sample. For assessment of in vitro enzymatic activity of PT samples by ADP-ribosylation assay, reactions contained, in 25 μl, 0.1 M Tris, pH 7.5, 20 mM DTT, 0.5 mM ATP, 1 μM 32 P-NAD (specific activity 30 Ci/mmol; NEN), 10–50 ng PT, and 0.5 μg GST-αC20 protein as substrate. The mixture was incubated 90 min at room temperature, sample buffer was added, and the sample was boiled 5 min and loaded onto 15% SDS-PAGE gels. After electrophoresis, gels were fixed, dried and exposed to X-ray film. Band intensities were measured by densitometry and used to calculate the extent of ADP-ribosylation of target proteins. Mass spectrometry analysis CHO cells were incubated overnight with PT and then lysates were made using Triton X-100 buffer at room temperature (to maximize the proportion of S1 in the soluble fraction). Purified 1C7 monoclonal antibody was allowed to bind to a PS10 chip (Ciphergen Biosystems) for 2 h at room temperature, which was then washed with PBS. The CHO cell lysates (soluble fraction) were diluted 1:1 with PBS and 100 μl of each lysate was added to a spot on the chip and incubated at 5°C for 4 days. The chip was washed 3 times with PBS containing 0.1% Triton X-100, 3 times with PBS, and twice with 5 mM HEPES (pH 7.0). After the chip was air-dried, matrix (Sinapinic acid) was added to each spot and allowed to dry. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry analysis of these samples was performed in a model PBS-II machine (Ciphergen). Mouse infection Six-week-old female BALB/c mice (Harlan) were used for infection experiments. Bacterial inocula were prepared and intranasal inoculation of mice was performed as previously described [ 29 ]. Seven days after inoculation, mice were sacrificed by carbon dioxide inhalation and the respiratory tract (trachea + lungs) was removed, homogenized in 2 ml PBS, and dilutions were plated on BG-blood agar plates containing streptomycin to determine the number of colony forming units (CFU) per respiratory tract. Authors' contributions NHC conceived of the study, performed some experiments, supervised personnel and drafted the manuscript. RMM performed most of the plasmid and strain constructions, protein purification, processing assays and cell culture work. GVA performed the mouse infection experiments, some plasmid and strain constructions, protein purification, processing assays and ADP-ribosylation assays. RDP performed some of the plasmid and strain constructions and processing assays. ZEVW performed the GST fusion constructions and purification, some ADP-ribosylation assays, cell culture work and contributed to supervision of the other personnel. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550662.xml |
546000 | Variants in the vitamin D receptor gene and asthma | Background Early lifetime exposure to dietary or supplementary vitamin D has been predicted to be a risk factor for later allergy. Twin studies suggest that response to vitamin D exposure might be influenced by genetic factors. As these effects are primarily mediated through the vitamin D receptor (VDR), single base variants in this gene may be risk factors for asthma or allergy. Results 951 individuals from 224 pedigrees with at least 2 asthmatic children were analyzed for 13 SNPs in the VDR. There was no preferential transmission to children with asthma. In their unaffected sibs, however, one allele in the 5' region was 0.5-fold undertransmitted (p = 0.049), while two other alleles in the 3' terminal region were 2-fold over-transmitted (p = 0.013 and 0.018). An association was also seen with bronchial hyperreactivity against methacholine and with specific immunoglobulin E serum levels. Conclusion The transmission disequilibrium in unaffected sibs of otherwise multiple-affected families seem to be a powerful statistical test. A preferential transmission of vitamin D receptor variants to children with asthma could not be confirmed but raises the possibility of a protective effect for unaffected children. | Background Early exposure to dietary and supplementary vitamin D has been predicted to be a risk factor for later allergy and asthma [ 1 ]. Supported by in vitro [ 2 ] and in vivo studies [ 3 ], also epidemiological studies [ 4 , 5 ] report a positive association between supplementary vitamin D use and later allergy [ 6 ]. Vitamin D has been used for many years in various doses and preparations to prevent rickets, a disease usually induced by poor dietary calcium intake and sun deprivation. It seems that widespread "historical" rickets in industrial countries was also a genetic disease. A formal twin analysis yielded a 91% concordance rate in monozygotic twins compared to 23% in dizygotic twins [ 7 ]. Also a very recent study of baseline gene expression in lymphoblastoid cell-lines found the expression of at least four vitamin D related genes as a heritable trait [pers. comm. Monks 2004], which also makes a genetically determined vitamin D sensitivity likely. It may be speculated that common rickets is the low sensitivity form (in the absence of proper endogenous vitamin D production), and allergy the high sensitivity form (in the presence of high oral vitamin D exposure). The active vitamin D metabolite 1,25(OH) 2 D 3 binds to nuclear vitamin D receptor (VDR), which exists from under 500 to over 25,000 copies / cell in many human tissues including thymus, bone marrow, B and T cells and lung alveolar cells [ 8 ]. The gene for VDR was cloned in 1988, it consists of 9 exons with at least 6 isoforms of exon 1 and spans 60–70 kb of genomic sequence (Fig. 1 ) [ 8 ]. The VDR is also a first-order positional candidate as nearly all asthma and allergy linkage studies found linkage on chromosome 12q [ 9 , 10 ]. While an own study of a single Fok1 restriction site (that alters the ATG start codon in the second exon of the VDR) in asthma families did not find an association [ 11 ], positive association of several VDR variants with asthma has been shown in the meantime by two U.S. [ 12 ] as well as one Canadian study [ 13 ]. Figure 1 Structure of the vitamin D receptor [40, 41]. Upper: LD blocks in Caucasians [14] where blocks "C" and "A" extend to both sides. In Africans block "C" is split into 3 parts, "C1", "C2" and "C3". Middle: Exon structure including several SNP variants examined in about 100 disease-association studies. Lower: Aligned protein domains, DNA binding, hinge and ligand binding region including phosphorylation sites. So far, dbSNP catalogued 117 SNPs in the VDR when a resequencing approach of the VDR published in June 2004 found 245 SNPs [ 14 ]. In this study three LD blocks were localized. Block "A" at the 3' end of exon 9 spans approximately 10.5 kb. VDR exons 3 – 9 are situated in block "B", which spans 40.8 kb. A 5.7 kb LD-breaking spot separates blocks "A" and "B", while blocks "B" and "C" are separated by a 1.3 kb LD-breaking spot; this region also includes VDR exon 2 and the commonly studied FokI SNP. All three LD blocks have now been covered by additional SNPs in our asthma family sample. Results The sample analyzed here consisted of 951 individuals from 224 pedigrees contributing 11,383 genotypes. Mean pedigree size was 4.4; the number of phase-known individuals ranged from 221 to 305 (with the exception of rs2853563) in affected, and from 24 to 41 in the unaffected, children. Except for rs2853563, the minor allele frequency always exceeded 19%. In two families both parents had asthma, in 82 only one parent had asthma and in 140 families both parents were disease-free. Of the markers tested, only marker rs2239186 showed a slightly reduced transmission ratio in asthmatic children (0.8, P = 0.073). In unaffected children three markers showed significantly altered ratios: 0.5 for hCV2880804, and 2.0 and 1.9 in rs1989969 and rs2853564, respectively. Excess transmission was generally more pronounced in unaffected children (Fig. 2 ), however, the three significant associations would also not persist if adjusted for multiple testing with the method described by Bonferroni. Figure 2 Excess transmission of VDR-SNPs in asthma families. Blue bars indicate transmission to affected children, grey bars transmission to unaffected children. The TDT DS test as a global family test seems to capture the information both from affected and unaffected children, with four SNPs being at least marginally significantly associated at the 5% level. As unaffected children might be the younger children (that still have not developed a phenotype), the age distribution of affected and unaffected children was also compared (Fig. 3 ) but no difference was found. Affected and non affected children, however, show several other differences, all known as risk factors and symptoms for asthma: There are more boys in the affected group (57,6% vs. 36,1%), they are more often exposed to indoor environmental tobacco smoke (43.0% vs. 31.7%) and they are suffering more frequently from eczema (43,0% vs. 26,9%). Their average log(IgE) values are higher (7,7 kU/l vs. 5,8 kU/l), their forced 1 second capacity FEV1 is lower (2387 ml vs. 2625 ml) together with the forced vital capacity (2876 vs. 2998). Figure 3 Age distribution in children with, blue box (left), and without asthma, grey box (right). Bronchial hyper-reactivity (BHR), measured as quantitative trait locus (QTL) by using the slope of the dose-response curve in a standardized methacholine challenge protocol, also indicated an association with the same three SNPs identified in unaffected sibs. Further dichotomizing BHR by comparing the upper versus all other quartiles also yielded significant associations (hCV2880804, P = 0.005, rs1989969 P = 0.001, rs2853564 P = 0.001). The sum score of all specific IgE serum levels (RAST) was associated with markers rs1989969 (P = 0.021) and rs2853564 (P = 0.018), while total IgE was not found to be associated. Table 2 summarizes the LD structure of all SNPs in the German families. LD was generally low, except for three SNPs on block "B". SNP rs2853563 probably does not interrupt block "B", as might be concluded from table 2 , as this marker has a very low minor allele frequency (table 1 ). The overall low LD was very similar in the Swedish and Turkish subgroups of our families and are in line with recently published data [ 12 - 14 ]. The association seen for the two SNPs at the 3'-terminal region is probably influenced by the high LD between these two SNPs. Table 1 Transmission disequilibrium of 13 VDR-SNPs in affected and unaffected children. P-values < 0.05 are indicated in bold. asthma no asthma LD block * dbSNP allele chr12 (bp) geno-types freq (%) T UT T/UT P T UT T/UT P P TDT DS A hCV2880804 C 47954855 918 28 170 178 1,0 0,668 18 33 0,5 0,049 0,055 -- rs2228570 T 47977944 724 35 159 150 1,1 0,609 21 12 1,8 0,117 0,079 ? rs3819545 C 47981753 912 38 186 191 1,0 0,797 25 31 0,8 0,423 1,000 B rs3782905 G 47982914 934 32 201 174 1,2 0,163 26 27 1,0 0,891 0,388 ? rs2853563 G 48248398 661 97 20 24 0,8 0,547 -- -- -- -- -- B rs731236 C 48251417 923 37 202 206 1,0 0,843 25 29 0,9 0,586 0,767 B rs1544410 A 48252495 896 37 190 186 1,0 0,837 23 26 0,9 0,668 1,000 B? rs2239185 C 48257219 903 49 198 214 0,9 0,431 29 24 1,2 0,492 0,650 ? rs987849 C 48267336 825 45 164 169 1,0 0,784 28 18 1,6 0,140 0,173 B rs1540339 A 48269986 916 36 189 187 1,0 0,575 25 27 0,9 0,782 0,706 ? rs2239186 C 48282070 929 19 116 145 0,8 0,073 20 18 1,1 0,746 0,189 C rs1989969 T 48290670 922 43 204 198 1,0 0,765 39 20 2,0 0,013 0,025 C rs2853564 C 48291147 920 44 196 201 1,0 0,802 38 20 1,9 0,018 0,021 *according to reference [15] Table 2 D' matrix of 13 VDR-SNPs in German parents. D' values > = 0.69 are indicated in bold. rs2228570 rs3819545 rs3782905 rs2853563 rs731236 rs1544410 rs2239185 rs987849 rs1540339 rs2239186 rs1989969 rs2853564 hCV2880804 0,01 0,02 -0,04 0,05 0,01 0,01 -0,02 -0,01 0,05 0,02 -0,27 -0,27 Rs2228570 0,02 -0,03 0,01 0,06 0,02 -0,01 -0,03 -0,03 -0,10 0,12 0,13 Rs3819545 -0,53 0,08 -0,41 -0,41 0,26 0,25 0,85 0,58 -0,02 -0,02 Rs3782905 -0,08 0,53 0,55 -0,44 -0,45 -0,45 -0,33 0,05 0,05 Rs2853563 -0,14 -0,16 0,20 -0,10 0,19 -0,01 -0,07 -0,08 Rs731236 0,98 -0,76 -0,69 -0,46 -0,32 0,07 0,05 Rs1544410 -0,76 -0,69 -0,46 -0,33 0,06 0,05 Rs2239185 0,85 0,28 0,33 -0,06 -0,05 Rs987849 0,22 0,40 -0,02 -0,01 Rs1540339 0,58 -0,07 -0,07 Rs2239186 -0,11 -0,11 Rs1989969 0,98 Finally, a 4-locus haplotype was constructed of those SNPs associated in the TDT DS . Again, no significant transmission distortion was found in affected children, while one haplotype showed a 5.1-fold over-transmission in unaffected children (P = 0.009). Discussion This study addresses a previously described association of VDR SNPs with asthma and related phenotypic traits. Although a preferential transmission of vitamin D receptor variants to children with asthma could not be confirmed, it raises the possibility of a protective effect in unaffected children. Although the effect is rather moderate, several SNPs support this association. If any, the association is probably more related to RNA turnover than to a structural modification of the receptor as there was no association with LD block "B" that codes for the translated exons. Gene expression can be varied over a 100-fold range by subtle modifications of the 3'-terminal sequence [ 15 ], which will requires further research on the function of these allelic variants in target tissues. This notion is partially in contrast with a previous study of 7 VDR SNPs in the CAMP (Childhood Asthma Management Program) study of 582 nuclear families where SNP rs7975232 (akin ApaI) in intron 8 showed a highly significant effect [ 12 ]. A confirmation study by the same group in a case-control sample of the Nurses' Health Study NHS [ 12 ] also associated asthma with rs3782905 (intron 2, P = 0.02), rs2239185 (intron 3, P = 0.02) and rs731236 (Ile352Ile, P = 0.03). A study of 223 independent Canadian families reported six out of twelve SNPs to be associated with asthma (rs3782905, rs1540339, rs2239182, rs2239185, BsmI, ApaI, TaqI), most of these on block "B". As none of these SNPs was giving rise to an amino acid change the authors speculated about an intronic regulatory SNP or one or more functional variants at the 3' end of the VDR locus. It is unlikely that increased or decreased vitamin D sensitivity is simply mediated by a genetic variation in the VDR. Vitamin D requires several enzymatic steps to be activated, transported and degraded; receptor signalling requires several co-factors and all of these may contribute additive or multiplicative effects on vitamin D sensitivity. The co-activator retinoic acid receptor RXR may itself affect Th1 and Th2 development [ 16 ]. Other transcription factors involved are SRC/p160, CBP and p300 [ 17 ]. The DRIP complex attaches to the VDR/RXR complex and binds to vitamin D responsive elements (VDRE) through histone acetyltransferase activity. Importantly, some of the vitamin D regulated genes are also located in allergy linkage regions. The renal 1-α-hydroxylase (12q13) and the 24-hydroxylase (20q13), as well as RXR (6p21), are all positional candidates. RXR has already been tagged by a SNP in a previous study [ 18 ] and also 3 SNPs in CYP24A1 (rs751089, rs2296241 and rs2248137) were significantly associated with asthma ( unpublished own observation ). CYP24A1 is particular interesting as it is the major enzyme of the degradation pathway that showed a 97-fold increase after vitamin D treatment of rats [ 19 ] or 12-fold increase in a human colon cancer cell line [ 20 ]. The number of genes regulated by vitamin D has been recently extended beyond those genes with known VDRE promoter motifs (calbindin, PTH, PTHRP, ITGB3, OC, GH, osteopontin, osteocalcin, c-fos, IL-2Rβ, NFκB, sCD23) to another 150 up- and down-regulated regulated genes [ 19 - 23 ]. The interaction of genetic variants in the VDR and other positional, as well as functional, candidate genes is therefore a current research topic. So far, only two gene associations have been published: Vitamin D binding protein (GC*2 and GC*1F) was associated with an increased risk for COPD [ 24 , 25 ] and osteopontin (OPN C8090T and T9250C) with increased total IgE in asthmatic patients [ 26 ]. In addition to its biological context, this study also has some implications on the statistical analysis as the rather low number of unaffected sibs seemed to contribute to a few positive associations. Despite enormous efforts to map complex genetic diseases, SNP association studies are often lacking power [ 27 ]. Linkage studies in affected sib pairs have been preferably used to map complex diseases to chromosomal regions [ 9 ], while "no substantial study of normal sib-pairs has been undertaken, making this family of surveys one of the largest undertaken in the absence of controls" [ 28 ] although unselected affected sib pairs tend to share more than half of their alleles [ 29 ]. This omission is even more remarkable as discordant sib pairs (DSP) have been shown to be a more powerful alternative [ 30 ]. Risch proposed to test DSP in the top ten and bottom ten percent distribution of quantitative traits, as pairs with intermediate values (between the 30 th and 70 th percentiles) did not provide much information for linkage analysis [ 31 ]. Although the DSP concept was appealing from a theoretical standpoint, it turned out that there are disadvantages for practical reasons. It requires a large amount of individuals to be screened, which might be the reason that the DSP approach has not received the expected attention except for a few studies (for a summary see [ 31 ]). Transmission disequilibrium testing of unaffected child – parent trios originating from families with another two affected offsprings, may be a powerful alternative. As there is a strong ascertainment bias of these families toward a genetic risk, as well as a disease causing environmental factor, being unaffected is an extreme phenotype ("being sane in an insane world"). The transmission to unaffected children can be seen as an independent cross-match to the transmission to affected children. The high power of testing unaffected sibs has already been predicted on theoretical grounds [ 32 ]. The number of DSPs required to achieve 80% power (with a difference in the allele frequency of 15% and λ s of 3.2) has been estimated to be approx. 250 [ 33 ]. A sample size of 1,500 families was estimated by including two affected and one unaffected children [ 34 ]. In this study already 50 DSPs were sufficient to show a significant distortion in the allele transmission. Non-paternity as a reason for discordant traits [ 35 ] is unlikely as nearly all families were included in a previous genome-wide scan. Conclusions The transmission disequilibrium in unaffected sibs in otherwise multiple-affected families seems to be a powerful test. A preferential transmission of vitamin D receptor variants to children with asthma could not be confirmed but raises the possibility of a protective effect in unaffected children. Methods Study population The German asthma sib pair families were collected in 26 paediatric centres in Germany and Sweden for an initial genome-wide linkage scan. In these families at least two children were required with confirmed doctor-diagnosed asthma, while prematurity or low birth weight of the children were excluded, along with any other severe pulmonary disease. All affected children should have after their 3 rd birthday a history of at least three years of recurrent wheezing and should not have any other airway disease diagnosed. Unaffected siblings were also sampled if they were at least 6 years old, eligible for pulmonary function testing and did not have doctor-diagnosed asthma. On the first home visit a complete pedigree of the family was drawn and information collected in a questionnaire. Participants were examined for several associated phenotypes. Pulmonary function tests were performed by forced flow volume tests and bronchial challenge was done by methacholine. Briefly, pulmonary function tests were performed by forced expiration in a sitting position using a nose-clip. Forced flow volume tests were performed until three reproducible loops were achieved. Of these the trial with the maximum sum of FVC and FEV1.0 was used for the analysis. Bronchial challenge with methacholine was done with increasing doses of 0, 0.156, 0.312, 0.625, 1.25, 2.5, 5, 10, 25 mg/ml during 5 consecutive breaths with 14 mg delivered from a de Vilbiss 646 nebulizer chamber by using a breath-triggered pump ZAN 200 (Zan, Oberthulpa, Germany). The provocation was stopped either with the occurrence of symptoms or a fall of 20% from the baseline FEV1.0 and the slope of the dose-response curve calculated. Total IgE was determined with an ELISA (Pharmacia Diagnostics, Uppsala, Sweden). The allergens tested were birch (betula verruscose) ALK SQ108, hazel (corylus avellana) ALK SQ113, the herbs ribworth (plantago lanceolata) ALK N342 and mugwort ALK SQ312, mixed grass ALK SQ299, dust mite dermatophagoides farinae ALK SQ 504, dermatophagoides pteronyssimus ALK SQ 503, cat dander ALK SQ555 and dog dander ALK SQ 553, and fungi (aspergillus fumigatus ALK N405 and alternaria alternata ALK N402), which were bought in one batch and stored at +5°C until analysis. The original family collection [ 36 ] has been expanded since 1994 to a larger sample, of which 218 families were available in 2002 for a complete genome scan. The consecutive families were tested with the same protocol as described earlier [ 36 ] except that the time-consuming methacholine challenge protocol was omitted. Excluded from the final sample were individuals with incomplete data, missing DNA samples, identical twins and all probands with more than 2 non-segregating out of 408 microsatellite markers. Another 6 families could be included in this analysis, resulting in a final sample of 224 families. Each study participant, including all children, signed a consent form. All study methods were approved in 1995 by the ethics commission of "Nordrhein-Westfalen" and again in 2001 by "Bayerische Landesärztekammer München". DNA preparation and genotyping DNA was isolated from peripheral white blood cells using Qiamp (Qiagen, Germany) or Puregene isolation kits (Gentra Systems, Minneapolis, MN, USA). From the VDR we selected 16 SNPs where 13 could finally be analyzed. They had to be polymorphic, complete, received a high calling score, passed paternity checks and were in Hardy-Weinberg equilibrium. The following three markers have been excluded from the analysis: rs2239179 (contaminant in mass spectrum peak), rs2853559 (Hardy-Weinberg disequilibrium, paternity errors) and rs797523 (typing error in primer sequence). Genotyping was performed using MALDI-TOF mass spectrometry of allele-specific primer extension products (Table 3 ) generated from amplified DNA sequences (MassARRAY, SEQUENOM Inc., San Diego, CA, USA). Primers were obtained from Metabion GmbH (Planegg-Martinsried, Germany). Table 3 Primer used for genotyping SNP left primer right primer extension primer stop mix hCV2880804 ACGTTGGATG-CTGGGATACTTCTGAGAGTG ACGTTGGATG-TTTTCCCTGGAAAGTTTGGG CCATTGTCCTGGTATAACCA ACG rs2228570 ACGTTGGATG-TCAAAGTCTCCAGGGTCAGG ACGTTGGATG-AGACCTCACAGAAGAGCACC CCCTGCTCCTTCAGGGA ACG rs3819545 ACGTTGGATG-AATGGTGGTTACTGCAGCTC ACGTTGGATG-GAAACCAGTCCTCTGTCATG TAGGTTCGGTCTTTGGCT ACG rs3782905 ACGTTGGATG-GGGTCTCAAATTCTTAATGAG ACGTTGGATG-AAACTAGCAGAAAGAGGCAG GTGGGAGGGAGTGCTGA ACT rs2853564 ACGTTGGATG-CTGCATTGCTCCTGACTTAG ACGTTGGATG-AGGTAGCTTAGCTCTGAGTC TTTCTGCAACCCTAAGCC ACT rs731236 ACGTTGGATG-TGTGCCTTCTTCTCTATCCC ACGTTGGATG-TGTACGTCTGCAGTGTGTTG CGGTCCTGGATGGCCTC ACT rs1544410 ACGTTGGATG-TAGATAAGCAGGGTTCCTGG ACGTTGGATG-AATGTTGAGCCCAGTTCACG AGCCTGAGTATTGGGAATG ACG rs2239185 ACGTTGGATG-CAATTCCAGTCACATCTCGG ACGTTGGATG-CCTGTGTGACATTTACACCC CCCTCCTCTGTCTTCAC ACT rs987849 ACGTTGGATG-GAATAGTGCCTTATAGATAG ACGTTGGATG-AGCTAGAAGTTCTGGTGATC GAAATATTCGTAATGCTGGAT ACT rs1540339 ACGTTGGATG-TCACACACATTCTCAGTGGG ACGTTGGATG-TTTGCAGAGGCTGTCTTCTC GTTGGTGCCCACCCTAA ACG rs2239186 ACGTTGGATG-GTCCACAGTGACTATAGACC ACGTTGGATG-AAGAAGGAGAAGCAGGCATC CAGGGGTGGAAGAAGAGGAG ACT rs1989969 ACGTTGGATG-TGTATGCAGAGCTTAGCAGG ACGTTGGATG-TTTCAGAGGTCAGAGGTGAC GTCAGAGGTGACATCCAG ACT rs2853564 ACGTTGGATG-CTGCATTGCTCCTGACTTAG ACGTTGGATG-AGGTAGCTTAGCTCTGAGTC TTTCTGCAACCCTAAGCC ACT Data handling and statistical analysis Clinical data and genotypes were transferred to a SQL 2000 database by using Cold Fusion 4.0 scripts. Statistical analyses were performed using R 1.8.1 [ 37 ] by accessing the database with the RODBC module. For each SNP, the distribution of genotypes in pseudo-controls created by combining the parental alleles not transmitted to asthma children was tested by a χ 2 -test as well as the transmission to their unaffected sibs. An extension of the classical TDT [ 34 ] was also implemented that incorporates effectively both affected and unaffected children (TDT DS ). The standardized linkage disequilibrium coefficient D' and the correlation coefficient R 2 were calculated for each pair of SNPs in parents by using the R package "genetics". All analyses were cross-checked by using SIBPAIR software. Haplotypes were estimated using TDTPHASED in the UNPHASED package [ 38 ] and transmission to affected and unaffected children tested separately. For phase-certain haplotypes a conditional logistic regression model was used, corresponding to the probability of the offspring conditional upon the parents. When phase was uncertain, unconditional logistic regression on the full likelihood of parents and offspring was used instead (see [ 39 ] for the formulations of these likelihoods). Transmitted haplotypes were compared to all untransmitted haplotypes, equivalent to the haplotype-based haplotype relative risk, while an EM algorithm was used to obtain maximum-likelihood estimates of case and control parental haplotype frequencies under both null and alternative hypotheses. Abbreviations VDR vitamin D receptor VDRE vitamin D responsive element SNP single nucleotide polymorphism MALDI-TOF matrix assisted laser desorption ionisation – time of flight DSP discordant sib pairs TDT transmission disequilibrium LD linkage disequilibrium QTL quantitative trait locus BHR bronchial hyperreactivity FEV1 forced volume during the 1st second Author's contribution The author developed the idea presented in this paper, initiated the study, applied for funding, developed protocols, participated in the clinical survey, planned the laboratory analysis, did the statistical analysis, and drafted the report. This manuscript contains no patient identifiable information. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546000.xml |
518961 | Different patterns of evolution for duplicated DNA repair genes in bacteria of the Xanthomonadales group | Background DNA repair genes encode proteins that protect organisms against genetic damage generated by environmental agents and by-products of cell metabolism. The importance of these genes in life maintenance is supported by their high conservation, and the presence of duplications of such genes may be easily traced, especially in prokaryotic genomes. Results The genome sequences of two Xanthomonas species were used as the basis for phylogenetic analyses of genes related to DNA repair that were found duplicated. Although 16S rRNA phylogenetic analyses confirm their classification at the basis of the gamma proteobacteria subdivision, differences were found in the origin of the various genes investigated. Except for lexA , detected as a recent duplication, most of the genes in more than one copy are represented by two highly divergent orthologs. Basically, one of such duplications is frequently positioned close to other gamma proteobacteria, but the second is often positioned close to unrelated bacteria. These orthologs may have occurred from old duplication events, followed by extensive gene loss, or were originated from lateral gene transfer (LGT), as is the case of the uvrD homolog. Conclusions Duplications of DNA repair related genes may result in redundancy and also improve the organisms' responses to environmental challenges. Most of such duplications, in Xanthomonas , seem to have arisen from old events and possibly enlarge both functional and evolutionary genome potentiality. | Background The availability of complete genome sequences from different organisms makes it possible to identify, by similarity, potential homologs of genes that have been experimentally tested in other living beings, resulting in the recognition of putative functions for the proteins encoded by them. This research concept represents a revolutionary tool in modern biology, as the data generated allow for recognition of the presence or absence of genes, giving indications of the metabolic pathways present in such organisms and revealing possible particularities of the individuals in their natural habitat. Moreover, the possibility of obtaining gene sequences from organisms that have long diverged makes it feasible to use these data to trace their evolutionary origin [ 1 ]. Computer analysis of genome data, and its capacity to rapidly generate relevant information, contributes to a better understanding of the different evolutionary histories, especially within prokaryotes. The inferred relationship among organisms, as first defined by the use of 16S rRNA sequences, was later confirmed either by the utilization of many other conserved genes [ 2 , 3 ] or even by alternative strategies to trace evolution with genetic data [ 4 ]. However, the utilization of a single gene to describe the organism evolution has been contested due to genomic complexity. In fact, the accumulated data have brought evidence to sustain that many prokaryotic genes do not follow vertical transmission, revealing the occurrence of gene exchange among different species, a phenomenon known as horizontal or lateral gene transfer (LGT, reviewed by Ochman [ 5 ]). All known forms of life present efficient systems to maintain the integrity of their genetic material. As DNA is under constant attack by different environmental agents and metabolic by-products, evolution has provided organisms with several DNA repair pathways to remove or to tolerate lesions in their genetic material. In fact, these pathways have at least two important contrasting roles in evolution, safeguarding the genome, and allowing for a certain level of mutations in the course of evolution. The critical balance of these two activities is probably the best reason for the high levels of conservation observed in DNA repair related proteins, even across the three kingdoms, Bacteria, Archaea and Eukarya. Detailed studies of many of the different DNA repair genes and protein domains have been described previously [ 6 , 7 ], confirming that information on DNA repair genes may be very useful as a source to track genome evolution. In this work, we investigated the DNA repair genes in the recently described genomes from the Xanthomonadales group [ 8 , 9 ] following an evolutionary perspective. The Xanthomonadales group bacteria have a great economic impact on agriculture in Brazil and worldwide. The characterization of DNA repair genes from these phytopathogens could help to understand the mechanisms by which these organisms respond to environmental conditions, including plant infection. On the other hand, this could contribute to defining universal features relating DNA repair with this life style. By comparing the evolutionarily close genomes of Xanthomonas axonopodis , X. campestris and Xylella fastidiosa , we found that certain DNA repair genes present duplications in both Xanthomonas species. The great relevance of gene duplication for expanding gene families, as well as for gene innovation, is a consensus among researchers. New genes can facilitate survival in new environments or make possible the use of new metabolites. We investigated the phylogeny of such duplicated genes, in search of evidence on the mechanisms by which cells evolve their DNA repair machinery. Although most DNA repair genes follow the conserved vertical transmission found for 16S rRNA phylogeny, the data clearly show that duplications may have arisen by different means. Examples of a recent duplication, as well as of other old or LGT events, generating paralogs, are presented. These results also help in tracing the origins of LGT events that lead to redundancy and also to functional diversification, especially of Xanthomonas bacteria. Results and Discussion DNA repair-related genes are normally highly conserved, and grant good genetic information for investigating the evolution of organisms. Orthologs of known bacterial DNA repair proteins were identified in the plant pathogen bacteria of the Xanthomonadales group and are listed in Table 1 . The different gene content of these closely related bacterial species are of particular interest, given that they can reveal gene loss or acquisition as a consequence of their different lifestyles. Few genes are missing in the genome of X. fastidiosa , when compared to both Xanthomonas species: ada-alkA (fusion), tag , phr , dinB and ligB . For evolution purposes, however, the presence of several duplications, especially in the Xanthomonas genomes, will be focused here. Table 1 Distribution of DNA repair genes in Xanthomonadales: presence of duplications. Repair Pathway Xanthomonas axonopodis [5.27 Mbp] Xanthomonas campestris [5.08 Mbp] Xylella fastidiosa [2.73 Mbp] Nucleotide Excision Repair (NER) uvrA(2) , uvrB , uvrC(2) , uvrD(2) , mfd uvrA(2) , uvrB , uvrC(2) , uvrD , mfd uvrA , uvrB , uvrC , uvrD , mfd Base Excision Repair (BER) alkA a , fpg , mag , mutY , nth , tag , ung , xthA (2) alkA a , fpg , mag , mutY , nth , tag , ung , xthA (2) fpg (2) , mag , mutY , nth , ung , xthA Mismatch Repair b (MMR) mutS , mutL mutS , mutL mutS , mutL Direct Repair alkB , phr , ogt alkB , phr , ogt , alkB , ogt Recombination Repair recA , recBCD , recF , recG , recJ , recN , recO , recR , recQ , ruvABC , sbcB recA , recBCD , recF , recG , recJ , recN , recO , recR , recQ , ruvABC , sbcB recA , recBCD , recF , recG , recJ , recN , recO , recR , recQ , ruvABC , sbcB Other DNA Repair related genes ada a , lexA(2) , dinB , ligA c , ligB c (2) ada a , lexA(2) , dinB , ligA c , ligB c (3) , umuDC lexA , ligA c Genome sizes are indicated within brackets. The DNA repair genes identified in the genome of the three organisms are shown. Those present in more than one copy due to duplications are marked in bold (numbers in parenthesis). a alkA and ada regulatory domain genes are fused in these bacteria. b mutH , found in E. coli , is not present in these 3 genomes. c ligA corresponds to the NAD-dependent ligase and ligB to the ATP-dependent ligase (see text). The RecA protein is almost universal among bacteria and is a clear example of phylogeny that follows 16S rRNA gene evolution. In fact, this gene is always unique in all genomes analyzed and has been proposed as an alternative molecule to be used in systematic studies of Bacteria [ 2 ]. Figure 1A shows the phylogenetic tree generated for this protein, and confirms the distinction of the main groups of bacteria, such as Firmicutes, Chlamydiales, Spirochaetales and Proteobacteria. Among the proteobacteria, the Xanthomonadales branch is independently positioned at the root of gamma subdivision. It is important to note that although this seems to be consistent with the classification of these bacteria as part of gamma proteobacteria, very often the trees, from these and other proteins (see below), place the Xanthomonadales in the same branch as beta proteobacteria ( Neisseria and Ralstonia ). Figure 1 Consensus unrooted trees generated by the Neighbor-Joining distance method for the RecA (A) and for the LexA proteins (B). The circles highlight the main groups of bacteria. The symbol * indicates the beta proteobacteria. Some groups of bacteria included in (A) which are absent in the other trees: Spirochaetales: TREPA: Treponema pallidum (gi| 7443874), BORBU: Borrelia burgdorferi (gi| 15594476); Chlamydiales: CHLTR Chlamydia trachomatis (gi| 7443880), CHLPN: Chlamydophila pneumonia e CWL029 (gi| 7443883). The homologs of X. axonopodis and X. fastidiosa are indicated inside the square boxes. In E. coli , the RecA protein has been shown to participate in recombinational repair, as well as in the control of a set of physiological changes to DNA damage, known as SOS response. The induction of this regulon stems from the co-protease activity of the RecA protein, which cleaves a repressor protein, denominated LexA, allowing the expression of the set of SOS genes. The presence of lexA and recA homologs in the Xanthomonadales indicates that these bacteria also present a SOS regulon. However, in Xanthomonas genomes, there are two copies of the lexA gene. The phylogeny of LexA proteins is presented in Figure 1B . The general topology of this tree indicates that LexA evolution follows a similar pattern to RecA, although the lexA gene is not found in all groups of bacteria. The products of the two copies of the Xanthomonas lexA paralogs are positioned close together in the same branch of Xanthomonadales, indicating a recent duplication of such a gene. The fact that they had branched before Xylella 's single lexA divergence indicates that this bacterium may have lost the duplication. Gene losses are expected to be extensive in Xylella , in agreement with this bacterium having a more specialized parasitic way of life [ 10 ]. The duplication of lexA in Xanthomonas points to a highly controlled SOS regulon, that may be important for fine-tuning the bacterial responses to stress induced in environmental changes. Indeed, functional characterization of lexA1 in X. campestris has been performed by gene disruption, and the data indicate this protein controls the expression of the recA gene, as expected for the SOS regulatory circuit [ 11 ]. The function of the second paralog, however, remains to be elucidated. Recent report indicates that the disruption of the lexA gene in Deinococcus radiodurans does not change the level of RecA expression, suggesting that LexA protein may be related to functions other than controlling the SOS regulon in that organism [ 12 ]. The nucleotide excision repair (NER) pathway is one of the most important, versatile and conserved systems of DNA damage removal in bacteria. It recognizes damages, which cause significant helix distortions in the DNA molecule, these being excised as an oligonucleotide by several enzymes that act as helicases and endonucleases. The main proteins that participate in such a pathway are known as UvrA, UvrB and UvrC, which, in sequential steps, interact with one another, recognize the damaged strand (UvrA), open the double helix (UvrB), and cleave DNA (UvrC) at both sides, few nucleotides away from the lesion. Subsequently, the oligonucleotide containing the damage is removed by a DNA helicase known as UvrD. The uvrB gene from X. campestris has been cloned and it was shown to participate in the resistance of these bacteria after UV irradiation [ 13 ]. The NER proteins are very well conserved and universal among bacteria. A complete set of orthologs of these genes is also found in a few species of the group Euryarchaeote: Methanothermobacter thermautotrophicus , Methanosarcina sp and Halobacterium sp. NRC-1 [ 14 ]. Other archaea may have a different unknown NER system [ 15 ]. The genes uvrA , uvrC and uvrD are duplicated in Xanthomonas and the phylogenies of the proteins encoded by these orthologs, together with the single uvrB , are presented in figure 2 . In general, the evolution of these proteins, particularly UvrB (figure 2B ), follows a pattern similar to RecA, the NER protein of Xanthomonas being positioned in the same branch of the Xylella 's ortholog, close to gamma proteobacteria as expected for a vertical descent. However, for the duplications, the patterns are different and more complex. The second ortholog of uvrA in X. axonopodis is phylogenetically closer to the also duplicated genes found in several other bacteria (figure 2A ), thus indicating an old duplication event in evolution. The absence of this ortholog in most of the proteobacteria could be due to extensive gene loss. However, the phylogenetic proximity with unrelated organisms (including a duplication in D. radiodurans ) points to an origin due to horizontal gene transfer from other bacteria. The functions of both uvrA orthologs are not necessarily related to DNA repair, since this activity can be provided by either one of them. It is relevant to mention that for the duplication found in D. radiodurans , White et al [ 16 ] have proposed a function related to the transport of damaged DNA out of the cell. This is due to the similarity of the UvrA protein with the ATP-binding subunit of a multifamily of genes involved in the transport across membranes, related to ABC transporters [ 17 ]. Figure 2 Consensus unrooted trees generated by the Neighbor-Joining distance method for the UvrA (A), UvrB (B), UvrC (C) proteins and for the UvrD helicase family (D). The numbers in front of organism names indicate the number of members of this gene family in the corresponding organism. The circles highlight the main groups of bacteria. Inside the square box, the homologs of X. axonopodis and X. fastidiosa. In (A) there is a clear distinction between the two UvrA orthologs separated by the line. In the upper part of the figure are grouped the organisms containing the second UvrA homolog, for which no function in DNA repair has yet been assigned. In (D) the names of the genes are based on annotation available. A similar pattern of evolution was observed for the phylogeny of UvrC protein (figure 2C ). One of the two copies present in X. axonopodis is close to the uvrC orthologs from other gamma proteobacteria, following a vertical transmission. However, a protein with considerable similarity to the N-terminal of UvrC is found in both Xanthomonas species. These orthologs form an independent branch of the phylogenetic tree of UvrC, close to a heterogeneous group of gram-positive bacteria. The role of this second UvrC homolog of E. coli in DNA repair (named Cho protein, for Uvr C ho molog) has recently been investigated in detail, and was shown to have an endonuclease activity in damaged DNA [ 18 ]. This protein makes an incision only at the 3' side of the lesion, while the well-known UvrC was demonstrated to incise both sides of the lesion in vitro [ 19 ]. Cho may backup UvrC in the repair process of certain kinds of obstructive damage, possibly broadening the repair capacity of the excision pathway in these bacteria [ 20 ]. The origin of such orthologs is not clear, and although other bacteria may present protein domains that have some similarity to Cho endonuclease, known complete Cho homologs are limited to the Azotobacter vinelandii , Escherichia coli , Salmonella typhimurium , Shiguella flexneri , and Xanthomonas . Curiously, in Beta proteobacteria, Ralstonia metallidurans and Chromobacterium violaceum , an endonuclease domain similar to Cho appears as a C-terminal fusion with a putative 3'-exonuclease, corresponding to the epsilon subunit of DNA polymerase III. A similar fusion protein was found in Mycobacterium tuberculosis , and an interesting coordinated action of these two activities (endonuclease and exonuclease) was proposed as a new mechanism of DNA repair [ 20 ]. A former duplication could explain the origin of cho in these bacteria, but, again, one would have to concede extensive gene loss in other species. Once more, horizontal transfer events, involving part of the uvrC gene (the one that encodes the N-terminal) to some gamma proteobacteria, could explain the limited occurrence of cho only in these bacteria. Moreover, some organisms present a duplication of the complete uvrC gene ( Clostridium acetobutylicum and Listeria ). The proteins encoded by these paralogs are closely positioned in the tree, thus indicating a recent origin for them, and, possibly, functional redundancy. The uvr D gene is part of a DNA helicase family, which includes the pcr A and rep genes [ 21 ]. The uvrD gene participates in the removal of damaged DNA strand, after the incision steps of NER or DNA mismatch repair have occurred. The evolution tree of these proteins is presented in figure 2D . Similar to uvrA and uvrC , there are two orthologs for these genes in the X. axonopodis genome. One of the orthologs encoded by the uvrD gene is closer to the gamma proteobacteria, branching with X. fastidiosa , following a typical vertical inheritance, while the second is similar to proteins from other prokaryotes, including Archaea and Bacteria, mainly from the firmicutes and alpha proteobacteria groups. The second ortholog of this gene from Sinorhizobium meliloti is found in plasmid DNA for which an alien origin is suggested, due to its lower GC content [ 22 ]. Additional analysis of the uvrD duplication in the X. axonopodis genome indicates that it is located close to transposon-related genes (Figure 3 ), the G+C content within this region (58.2%) being low when compared to what is found in the rest of the genome (average 64.7%). Moreover, the closest ortholog of this gene is also found in a plasmid of Agrobacterium tumefaciens (figure 2D ). These data are compatible with a recent LGT event for this gene. The absence of uvrD duplication in the genome of X. campestris gives further support to the LGT hypothesis, indicating that it has been recently acquired in the X. axonopodis genome, possibly by means of plasmid transfer and/or transposon insertion. Figure 3 Location vicinity of the uvrD homolog ( uvrD 2) gene in the genome of Xanthomonas axonopodis pv. citri. A bold arrow in the square box represents the ORF of this gene. The dotted arrows on each side represent transposon related proteins and the white ones represent hypothetical proteins. The numbers of Kb indicate the position at the genome. The accession numbers of the proteins corresponding to the genes shown in the figure are: gi| 21244654 (XAC3935), gi| 21244655 (XAC3936), gi| 21244656 (XAC3937), gi| 21244657 (XAC3938), gi| 21244658 (XAC3939), gi| 21244659 (XAC3940), gi| 21244660 (XAC3941), gi| 21244661 (XAC3942), gi| 21244662 (XAC3943), gi| 21244663 (XAC3944) Base excision repair (BER) protects genetic material from a wide range of DNA damaging agents [ 23 ]. The plasticity of this repair pathway is given by the presence of several different glycosylases, lesion recognition proteins that catalyze the first step in BER. The three organisms present similar sets of glycosylases, but X. fastidiosa bears two identical copies of fpg , probably due to its close proximity to the also duplicated rRNA genes [ 8 ]. This duplication may also provide to this bacterium, an enhanced protection against oxidative DNA damage. The presence of duplicated xthA homologs (apurinic/apyrimidinic endonuclease) in both Xanthomonas is another remarkable feature of BER in this group. Phylogenetic trees generated for this protein family show these orthologs located in different branches, indicating that the duplication is not a recent event. However, a miscellaneous branching pattern of the tree obtained for the different bacterial groups, results difficult to track the evolution of these genes (data not shown). The DNA ligases catalyze the joining of breaks in the phosphodiester backbone of the DNA molecule and, thus, play an essential role in several processes of DNA repair, replication and recombination. These enzymes are evolutionary related, although two distinct families of DNA ligases are found: one that is typical for Bacteria, using NAD+ as cofactor, and a second that is typical of Eukaryotes and Archaea, but using ATP as cofactor (reviewed by Wilkinson et al [ 24 ]). As for all bacteria, only single copies of the ligA gene, encoding the NAD-dependent DNA ligase, is found in the Xanthomonas and Xylella genomes. The phylogeny for these proteins is presented in figure 4A , and it clearly follows a vertical descent, with the Xanthomonadales branch close to gamma and beta proteobacteria. However, as described for other bacteria, both Xanthomonas genomes present extra copies of putative ATP-dependent DNA ligases (two in X. axonopodis and three in X. campestris ). The phylogenetic tree of ATP-dependent DNA ligases is shown in figure 4B . There is a clear independent branch, where most of the archaeal ATP-dependent DNA ligases are found, except for the orthologs observed in Mycobacterium tuberculosis and Streptomyces coelicolor . The other bacterial orthologs branch independently, wherein alpha proteobacteria predominate. A curious observation is the high and variable number of ATP DNA-ligases within the genomes of plant symbiontes, especially in the alpha proteobacteria (six in Agrobacterium tumefasciens , nine in Sinorhizobium meliloti and eleven in Mesorhizobium loti ). It is possible that these X. axonopodis genes may have arisen from recent duplications, soon after gene introduction in alpha proteobacteria, probably by means of LGT from Archaea. The fact that these bacteria inhabit a common niche in plants could facilitate mutual gene exchange. However, the function of such ligases in these bacteria is unknown. As the NAD (+)-dependent ligase is present in all bacterial genomes, these Archaea-related ligase orthologs, present in certain bacteria, seem to be redundant, their roles in cell metabolism remaining a puzzle. Since NAD + -dependent DNA ligases are typically eubacterial, and cannot be replaced [ 24 ], the presence of additional ATP-dependent ligases is an unsolved question. Several lines of evidence indicate that the ligation reactions can be processed with different fidelity depending on the enzyme. Bacterial NAD + -dependent DNA ligases appear to perform more accurate ligation reactions, with few mispaired nucleotides being allowed in the DNA extremities [ 25 ]. NAD + -dependent DNA ligase from Thermus species exhibit enhanced mismatched ligations under certain conditions but catalyze reactions with 1–2 orders of magnitude more discriminative towards correct nucleotide matches than the ATP-dependent DNA ligase from T4-phage [ 26 ]. Working with the ATP-dependent DNA ligase from the hyperthermophilic archaeon, Thermococcus kodakaraensis , Nakatani et al [ 27 ] found that the enzyme could seal substrates with mismatched base-pairing at the 5' end of the nick, but did not show activity towards the 3' mismatched substrates. Figure 4 Consensus unrooted trees generated by the Neighbor-Joining distance method for the NAD+ dependent (A) and ATP-dependent DNA ligases (B). The circles highlight the main groups of bacteria. The homologs in Xanthomonadales are in square boxes. The symbol * indicates the beta proteobacteria. Some copies of homologs were excluded from this analysis given the low similarity among the DNA ligase ATP-dependent. Therefore, the presence of ATP-dependent DNA ligases in certain bacteria could be connected to the ligation of DNA breaks under several contexts that would generate genetic variability, with possible evolutionary advantages. In the alpha-proteobacteria group, a non homologous end joining appears to be important for the integration of inserting elements in the genome of host plants, as occurs with Agrobacterium sp T-DNA [ 28 ] or for the amplification of Rhizobium species amplicons present in pNGR234 plasmid [ 29 ]. In Xanthomonas the presence of the ATP-dependent DNA ligase could also be linked to the elevated number of transposable elements [ 9 ]. However, the association of this type of DNA ligase with specific processes that lead to genetic variability, as proposed above, is still under investigation. Some other features of the DNA repair genes in Xanthomonadales are interesting to mention (Table 1 ). The absence of a putative photolyase gene ( phr ) in X. fastidiosa , while present in both Xanthomonas , may be related to its limited habitat within the plant xylem or inside the insect vector [ 8 ]. It is also remarkable that only X. campestris bears the umuC and umuD genes, which encode the DNA polymerase V (UmuD' 2 C), related to translesion synthesis [ 30 ]. In fact, both genes are located at the genome close to bacteriophage related genes [ 9 ], suggesting a recent acquisition by LGT, in a similar manner to X. axonopodis uvrD2 gene. Conclusions Since the genomes of Xanthomonas (5.1 Mbp) are much larger than that of X. fastidiosa (2.7 Mbp), it was not a surprise to find more duplicated DNA repair genes in the former bacteria. Mechanisms for the protection of genetic information may reflect how the organism deals with stress and a hostile environment. Thus, the increased number of DNA repair genes in Xanthomonas may be due to the fact that these bacteria have a more variable habitat when compared to Xylella , which lives most of the time inside its hosts as a parasite. In this work, DNA repair genes, which appeared duplicated in the genomes, were analyzed focusing on their evolution, although it should be pointed out that their functions in vivo remain to be investigated. The duplicated genes found in Xanthomonas have close orthologs in other bacteria. As Xanthomonas are very closely related to Xylella , it is thus possible that, in these cases, duplications arose before the split Xanthomonas - Xylella , and were lost in the latter. For the genes investigated, evolution patterns indicate that duplicated genes may result mainly from relatively ancient origins. Phylogenetic errors of construction, such as long branch attraction effect, cannot be completely excluded, although the presence of close orthologs reinforce the trees generated. Moreover, the duplications are normally positioned near to orthologs also found in the genomes of some distantly related bacteria. A clear exception is the most likely recent duplication found for the lexA paralogs of Xanthomonas , but this seems to be an unusual example. The possibility that gene duplications would have occurred in an early common ancestor, followed by gene loss in most other bacteria, cannot be the only explanation for many of the genes analyzed. Therefore, horizontal gene transfer among different bacteria possibly originated some of these paralogs. A clear example of recent LGT is the uvrD duplication, which is often found associated with DNA mobile elements. An origin from other life kingdoms may also have occurred, as for the ATP dependent DNA ligase, a common ligase in Archaea, which may have been acquired and were established in certain bacterial genomes, including Xanthomonas . The LGT, more than any other genetic process, makes possible faster ecological changes with the immediate incorporation of a gene or group of genes [ 31 ]. Eventually, organisms may acquire pathogenic features by LGT events [ 32 , 33 ]. In fact, a more efficient DNA repair system to protect genetic information would provide pathogenic organisms with tools to respond to stress caused in the host-pathogen interaction [ 10 ]. The new genes acquired by lateral gene exchange are expected to be maintained when they provide a selective advantage to the recipient cell [ 5 ]. For the DNA repair genes investigated in this study, most resulted in redundancy, pointing to function diversification among the orthologs. This seems to be the case of the uvrC homolog ( cho ), which has been found to have a complementary function in E. coli [ 18 - 20 ]. The fact that the closest orthologs, such as ATP dependent DNA ligases, are also observed in other bacteria that interact with plants may indicate both that they may play important roles in this interaction and in their necessity to adapt to the host. A common niche could also favor genetic exchange among these bacteria and would provide for the possibility of their sharing similar molecular mechanisms. In Mycobacterium tuberculosis some DNA repair genes are induced by DNA damage, independently of the RecA protein [ 34 ]. Among them are orthologs of uvr A, uvrD and ligB , which are duplicated in Xanthomonas. This novel mechanism present in M. tuberculosis may also occur in Xanthomonas and support the idea that these duplications are also required protecting the genome against damage. Curiously, the duplicated genes found in Xanthomonas do not replace the orthologs that present vertical inheritance, similar to 16S rRNA. This reinforces the idea that they may complement the known DNA repair mechanisms with other different functions. The search for such novel functions for these genes may not only improve our knowledge on how cells protect their genomes against DNA damage, but also about how DNA repair processes evolve in bacteria. Methods Sequences of DNA repair-related proteins were obtained at the National Center of Biotechnology Information GenBank database (35). The list of organisms, with abbreviations used and proteins analyzed, is shown in Table 2 . An expanded version, containing all accession numbers of the genes employed in phylogenetic analyses, is shown in Table S1 (see additional file 1 ). The analysis of Xanthomonas was performed comparing the two different genomes of the species X. axonopodis and X. campestris. As most of their genes are very similar, only X. axonopodis homologs are shown, differences being described in the text. Protein sequences from complete genomes (Bacteria and Archaea) were aligned using the ClustalX multiple sequence alignment program [ 36 ] with manual adjustment with Genedoc (v2.6.02). Only unambiguously aligned positions (excluding poorly conserved and gap regions) were used in phylogenetic analysis. Phylogenetic trees were generated for each group of protein homolog from sequence alignments using the Phylip program version 3.5 [ 37 ]. Parsimony analysis was conducted using the Protpars program, and distance methods were performed using the Neighbor-Joining method in Phylip, with the distance PAM matrix model [ 38 ]. Bootstrap support (resampled 1,000 times) was calculated, and strict consensus trees constructed. Only bootstrap values greater than 50% are shown. Similar topologies were found for both algorithms employed, and only Neighbor-Joining is displayed. The consensus trees so obtained were viewed through TreeView software [ 39 ]. The same set of prokaryote species was used in all analyses, although few organisms were excluded from some trees, for simplification. The option for non-rooted trees aims at demonstrating only relationship among organisms without, however, linking ancestors and descendants. Table 2 Presence of DNA repair genes investigated in this work. Taxa Genes b Organisms (Abbreviation) a lex A lig rec A uvr A uvr B uvr C uvrD family Aeropyrum pernix (AEROP) Archaea - 1 - - - - - Archaeoglobus fulgidus (ARCFU) Archaea - 2 - - - - - Halobacterium (HALOB) Archaea - 1 - 1 1 1 1 Methanobacterium thermoautotrophicum (METTH) Archaea - 1 - 1 1 1 2 Methanococcus jannaschii (METJA) Archaea - 1 - - - - - Pyrococcus horikoshii (PYHOR) Archaea - 1 - - - - - Sulfolobus solfataricus (SULFO) Archaea - 1 - - - - - Mycobacterium tuberculosis H37 (MYCTU) Actinobacteria 1 4 1 1 1 1 3 Streptomyces coelicolor A3(2) (STRCO) Actinobacteria 1 5 1 4 1 1 4 Chlorobium tepidum TLS (CLORB) Chlorobi - 1 1 2 1 1 1 Bacillus subtilis (BACSU) Firmicutes 1 3 1 1 1 1 2 Clostridium acetobutylicum (CLOST) Firmicutes 1 2 1 2 1 2 2 Listeria innocua (LISTI) Firmicutes 1 1 1 3 1 2 1 Oceanobacillus iheyensis (OCENO) Firmicutes 1 2 1 2 1 1 1 Deinococcus radiodurans (DEIRA) Thermus/ Deinococcus 2 1 1 2 1 1 1 Thermotoga marítima (THEMA) Thermotogae 1 1 1 1 1 1 1 Synechocystis (SYNEC) Cyanobacteria 1 2 1 1 1 1 1 Agrobacterium tumefaciens Cereon (AGROB) Alpha proteobacteria 1 7 1 1 1 1 2 Caulobacter crescentus (CAULO) Alpha proteobacteria 1 2 1 1 1 1 2 Mesorhizobium loti (MESLO) Alpha proteobacteria 1 12 1 1 1 1 2 Sinorhizobium meliloti (RHIME) Alpha proteobacteria 1 10 1 1 1 1 2 Neisseria meningitidis Z2491 (NEIMA) Beta proteobacteria 1 1 1 1 1 1 1 Ralstonia solanacearum (RALST) Beta proteobacteria 1 1 1 2 1 1 2 Buchnera sp (BUCAI) Gamma proteobacteria - 1 - - - - - Escherichia coli. (ECOLI) Gamma proteobacteria 1 1 1 1 1 2 1 Haemophilus influenzae (HAEIN) Gamma proteobacteria 1 1 1 1 1 1 1 Pseudomonas aeruginosa (PSEAE) Gamma proteobacteria 1 2 1 1 1 1 1 Salmonella typhimurium LT2 (SALTY) Gamma proteobacteria 1 1 1 1 1 2 1 Vibrio cholerae (VICHO) Gamma proteobacteria 1 2 1 1 1 1 1 Xanthomonas axonopodis pv citri (XANTH) Gamma proteobacteria 2 3 1 2 1 2 2 Xylella fastidiosa (XYFAS) Gamma proteobacteria 1 1 1 1 1 1 1 a. The organisms are listed in alphabetic order within the taxa. b. The numbers indicate the amount of homologs. Authors' contributions MM-P carried out the phylogenetic analyses and, together with RSG and CFMM, designed and conceived the ideas and the writing of the manuscript. CL gave substantial contribution on the possible involvement of ATP-dependent DNA ligases, when present in bacterial genomes. KML-B and KAA participated in the sequencing and DNA repair genes annotation in Xanthomonas sp. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Accession numbers for the genes indicated in the figures. Contains all accession numbers of the genes used in the phylogenetic analyses. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC518961.xml |
523854 | Randomised controlled trial of gabapentin in Complex Regional Pain Syndrome type 1 [ISRCTN84121379] | Background Complex Regional Pain Syndrome type one (CRPS I) or formerly Reflex Sympathetic Dystrophy (RSD) is a disabling syndrome, in which a painful limb is accompanied by varying symptoms. Neuropathic pain is a prominent feature of CRPS I, and is often refractory to treatment. Since gabapentin is an anticonvulsant with a proven analgesic effect in various neuropathic pain syndromes, we sought to study the efficacy of the anticonvulsant gabapentin as treatment for pain in patients with CRPS I. Methods We did a randomized double blind placebo controlled crossover study with two three-weeks treatment periods with gabapentin and placebo separated by a two-weeks washout period. Patients started at random with gabapentin or placebo, which was administered in identical capsules three times daily. We included 58 patients with CRPS type 1. Results Patients reported significant pain relief in favor of gabapentin in the first period. Therapy effect in the second period was less; finally resulting in no significant effect combining results of both periods. The CRPS patients had sensory deficits at baseline. We found that this sensory deficit was significantly reversed in gabapentin users in comparison to placebo users. Conclusions Gabapentin had a mild effect on pain in CRPS I. It significantly reduced the sensory deficit in the affected limb. A subpopulation of CRPS patients may benefit from gabapentin. | Background Complex Regional Pain Syndrome type one (CRPS I) or formerly Reflex Sympathetic Dystrophy (RSD) is a disabling syndrome, in which a painful limb is accompanied by varying symptoms like edema, hyperhidrosis, hypertrichosis, allodynia, coloring of the skin and, over time, atrophy of the involved tissue. Spontaneous recovery does occur and several therapies have been described, but for some patients CRPS I is a chronic disabling disease[ 1 ]. Neuropathic pain is a prominent feature of CRPS I, occurring in 75% of cases[ 1 ], and many researchers go as far as classifying CRPS I as a neuropathic pain syndrome [ 2 - 6 ]. Gabapentin (Neurontin ® , Pfizer) is an anticonvulsant with a proven analgesic effect in various neuropathic pain syndromes [ 7 - 15 ]. Anecdotal reports suggest that gabapentin may also be an effective analgesic in CRPS patients[ 3 , 8 , 16 - 27 ]. To study this hypothesis, we conducted a double blind, placebo-controlled crossover trial of gabapentin in 58 patients with Complex Regional Pain Syndrome type I. Methods Study population This study complied with the Declaration of Helsinki regarding investigations in humans after approval of the protocol by the Institutional Review Board of the University Hospital Maastricht, the Netherlands. Patients were recruited from a database with patients who, in recent years, had been diagnosed with complex regional pain syndrome type I in our hospital. All patients had been treated in our pain management and research center (dept. of Anesthesiology, University Hospital Maastricht, The Netherlands) and had received sympathetic blocks[ 28 ], mannitol infusions[ 29 , 30 ], and transcutaneous neuromodulation[ 31 ]. All participating patients fulfilled the IASP criteria[ 32 ] for the diagnosis of CRPS type I and were included if they were between 18 – 75 years old and had a score for pain > 3, as rated on a visual analog score (VAS), where 0 is no pain and 10 is the worst pain imaginable. Apart from IASP criteria, all patients had functional loss and pain outside the original traumatized area. Patients were excluded in case of a possibility of health risk or confounding by other diseases of syndromes, like e.g., pregnancy, known kidney and/or severe liver disease, another (2nd) chronic pain syndrome, known nerve damage in the affected area, active infection or diabetes mellitus. Patients were participating in 8-week periods from 19-11-1998 until 2-12-1999. Gabapentin was not registered as a drug in the Netherlands before or during the trial. After the trial the producing pharmaceutical company supplied gabapentin for compassionate use if indicated. Treatment Since our patient population consisted of chronic CRPS I patients with a multiple years' duration of pain complaints refractory to various treatments, we assumed that their pain complaints would be more or less stable. We therefore undertook a double blind, randomized crossover study. Randomization of patients took place after baseline measurements and written informed consent. The assignment scheme was generated by our hospital pharmacy from a table of random numbers. The closed envelopes containing the assignments were prenumbered and kept at the pharmacy. The first treatment group received gabapentin, followed by a washout period and placebo treatment. The second treatment group received placebo treatment, which was followed by a washout period and gabapentin treatment. Each medication period lasted three weeks separated by the two-weeks washout period. Medication was stocked and delivered to the patient at the hospital pharmacy. Both the gabapentin capsules and the identical placebo capsules were delivered immediately before the start of the two medication periods. Left over medication was recollected and counted. The gabapentin (GBP) dose was slowly increased to reduce adverse side effects: 600 mg's GBP AN once a day on day 1–2 600 mg's GBP b.i.d. on day 3–4 600 mg's GBP t.i.d on day 5–21 Placebo dose was identically titrated. Patients were allowed to take their usual analgesics and were told preferably not to change the usual dose. Follow-up measurements The patients were reevaluated at the hospital three weeks (T1), five weeks (T2) and eight weeks (T3) after randomization. During the trial, the patient noted her/his pain rate of the past 24 hr (VAS) and the use of additional analgesics in a diary. During each hospital visit the following assessments were done: 1. Global perceived effect (GPE) on pain indicating: worst ever; much worse; somewhat worse; not improved/not worse; somewhat improved; much improved and best ever. GPE on function was scored on an analogous scale. 2. Neuropathic pain scale (NPS), a 10 item qualitative evaluation of neuropathic pain[ 33 ]. 3. Sensibility through Von Frey monofilament skin application each on 9 areas corresponding to cutaneous nerve branches and dermatomes of either both hands or both feet[ 34 ]. Stimulus placement of filaments was as follows: one second for placement, one second for bending and one second for removal. (handset with resp. 0.0677, 0.4082, 2.052 and 3.632 grams calculated force, North Coast Medical, Inc., San José, USA). 4. Mechanic allodynia test with brush strokes and static pressure with the finger tip[ 35 ], on 9 areas corresponding to cutaneous nerve branches and dermatomes of either both hands or both feet. 5. Edema, discoloration, and changed skin temperature were scored after physical examination on a three point scale indicating no, some or overt presence of each sign, the latter two signs in comparison to the healthy or healthiest limb. Physical examination in CRPS is well comparable to instrumental evaluation of signs with volumeter, infrared thermometer and goniometer[ 36 ]. 6. Impairment and disability tests: Symptom Checklist-90-Revised (SCL- 90 -R)[ 37 ], Brief Pain Inventory[ 38 ], adapted for CRPS to measure the influence of CRPS in general on daily life by 0–10 scale ranging from 0 ('CRPS has not interfered') to 10 ('CRPS completely interfered'), 'range of motion' as a parameter of limb function. Side effects during treatment A blinded independent investigator (STvdB) did sensibility, allodynia and range of motion tests (see above). A physician (AvdV), who examined each patient, did all the other measurements throughout the trial. Patient, investigator and physician were unaware of the treatment received. We tested blinding by questioning physician and participants after each medication period. Statistical analysis The statistical analysis of VAS-scores was determined per patient using estimating medication and period effect through linear regression analyses. Possible relationship of patient characteristics and outcome was tested by Pearson R's test. Mann-Whitney analyses were used for monofilament sensitivity on log-transformed data. Three point scales and seven point scales were dichotomized and like the SCL-90-R, NPS and CRPS-Brief Inventory questionnaires intra-individual paired tested (McNemar, t-test, Bonferroni-Holm corrected for multiple tests). Student t-tests and regression analysis were used to test treatment effect, which is calculated in crossover studies as ((AT1-AT0)-(AT3-AT2))/2+((BT3-BT2))-BT1-BT0)/2, where A represents data of placebo starters and B data of gabapentin starters both before (T0,T2) and after (T1,T3) treatments[ 39 ]. Blinding was tested with Chi-square analyses. Possible related factors to therapy effect were analyzed with forward stepwise logistic regression. Data analyses required complete data sets. Patients who were not completing one or two treatments were excluded for analyses. We tested two-tailed, with α = 0.05 as a level of significance (Excel 2000, SPSS 10.0 for Windows). Results Demographics After randomization 58 patients were enrolled, with a mean age of 44.0 (range 24–75) resulting in 29 patients in the gabapentin-placebo arm and 29 patients in the placebo-gabapentin arm; 49 patients completed the gabapentin period, 50 patients the placebo period, 46 patients completed both periods and were used for further within-patient paired analysis (Fig. 1 ). Twelve patients discontinued treatment of which 6 during the placebo treatment, 2 during washout and 4 during GBP treatment. Three of these four GBP users discontinued due to side effects (Fig. 1 ). Between randomization and start of (placebo) medication one patient withdrew after rereading the information letter about possible side effects. These patients were excluded from analysis, since intra-individual testing was necessary for most of the data-analyses. Patients, who could not be used for analysis, did not differ in their characteristics from the total group nor comparing between the two arms of treatment (Tables 1 and 2 ). When comparing the placebo-GBP arm and GBP-placebo arm on sexes, age and pain level before period 1 or 2, duration of illness, SCL-90-R score, we could not find a difference between the two arms (Tables 1 and 2 ). SCL-90-R score revealed increased values on any subscale comparing to standard norms, indicating personal distress (Table 2 ). We found relative higher scores on somatic and sleeping complaints. The SCL-90-R scores were identical to control chronic pain patients (N = 143), besides higher score on sleeping complaints (T. Forouzanfar, data not published). Trial medication was returned and counted afterwards, but revealed no lack of compliance in any patient. Figure 1 Selection of patients participating in the trial Table 1 Patient characteristics Placebo starter GBP starter Excluded from analysis Placebo starter GBP starter N = 24 N = 22 N = 5 N = 7 Sex (F/M) 21/4 18/4 3/2 6/1 Age in years 42 (± 13) 47 (± 14) 40 (± 11) 43 (± 11) Duration in months 43 (± 36) 44 (± 21) 83 (± 39) 45 (± 30) VAS0 64.2 (± 16) 62.5 (± 18) 62 (± 10) 67 (± 12) VAS2 67 (± 20) 64(± 21) Upper extremity in pain 3R 8L 3RL = 14 8R 7L 4RL = 18 2R 0L 1RL 2R 4L 0RL Lower extremity in pain 2R 7L 4RL = 13 3R 3L 0RL = 6 2R 1L 0RL 1R 1L 1RL R/L/RL represents no. of patients that report pain in resp. right, left or bilateral extremities. A few patients had upper and lower extremity pain. VAS is pain level on visual analogue scale. VAS0 is day 1, VAS2 is day 21 (post wash-out). Data are mean with (SD) Table 2 Basic characteristics of participating patients on neuropathic pain scale (NPS), CRPS brief inventory and SCL-90-R. Data are mean with (± standard deviation). NPS Intensity Sharpn. Hot Aching Cold Sens. Itch. Comfo. Deep p. Superf.P. Mean N = 24 7,3 (± 1,8) 7,3 (± 1,5) 6,0 (± 3,2) 7,0 (± 2,4) 6,0 (± 3,2) 6,6 (± 2,5) 2,8 (± 2,5) 7,8 (± 1,6) 7,6 (± 1,3) 6,0 (± 2,7) Mean N = 22 7,3 (± 1,4) 7,4 (± 1,5) 5,9 (± 3,1) 7,2 (± 1,6) 5,9 (± 3,1) 7,2 (± 2,5) 3,7 (± 3,1) 7,7 (± 1,4) 7,8 (± 1,2) 6,8 (± 2,4) Lost ABN = 5) 7,6 (± 0,5) 8 (± 1,2) 6,2 (± 3,8) 6,8 (± 1,8) 8,2 (± 0,8) 8,4 (± 0,9) 2,8 (± 3,8) 7,3 (± 1,7) 8,2 (± 1,3) 7,4 (± 1,1) Lost N = 7 7,7 (± 1,4) 7 (± 1,3) 5,7 (± 3,3) 8,3 (± 1,0) 8,4 (± 1,7) 8,6 (± 1,1) 2,3 (± 2,9) 8,8 (± 1,0) 8,3 (± 1,1) 8,6 (± 0,8) SCL-90-R anxiety fobic depression somatiz Obs-comp sensitivity hostility insomnia psneu Total AB (n = 24) 15,9 (± 5,8) 10,9 (± 4,0) 31,1 (± 11,4) 26,2 (± 8,3) 19,2 (± 7) 26,8 (± 10,1) 10,2 (± 5,4) 10,1 (± 3,9) 163,0 (± 47,5) Total BA (n = 21) 15,9 (± 5,8) 11,2 (± 6,3) 33,6 (± 14,4) 25 (± 8) 19,7 (± 6,0) 28,1 (± 10,5) 8 (± 1,9) 10,3 (± 3,5) 163,8 (± 44,9) Lost AB (n = 5) 18,4 (± 11,2) 13,4 (± 8,3) 27,8 (± 10) 26,8 (± 7,8) 21 (± 2,9) 26 (± 2) 9,2 (± 2,8) 11,6 (± 2,1) 166,8 (± 41,2) Lost BA (n = 6) 19,7 (± 11,1) 12,2 (± 4,4) 33 (± 17,5) 29,17 (± 11,5) 22,3 (± 9,8) 33,5 (± 18,0) 11,7 (± 7,5) 12,8 (± 2,1) 189,7 (± 80,1) CRPS brief inventory= = = = = = = = = = 1 2 3 4 5 6 7 8 9 10 Mean N = 24 7,4 (± 1,7) 6,5 (± 2,1) 6,3 (± 3,1) 7,6 (± 2,0) 4,2 (± 2,6) 7,0 (± 2,8) 6,4 (± 2,2) 4,3 (± 3,4) 7,2 (± 2,2) 5,6 (± 2,5) Mean N = 22 7,0 (± 2,0) 5,0 (± 3,0) 6,3 (± 3,0) 7,8 (± 2,3) 4,8 (± 2,9) 7,7 (± 2,1) 5,1 (± 3,1) 5,1 (± 2,7) 6,8 (± 2,5) 5,5 (± 2,5) Lost AB n = 5 7,4 (± 1,8) 7,2 (± 1,6) 7,8 (± 0,4) 9 (± 1) 4,6 (± 1,5) 8,2 (± 0,8) 6 (± 2,6) 6,4 (± 2,6) 7,2 (± 3,6) 6,8 (± 1,1) Lost BA n = 7 8,6 (± 1,4) 6 (± 3) 6,4 (± 3,9) 9 (± 1,2) 5 (± 2,9) 8 (± 1,6) 7 (± 2,8) 6,7 (± 1,8) 7,3 (± 2,3) 6,6 (± 2,4) NPS description of pain in terms of 1. intensity 2. sharpness 3. hot 4. aching 5. cold 6. sensitive 7. itching 9. comfortability 10a. intensity deep pain 10b. intensity superficial pain. Item 8 is a nominal scale left out of analysis. Symptom Checklist-90-Revised (SCL-90-R) subscale on anxiety, phobic anxiety, depression, somatization, obsessive compulsive, interpersonal sensitivity, hostility, insomnia and psycho neuroticism. CRPS BI : influence of CRPS on 1. general activity 2. mood 3. mobility 4. normal work 5. personal relationships 6. sleep 7. enjoyment of life 8. self care 9. recreational hobbies 10. social activities. CRPS BI and NPS on a 0–10 scale Blinding After each medication period both patient and physician were asked about their ideas concerning study medication in the past period. The treating physician guessed the used medication correctly more often after both phases than can be explained by coincidence (p = 0.000). Blinding for patients was sufficient in the first phase, but not anymore after the second phase (p = 0.2 versus p = 0.000). Response to treatment Pain Comparing gabapentin and placebo users in terms of pain relief, there was a significant pain relief in favor of gabapentin in the first period. Therapy effect in the second period was less, finally resulting in no significant effect combining results of both periods. There was an unexpected increase of pain level above baseline in the washout period for both the gabapentin starters and placebo starters (Figure 2 ). Figure 2 VAS for pain in both groups at start (T0), three weeks (T1), five weeks (T2), and eight weeks (T3) after randomization. T0-1 is the first treatment period, and T2-3 the second Global perceived pain relief as measured by the seven-point scale showed a significant effect for gabapentin, and also more pronounced in the first period. This measurement also found a significant effect in the second period, with an effect being defined as a patient scoring 'much improvement'. Statistical analysis of global perceived effect showed significant more treatment effect (p = 0.002) with 43 % versus 17 % reported pain relief respectively during gabapentin compared to placebo treatment. 13 % of patients reported aggravation of pain during gabapentin vs. 9 % during placebo treatment (Figure 3 and table 3 ). Stepwise forward logistic regression analysis of baseline value of pain level, age, sex, duration of illness, location of illness, mono- or bilateral CRPS, trial arm and all items of CRPS-BI, NPS and SCL-90-R was performed. Only the level of self care was related to perceived pain relief during GBP. The neuropathic pain scale, indicating different aspect of pain, improved significantly in terms of less hot and more comfortable, but not when corrected for multiple tests (Bonferroni-Holm correction). We found that during gabapentin use, patients reported equal use of co-medication comparing to baseline assessment and placebo-use with a non-significant trend towards less medication during GBP use. Figure 3 Global perceived pain relief (on a seven-point scale) as reported by patients. GBP-1 and -2 denote patients receiving GBP in the first and second period; placebo-1 and -2 are analogously denoted. Table 3 Patients (%) with global perceived effect on pain in the four arms of treatment and totals for the two treatments. Treatment period GBP-1= Placebo-1= Wash-out= GBP-2= Placebo-2= % some improvement (n) 45% (10) 13% (3) 1 8% (2) 13% (3) % much improvement (n) 14% (3) 5% (1) 0 21% (5) 4% (1) % total (n/N) 59% (13/22) a 17% (4/24) 1 29% (7/24) 18% (4/22) = Total = GBP = = Total = placebo = = = % some improvement 26% (12/46) 13% (6/46) % much improvement 17% (8/46)β 4% (2/46) % total (n/N) 43% (20/46) a 17% (8/46) worsened 13% (6/46) 9% (4/46) GBP-1 is gabapentin treatment before wash-out. GBP-2 is gabapentin treatment after wash-out. 'α' is significant, P < 0.005, 'β' is P < 0.10 McNemar two sided tested gabapentin versus placebo. Sensory tests Each participant was tested throughout the study on response to mechanical stimuli with von Frey filaments. The CRPS patients had sensory deficits at baseline. Application of smaller filaments was not felt in multiple skin areas. We found, with Mann-Whitney analyses, that this sensory deficit was significantly reversed in gabapentin users in comparison to placebo users (p = 0.027). This difference was found in patients with upper and lower extremity CRPS, but was still significant in the subgroup of lower extremity CRPS (p = 0.011) as seen in table 4 . Table 4 Mann-Whitney scores of monofilament application in CRPS patients testing cutaneous sensibility thresholds Mean ranking Hand Feet Total Placebo 12.0 (N = 12) 5.5 (N = 10) 16.8 (N = 22) Gabapentin 15.6 (N = 15) 12.0*(N = 3) 25.0*(N = 18) Significant different values (p < 0.05) are marked with*. Mechanical allodynia to static and dynamic stimuli (soft touch and brush) was measured by a mean of 11-point scales (range 0–10) of 9 areas of the hand/feet corresponding to cutaneous nerve branches. We found no effect of gabapentin on allodynia in comparison to placebo. Other symptoms No difference was found on the parameters edema, discoloration, range of motion of wrist/ankle and fingers/toes between placebo and GBP. 10 patients out of 45 improved in relative skin temperature during placebo use compared to 18 patients out of 45 in gabapentin, which is two sided tested not significantly different (McNemar analysis, p = 0.096). Limb dysfunction and quality of life The reported function improvement was, with 10 positive responders during GBP versus 7 positive responders during placebo, not significantly different (N = 46) between the two treatments. The SCL-90 showed no significantly better scores during gabapentin treatment. CRPS-BI showed improvement of sleep between placebo treatment and gabapentin treatment., but this effect disappeared after Bonferroni-Holm correction. Adverse effects Dizziness, somnolence and lethargy were significantly more often reported during gabapentin use than during placebo. Before washout 95 % of patients (n = 21) reported side effects during gabapentin use versus 58 % in placebo treatment (n = 14). After washout this was respectively 63% (n = 15) in GBP and 32% (n = 7) in placebo use. For more details on side effects see table 6. Since a high incidence of side effects can produce a stronger placebo effect, we analyzed the possible correlation between side effects and pain relief. There was a small relation between perceived side effects and pain relief in placebo users in period 2 (p = 0.04, Pearson's R value is 0.4), but, whether in period 1 or period 2, no relationship was found during the use of gabapentin (p = 0.2 in period 1, P = 0.4 in period 2). Discussion To evaluate gabapentin treatment as a treatment for pain in CRPS, we conducted a placebo-controlled crossover study. We conclude from our trial that overall, gabapentin did not relieve pain as compared to placebo on pain visual analogue scores, our primary outcome measure. Gabapentin relieved pain in a subgroup of patients and gave a significant global perceived pain relief. The effect was mild and there was no patient in which gabapentin completely eliminated pain. Moreover, the frequency of side effects as dizziness, somnolence and lethargy was higher during gabapentin treatment than with placebo. These side effects probably also account for the relative lack of blinding we observed in our study. This does not mean that the study was biased: our population was chronic CRPS patients who all had undergone numerous unsuccessful treatments, and clearly wanted the drug to work. Any possible bias would therefore have been positive towards gabapentin. Although we did not find a significant pain reducing effect when analyzing the complete trial, we did find a significant effect in the first half of the trial. In fact, the difference in outcome between the two trial halves is striking. There was a reverse carry-over effect resulting in increasing pain above baseline after the washout period for both gabapentin and placebo starters. The increase of pain intensity above baseline level in the second period (before the start of placebo treatment) cannot be explained pharmacologically. Gabapentin has no known biological dependency or tolerance mechanism. It can be a period effect, although this would more likely result in a regression to the middle instead of increasing pain. Perhaps this is a reversed placebo effect in which the expectation and/or the actual perception of not receiving gabapentin anymore might increase pain intensity. Kemler and de Vet found that treatment allocation in a trial could influence pain intensity in CRPS[ 40 ]. The decreasing therapy effect after washout is found in other crossover pain trials[ 41 ]. Expectation and attention have been shown to be powerful influences on pain pathways in the brain[ 42 ], and perhaps a crossover design is not suited to study treatments in chronic pain patients. We found a decreased sensory deficit in gabapentin users compared to placebo users. We did not expect this, but found in the literature several cases in which gabapentin decreased the area of hypesthesia in neuropathic pain syndromes[ 43 ]. This has, to our knowledge, never been described for any other medication. Numbness or mechanical hypesthesia is a frequently found complaint for approximately 75 % of CRPS patients, which can improve in time spontaneously and after placebo treatment[ 44 ]. It is possible that the somatosensory findings and pain outside the original area of trauma can be attributed to referred pain mechanisms. Gabapentin has been reported to alleviate referred pain[ 45 ]. Since many CRPS patients have mechanical hypesthesia, we hypothesize that gabapentin influences some common neural pathway for 'referred' sensations, whether mechanical sensation or pain. Conclusions Gabapentin had a mild effect on pain in patients CRPS I. It significantly reduced the sensory deficit in the affected limb. A subpopulation of CRPS patients may benefit from gabapentin, but then for each individual patient the benefit has to be weighed against the frequently occurring side effects. Competing interests Parke-Davis (now a Warner-Lambert/Pfizer division) supplied gabapentin and matching placebo capsules for this trial. Drs. Van de Vusse and Weber have received financial support from Parke-Davis to attend one congress. Parke-Davis has had no role in the writing of this manuscript Authors' contributions AvdV initiated the trial and wrote, with WEJW and AHFK, the protocol. The study and its data management was done by AvdV and SS-vdB. AHFK did the statistical analyses. AvdV wrote the first draft of the manuscript, which was finished in its final form by WEJW. Table 5 Side effects as mentioned after treatment Adverse effect Gabapentin (N = 54) n (%) Placebo (N = 51) n(%) Significance Dizziness 20 (37.3) 2 (3.9) P = 0.0000 Somnolence 15 (27.8) 3 (5.9) P = 0.003 Lethargy 11 (20.4) 1 (2.0) P = 0.003 Nausea 10 (18.5) 5 (9.8) n.s. Headache 8 (14.8) 3 (5.9) n.s. Stomach problems 4 (7.4) 3 (5.9) n.s. 'drunken' 4 (7.4) 0 (0) n.s. Disturbed gait 4 (7.4) 0 (0) n.s. Water retention 1 (1.9) 3 (5.9) n.s. Data on all patients who started treatment and returned for assessment after 3 weeks, with or without completing 3 weeks of treatment. n.s. is 'not significant' Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC523854.xml |
544944 | Conflict and HIV: A framework for risk assessment to prevent HIV in conflict-affected settings in Africa | In sub-Saharan Africa, HIV/AIDS and violent conflict interact to shape population health and development in dramatic ways. HIV/AIDS can create conditions conducive to conflict. Conflict can affect the epidemiology of HIV/AIDS. Conflict is generally understood to accelerate HIV transmission, but this view is simplistic and disregards complex interrelationships between factors that can inhibit and accelerate the spread of HIV in conflict and post conflict settings, respectively. This paper provides a framework for understanding these factors and discusses their implications for policy formulation and program planning in conflict-affected settings. | Introduction Of the obstacles to development in the sub-Saharan African (SSA) region, perhaps none has had a more profound impact than the dual burdens of HIV/AIDS and conflict. During the past quarter century, no region of the world has been more acutely affected by large-scale violent conflict than SSA. Almost all SSA countries have directly experienced, or border a country that has directly experienced, violent conflict. The number of states engaged in significant violent conflicts doubled between 1989 and 2000, from 11 to 22 [ 1 , 2 ]. A "conflict belt" stretches from Angola to the Horn of Africa, while peace in western Africa remains elusive. The same quarter century has seen the development of an even more pervasive crisis – the HIV/AIDS pandemic. SSA continues to account for the large majority (66%) of the world's HIV/AIDS cases [ 3 ], even though its population comprises only 10% of the world's total population. There is great diversity across Africa in the levels and trends of HIV infection. While stabilization of the epidemic appears to have begun in several countries, population prevalence rates across most of the continent continue to increase, including among rural populations and sociodemographic groups not previously considered at elevated risk. Although much has been written about HIV and conflict individually, surprisingly little has been written about the dynamics of the relationship between the two crises. In fact, an extensive keyword search of the internet and peer-reviewed journal databases turned up fewer than 100 references to the intersection of HIV and conflict. Virtually all studies are descriptive and only one utilized hypothesis-testing analytical strategies [ 4 ]. Although constraints on conducting such research are considerable, research on the interface between the two crises is of critical importance. A clearer understanding of the dynamics of the interface between conflict and HIV is crucial for the development of effective and efficient strategies to reduce population risk. Some literature on conflict-affected countries in SSA underscores mechanisms by which HIV/AIDS and violent conflict may exhibit bi-directional causal associations on the population level. HIV/AIDS has been recognized to play a potential role in creating conditions conducive to violent conflict on the continent, although there is as yet no good empirical evidence to that effect. A policy forum held at the United States Institute for Peace [ 2 ] concluded that the pandemic will emerge as a deeply destabilizing force across the social, political, and economic landscapes of Africa. For example, large numbers of AIDS orphans and vulnerable children strain the social support networks in many southern African countries [ 5 , 6 ]. The psychological trauma and the lack of parental affection and supervision experienced by AIDS orphans put them at risk of involvement with criminal or antisocial activities (e.g. as child soldiers), or activities that serve to further their risk of contracting and further propagating the disease (e.g. as child prostitutes). The extent of the risks faced by AIDS orphans – e.g. risks for anti-social and criminal behavior later in life – needs to be sufficiently researched. By causing elevated AIDS-related mortality among the 15–45 year-old age group, the illness degrades human capital, undermines household capacity and stability, reduces economic productivity, and robs social and political institutions of intellectual resources [ 7 ]. On the other hand, violent conflict clearly influences the epidemiology of HIV. To date, the literature emphasizes conflict as a risk factor for HIV transmission. Conflict destroys social and physical infrastructure, resulting in untreated sexually transmitted infections (STIs), poor health and malnutrition and, as a consequence, increased risk of transmission in the event of viral exposure. The migration and poverty created or exacerbated by conflict may result in increased exposure opportunity through: (1) increased prevalence of casual or commercial sexual activity; (2) increased interactions among civilians and combatants/military personnel, known for their high risk behaviors; (3) the development of cultures of violence that promote sexual violence and predation; (4) mass migration, which increases sexual mixing among populations; and (5) the destruction of public health education mechanisms (e.g. mass media, health facilities, and formal education), which negatively affects public health-related knowledge, attitudes, and practices [ 8 , 9 ]. However, the epidemiologic data despite their limitations 2 , suggest that the relationship between conflict and HIV levels may be more complex than this general picture of joint potentiation implies. With few exceptions, countries that have experienced widespread violent conflict have apparently lower levels of HIV infection compared to those that have experienced relative peace (compare figures 3c and 3d ). While many factors operate during conflict to increase vulnerability of affected populations to HIV, exposure opportunities at an aggregate level may actually be lower, therefore decreasing HIV risk. Alternatively, when conflict subsides, exposure opportunity may increase, leading to the potentially explosive spread of HIV. At the end of the Angola conflict in 2002, the country HIV prevalence was relatively lower than the rates in other Southern African countries, which suggests that conflict may have slowed HIV spread in this case [ 10 ]. Figure 3 Maps of Africa The present paper evolved out of the observation that available evidence for conflict-affected countries in SSA suggests a complex set of possible net effects of conflict on the HIV epidemic, with multiple and quite variable outcomes. The implications of the analysis and findings have great significance for developing policies and programs to confront HIV in the context of conflict. These are discussed along with recommendations for improved policies and programs to address this important constraint to African health development. A Framework for Understanding the Interrelationships between Conflict and HIV Our framework develops two important aspects of the problem of HIV and conflict in SSA. These are: • the importance of ecological in addition to individual risk factor explanatory models, and • the importance of comparing the influences of conflict both during and post conflict. We also develop the notion that conflict is a complex social phenomenon and that its effects are highly contextualized. To articulate a framework for understanding the interface between the two crises, the concepts of vulnerability , hazard exposure opportunity and risk are useful. These are borrowed from the disaster literature [ 11 ] but are germane for understanding the evolution of HIV/AIDS as a crisis. Vulnerability is the ability of a population to withstand hazards or shocks to the system when they are present. Classical vulnerability factors include poverty, low education/knowledge, poor social infrastructure and attitudinal factors. Additional factors specific to conflict and HIV include levels of economically-motivated sex, levels and types of civil-military interactions, migration patterns, sex-related knowledge and attitudes, and population health status (particularly STIs and nutrition). Vulnerable groups in conflict settings may include child-headed households, child soldiers, unaccompanied children, women, demobilized soldiers, and repatriating refugees. Vulnerability means that, when exposed to a hazard, an individual or group is more likely to experience adverse effects (risk). Hazards or shocks to human communities such as conflict affect the HIV exposure opportunity of members of these affected communities. HIV exposure opportunity can be mediated by war or other ways in which these communities interact with other communities (regional human ecology), which ultimately affects disassortive mixing (i.e. mixing of population groups of differing levels of HIV prevalence). In Southern Africa, the regional ecology is one that favors extraordinarily high HIV risk through, for example, high population density, good physical infrastructure, economically-motivated mobility, high poverty levels, and large wealth disparities within and between countries. By lowering exposure opportunity, war may lead to isolation from the general regional ecology and, therefore, to lower HIV risk at the population level. Alternatively, war leads to a changed and often more intense mixing of mobile military populations and civilians, which can increase HIV risk through disassortive mixing. Figure 1 illustrates how conflict shocks may affect vulnerability and exposure opportunity to affect population HIV risk. Conflict shocks can weaken a community's ability to avoid HIV exposure/infection (vulnerability), or it can influence exposure opportunity itself. Vulnerability and exposure are the basic determinants of population-level HIV risk. Underlying determinants here include violent conflict and the regional ecology of HIV, which exhibit measurable effects on both vulnerability and exposure opportunity (and interact with each other). Finally, HIV infection goes on to influence the progression of conflict and the social ecology of HIV in a feedback loop. The model has utility for structured inquiry into the effects of conflict on HIV. It draws attention to mechanisms by which vulnerability and risk of exposure, and therefore risk of transmission, may be increased or decreased during conflict. The relative importance of each of the components, and therefore the ultimate effect of conflict (i.e. augmenting or reducing risk), will be highly context specific. Figure 1 Conceptual Framework of Principal Causes of HIV Risk in Conflict-Affected Populations Figure 2 illustrates that there is an important time dimension to consider as well. The most basic distinction of interest is that of conflict and post conflict, although these are rarely clear-cut distinctions. What is important to note here is that vulnerability increases during conflict and rarely decreases rapidly after conflict subsides because of the profound societal changes that generally occur during conflict. On the other hand, opportunity for exposure to HIV may change dramatically post conflict due to decreased population isolation and rapid improvement in freedom of movement. These changes will likely be most acute in countries with high economic potential, such as Angola, Côte d'Ivoire and the Democratic Republic of Congo. The juxtaposition of high vulnerability and increased exposure opportunities post-conflict can lead to explosive growth in the epidemic. This already has occurred to some extent in Mozambique [ 12 ]. Figure 2 HIV Vulnerability and Exposure Opportunity in Relation to Conflict Phase This finding is critical in that it explains in part why, in some chronic conflict settings, apathy has developed towards HIV because seroprevalence levels may be low. However, the potential for rapid progression of the infection post conflict due to high vulnerability argues for a much more aggressive and deliberate approach to HIV in post-conflict settings. Conflict as an Analytical Factor Considerable research has been conducted to date to construct comprehensive typologies of conflict. Several well-established research initiatives, such as the Correlates of War Project [ 13 ], have developed typologies of conflict for application to conflict early warning and prevention efforts. These typologies categorize conflicts based upon variables associated with either the determinants of conflict or the manifestations of conflict. Typologies that focus on the determinants of conflict categorize conflicts primarily based upon characteristics of the political, legal, economic, social, or cultural environments that are associated with greater risk of conflict. Examples of such factors include [ 14 ]: • political/legal status and structure of warring parties (e.g. state, non-state, internal, or external; military capabilities and levels of discipline of combatants); • economic context (e.g. economic disparities, distribution of poverty, and access to critical resources); • nature of political system (e.g. democratic or authoritarian); • self-identified characteristics distinguishing warring parties (e.g. ethnic, religious, class, regional, or social identity); • characteristics of physical environment as it affects the conflict (e.g. mountainous or flat); and • purpose of conflict (e.g. motives of combatants, points of contention, and ideological differences). In contrast, some approaches focus on the manifestations of conflict, defining categories in terms of measurable aspects of the conflict and its effects on populations. Examples include: • geographic scale of conflict (e.g. sub national, national, or international; inter-state, extra-state, or intra-state); • time-scale of conflict (e.g. duration and onset); • types of military technology, tactics, and funding methods employed; • involvement of civilians; • levels of mortality (e.g. battle-related and indirect); • levels of other negative health outcomes (e.g. morbidity and malnutrition); and • levels of displacement (e.g. internal or cross-border). A determinant-based typology has more direct application to the critical areas of conflict early warning and prevention, despite the analytical complexities derived from the high degree of interdependence (i.e. interaction) among these determinants [ 15 ]. However, most existing classification schemes fail to incorporate an emphasis on the public health impacts of conflicts other than battle-related fatalities. For example, other categories of war-related mortality, such as civilian deaths, deaths following famine or disease and deaths that are allowed to occur for political reasons, are often omitted. Similarly, morbidity, malnutrition and displacement among civilians, highly characteristic of post-Cold War conflicts in SSA, have been largely overlooked [ 14 ]. These population-level results of conflict appear, in many cases, to help explain the links between conflict and HIV/AIDS progression. Therefore, the present framework draws from both types of typologies for maximum utility regarding the problem of HIV and conflict, recognizing the complex nature of conflict as an epidemiologic study factor. Aspects of Violent Conflict that Directly Affect the HIV Epidemic Despite large cross-cultural and historical variation in the determinants and manifestations of conflict, and variation in the systems that have been developed to analyze conflict, a model can be developed specific to inquiry about the public health impacts of conflict on HIV epidemiology. Conflict can be analyzed in terms of the following dimensions, all of which may help to shape its influence on HIV risk. Time-scale of conflict Both the duration of the conflict and the point of conflict onset relative to the progression of the epidemic should be considered. Chronic conflict, for example, may engender profound societal changes that are manifested in immediate increases in population risk of HIV. For example, widespread impoverishment resulting from war may fuel high levels of commercial sex as a survival strategy. Similarly, displaced populations are believed to be at greater risk of sexual violence or sexual activity as a way to negotiate access to key resources for survival. A recent finding regarding the behavior of humanitarian aid workers in western Africa tragically supports this assertion [ 16 ]. Longer-duration conflicts generally lead to greater cumulative effects of conflict on social infrastructure. Populations may be isolated from modern communications for a long period of time, resulting in much greater naïveté regarding the epidemiology and prevention of the disease. In low-prevalence conflict settings this may not impact transmission significantly; post conflict, however, this may exacerbate vulnerability. Alternatively, chronic conflict may result in lower exposure opportunities following reduced social mixing due to isolation and limited population mobility. During the war in Angola, for example, mobility was limited and most of the population was concentrated in small "islands of security" around provincial capitals. HIV seroprevalence remained low as a result. Equally, the point of conflict onset relative to the progression of the epidemic may determine the degree to which conflict may result in sustained low seroprevalence levels for the duration of the war. In Rwanda, for example, sentinel surveys among pregnant women and STI patients demonstrated prevalence rates exceeding 30% before the 1994 genocide [ 17 ]. Because HIV was already so prevalent, community isolation did not likely curtail the local spread of the disease. In contrast, prevalence rates in Mozambique in sentinel surveys of high-risk populations appear to have remained relatively low until the war ended, at which point the resumption of normal patterns of social mixing occurred alongside a marked rise in prevalence rates [ 17 ]. Thus, when initial low prevalence rates are combined with isolation for long periods of time, HIV progression at the population level may be considerably attenuated. Characteristics and involvement of parties involved in conflict The political/legal status , differential HIV prevalence rates , relative size , motives , and tactics characterizing combatants and affected civilian populations may all shape the progression of the epidemic. In terms of political/legal status, combatant groups may comprise government military forces, paramilitary forces, organized rebel groups, or highly fragmented rebel groups. Available data suggest but do not conclusively confirm the oft cited axiom that significant differentials in seroprevalence can exist between government military and civilian populations in Africa [ 18 ]. More recent findings suggest that this too is contextualized [ 19 ]. Almost no data is available regarding other types of armed groups. Modern conflict in SSA often inflicts a high degree of sexual violence upon civilian populations that, if civil-military seroprevalence differentials exist, will result in increased mixing and HIV spread. Additionally, commercial sexual activity and other commercial activities may follow soldiers, again facilitating HIV spread. The size and motives/tactics of armed groups may determine in part the types of interactions (and violence of those interactions) with the civilian population. Geographic scale and dynamics of conflict The scale and geographic focus of the conflict highlight geographic areas that may be differentially affected by the conflict or the epidemic. In terms of scale, conflicts may take place on a regional, national, or sub-national level. Most post-Cold War conflicts in SSA involve civil conflict; many conflicts have international and regional dimensions. The war that started in the Democratic Republic of Congo (DRC) in 1998 drew armies from at least seven African countries experiencing wide variations in their levels of HIV prevalence. The concept of the geographic focus of the conflict highlights the fact that the effects of war are unlikely to be homogeneous in any situation. This gives rise to distinct local ecologies that may experience lower HIV vulnerability and exposure to HIV hazards through the factors listed above, particularly isolation and population mixing associated with military and forced migration. For example, the Ethiopian conflict resulted in a large concentration of military along the Ethiopian-Eritrean border and accompanying civilian commercial activity. In some cases, such as Mozambique, conflicts have resulted in intensified and highly localized trading corridors between outside countries of higher seroprevalence and lower prevalence areas. Specific Mechanisms through which Conflict Influences HIV Risk Factors that May Decrease Risk Factors may decrease risk by decreasing vulnerability, or more commonly, by decreasing exposure opportunity. The following factors are postulated to accompany conflict in post-Cold War SSA and may explain how conflict may actually limit the spread of the epidemic during the period of conflict. Factor 1: Increased isolation of communities Conflict isolates communities by destroying transport systems, making travel unsafe, and disrupting the market-based activities that encourage economic migration. Conflict may freeze normal cross-border migration, as in the case of Ethiopia and Eritrea. On the sub-national level, civil conflict may isolate rural communities controlled by armed factions, as in Angola, or limit population movement because of the loss of transport infrastructure, as in the Democratic Republic of Congo. Where conflict is chronic, the effect of limiting population movement and therefore population mixing could be a very significant contributor to the relatively lower levels of HIV found among affected populations. Factor 2: Increased death rates among high risk groups Another aspect of conflict that may decrease population HIV risk is differential mortality among high-risk groups. It is well established that mortality among adult males is elevated in conflict-affected settings. Post-genocide Rwanda has shown a demographic shift such that among adults between the ages of 15 and 54 years, women far outnumber men [ 20 ]. In addition, poor nutrition and the lack of access to health services probably decreases the survival time of HIV-infected individuals. A recent study in Guinea Bissau demonstrated a strong differential in mortality between war-affected cohorts of a tuberculosis treatment program according to HIV status [ 21 ]. Factor 3: Decreased casual sex associated with trauma and depression Available evidence points to the unexplored possibility that conflict may result in decreased sexual activity, most commonly as a result of psychological sequelae of trauma such as post-traumatic stress disorder (PTSD). It has been shown that absent or low libido in those with post-traumatic stress disorder can be as high as 69% [ 22 ]. In those patients with general depression, reduced libido is present in up to three quarters of patients [ 23 ]. An elevated level of depression in conflict-affected settings has been documented [ 24 ]. Research in Rwanda in the late 1990s investigated the prevalence of clinical depression (as per the Diagnostic and Statistical Manual for Mental Disorders, DSM-IV criteria, measured using an adapted version of the Hopkins Symptom Checklist); the prevalence of a local severe depression-like syndrome of "mental trauma" (guhahamuka) ; and the prevalence of a local, less acute syndrome of "severe grief" (agahinda gakabije) . In the commune that experienced significantly lower levels of violence during the genocide (Butamwa), only 5.6% of adults had depression, and 31.9% of adults had agahinda gakabije . In the commune that experienced widespread violent conflict during the genocide, almost one-fifth (17.9%) of adults had depression and almost half (41.8%) of adults had agahinda gakabije [ 24 ]. The results, though inconclusive, suggest that depression-like syndromes may be highly prevalent in some settings. Factor 4: Disruption of sexual networks following conscription or displacement Conflict may lead to the disruption of sexual networks associated with forced migration and/or the conscription of husbands and sexual partners. Females may have fewer opportunities for casual sex, though this factor remains unexplored in the research literature. This may hold most true in displaced communities, which are often comprised disproportionately of women and children. Factors that May Increase Risk Accelerating factors in this model constitute factors that tend to enhance the spread of HIV by worsening dimensions of population vulnerability or increasing HIV exposure opportunity. Factor 1: Increased interaction among military and civilians Conflict has been demonstrated to result in the increased sexual mixing of military with civilian groups, especially in areas of high military concentration for extended periods of time [ 25 ]. In post-conflict settings, demobilization of combatants may also result in disassortive mixing. It has been documented that in the African context, some military groups have higher HIV risk than the general population [ 26 ], although this has not been demonstrated conclusively in all contexts. Although military seroprevalence data are not typically available in the public domain, a recent analysis suggests that seroprevalence levels are commonly at least 5% higher among military than their civilian counterparts in Africa [ 18 ]. It is important to note, however, that military infection levels vary greatly between and within military organizations. In Cambodia, for example, household surveys estimate prevalence rates of police and military personnel at 8%, while the rate among the civilian population is 2.7% [ 27 , 12 ]. Military recruits in Myanmar, however, appear to have prevalence rates similar to that of the general public [ 27 ]. In a large HIV prevalence study in Ethiopia, prevalence among urban military was 7.2%, while among urban civilians the level was 6.4%. Rural military registered a lower rate than the general rural population [ 28 ]. Factor 2: Increased levels of commercial or casual sex Impoverishment coupled with discrimination against women and the erosion of traditional behavioral norms may give rise to high levels of sex driven by economic motives in conflict and transitional societies. This again is frequently cited as an important consequence of war, but is difficult to quantify. What is clear is that African countries that have experienced war have lasting socioeconomic effects. For example, Mozambique and Angola are among the three lowest ranking countries on all components of the Human Development Index among Southern African countries [ 29 ]. Infant mortality in these two countries rank among the highest in the world. Among refugee and displaced populations poverty results from the severing of livelihood strategies and catastrophic asset loss. Semi-permanent refugee populations that relocate near population centers may be forced to participate in commercial sex in order to ensure household livelihoods or, in extreme cases (e.g. poor female-headed households), to exchange sex for food and other assets [ 30 - 32 ]. In addition, high levels of female illiteracy affect the ability of women to seek alternative forms of livelihood. In northern Uganda, many separated and widowed female Sudanese refugees began brewing and selling beer to sustain themselves and their children. This unfortunately led to an "increase in unprotected sex with multiple partners while under the influence of alcohol" [ 33 ]. These vulnerabilities characterize populations in both conflict and post-conflict phases. Factor 3: Decreased availability of reproductive health and other health services Destruction of the health sector is a common feature of conflicts and its reconstruction has not been rapid in most SSA countries. Massive loss of health infrastructure – both personnel and physical infrastructure – is common in conflict-affected countries of Africa. Mozambique lost the majority of its clinics during the civil war [ 34 ]. Rwanda was estimated to have lost more than 80% of its health personnel through death or flight during the genocide [ 35 ]. Access and utilization failures result in lack of treatment for STIs and, subsequently, poor health, which may result in greater population-level HIV risk. In Guinea-Bissau, for example, interruption of TB treatment for HIV patients due to the civil conflict was directly responsible for the significantly higher mortality rate experienced by HIV patients. Those who had completed TB treatment before the outbreak of the war, showed no differential increase in mortality [ 21 ]. Lack of infrastructure and changing utilization patterns also handicap surveillance efforts [ 9 ]. This may delay recognition of HIV, as well as other diseases, as a public health problem. Factor 4: Decreased utilization of reproductive health and other health services Not only is infrastructure lost, but utilization patterns also are affected by violent conflict. People may not be able to get to health care services because of ambient danger. They may also be reluctant to use services because they distrust providers. This may have been a factor in Rwanda, for example, where providers were particularly implicated in genocide activities during the war [ 36 ]. Another deterrent to use is the tendency for conflict-affected populations to become more reliant on self-care, traditional health systems, or emergent predatory health providers, as has been documented in several instances [ 37 ]. Factor 5: Increased levels of malnutrition While quality evidence-based research demonstrating direct links between malnutrition and increased susceptibility to HIV seroconversion is scarce, the importance nutrition plays in limiting infection and regulating the immune system is well documented. Malnutrition and micronutrient deficiencies impair immune function, thereby increasing vulnerability to infections in general. Vitamin A, for example, has been shown to play an important role in immune function, including the maintenance of mucosal epithelia, the growth of immunogenic cells and antibody response [ 38 ]. Supplementation with vitamin A increases levels of natural killer cells in HIV infected children [ 39 ] and decreases morbidity due to other diseases such as measles and malaria [ 40 , 41 ]. Similarly, vitamin E is associated with neutrophil phagocytosis and lymphocyte proliferation [ 42 ]. Such deficiencies are associated with accelerated disease progression in HIV patients [ 43 ], greater risk of vertical transmission of HIV [ 44 , 38 ] and increased HIV loads [ 45 , 46 ]. It should be noted, however, that other studies have concluded that vitamin A deficiency is not associated with increased vertical transmission [ 48 - 52 ]. In addition, malnutrition levels are generally a good indicator of health status and social equity. High levels of micronutrient deficiency and general malnutrition are widely documented in conflict-affected populations, resulting in decreased resilience to infections. It is known that poor nutritional status is associated with vulnerability to progression from tuberculosis infection to disease. The immunosuppression associated with HIV infection is a major risk factor for the progression of latent tuberculosis infection to active disease and death [ 53 ]. The increased level of HIV in a community will certainly contribute to a high dual HIV-TB burden. Factor 6: Decreased use of means to prevent HIV transmission The isolation and poverty caused by war often results in decreased knowledge of, and access to, means to prevent HIV transmission. Population probability surveys available through the Demographic and Health Surveys, UNICEF's Multiple Indicator Surveys, and specialized HIV behavioral surveys show that knowledge levels and condom use are quite low in conflict-affected countries [ 9 ] and that they contrast with regional and sub-regional norms, especially in cases of protracted and widespread conflict. Depressed knowledge levels reflect the failure of mass media campaigns, formal education, and literacy and clinic-based education activities during and following conflict. As illustrated in Table 2 , general awareness of HIV as a health threat often significantly surpasses in prevalence the awareness of specific measures that may be taken to prevent transmission, such as the utilization of condoms and the avoidance of multiple sexual partners. Table 2 Knowledge, Attitudes and Practices Related to HIV/AIDS, Selected Countries in SSA Country % heard of HIV % know no ways to prevent % know condom use Mozambique (DHS, 1997) 82.2 65.8 15.4 Eritrea (DHS, 1995) 80.6 24.2 34.6 Ethiopia (DHS, 2000) 84.7 31.5 33.5 Sierra Leone (MICS, 2000) 54.0 -- 27.0 Somalia (MICS, 2000) 36.6 88.3 2.8 Sources: Marco-International, Demographic and Health Surveys (DHS) . UNICEF, Multiple Indicator Cluster Survey (MICS) . Additionally, knowledge levels tend to exhibit marked intra-national variability, particularly among socially and economically marginalized groups. This variability may be enhanced in conflict-affected countries through regional isolation [ 54 ]. The case of Rwanda suggests that conflict may affect contraceptive use and desired family size. Popular wisdom suggests that post-conflict populations may want to repopulate and, to an extent, that tendency is supported by examination of Demographic and Health Survey (DHS) data collected before and after the genocide of 1994. In 1992 and 2000, the DHS documented rates of awareness of HIV exceeding 80% and awareness of modern methods of contraception exceeding 90% [ 20 , 55 ]. Despite the relatively high levels of exposure to information, condom use remained low in 2000, though use is significant in higher risk groups. While this may be due to the disruption of social marketing campaigns and limited access to condoms, desired fertility may have increased since the war, thereby reducing the utilization of modern methods of contraception. From 1992 to 2000, women's rates of utilization of modern methods of contraception decreased from 8.6% to 2.7% (12.9% to 4.3% for women "in union"). During the same period, the percentage of women reporting a desire to have six or more children increased from 14.9% to 28.6% [ 20 , 55 ]. These data highlight the fact that the constraints to adoption of condom use remain significant on the population level and may in part represent a desire to repopulate. In these cases, HIV prevention programs will need to be carefully targeted to take into account this underlying dynamic. Factor 7: Increased population mixing following large internal or regional population movements On the whole, forced migration may increase HIV risk, as forced migration movement tends to be in a rural-to-urban direction, which greatly enhances the possibility of disassortive mixing. In addition, the migration process is often associated with high levels of physical danger and exposure to sexual violence. Where forced migrants remain in highly insecure areas, migration may be associated with frequent assaults by combatants. In addition, migration patterns may be quite fluid, enabling dislocated populations to move back and forth between higher and lower risk areas, thus increasing disassortive mixing. Research suggests that urban rates of casual/commercial sexual activity tend to exceed rural rates and that exchange of rural/urban populations tends to undermine traditional norms governing sexual activity in rural areas [ 56 ]. It has been shown that war can increase partner exchange, as relationships generally tend to be shorter-term, thereby increasing the reproductive rate of the disease [ 57 , 58 ]. Due to the positive relationship between frequency of STIs and HIV, frequent partner exchange and its associated increased risk of STI infection, HIV transmission is further exacerbated [ 59 ]. Fluid population movements are particularly common during prolonged conflicts in border areas that might give rise to population mixing and then repatriation. In the case of Rwanda, research illustrates that the post-war period has seen a sharp decrease in the HIV prevalence differential between rural and urban women attending antenatal clinic services in Kigali [ 60 ]. The trend may be due in large part to migration between rural and urban communities, combined with the high level of sexual violence inflicted on rural women during the genocide. Factor 8: Emergence of norms of sexual predation and violence Coupled with increased population movement is the frequent emergence of norms of sexual predation and sexual violence within conflict-affected areas. The phenomenon of rape as a war tactic is increasingly being recognized and documented. The widespread infliction of sexual violence upon women during the Rwandan genocide and its aftermath illustrates the extent to which sexual violence may be utilized as an instrument of war. While exact figures are unavailable, it is estimated that between 250,000 and 500,000 cases of rape occurred during the conflict [ 61 , 62 ]. In Liberia, 49% of women surveyed reported at least one act of sexual or physical abuse by either a soldier or a fighter during the civil war [ 63 ]. In Sierra-Leone, 9% of those surveyed reported a war-related incident of sexual violence [ 64 ]. Similar accounts have been reported across the world including Kosovo, Azerbaijan, Iraq and others. In cases of HIV resulting from sexual violence, the shame and social stigma attached to rape prevent women from seeking testing or care. It should be noted that in some conflict-affected populations, research suggests discriminatory cultural attitudes and practices. In Rwanda, research in 1990 found that men control sexual decision-making, and that HIV positive women were more likely to report coercive sex and violence with their sexual partner than HIV negative women [ 65 ]. In Angola, of the 38% of women who had been physically abused, 69% had been abused by their husband or boyfriend and 23% by their mother or father [ 66 ]. Therefore, HIV treatment and prevention programs need to address the sociocultural determinants of unequal power sharing in sexual partnerships. It should also be noted that in some African cultures including Rwanda, mourning rituals involve intercourse between the widow or widower and another individual. Widows may be forced to have intercourse with a close male relative (i.e. brother or cousin) of her deceased husband to achieve the purification intended from the ceremony [ 67 ]. This ceremony, which may occur more frequently during periods of elevated mortality in conflict situations, places the economically vulnerable widow at an elevated risk of HIV transmission. Factor 9: Fragmentation of families and resultant vulnerable household structures Like HIV, conflict decimates family structures through mortality and dislocation, and results in lasting effects on society [ 1 ]. Conflict-affected populations typically have higher rates of child-headed households (e.g. orphans). They may also have higher dependency ratios because of greater numbers of female-headed households and, in some cases, higher levels of handicap and fewer able-bodied men. When juxtaposed with proximity to economically remunerative sex, this change in household ecology would favor greater vulnerability. Putting it Together at a Regional Level: Social Ecology of HIV and Conflict The models and mechanisms identified above help to develop an explanatory model built on a foundation of social ecology. A social ecology approach argues for models of explanation that explore the interactions of multiple causes (environmental, social, and biological) working through different mechanisms and at differing levels of scale (individual, household, community etc.) with emphasis on dynamic change over time. The social ecology of the epidemic is defined in terms of sociodemographic, socioeconomic, structural, contextual, biologic and behavioral variables that facilitate or inhibit progression of the epidemic [ 68 - 70 ]. The ecological perspective explains how conflict might impede the progress of the epidemic and it provides clues as to regional strategic factors that may exacerbate risk in the post-conflict setting. While the epidemiologic literature postulates a number of factors that we do not elaborate here (such as comorbidity and religious practice) these factors also are likely to be important. For the sake of illustrative simplicity, we examine four key variables not commonly cited that are more closely linked to the conflict-HIV axis: (1) population density, (2) level and geographic distribution of economic growth, (3) the prevalence of poverty, and (4) the existence of physical infrastructure, particularly transport infrastructure. One key feature of mapped data is the relative correspondence of population density, road infrastructure, economic productivity, and HIV risk in Southern Africa (see Figures 3a,3b,3c ). Central Africa is marked by more clustered populations and sparse road infrastructure, especially in Congo and Angola – those areas that have experienced chronic conflict. Coastal West Africa has high population density and road density but comparatively low HIV seroprevalence. This may be due in part to poor road quality and lack of road connectedness to areas of high HIV risk. Also the economic productivity of western Africa is much lower than that of southern Africa. Therefore, economic migration patterns may not be as intense. As mentioned earlier, other factors, such as the moderating influence of religion and biological co-factors (e.g. circumcision, and STI rates), may also be important. It is also possible that conflict in central Africa may have moderated HIV risk by buffering the west coast of Africa from movement of HIV up the coast from southern Africa. Population density may directly influence the occurrence, severity, and spread of violent conflict and HIV. Where population density is lower, population mixing associated with conflict may be more sporadic (as opposed to consistent and sustained). Population density paired with excellent road infrastructure may have a synergistic effect on HIV risk. This may, in part, explain the pattern of risk seen in southern and eastern Africa. Economics and poverty are important drivers. Although higher economic output is associated with higher levels of HIV in general, the poor are increasingly affected for a variety of well-accepted reasons. From this perspective, Southern Africa remains the most problematic with respect to the potential for rapid northward spread of HIV. Angola and Mozambique are characterized by high poverty, economic potential, and in the case of Angola, the potential to be a gateway to West Africa. One factor that may be driving the epidemic is the interaction between poor women and rich men (or men with some income, such as the military and truck drivers) as exemplified by Drain et al. [ 68 ] who found that income inequality was independently associated with HIV seroprevalence. The ecology of HIV and conflict also results in greater micro-level variation in the determinants of HIV risk. Mock and Drapcho [ 37 ] showed that regional variability and the design effects (sample variation across clusters/villages) associated with measures of nutrition and mortality were far greater among post-conflict countries surveyed by DHS than are typically found in more stable settings. This is plausible given that conflict does not have a consistent effect in all areas of countries. Also, it would be expected that functioning social systems found in stable settings might have an equalizing effect on health status. How has the International Community Responded to the Joint Effects of HIV and Conflict? Sadly, the international community has compartmentalized its responses to HIV and conflict – as well as its relief, recovery, and development programming instruments – which precludes an integrated and aggressive attack on the epidemic. As a result, very little has been learned in terms of designing and implementing programs to address HIV among conflicted-affected populations, with some exceptions [ 71 ]. The current structure of development assistance results in poor availability of resources to address HIV in conflict settings, as these are traditionally the domain of humanitarian assistance. To date, though much lip service is paid to the concept of developmental relief, the bulk of all humanitarian assistance is supply-side delivery of immediate survival commodities and services. This approach continues to dominate even though humanitarian assistance may be provided to conflict-affected population for years and decades, and even when displacement may provide unique opportunities to reach populations that might otherwise be inaccessible. Similarly, the immediate post-conflict period is typically serviced by transition programs that emphasize demobilization, reinsertion, reintegration and development of the foundations of governance. While these are clearly important considerations, a problem as severe as HIV cannot be compartmentalized as a development problem (i.e. not a humanitarian or transition-period concern). And indeed, problem-focused activities such as HIV prevention might be a motivating cause for the stimulation of civil society groups. Even internal to the development community, the problem of HIV is not linked to the problem of conflict, but rather these two issues are seen and treated as unrelated concerns. Different strategies and partners are managed by separate bureaucratic units that have rare interactions. Such compartmentalization of both conflict and HIV along humanitarian/development lines and internal to development management has resulted in fragmented approaches to addresses these important and interactive influences on the health development of SSA. Similarly, the transitional period should be assessed for opportunities to creatively integrate HIV-related interventions into priority program strategies to promote economic recovery and social rehabilitation. Examples of such integrated programs include integrating HIV education into micro-credit or economic development programs and incorporating HIV risk reduction strategies into demobilization and social integration programs. Demobilized ex-combatants might also be incorporated in educational and health extension programs such that they become part of the solution instead of the problem. Humanitarian assistance provides numerous opportunities for the cross-sectoral integration of effective HIV-directed initiatives, including the opportunity for synergistic amelioration of adverse health outcomes. Even though conflicts typically last for years or decades, countries affected by conflict continue to receive assistance, primarily for immediate survival needs, through humanitarian assistance efforts. In post-accord transition programs, the emphasis is on establishing democratic rule, governance, and re-integration. Sequential application of traditional humanitarian and transition interventions ignores the regional context of high HIV risk. Since HIV risk may be lower in conflict settings while vulnerability to HIV is increasing, this programming approach results in a major constraint to timely, prevention-oriented intervention. Implications for Policies and Programs Our analysis suggests that the relationship between conflict and HIV is complex and contextualized; however, important general conclusions can serve as a basis for action. The analysis demonstrates that while vulnerability to HIV is heightened as a result of conflict, exposure opportunities may be significantly reduced. This may lead to important opportunities for interventions to keep HIV prevalence rates low in the affected settings (i.e. to prevent HIV in relatively lower-prevalence countries). More urgently, post-conflict changes in exposure opportunities could result in explosive epidemic waves. The case of Angola is particularly troublesome given its strategic location and economic potential. Conflict and HIV are inter-related problems that demand a clear strategy and coordinated use of humanitarian and development assets. This means that objectives for addressing these problems should drive the response, and conflict should be viewed as a key determinant of HIV risk. The HIV/AIDS epidemic is a major constraint to development in Africa. Programs and bureaucracies should more clearly align along a consistent vision of HIV prevention and mitigation in both conflict and post-conflict settings. A portion of the Declaration of Commitment on HIV/AIDS, adopted at the United Nations General Assembly Special Session on HIV/AIDS (UNGASS) on June 27, 2001, articulates strategies and goals to address HIV/AIDS in conflict and disaster-affected regions. It calls for the development and implementation of national strategies that incorporate HIV/AIDS awareness, prevention, care, and treatment elements into programs or actions that respond to emergency situations. The declaration recognizes that populations destabilized by armed conflict, humanitarian emergencies, and natural disasters – including refugees, internally displaced persons and, in particular, women and children – are at increased risk of exposure to HIV infection, and calls for HIV/AIDS components to be factored into international assistance programs where appropriate [ 72 ]. As international, regional and national agencies strive to abide by the Declaration of Commitment on HIV/AIDS, the framework provided here will be useful in the identification of determinants of HIV risk. We recommend that factors affecting HIV risk in conflict settings be systematically assessed as a basis for strategic planning to address HIV in conflict. The assessment should include vulnerability profiling, exposure risk assessment, and characterization of mechanisms through which conflict affects HIV risk. It is particularly important to pre-empt disassortive mixing associated with post-conflict improvements in mobility and resettlement. The assessment should be conducted at the different planning levels (i.e. regional, national and sub-national). Conflict risk assessment should also be a key component so that synergistic programming between conflict and HIV initiatives can be achieved. Examples of these include: • potentiating civil society organizations around the HIV problem, especially in areas of high prevalence; • incorporating HIV prevention as a key element in demobilization and reinsertion initiatives, including the possible use of ex-combatants as HIV educators/mobilizers; and • aggressive and progressive approaches to poverty alleviation and reduction. Poverty is particularly problematic in chronic conflict contexts, even when societies have high development potential (e.g. the DRC and Angola). Aggressive development programs are probably the most central strategy to confronting HIV and conflict. HIV prevention and conflict resolution can be inserted into a number of the specific components of these programs. Targeting women- and child-headed households, and making it economically feasible for families to send youth to school are also of particular importance. Our analysis stresses the importance of maintaining a global perspective, while at the same time recognizing that micro-planning may be even more important in conflicted-affected settings than in stable settings. This is because local ecologies may be more diverse due to the varying spatial and temporal effects of conflicts. Indeed, most countries that have experienced large-scale conflict have had quiet zones where life was relatively stable, even during the course of large-scale war. These stable areas could absorb major non-emergency initiatives. In post-conflict settings, these micro-level differences persist, while others, such as differing levels of infrastructure destruction, ethnic tensions and pockets of high HIV prevalence, may require highly specific approaches. These findings also suggest somewhat different approaches to HIV surveillance in conflict-affected settings. First, a more deliberate attempt should be made to support surveillance in countries and areas affected by conflict so that a better evidence base is developed. Unfortunately, a review of the UNAIDS surveillance database revealed that conflict-affected countries have little or no systematic surveillance, despite the existence of relatively stable areas [ 73 ]. This may be due to the fact that lab testing and quality control for HIV surveillance is generally centralized. Perhaps a more de-centralized approach would better ensure continued data collected in conflict-setting such that at least some regions of a country would continue to collect data during conflict. Higher micro-level variation and greater social change in the post-conflict setting argues for more finely graded surveillance. Also, surveillance should take into account the differing risk groups resulting from conflict, and the dynamics of exposure opportunity that occur as a result of opening international borders, rapidly evolving trade corridors and improved internal mobility. Finally, we argue that information strategies, including HIV/conflict risk assessments and surveillance, should be rationally planned and implemented as a basis for intervention planning and program evaluation during the early phases of conflict response. Seroprevalence or other proxy measures of HIV infection must be monitored more deliberately as a part of surveillance. Conflict-HIV vulnerability/risk assessment tools can be developed based on the factors enumerated above. They should be applied periodically to more effectively respond to a dynamic setting. Improved HIV status information together with these planning data should foster a more evidence-based approach to preventing and mitigating HIV in conflict settings. We call for mainstreaming HIV/AIDS prevention and care policies into conflict prevention, peacekeeping operations, humanitarian responses to crises, post conflict reconstruction planning, implementation and evaluation. Competing interests The author(s) declare that they have no competing interests. Authors' contributions Dr. Mock responsible for overall framework and approach for this paper. Drs. Duale and Brown contributed HIV literature synthesis. Ms. Mathys, O'Maonaigh, Abul-Husn and Elliot extracted literature. All authors read and approved the manuscript. Table 1 HIV/AIDS Risk in Selected Sub-Saharan Africa Countries People living with HIV/AIDS % Adults 1999, 1 2001 2 Women 2 15–49, 2001 Children 2 0–14, 2001 Cumulative AIDS Rate, per 1,000 (year) 1 Estimated Num. of Death due to AIDS, 2001 3 Estimated Num. of AIDS Orphans 2001 4 ANGOLA 2.8, 5.5 190,000 37,000 0.2 (1997) 24,000 104,000 BOTSWANA 35.8, 38.8 170,000 28,000 4.7 (1998) 26,000 69,000 3 BURKINA FASO 6.4, 6.5 220,000 61,000 1.0 (1997) 44,000 268,000 BURUNDI 11.3, 8.3 190,000 55,000 1.7 (1996) 40,000 237,000 CONGO 6.4, 7.2 59,000 15,000 3.9 (1998) 11,000 78,000 CONGO DR 5.1, 4.9 670,000 170,000 0.8 (1998) 120,000 927,000 COTE D' IVORIE 10.8, 9.7 400,000 84,000 2.6 (1996) 75,000 420,000 ERITREA 2.9, 2.8 30,000 4,000 1.3 (1998) 350 24,000 ETHIOPIA 10.6, 6.4 1,100,000 230,000 1.3 (2000) 160,000 989,000 GUINEA 1.5 (1999) 29,000 5 2,700 5 0.6 (1998) 5,600 29,000 KENYA 14, 15.0 1,400,000 220,000 2.7 (1998) 190,000 892,000 LIBERIA 2.8 (1999) NA 2,000 0.1 (1998) 4,500 39,000 MOZAMBIQUE 13.2, 13.0 630,000 80,000 0.6 (1998) 60,000 418,000 NAMIBIA 19.5, 22.5 110,000 30,000 4.1 (1997) 13,000 47,000 3 NIGERIA 5.1, 5.8 1,700,000 270,000 0.2 (1999) 170,000 995,000 RWANDA 11.2, 8.9 250,000 65,000 3 2.2 (1997) 49,000 264,000 SIERRA LEONE 3.0, 7.0 90,000 16,000 0.0 (1996) 11,000 42,000 SOUTH AFRICA 19.9, 20.1 2,700,000 250,000 0.3 (1996) 360,000 660,000 3 TANZANIA 8.1, 7.8 750,000 170,000 3.2 (1998) 140,000 815,000 UGANDA 8.3, 5.0 280,000 110,000 2.5 (1997) 84,000 884,000 ZAMBIA 20, 21.5 590,000 150,000 5.0 (1997) 120,000 572,000 1 International Program Center, Population Division, U.S. Census Bureau. Updated June 2000. HIV/AIDS Surveillance Data Base. "HIV /AIDS Country Profiles." Online [accessed April 5, 2002]. 2 United Nations Development Program. 2002. "Human Development Indicators 2002." Aggregates calculated for the Human Development Report Office by UNAIDS. Online [accessed January 14, 2003]. 3 UNAIDS, WHO. Updated 2002. "Epidemiological Fact Sheets on HIV and Sexually Transmitted Infections." [accessed January 22, 2003]. 4 Joint USAID/UNICEF/UNAIDS Report. 2002. "Children on the Brink." Appendix I. Online [accessed January 14, 2003]. 5 United Nations Development Program. 2001. "Human Development Indicators 2001." Aggregates calculated for the Human Development Report Office by UNAIDS. Online [accessed January 14, 2003]. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544944.xml |
551540 | Genomic analysis of early murine mammary gland development using novel probe-level algorithms | A novel algorithm (ChipStat) is presented for detecting gene-expression changes from Affymetrix microarray data. The method is used to identify changes in murine mammary development. | Background The widespread use of DNA microarrays to measure transcript abundance from a significant fraction of the genome has proven to be a valuable tool for identifying functional cellular pathways as well as for capturing the global state of a biological system [ 1 - 4 ]. These arrays have typically been constructed by spotting large, pre-synthesized strands of nucleic acid on an appropriate surface [ 5 ] or by directly synthesizing smaller oligonucleotides in situ at defined locations [ 6 ]. The latter technique has been implemented in Affymetrix oligonucleotide microarrays designed for expression analysis. Because hybridization to short (25-mer) oligonucleotides is used to measure expression, Affymetrix arrays contain multiple, independent oligonucleotides designed to bind a unique transcript. In this way, specificity and a high signal-to-noise ratio can be maintained despite the noise due to the hybridization itself. When the intensity of hybridization to a given oligonucleotide designed to detect the transcript (a 'perfect match' probe, PM) is corrected by its corresponding (single base-pair 'mismatch', MM) control, an estimate of gene expression (PM - MM) is derived. This probe pair value is then combined with values from the other, independent, oligonucleotides designed to bind the same transcript (together designated the probe set) to obtain a more robust estimate of transcript abundance [ 7 ]. The ability to sensitively detect changes in gene expression is crucial for a transcript-level analysis of developmental processes and other processes involving changes in the relative sizes of cellular compartments. Early attempts to limit the false-positive rate of microarray studies focused on the magnitude of fold-change in gene expression (see, for example [ 1 ]). For studying purified cell populations, where a substantial change in gene expression is more likely to reflect biologically relevant function, such a crude limitation was acceptable. However, adequate studies of complex tissues require a substantially more sensitive method of detection. For example, a small yet reproducible change in gene expression within a whole organ may reflect a substantial expansion or regulatory change within a subpopulation of cells that overexpress a given gene relative to the surrounding tissue. Thus, a method for identifying such small, statistically significant changes in gene expression is required. Because of the variety of techniques used to measure gene expression, it has become commonplace to utilize simple, numerical estimates of gene expression as the starting point for such identification. One major drawback to this approach has been that individual probe cell information from Affymetrix microarrays is routinely discarded. This issue has only recently begun to be addressed [ 8 - 10 ], and it appears that a substantial amount of useful information can be obtained from probe-level analysis. An additional compromise has been driven by the practical difficulties of performing large numbers of microarray experiments. Given limited samples, permutation of the existing experimental dataset, rather than use of independent sets of control samples, has been widely used to estimate the statistical significance of differential gene expression [ 11 ]. Although this technique has been useful given the historically high cost of performing microarray analysis, it may inherently limit the sensitivity of the results obtained. As such, a test for differential gene expression that utilizes a 'gold standard' negative-control dataset would have clear advantages. The impetus for the work described here is the desire to sensitively identify coherent patterns of gene expression during mammary gland development. At 2 weeks of age, the female FVB mouse mammary gland exists as a rudimentary epithelial tree embedded at one end of a fat pad composed of adipose tissue and fibroblasts. Previous work has demonstrated a fundamental transition in the composition of the mammary adipose compartment from brown fat to white fat during early development [ 4 ]. By 3 weeks of age, the onset of puberty heralds the beginning of the process of ductal morphogenesis, which results in the formation of the branching epithelial tree of the adult gland. The onset of puberty results not only in the rapid growth of a ductal epithelial tree but also the appearance of specialized, highly proliferative structures known as terminal end buds that elaborate this tree via branching morphogenesis [ 12 , 13 ]. Furthermore, puberty is known to be a time of increased susceptibility to carcinogenesis [ 14 , 15 ]. Thus, a detailed examination of transcriptional changes during this period would be of substantial use. We describe here a novel algorithm for sensitively detecting gene-expression changes using information derived from individual probe cell hybridizations to Affymetrix oligonucleotide microarrays. In addition to modeling the predicted behavior of this algorithm, we have generated an independent cohort of control samples derived from the murine mammary gland that can be used to empirically calibrate its statistical behavior. We have then used this algorithm to analyze a biological transition in early murine mammary gland development in order to compare the sensitivity of this approach to other commonly used algorithms. In conjunction with a second novel algorithm, we have developed an aggregate approach to the reliable detection of differential gene expression that yields substantially improved sensitivity across a range of false-positive rates and have applied this approach to the analysis of early murine mammary gland development. Results A variety of traditional statistical methods, such as the t test, have been used in conjunction with microarray datasets to detect changes in gene expression (see for example [ 16 ]). Given the large numbers of genes tested, it is widely recognized that a stringent threshold for statistical significance is necessary in order to reduce the number of false positive changes. For example, a threshold of statistical significance of P < 0.001 would be expected to yield around 100 false positives on a typical array measuring 10,000 genes. Some algorithms, such as significance analysis for microarrays (SAM) [ 11 ], explicitly control the number of expected false-positive results using permutations of the existing dataset. Regardless of the method utilized, statistical differences are typically calculated on the basis of an aggregate measure of gene expression (a gene signal). However, a fundamental difficulty with these methods is that they often do not have the requisite statistical power to sensitively detect changes in gene expression after correction for multiple hypothesis testing. We reasoned that utilizing the multiple hybridizations to independent oligonucleotides on the Affymetrix platform might allow us to develop a method for detecting expression changes with substantially greater statistical power. To test this approach, we developed a novel analytical algorithm that is based on identifying individual differences at a given statistical significance between corresponding probe pairs. To a first approximation, the signal on any given probe cell can be modeled as: S = M + E(b) + E(p) + E(h), E ~ N Where S is the signal detected on the microarray, M is the average message level in a given experimental state, E(b) is noise due to biological variation between animals or animal pools, E(p) is the noise due to variations in sample measurement, and E(h) is the noise inherent in hybridization to oligonucleotide features on the array. The goal of our analysis was to identify a method that would allow us to reliably distinguish significant differences in M under particular experimental conditions. Given this model, we reasoned that the relative magnitude of E(b) + E(p) (the experimental noise) compared with E(h) (the hybridization noise) should determine whether comparisons between individual probe pairs would be useful. If the bulk of noise in our microarray data was due to factors influencing the level of transcript available for measurement (that is, E(b) + E(p) >> E(h)), then individual probe-pair measurements should only reflect the pre-hybridization bias in transcript availability. In this case, the t -test or other measurement based on the average of the probe set would be expected to perform as well as an algorithm based on individual probe-pair comparisons. In contrast, if most noise in the measurement of true transcript level exists at the level of hybridization to a given oligonuclotide (E(b) + E(p) << E(h)), then the independent measurements of probe-pair differences more closely approximate independent measurements of differences in gene expression. In the most extreme case - if E(h) is sufficiently larger than E(b) + E(p) - each oligonucleotide in the probe set could be considered as an independent measurement of gene expression and the probability of observing a given number of probe pairs changing under the null hypothesis would be determined by the binomial distribution. To explore this possibility, we implemented an algorithm, hereafter designated ChipStat, that takes corresponding probe pairs across two comparison groups and tests them for statistical significance with P less than a fixed value (hereafter denoted p ps ). To avoid making assumptions about equal variance in both groups, a heteroscedastic t -test is used. We would expect that probe sets in which larger numbers of individual probe pairs show a significant change in the same direction are more likely to be measuring differentially regulated genes. Thus, for any given probe set, the number of probe pairs (0-16) changing in a given direction with P less than p ps is tabulated and used as a measure of the significance of change in gene expression. We simulated the expected behavior of this algorithm under the null hypothesis (no difference in gene expression) across various ratios of E(b) + E(p) and E(h) (see Materials and methods for details). Results are shown in Figure 1 . Validation and optimization of the ChipStat algorithm Although this approach provides a statistical methodology for identifying changes in gene expression, it is only possible to directly calculate a P value associated with this change in limiting cases. If E(h) >> E(b) + E(p), the binomial distribution can be used to calculate the resulting significance (given the number of changes, total number of probe pairs, and p ps ); however, the relative contributions of E(h), E(b), and E(p) to the total error function are not known a priori . To empirically measure the null distribution for three-sample versus three-sample comparisons, a cohort of independent control samples for our experimental system was generated. To do this, the third, fourth and fifth mammary glands were harvested from 18 age-matched 5-week-old control female mice. After extraction of RNA, groups of three animals were pooled to create six initial RNA samples. Biotinylated cRNA was then independently prepared from these pooled RNA samples and hybridized to Affymetrix MG_U74Av2 oligonucleotide microarrays, yielding six datasets. All possible three by three combinations were compared across 11,820 probe sets (corresponding to all probe sets on the MG_U74Av2 that contain exactly 16 probe pairs), and the cumulative distribution of false positives as a function of p ps and the number of probe pairs changed was tabulated. Results are shown for p ps = 0.05 (Figure 2 ). It is notable that very few false positives are associated with large numbers (more than 10/16) of probe pairs changing. While the number of false-positive probe sets does not decline as rapidly as the binomial distribution, the overall curve is consistent with a large component of hybridization noise (compare Figures 1 and 2 ), suggesting the utility of a probe-level approach. Likelihood maximization of our initial statistical model (E ~ N, ignoring probe-specific effects) using results for low numbers of probe pairs (0 to 6) changing suggests that E(h) (hybridization noise) is approximately 2.5 times greater than E(b) + E(p) (experimental noise). We note, however, that the empirically derived null distribution can be used to derive a valid test of significance for ChipStat regardless of the validity of the underlying model and without any direct calculation of relative noise contributions by E(h), E(b) and E(p). An ideal method for identifying differentially regulated genes would maximize the number of genes identified while maintaining a low fixed number of expected false positives. We have previously shown the utility of testing the statistical overlap of discrete gene lists with biologically relevant annotation in order to identify functional pathways during murine mammary gland development [ 4 ]. This maximization is therefore of particular experimental interest. To evaluate the ChipStat algorithm from this perspective, we performed triplicate microarray measurements of RNA derived from the mammary glands of independent pools (more than 10 animals per pool) of wild-type female FVB mice harvested at 2 or 5 weeks of postnatal development. We wished to determine the number of statistically significant increases in gene expression from 2 to 5 weeks of age, a period of postnatal development that encompasses the rapid epithelial proliferation that accompanies ductal morphogenesis in the mammary gland at the onset of puberty [ 17 ]. ChipStat was used to analyze differences between the 2- and 5-week mammary gland samples ( p ps = 0.05), and the number of statistically significant increases was measured as a function of the number of genes expected to appear on the list by chance. Results are shown in Figure 3a . The number of expected false positives was empirically obtained from the negative-control dataset described previously. Thus, for example, under conditions p ps = 0.05 with 8/16 probe pairs increasing, where around five genes are expected to be identified by chance, we find that the measured number of differentially regulated genes is around 160. This corresponds to a false-positive rate of approximately 3% (or, conversely, a true-positive rate of approximately 97%). It is also apparent (Figure 3a ) that the sensitivity of detection can be 'tuned' on the basis of the number of false positives that are deemed acceptable. To determine whether the sensitivity of this algorithm could be further optimized, similar analyses were performed at various values of p ps (Figure 3b ). These data suggest that relative sensitivity as a function of false-positive rate is maximized at p ps approximately equal to 0.04-0.05 (note the similarity of these curves in Figure 3b ). Furthermore, while certain other values of p ps yield increased sensitivity at specific points (for example, p ps = 0.03 at around four genes expected by chance; data not shown), values of 0.04-0.05 appear appropriate across most highly-significant P values. A marked decrease in sensitivity for a given false-positive rate is noted both at low (0.01) and high (0.1, 0.15) values of p ps . Although the use of negative-control samples provides a definitive method for evaluating the behavior of our statistical algorithms, we independently verified these results using northern blot hybridization. Genes differentially expressed (6/16 probe pairs increasing, p ps = 0.04) from 2 to 5 weeks of mammary gland development were identified, and analysis of the control data suggested that fewer than 10 increases would be expected by chance at this significance level (corresponding to P < 7.7 × 10 -4 ). Manual inspection of the resulting list revealed the presence of a number of genes known to be upregulated during this developmental transition, including cytokeratin 19 ( Krt1-19 ), cytokeratin 8 ( Krt2-8 ), and κ casein ( Csnk ). However, to avoid bias toward previously studied genes or known genes with high fold change, genes were randomly selected from subsets of this list corresponding to high-stringency ( P < 2.2 × 10 -4 ), low-stringency with high fold change (2.2 × 10 -4 < P < 7.7 × 10 -4 , ≥ 1.8-fold change), and low-stringency with low fold change (2.2 × 10 -4 < P < 7.7 × 10 -4 , < 1.8-fold change). Results from northern blot analyses using probes for these randomly selected genes are shown in Table 1 . Of nine genes selected, eight were shown to change significantly via northern blot analysis. Of note, the single gene that did not show a significant change ( Ldh1 ) was from the low-stringency group and was predicted to show only a 1.37-fold change. In contrast, northern hybridization confirmed the differential expression of other genes with only modest fold-changes (for example, Sqstm1 , 1.48-fold change from 2 to 5 weeks). As the genes tested were not biased toward higher fold change (only 2/75 genes with fold change > 3 were randomly selected for northern confirmation), our data demonstrate the ability of ChipStat to reliably detect the types of small, reproducible changes in gene expression that are necessary for whole-organ analysis. Comparison of ChipStat with other analytical methods Other methods of detecting differential gene expression have been widely utilized, including SAM [ 11 ] and dChip [ 8 ]. As previously discussed, SAM utilizes an aggregate (probe-set-level) estimate of gene expression as its analytical starting point. Similarly, although dChip utilizes probe-cell-level analysis to determine the level and statistical bounds of gene expression, it does not explicitly make use of probe-level comparisons for identifying differentially regulated genes. More recently, the logit-T algorithm, which in contrast to SAM and dChip utilizes probe-pair-level comparisons for statistical testing, has been shown to improve differential expression testing performance in a variety of Latin square datasets reflecting technical replicates of samples with spiked-in transcripts [ 10 ]. We therefore wished to determine the performance of the ChipStat algorithm relative to these methodologies. Further, as our control dataset incorporates biological and experimental variability in addition to sample preparation and hybridization noise, we reasoned that it would provide a more appropriate estimate of the performance of these algorithms when analyzing data from an experimentally plausible animal model. SAM, dChip, the t -test and logit-T all provide a P value estimating statistical significance in the absence of an empirical measurement of the underlying null distribution; Figure 3c shows a comparison with ChipStat when using these estimated P values. However, as ChipStat requires the additional information provided by this empirical distribution for statistical calibration, the inherent performance of other algorithms may be underestimated if they are not similarly calibrated. To correct for this difference, the significance of SAM, dChip and logit-T values were assessed using all three by three combinations of the null dataset (given the permutation-based calibration of false-discovery rate utilized by SAM, note that SAM values are not predicted to improve significantly using this method of calibration). Results are shown in Figure 3d . In the case of the t -test, results obtained using calculated P values are generally within 5% of comparable results using empirically calibrated P values. Logit-T and dChip appear much less sensitive when using reported P values, although both of these techniques show improvement when calibrated using the control dataset. Of particular note, logit-T performs only slightly less well than ChipStat when calibrated against our control distribution, consistent with the fact that it was the only other algorithm considered that performs probe-pair-level comparisons when testing for differential gene expression. Design and validation of the Intersector algorithm Although the Affymetrix Microarray Suite (MAS) software utilizes probe-level information in identifying differentially expressed genes, its use has been restricted to single-array comparisons. As a result, it has been widely recognized that this approach generates an unacceptably high number of false-positive results. The use of replicate samples, however, might be expected to lower the false-positive rate while achieving a higher sensitivity. We therefore combined pairwise comparisons between triplicate data points in two different groups (that is, nine comparisons in total) and determined differential expression based on the Affymetrix call (for example, increases + marginal increases) for these comparisons. A similar technique, in which a simple majority cutoff (5/9 changes) was considered to denote significant change, has recently been described [ 18 ]. Although this approach involves N 2 comparisons in general for equal groups of N arrays, it is easily feasible for three-sample versus three-sample comparisons. We have designated this approach Intersector. Significantly, the control data previously generated to calibrate ChipStat also allow us to determine the empirical false-positive rate for Intersector as a function of the number of 'increase' calls and to perform direct comparisons with other algorithms. The performance of the Intersector algorithm in comparing 2- versus 5-week mammary gland gene expression is shown in Figure 4a . Interestingly, the Intersector algorithm is able to achieve a slightly improved sensitivity at a given false-positive rate when compared with ChipStat. To determine whether the particular version of the MAS algorithm influences this result, all analyses were run using difference calls from both MAS 4.0 and MAS 5.0 (see Figure 4a ). Although the number of changes required to achieve similar sensitivity was different, the Intersector results from MAS 4.0 and MAS 5.0 are comparable at a given false-positive rate. Given substantial differences between the types of probe-pair comparisons performed by ChipStat and MAS, we next wished to ascertain if these algorithms identify the same sets of upregulated genes. Direct comparison requires that the analyses result in comparable false-detection rates. We therefore compared the lists at thresholds corresponding to approximately 2.5 genes expected by chance, and the closest available threshold with each algorithm was chosen. The resulting thresholds were Intersector (MAS4) 7/9 (1.75 expected by chance), Intersector (MAS5) 8/9 (2.8 expected by chance), and ChipStat (.04) 8/16 (2.68 expected by chance). Notably, examination of these lists demonstrates that each algorithm (Intersector with MAS 4.0 data, Intersector with MAS 5.0 data and ChipStat) detects a discrete set of genes that are not detected by the others (Figure 4b ). This is particularly intriguing since empirically estimated false positive rates suggest that these groups of genes are not likely to reflect chance fluctuations alone. Thus, in addition to identifying a core set of regulated genes, the Intersector and ChipStat algorithms each detect sets of complementary, nonoverlapping genes that change significantly. To confirm this result, five out of the 13 genes uniquely identified by ChipStat were randomly chosen for confirmation. One of these genes was undetectable by northern blot hybridization, and the remaining 4/4 showed differential expression in the predicted direction (5 weeks > 2 weeks) (Table 1 , and data not shown). This demonstrates that, at comparable levels of statistical stringency, ChipStat correctly identifies differentially expressed genes that are not identified by Intersector. Further, having directly tested approximately 40% of all genes in this category, no false positives were identified. Examination of lower stringency lists (9.5 expected by chance from ChipStat, 7.4 expected by chance from Intersector using MAS5) also revealed sets of genes identified by ChipStat or Intersector alone. For example, the 'Intersector only' list created at this lower stringency contains α -, β -, and γ -casein; previous work in our lab has demonstrated that these genes are differentially regulated with expression at 5 weeks greater than that at 2 weeks (data not shown). Development of a hybrid approach Given the presence of genes uniquely identified by Intersector or ChipStat at a given false positive rate and the feasibility of performing Intersector analysis on small numbers of replicates, we next explored whether a combination of these approaches could further improve overall detection. To test this, all possible pairwise threshold combinations of ChipStat (p ps = 0.05, 0/16 to 16/16 probe pairs changing) and Intersector (0/9 to 9/9 increases or marginal increases) were combined, and aggregate lists of genes identified by both algorithms were tabulated (see Additional data file 1). The results demonstrate that a combination of these two approaches can lower the expected false positive rate while maintaining a high sensitivity. For example, the combination of ChipStat (p ps = 0.05, 6/16 probe pairs increasing) and Intersector (7/9 increases + marginal increases) detects 209 increasing probe sets with only 3.4 expected to increase by chance (expected false-positive rate less than 2%). A comparison of the false-positive rates for single (ChipStat or Intersector alone) and combined (ChipStat and Intersector) approaches is shown in Figure 4c . Note that the total number of probe sets detected by the combined approach shown in Figure 4c is greater than the number detected by the single approach with a comparable false-detection rate (209 probe sets and 173 probe sets, respectively). The behavior of optimal combinations with respect to the number of genes detected is shown in Figure 4d . One additional feature of this combined approach is the ability to 'fine-tune' the number of expected false positives. That is, while Intersector (MAS5) allows no choice between approximately three and approximately seven expected false positives (2.8 and 7.35, corresponding to 8/9 or 7/9 changes, respectively), the combined approach provides a smoother continuum of values. More important, these data show that, for certain targeted numbers of expected false positives, a combination of ChipStat and Intersector can provide improved performance in gene detection compared with either algorithm alone. Genomic characterization of early mammary gland development The goal of these methodological developments has been the elucidation of biological mechanisms underlying mammary gland development and carcinogenesis. We therefore used the hybrid ChipStat/Intersector lists representing early mammary gland development as a basis for further exploration of developmental processes during this time period. A complete list of genes differentially expressed between 2- and 5-week murine mammary gland was compiled using the techniques described above. The results are listed in Additional data file 2. To identify coherent functional patterns of gene expression during neonatal development through the onset of puberty, statistically significant associations between Gene Ontology (GO) categories [ 19 ] and lists of up- and downregulated genes were identified using EASE [ 20 ]. Multiple testing correction was performed using within-system bootstrapping, and a corrected significance threshold of P less than 0.05 was used. Results are shown in Table 2 . Upregulated genes were associated with a total of 22 GO categories, and downregulated genes with 10 categories. In addition, this approach provides a convenient test of whether the increased sensitivity of ChipStat/Intersector yields corresponding power in identifying patterns of biological activity. To test this directly, lists of differentially expressed genes with the same number of expected false positives (empirically calibrated as previously) were identified using dChip and logit-T. These lists were then tested for association with GO annotation, and the results are shown (Table 1 , Figure 5 ). Of note, ChipStat/Intersector lists were associated with a greater number of GO categories than were dChip or logit-T, and this was true for both up- and downregulated gene lists. Consistent with our suggestion that logit-T should be most similar to ChipStat/Intersector because of its use of probe-pair-level comparisons, logit-T also generated lists that are statistically associated with a larger number of GO categories than did dChip (Figure 5 ), although it did not outperform ChipStat/Intersector. ChipStat/Intersector identified 22/22 of categories associated with any of the list of upregulated genes and 10/11 categories identified using any of the lists of downregulated genes. A single downregulated category ('cellular component: extracellular') was associated only with the logit-T list. To provide a crude check on the reliability of these results in addition to the confirmation previously performed, gene lists were examined for association with previously described biological processes. In addition to individual genes that are consistent with epithelial proliferation and differentiation (discussed above), several statistically associated categories represent pathways that have been previously described in the mammary gland during this developmental window [ 4 ]. These include 'blood vessel development' and 'mitochondrial inner membrane'. The latter category reflects the previously reported decrease in brown adipose tissue at the end of the neonatal period and the corresponding decrease in the capability of the mouse to utilize adaptive thermogenesis to maintain body temperature. Brown adipose tissue is not only rich in mitochondria, but the fatty-acid metabolic pathways necessary for adequate thermogenic activity are also spatially localized at the inner mitochondrial membrane. Of note, this category only reached statistical significance using the ChipStat/Intersector list. Interestingly, 'pheromone binding' and 'odorant binding' categories are also associated with upregulated expression at the onset of puberty. Genes within these categories are primarily members of the major urinary protein (MUP) gene family, and MUP transcripts ( Mup1 , Mup3 , Mup4 , Mup5 ) account for four of the five most highly upregulated genes from 2 to 5 weeks. Large quantities of MUPs are synthesized in the male liver and excreted in the urine, where they bind pheromone and play a role in signaling for complex behavioral traits [ 21 , 22 ]. MUP levels are upregulated during puberty in the liver, although expression levels are much higher in males than in females. While MUP expression within the mammary gland has previously been reported [ 23 , 24 ], its expression was considered to be detectable only with the onset of pregnancy. Our data show that MUPs are highly upregulated in the female mammary gland during the 2- to 5-week transition. Interestingly, Slp (sex-limited protein), which also shows sex-restricted expression in the male liver and - like Mup expression - is normally repressed by Rsl [ 25 ], is also significantly upregulated during this period. Additional examination of these gene lists revealed an interesting transcriptional pattern that is not reflected in the current GO hierarchy. The nontranslated RNA transcript Meg3/Gtl2 is significantly downregulated from 2 to 5 weeks of development, and its reciprocally imprinted neighbor Dlk1 [ 26 ] shows a similar decrease. This is noteworthy because two other genes with decreasing expression, H19 (nontranslated RNA) and Igf2 , are also reciprocally imprinted neighbors, suggesting the possibility of a common regulatory mechanism for altering expression from loci exhibiting this genomic organizational structure (see [ 27 ]). Discussion The ability to reliably detect changes in gene expression is critical for the analysis of experimental microarray data. This problem assumes particular importance when analyzing complex mixtures of cells, such as those derived from a whole organ during ontogeny. The challenge can be most clearly seen by considering a small subpopulation of cells that demonstrate a marked change in gene expression. If the expression of this gene is uniform and low throughout the rest of the tissue, the biologically relevant change within a few cells will appear as a low fold change in organ-wide gene expression. A variety of such nonabundant yet developmentally critical cell types have been described. For example, the proliferative capacity of small structures in the mammary gland known as terminal end buds gives rise to the extensive ductal structure that is elaborated during puberty [ 17 ]. More recently, the characteristics of mammary stem cells have been described, and these cells have been suggested to serve as targets for carcinogenesis [ 28 , 29 ]. To facilitate the study of such subpopulations within a whole-organ context, therefore, we have developed a novel approach to the analysis of Affymetrix oligonucleotide microarray data. A variety of nonparametric and parametric statistical tests, including variants of Student's t -test, have been used to identify significant changes in gene expression using replicate microarray data. Given the substantial economic investment required for large microarray experiments, attempts have also been made to improve detection of differentially regulated genes through better estimates of the null distribution using permutation analysis; the use of software incorporating such methods, such as SAM [ 11 ], has become widespread. A different approach to improved detection (dChip, see [ 8 ]) has attempted to use probe-level information to derive an improved estimate of relative gene expression before assessing differential regulation. While much work has focused on such use of probe-level analysis for estimating gene expression [ 8 , 9 ], the analysis of replicate data at the probe level for identifying differentially expressed genes has only recently become a focus [ 10 , 30 ]. In particular, if hybridization noise contributes a substantial portion of the overall noise inherent in microarray measurements, the use of multiple probe pairs devoted to measuring a single gene suggests a potential approach to overcoming this noise. The ChipStat algorithm uses heteroscedastic t -test comparisons between probe pairs, and the number of probe pairs that change greater than a significance threshold are tabulated. A greater number of consistently changing probe pairs should indicate that the difference is less likely to be due to hybridization noise, and thus this number relates the overall probability that the probe set is measuring a true change in gene expression. The processing time for the ChipStat algorithm scales as a linear function of the number of replicates processed ( O (N)), and thus it is feasible to apply this approach to much larger numbers of samples. To assess the statistical significance of ChipStat results, it was necessary to empirically measure the underlying null distribution. While the recent availability of a number of publicly available Latin square datasets representing measurements of spiked-in control samples has greatly facilitated measurements of this sort [ 31 ], these datasets reflect technical replicates without biological noise. As we have demonstrated, the behavior of the ChipStat algorithm would be expected to change depending on the relative contributions of biological/experimental noise and probe-level hybridization noise. Thus, a set of negative control samples reflecting an experimental system that include biological noise was required. To generate these samples, mammary glands from six independent cohorts of mice were harvested. These data provide a true, gold-standard negative control within a representative mammalian experimental system, and we anticipate that their public availability will be similarly useful to the broader scientific community in analytical development and validation. Furthermore, the use of this dataset as an empirical calibration control for ChipStat argues that these results will be valid independent of the adequacy of the statistical noise model used. It is worth noting that the use of pooled groups of animals is likely an important parameter, as single-animals groups, for example, would be expected to exhibit increased biological variability and thus decrease the proportional contribution of hybridization noise. Given empirical measurements of the expected number of false positives for a given set of analytical parameters, it was possible to assess the relative sensitivity of a variety of algorithms using a positive control dataset (2-week versus 5-week murine mammary gland) known to contain a substantial number of increasing transcripts. Consistent with our hypothesis that probe-level comparison analysis should improve sensitivity, ChipStat was able to substantially outperform a variety of methods ( t -test, SAM, and dChip) based on aggregate gene-expression measures (Figures 3c,d ). Furthermore, this remained the case even when the statistical significance of dChip was recalibrated using a negative control dataset. Recently, Lemon et al . have described a method (logit-T) that is also based on probe-level t -test comparisons for identifying differentially expressed genes [ 10 ]. The logit-T algorithm estimates statistical significance using the median result of t -tests performed on log-transformed PM probe data. ChipStat differs from this approach in several significant respects. These include the use of a fixed P value threshold for pairwise probe comparisons and the use of the degree of reproducibility across the entire probe set as an indication of statistical significance. Results from the empirical control data suggest that ChipStat performs slightly better than logit-T in most cases within our biological system. Interestingly, however, the advantage of ChipStat over logit-T was more modest than the advantage over SAM, dChip, and the t -test; as logit-T also uses probe-level comparisons, this result is consistent with our overall observations regarding the increased power of probe-based analysis. It is also worth noting that the nominal P values derived from both logit-T and dChip substantially underestimated statistical significance prior to correction with our control data, suggesting that, for example, the median P value cannot be used to directly assess significance without such correction. One additional difference between ChipStat and logit-T stems from the use of mismatch (MM) probe cells (ChipStat) and log-transformed data (logit-T). As currently implemented, the ChipStat algorithm compares differences in probe pair (PM - MM) values rather than in PM values alone. Interestingly, the use of PM values within the ChipStat algorithm does not result in superior performance (data not shown), and log(PM) data yield performance that is roughly comparable to PM - MM (data not shown). Further work will be required to determine if the log(PM) approach can be adapted to improve the performance of ChipStat. The Intersector algorithm tabulates MAS calls from all pairwise comparisons across replicate groups. As we have shown, this algorithm provides the most sensitive method for detecting gene expression changes at low false-detection rates. However, it suffers from several substantial drawbacks. First, the proprietary nature of the Affymetrix algorithm and its associated decision matrices limits the ability to automate the analytical process. Additionally, because N 2 pairwise comparisons are required for equal groups of N replicates (that is, O (N 2 )), this method is not easily scalable to larger numbers of samples. In contrast, ChipStat scales linearly with N, and the use of the heteroscedastic t -test also makes it possible to precompute results for a (potentially large) baseline control population against which multiple comparisons will be performed. While both approaches are feasible for triplicate comparisons, extension of Intersector to much larger numbers is unlikely to be practical. A third disadvantage to the Intersector approach stems from the lack of a detailed model for its underlying statistical framework. Both ChipStat and Intersector, as currently described, require the use of control samples to generate an estimate of statistical significance. Thus, extension of these results to encompass either a substantially different experimental system or larger numbers of replicates will require the generation of new empirical significance curves. In the case of large numbers of replicates, however, the cost of generating such data is likely to remain prohibitive at least in the near future. Statistical simulations of ChipStat behavior may, however, provide a mechanism for extending the current control curves for larger datasets. This approach would rely on the relative estimates of E(b) + E(p) and E(h) obtained by fitting the current empirical curve derived from six samples. While a small number of probe sets change more often than would be predicted by simulation, it should be possible to conservatively estimate an upper bound to the P value curve by overestimating the relative contribution of E(b) + E(p) vs. E(h). Further experimental work will be required to confirm this possibility. One caveat to this approach is that the simplified statistical model that we have used to illustrate the theoretical advantages of probe-level comparisons does not account for the variability in the behavior of specific probe cells that exist on Affymetrix arrays. In contrast, the model-based approach to signal estimation implemented in dChip explicitly incorporates such variability and has been shown to provide a good fit to empirical measurements of array data [ 8 , 32 ]. It is likely that incorporation of probe-specific parameters in this way would improve the ability to predict the theoretical behavior of ChipStat and provide a better estimate of hybridization noise from our empirical data. Given this likelihood, current estimates of the relative contributions of E(b) + E(p) and E(h) should be taken as provisional. In this context, it is worth noting that the ability to perform our current validation and to tune both Intersector and ChipStat was critically dependent on the gene-expression datasets derived from our independent cohorts of control animals. One might naively assume, in the absence of true negative control data, that robust changes in gene expression should be detected by simply taking the Affymetrix MAS calls and requiring that they consistently demonstrate increases for all pairwise comparisons. In contrast, our data show that the Intersector algorithm can achieve increased sensitivity while retaining an appropriately low (and defined) false-positive rate. Both the Intersector and ChipStat algorithms can be tuned using negative control data for sensitivity versus false-positive rate, depending on the type of analysis and application-specific tolerance for false-positive calls. Furthermore, these algorithms can be combined to further improve their sensitivity. As we have demonstrated that each of these algorithms detects a population of probe sets not identified by the other at a comparable stringency, this combined approach may yield the best result. Given these considerations, we favor the use of the hybrid ChipStat/Intersector approach for small number of replicates (around three), with ChipStat alone being useful for large numbers of replicates. Although ChipStat shows greater sensitivity than logit-T at moderate numbers of false positives (more than five expected false positives out of 12,488 probe sets), their comparable performance at high stringency (less than five expected false positives) suggests that the overlap in genes identified by these two techniques may also be of interest. An additional piece of evidence for the utility of our approach is provided by the statistical association of GO annotation with lists derived from ChipStat/Intersector, dChip or logit-T. At the level of significance tested (3.4 genes per list expected by chance), ChipStat/Intersector lists were statistically associated with a greater number of GO terms than were lists derived from dChip or logit-T. Furthermore, as would be predicted from the fact that logit-T is also a probe pair-level comparison method, logit-T lists are associated with GO terms at a level that is intermediate between dChip and ChipStat/Intersector. One of the terms associated only with the ChipStat/Intersector list of downregulated genes is 'mitochondrial inner membrane'; this example is particularly noteworthy in light of previous work demonstrating a presumptive role for enzymes of fatty acid oxidation in adaptive thermogenesis during the neonatal period [ 4 ]. It should be noted that these results depend on the level of significance chosen for generation of the original lists, and an increase in the total number of differentially expressed genes identified may actually decrease the statistical significance of a given association if it does not result in the detection of more genes within the category in question. Despite some caveats as to the generalizability of these results, our data demonstrate that the improved sensitivity of ChipStat/Intersector can measurably influence the ability to interpret patterns of biological activity. Early murine mammary gland development For the FVB murine mammary gland, the period from 2 to 5 weeks of age encompasses critical developmental milestones that include the suckling-weaning transition as well as the profound hormonal changes that characterize the onset of puberty and its consequent rapid ductal epithelial proliferation. Our present work has more completely characterized changes in the transcriptome that occur during early murine mammary gland development than have previous reports. A total of 213 upregulated and 130 downregulated probe sets were identified under conditions designed to yield a low expected false-positive rate (3.4 probe sets expected to change by chance per list). Four out of five of the most highly upregulated transcripts through the onset of puberty are members of the MUP family of odorant-binding proteins. MUPs are lipocalins that can bind hydrophobic molecules such as pheromones, and they have previously been shown to play a role both in the delivery of signals within the urine as well as in the reception of these signals on the nasal epithelium ([ 33 , 34 ]; see [ 35 ] for review). Isoform-specific MUP expression has also previously been reported in a number of secretory glands, including the murine mammary gland [ 23 , 24 ]. However, detectable expression has previously been reported only beginning with the first pregnancy [ 23 ]. Our results demonstrate a striking increase in the expression of a variety of MUP isoforms as the mammary gland makes the transition from the neonatal period through the beginning of puberty. This expression pattern is noteworthy given the known effect of puberty on MUP expression in the liver [ 36 ]. Interestingly, however, expression in the liver is markedly greater in the male and has been causally linked to the male pattern of growth-hormone pulses [ 36 ]. As this male-specific pattern of expression has been shown to be Stat5b-dependent, the availability of Stat5b -/- mice should allow future determination of whether mammary expression is mediated via a similar signaling pathway. Regardless of this, despite an interval of over two decades since the first description of MUP expression in the mammary gland, a functional role has still not been elucidated. Although it has long been assumed that MUP synthesis occurs in the secretory epithelium of expressing organs, our observation that these molecules are upregulated during puberty (with a corresponding approximately threefold downregulation following puberty, data not shown) suggests that their functional role may not be limited to the secretory function of the gland. Delta-like kinase (Dlk1) is a member of the epidermal growth factor (EGF) superfamily [ 37 ] that is encoded on murine chromosome 12 [ 38 ]. Dlk1 is one of several genes showing substantial (greater than fivefold) downregulation from 2 to 5 weeks of murine mammary gland development. As this gene was first identified as a preadipocyte transcript that is downregulated during subsequent differentiation [ 38 ], we hypothesize that its relatively high expression during the neonatal period reflects ongoing differentiation of the mammary fat pad. This kinase has also been shown to have a role in other developmental contexts, specifically within neuroendocrine tissues. Further work will be required to elucidate its specific role in the mammary gland. Notable, however, is the corresponding downregulation (more than 10-fold) of Meg3/Gtl2 , a noncoding RNA that is reciprocally imprinted with Dlk1 [ 26 ]. This Dlk1-Meg3/Gtl2 regulation has been compared with Igf2-H19 , another tandem pair of reciprocally imprinted genes in which one member produces a noncoding RNA [ 27 , 39 ]. Interestingly, both Igf2 and H19 are also downregulated during this time period, suggesting the hypothesis that a common regulatory mechanism exists for the tandem control of both imprinted genes at these loci. It will be particularly important to determine whether there is functional significance to this Igf2-H19 regulation, or whether it reflects the epiphenomenal byproduct of a mechanism designed to downregulate Dlk1 during adipocyte development. Conclusions We have developed two novel algorithms for the analysis of Affymetrix oligonucleotide microarray data. We have validated these algorithms by using empirically derived distributions from control animals to calibrate their statistical significance. These control data, which reflect both experimental and biological sources of variability likely to be representative of many mammalian experimental systems, should facilitate further work in this area. For triplicate samples, Intersector appears to provide the most sensitivity at a given threshold of statistical significance, and its performance is substantially superior to other widely used methods including the t -test, SAM, dChip, and logit-T. However, its lack of scalability, along with the baseline time required for processing, make it unsuitable for larger numbers of replicates. ChipStat, in contrast, provides comparable sensitivity with triplicate samples and has the capability of handling much larger numbers of replicates in order to improve the reliable dectection of small changes in gene expression. Both algorithms provide a substantial increase in the ability to sensitively detect statistically significant changes in gene expression within the context of the whole mammary gland. We have applied these techniques to the analysis of genomic patterns during early murine mammary gland development. In addition to detecting patterns reflecting known biology, we have noted the coordinate upregulation of a class of molecules not previously known to be differentially regulated in the mammary gland. We also suggest that peri-pubertal changes in the mammary gland may utilize mechanisms for tandem upregulation of multiple imprinted regions. Our observations suggest a variety of future directions for functional validation and demonstrate the utility of coupling sensitive detection of differential gene expression with pathway analysis for the elucidation of biological patterns during organogenesis. Materials and methods Animals, RNA isolation, and northern blot hybridization The third, fourth and fifth mammary glands were harvested from FVB mice at the indicated time points. Samples from 2 and 5 weeks of age reflect triplicate pools of 10 animals at each time point (total 60 animals). In addition, tissue from 18 control animals was harvested when they were 6 weeks and 4 days old. These control animals also carry a transgenic construct consisting of the murine mammary tumor virus (MMTV) promoter upstream of the reverse tetracycline transactivator (rtTA) and had been given 2.0 mg/ml doxycycline in drinking water for 96 h before harvest. This line (previously designated MTB) has been previously described, and no developmental abnormalities have been noted [ 40 ]. All animal experimentation was conducted in accord with accepted standards of humane care, and protocols for animal work were approved by the University of Pennsylvania institutional committee on animal care. All tissue was snap frozen after removal of the lymph node present in the fourth gland, and total RNA was isolated by homogenization in guanidinium isothiocyanate and subsequent centrifugation through a cesium chloride cushion as previously described [ 41 ]. Northern blot hybridization was performed as previously described [ 42 ]. Arrays and hybridization Approximately 15-20 μ g total RNA was used for each hybridization. RNA was visualized by gel electrophoresis to ensure its integrity before analysis. Biotinylated cRNA was generated and hybridized to Affymetrix MG_U74Av2 arrays according to the manufacturer's instructions. To scale between chips, these expression values were rank ordered, and the median approximately 96% were averaged. Chips were scaled relative to each other to equalize this average value. All Affymetrix control probe sets were eliminated from analysis, yielding data from a total of 12,422 probe sets. Datasets are publicly available as CEL files designated MTB_ [ 1 - 6 ] (Additional data files 3-8 available with the online version of this paper), 2wk_G0P0_ [ 1 - 3 ] (Additional data files 9-11) and 5wk_G0P0_ [ 1 - 3 ] (Additional data files 12-14) containing results derived from control cohorts, 2-week nulliparous cohorts, and 5-week nulliparous cohorts respectively. Algorithms and software To detect differentially regulated genes, we implemented an algorithm (ChipStat) that takes identical probe pairs across two comparison groups and performs a heteroscedastic t -test. The number of probe pairs within a probe set that are significantly different ( P < p ps where p ps is a fixed value) was tabulated. We consider that a greater number of probe pairs changing in a given direction indicates a greater probability that the gene detected by the probe set is differentially expressed. If the bulk of the noise within the array data derives from pre-hybridization experimental factors (that is, E(b) + E(p); see Results section for definition), the expectation is that all probe pairs would change coordinately. That is, if there are 16 probe pairs in the probe set, we would expect (for E(b) + E(p) >> E(h)) that under the null hypothesis (no change in gene expression) either 0/16 or 16/16 probe pairs should change significantly (at frequencies of approximately 1 - p ps and approximately p ps , respectively). Conversely, if the bulk of the noise derives from hybridization to individual probe cells (that is, if E(b) + E(p) << E(h)), then the number of probe pairs r that change within a given probe set of size t can be approximated by the binomial distribution: However, under experimentally realistic conditions, neither of these limiting cases is likely to apply. Therefore, to empirically determine the null distribution using six independent, biologically identical control populations, all pairwise three by three combinations were compared and the number of probe pairs changing was tabulated. To determine the expected number of changes per probe set when fewer than 16 probe pairs are available, these analyses were repeated after randomly discarding 1, 2...15 probe pairs. In this way, a similar statistical estimate was obtained for the 602 probe sets on the MG_U74Av2 array that have fewer than 16 probe pairs per probe set. A conservative simplification of these data was performed by rounding up the significance of changes in these 602 probe sets to the nearest appropriate bin in the 16 probe pair per probe set curve. A Microsoft Windows-compatible application implementing the ChipStat algorithm is freely available for academic use [ 43 ]. On the basis of the simplified statistical model described, a Monte Carlo simulation was implemented to determine the number of expected false-positive values as a function of p ps for various relative proportions of E(b) + E(p) and E(h). Briefly, a random test dataset was generated in which equal gene expression was perturbed by Gaussian noise (representing E(b) + E(p)). Each expression value was then independently perturbed 16 times (representing 16 probe pairs/probe set) by another Gaussian noise function (representing E(h)), and comparisons were tabulated using the ChipStat algorithm. This simulation was implemented in C and the source code is available [ 43 ]. All values reported reflect the mean of 100 trials, where each trial simulates 11,820 probe sets with 16 probe pairs each. The relative contributions of E(b) + E(p) and E(h) were estimated by maximizing the likelihood function: with respect to (E(b) + E(p)) / E(h) where x i is the number of times i probe pairs increased significantly and μ i and σ i represent the mean and standard deviation from the Monte Carlo simulations. A separate algorithm (Intersector) uses pairwise calls of differential gene expression derived from Affymetrix Microarray Suite (MAS) analysis. All pairwise comparisons were performed (that is, 3 × 3 = 9 comparisons for a 3- vs 3-replicate comparison) using the manufacturer's default settings, and the number of 'increases' or 'marginal increases' was tabulated. Similarly to the ChipStat method described above, the null distribution was generated by tabulating results from all 20 distinguishable 3 vs 3 combinations of the six control samples. Results were obtained using both MAS version 4 (MAS4) and MAS version 5 (MAS5), as indicated in the text and figures. Tests for differential gene expression using a homoscedastic t -test or SAM [ 11 ] were performed using signal values derived from MAS5. SAM results were obtained using software obtained from its authors [ 44 ]. Because the analyses described are reported as a function of the number of genes expected to increase by chance (essentially a one-tailed test of significance), the false-discovery rate reported by SAM was multiplied by 0.5 to derive a corrected false-positive rate (false-increase rate). dChip analysis [ 8 ] was performed using software available from its authors [ 45 ], and a PM-only expression model was constructed. Logit-T analysis [ 10 ] was performed using software provided by its authors and compiled to run locally on an AMD Linux server. Both dChip and Logit-T significance values were empirically calibrated by analyzing all possible 3 vs 3 combinations of control arrays (20 total) and tabulating the average number of false positives as a function of the reported significance. Association with biological annotation Associations between GO [ 19 ] annotation and lists of differentially expressed genes were identified using EASE [ 20 ]. Multiple testing correction was performed using within-system bootstrapping, and a final cutoff of P < 0.05 was used to identify statistically significant associations. Additional data files The following additional data are available with the online version of this paper. Additional data file 1 contains a table showing ChipStat and Intersector in combination. For each level of stringency available, the pairwise intersection of ChipStat (CS, p ps = 0.05) and Intersector (IT, MAS5) lists of significantly increasing probe sets was generated. Rows indicate the threshold number of probe pairs (0-16) significantly increasing from ChipStat, and columns indicate the threshold number of Increase or Marginal Increase calls (0-9) identified by Intersector. ( a ) Number of increasing probe sets in 2- vs 5-week murine mammary gland. Selected results correspond to values plotted on the y axis of Figure 4d (number of probe sets increasing). ( b ) Average number of increasing probe sets using all 3 × 3 combinations of 6 negative control samples. Selected results correspond to values plotted on the x axis of Figure 4d (expected number of probe sets increasing by chance). Additional data file 2 contains a table showing differential gene expression in 2- vs 5-week murine mammary gland using a hybrid ChipStat/Intersector approach. The criteria ChipStat p ps = 0.05, 6/16 probe pairs increasing and Intersector 7/9 increases + marginal increases, were used to identify lists of probe sets that are up- and downregulated from 2 to 5 weeks of FVB female murine mammary gland development. Additional data files 3 , 4 , 5 , 6 , 7 and 8 contain six control files containing CEL file data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment. Additional data files 9 , 10 and 11 contain three CEL files of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized with mammary gland RNA from independent pools of 10 female FVB mice harvested at 2 weeks of age. Additional data files 12 , 13 and 14 contain three CEL files of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to mammary gland RNA from independent pools of 10 female FVB mice harvested at 5 weeks of age. Supplementary Material Additional data file 1 A table showing ChipStat and Intersector in combination Click here for additional data file Additional data file 2 A table showing differential gene expression in 2- vs 5-week murine mammary gland using a hybrid ChipStat/Intersector approach Click here for additional data file Additional data file 3 Control file 1 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 4 Control file 2 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 5 Control file 3 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 6 Control file 4 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 7 Control file 5 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 8 Control file 6 containing CEL data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to RNA from the third to fifth mammary glands harvested from independent pools of three female MTB transgenic mice at 6 weeks 4 days old after 96 hours of doxycycline treatment Click here for additional data file Additional data file 9 CEL file 1 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized with mammary gland RNA from independent pools of 10 female FVB mice harvested at 2 weeks of age Click here for additional data file Additional data file 10 CEL file 2 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized with mammary gland RNA from independent pools of 10 female FVB mice harvested at 2 weeks of age Click here for additional data file Additional data file 11 CEL file 3 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized with mammary gland RNA from independent pools of 10 female FVB mice harvested at 2 weeks of age Click here for additional data file Additional data file 12 CEL file 1 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to mammary gland RNA from independent pools of 10 female FVB mice harvested at 5 weeks of age Click here for additional data file Additional data file 13 CEL file 2 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to mammary gland RNA from independent pools of 10 female FVB mice harvested at 5 weeks of age Click here for additional data file Additional data file 14 CEL file 3 of data from Affymetrix MG_U74Av2 oligonucleotide microarrays hybridized to mammary gland RNA from independent pools of 10 female FVB mice harvested at 5 weeks of age Click here for additional data file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC551540.xml |
406395 | A Gene That Directs the Regeneration of Injured Muscle from Adult Stem Cells | null | If the United States' Human Cloning Prohibition Act of 2003 (H.R. 534) becomes law, American researchers practicing any form of cloning could face up to ten years in prison and a minimum $1 million fine. The bill criminalizes a research procedure, called somatic cell nuclear transfer, that involves removing the DNA from a fertilized egg and replacing it with the DNA of a body (soma) cell. While the procedure could theoretically be used to clone a human being, used therapeutically its great promise lies in yielding a renewable source of stem cells to repair and regenerate tissue damaged by disease or injury. Embryonic stem cells appear most suited to this task, but some researchers are finding that adult stem cells could perform similar duties in certain tissues. And adult stem cells, it appears, are responsive to genetic manipulation. H.R. 534 does not threaten researchers working with adult stem cells. Pax7-infected stem cells rescue dystrophin expression The precise origin of adult stem cells is unclear, though some propose that they are “set aside” during embryonic development and sequestered in mature tissue. These cells, which can make identical copies of themselves or give rise to specialized cells, serve primarily to replace damaged or injured cells. Skeletal muscle has a remarkable capacity to regenerate following exercise or injury and harbors two different types of adult stem cells to accomplish the job: satellite cells and adult stem cells that can be isolated as side population (SP) cells. Like embryonic stem cells, the adult cells commit to a certain fate once particular genes are activated. It was thought that only satellite cells could mediate skeletal muscle regeneration until recently, when scientists found that adult stem cells not only participate in muscle tissue regeneration but also spawn satellite cells. A certain population of these stem cells, which are recognized by the cell surface proteins CD45 and Sca1 (stem cell antigen-1), is involved in normal muscle tissue repair, but is only triggered into the muscle cell development pathway by injury. The question then arises: what molecular factors turn these adult stem cells into muscle cells? Now Michael Rudnicki and colleagues have shown that one gene, Pax7, plays a crucial role in directing the differentiation of these adult stem cells into skeletal muscle cells. In previous studies, Rudnicki's group demonstrated that Pax7 is required to turn adult stem cells into myogenic cells during regeneration. Here, the researchers worked with mouse models and in vitro experiments to investigate which cell populations Pax7 targets and how the gene initiates muscle cell formation in injured tissue. They show that CD45:Sca1 cells taken from regenerating muscle in mice lacking the Pax7 gene could not become muscle cells. And they show that by putting Pax7 back into CD45:Sca1 cells taken from uninjured muscle, they can generate a population of proliferating myoblasts that readily differentiate into muscle cells. When CD45:Sca1 cells engineered to express Pax7 proteins were injected into the muscles of mice lacking dystrophin (the protein defective in muscular dystrophy), the cells differentiated, forming dystrophin-expressing muscle cells in the defective muscle. This shows that engineered “donor cells” can differentiate in living tissue and help repair dystrophic muscle. When the researchers injected Pax7 (using a gene therapy virus) into the damaged muscle of mice lacking Pax7 , they observed the production of muscle-forming cells that not only gave rise to differentiated muscle cells, but also aided in tissue repair. The researchers argue that these results “unequivocally establish” Pax7 as a key regulator of muscle cell differentiation in specific populations of adult stem cells during muscle tissue regeneration. If therapeutic strategies that activate Pax7 in adult stem cells can turn them into muscle cells, effectively replenishing injured or diseased muscle tissue, there's hope of reversing the debilitating effects of progressive muscle-wasting diseases. Though the clinical efficacy of such an approach will require intensive investigation, the results on these adult stem cells are encouraging—especially in this political climate. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC406395.xml |
368165 | A Single Mutation Transforms an Iron Transporter into an Ion Channel | null | Trace heavy metals are essential for a number of metabolic reactions in living systems, but cells walk a fine line between feast or famine. While iron, zinc, cobalt, and manganese, for example, contribute to the catabolic activity of enzymes involved in essential pathways from gene regulation to cell signaling, even a mild surplus of these metals can kill cells and cause a variety of diseases. Maintaining the proper concentration, or homeostasis, of cellular metals requires strict policing of what passes through cell membranes and organelles. A single mutation of the amino acid glycine (G) to arginine (R) turns a membrane transporter into a calcium channel One way cells regulate entry is through the hydrophobic lipid (fatty) layer that makes up the cell membrane. While the lipid membrane allows most small fat-soluble or uncharged molecules to simply diffuse through it, nearly all water-soluble molecules, including metal compounds—which typically break down into ions (molecules with positive or negative charge) in solution—rely on either transport or channel proteins to get through. Two types of proteins manage the transport and uptake of iron ions in mammalian cells: the transferrin receptor helps to concentrate iron in discrete intracellular compartments called endosomes, while a protein called divalent metal transporter-1 (DMT1) releases iron into the cytoplasm, where it supports essential metabolic processes. DMT1 also serves to bring dietary iron directly into the intestinal cells involved in iron absorption. DMT1 preferentially carries iron, zinc, copper, and manganese, but not calcium. This selectivity helps strike the right balance of the concentration of these metals in the cell. Recent structural analyses of transporters, however, have raised the possibility that this selectivity may not be as fixed as once thought. Lending support to the notion that the distinctions between transporters and ion channels are blurring, David Clapham, Nancy Andrews, and colleagues report that a mutation causing a single amino acid substitution in the DMT1 metal ion transporter opens a passageway that converts the transporter into a calcium channel. DMT1 is essential for maintaining iron homeostasis and the only molecule known to facilitate transmembrane iron uptake in higher eukaryotes, including humans. It is expressed mainly in epithelial cells of the small intestine, where iron metabolism is monitored, and in endosomes, which release transferrin-imported iron. The Clapham and Andrews groups focused on a mutation in the DMT1 transporter called G185R—which substitutes the arginine (R) amino acid for glycine (G) at a particular location in the protein's amino acid chain, position 185—because the identical mutation has occurred spontaneously in three separate laboratory strains of rodents (two mouse and one rat strain). That a single substitution has arisen independently and persisted in multiple rodent generations suggests it may confer some type of selective advantage. To investigate this idea, the researchers compared the properties of “wild-type” (nonmutant) DMT1 and mutant G185R in laboratory cell lines. They found that cells expressing G185R mutant proteins had much lower levels of iron uptake than cells expressing the nonmutant proteins, but that they also permitted the influx of calcium ions. To see whether the G185R-mediated calcium permeability had a physiological effect on the mice with this mutation, the researchers compared the properties of intestinal epithelial cells taken from the mutant and nonmutant animals. The intestinal cells in the mutant mice showed high levels of the G185R protein and a large current of charged molecules—much as would occur in an ion channel. This current was observed in both the cell lines expressing G185R and the cells extracted from the G185R mutant mice. The G185R mutation, the researchers conclude, appears to either expose or enhance a calcium “permeation pathway” that exhibits the properties of a calcium channel. This transformation appears to offer a selective advantage, since mice engineered without the DMT1 protein die within a week of birth while mice born with the G185R DMT1 mutation can live for over a year. Though the G185R mice exhibit severe iron deficiency, the modest function retained by G185R in combination with the increased influx of calcium may be enough to extend their lifespan. The increased levels of calcium, the researchers propose, may support iron uptake through some other pathway, an advantage that might explain why such a mutation would persist. Whatever mechanism accounts for this advantage, the G185R mutation transforms DMT1 transporter into an “unambiguous” calcium ion channel. Investigating the structural and biochemical properties of this molecular changeling will provide valuable insights into the emerging model of a transporter–channel continuum—which suggests a remarkable adaptability to shifting environmental conditions. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368165.xml |
538284 | Increase of malaria attacks among children presenting concomitant infection by Schistosoma mansoni in Senegal | Helminthic infections concomitant with malaria are common in inter-tropical areas. A recent study showed that mice co-infected with Schistosoma mansoni and Plasmodium chabaudi develop higher P. chabaudi parasitaemia and had a higher mortality rate. This important observation deserved to be further investigated among human populations. Malaria attacks were recorded in 512 children aged 6–15 years living in Richard Toll (Northern Senegal) among whom 336 were infected by S. mansoni , and 175 were not. The incidence rate of malaria attacks was significantly higher among S. mansoni -infected individuals, particularly those carrying the highest worm loads, as compared to uninfected subjects (26.6% versus 16,4 %). In contrast, the rate of malaria attacks was lower, without reaching significance, in medium grade S. mansoni infections. Thus, infection by S. mansoni affects susceptibility to malaria, but this can vary according to the intensity of parasite load. The immunological mechanisms underlying this dual effect need to be further explored. | Introduction Malaria is prevalent in many parts of tropical Africa, where other concomitant parasitic infections are common. However, little is known about how concurrent infections affect the expression to and/or pathogenesis of each other. A recent study showed that Schistosoma mansoni and Plasmodium chabaudi co-infected mice develop higher P. chabaudi parasitemia and higher mortality rate [ 1 ]. This observation was supported in the case of human infections in subjects carrying intestinal helminths who were given Levamisole which led to the reduction of the malaria attack rate [ 2 ] and by further studies in helminth-free and helminth-carrying malaria-exposed individuals, which confirmed the deleterious effect of worm carriage upon an individual's susceptibility to malaria [ 3 ]. In the Senegal river basin, where malaria is hypoendemic, extensive irrigation programmes have been developed, promoting a spread of S. mansoni infection [ 4 ]. The exposure of the inhabitants to these two infections, in a situation where other helminthic infections were rare, provided an opportunity to study the expression of malaria in a schistosoma exposed population. Patients and methods Study area The study took place in Gallo Malick, a district of Richard Toll, which is located near a canal ensuring the irrigation of rice and sugar cane fields. The population was estimated in 1998 to reach 3,685 inhabitants. Annual rainfall amounts to around 250 mm water. The district is approximately 1 km long and 500 m wide. A dispensary is set up in the centre of the district and is thus easily accessible. Population study In September 1998, after obtaining agreement from the parents, two stools examinations were carried out in all children aged between 5 and 15 years. From 25 mg of stools, two slides were prepared, according to the modified Kato-Katz method [ 5 ]. The parasitic burden was obtained by multiplying the average value of the burden of the two slides by 40 to express the result in the number of eggs per gram of stools. Children were given a card that entitled them to have free access to the health centre. For each consultation motivated by an episode of fever or an history of fever within 24 hours, a thick smear was performed. Thick smears prepared from capillary blood were examined over 200 microscopic fields. The average number of leucocytes per field was estimated in 10 fields. Parasite density was evaluated based on an average 8,000 leukocytes per μl of blood. Following national recommendations, any fever attack was considered suspect of malaria and treated by chloroquine (25 mg/kg over three days in a 10-10-5 posology), as the drug which was still effective in this area at that time. The follow-up was implemented between September 1998 and April 1999. In January 1999, a further stool examination and a urine filtration for the detection of Schistosoma haematobium eggs, were performed. Ten ml of urine were filtered through a 12 μ millipore membrane and the eggs on the whole filter surface were counted. A questionnaire was issued to check habits with regard to protection against mosquitoes and usage of anti-malarial drug-prophylaxis. It was also ascertained that none of the included children had been administered anti- S. mansoni treatment (praziquantel) over the past year (September 97 – September 98). In March 99, all children who presented with at least one S. mansoni positive stool examination were treated with praziquantel (40 mg/kg). Any child presenting with a body temperature > 38°C or having a history of fever-in the 24 hours preceding the consultation and with a parasite density ≥ 5000 parasites/μl of blood was defined as suffering from a malaria attack. Any child whose tool tested positive for S. mansoni at least once was defined as S. mansoni positive. If both examinations proved positive, the highest parasitic burden was kept for further analysis. Parasite loads were classified into four categories: A) 1 to 100, B) 101 to 400, C) 401 to 1000, and D) > 1000 eggs per one gram of stools. In order to exclude possible interactions with other helminthic infections, children from the group not infected by S. mansoni but presenting other intestinal parasitic infection were excluded from the analysis. When houses where children had a malaria attack and those where the children were carrying schistosomiasis were located on a map, the two pathologies were found to be distributed in a uniform way in the whole district, without evidence of clustering of double infection malaria- S. mansoni . This is in agreement with the distinct sources of infection, Anopheles larvae breeding in small water collections in gardens, and Schistosoma vectors in rice fields and irrigation canals. Comparison between children presenting at least one malaria attack and children not having presented any malaria attack was performed using a forward logistic regression model using STATA statistical software. The variables included in the model were sex, S. mansoni categories eggs load and age. The period between the beginning of the study and the date of a malaria attack was compared between groups of S. mansoni infections using a lifetime estimate table from the EGRET programme (Statistics and Epidemiology Research Corporation, Seattle, Washington). Any p value lower than 0.05 was considered significant. Results In September 1998, 525 children underwent two stool examinations. Three-hundred and thirty-six-were found to carry S. mansoni eggs and 189 were negative for both stool examinations. Urine filtration detected only 13 children excreting eggs of Schistosoma haematobium (2.7%). Among them, 11 were also positive for S. mansoni . The stool examination showed the presence of 31 other intestinal parasitic infections (Ascaris and Trichuris). Patients negative for S. mansoni and carriers of another intestinal (12 subjects) or urinary parasite (2 subjects) were excluded of the analysis. In total, 511 children were included in the analysis (336 infected by S. mansoni (65.7%) and 175 (34.3%) not infected). The prevalence increased as a function of age, reaching 80% in children older than 11 years with > 30% of children presenting with high schistosome loads, i.e. > 1,000 eggs/ 1 g of stools. The malaria index was 11.2% in September, 8.1 % in October, 8.6 % in November and 5% in February. Malaria attacks were detected by passive case detection, ie as out-patients at the dispensary. Among 262 of the cohort patients consulting for fever, 107 cases (40.8 %) were attributed to a malaria attack, according to the criteria described. Only 10 children underwent two malaria attacks. In total, 18.9 % (97/511) of the children included in the analysis presented with a malaria attack at least once. Chemoprophylaxis for children is not recommended by the National Control Programme, but 7.9 % of the parents reported that they were giving a chemoprophylactic treatment to their children. 58.9 % stated they used a mosquito bednet. These proportions were the same in the two groups of children, infected by S. mansonii or not. However, the malaria attack prevalence was also the same whether or not the children were sleeping under a mosquito bednet. The incidence rate of malaria attacks was 20.2 % (68/336) in the group of children concomitantly infected by S. mansoni and 16.6% (29/175) in those non-infected (p = 0.40). The malarial incidence, however, varied depending on the load of eggs. It was high in all groups, but the highest (26.6 %) in those carrying the highest worm loads (> 1,000), except in subjects presenting medium loads (>100 and < 400 eggs/g of stools) where malarial incidence was lower than in S. mansoni negative individuals (9.4 %). Sex and age had no significant influence, which is not surprising since this is a mesoendemic area. Using a logistic regression model and taking the negative group as reference, the difference was significant with the group carrying a high load of eggs (RR = 2.24 (1.2 – 4.2) (Table I ). Among all S. mansoni positive individuals, and using the group with medium egg load as reference (lower incidence of malaria attacks), the malaria incidence was significantly increased for low S. mansoni egg carriage (1–100) (RR = 2.51 (1.05–6) as well as high S. mansoni egg carriage (>1,000) RR = 3.12(1.33–7.29). Table 1 Logistic regression model for malaria attack adjusting for sex, age and load in eggs of S. mansoni /g of stools, n = 511, Richard Toll, Senegal, 1999 Odds Ratio P>|z| [95% Conf. Interval] Sex* .72 0.16 .46–1.13 Egg's load** 1–100 (n = 99) 1.82 0.06 .97 – 3.42 101–400 (n = 73) .72 0.46 .31 – 1.70 401–1000 (n = 55) 1.46 0.35 .66 – 3.25 > 1000 (n = 109) 2.24 0.01 1.20–4.20 Age .99 0.79 .92–1.07 *Female, ** Non-infected children as reference, n = number of subjects in each group Out of 10 children who presented two malaria attacks, nine were infected by S.m.; four presented a schistosome load higher than 1,000 eggs/g of stools, and three > 400 and <1,000. The cumulative incidence of malaria attacks based on the Kaplan-Meier analysis according to the day of follow-up shows that the difference between subjects carrying high S. mansoni loads and other groups increased over time during the follow-up (Fig 1 ). This difference is particularly clear over the first ten weeks. Figure 1 Probability of not having had a malaria attack in children presenting S. mansoni infection or without S. mansoni infection Discussion The high prevalence of S. mansoni and the low prevalence of urinary schistosomiasis in the area studied are in agreement with previous reports [ 4 , 6 , 7 ]. The prevalence of intestinal helminths, such as Ascaris and hookworms, was also low. The high prevalence of S. mansoni , together with a low prevalence of other helminthic infections, including S. haematobium , make this area suitable for studying the influence of S. mansoni upon P. falciparum infection. Malarial indices were consistently lower than 20 %, in agreement with previous studies which classified this northern Sahel area as meso-endemic [ 8 , 9 ]. Entomological studies suggest that this low endemicity could to be due to the dominance of Anopheles pharoensis , which is a poor vector in view of its short life-expectancy [ 10 , 11 ]. The analysis of the incidence of the malaria attacks by amount of parasite load in S. mansoni eggs suggests a more complex mechanism than a simple linear link between the frequency of malaria infection and the degree of infestation by S. mansoni . Indeed, the data show a greater rate of malaria attacks in children with either a high load (> 400 and > 1,000) or a low load of eggs (1–100), whereas a lower attack rate was observed in children presenting a medium egg load (>100 and <400 eggs/g), although this opposite trend did not reach significance. Protection against falciparum malaria has been found to be associated with the preferential production of the cytophilic classes, IgG1 and IgG3, of antibodies [ 12 ], this being related to their ability to cooperate with blood monocytes in an ADCC-like (Antibody-Dependant Cellular cytotoxicity) mechanism [ 13 ]. Conversely, the very long delay needed to reach a state of protection was associated with the preferential production of non-cytophilic classes of antibodies, such as IgG2, IgG4 and IgM [ 13 ]. This also immediately raised the question of why the immune response to falciparum malaria is channeled to non-cytophilic classes in children and led to formulate the hypothesis that it could be related to helminthic co-infections, which are known to induce a Th2-like type of response. Indeed, children are prone to much higher helminthic loads than are adults. In Madagascar, a study conducted in children carrying intestinal helminths and treated with levamisole, suggested after a two-years follow-up, that a three-fold decrease in malaria attack rate was induced in helminth-treated subjects, as compared to non-treated paired controls [ 2 ]. These initial results were confirmed by more recent studies in which levamisole was not used [ 3 , 14 ]. In the present study, this observation has been confirmed with yet another worm infection, S mansoni , but only for those having the highest loads. The opposite effect was found in individuals carrying medium schistosome infections. As immunological studies could not be performed, one can only speculate about this biphasic effect. The production of cytophilic classes against malaria requires that the T-cells helper effect is provided by Th1 type of T-cells, however cytokines produced by T-cells specific for schistosome eggs or worms can influence responses to malaria. It has been reported that, during the first phase of S. mansoni infection, T-cells are stimulated which secrete cytokines belonging, in majority, to the Th1 type. The switch towards Th2 type cytokines occurs later on and is dependent on egg production [ 15 ]. In the case of this study, medium grade egg deposition may not be sufficient to modify the initial Th1 type of response, which would be dominant, contribute to accentuate the Th1 response to malaria and, therefore, to increase protection against malaria. Conversely, in subjects with high egg production, Th2 would become dominant and contribute to drive the antimalarial immune response towards non-cytophilic classes. An alternative hypothesis could be that lower egg-output actually reflects strong granuloma formation which, itself, is Th1 related, and conversely the high egg-output would indicate a Th2 type of response. Whereas this may account for the difference observed between medium and high worm load, it still does not provide an explanation for the increased susceptibility to malaria in the group excreting the lowest number of S. mansoni eggs. Obviously, further studies, particularly of T-cell responses to both malarial and schistosome antigens are required to sort out this issue. Conclusions Helminthic infections are a fact of life in malaria endemic areas and their influence on the course of infection and the epidemiology of malaria is a fascinating though neglected area of research. This study shows that S. mansoni infection can increase the susceptibility to malaria in subjects excreting high schistosome egg loads. Contribution of authors CS, PM, JA, PC, MD were responsible for field and laboratory studies. JYL was responsible for the statistical analysis. PD inspired and designed the study | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538284.xml |
529438 | TETRA: a web-service and a stand-alone program for the analysis and comparison of tetranucleotide usage patterns in DNA sequences | Background In the emerging field of environmental genomics, direct cloning and sequencing of genomic fragments from complex microbial communities has proven to be a valuable source of new enzymes, expanding the knowledge of basic biological processes. The central problem of this so called metagenome-approach is that the cloned fragments often lack suitable phylogenetic marker genes, rendering the identification of clones that are likely to originate from the same genome difficult or impossible. In such cases, the analysis of intrinsic DNA-signatures like tetranucleotide frequencies can provide valuable hints on fragment affiliation. With this application in mind, the TETRA web-service and the TETRA stand-alone program have been developed, both of which automate the task of comparative tetranucleotide frequency analysis. Availability: Results TETRA provides a statistical analysis of tetranucleotide usage patterns in genomic fragments, either via a web-service or a stand-alone program. With respect to discriminatory power, such an analysis outperforms the assignment of genomic fragments based on the (G+C)-content, which is a widely-used sequence-based measure for assessing fragment relatedness. While the web-service is restricted to the calculation of correlation coefficients between tetranucleotide usage patterns of submitted DNA sequences, the stand-alone program generates a much more detailed output, comprising all raw data and graphical plots. The stand-alone program is controlled via a graphical user interface and can batch-process a multitude of sequences. Furthermore, it comes with pre-computed tetranucleotide usage patterns for 166 prokaryote chromosomes, providing a useful reference dataset and source for data-mining. Conclusions Up to now, the analysis of skewed oligonucleotide distributions within DNA sequences is not a commonly used tool within metagenomics. With the TETRA web-service and stand-alone program, the method is now accessible in an easy to use manner for a broad audience. This will hopefully facilitate the interrelation of genomic fragments from metagenome libraries, ultimately leading to new insights into the genetic potentials of yet uncultured microorganisms. | Background At present, a majority of the microbes from natural microbial communities cannot be transferred into pure cultures, either because proper cultivation conditions have yet to be found, or due to currently unidentified fundamental obstacles [ 1 ]. For decades, this has limited our understanding of the functioning of microbes within their natural habitats, such as their metabolic roles, interactions and dependencies. The metagenome-approach allows for the first time to circumvent the restrictions imposed by the limited culturability of environmental microorganisms [ 2 ]. Now, DNA fragments of 40 – 150 kb of uncultured microorganisms can be cloned directly from the environment. This delivers insights into the microorganisms' genetic potentials, sometimes even allowing the reconstruction of entire genomes. Prominent example include the unexpected finding of bacteriorhodopsin in marine Gammaproteobacteria [ 3 - 6 ], and the almost complete reconstruction of two bacterial genomes from an acid mine drainage microbial biofilm [ 7 ], respectively. However, the metagenome-approach is not without its limitations and problems. A major constraint is that especially small genomic fragments, as are obtained from libraries that have been constructed with fosmids or cosmids as cloning vectors, often lack suitable phylogenetic marker genes. This leads to the problem that fragments belonging to the same organism cannot be reliably identified as such unless they overlap. In order to nonetheless interrelate such genomic fragments, measures such as the (G+C)-content or BLAST hits and codon usage of the fragment's coding regions are commonly used to assess whether two unlinked fragments from a metagenome library belong to the same organism. These measures, however, can produce ambiguous or even misleading results, and should be supplemented by additional tools that assess the relatedness of the genomic fragments [ 8 ]. Since numerous studies have shown that oligonucleotide frequencies within DNA sequences exhibit species-specific patterns [ 9 - 18 ], comparative analysis of such oligonucleotide frequencies is a promising approach to this problem. For tetranucleotides, it has even been demonstrated that their frequencies carry an innate but weak phylogenetic signal [ 19 ]. Comparative analysis of tetranucleotide usage patterns also provides a good balance between computational requirements and attainable resolution. This makes the method particularly well-suited for use as a high-throughput method that can assist in tackling the fragment identification problem in metagenomics [ 8 ]. In order to automate and facilitate such an analysis, the TETRA software suite was developed, comprising both, a web-service and a stand-alone program. Implementation The algorithms that are used within TETRA have been described elsewhere [ 8 ]. In brief, DNA sequences are extended by their reverse-complements to compensate for different patterns of tetranucleotide over- and underrepresentation between the leading and the lagging strand. Then, the frequencies of all 256 possible tetranucleotides are counted and the corresponding expected frequencies are calculated by means of a maximal-order Markov model from the sequences' di- and trinucleotide composition. In order to evaluate the significance of the level of over- or underrepresentation for each tetranucleotide, the divergence between the observed and expected tetranucleotide frequencies is then transferred into z-scores using an approximation published by Schbath [ 20 , 21 ]. Finally, all DNA sequences are compared in pairs by computing the Pearson's correlation coefficient of their z-scores. Details on the method, its applicability and its limits are given in Teeling et al. (2004) and the TETRA online manual. The TETRA web-service [ 22 ] has been implemented as set of PERL CGI scripts. Access is free to all users. A multi-headed FASTA file with DNA sequence data can be uploaded (actual file size limit: 2 Mb) and after having entered a valid e-mail address, the calculation can be started (Figure 1 ). Results are sent to the respective e-mail address as a tab-delimited crosstabulation of correlation coefficients in plain text format. The TETRA stand-alone program can be downloaded for free from the TETRA website [ 23 ]. The current release has been implemented in REALbasic ( REAL Software Inc., Austin, Texas) and is available for Mac OS X. Versions for Linux and Windows are also available, but differ in details regarding their implementation and features. The counting of the tetranucleotides in the current version of TETRA stand-alone program is done by ocount – a self-written C program that has been integrated into the program. Results and discussion TETRA web-service The TETRA web-service computes correlation coefficients between tetranucleotide usage patterns of DNA sequences, which can be used as an indicator of sequence relatedness. Details on the in- and output formats is available in the comprehensive online documentation [ 22 ]. TETRA stand-alone program The stand-alone version of TETRA has many additional features that are not available via the TETRA web-service. Firstly, it comes with pre-computed tetranucleotide usage patterns of all 166 prokaryote chromosomes that were publicly available by June 2004 (Figure 2 ). These patterns have been incorporated into the program to provide the user with reference data that can also be used to get familiar with the program. With a few mouse clicks, correlation coefficients for the tetranucleotide usage patterns of all genomes can be computed and exported into PHYLIP format [ 24 ]. While not being well-suited for phylogenetic reconstruction, the resolution boundaries of the method can be easily evaluated by looking at the resulting whole genome trees. Secondly, besides calculating correlation coefficients for tetranucleotide usage patterns, the TETRA stand-alone program allows the user to investigate the raw data (Figure 2 ) and can produce plots for a more detailed analysis of tetranucleotide over- and underrepresentations (Figure 3 ). This allows for hints into possible restriction sites by the examination of significantly underrepresented tetranucleotides. Tetranucleotide usage patterns for user-provided sequences can be generated in two ways. Single sequences shorter than 100 kb can be pasted into the so called 'Single Sequence Window'. From there, a sequence can be extended by its reverse complement and its tetranucleotide usage pattern can be calculated. Additionally, the sequence's base composition and GC-content can be computed. Sequences longer than 100 kb or files with multiple sequences can be imported by the 'Batch Mode'. The 'Batch Mode' reads a multi-headed FASTA file and computes the tetranucleotide usage patterns of all sequences within this file in a fully automated manner. The tetranucleotide usage patterns of an average-sized genome (4 Mb) is computed in less than 10 minutes on a dual 1.8 GHz G5 (IBM PPC 970) computer. Newly computed tetranucleotide usage patterns are displayed within the 'Navigator' window, which is the central place for data management, access to the raw data and the calculation of plots and correlation coefficients (Figure 2 ). Raw data and correlation coefficients that have been computed for multiple patterns can be saved as tab-delimited tables in plain-text format and the graphical output (2D-plots) can be saved in JPEG-format. A detailed documentation of the TETRA stand-alone program and its functions is available via the program's online help system. Applicability As has been demonstrated in a previous study [ 8 ], the analysis of tetranucleotide usage patterns is often (but not always) a much more reliable measure of sequence relatedness than the (G+C)-content. However, as a sequence-based measure it is affected by local changes in sequence composition. For example, large stretches of horizontally acquired genes will blur the resolution. Likewise, resolution is a function of sequence-length, i.e. the shorter the sequence, the less meaningful a tetranucleotide frequency analysis will be. While the method works quite well for sequences in the range of 40 kb, it is certainly not suited for the analysis of single-read end-sequences, which are usually shorter than 1 kb. Since the phylogenetic signal within tetranucleotide usage patterns is faint, the method performs weakly for whole genome phylogenetic tree reconstructions. In a whole-genome tree calculated from the pre-computed 166 prokaryotic chromosomes (data not shown), organisms are mostly grouped at the species level and at the level of genera, when these are closely related (i.e. Escherichia sp., Shigella sp., Yersinia sp. or Mesorhizobium sp., Sinorhizobium sp., Bradyrhizobium sp.). However, more distantly related genera or even species with larger evolutionary distances are often not correctly clustered (e.g. Prochlorococcus sp.). Therefore, the analysis of tetranucleotide usage patterns should not be regarded as a tool to deduce phylogenetic relationships, but rather as a fingerprinting technique for genomic fragment correlation. For example, assignment of fosmid-sized genomic fragments from metagenome libraries of a microbial consortia that mediates the anaerobic oxidation of methane was possible using tetranucleotide frequency analysis, and was shown to be in perfect agreement with 16S rRNA sequence analysis [ 8 ]. Conclusions With the worldwide ongoing programs to sequence and analyze natural communities, new approaches for sequence correlation beyond G+C content, read densities and codon usage have to be developed and made available to the users. The easy to use TETRA software will facilitate this task and provide additional decision support for, e.g., fragment assignment also when complete genomes have to be assembled in environmental sequencing projects. Availability and requirements • Project name: TETRA • Project home page: • Operating system(s): Platform independent (web-service); Mac OS X (stand-alone program) • Programming language: REALbasic • Other requirements: none • License: none • Any restrictions to use by non-academics: none List of abbreviations BLAST – basic local alignment search tool megx – marine environmental genomics Authors' contributions TETRA was implemented by HT and JW, TL contributed to the TETRA web-service, MB and FOG contributed important ideas regarding implementation, features and tested the programs. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC529438.xml |
368159 | No Evidence of Neandertal mtDNA Contribution to Early Modern Humans | The retrieval of mitochondrial DNA (mtDNA) sequences from four Neandertal fossils from Germany, Russia, and Croatia has demonstrated that these individuals carried closely related mtDNAs that are not found among current humans. However, these results do not definitively resolve the question of a possible Neandertal contribution to the gene pool of modern humans since such a contribution might have been erased by genetic drift or by the continuous influx of modern human DNA into the Neandertal gene pool. A further concern is that if some Neandertals carried mtDNA sequences similar to contemporaneous humans, such sequences may be erroneously regarded as modern contaminations when retrieved from fossils. Here we address these issues by the analysis of 24 Neandertal and 40 early modern human remains. The biomolecular preservation of four Neandertals and of five early modern humans was good enough to suggest the preservation of DNA. All four Neandertals yielded mtDNA sequences similar to those previously determined from Neandertal individuals, whereas none of the five early modern humans contained such mtDNA sequences. In combination with current mtDNA data, this excludes any large genetic contribution by Neandertals to early modern humans, but does not rule out the possibility of a smaller contribution. | Introduction Despite intense research efforts, no consensus has been reached about the genetic relationship between early modern humans and archaic human forms such as the Neandertals. While supporters of “multiregional evolution” argue for genetic exchange or even continuity between archaic and modern humans ( Weidenreich 1943 ; Wolpoff et al. 1984 , Wolpoff et al. 2000 ; Duarte et al. 1999 ; Hawks and Wolpoff 2001 ), proponents of a “single African origin” of contemporary humans claim that negligible genetic interaction took place ( Cann et al. 1987 ; Stringer and Andrews 1988 ; Ingman et al. 2000 ; Underhill et al. 2000 ; Stringer 2002 ). Mitochondrial DNA (mtDNA) sequences from early modern humans would in principle be able to resolve the question of a contribution of Neandertal mtDNA to modern humans. However, human DNA is pervasive in palaeontological and archaeological remains as well as in most laboratory environments (e.g., Krings et al. 2000 ; Hofreiter et al. 2001b ; Wandeler et al. 2003 ). It is therefore currently impossible to differentiate contaminating modern DNA sequences from endogenous human DNA in human remains. Thus, although mtDNA sequences have been reported from remains of early modern humans ( Adcock et al. 2001 ; Caramelli et al. 2003 ), it is not possible to determine whether such DNA sequences indeed represent endogenous DNA sequences ( Abbott 2003 ). A related problem is that if a Neandertal fossil yields modern human-like DNA sequences, those might be discarded as putative contaminations ( Nordborg 1998 ; Trinkaus 2001 ), even if they may be endogenous and represent evidence for a close genetic relationship or interbreeding between the two groups. To explore the genetic relationship between early modern humans and Neandertals in spite of these difficulties, we made use of the fact that the four Neandertal mtDNA sequences determined to date can easily be distinguished from those of modern humans ( Krings et al. 1997 , Krings et al. 2000 ; Ovchinnikov et al. 2000 ; Schmitz et al. 2002 ; Knight 2003 ). This allowed us to ask whether all well-preserved Neandertal remains contain Neandertal-like mtDNA and whether all well-preserved early modern human remains fail to contain such DNA sequences. Thus, we did not attempt to determine DNA sequences that are similar to present-day human mtDNA. Instead, we determined whether Neandertal-like mtDNA sequences were present or absent in well-preserved remains of Neandertals and of early modern humans. Results and Discussion The preservation of endogenous DNA in fossils is correlated with the amount, composition, and chemical preservation of amino acids ( Poinar et al. 1996 ). We find that endogenous DNA can be amplified from Pleistocene remains when the amino acid content is more than 30,000 parts per million (ppm), the ratio of glycine to aspartic acid between two and ten, and the aspartic acid racemization (i.e., the stereoisomeric D/L ratio) less than 0.10 ( Poinar et al. 1996 ; Krings et al. 1997 , 2000; Schmitz et al. 2002 ; data not shown). We analyzed the amino acid preservation of 24 Neandertal and 40 early modern human fossils ( Table S1 ). Several important Neandertal fossils, such as La Ferrassie and Krapina, as well as important modern human fossils, such as Veternica, proved to be too poorly preserved to be likely to allow DNA retrieval. Thus, further destructive sampling of these specimens was not considered justified. However, four Neandertal and five early modern human fossils fulfilled the above criteria for amino acid preservation and were thus expected to contain endogenous DNA ( Figure 1 ; Table 1 ). These samples were geographically well distributed across Europe ( Figure 2 ) and included remains whose morphology is typical of Neandertals (e.g., La Chapelle-aux-Saints) and of modern humans (La Madeleine, Cro-Magnon). They also included samples that have sometimes been considered “transitional” between Neandertals and modern humans, based on their morphological features: Vindija ( Smith 1984 ) and Mladecˇ ( Frayer 1986 , Frayer 1992 ; Wolpoff 1999 ). Figure 1 Amino Acid Analyses of 64 Hominid Remains For each bone, the extent of aspartic acid racemization (D/L) and the amino acid concentration (ppm) is given. The dash lines delimit the area of amino acid preservation compatible with DNA retrieval. Circles and triangles represent early modern humans and Neandertals, respectively. The samples from which DNA extractions were performed are green (see also Table S1). Figure 2 Geographical Origin of Neandertal and Early Modern Human Samples from Which mtDNA Sequences Have Been Analyzed Filled squares and filled circles represent Neandertal and early modern human remains, respectively, analyzed in this study. The four Neandertal remains formerly analyzed are represented by empty squares. Table 1 DNA Retrieved from Late Pleistocene Fossils in This Study a For each specimen and primer pair, the number of amplifications yielding a specific product is given followed by the total number of amplification attempted b A single amplification using the indicated “Neandertal” primers was attempted. The sequence was confirmed by amplification of larger overlapping fragments (cf. Figure S1) If low amounts of DNA are preserved in a specimen, some extracts will fail to contain DNA molecules by chance ( Hofreiter et al. 2001a ). Therefore, except in the case of Mladecˇ 2, in which the amount of material available permitted only two extractions, we extracted each of the four Neandertal and the five early modern human samples three times. For each extraction, amplifications were performed using two primer pairs: (i) “hominoid primers” that amplify homologous mtDNA sequences from the previously determined Neandertals and contemporary modern humans, as well as African great apes; (ii) “Neandertal primers” that, under the conditions used, amplify only Neandertal mtDNAs even in the presence of a large excess of modern human DNA ( Krings et al. 2000 ; Schmitz et al. 2002 ). Since authentic ancient DNA is typically highly degraded, both primer pairs were designed to amplify short mtDNA fragments (72 and 31 bp, respectively, excluding primers). In each of these fragments, two substitutions allow the discrimination of previously determined Neandertal mtDNA sequences from contemporary modern human sequences. The sensitivity of both primer pairs is similar, as shown by the fact that they are both able to amplify single template molecules as judged from nucleotide misincorporation patterns ( Hofreiter et al. 2001a ). In order to determine the nature of the DNA sequences amplified, each amplification product was cloned and approximately 30 clones were sequenced for each “hominoid product” and ten clones for each “Neandertal product.” When amplified with the hominoid primers, all Neandertal and all early modern human remains yielded modern human DNA sequences (see Table 1 ). In addition, five cave bear teeth from Vindija, Croatia, and one from Gamssulzen, Austria, extracted in parallel with the hominid samples, all yielded human sequences. This confirms previous results in showing that most, if not all, ancient remains yield human DNA sequences when amplification conditions that allow single DNA molecules to be detected are used ( Hofreiter et al. 2001b ). For three Neandertal and all five modern human remains, several different mtDNA sequences were retrieved from individual extractions, and in the case of one Neandertal and one modern human, at least two of the sequences were also found in an independent extraction from the same specimen. Additionally, one of the cave bear teeth yielded a human sequence found in two independent extracts. Thus, the fact that a DNA sequence is found in two independent extracts is a necessary, but not sufficient, criterion of authenticity when human remains are analyzed. This implies that in the absence of further technical improvements, it is impossible to produce undisputable human mtDNA sequences from ancient human remains. In addition to DNA sequences identical to those previously amplified from present-day humans, the Neandertal bones Vi-77 and Vi-80 from Vindija yielded four out of 89 and 73 out of 85 mtDNA sequences, respectively, that were identical to previously determined Neandertal sequences. Thus, these two specimens contain a proportion of Neandertal-like mtDNA sequences (i.e., sequences that carry two substitutions that differentiate Neandertal mtDNA sequences from modern human mtDNA sequences as described above) that is high enough to detect using primers that amplify also modern human DNA. When amplified with Neandertal-specific primers, Neandertal-like mtDNA sequences were amplified from two independent extractions from all Neandertal fossils (see Table 1 ; Figure 3 ). For one of these, Vi-80 from Vindija, DNA preservation was sufficient to allow the retrieval of longer fragments and thus the reconstruction of 357 bp of the hypervariable region I (see Supporting Information section; Figure S1 ). This mtDNA sequence was identical to that retrieved from another bone from the same locality (Vi-75; Krings et al. 2000 ). In contrast to the Neandertal remains, none of the early modern human extracts yielded any amplification products with the Neandertal primers, although these remains are similar in chemical preservation to the Neandertal remains (see Figure 1 ). Figure 3 Sequences Obtained from the Neandertal Remains Using the “Neandertal Primers” Dots indicate identity to the human reference sequence ( Anderson et al. 1981 ) given above. The four upper DNA sequences were determined in this study. Previously determined DNA sequences are shown below. Thus, all Neandertal remains analyzed yielded mtDNA sequences that are not found in the human mtDNA gene pool today but are similar to those found in four previously published Neandertals ( Krings et al. 1997 , Krings et al. 2000 ; Ovchinnikov et al. 2000 ; Schmitz et al. 2002 ) (see Figure 3 ). This is compatible with results suggesting that the extent of Neandertal mtDNA diversity was similar to that of current humans and lower than that of the great apes ( Krings et al. 2000 ; Schmitz et al. 2002 ). It is noteworthy that this result is not an artifact created by discarding “modern-like” mtDNA sequences amplified from Neandertals ( Trinkaus 2001 ), since all Neandertal remains with good biomolecular preservation yield “Neandertal-like” mtDNA sequence. Furthermore, none of the five early modern humans yields “Neandertal-like” mtDNA sequences in spite of the fact that these remains are as well preserved in terms of amino acids as the Neandertal remains. Thus, we fail to detect any evidence of mtDNA gene flow from Neandertals to early modern humans or from early modern humans to Neandertals. However, a relevant question is what extent of gene flow between Neandertals and early modern humans the current data allow us to exclude. In this regard, it is of relevance that the five early modern humans analyzed lived much closer in time to the Neandertals than do contemporary individuals. The probability that mtDNA sequences potentially contributed to modern humans by Neandertals were lost by drift ( Nordborg 1998 ) or swamped by continuous influx of modern human mtDNAs ( Enflo et al. 2001 ) in the Neandertal gene pool is therefore much smaller than when contemporary humans are analyzed (e.g., Relethford 1999 ). In fact, the five early modern humans analyzed almost double the amount of information about the Upper Pleistocene mtDNA gene pool since, under a model of constant effective population size, all contemporary humans trace their mtDNA ancestors back to only four to seven mtDNA lineages 20,000 to 30,000 years ago ( Figure 4 A; Figure S2 ), while all other mtDNA sequences present in the gene pool at that time have been lost by random genetic drift. Since the probability is very low ( p < 0.007) that one or more of the five early modern humans analyzed here are among these few ancestors of current humans, the five Upper Pleistocene individuals can be added to the ancestors of the current mtDNA gene pool to allow us to ask what extent of Neandertal mtDNA contribution to early modern humans can be statistically excluded using the coalescent. Under the model of a constant human effective population size ( Tavare 1984 ; Nordborg 1998 ) of 10,000 over time ( Figure 4 A), any contribution of Neandertal mtDNA to modern humans 30,000 years ago larger than 25% can be excluded at the 5% level ( Figure S3 ). A more realistic scenario may be that the spread of modern humans was accompanied by an increase in population size before and during their migration out of Africa and subsequent colonization of western Eurasia (see Figure 4 B). In that case, the Neandertal contribution that can be excluded is smaller (i.e., less gene flow could have taken place), but that depends critically on when and how the expansion occurred. Finally, under the unlikely scenario that population size was constant during the migration out of Africa and colonization of Europe and expanded only after a putative merging with Neandertals, the Neandertal contribution could have been larger, but this also depends on the nature of the growth (see Figure 4 C). Figure 4 Schematic Model of Putative Contribution of Neandertal mtDNA to the Gene Pool of Modern Humans (A) Under the assumption of a constant effective population size of 10,000 for modern humans, contemporary mtDNAs trace back to approximately five mtDNA lineages 25,000 years ago. The modern human fossils represent five additional samples from around the time of putative admixture (stars). The contemporary and early modern human (EMH) samples reject a Neandertal contribution of 25% or more to modern humans about 30,000 years ago ( p ≤ 0.05). (B) Under the more realistic scenario of an expansion of the human population during and after the colonization of Europe, a smaller Neandertal contribution can be excluded because the number of ancestors of the current human gene pool was larger 30,000 years ago. However, the contribution that can be excluded would depend on when and how the expansion occurred. (C) Under the scenario that population size was constant before a putative merging with the Neandertal population and expanded only thereafter, the Neandertal contribution could have been larger, but similarly depends on how the expansion occurred. Concluding Remarks It is noteworthy that under the model of constant population size, about 50 early modern human remains would need to be studied to exclude a Neandertal mtDNA contribution of 10%. To exclude a 5% contribution, one would need to study more early modern human remains than have been discovered to date. Thus, definitive knowledge of the extent of a putative contribution of Neandertals to the modern human gene pool will not be possible, although extensive studies of variation in the current human gene pool may clarify this question ( Wall 2000 ). It is, however, worthwhile to note that samples considered as anatomically “transitional” between modern humans and Neandertals, such as Vindija ( Smith 1984 ; Wolpoff 1999 ) and Mladecˇ ( Frayer 1986 , Frayer 1992 ; Wolpoff 1999 ), analyzed here, fail to show any evidence of mtDNA admixture between the two groups. Thus, while it cannot be excluded that Neandertals contributed variants at some genetic loci to contemporary humans, no positive evidence of any such contribution has yet been detected. Materials and Methods Amino acid preservation About 10 mg of bone were removed from each specimen and analyzed as in Schmitz et al. (2002 ) with minor modifications. In brief, proteins are hydrolyzed and amino acids labeled with o -phtaldialdehyde/ N -acetyl-L-cysteine and analyzed by high performance liquid chromatography (Shimadzu, Kyoto, Japan) under conditions that separate the different amino acids as well as their stereoisomers. Eight amino acids are analyzed and their respective concentration measured: D- and L-alanine, glycine, D- and L-aspartic acid, serine, glutamic acid, valine, D- and L-leucine, and isoleucine. DNA extraction and amplification DNA extractions were performed in a laboratory dedicated to ancient DNA work. In this laboratory, positive air pressure is maintained with filtered air at all times, and all areas and equipment are treated with UV light when the laboratory is not used. A maximum of six bone or teeth samples were processed together with two blank extractions. Neandertal samples were always processed together with early modern human samples or cave bear samples. For each extraction, the samples were ground and between 30 mg and 120 mg of bone powder was extracted as in Krings et al. (1997 ). mtDNA sequences were amplified by polymerase chain reaction (PCR) using 5 μl of extract and 60 cycles. In addition, a minimum of four blank PCRs were performed together with each amplification from extracts. The “Neandertal-specific” amplification was carried out using the primers NL16230/NH16262 ( Krings et al. 1997 ) and an annealing temperature of 60°C. We consider it highly unlikely that the Neandertal-specific mtDNA fragments represent contaminations from other Neandertals, given that none of the extracts of modern humans or cave bears processed in parallel with the Neandertal remains yielded such products. The “hominoid” amplification was performed with the primers L16022/H16095 ( Krings et al. 1997 ) and an annealing temperature of 54°C. PCR products were cloned into Escherichia coli using the TOPO TA cloning kit (Invitrogen, Leek, The Netherlands), and ten or 30 clones of each amplification were sequenced on a ABI 3700 (Applied Biosystems, Foster City, California, United States). Estimation of admixture Given that previous analyses of mtDNA sequences have rejected a model of complete panmixia between Neandertals and early modern humans ( Nordborg 1998 ), we focused on the estimation of the level of admixture between Neandertals and early modern humans that can be excluded. For this purpose, we considered a population of early modern humans that merged at Tm with a (genetically different) population of Neandertal individuals (see Figure 4 ) from which point the fused population was panmictic. The probability of picking K individuals by chance in the merged population that all carry a modern human mtDNA sequence is (1 − c ) K , where c represents the Neandertal genetic contribution to the merged population. If none of n mtDNA sequences sampled in the merged population is Neandertal-like, we can exclude (at the 5% level) contributions that give a probability smaller than 0.05 of observing only modern human sequences, i.e., (1 − c ) K < 0.05. The number of ancestors of n samples at the time t is represented by a probability distribution, A n ( t ). Thus, the probability of observing only one kind of sequences in n samples becomes: where K vary from 1 to n . For a population of constant size over time, Pr(A n ( t ) = K ) has been derived in Tavare (1984 ). We estimated the number of ancestors of n samples at time t as the expected value of A n ( t ), E(A n ( t )), according to this model and calculate the probability of observing only human sequences for different values of c . Supporting Information Determination of the mtDNA Sequence of Vi-80 from Vindija, Croatia The entire hypervariable region I sequence was determined from this specimen using amplifications and clones given in Figure S1. Its sequence is identical to the sequence previously determined from individual Vi-75 from Vindija ( Krings et al. 2000 ). We could exclude cross-contamination from the old extract to this bone because different primers were used and some of the fragments of mtDNA amplified from Vi-80 were longer than those used to determine the sequence of Vi-75. Morphological analyses do not exclude that these two fragmentary bones (Vi-75 and Vi-80) may come from a single individual. Carbon-14 accelerator mass spectrometry dating, conducted in the Ångstrom Laboratory (Uppsala University, Sweden), yielded a date for Vi-80 of 38,310 ± 2,130 BP (before present). Since Vi-75 has been previously dated to over 42,000 BP ( Krings et al. 2000 ), the possibility exists that the dates overlap since 42,000 BP is within two standard deviations of the Vi-80 date. Therefore, the bone labeled Vi-80 that yields the new mtDNA sequence could either be (i) a fragment of the same skeleton (individual) that was already successfully extracted, (ii) a bone from another individual maternally related to the first individual amplified, or (iii) another unrelated individual having by chance the same mtDNA sequence, which is not unlikely given the apparently low mtDNA diversity of Neandertals ( Krings et al. 2000 ; Schmitz et al. 2002 ). Figure S1 The DNA Sequences of the Clones Used to Reconstruct the Sequence of the Mitochondrial Hypervariable Region I from the Bone Vi-80 (30 KB PDF). Click here for additional data file. Figure S2 Expected Number of Ancestors E(A n ( t )) of n Individuals under a Model of Constant Population Size of Ne = 10,000 The number of ancestors of n individuals (x axis) is estimated at 20,000, 25,000, and 30,000 years ago. For example, 150 humans living today have approximately seven ancestors 20,000 years ago. (56 KB PDF). Click here for additional data file. Figure S3 Probability of Different Levels of Admixture Probability of observing only modern human mtDNA sequences in both five early human remains and the current mtDNA gene pool given different proportion of Neandertal contribution c (x axis) under a model of constant population size (see text; Materials and Methods ). For example, the probability of observing only human mtDNA sequences given a Neandertal contribution of 25% or more is smaller than 0.05 (dotted line). (42 KB PDF). Click here for additional data file. Table S1 Results of the Amino Acid Analyses of 40 Human and 24 Neandertal Remains The bones were analyzed by high performance liquid chromatography for their amino acid content (see Materials and Methods ). The extent of racemization of aspartic acid (D-/L-Asp), the ratio of glycine to aspartic acid (Gly/Asp), and the total amount of the eight amino acid analyzed (ppm) are given for each specimen. Zero indicates values below detection level. The five human and four Neandertal specimens from which DNA extraction were performed are displayed in green. (54 KB PDF). Click here for additional data file. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368159.xml |
528726 | Combining gene expression data from different generations of oligonucleotide arrays | Background One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform. Results We first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis. Conclusions Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively. | Background By providing a genome-wide view of gene expression, microarrays have become a common exploratory tool in many areas of biological and clinical studies [ 1 - 3 ]. While there are several different microarray platforms, photolithographically synthesized oligonucleotide arrays from Affymetrix have become one of the principal technologies. These arrays feature multiple 25-mer probes (a "probe set") for each gene, with their measurements summarized into a single number for the estimated expression level of that gene. Because of the important role played by this technology, many methodological studies have focused on improving the extraction of information from these arrays, from image analysis and the proper role of perfect and mismatch probes to distributional properties of the measurements and optimal statistical tests for differential expression [ 4 , 5 ]. Large-scale gene expression data often contain a large amount of noise from various experimental factors. Fortunately, in most cases, the technical variability is relatively small compared to the biological one and its effect can be minimized by using a sufficient number of replicates [ 6 - 8 ]. However, the high cost of microarray experiments often prevents gathering of enough samples for a reliable analysis in a single laboratory. In such cases, employing existing microarray datasets from other studies can be an efficient way of improving the reliability of a study. Moreover, as the number of publicly available datasets grows rapidly on public data depositories (e.g., Gene Expression Omnibus [ 9 ]; Stanford Microarray Database [ 10 ]; ArrayExpress at EBI [ 11 ]), it is clear that these datasets should be combined to generate a more comprehensive understanding of underlying biology. Several issues have made this process difficult so far. First, different datasets have been processed using different procedures due to a lack of uniform standards, e.g., for background correction, normalization, and calculation of expression values. This makes it difficult to compare them directly. Raw data files are generally unavailable and, even if they are, reprocessing them requires substantial effort. Second, we have lacked datasets with enough controls and replicates, performed under a proper experimental design and with adequate annotations, in order to make proper comparisons. Third, possibly the most troublesome, the experiments have been performed on many different platforms, with significant differences among them. Even within a single platform, technological and algorithmic advances as well as the evolving annotations of the genomes have resulted in succeeding generations of arrays with substantial modification from one generation to the next. Until now, several studies have found varying degrees of disagreement between platforms, sometimes with large discrepancies that call into the question the reliability of certain conclusions reached in microarray studies [ 12 - 19 ]. A comparison of two Affymetrix arrays, HuGeneFL and HG-U95A, was made previously, but only with the conclusion that the reproducibility is high when the two probe sets share many exact probes and that it is low when they do not [ 20 ]. In this work, we carry out a thorough examination of the comparability between the two generations of Affymetrix human GeneChip arrays, HG-U95Av2 and HG-U133A, both of which have been used extensively for studying human gene expression patterns. We then propose a method for enhancing their comparability. The analysis we carry out is made possible by a dataset consisting of the same tissue samples hybridized on both platforms. The procedure is illustrated in Figure 1 . Using our replicate dataset, we first examine the effectiveness of three schemes for matching the probe sets across different arrays. We then quantify the surprising amount of difference in analysis results between the platforms, as revealed in correlation analysis, hierarchical clustering, and selection of differentially expressed genes. We find that comparability can be improved by rescaling expression values or data filtering but that these techniques are limited to few specific analyses. As a generic method for comparative analysis, we propose selecting a subset of probes that have sequence overlaps with the probes on the other array and recalculating the expression levels based only on this subset. We demonstrate that this probe filtering significantly improves the reproducibility, without eliminating a significant number of genes from the analysis. Results Comparison of the methods for probe set matching The most common method of matching genes in cross-platform studies is to match the UniGene IDs among genes [ 12 , 15 - 18 ]. One potential problem with this method is that as the UniGene database is updated, some tags are retired and new ones are created, and these may not be tracked correctly unless the same version of UniGene was used to annotate each platform. LocusLink does not suffer from this problem as much and therefore may be preferable in some cases. We tested three methods for matching probe sets between U95Av2 and U133A: UniGene IDs, LocusLink IDs, and Best Match provided by Affymetrix [ 21 ]. As shown in Table 1 , there are about 9000 unique IDs shared between U95Av2 and U133A in all three cases, with slightly more for the Best Match. The number of probe sets involved is higher for UniGene and LocusLink matching, since there are multiple probe sets corresponding to the same ID in those cases. For Best Match, the sequence mapping is restricted to many-to-one matching. As a simple way to assess comparability, the Pearson correlation coefficient between each array pair from the same sample was calculated and the 14 correlation coefficients were averaged. The results are summarized in Table 1 . UniGene and LocusLink matching give practically identical results. Best Match, on the other hand, shows somewhat higher reproducibility than other matching methods (.870 vs .831–.832). The main reason for the higher reproducibility in Best Match is most likely that more comparable probes are chosen among multiple matches by considering the sequence information. The overall reproducibility, however, is surprisingly low. It has been observed in many replicate studies that expression values from Affymetrix arrays show high reproducibility, typically in the range of >0.98 [ 20 , 22 , 23 ]. The low correlation coefficient is already an indication that the cross-generation comparison may not be simple. We use the Best Match in the following sections; UniGene or LocusLink matching performs similarly or slightly worse than Best Match. In a similar study [ 24 ], the authors report the average correlation of .81 ± .01 between two different generations of Affymetrix Arabidopsis arrays. But they conclude that this reproducibility is sufficiently high and that the array generations can be compared without further manipulation of the data. However, in our experience, this number is much too low. In the current data set, for instance, the samples in different disease groups give significantly higher correlation coefficients than that. This is clearly demonstrated later in Figure 2(b) , where the arrays in the same generation are shown to be more highly correlated than the arrays in the same disease class. Exactly matched probes between array generations are highly reproducible There was a possibility that the lack of high correlation between the two versions was caused by a true inconsistency present in the data, perhaps due to RNA degradation between the times when the hybridizations on the two platforms were performed. To make sure that this was not the case, we investigated the quality of our data by examining the subset of probes which have the exactly same sequences between the array generations. When we examined about 5% of probes that have the same sequence between U95Av2 and U133A, the mean correlation coefficient of array pairs, calculated by PM intensity, was 0.967 ± 0.007. (A calculation using PM-MM values also gives a very similar result.) This is similar to the conclusion in [ 20 ] that the probe sets with exactly the same set of probes have a very high correlation. The high correlation in our dataset confirms that the samples and other experimental factors were nearly identical between the two hybridizations and that any discordant result in comparative analysis is therefore most likely due to the differences in the probe design of the two arrays. When we compare the expression values between Best Match and the exactly matched probes, we can easily see the lack of reproducibility for the Best Match case (See Figure 2 in Additional File 1 ). It is clear that the probe-level sequence information has a large impact on the relationship between the abundance of transcript and the reported intensity [ 25 ] and that the use of probe sequences would be necessary in order to choose a subset of relatively consistent probes between U95Av2 and U133A for enhanced reproducibility. Standard probe set matching produces discordant results in analyses To determine the extent to which the analysis results from the two versions of the arrays agree, we employ the two most frequent tools for exploratory analysis: cluster analysis and identification of differentially expressed genes. For evaluating the compatibility in terms of cluster analysis, we combined the datasets from U95Av2 and U133A by Best Match. Then, the 28 samples were clustered by agglomerative hierarchical clustering method with the Pearson correlation coefficient as the distance measure. Figure 2(a) shows the dendrogram of 28 samples. Unexpectedly, instead of each array pair from the same biopsy specimen clustering together, the two array types form the two main clusters. In other words, the most distinguishing feature of the data is the array version, rather than the actual characteristics of the samples. To examine the reason for this incongruent result, correlation coefficients of all the possible sample pairings of the combined dataset were calculated. Figure 2(b) shows the correlation coefficients as a color map. The two red parts of the map (upper left and lower right) represent the high correlation coefficients among samples from the same array version. Compared to these, the correlation coefficients across U95Av2 and U133A are relatively low (lower left and upper right parts of the map). Next, we identified differentially expressed genes between the DMs and other myopathies from each dataset (5 vs 9 samples), using the two-sample t -test with unequal variances (the Wilcoxon test gives very similar results). If the two generations of arrays were comparable, the lists of differentially expressed genes should contain many overlapping genes. To increase the possibility of overlaps, we filtered out non-expressed genes by deleting those in which more than 75% of the samples received Absent calls in both U95Av2 and U133A arrays. When we examine the list of genes identified in common in the two cases, however, its length is disappointingly small. When we look at the list of length 100 or smaller, the percentage of overlap does not exceed 25%. The plot of the percentage of genes common in both lists as a function of the list size is virtually identical to the dashed line in Figure 7b (A detailed plot is shown in Figure 4 of Supplementary Material). This low overlap indicates that the two array types give highly inconsistent results and brings into question the reliability of the highly ranked genes in either platform. We do note, however, that this result must be interpreted in terms of the sample size and other characteristics of the specific dataset. A low percentage is often partially due to the presence of a large number of genes that are differentially expressed to a similar extent in a particular dataset, in which case a ranking of the genes would be expected to be somewhat unstable. Gene scaling and data filtering can enhance comparability in specific situations To understand the reason for the discordance observed in Figure 2(a) , we have examined a large number of probes. The underlying problem, we have discovered, is due to a large number of probe sets that exhibit similar relative expression patterns but at different absolute levels. As an illustration, we plot the expression pattern of one such probe set pair, 35828_at of U95Av2 and 208978_at of U133A, in Figure 3(a) . Clearly, although the expression patterns of these genes are similar in terms of a correlation coefficient, their scales are very different. This behavior is not simple to explain, but we believe it may be related to a large amount of cross-hybridization by a subset of badly designed probes in a probe set, especially for U95Av2. That would have the effect of amplifying the overall expression values. A simple solution to this problem is to scale expression values for each gene across samples, for instance, making the mean to be 0 and the standard deviation to be 1. The effect of this gene scaling on the gene pair from Figure 3(a) is illustrated in Figure 3(b) . The similarity in the expression pattern is more clearly visible and the measurements for this gene are now more comparable. While the Pearson correlations for the genes are not impacted by this linear scaling for genes, the correlations do change for the arrays. Figures 2(c) and 2(d) show the effect of gene scaling on the clustering result and the correlation coefficient of sample pairs, respectively. In Figure 2(c) , the arrays from each platform corresponding to the same sample are now clustered together in every case. In Figure 2(d) , the high correlation among the arrays of same type (shown by red colors in Figure 2(b) ) is diminished and the correlation between specimen samples across array types is highlighted (shown by dark red diagonal lines in upper right and lower left areas). For comparing datasets in a cluster analysis, gene scaling appears to work very well. While gene scaling was effective in cluster analysis, it is limited to evening the influence of different genes in a global analysis by focusing on their patterns. It does not enhance the comparability, for instance, in terms of identifying differentially expressed genes in most algorithms. For that case, some simple filtering schemes could enhance reproducibility instead. One way is to consider only the genes that exhibit strong correlations between the two versions. To see the impact of this on the selection of differentially expressed genes, we calculated the overlap for the 1,000 genes whose profiles on the two array versions were highly correlated. The result is plotted in Figure 4(a) (solid line). To make sure that the increase in the overlap percentage is not due to the smaller number of genes, we also calculated the overlap for bootstrap samples of same size and averaged the result in Figure 4(a) (dashed line). As expected, data filtering by correlation coefficients greatly improved the comparability, more than doubling the percentage of genes in common. With more datasets such as the one we examine here, it is in theory possible to catalog a comprehensive list of genes that are reproducible across arrays, and use only these genes in subsequent comparative studies. Instead of choosing highly-correlated gene pairs, we can also filter data by expression values. Figure 4(b) shows the distribution of correlation coefficients for genes between the versions stratified by their average expression values. We first note that the distribution for all genes is very wide, with the Pearson correlation coefficient of .426 ± 390, reflecting the poor concordance for the probe set values on the two platforms. With the stratification, it is clear that highly expressed genes tend to give more reproducible expression patterns across the two versions, although there still is a fraction of genes with low or even negative correlation. The disadvantage of this type of filtering is that, as in the filtering by correlation, it inevitably reduces the number of probe sets for the analysis significantly. Probe filtering by overlapping length highly improves reproducibility with enough probe sets for comparison We now describe a more general method for improving comparability by filtering at the probe level, instead of at the probe set level. We have already observed that the probes with exactly the same sequences on the two generations give highly reproducible values (Additional File 1 , Figure 2) but that the probe sets do not. This implies that specific probe sequences within the same target region can produce strikingly different results, and suggests that comparability would improve if we select only those probes that have sequence similarities on the two arrays. To carry this out, we mapped the location of all probes using BLAT, as described in Methods. When we select a subset of probes, we mask the rest in the raw data (cel files) and then recompute the expression values using the same algorithm used in MAS 5.0. An optimal selection scheme requires a balance. On the one hand, we would like to require as large a sequence overlap as possible between the probes to ensure high reproducibility. On the other hand, a stringent restriction means that the number of usable probe sets in an array is reduced and also that each probe set value will be less robust because it is derived from fewer probes. Figure 5 shows the correlation coefficient of array pairs from the same sample according to two criteria: the minimum overlapping length (1 bp ~ 25 bp) and the minimum fraction of used probes per probe set (10% ~ 100%). The latter refers to the fraction for each probe set, e.g., 30% minimum means that at least 4 out of 11 probes for U133A and 5 out of 16 for U95Av2 must satisfy the sequence overlap requirement. If there are too few probes left in a probe set, we discard the probe set as unreliable. In Figure 5 , we plot the average of the correlations for the pairs of U95Av2 and U133 chips on which the same sample is hybridized. We see that the average correlation improves substantially with the greater amount of sequence overlap at all ranges. It also improves with the minimum percentage of probes used but only slightly. Figure 6 shows the number of usable probe set pairs according to the same two criteria. It appears, for example, that we can obtain highly comparable results (correlation coefficient > 0.9) with a large number of probe sets (more than 80%) for comparative analysis. For a given value of minimum overlap length, we can also calculate the average number of probes per probe set (See Figure 5 in Supplementary Material) in addition to the number of retained probe sets. With 20 bp minimum overlap, more than 90% of probe sets can be used, with the expression levels calculated from an average of 30% of the original probes per probe set. To emphasize the improvement, we again show in Figure 7(a) the increase in the mean correlation coefficient of array pairs, without any criterion on the fraction of used probes per probe set. As a baseline, the mean correlation coefficient of array pairs using Best Match is also represented (dashed line). Enhancement in the mean correlation coefficient of array pairs is roughly proportional to the minimum overlapping length. It appears that the mean correlation coefficient can be worse than in the case of Best Match when the minimum overlapping length is less than 10 bp. It is possibly because such a small overlap constitutes enough dissimilarity as to confer no functional relationship between the probes and instead other good probes that do not have overlaps are thrown away. Based on Figures 5 and 7(a) , we suggest that the minimum overlapping length of more than 18 bp is necessary for obtaining significantly improved results in terms of correlation coefficient of array pairs (>0.9). Next, we show the improvement of comparability in terms of selecting differentially expressed genes. Figure 7(b) shows the percentage of commonly identified differentially expressed genes between U95Av2 data and U133A data when the probes are filtered with minimum overlapping length of 18 bp. The number of usable probe set pairs in this case is more than 9,500. For comparison, the result for the Best Match (10,507 probe set pairs) case is also drawn (dashed line). From Figure 7(b) , it is clear that the improvement in comparability is significant, especially when the number of selected genes is small. For example, without the probe filtering, the lists of top 15 genes in the two data sets have no genes in common; with filtering, 30 ~ 50% of the genes are shared. These results demonstrate that the filtered and recomputed data sets are more comparable with only a small reduction in the number of usable probe sets. Deviation from the original expression profile after probe filtering can be controlled by criterion on the overlapping length A reduction in the number of usable probes inevitably results in the deviation of the recomputed expression values from the original values calculated using all probes. Figure 8(a) shows the mean Spearman correlation coefficients between the expression values using all probes and those using only the selected probes by our criteria. We use the Spearman correlation here to capture the changes in the ranks of genes. As expected, the correlation decreases, as more stringent criteria are applied and a smaller subset of probes is chosen. Interestingly, the deviation in U95Av2 arrays is much larger than in U133A arrays, although the average fraction of used probes per probe set in each case is similar (see Figure 5 of Supplementary Material). For example, the mean correlation coefficient is greater than 0.9 in U133A when the criterion on the minimum overlapping length is less than 20 bp. For the same criterion, the mean correlation coefficient is about 0.85 in U95Av2. This appears to indicate that, in the process of making the two versions more similar, the larger changes occur to the expression levels in U95Av2 arrays. This result is consistent with the fact that probe design for U133A was performed in a more principled way than for U95Av2 and that U133A values are closer to the true values [ 25 ]. In addition to recalculating the expression values, the Affymetrix Present or Absent calls can also be calculated. Figure 8(b) shows the percentage of Present calls for each reduced group of probe sets. The probe filtering appears to reduce the percentage of Present calls, possibly because having fewer probes per probe set increases the likelihood of Absent calls. The usefulness of these calls can be debated; we simply present it here for those who find the calls helpful. In any case, we note that the percentage sharply drops down as the minimum overlapping length increases past 18 bp. Both Figures 8(a) and 8(b) indicate that 18–20 bp may be a reasonable cut-off values for the overlap length. We note that in filtering the probes, our goal is to simply make the expression profiles from U95Av2 and U133A more comparable. In the process, it is possible that this procedure sometimes results in less accurate expression values in absolute terms. By requiring that the probes in U133A have a sequence overlap with the less reliable set in U95Av2, we may be discarding some useful probes and, as a result, may be producing less accurate expression values. This is a trade-off that we make in order to utilize other data sets for a comparative study, but we should be aware of this fact in subsequent analysis. Conclusions Comparative analysis of different microarray types has a potential to generate more comprehensive and reliable results by fully exploiting available data. Understanding and resolving both the inter-platform and inter-generation data remain an important and challenging practical issue. So far, attempts at such comparisons have been few, and many were limited to simple observations of low correlations in expression values. In this work, we provided a more quantitative and comprehensive description of the issues and inconsistencies through the analysis of a unique dataset consisting of HG-U95Av2 and HG-U133A hybridizations for each of the sample biopsies, and then we described a general method for resolving some of the problems. We first observed in cluster analysis that with a standard matching of genes, the dominant feature of the dataset is not the sample characteristics but the array type. But we found that for clustering, this problem can be mitigated by rescaling each gene. We note, however, that this method is effective under certain assumptions, e.g., that there are enough samples for each array type and that each dataset does not contain unrelated experiments. If two groups of patients under study are measured on two different arrays, for example, a gene scaling will simply make the samples more homogeneous and reduce the differences between the groups. We also examined the inconsistencies in the list of differentially expressed genes obtained in the two cases. The overlap was very low, indicating that such a list may be platform-dependent and must be interpreted with caution. Some data filtering steps, either by selecting a subset of genes that are empirically shown to be well-correlated between platforms or by focusing only on highly-expressed genes, can be helpful at times, but they do not resolve the underlying problem. Our approach based on the probe-level sequence information resulted in a significant improvement in the reproducibility in terms of correlation coefficients and selection of differentially expressed genes. As the probes aligned to multiple regions in the genome are eliminated and the probes that share larger segments are selected, the expression values become more consistent. This result is promising because it does not use data-dependent information such as the empirical correlation for each gene between different versions of arrays, which can only be obtained through special datasets such as ours. We examined the effect of the minimal sequence overlap length and the minimum number of probes per gene on the reproducibility, and found that, when the parameters are chosen properly, higher correlation can be attained while retaining a large number of probes for further analysis. We also examined the deviation from the original data when new expression values are calculated after probe filtering. In general, we recommend the minimum overlapping length of 18 ~ 20 bp and that at least 10 ~ 20% of probes in a probe set be present in the filtering step for a comparative analysis between U95Av2 and U133A. Combining data across multiple platforms remains a formidable challenge. As a first step, we have studied the issues associated with combining data from multiple generations of a single platform and proposed one method. From our analysis, it is clear that technological issues can have significant effect and that one should be aware of the potential pitfalls in studies involving more than a single array type. In principle, the approach of selecting probes with sequence overlaps can be applied to other array types as well as to different versions of oligonucleotide arrays. For example, to study expression profiles of conserved regions across species using a different array for each species, more accurate results may be obtained by using only a subset of probes with sequence similarity. In each case, appropriate criteria for the length of overlap and the number of probes needed for a robust estimate of a probe set value need to be investigated for different contexts, but the results we provide in this work can serve as a guide. Methods Microarray data Muscle tissue samples of 14 patients with inflammatory myopathies were collected. Among the 14 patients, 5 had dermatomyositis (DM) and 9 had other inflammatory myopathies including necrotizing myopathy, inclusion body myositis, granulomatous myositis, and polymyositis. Because the molecular profile of DM is sufficiently different from those of the rest, we can think of the DMs as one group and the rest as the other group in a two-group comparison [ 26 ]. Total RNA was extracted from muscle biopsy tissues and labeled. A portion was hybridized to HG-U95Av2 arrays; the remaining supply was frozen and then later hybridized to HG-U133A arrays at the same facility. Matching probe sets between U95Av2 and U133A Although they belong to the same oligonucleotide array platform, the changes from the older version (U95Av2) to the newer one (U133A) were substantial: 1) Main source of probe selection region is different (UniGene Build 95 and 133; for the U133 set, other sequence databases such as dbEST were extensively used for choosing the probe selection region); 2) The number of probe pairs was reduced from 16 to 11 for a single gene; and 3) Probe selection method was improved [ 25 ]. The annotation for each probe set in U95Av2 and U133A was obtained from NetAffx Analysis Center (NetAffx annotation files (annotation date: 12/10/2003)) [ 27 ]. According to the annotation information, U95Av2 has 12,625 probe sets, which are annotated by 9,091 UniGene and 8,672 LocusLink identifiers. The newer version U133A consists of 22,283 probe sets annotated by 13,624 UniGene and 12,769 LocusLink identifiers. Here, the UniGene identifier was assigned by matching the representative sequence of each probe set to the UniGene database at the time of annotation. The LocusLink identifier was derived from the matched UniGene record (Annotation Methodology, Affymetrix web site). For considering variations in the probe sets for the same transcript between different array versions, Affymetrix provides the probe set matching tables for comparative analysis. These matching tables were constructed based on the sequence information of probe sets as follows [ 21 ]. First, all possible probe set pairs between two array generations were checked by their similarity in the representative sequence for selection. Among the selected probe set pairs, "Good Match" pairs were chosen by the following criteria: 1) Percent identity between the representative sequences >90%; 2) Length of the representative sequence >100 base pairs (bp); 3) At least one perfect match (PM) probe of one array generation should be perfectly aligned to the probe selection region of the other array generation. In addition, "Best Match" is a subset of Good Match selected by more stringent criteria on the similarity of probe set pairs [ 21 ]. Best Match is used in the rest of the paper as it performs better than Good Match in all instances. When there is more than one probe set matching on either or both arrays, we take the average of the measurements. BLAT for the alignment of probes For improving compatibility between U95Av2 and U133A, those probes whose sequence overlapped with any of the probes for the same gene on the other platform were selected. The extent of overlap necessary is described in the Results section. First, all the perfect match (PM) probes were aligned to the coding regions of the genome. Of commonly used short sequence alignment tools such as SIM4 [ 28 ], SPIDEY [ 29 ], and BLAT [ 30 ], we used BLAT (build version 26, available at as a stand-alone program) because it appears to be more accurate and faster than others for matching short sequences with high sequence identity (more than 90%). BLAT has been used previously for annotating the probe sets of HG-U95Av2 in GeneAnnot system from Weizmann Institute of Science [ 31 ]. The alignment was done on the human chromosome sequence Build 34 (July 2003 freeze), available at UCSC Genome Bioinformatics ( [ 32 ]). We ran BLAT with its default options (-tileSize = 11 -minMatch = 2 -minScore = 30, -minIdentity = 90 -maxGap = 2), without the overused tile file to avoid missing any matches. From the BLAT search result, only the 25-mer perfect alignments were considered for further analysis. All probes aligned to more than two regions in genomic DNA were discarded because of the possibility of cross hybridization. In each matched probe set pair, the overlapping lengths between all the possible PM probe pairings (16 × 11) were calculated. Filtering probes by overlapping length The length of the overlap between probe sequences (1 bp ~ 25 bp) was used as a criterion for choosing probes for comparative analysis. The expression values were recomputed each time using only the selected probes by masking out the other probes from the raw (.cel) files. The values were calculated by the Statistical Expression Analysis Algorithm using Microarray Suite version 5.0 (MAS 5.0) (Affymetrix, Santa Clara, CA) without linear scaling to target intensity. MAS 5.0 is a robust estimator of expression index based on one-step biweight estimation algorithm, considering both perfect match (PM) and mismatch (MM) probes. This algorithm alleviates the problem of unstable expression values to some extent when a fraction of the probes is eliminated in our analysis. Authors' contributions KBH carried out probe set matching, performed BLAT searches as well as statistical analysis, and drafted the manuscript. SWK carried out the raw data processing, performed statistical analysis, and provided input on drafts of the manuscript. SAG participated in the design of the study as well as providing the microarray data set for this study. PJP conceived the original idea of this study, participated in its design and coordination, and wrote sections of the manuscript. All authors read and approved the final manuscript. Supplementary Material Additional File 1 Supplementary material for the paper "Combining gene expression data from different generations of oligonucleotide arrays" Supplementary figures for the paper Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC528726.xml |
538253 | Historical measures of social context in life course studies: retrospective linkage of addresses to decennial censuses | Background There is evidence of a contribution of early life socioeconomic exposures to the risk of chronic diseases in adulthood. However, extant studies investigating the impact of the neighborhood social environment on health tend to characterize only the current social environment. This in part may be due to complexities involved in obtaining and geocoding historical addresses. The Life Course Socioeconomic Status, Social Context, and Cardiovascular Disease Study collected information on childhood (1930–1950) and early adulthood (1960–1980) place of residence from 12,681 black and white middle-aged and older men and women from four U.S. communities to link participants with census-based socioeconomic indicators over the life course. Results Most (99%) participants were linked to 1930–50 county level socioeconomic census data (the smallest level of aggregation universally available during this time period) corresponding to childhood place of residence. Linkage did not vary by race, gender, birth cohort, or level of educational attainment. A commercial geocoding vendor processed participants' self-reported street addresses for ages 30, 40, and 50. For 1970 and 1980 censuses, spatial coordinates were overlaid onto shape files containing census tract boundaries; for 1960 no shape files existed and comparability files were used. Several methods were tested for accuracy and to increase linkage. Successful linkage to historical census tracts varied by census (66% for 1960, 76% for 1970, 85% for 1980). This compares to linkage rates of 94% for current addresses provided by participants over the course of the ARIC examinations. Conclusion There are complexities and limitations in characterizing the past social context. However, our results suggest that it is feasible to characterize the earlier social environment with known levels of measurement error and that such an approach should be considered in future studies. | Background Consideration of the impact of neighborhood social environment on health is now common in social epidemiologic studies [ 1 - 7 ]. While studies of the influence of individual measures of socioeconomic status (SES) on health often include queries for various points during the life course [ 8 - 10 ], estimates of the impact of the neighborhood environment have tended to characterize only the current social context. Current addresses are typically sent to a commercial geocoding vendor and proprietary software is used in conjunction with the Topologically Integrated Geographic Encoding and Referencing (TIGER/Line ® ) files to link the addresses with spatial coordinates within statistical tabulation areas [block group, tract, zip code tabulation area, county]. Notwithstanding concerns about the accuracy in the assignment of statistical tabulation areas by commercial geocoders [ 11 - 14 ], efforts to geocode current addresses are generally successful with reported match rates of 90% or higher at the tract and block group level [ 1 , 15 ]. Obtaining and geocoding historical addresses is more complex and has rarely been undertaken despite the potential advantages derived from its inclusion in life course studies. The completeness and accuracy of historical addresses may not be as high as that of current addresses, unless added care is taken during data collection. Further, widespread use of geocoding in research applications is relatively new and commercial geocoding databases are typically optimized to current street atlases and most recent census tract boundaries. Accurate past addresses, even when assigned correct spatial coordinates, would not be linked with correct historical social contextual data if census tracts had not been defined or summary census data was not available for the area when an individual resided at the address or if the census boundaries had changed over time. The Life Course SES, Social Context, and Cardiovascular Disease (LC-SES) Study retrospectively collected place of residence during childhood and earlier adulthood on a cohort of middle-aged and older persons. We report on the methods used and our success rate in placing participants into historical census areas and linking them with measures of the social context over time based on self-reported place of residence during childhood and at ages 30, 40, and 50 years. Results The procedures used to obtain the results described in this section are explained in detail in the methods section of this paper as well as in the LC-SES Study manual of procedures, available on the study website [ 16 ]. Linkage of childhood residence to county level census data from 1930–1950 Of 12,681 participants, we excluded 304 who reported living outside of the United States during most of their childhood. Of the remaining 12,377 participants 86% provided apparently correct information on county and state and 10% provided a county which was misspelled. Spelling errors were corrected using a listing of counties in the U.S. available on a publicly accessible website [ 17 ]. The remaining 4% of participants did not provide any information on city or county, transposed city and county information, or provided information on a city but not county. Obvious transposition errors were corrected and in cases where the participant provided a city but not a county we searched the publicly available website [ 17 ] to identify the matching county. In instances where a city of the same name was listed in multiple counties (n = 27), we did not assign a county. In all, 12,187 (98.5%) of participants reporting a childhood residence in the U.S. were successfully linked with county level U.S. census data. Linkage did not vary by race, gender, adult educational attainment or birth cohort (data not shown). Birth cohort and geographical distribution of participants Participants ranged in age from 45–64 years at the baseline ARIC examination (1987–89). Given their 20 year age span, the years at which they were aged 30 (and 40 and 50) years ranged over several decades, requiring that those from different birth cohorts be linked to data from different census years (Table 1 ). Table 1 Number of participants assigned to 1960–1980 censuses, overall and by age decade, the LC-SES study, 2001–2002 Census Year Age 30 N Age 40 N Age 50 N Total N 1960 7085 1115 - 8200 1970 5596 5965 1110 12671 1980 - 1891 1386 3277 Total 12681 8971 2496 24148 At baseline, ARIC participants were recruited based on their stable residence in the four study communities. However, at age 30 participants were residing in all 50 states, at age 40 in 47 states, and at age 50 in 31 states. Nonetheless, as shown in Table 2 , for all three ages, most participants were already residing in the study areas (as defined by county and state). By age 50, 91% were residing in the study area and only 5% lived out of state. Table 2 Correspondence of county and state of residence at ages 30, 40, and 50 to that at time of ARIC visit 1 exam, the LC-SES study, 2001–2002 Age 30 Age 40 Age 50 County and state of residence at ages 30–50 vs. that at ARIC baseline examination N = 12,681 % N = 8,971 % N = 2,496 % Residence in same county and state 72 85 91 Residence in different county but same state 11 6 4 Residence in different county and state 17 9 5 Linkage of addresses at ages 30, 40, and 50 to 1960–1980 census tract data Table 3 provides a summary of results for linking with 1990 geocoding maps (stage 1 of the process). We submitted 22,140 (92%) of all historical addresses [address refers to a street name and number (if available) and city and state] provided by participants to the geocoding vendor. Those not submitted included P.O. box addresses, as well as those for whom no street information was provided. Of the addresses submitted to the vendor, 75% were assigned spatial coordinates that placed the addresses within a 1990 census tract. About half of the 5,550 addresses that were not assigned coordinates within a census tract were street names without numbers; the rest were cross-streets and apparently complete addresses. Table 3 Historical addresses queried, geocoding success rates and characteristics of addresses not successfully geocoded, the LC-SES study, 2001–2002. 1 The address information was assigned to the centroid of a zip code area in which all addresses fell within a single block group or census tract or more than 80% of addresses fell within the same census tract. N %age Addresses for ages 30, 40, and 50 queried 24,148 100 Partial or complete street address provided 22,140 92 No address, P.O box, or no street name 2,008 8 Commercial Geocoding Results 22,140 100 Address match (geocoded to 1990 census tract) 16,445 74 Usable centroid match 1 145 <1 Not matched or geocoded to census tract 5,550 25 Characteristics of addresses not matched or geocoded to census tract 5,550 100 Street with number 1,690 30 Cross-street 923 17 Street name without number 2,937 53 Table 4 summarizes our linkage of addresses using the two step process of first linking to the 1990 geocoding maps to get spatial coordinates, and then using the spatial coordinates to obtain the comparable 1960, 1970, and 1980 census tracts. The proportion of addresses judged to be adequate for commercial geocoding (participant recalled at least a partial street address and a city and state) was modestly lower for 1960 than for later years. The proportion that were successfully geocoded to a 1990 tract, and the proportion that were assigned a tract for the historical census, increased steadily from 1960 to 1980. Most addresses with a 1990 tract assignment were placed into the appropriate historical tract for the 1970 and 1980 censuses. Although 61% of 1960 addresses were successfully geocoded to a 1990 tract, only 26% could be assigned a 1960 tract, largely because much of the U.S. was not assigned census tracts in 1960. Use of tract data from the next available census (1970) increased the yield by 16%. Table 4 Percentages of addresses geocoded to 1990 census and then assigned to a 1960, 1970, and 1980 census tract, the LC-SES study, 2001–2002. 1 Jackson, MS & Washington Co., MD print files of U.S. Bureau of the Census housing data for 1960 [34]. 2 Includes some addresses sent to vendor but not assigned a latitude and longitude. % of All Addresses Street addresses for 1960 (N = 8200) Sent to geocoding vendor 89 Vendor assigned latitude and longitude 61 1960 tract assigned using overlay/comparability file 26 1960 Assigned area by overlay (non tract area) 1 16 1970 tract Assigned (non tract area-1960) 16 1960 tract Assigned manually 2 8 Total addresses assigned tract 66 Street addresses for 1970 (N = 12671) Sent to geocoding vendor 93 Vendor assigned latitude and longitude 71 1970 tract assigned using overlay 69 1970 tract assigned manually 2 7 Total addresses assigned tract 76 Street addresses for 1980 (N = 3277) Sent to geocoding vendor 94 Vendor assigned latitude and longitude 81 1970 tract assigned using overlay 80 1970 tract assigned manually 2 5 Total addresses assigned tract 85 Manually assigning tracts to addresses modestly increased the proportions that were successfully assigned a census tract for the censuses corresponding to places of residence at ages 30–50 (increase of 8% for 1960, 7% for 1970, and 5% for 1980). Success rates associated with efforts to manually assign historic tracts to addresses varied considerably across study areas and also according to the reasons for the failure of the automated geocoding procedure. Of the addresses which we attempted to manually assign a census tract, we were successful for 54% of Forsyth, NC addresses, 45% of Jackson, MS addresses, 30% of Minneapolis, MN address and 29% of Washington County, MD addresses (data not shown). Rates were particularly low in MD because many roads were located in areas not classified into tracts in the 1960 census and because the conversion to a grid address system – during which time some streets renumbered and renamed – did not occur until the early 1990s. In contrast, the low success rate in MN occurred primarily because the tracts were physically small and streets tended to cross multiple tracts. Figure 1 shows the proportion of participants not linked to a historical census tract by adult age and census year. Overall, the rate of successful assignment to a historical census tract was lower at younger ages (67% for age 30, 81% for age 40, 86% for age 50) and within each age decade, for earlier censuses. Figure 1 Percentage of addresses not assigned a census tract by age and census year, the LC-SES study, 2001–2002. Variation in linkage to census tracts by sociodemographic characteristics Table 5 presents childhood and midlife socio-demographic characteristics of participants by success of census tract assignment at ages 30, 40, and 50. There was no difference in the proportion of participants assigned a census tract by mean age at baseline. African-Americans comprised modestly higher proportions of those groups not assigned to census tracts. For ages 30 and 40, a modest but greater proportion of men were in the group not assigned a census tract. There were differences in both educational attainment and family income between those assigned and not assigned census tracts. Those in the lowest strata of income and education tended to be more heavily represented in the group not assigned census tracts; this pattern was also observed for those in the highest educational group at age 30. Table 5 Comparison of sociodemographic characteristics of those with and without tract assignment 1 , the LC-SES study, 2001–2002. 1 Chi Square test used to statistically compare differences in proportions and t-test used to statistically compare differences in means of those assigned and not assigned census tracts. 2 Ns for each characteristic vary slightly due to missing data. * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001 Age 30 Age 40 Age 50 Tract assigned Tract assigned Tract assigned Characteristics at baseline examination Yes No Yes No Yes No Total N (%) 2 8,448 (67) 4,233 (33) 7,262 (81) 1,709 (19) 2,143 (86) 353 (14) Mean age 53 54 56.3 57 62 62 % Male 41 46**** 43 47* 46 46 % African American 25 26 23 25 21 25 Educational attainment (%) < 12 years 21 21**** 23 26*** 28 35*** 12 years or equivalent 44 36 42 37 40 40 > 12 years 35 43 35 37 32 35 Family income (1987–89) (%) < $16,000 19 21** 20 25**** 28 36* $16,00–49,999 55 51 54 53 56 51 $50,000 26 28 25 22 16 13 % Born outside of study state 20 38**** 23 36**** 23 35**** Father's education (%) 0–9 years 53 48**** 55 52 57 61 9–12 years 35 34 32 34 29 23 > 12 years 12 17 13 14 14 15 Father's occupation (%) Professional & management 11 14 11 12 10 15 Technical & sales 11 11 11 11 12 8 Mechanical & crafts 21 18 20 19 21 15 Farming 30 31 32 33 34 39 Laborers, operators & drivers 21 19 20 19 17 14 Service 7 7 7 6 7 8 % Parents owning home 92 86**** 93 82**** 93 80**** There were variations, albeit inconsistent, in early life sociodemographic characteristics and assignment to census tract of residence at ages 30, 40, and 50. Those living outside of their current (at baseline) state of residence during childhood were markedly less likely to be linked with a census tract at ages 30–50, while those whose parents were homeowners were more likely to be assigned tracts. Those who had fathers with twelve or more years of education or who were in managerial and professional or in farming occupations were modestly but more heavily represented in the groups not assigned tracts. In contrast, those with fathers who were in blue collar occupations (mechanical and crafts; laborers, operators, and drivers) were consistently less likely to be in the group not assigned tracts. These differences by fathers' occupations, while consistent, were generally modest. Discussion Assessment of social circumstances in childhood and early adulthood in life course studies is typically limited to individual level measures of parental / own occupation or education [ 8 - 10 ]. The contribution of the contemporaneous social context to a variety of health outcomes [ 1 , 4 - 6 ] suggests that evaluation of the impact of earlier socio-environmental exposures on health is also of interest. Its inclusion in life course paradigms is not novel [ 18 , 19 ] but its implementation in population-based studies in the U.S. is, in part because of uncharted approaches to the measurement of historical context on a scale suitable to epidemiologic studies. We report on our methods, completion, and error rates in retrospectively collecting former places of residence in a middle-aged and older cohort and linking this information with census data. We successfully linked 99% of participants with 1930–1950 county level census data corresponding to their childhood place of residence. Successful linkage of addresses from ages 30–50 with corresponding census tract level data from the 1960–80 censuses was lower. Approximately two-thirds of participants were assigned a census tract for 1960, 76% for 1970 and 85% for 1980. For purposes of comparison, ARIC participant addresses at the time of each of the ARIC examinations (1987–1999) achieved geocoding match rates (by the same vendor) of 94%. Match rates of participants' addresses to the 1960–1980 U.S. census tracts were lower largely for three reasons: limited ability to recall complete historical addresses, obsolete or unusable addresses (e.g., change in street numbering, renaming of rural routes), and the previously incomplete coverage of census tracts in the U.S. Linkage rates were considerably higher in 1970 when census tracts were in place at all of our study sites. Now the coverage of census tracts is complete for the U.S. and grid address systems are common even in rural areas. Thus, studies of more recent birth cohorts though still faced with limitations of recall would be expected to have higher linkage rates. The yield from attempts to commercially geocode incomplete street addresses (e.g., street name but not number) were quite low, even when street fell completely within the boundaries of one census tract. TIGER/Line ® files represent streets as a series of segments. When streets consisted of more than one segment, even when all were located within a single tract, it appears that commercial geocoding software was not able to assign a census tract. We were able to assign census tracts to a sizable portion of these addresses by using detailed street maps overlaid with historical census boundaries. However, this process involves multiple steps and is labor intensive and thus can be practically implemented only in areas where a sizable number of addresses are located. Recall of county, city, and state of residence during childhood was virtually complete, while recall of street address of former places of residence was more limited. The potential limitations of retrospectively recalled data are known [ 20 , 21 ], suggesting the need to assess the accuracy of addresses corresponding to former places of residence information provided by interviewees. Review of a subset of decedents indicated that recall of county and state of birth showed greater than 90% concordance with that recorded on their birth certificate (KM Rose, unpublished data). While it is technically possible to use historical city directories to verify addresses, privacy concerns prevent us from linking addresses to participant names. In future studies, advanced notification to the interviewee should be considered as it would offer them the opportunity to consult records and / or a spouse, potentially reducing the degree to which some individuals may not be able to recall a complete street address. Linkage to county-level place of childhood residence did not vary by participant sociodemographic characteristics. In contrast, successful linkage of the later but more detailed address information to 1960–1980 census tract data varied by sociodemographic characteristics (gender, family income, father's and own education). More striking was the substantial difference seen between those born in vs. outside the study state. Those born outside of the study states were between 1.5 and 1.9 times more likely to not be assigned a tract than those born in one of the study states. To some extent, this occurred because a higher proportion of the participants born in other states originated from areas lacking census tracts at the time of the pertinent historical census. The optimal geographical unit of analysis for contextual measures is discussed in the literature [ 22 - 24 ]. Studies tend to use either census tracts or block groups, and reports suggest that the two produce similar results [ 1 , 22 ]. There is concern that data aggregated at the county level is not optimal to characterize the social environment. However, ecological studies as well as those including an assessment of individual-level SES [ 25 - 29 ] have reported inverse associations between county-level socioeconomic characteristics and health outcomes. Since childhood county of residence is recalled quite well per our results and it corresponds to the smallest level of geographical aggregation at which census data is available prior to 1960, its use as a measure of the social environment in life course studies deserves consideration. Our purpose in assigning current and former adulthood places of residence to census tracts was to link participants with census-based neighborhood profiles to provide area-based measures of the social context (s) across epochs spanning early to later adulthood. Although the approach presented here had not been previously attempted and has logistical complexities, its feasibility, success and error rates are now documented. The opportunity to acquire area-based measures of SES in a historical context does not obviate the methodologic challenges associated with life course research, however. Among the latter it is worth mentioning that many census variables differ across censuses (see table entitled "SES var by census in the Census Tract SES section of the LC-SES Study website [ 30 ]). For example, the percentage living below the poverty level was not calculated until the 1970 census and prior to 1940, years of education were not collected. Also, the meanings and distributions of census variables are subject to secular change (i.e., over time the average educational level of the U.S. population has increased, mean/median incomes and housing values change across time). Thus, careful consideration of birth cohort effects and of the social and economic contexts at each point of data collection is required. Conclusions The importance of the social and economic environments in influencing health is increasingly recognized, yet most research to date is limited to the current social context [ 1 - 6 ]. We believe that this deficit is largely driven by the greater complexity and limitations inherent in retrospectively characterizing the past social context. The experience of the LC-SES study suggests that it is feasible to do this effectively. Studies incorporating such an approach offer the potential of improved understanding of socioenvironmental influences over the life course on health, and should be considered. Methods Study participants The Atherosclerosis Risk in Communities (ARIC) study is an investigation of the etiology and natural history of atherosclerosis and its sequelae. At baseline (1987–89), 15,792 African American and white middle-aged men and women from four U.S. communities (Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD) were included. An account of the design and procedures is published [ 31 ]. Since baseline, the ARIC study telephones participants annually to establish vital status and assess indices of cardiovascular disease, including hospitalizations. Institutional Review Boards (IRB) at each ARIC centre approved the study, and the investigators obtained informed, written consent from all participants. An ancillary study to ARIC, the LC-SES Study was initiated in Spring 2001 to examine the association between SES across life and adult CVD-related conditions, and to determine the extent to which the current and historical context [neighborhood estimated at the county (early childhood) and census tract (early adulthood) level] modify the association of individual-level SES exposures and CVD. Trained interviewers administered a telephone questionnaire including 44 questions about parental and early adulthood occupational and educational exposures, current sociodemographic characteristics and childhood and earlier adulthood places of residence. Participants responding to the questionnaire (N = 12681), represent 81% of the ARIC baseline cohort and approximately 94% of cohort survivors. Additional details about the LC-SES Study can be found in the manual of procedures [ 16 ] and other documents available on the study website [ 32 ]. Ascertainment of childhood and early adulthood residences Participants were asked "Where did you mostly live when you were a child? If possible, give me the city/town, county, and state of residence." Participants were also asked to provide their address (street number and name, city, county, state, and zip code) at various points during adulthood. Everyone was asked to provide addresses for age 30 (n = 12,681), and those who had first participated in the ARIC study after age 49 (n = 8,971) or 59 (n = 2,496) were also asked to provide addresses for ages 40/50 and 50, respectively. Those unable to provide an exact address were asked to provide the street name and the closest cross-street. Editing & linking childhood county of residence with 1930–50 censuses The year at which participants were aged ten years, which represented the approximate midpoint of childhood, was determined in order to link with the county-level socioeconomic data from the closest census year (1930, 1940, 1950). When a city, but not a county was provided, we used a publicly available website to attempt to identify the correct county [ 17 ]. County was chosen, as it was the smallest level of aggregation universally available in published census data before 1960. These data were obtained electronically through the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan. Preparing addresses at ages 30, 40, 50 for geocoding Prior to geocoding, all state data was standardized to conform to the two-digit U.S. Postal Services state coding system. Within each state the accuracy of the spellings of cities were verified. Street addresses were reviewed and computer programs written to correct obvious misspellings and to standardize formats. We did not submit zip codes because those accompanying the historical address could have changed over time. Because our goal was to classify the social environment where participants lived, we excluded post office box addresses as they do not necessarily correspond to actual residences. These along with other incomplete and unusable addresses (e.g., institutions, military APO, c/o, etc.) were not sent for geocoding. After editing, addresses and an encrypted study ID number were sent to a commercial vendor under contractual terms of confidentiality negotiated by university counsel and approved by the IRB. Geocoding The vender assigned to each address: spatial coordinates, Federal Information Processing Standards (FIPS) codes for statistical tabulation areas corresponding to 1990 census boundaries, and a match code describing the degree of accuracy of the geocoding. The accuracy rating assigned by the vendor ranged from" house range address matches" (best) to the "centroid of county" (worst). As we were interested in accurately classifying each participant's place of residence at the level of the census tract (the smallest geographical unit at which data for all censuses since 1960 was available), we accepted only house range address matches (e.g., accuracy at level of exact address, intersection, or street segment) or matches to centroids of zip code areas where everyone lived within a census block group, census tract or where more than 80% of addresses in area were located in the same tract. Rural routes were sent to the vendor but these addresses were not successfully geocoded. Comparison of geocoding methods Two methods were considered to link the spatial coordinates obtained from the vendor with the appropriate historical census tract. The overlay method uses the spatial coordinates assigned to exact address matches in conjunction with historical boundary maps to place addresses into historical tracts. The comparability file method uses current US Bureau of the Census tract assignments that are traced back in time stepwise to 1980 tracts, then from 1980 to 1970 tracts using files that describe tract changes from decade to decade. As a test, we compared the 1970 tract assignments by the two methods for 13,044 addresses that were successfully geocoded to the 1990 census by the geocoding vendor. While all addresses were assigned tracts using the overlay method, 36% could not be assigned a 1970 tract using the comparability files due to census tract merges (a tract contains parts of more then one tract from the previous decade). Of the remaining addresses (n = 8348), 97% were assigned the same tract by both methods. Because there are known errors in the assignment of spatial coordinates by commercial geocoding vendors [ 11 , 12 , 14 ], we could not rule out minor errors in the placement of tract boundaries included in polygon files. We also found an error in a comparability file during this test. We chose the overlay method to link with 1970 and 1980 censuses because it allowed us to locate addresses that could not be assigned tracts using the comparability files with no obvious lack of accuracy. Linking addresses at ages 30, 40 and 50 with 1960–80 census tracts We determined the census year (1960, 1970, 1980) that corresponded most closely to when the participant resided at each address. Arcview GIS Version 3.3 software was used to overlay the spatial coordinates assigned to addresses by the vendor onto Geolytics, Inc. shape files of census tract and block numbering area boundaries of the appropriate census year [Census CD 1970, Census CD 1980]. The spatial coordinates falling within the historical tracts were assigned the corresponding tract number. Figure 2 provides an example of the overlay of the spatial coordinates of Forsyth County, NC addresses that were matched with the 1970 census boundaries. Figure 2 1970 census tracts in Forsyth County, NC and geocoded 1970 participant addresses, the LC-SES study, 2001–2002. Electronic shape files were not available for the 1960 census. Thus, 1960 addresses were placed into 1970 tracts using the overlay method and then mapped to the appropriate 1960 tracts using files providing data on the correspondence between 1970 and 1960 tracts. These were obtained from print volumes of comparability files published by the US Bureau of the Census [ 33 ] and keyed into a database. If the 1970 tract was a merged tract it was not possible to uniquely identify the 1960 tract. In these circumstances we attempted to manually place the address in a tract as described below. Assigning tracts when commercial geocoding efforts failed When a 1960 address fell into a 1970 tract made up of merged 1960 tracts or when addresses were not geocoded by the commercial vendor [street name but not number, cross streets, obsolete addresses (road renamed or renumbered)], we attempted to manually place addresses into historical census tracts. Because this process is labor intensive, we undertook this effort only for addresses which were located within the four ARIC study communities (as a large number of addresses were not clustered in other areas). First, we obtained detailed street maps for the four study areas and overlaid them with census tract boundaries and numbers from the three historical censuses. Then, using web-based Mapquest ® tools and the street map legends, we attempted to locate each address. If a street was contained within the boundary of a census tract, we assigned it the corresponding tract number. If a street crossed a census tract boundary or was the boundary for two or more tracts, we did not assign a census tract. A large number of historical addresses in Washington County, MD were obsolete, because in the early 1990s the state changed to a grid address system to improve emergency response systems. Thus, we obtained historical street maps from the Hagerstown, MD Public Library and tried to locate the original street names in an attempt to manually assign a census tract using the procedure described above. Linking with 1960–1980 socioeconomic census data For addresses placed within a 1960–1980 census tract, we linked with tract level socioeconomic data. For 1970 and 1980 we used data from Geolytics, Inc. (Census CD 1970, Census CD 1980). The ODUM Institute at the University of North Carolina, USA provided electronic 1960 census tract data. Jackson MS and Washington County MD had not been assigned census tracts in 1960. For Jackson, MS and the portion of Washington County, MD falling within the Hagerstown city limits, we obtained 1960 census housing data at the level of city blocks from print volumes [ 34 ], and aggregated them into tract data using the1970 tract boundaries. However, for other areas without census tracts in 1960 this information was either not available (e.g., areas near Hagerstown but outside of the city limit) or it was not feasible to collect it from print volumes because of a small number of participants in the areas. For these addresses, data from the next closest census, 1970, were substituted. Authors' contributions KMR conceived of and led the writing of the manuscript. JLW analyzed the data on early adulthood and developed the methods for assigning census tracts to historic addresses. GH, the principal investigator of the LC-SES Study, contributed to the conceptualization and writing of this manuscript. EAW assessed the accuracy of the commercial geocoding and developed standardized procedures for manual geocoding. SK developed standardized procedures for editing the recalled address data. RP analyzed data pertaining to childhood place of residence. DY was instrumental in reviewing methods for placing participants into their historical tracts. AVDR provided expert input on methods of geocoding. All authors helped to frame the ideas, interpret findings, and review drafts of the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538253.xml |
521070 | A high-resolution radiation hybrid map of chicken chromosome 5 and comparison with human chromosomes | Background The resolution of radiation hybrid (RH) maps is intermediate between that of the genetic and BAC (Bacterial Artificial Chromosome) contig maps. Moreover, once framework RH maps of a genome have been constructed, a quick location of markers by simple PCR on the RH panel is possible. The chicken ChickRH6 panel recently produced was used here to construct a high resolution RH map of chicken GGA5. To confirm the validity of the map and to provide valuable comparative mapping information, both markers from the genetic map and a high number of ESTs (Expressed Sequence Tags) were used. Finally, this RH map was used for testing the accuracy of the chicken genome assembly for chromosome 5. Results A total of 169 markers (21 microsatellites and 148 ESTs) were typed on the ChickRH6 RH panel, of which 134 were assigned to GGA5. The final map is composed of 73 framework markers extending over a 1315.6 cR distance. The remaining 61 markers were placed alongside the framework markers within confidence intervals. Conclusion The high resolution framework map obtained in this study has markers covering the entire chicken chromosome 5 and reveals the existence of a high number of rearrangements when compared to the human genome. Only two discrepancies were observed in relation to the sequence assembly recently reported for this chromosome. | Background Chicken is the first major agricultural species for which the complete genome sequencing was undertaken. This is partly due to its position as a model species in various fields of biology including embryo development, oncology, immunology and evolution [ 1 ]. Moreover, as it is the only bird species for which the genome study is so advanced, very much is expected from its use in comparative genome analyses for annotation, including that of the human genome, by detection of conserved sequences [ 2 , 3 ]. Its intermediate phylogenetic position between mammals and fishes will also certainly provide valuable information on the evolution of vertebrate karyotypes. Radiation hybrid maps have a resolution power intermediate to that of the genetic and BAC contig maps and are also a powerful tool for the mapping of ESTs and genes by simple PCR. They are thus useful at two levels: first, they can be used constructively as scaffolds for a correct genome assembly or for detecting and correcting misassembled portions of the genome; second, before obtaining whole annotated genome sequences, they are very efficient tools for inter-species comparative genome analyses through the easy mapping of genes and ESTs [ 4 - 7 ]. The successful production of a RH panel in chicken is quite recent [ 8 ], and therefore RH maps are only available for a limited number of chromosomes [ 9 - 11 ]. Having identified QTL (Quantitative Trait Loci) for fatness on chicken chromosome 5 [ 12 ], our objective was to build a high-resolution and gene-rich RH map for this chromosome, as a basis for high precision comparative mapping with human and for the development of new polymorphic markers. The available human/chicken comparative mapping data indicated conservation of synteny between GGA5 and portions of HSA11, HSA14 and HSA15. In addition, two genes from HSA1 had also been shown to be located on GGA5 [ 13 ]. This information was used to develop markers from chicken EST sequence data orthologous to genes in these human regions, in addition to the existing markers from the chicken chromosome 5 genetic map. While in the process of finishing our map, the first draft sequence assembly of the chicken genome was released (March 1 st , 2004). The quality of both the GGA5 RH map and of the sequence assembly was therefore checked by alignment of all the markers by BLAST searches. Results and discussion Development of EST markers In addition to the 21 microsatellite markers from the genetic map, and 9 primer pairs chosen either from available primer data in the literature or designed using the gene sequence deposited in Genbank/EMBL, 156 primer pairs were chosen from chicken EST markers selected on the basis of the known conservations of synteny between human and chicken using the ICCARE (Interactive Comparative Clustering and Annotation foR Est) software . Constraints on the design of primers were to avoid presence of long introns, whose position and length was predicted on the basis of the orthologous human gene structure, and to design primers in the most divergent regions of the human/chicken alignment, to limit cross-amplification with the hamster DNA present in the hybrids. One hundred and thirty nine primer pairs out of 156 (89.1%) enabled a successful amplification and the subsequent mapping of the corresponding genes, confirming the high success rate obtained when using the ICCARE software for designing chicken PCR primers based on EST data [ 10 ]. Construction of the GGA5 RH map Altogether, genotyping data was obtained for a total of 169 markers, comprising 148 gene fragments (of which 139 developed using ICCARE) and 21 microsatellites from the GGA5 genetic map. Two-point analysis using a LOD threshold of 6 enabled to constitute a group of 134 markers, including all the microsatellite markers from the genetic map. The remaining 35 markers correspond to the external boundaries of the regions of conserved synteny with human, from which ESTs were chosen for marker development and map either to other chromosomes for which RH maps were developed (GGA1, 10, 18 or 24) or to unknown regions (data not shown). After multipoint analysis, a 1000:1 framework map 1315.6 cR 6000 long, comprising a total of 73 markers including 12 microsatellites and 61 ESTs was obtained. The remaining 61 markers are located relative to the framework map within confidence intervals, to build a comprehensive map (figure 1 ). Figure 1 Comparison RH / genetic maps for chicken chromosome 5. The framework RH map is 1315.6 cR 6000 long. Position of markers included only in the comprehensive map is indicated with error bars to the left of the framework map. Markers for which the genetic position is known (Schmid et al, 2000) are indicated by links to the genetic map (middle). Retention frequency along the map is represented on the right. To compare the RH and the genetic maps, the best possible position of the non-framework common markers had to be estimated. That of the markers on the RH map was computed by the Carthagene program and is indicated in addition to the confidence interval. For the genetic map, the central position of the marker's confidence interval was used as their most probable position. As a result, the order of the markers on the RH map matches exactly that of the same markers on genetic map [ 13 ], with only one notable discrepancy concerning the position of BRF1 (figure 1 ). However, when the position of this gene was checked on the sequence assembly, the agreement was with the RH map, suggesting the position of this gene on the genetic map is erroneous. An average retention frequency of 21.4% was observed for the 134 GGA5 markers studied here, although with a high variation, with values ranging from 6.8% to 55.7%. This finding is within the range observed in other studies reported on this panel: 21.9% overall retention using 42 markers chosen genome-wise [ 8 ], 24 % for GGA4 [ 11 ], 20.1 for GGA7 [ 10 ] and 18% for GGA15 [ 9 ]. As already noticed for several species including human [ 14 , 15 ] or cow [ 16 ], but also for chicken chromosomes 4 and 7 [ 10 , 11 ], a centromeric effect is detected when observing retention frequencies of markers along the map, with a higher retention of markers in the region between 50 to 200 cR, in which the retention culminates at a value of 55.7%, whereas it is around 15% for the rest of the chromosome (400 cR downwards). Alignment of the RH map to the genomic sequence A preliminary data set based on the first draft chicken genome assembly has been deposited into public databases by a team led by R. Wilson and W. Warren, from the Washington University School of Medicine in St. Louis (1st March, 2004, ). We compared our data with the GGA5 sequence, by using BLASTN searches and sequence alignments. The agreement between the RH framework map and the sequence orders is almost perfect (figure 2 ), although with a few discrepancies, most of them suggesting possible improvements to be made in the sequence assembly. Figure 2 Comparison between RH map and chicken genome assembly. The RH map (left) obtained in this study is compared to the draft sequence assembly (right, ). For each marker on the framework map, a line joins both positions (cR and Mb) together. Discrepancies or missing data are indicated. Unknown: sequence of unknown location in the assembly; absent: sequence not found (no BLAST hit); 5_random: sequence attributed to GGA5, but whose position is unknown precisely in the assembly. First, a group of markers ( GPR48 , PAX6 , SPON1 and CSTF3 ), that we developed on the basis of the conservation of synteny between GGA5 and HSA11, is assigned to GGA3 in the sequence assembly. Three of these markers are on the framework map and for all four, the RH genotypings obtained are very similar to those obtained with the flanking RH framework markers SLC17A6 and ARNTL (two-point LOD scores ranging from 7.1 to 15.7), both located on the GGA5 sequence assembly. Furthermore, when two-point analysis of the four markers was computed with the flanking markers LOC134957 (1.2 Mb to GPR48 ) and SLC22A3 (0.6 Mb to CSTF3 ) suggested in the GGA3 sequence assembly, LOD scores were equal to zero. This part of the genome assigned to a wrong chromosome on the sequence assembly covers a region at least 50 cR long, corresponding to a distance of 2 to 3 Mb, as estimated from the cR to Mb ratio. Indeed, the length of the sequence between the two extreme markers CSTF3 and GPR48 on the GGA3 assembly is 2.703 Mb. The retention frequency of these four markers is amongst the highest of all, suggesting that their location is close to the centromere and that the possible sequence assembly problems are related to this proximity, perhaps due to repetitive sequences. Second, we observed an inversion of the gene order for a segment in the upper part of the chromosome (first 86.2 cR or 3.08 Mb, figure 2 ) adjacent to the group we described as wrongly assigned to GGA3 in the sequence assembly. As the difference of likelihood between our 1000:1 framework map and the map order in this area suggested from the assembly is higher than 10 15 , we considered that order of the RH map is the correct one. This could also be due to assembly difficulties close to the centromere region. Third, several markers absent in the sequence assembly could be localised on the RH map (figure 2 ). Most of these markers belong to regions for which sequence information is available, but that couldn't be incorporated in the sequence assembly at all (Unknown) or that could be assigned to GGA5, but without a clear location (5_random). In addition, one gene ( MAX ) also appeared to belong to a region with no sequence available (no blast hit). This gene had previously been located on the cytogenetic map to the short arm of GGA5 [ 17 ], so we consider our data as a confirmation. Fourth, we observed a discrepancy in the local order of the two framework map markers MCW238 and GTF2A1 . However, the difference of likelihood between our framework map and the same map with an inversion of these two markers is only 10 3.7 . It is therefore difficult to conclude as to which between the sequence and the RH map presents the correct order. From these data we conclude that radiation hybrid maps can be useful to help detect errors in the draft sequence assembly and for mapping genes either absent or of unknown location in the assembly. Comparison cR 6000 /cM/kb The average cR/cM ratio is 6.5 when calculated over the whole map length. This relatively high value, as compared to the 4 cR/cM obtained for GGA7 [ 10 ], must be inflected by the disparity observed along the chromosome (figure 1 ). This heterogeneity actually reflects disparities in the recombination rate along the chromosome, with recombination events more frequent at the end of the long arm. The agreement between the gene order found on RH map and the sequence assembly is very high. Considering only the q arm of the chromosome, the cR/Mb ratio is 22.9, or 43.7 kb per cR. This ratio, similar to that obtained for GGA2 (S. Leroux, personal communication), is quite lower than the 63 kb/cR and 61 kb/cR values obtained for GGA15 [ 9 ] and GGA7 [ 10 ] respectively, suggesting a higher resolution for the larger chromosomes. This result can have two origins: first, the kb/cR ratio is not constant from one chromosome to another, regardless of their physical length [ 18 , 19 , 14 ]; second, the previous calculations were based on physical length values estimated from cytogenetic studies: 21 Mb for GGA15 [ 20 ] and 41 Mb for GGA7 [ 21 ]. If we consider the actual chromosome length based on sequence assembly, these chromosomes are shorter than previously estimated, with values of 12.4 and 37.3 Mb , the ratio is thus now closer to the value we obtain here for GGA5. Comparative mapping Figure 3 and figure 4 (see additional file 2 ) synthesize the comparative maps generated by us between GGA5 and its human and mouse counterparts. As indicated earlier [ 13 , 22 - 28 ], conserved synteny was observed between this chicken chromosome and portions of human chromosomes 11, 14 and 15. No correspondence was detected with HSA1, as is also supported by the GGA5 sequence assembly . The results indicate a high number of chromosomal rearrangements in the chicken and human lineages in the region corresponding to GGA5. The results presented in figures 3 and 4 make us conclude that, as previously observed [ 10 , 29 ], the number of synteny blocks is higher between chicken and mouse than between chicken and human. The high number of intra-chromosomal rearrangements within the regions of conserved synteny between birds and mammals is in accordance with results obtained for other chromosomes, e.g., GGA7 [ 10 ], GGA10 [ 25 ], GGA15 [ 20 ], and chicken regions homologous to HSA19 [ 30 ]. Figure 3 Comparative positions between chicken, human and mouse genomes for the framework map genes. The position of each gene on the chicken, human and mouse maps is given: chicken chromosome (GGA), cR position (this study); human chromosome (HSA), Mb position, and mouse chromosome (MMU), Mb position. The position used for human and mouse genes are from EnsMart v19.1 (human build 34, update v19.34a.1; mouse build 30, update v19.30.1 – ). Coloured blocks indicate the blocks of conserved gene order, using the human as reference. Conclusions We have built a high resolution RH map of chicken chromosome 5 using the ChickRH6 panel. In doing this, we fulfilled our objective of obtaining a detailed comparative map of GGA5, providing jointly a source of potential polymorphic markers and of candidate genes for QTL mapping on this chromosome. At the end of our work, the first draft chicken genome assembly was released and we aligned it to our GGA5 RH map. Although we detected a few errors to correct, this allowed us to demonstrate the high quality of the sequence assembly, which may have benefited from a low frequency of repeated elements. In the near future, the ChickRH6 panel will be used to assist in improving the chicken genome assembly. This is clearly needed in the regions for which the genetic map is still not complete, such as some microchromosomes, but also for parts of macrochromosomes, as shown in this study. Methods Development of markers Twenty one microsatellite markers distributed along GGA5 were chosen from the genetic map. Their primer sequences are available at . Human and mouse genes from regions for which available comparative mapping data suggested a conservation of synteny with GGA5 were selected for marker development. Except for CKB , IGF2 and RYR3 for which primers were chosen from the literature, and 6 other genes for which primers were designed from sequences deposited in Genbank/EMBL, primers pairs were designed from the available chicken EST sequence of orthologs defined using the ICCARE (Interspecific Comparative Clustering and Annotation foR ESTs) software (T. Faraut, ). The exonic structure of the genes was taken into account by extrapolating the information available from an alignment to the human genomic sequence. A link with the Primer3 software allowed us to design the primers. Primer data for markers amplifying successfully and accession numbers of the sequences used as a basis for primer design, are indicated in Table 1 (see additional file 1 ). Radiation hybrids – PCR amplification The generation of the RH panel has already been described [ 8 ]. The final panel is composed of 90 clones with an average retention frequency of 21.9%. PCR amplifications were carried out for each marker in 15 μl reactions containing 25 ng DNA, 0.2 μM of each primer, 0.3 U of Taq polymerase (Life Technologies-GIBCO BRL), 20 mM Tris-HCl pH 8.4, 50 mM KCl, 0.05% W-1 detergent, 2 mM MgCl2, 0.2 mM dNTP. Amplifications were carried out on a GeneAmp PCR System 9700 thermocycler (Applied Biosystem). The first 5 min denaturation was followed by 30 cycles, each of denaturation at 94°C for 30 s, annealing at Tm for 30 s and elongation at 72°C for 30 s. PCR products were analyzed on 2% agarose gels, electrophoresed in 1 X TBE buffer, and visualized by ethidium bromide staining. Each marker was genotyped twice and a third genotyping was performed in cases of discrepancies between the first two experiments. Map construction The genotyping data obtained was analyzed with the Carthagene software [ 31 , 32 ]. A group of GGA5 markers was defined by two-point analysis using a LOD threshold of 6. By using all the markers from this group, a 1000:1 framework map (a map whose likelihood is at least 1000 fold higher than the next possible highest likelihood using the same markers in alternate orders) was built under a haploid model. This framework was constructed using a stepwise locus adding strategy, starting from the triplet of markers whose order is the most likely ("buildfw" option). The framework map thus automatically built was further improved towards larger distance coverage by removing markers that prevented its extension. The different provisional framework maps were checked by using a simulated annealing greedy algorithm testing for possible improvements of the map by inversion of large fragments, and a flips algorithm testing all possible local permutations within a sliding window of six markers. After validation of the framework map built under the haploid model, the distances between markers of the framework were re-evaluated under a diploid model. Finally, markers not included in the framework map were mapped relative to it, to determine their most likely positions. The human and mouse reference maps were built from data available through EnsMart v19.1 (14 th January 2004 – ). RH maps were drawn with MapChart 2.0 [ 33 ]. Sequence comparison Sequences for all the mapped fragments were used for a BLAST search over the entire chicken genome assembly at the Ensembl chicken site to determine their position in the sequence. The sequence assembly map of our markers was visualised with MapChart 2.0 [ 33 ]. Authors' contributions FP and BA carried out most of the molecular studies. FP drafted the manuscript. MM made the RH panel. RC and MG were involved in the GGA5 study. FV, SL, KF and SB were involved in the characterization of the panel. We use the Carthagene software thanks to DM. Construction of the maps was done after fruitful discussions with MM and SL. AV and MD conceived the study, and participated in its design and coordination. AV finalised the manuscript. All authors read and approved the final manuscript. Supplementary Material Additional File 2 Comparative maps of chicken chromosome 5 and human chromosomes 11, 14 and 15. The framework RH map (this study) is shown on the left. Conserved blocks are indicated by coloured plain boxes. Empty boxes show HSA regions for which the chicken homologous part of the genome is not positioned on GGA5. Click here for file Additional File 1 Primer pairs for the studied gene fragments Accession numbers for the chicken EST sequences from which the primers were chosen are given in this Excel file Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521070.xml |
551597 | The Anal Pap Smear: Cytomorphology of squamous intraepithelial lesions | Background Anal smears are increasingly being used as a screening test for anal squamous intraepithelial lesions (ASILs). This study was undertaken to assess the usefulness and limitations of anal smears in screening for ASILs. Methods The cytomorphological features of 200 consecutive anal smears collected in liquid medium from 198 patients were studied and findings were correlated with results of surgical biopsies and/or repeat smears that became available for 71 patients within six months. Results Adequate cellularity was defined as an average of 6 or more nucleated squamous cells/hpf. A glandular/transitional component was not required for adequacy. Dysplastic cells, atypical parakeratotic cells and bi/multinucleated cells were frequent findings in ASIL while koilocytes were infrequent. Smears from LSIL cases most frequently showed mildly dysplastic and bi/multinucleate squamous cells followed by parakeratotic cells (PK), atypical parakeratotic cells (APK), and koilocytes. HSIL smears contained squamous cells with features of moderate/severe dysplasia and many APKs. Features of LSIL were also found in most HSIL smears. Conclusions In this study liquid based anal smears had a high sensitivity (98%) for detection of ASIL but a low specificity (50%) for predicting the severity of the abnormality in subsequent biopsy. Patients with cytologic diagnoses of ASC-US and LSIL had a significant risk (46–56%) of HSIL at biopsy. We suggest that all patients with a diagnosis of ASC-US and above be recommended for high resolution anoscopy with biopsy. | Note For corresponding Editorial, please see Leiman, 2005 [ 25 ] Background The incidence of anal squamous carcinoma and its precursor lesions has increased in recent years particularly among men having sex with men (MSM) [ 1 ]. Prior to the human immunodeficiency virus (HIV) epidemic the incidence of anal cancer in this high risk population was estimated at 36.9 per 100,000 [ 2 ], similar to the incidence of cervical cancer prior to adoption of routine cervical cytology screening programs. Among MSM, the incidence of anal cancer in HIV positive individuals has been estimated to be twice that in HIV negative individuals [ 3 , 4 ]. The American Cancer Society projected that about 4,010 new cases of anal cancer would be diagnosed in the United States in 2004, (up from 3,400 cases in 2000) and that about 580 persons would die of the disease during the year [ 5 ]. Anal and cervical lesions share many histological and pathological characteristics including the implication of human papilloma virus (HPV) in the pathogenesis of precursor squamous intraepithelial lesions and invasive cancer [ 6 ]. Just as routine Pap smear screening has dramatically reduced the incidence of cervical cancer, it is anticipated that screening populations at high risk for anal squamous intraepithelial lesions (ASILs) will reduce the incidence of anal cancer in these individuals. Accordingly we and other laboratories are experiencing a substantial increase in the number of anal smears submitted for cytologic evaluation. This study was performed to assess the usefulness and limitations of anal smears in screening for ASILs. Materials And Methods After approval from the IRB, 200 consecutive anal smears submitted from 198 patients were retrieved from the files of the pathology department at Cedars-Sinai Medical Center. The samples had all been collected from the anal canal using the Rovers endocervex brush (Therapak Corp., Irwindale, CA, distributor for Rovers Medical Devices, OSS, The Netherlands), the Digene cervical sampler brush (Digene Corp. Gaithersburg, MD), or the brush from SurePath sample collection kit (TriPath Care Tech, TriPath Imaging, Inc. Burlington, NC) (Figure 1 ) and submitted in liquid medium (SurePath™, TriPath Imaging™, Burlington, NC). All of the patients were males between the ages of 24 and 67 years (mean: 40.7 yrs., median: 41 yrs). HIV status was available for 79 patients, 37 of whom were HIV positive. Figure 1 Collection brushes. A. Brush from SurePath sample collection kit (TriPath Care Tech, TriPath Imaging, Inc. Burlington, NC.) B. Rovers endocervex brush (Therapak Corp., Irwindale, CA, distributor for Rovers Medical Devices, OSS, The Netherlands) C . Digene cervical sampler brush (Digene Corp., Gaithersburg, MD) Retrieved slides were reviewed by three cytopathologists and evaluated for cellularity and presence of anucleated squamous cells, glandular/ transitional cells (G/TZ), parakeratotic cells (PKs), atypical parakeratotic cells (APKs), koilocytes, binucleated and/or multinucleated squamous cells (B/MSCs), and dysplastic cells. The number of cells exhibiting each of these morphologic features was recorded as none, rare (no more than 2 cells/smear), and present (3 or more cells/smear). For this study cellularity was defined as the average number of nucleated squamous cells per 40x high power field (nsc/hpf) calculated by counting 10 hpfs. All of the anal smears had been reported using a modified Bethesda 2001 System terminology recommended for cervical smears [ 7 ]. After discrepancies were resolved by re-evaluation, discussion, and concurrence by at least two cytopathologists, the diagnoses were as follows: unsatisfactory due to insufficient cellularity (17 smears), negative for intraepithelial lesion or malignancy (NIL; 58 smears), atypical squamous cells of undetermined significance (ASC-US; 42 smears), low grade squamous intraepithelial lesion (LSIL; 59 smears), atypical squamous cells of undetermined significance cannot exclude high grade squamous intraepithelial lesion (ASC-H; 17 smears), and high grade squamous intraepithelial lesion (HSIL; 7 smears). Revised cytologic diagnoses were correlated with concurrent and/or follow up tissue biopsies or with repeat anal smears all obtained within six months. Statistical analyses were performed using the Fishers Test. A two sided p value of 0.05 was considered as significant [ 8 ]. Results Cellularity For purposes of this study we required an average of at least 6 nsc/hpf for cellularity to be considered adequate. This was based on the observation that only smears averaging 6 or more nsc/hpf included abnormal cytologic diagnoses ranging from ASC-US through HSIL whereas smears averaging 5 or fewer nsc/hpf were either NIL or ASC-US. 91% (181) of the 200 smears contained an average of 6 or more nsc/hpf. Of the 19 cases that averaged fewer than 6 nsc/hpf, 17 were designated as unsatisfactory and excluded from the study while two that contained atypical squamous cells were reported as ASC-US and included in the subsequent morphologic analysis. Of note, all of the 7 smears with HSIL and 16/17 smears with ASC-H were cellular with an average of 8 or more nsc/hpf. Anucleated squamous cells Anucleated squamous cells were present in smears that were NIL and in smears with diagnoses ranging from ASC-US to HSIL. There were numerous anucleated squamous cells in 7 smears that were reported as unsatisfactory. Among the abnormal smears, neither the presence nor number of anucleated squamous cells correlated with cytologic diagnosis. Glandular/transitional cells Three or more groups of G/TZ were present in 56% (103) of the smears while rare G/TZ were seen in an additional 18% (33) smears. Of these smears 68% (93/136) had an abnormal cytologic diagnosis (27 ASC-US, 45 LSIL, 14 ASC-H, 7 HSIL). In comparison 26% (47) of smears contained no G/TZ of which 68% (32) were reported as abnormal (15 ASC-US, 14 LSIL, 3 ASC-H) suggesting that the presence of glandular cells did not facilitate abnormal diagnoses. Again all of the 7 smears with HSIL and 12/17 smears with ASC-H contained 3 or more groups of glandular cells, while two smears with ASC-H contained only rare glandular cells. Parakeratotic cells Parakeratotic cells were observed in 71% (130) of the smears in the study. Parakeratotic cells were observed in negative (63%, 37/58) as well as in abnormal (74%, 93/125) cases. In negative cases rare parakeratotic cells were observed more often (in 72%, 27 cases) whereas in smears with epithelial abnormalities presence of rare parakeratotic cells and frequent (>3) parakeratotic cells were about evenly distributed (46%, 43 cases vs 54%, 50 cases). Atypical parakeratotic cells APKs were found in 40% (74) of the 183 smears. The number of cases showing APKs increased with the severity of the dysplasia. There were 3 or more APKs in 22% (41) of the smears constituting 7% of ASC-US, 41% of LSIL, 53% of ASC-H and 71% of HSIL cases. Rare APKs were found in 18% (33) of the smears that were interpreted as ASC-US or above. APKs were not found in any of the negative smears and were seen in 72% of the SIL smears. Koilocytes Classical koilocytes were infrequent (17%) in all diagnostic categories (Figure 2 ). Three or more koilocytes were seen in only 10% (6/59) of the LSIL smears and in 6% (1/17) of the ASC-H cases. Rare koilocytes were found in 2% (1/42) of the ASC-US, 20% (12/59) of the LSIL, and 14% (1/7) of the HSIL smears. Figure 2 Low grade squamous intraepithelial lesion with typical koilocyte. Papanicolaou stain × 40× Multinucleation B/MSCs were observed more frequently in abnormal smears – 81% (101/125) as compared to 33% (19/58) of the NIL smears (Figure 3 ). Among the abnormal cases, 3 or more B/MSCs were present in 59% (74/125 cases) which included 31% (13/42) of ASC-US, 75% (44/59) of LSILs, 76% (13/17) of ASC-Hs, and 43% (4/7) of HSILs. Rare B/MSCs were observed in the remaining 41% cases which included 31% (13/42) of ASC-US, 15% (9/59) of LSILs, 18% (3/17) of ASC-Hs, and 29% (2/7) of HSILs. Although B/MSCs were observed in some smears with cytologic diagnosis of NIL, their presence correlated significantly with an abnormal cytologic diagnosis (p < 0.0001). Figure 3 Low grade squamous intraepithelial lesion with bi- and multinucleated cells Papanicolaou stain × 40× Dysplastic squamous cells 84% (50/59) of the smears diagnosed as LSIL contained 3 or more squamous cells with features of mild dysplasia (Figure 4 ), 6 cases had rare mildly dysplastic cells, and 3 smears contained typical koilocytes but no dysplastic cells. Three or more cells exhibiting moderate/severe dysplasia were present in all smears diagnosed as HSIL (Figure 5 ). ASC-H cases contained 2 or fewer abnormal cells with features of high grade dysplasia in 5 cases, whereas the remaining showed small cells with dense cytoplasm and atypical nuclei raising the possibility of atypical metaplastic and/or atypical parakeratotic cells. 71% of the smears diagnosed as ASC-H (12/17) and HSIL (5/7) also contained 3 or more mildly dysplastic cells and rare mildly dysplastic cells were found in an additional 4 ASC-H and 2 HSIL smears. Figure 4 Low grade squamous intraepithelial lesion with mildly dyplastic cells Papanicolaou stain × 40× Figure 5 A. & B. High grade squamous intraepithelial lesion showing small to medium severely dysplastic cells. Papanicolaou stain × 40× Table 1 summarizes the frequency of these cytomorphologic features with respect to the cytodiagnostic categories. The most frequent findings in smears diagnosed as LSIL were mildly dysplastic and B/MSCs followed by PKs, APKs, and koilocytes. Smears diagnosed as HSIL contained multiple squamous cells with features of moderate/ severe dysplasia, many APKs, and varying numbers of PKs, B/MSCs, and koilocytes. Each of the smears diagnosed as HSIL also contained some mildly dysplastic cells but classical koilocytes were infrequent. Table 1 Frequency and distribution of cytologic findings in anal smears Cytologic diagnosis (n = 183) Cytologic features Parakeratosis Atypical Parakeratosis Koilocytes Bi/Multi-nucleation Mild dysplasia Moderate-severe dysplasia NIL (n = 58) + - - + - - ASC-US (n = 42) + + + + + - LSIL (n = 59) ++ ++ + +++ +++ - ASC-H (n = 17) ++ ++ + +++ ++ + HSIL (n = 7) ++ +++ + ++ ++ +++ +, ++, +++ indicates feature is present in 3 or more cells in 1–33%, 34–74%, or >75% of cases, respectively n = number of cases Correlation with follow up diagnosis Within six months of the index anal smear, follow up consisting of 56 biopsies and 15 smears became available for 39% (71) of the 183 smears constituting 39% (181) of the patients in the study. As shown in Table 2 , 86% (57 of 66) smears diagnosed as ASC-US or above were confirmed as abnormal on subsequent biopsy (54) or repeat smear (12). Follow up for 11 smears diagnosed as ASC-US yielded 4 negative, 2 AIN I, 1 AIN II, and 4 AIN III. Five smears diagnosed as LSIL were negative, 11 were AIN I, and 20 were AIN II-III on subsequent follow up. HPV Digene Hybrid Capture II assay was performed on 3 of the 4 ASC-US cases and 3 of the 5 LSIL cases that were negative on follow up. The 3 ASC-US cases tested negative for HPV DNA. The 3 LSIL cases tested positive for both low and high risk HPV DNA and repeat smears at 8 and 10 months respectively showed persistent LSIL in 2 of these cases. Biopsy confirmed 100% of the HSIL diagnoses and 76% (13/17) of the ASC-H diagnoses. Two cases diagnosed as ASC-H on cytology showed AIN I on biopsy; no follow up became available for the remaining 2 cases that had been diagnosed as ASC-H. Only 5 smears diagnosed as NIL had follow up biopsy; 4 were negative and 1 showed AIN II. Table 2 Follow up diagnoses at 6 months Cytologic diagnoses Diagnosis at followup ‡ Negative AIN I AIN II AIN III NIL (5) 4 - 1 - ASC-US (11) 4† 2 1 4 LSIL (36) 5* 11 17 3 ASC-H (15) - 2 5 8 HSIL (4) - - 1 3 Total cases (71) 13 15 25 18 †3 of these cases tested negative for HPV DNA utilizing Digene HCII *3 of these cases tested positive for high and low risk HPV DNA utilizing Digene HCII and 2 of these cases showed persistent LSIL on follow up at 8 and 10 months respectively ‡ Follow up constitutes a composite of 56 biopsies and 15 repeat smears Discussion ASIL presents unique challenges in diagnosis and clinical management. By decreasing deaths from opportunistic infections, widespread use of highly active antiretroviral agents and other therapies have done much to improve survival of HIV infected individuals. However, because these therapies do not impact the incidence of HPV infections or malignancies in these individuals, the increased life span of HIV+ individuals probably provides the primary explanation for the rapid and continuing increase in HPV associated AIN that these individuals are experiencing [ 9 - 12 ]. With the help of cytology screening, anal squamous carcinoma may be one of very few preventable malignancies in these individuals. Anal cytology has been shown to be a cost-effective screening method for detection of ASIL in populations at high risk for anal carcinoma[ 13 ]. To date there are few studies that address selected cytomorphologic features and diagnostic limitations associated with anal cytology. Based on the follow up available in our study, a diagnosis of ASC-US and above detected 86% of AINs. If one includes the 5 LSIL smears that were negative on follow up biopsy (all 5 confirmed as LSIL on smear review by three cytopathologists, 3 additionally confirmed by repeat smears testing and/or HPV DNA), then the detection rate increase to 94%. Only one AIN lesion was NIL on cytology. This further confirms that anal smears are a sensitive means for detection of ASIL with a sensitivity of 98%. However, as seen in our study anal cytology was a poor predictor of the severity of AIN lesions and frequently underdiagnosed these lesions. Specificity was calculated at only 50%. Follow up for 5 of 11 (46%) ASC-US smears showed AIN II-III and follow up in 20 of 36 (56%) LSIL smears showed AIN II-III. Conversely, of the 43 cases with AIN II-III on biopsy, only 4 (9%) had been correctly diagnosed as HSIL and only 13 (30%) had been reported as ASC-H while 26 (60%) had been reported as LSIL or below on cytology. The percent cases correctly diagnosed as HSIL may be improved from 9 to 13 (21%) if the 5 ASC-H cases with only 1–2 high grade dysplastic cells in the smear were also reported as HSIL. However, this is difficult in "real life" particularly since ASC-H cases frequently also contain atypical parakeratotic cells. In summary, cytology underdiagnosed 35% (25) of the 71 cases with follow up. There were no high-grade overcalls. In our study, a diagnosis of ASC-H or HSIL accurately predicted the presence of AIN II-III in 90% of cases. However, a cytologic diagnosis of ASC-US or LSIL also held a 46–56% chance that a high-grade AIN would be present on biopsy. This figure is high when compared to cervical cytology where ASC-US and LSIL have been associated with only a 5–17% chance of HSIL on biopsy [ 14 , 15 ]. Prior experience with anal smears as documented in the literature[ 16 , 17 ] reveals that anal smears have low sensitivity and specificity for AIN lesions with poor detection of high grade lesions. Defining abnormal cytology to include ASC-US and ASIL, Palefsky et al [ 16 ] reported the sensitivity of anal cytology for detection of biopsy-proven ASIL to be 69% in 407 HIV-positive and 47% in 251 HIV-negative homosexual or bisexual men. The authors also note that the grade of disease on anal cytology did not always correspond to the histologic grade, a finding similar to ours. Anal smears were obtained by dacron swabs in this study. Similarly, Panther et al [ 18 ] reported that anal cytology is an inaccurate predictor of the presence of HSIL, regardless of HIV status. The authors analyzed 153 paired specimens of anal cytology and anal biopsies or surgical excisions and obtained a sensitivity of only 47% for detection of a high-grade lesion (ASIL II, III, or invasive squamous cell cancer). Moreover, in their study a cytologic diagnosis of ASC-US (n = 30) was associated with a broad distribution of histologic diagnoses (7 NIL, 11 AIN I, 7 AIN II, or 5 AIN III). Thus, the authors concluded that the presence of any abnormal anal cytologic finding indicates a potential for HSIL on histologic examination. Our study supports this finding. We attribute the higher detection rate for AIN in our study to the collection of specimens in liquid medium using brushes resulting in greater cellularity of our specimens. Liquid-based preparations have also been shown to virtually eliminate poor fixation/air drying artifacts and markedly reduce obscuring fecal contamination thereby providing superior quality material compared to conventional smears [ 19 , 20 ]. A comparable sensitivity level of 92% has been reported by Friedlander et al [ 17 ] utilizing thin prep liquid based collection medium (Cytyc, Boxborough, MA). There is a paucity of literature regarding criteria for adequate anal cytology samples. The 2001 Consensus Conference in Bethesda [ 7 ] suggested that 3 – 6 nsc/hpf may be considered adequate for SurePath preparations. An average of 6 or more nsc/hpf detected 123 of the 125 of the abnormal cases in this study (2 undetected ASC-US had lower cellularity). Moreover, although smears with diagnoses of HSIL or ASC-H contained 8 or more nsc/hpf, no statistical association was observed between smear cellularity and undetected HSIL lesions. Thus, for SurePath preparations an average of 6 or more nsc/hpf is recommended as an adequacy guideline. The presence of G/TZ was not a prerequisite for adequacy in our study. Smears with and without G/TZ detected the same percentage (68%) of abnormal cases. Although most HSIL and ASC-H smears contained 3 or more groups of G/TZs, absence of G/TZ did not correlate statistically with undetected AIN II/III lesions. Thus we do not consider the presence of G/TZ as essential for adequacy, a situation analogous to cervical Pap smears [ 7 , 21 , 22 ]. Interestingly, we did not encounter any cases of atypical glandular cells of undetermined significance, glandular dysplasia, or adenocarcinoma in our smears. At this time, it is not clear whether individuals at increased risk for ASIL are also at increased risk for anorectal glandular dysplasia and adenocarcinoma. On review of the morphological features of AIN lesions in cytology smears, we noticed some salient features. Dysplastic cells were the most reliable indicators of ASIL/AIN. Typical koilocytes were infrequent, observed in only 17% of SILs, a finding previously observed by Darragh et al [ 19 ] who reported that koilocytes were (a) less frequently observed in anal smears than in cervical smears and (b) absent in some smears that were diagnostic for AIN. APKs, on the other hand, were frequent, present in 72% SILs, and helpful in the diagnosis of ASIL. They were observed most frequently and in greatest numbers in HSIL lesions. Friedlander et al [ 17 ], in a review of 70 ThinPrep anal smears for selected cytomorphologic features reported APKs in 62% and koilocytes in 21% of smears. They emphasized the "ubiquitous presence of atypical keratinized squamous cells" and caution against overinterpretation of these cells as indicative of HSIL or squamous carcinoma. B/MSCs were also good indicators of abnormal smears. Although, they may be seen in small numbers in negative smears, when present in large numbers, B/MSCs should trigger a search for ASIL. Parakeratotic cells, although frequently observed were not helpful in the diagnosis of ASIL, a finding supported by Friedlander et al [ 17 ] who observed parakeratotic cells in 84% of their study cases. Similar studies in cervical smears have shown that parakerstosis in otherwise negative Pap smears, is not a reliable marker for cervical intraepithelial neoplasia [ 23 , 24 ]. In ASC-H and HSIL, high grade squamous cells are usually small, found as single cells or small sheets admixed with mildly dysplastic cells and atypical parakeratotic cells. Careful scrutiny is required to not miss these high grade lesions. Our experience with anal cytology also indicates that other infectious agents are rarely diagnosed in anal smears. Candida was present in one case. Herpes or trichomonads were not seen. Conclusions To summarize, liquid based anal smears provide a sensitive method for screening populations at increased risk for ASIL but have a low specificity for predicting the severity of the lesion. Patients with cytologic diagnosis of ASC-US and LSIL have a significant risk of having HSIL and should be recommended for high resolution anoscopy with biopsy. Competing interests The author(s) declare that they have no competing interests. Authors' contributions SA participated in the acquisition, analysis and interpretation of data and helped to draft the manuscript. AEW participated in its design, in the acquisition, analysis and interpretation of data and helped to write the manuscript. PT participated in its design, in the acquisition, analysis and interpretation of data and helped to write the manuscript. SB conceived of the study, participated in its design, in the acquisition, analysis and interpretation of data and helped to write the manuscript. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC551597.xml |
368171 | Perceptual “Read-Out” of Conjoined Direction and Disparity Maps in Extrastriate Area MT | Cortical neurons are frequently tuned to several stimulus dimensions, and many cortical areas contain intercalated maps of multiple variables. Relatively little is known about how information is “read out” of these multidimensional maps. For example, how does an organism extract information relevant to the task at hand from neurons that are also tuned to other, irrelevant stimulus dimensions? We addressed this question by employing microstimulation techniques to examine the contribution of disparity-tuned neurons in the middle temporal (MT) visual area to performance on a direction discrimination task. Most MT neurons are tuned to both binocular disparity and the direction of stimulus motion, and MT contains topographic maps of both parameters. We assessed the effect of microstimulation on direction judgments after first characterizing the disparity tuning of each stimulation site. Although the disparity of the stimulus was irrelevant to the required task, we found that microstimulation effects were strongly modulated by the disparity tuning of the stimulated neurons. For two of three monkeys, microstimulation of nondisparity-selective sites produced large biases in direction judgments, whereas stimulation of disparity-selective sites had little or no effect. The binocular disparity was optimized for each stimulation site, and our result could not be explained by variations in direction tuning, response strength, or any other tuning property that we examined. When microstimulation of a disparity-tuned site did affect direction judgments, the effects tended to be stronger at the preferred disparity of a stimulation site than at the nonpreferred disparity, indicating that monkeys can selectively monitor direction columns that are best tuned to an appropriate conjunction of parameters. We conclude that the contribution of neurons to behavior can depend strongly upon tuning to stimulus dimensions that appear to be irrelevant to the current task, and we suggest that these findings are best explained in terms of the strategy used by animals to perform the task. | Introduction Determining how information is “read out” of sensory maps in the cerebral cortex is of fundamental importance for understanding how neural activity gives rise to cognitive processes such as perception, planning for action, and working memory. A substantial portion of our knowledge about sensory read-out comes from studies of the middle temporal (MT) visual area, an extrastriate area known to play important roles in processing visual motion information (for reviews, see Maunsell and Newsome 1987 ; Albright 1993 ; Andersen 1997 ). The vast majority of MT neurons are directionally selective ( Zeki 1974 ), and they are arranged in an orderly system of direction columns that run perpendicular to the cortical surface ( Albright et al. 1984 ; Malonek et al. 1994 ). In addition, most MT neurons are also selective for binocular disparity ( Maunsell and Van Essen 1983 ; DeAngelis and Uka 2003 ), and these neurons are organized in a topographic map of disparity preference. Regions of strong disparity selectivity are intercalated among patches of MT neurons with weak disparity tuning, and these strongly tuned regions contain a set of disparity columns that are interwoven with the direction columns ( DeAngelis and Newsome 1999 ). Understanding how information is read out of cortical structures is complicated by the existence of topographic maps for multiple stimulus dimensions or features within a single area, such as those in MT and many other sensory areas of the cortex ( Mountcastle 1997 ). For example, several studies have shown that electrical microstimulation of direction columns in MT can influence perceptual judgments of visual motion during the performance of a direction discrimination task ( Salzman et al. 1990 , 1992 ; Murasugi et al. 1993 ; Salzman and Newsome 1994 ; Bisley et al. 2001 ; Nichols and Newsome 2002 ), and, similarly, that microstimulation of disparity columns can influence perceptual judgments of depth ( DeAngelis et al. 1998 ). In all of these studies, however, the presence and size of the microstimulation effects were highly variable from experiment to experiment, suggesting that the read-out mechanism is more complex than is presently understood. Notably, each of these studies concentrated on a single physiological property—the one of direct relevance to the task at hand—in selecting MT sites for microstimulation experiments (direction tuning for direction discrimination tasks, and disparity tuning for depth discrimination tasks). Potential effects of tuning to multiple stimulus parameters on the read-out mechanism were largely ignored. We therefore designed the current study to ask two specific questions concerning the interaction of direction and disparity tuning in motion perception. (1) Do MT columns that possess or lack disparity tuning contribute differentially to direction judgments? We used electrical microstimulation to test the hypothesis that neurons in the nondisparity-selective regions of MT contribute to motion perception, whereas those in the disparity-selective regions are mainly involved in depth perception. Our hypothesis was confirmed for two of the three monkeys in this study: microstimulation of nondisparity-selective sites produced strong direction biases, whereas stimulation of disparity-selective sites had little or no effect. For the third monkey, microstimulation biased direction judgments when it was applied at either disparity-selective or nonselective sites. For disparity-tuned sites that did yield effects on direction judgments, we also asked a second question. (2) Does the influence of a disparity-tuned column on direction judgments vary as a function of the actual disparity of the motion display? We found that stimulation effects were stronger when the disparity of the visual stimulus matched the preferred disparity of the stimulated column. We conclude that tuning for task-irrelevant stimulus dimensions can exert dramatic effects on the contribution of cortical neurons to a particular perceptual judgment. In extreme cases, columns tuned for an irrelevant dimension (disparity) fail to contribute at all to perceptual judgments of the task-relevant dimension (direction). In less extreme cases, the contribution of a column is modulated by tuning along the task-irrelevant dimension, so that microstimulation effects are obtained primarily when the visual stimulus possesses the right conjunction of properties (direction and disparity) to excite the column optimally. We discuss our findings in terms of the strategies employed by animals to solve the task. Results Microstimulation experiments were performed at 102 recording sites in area MT of three rhesus monkeys (38 sites in monkey S, 36 sites in monkey T, and 28 sites in monkey R) during the performance of the direction discrimination task illustrated in Figure 1 (see Materials and Methods for details). The results are presented in three sections. First, we examine how the effects of microstimulation depend on the strength of disparity tuning at the stimulation site. Second, we present control analyses to exclude trivial explanations for the dependence of microstimulation effects on disparity-tuning strength. Third, for sites where the multiunit (MU) activity exhibited moderate to strong disparity selectivity, we examine whether the effect of microstimulation on direction judgments depends on the disparity at which the visual stimulus is presented. Figure 1 Behavioral Task Used to Assess the Effects of Microstimulation on Direction Discrimination Performance (A) Schematic depiction of the visual stimulus display, showing the FP, the preferred and null response targets, and a variable-coherence random-dot pattern presented within the MU RF of MT neurons. An adjustable fraction of the dots (signal dots, filled circles) moved in the preferred or null direction of the MT neurons, while the remaining dots (noise dots, open circles) were randomly replotted on each refresh of the display, thus creating a masking motion noise. Signal and noise dots could be presented at a range of binocular disparities. Outside the MU RF, the remainder of the visual display was filled with zero-disparity, stationary dots (not shown). (B) Sequence of trial events in the microstimulation experiment. During each trial, the FP appeared first. Roughly 300–500 ms after the monkey achieved fixation, the random-dot pattern appeared in the MU RF. On half of the trials, selected at random, microstimulation was turned on during the visual stimulus. After a 1-s viewing period, dots and microstimulation were extinguished, and the two small target disks appeared. The animal was rewarded for making a saccade to the target corresponding to the direction of motion of the signal dots. Relationship between Efficacy of Microstimulation and Disparity Selectivity We have previously shown that disparity-selective neurons tend to occur within discrete patches of MT ( DeAngelis and Newsome 1999 ). Given this patchy distribution, we asked whether disparity-selective and nonselective patches of MT contribute equally to performance on the direction discrimination task. In all cases, the disparity of the visual stimulus was chosen to elicit a near-maximal response from MU activity at the stimulation site. Also, because microstimulation was only attempted in portions of electrode penetrations where direction selectivity was consistently near-maximal (see Materials and Methods ), all experiments were done at MU recording sites with strong direction tuning. Figure 2 shows data from two illustrative experiments performed on monkey S. Figure 2 A shows the disparity tuning of MU activity at a stimulation site with modest disparity selectivity. Based on this tuning curve, we chose a small near disparity of −0.1° for the random-dot stimuli used in the direction discrimination task (arrowhead in Figure 2 A). Microstimulation at this weakly tuned site strongly biased the monkey's decisions toward the preferred direction of motion ( Figure 2 B). The net effect of this bias was a large leftward shift of the psychometric function (equivalent to 38.7% dots; logistic regression, p << 0.001), with no significant change in the slope of the curve (logistic regression, p > 0.5). This effect is qualitatively similar to those obtained previously in our laboratories (e.g., Salzman et al. 1992 ; Murasugi et al. 1993 ). Figure 2 Effect of Microstimulation on Direction Judgments at Two Illustrative Stimulation Sites from Monkey S A site with weak disparity tuning (DTI = 0.37) is shown in (A) and (B) and a site with strong disparity tuning (DTI = 0.87) is shown in (C) and (D). (A) Disparity tuning of MU activity at a stimulation site with weak disparity selectivity. Filled circles show the mean response to four stimulus presentations at each disparity, with error bars indicating ±1 SE. The solid curve is a cubic spline interpolation. The letters “L” and “R” are plotted at the response levels obtained when the same stimulus is shown only to the left and right eyes, respectively. The dashed horizontal line gives the spontaneous activity level in the absence of any visual stimulus, and the arrowhead denotes the disparity chosen for the direction discrimination task. (B) Effect of microstimulation on direction judgments for the site with the disparity tuning indicated in (A). The proportion of decisions made by the monkey toward the neurons' preferred direction of motion is plotted against the motion coherence of the random-dot stimulus. Open circles show the behavior obtained in the absence of microstimulation; the dashed curve is the best fit to these data using logistic regression. Filled circles and the solid curve show data from randomly interleaved trials in which microstimulation was applied. Note the large leftward shift of the psychometric function, equivalent to 38.7% dots (logistic regression, p < 0.001). (C) Disparity tuning of MU activity at a stimulation site with strong disparity selectivity. Again, the arrowhead denotes the disparity at which dots were presented in the direction discrimination task. (D) Effect of microstimulation on direction judgments for the site with the disparity tuning indicated in (C). In this case, there was no significant shift of the psychometric function when microstimulation was applied ( p > 0.5); the small difference in slope between stimulated and nonstimulated trials is also not significant ( p > 0.25). Figure 2 C shows MU responses for a stimulation site with strong disparity selectivity. Activity at this site exhibited a clear preference for far disparities, and we chose a disparity of 0.4° for the direction discrimination task. Despite the fact that dots were presented at the preferred disparity and MU activity was strongly direction selective (data not shown), microstimulation had no significant effect on the monkey's judgments ( Figure 2 D; logistic regression, p > 0.5 for shift, p > 0.25 for slope). Thus, the activity of neurons at this stimulation site did not appear to contribute to direction discrimination. Figure 3 A summarizes results from 38 similar experiments performed in monkey S (black symbols) and 36 experiments in monkey T (red symbols). The effect of microstimulation on direction judgments is plotted against the Disparity Tuning Index (DTI) of MU activity at each stimulation site. DTI values near 1.0 indicate very strong disparity selectivity, whereas values near 0.0 denote poor tuning (see Materials and Methods , Equation 2 ). Filled symbols denote statistically significant shifts of the psychometric function due to microstimulation (logistic regression, p < 0.05), whereas open symbols indicate nonsignificant effects. The filled and open triangles correspond to the examples shown in Figure 2 B and 2 D, respectively. For both monkeys, the data reveal a strong negative correlation between the magnitude of the stimulation effect and the DTI of MU activity (linear regression, monkey S, r = −0.69, n = 38; monkey T, r = −0.52, n = 36; p << 0.001 for both animals). An analysis of covariance that included monkey identity as a coregressor revealed no significant difference between regression slopes for the two animals (ANCOVA, p > 0.6). Note that microstimulation almost always produced a significant effect on direction judgments in experiments for which the DTI was less than 0.5. In contrast, significant effects of microstimulation occurred much less frequently when the DTI exceeded 0.5. Figure 3 Relationship between the Efficacy of Microstimulation and the Strength of Disparity Tuning Each datum represents one experiment, with filled symbols denoting significant effects of microstimulation (logistic regression, p < 0.05). The vertical axis shows the leftward shift of the psychometric function induced by microstimulation. Thus, positive values correspond to shifts toward the preferred direction of motion. The horizontal axis shows the DTI for MU activity at each stimulation site. (A) Data for monkey S (black symbols, n = 38) and monkey T (red symbols, n = 36). For both animals, there is a highly significant tendency for the effect of microstimulation to decline with increasing disparity selectivity (linear regression, r = −0.69 for monkey S, r = −0.52 for monkey T, p < 0.001 for both). The black, filled triangle denotes the experiment depicted in Figure 2 A and 2 B; the black, open triangle corresponds to the experiment of Figure 2 C and 2 D. (B) Data for monkey R ( n = 28). In this case, the two variables are uncorrelated ( r = −0.025, p > 0.9). The result in Figure 3 A is interesting for two main reasons. First, it suggests that a substantial amount of variance in the efficacy of microstimulation may be accounted for by the disparity tuning of neurons at the stimulation site. This may explain why previous microstimulation studies reported a large number of nonsignificant effects (e.g., Salzman et al. 1992 ; Murasugi et al. 1993 ). In those studies, the disparity tuning of activity at stimulation sites was not measured, and all stimuli were presented at zero disparity. Second, this result is interesting because it suggests that monkeys S and T may read out activity from MT in a manner that is highly dependent on the functional architecture for binocular disparity. In formulating decisions about motion direction, these animals appeared to rely most heavily on direction-selective columns that were nonselective for disparity. In contrast, columns that were strongly tuned for disparity exerted substantially less influence on the animals' decisions. We shall address possible explanations for this finding in the Discussion. We obtained quite different results in a third animal, monkey R ( Figure 3 B). For this animal there was no significant correlation between the strength of the microstimulation effect and the DTI ( r = −0.025, p > 0.9, n = 28). We often observed significant effects of microstimulation at sites with strong disparity tuning. It is worth emphasizing that all of the data in Figure 3 were collected using a near-optimal stimulus disparity. Thus, monkey R's decisions were usually biased by microstimulation of any direction column that was strongly activated by the visual stimulus. Effects of microstimulation at nonoptimal stimulus disparities will be addressed in a later section. The individual differences between monkeys in the data of Figure 3 may reflect different strategies used by the animals to extract motion information from area MT. Under the conditions of our task, it appears that monkeys S and T relied predominantly on direction columns with poor disparity tuning, whereas monkey R seemed also to utilize motion signals carried by regions of MT with strong disparity selectivity. In principle, this difference in strategy might have allowed monkey R to perform better on the task, as he could pool MT responses over a larger population of neurons. To examine this possibility, we analyzed the monkeys' behavioral data from trials when microstimulation was turned off, and we computed a psychophysical threshold for each stimulus disparity in each experiment (see Britten et al. 1992 for methodological details). Interestingly, we found that the mean psychophysical threshold for monkey R (16.1% ± 1.2% standard error [SE], n = 51) was significantly lower than the mean psychophysical thresholds for monkey S (21.5% ± 0.9% SE, n = 89) and monkey T (22.8% ± 1.0% SE, n = 70) (Student's t-test, p < 0.0005 for both comparisons). In contrast, the average slope of the psychometric functions did not differ between the three animals (ANOVA, p > 0.7). We shall consider these issues further in the Discussion. Functional Segregation of the Perceptual Effects of Microstimulation Monkeys T and R were subjects both in the current set of experiments and in a separate study in which we showed that stimulation of disparity-tuned columns influences perceptual judgments of depth ( DeAngelis et al. 1998 ). For these animals, therefore, we were able to compare directly how the strength of microstimulation effects in these two tasks depended on the disparity selectivity of the stimulation sites. Figure 4 shows, for monkey T, the strength of the microstimulation effects in the direction discrimination task (red symbols, reproduced from Figure 3 A) and in the depth discrimination task (blue symbols, r = 0.45, p = 0.01, n = 32) as a function of the DTI. The data reveal a clear inverse relationship between the two effects. Columns with low DTIs produce large effects on direction discrimination performance and little or no effect on depth discrimination. In contrast, columns with large DTIs show the converse pattern. In this monkey, therefore, the functional segregation of MT columns according to the strength of disparity tuning is particularly clear. Figure 4 Effects of Microstimulation on Direction Discrimination and Depth Discrimination for One Animal (Monkey T) That Was Tested in Both Tasks Plotted as a function of DTI, red circles indicate the horizontal shift of the psychometric function induced by microstimulation during the direction discrimination task with stimuli at the preferred disparity for each site (left axis). These data, along with the best linear fit (solid line), are replotted from Figure 3 A. Blue circles denote the effects of microstimulation during a depth discrimination task with stimuli at the preferred direction of motion for each site (right axis; data from DeAngelis et al. 1998 ). The dashed line shows the best linear fit to these data ( r = 0.45, p = 0.01, n = 32). It is important to note that the differences between animals seen in Figure 3 cannot be explained by any training experience involving the depth discrimination task. The present experiments were completed before any of the animals were subsequently trained to perform the depth discrimination task. Excluding Alternative Explanations for Dependence of Microstimulation Effects on Disparity Selectivity The striking result in Figure 3 A could be explained trivially if disparity-tuned sites provide relatively poor information about motion direction. This situation might occur under at least three possible conditions: (1) sites with strong disparity tuning exhibit weaker or broader direction selectivity than nondisparity-tuned sites, (2) direction preferences are more variable within microstimulation sites that have strong disparity tuning (i.e., direction columns are smaller or less orderly), or (3) neural responses are simply weaker at sites with strong disparity tuning. If disparity-tuned sites indeed provide less-reliable information about the direction of motion, it would be no surprise that the monkey ignored these sites in forming its perceptual decisions. We now describe a battery of analyses to test these possibilities. Unfortunately, we cannot address the first possibility with our current data set since we did not collect quantitative direction-tuning curves in each experiment due to time limitations (see Materials and Methods ). We have, however, examined the relationship between disparity tuning and direction tuning in a large number of separate MU recording experiments conducted in monkey S ( n = 162) and in three additional monkeys ( n = 409). Across this unbiased sample of 571 recordings, we find no significant correlation between Disparity Tuning Index (DTI) and Direction Tuning Index ( r = 0.09, p = 0.11; Figure S1 ). A similar lack of correlation between direction and disparity selectivity was recently reported for a sample of 501 single units recorded in MT ( DeAngelis and Uka 2003 ). We also find no significant correlation ( r = 0.07, p = 0.17) between direction-tuning bandwidth and DTI across our sample of 571 MU recordings, indicating that the sharpness of direction tuning also does not covary with disparity selectivity. These observations, combined with the fact that we only performed microstimulation experiments in the portions of MT with the strongest direction tuning (see Materials and Methods ), make us quite confident that the findings shown in Figure 3 A do not result from any correlation between direction and disparity tuning in MT. The last two concerns described above can be addressed directly from the primary data set described in this paper. To evaluate the possibility that direction preferences are more variable within regions of strong disparity tuning (point 2 above), we computed the standard deviation (SD) of directional preferences within a 400-μm region around each microstimulation site. We find no significant correlation between the strength of microstimulation effects and the SD of preferred directions ( r = −0.04, p = 0.68; Figure S2 A) and, similarly, no significant correlation between the DTI and the SD of preferred directions ( r = −0.05, p = 0.65; Figure S2 B). Thus, the findings shown in Figure 3 A do not result from variability in directional preferences. This analysis was performed using estimates of preferred directions from our receptive-field (RF) mapping procedure (see Material and Methods). A separate analysis shows that these estimates have sufficient accuracy and precision for our purposes ( Figure S3 ). Systematic variations in responsiveness as a function of disparity tuning (point 3 above) can be excluded as a possible explanation for our findings because there is no correlation between the peak response of MU activity and the DTI ( r = −0.09, p = 0.43; data taken from the disparity-tuning curve measured at each stimulation site). Correspondingly, there is no significant correlation between the strength of the microstimulation effects and the peak MU response ( r = 0.17, p = 0.08), and all of the microstimulation effects in Figure 3 were obtained using the disparity that elicited the largest MU response. Similar findings were obtained for each monkey analyzed separately. Finally, using a dataset of 409 MU recordings and a multiple regression analysis, we also tested for correlations between DTI and several other response properties, including preferred speed, Speed Tuning Index, RF eccentricity, optimal stimulus size, and percentage of surround inhibition. None of these variables was significantly correlated with DTI ( p > 0.1 for all), indicating that variations in these parameters are also unlikely to account for the results shown in Figure 3 A. Collectively, the analyses described above indicate that the failure of microstimulation to elicit behavioral biases at disparity-selective sites cannot be explained by any basic response properties of MT neurons. Selectivity of Microstimulation Effects for Binocular Disparity Although significant microstimulation effects were rare at sites with strong disparity tuning in monkeys S and T, significant effects occurred at a good number of sites with moderate disparity tuning (i.e., DTI > 0.4). At these sites, and at many sites in monkey R, we could ask whether the efficacy of microstimulation varied when the random-dot stimulus was presented at different points along the disparity-tuning curve of the stimulated column. The logic of this experiment is illustrated for a disparity-selective site in Figure 5 A. We hypothesize that neural activity in an MT column that prefers far disparities (shaded oval in 5 A) is used primarily to judge direction of motion for planar stimuli at far disparities. Signals from this column should not influence perceptual decisions when the visual stimulus has a near disparity. Accordingly we predict that microstimulation should bias the monkey's choices when dots are presented at the far disparity ( Figure 5 A, left) and have little or no effect when dots are presented at the near disparity ( Figure 5 A, right). “Tuned” microstimulation effects of this nature would indicate that motion signals are read out of MT in a disparity-specific fashion. Alternatively, one could imagine that motion signals are pooled across all disparity columns, in which case we should observe nonselective microstimulation effects that are similar for both far and near disparities. For nondisparity-selective stimulation sites ( Figure 5 B, the receptive field is elongated in depth with respect to the animal's head), we predict that microstimulation will bias the monkey's choices regardless of the binocular disparity given to the visual stimulus. Figure 5 Schematic Illustration of Experiments Designed to Examine Whether Microstimulation Has Disparity-Dependent Effects on Direction Discrimination Each panel is the top-down view of a subject, whose two eyes are represented by the large, open circles. The plane of fixation is indicated by the long horizontal line, along which dots are plotted to represent the stationary, zero-disparity background of random dots. The shaded oval represents the RF—in width and depth—of a hypothetical cluster of MT neurons. (A) Depiction of a disparity-selective site that prefers far disparities (the RF is located behind the plane of fixation). Here, we expect microstimulation to have a significant effect on direction discrimination when dots are presented at the preferred disparity (left) but not when dots are presented at a nonpreferred disparity (right). (B) Depiction of a nondisparity-selective site. The RF is extended in depth, indicating that it has little disparity selectivity. In this case, the effect of microstimulation should not depend on whether dots are presented at either a far (left) or a near (right) disparity. Figure 6 shows an example of a nicely tuned microstimulation effect. MU activity at this stimulation site exhibited moderate disparity selectivity, with a tuning curve that peaked just to the right of zero disparity ( Figure 6 A). We performed the microstimulation experiment at two different disparities, denoted by the arrowheads in Figure 6 A. In the first block of trials, we presented dots at the preferred disparity (+0.1°), and microstimulation produced a clear leftward shift of the psychometric function that was equivalent to 17% dots ( Figure 6 B; logistic regression, p < 0.001). In the second block of trials, we presented dots at the nonpreferred disparity (−0.5°), and microstimulation exerted no effect whatsoever on the monkey's choices ( Figure 6 C; logistic regression, p > 0.5). To be certain that this effect did not result from some nonstationarity in electrode position, cell responsiveness, etc. ( Salzman et al. 1992 ), we collected a third set of data with dots again presented at the preferred disparity. Again, microstimulation produced a leftward shift of the psychometric function equivalent to 17% dots ( Figure 6 D; p < 0.001). At this stimulation site, therefore, we were able to switch the result from a very substantial effect to no effect and back again simply by manipulating the disparity of the random-dot stimuli. Figure 6 Example of a Disparity-Selective Microstimulation Effect (A) Disparity tuning of MU activity at this stimulation site. Conventions as in Figure 2 A. Arrowheads and letters indicate the disparity values used to perform the microstimulation experiments illustrated in (B), (C), and (D). DTI = 0.55. (B) First block of direction discrimination trials, in which dots were presented at the preferred disparity (0.1°). The stimulation psychometric function (filled symbols, solid curve) is shifted well to the left of the nonstimulation function (open symbols, dashed curve) by an amount equivalent to 17% dots (logistic regression, p < 0.001), with no corresponding change in the slope of the curve ( p > 0.9). (C) Second block of discrimination trials, in which dots were presented at a nonpreferred disparity (-0.5°). In this case, the two psychometric functions did not differ significantly in horizontal position ( p > 0.8) or in slope ( p > 0.5). (D) Third block of discrimination trials, with dots again presented at the preferred disparity (repeat of [B]). Again, microstimulation produced a leftward shift equivalent to 17% dots ( p < 0.001). The small increase in the slope of the stimulation psychometric function is not significant ( p > 0.2). Figure 7 depicts data from experiments performed at a nondisparity-selective site. The MU activity at this site exhibited little selectivity for binocular disparity, although the tuning was marginally significant ( Figure 7 A; ANOVA, p = 0.025). We chose three different disparities at which to perform the direction discrimination task: 0°, 0.6°, and −0.6°. Figure 7 B– 7 D show the effects of microstimulation on direction judgments at these three different disparities. In each case, microstimulation induced a significant leftward shift of the psychometric function (logistic regression, p < 0.0001), with no corresponding change in slope ( p > 0.4). Figure 7 Example of a Nondisparity-Selective Effect of Microstimulation at a Site with Poor Disparity Tuning (A) MU disparity-tuning curve; DTI = 0.27. (B–D) Effects of microstimulation on direction discrimination when dots were presented at disparities of 0°, 0.6°, and −0.6°, respectively. In each case, the leftward shift of the psychometric function is highly significant (logistic regression, p < 0.0001) while the slopes were unchanged ( p > 0.4). The individual example sites in Figures 6 and 7 conform well to the predictions of our hypothesis outlined in Figure 5 . We observed considerable variation across the population of experiments, however, so we quantified the disparity selectivity of each microstimulation effect in order to evaluate statistical trends in the population. We performed this analysis on 65 out of 102 data sets for which we had applied microstimulation at both the preferred and nonpreferred disparities, and for which the effect of microstimulation was significant ( p < 0.05) for at least one of the two disparities. We computed a Microstimulation Selectivity Ratio (MSR) as follows: where E P is the effect of microstimulation when dots are presented at the preferred disparity, and E NP is the effect when dots are presented at the nonpreferred disparity. This index is a standard contrast measure, except that the quantities in the denominator are absolute values. This formulation was necessary to keep the index bounded between −1.0 and 1.0. Figure 8 shows the MSR plotted against the DTI, with different symbols denoting data from the three monkeys. To analyze the relationship between MSR and DTI without confounding possible effects of monkey differences, we performed an analysis of covariance (ANCOVA) with DTI and monkey identity as factors. This analysis reveals a significant correlation between MSR and DTI (ANCOVA, r = 0.37, F(1,61) = 9.9, p < 0.005), with no significant differences between the three monkeys (F(2,61) = 0.14, p > 0.8). Figure 8 Quantitative Summary of the Disparity Selectivity of Microstimulation Effects The ordinate is the MSR, which was computed from the leftward shifts of the psychometric function measured at both the preferred and nonpreferred disparities ( Equation 1 ). The abscissa is the DTI of MU activity at each stimulation site. Data are shown for 65/102 stimulation sites for which a significant effect of microstimulation was observed at either the preferred or nonpreferred disparity. Results from monkeys S, R, and T are shown as black circles, blue squares, and red triangles, respectively. Data points with an MSR equal to1.0 correspond to cases where there was a leftward shift of the psychometric function at the preferred disparity and a rightward (i.e., null-direction) shift, or no shift, at the nonpreferred disparity. The dashed line shows the best linear fit to the data (ANCOVA, r = 0.37, p < 0.005). Thus, as hypothesized (see Figure 5 ), microstimulation generally exerted selective effects at sites with strong disparity tuning, and nonselective effects at sites with poor tuning. Although this relationship between MSR and DTI was not very strong (as evidenced by the large scatter of points in Figure 8 ), almost all of the strongly selective microstimulation effects (MSR > 0.5) occurred at sites with moderate to strong disparity tuning (DTI > 0.4). The upper left corner of Figure 8 is notably unpopulated, indicating that selective effects of microstimulation did not occur at poorly disparity-tuned sites. Possible reasons for the variability in Figure 8 will be discussed below. Discussion Using microstimulation to probe the link between neuronal activity and behavior, we have tested whether the contribution of MT neurons to direction discrimination depends on their disparity selectivity. This work addresses the general question of how neurons that are tuned to multiple stimulus dimensions contribute to behavior in situations where one or more of these stimulus dimensions are task-irrelevant. Relatively little is currently known about how the responses of sensory neurons are pooled by decision mechanisms (see Shadlen et al. 1996 ) and how the demands of a particular task alter the pooling strategies that are used. The present study provides new insights into these issues. Our first main finding is that the strength of tuning for binocular disparity (an irrelevant variable in the direction discrimination task) accounts for a substantial proportion of variance in the strength of microstimulation effects (48% of variance for monkey S, 27% for monkey T). Two of our three monkeys relied mainly on nondisparity-selective sites for performing the direction discrimination task, even though the stimulus was tailored to the disparity preference of all sites. Our second main finding is that the efficacy of microstimulation is reduced when the stimulus disparity is adjusted to be suboptimal for neurons at the stimulation site. Thus, to the limited extent that our monkeys made use of signals from disparity-selective neurons, they did tend to monitor more closely neurons with tuning properties that were matched to the stimulus. This latter finding can be viewed as a generalization to three dimensions of the previous result that microstimulation effects were reduced by moving the visual stimulus out of the RF of the stimulated neurons ( Salzman et al. 1992 ). Effects of Disparity Tuning Strength: Local Circuit Properties, Connectivity, or Task Strategy? How can we explain the finding (see Figure 3 A) that regions of MT that are selective for both direction and disparity generally do not contribute to direction discrimination, despite the fact that stimulus parameters were always optimized for the disparity tuning of these neurons? One relatively uninteresting possibility is that unknown cellular or circuit properties specific to disparity-sensitive columns limit the efficacy of microstimulation. For example, disparity-selective regions of MT, which tend to be segregated from nonselective regions ( DeAngelis and Newsome 1999 ), might have different biophysical properties, metabolic properties, local connectivity, or patterns of afferent input. Such factors are unlikely to account for our results, however, given the data illustrated for monkey T in Figure 4 . Because columns with large disparity-tuning indices generally fail to yield effects in the direction discrimination task but yield good effects in the disparity discrimination task, we can reject explanations based on factors endogenous to local regions of MT. A second possibility is that the output connections of disparity-selective and nonselective regions of MT have different targets, such that decision mechanisms for motion receive input from nondisparity-selective portions of MT whereas decision mechanisms for depth receive input from disparity-tuned regions. Experiments have not been done to test this hypothesis, so we cannot rule it out. One argument against this idea, however, is that one of the three monkeys (monkey R) did not show a dependence of microstimulation effects on disparity selectivity (see Figure 3 B). Thus, for anatomical projections of MT to explain our findings, we would have to assume that both disparity-selective and nonselective regions of MT project to decision mechanisms for motion perception in monkey R, but not in the other two animals. Experiments involving tracer injections into regions of MT chosen for strong versus weak disparity tuning would be valuable for examining this possibility. A third possibility, which we favor, is that our findings reflect the strategy that each monkey adopted for reading out motion signals from MT during the extended period of training on the task. In this scenario, all regions of MT could project to decision mechanisms for both motion and depth, but the relative weights of the connections would vary with the animal's task strategy. This would allow the read-out strategy to be altered rapidly based on the demands of the task. In our experiments, one strategy for performing the task would be to extract motion signals from all MT columns with the appropriate direction selectivity and spatial RF, regardless of their disparity selectivity. This strategy would entail pooling signals from many columns, including those with unfavorable signal-to-noise ratios due to their poor responsiveness to stimuli of nonoptimal disparity. A second strategy, which could yield better performance, would be to monitor primarily columns that are maximally activated by the stimulus, but this would entail pooling responses from columns with different disparity preferences when the stimulus disparity changed. Thus, some sort of complex “switching” would be required to route information to the decision process from the set of columns optimal for each experiment. A third, and perhaps the simplest, strategy would be to monitor motion signals only from the nondisparity-selective portions of MT; these columns would respond well to all stimulus disparities, providing a good signal-to-noise ratio for all stimulus sets on which the monkey was trained. This strategy offers the further advantage that one can monitor the same set of columns for all stimulus conditions in our task. Given that correlated noise among neurons limits the benefits of pooling across large populations of neurons ( Britten et al. 1992 ; Shadlen et al. 1996 ), this last strategy might yield performance almost as good as that obtained by monitoring all columns that are strongly activated by a particular disparity. If monkeys were to adopt the simple strategy of monitoring only the nondisparity-selective regions of MT, then the microstimulation results shown in Figure 3 A (monkeys S and T) would be expected. The very different results seen for monkey R (see Figure 3 B) would not be the result of distinct output projections from disparity-selective and nonselective regions of MT, but rather would indicate that synaptic weights were dynamically modulated in monkey R to route information to decision circuits from all columns that were well activated by the stimuli. This conclusion is supported by the data shown in Figures 3 B and 8 , which together show that monkey R monitors direction signals from disparity-selective columns provided that the stimulus disparity matches the disparity preference of the neurons. Indeed, our finding that monkey R had a significantly lower psychophysical threshold than the other two animals is fully consistent with the task strategy suggested by our microstimulation results. In future experiments, it will be interesting to find ways to alter the monkeys' task strategies while using microstimulation to probe the contributions made by a single column of MT neurons. Disparity Tuning of Microstimulation Effects: Origins of Variability We found a statistically significant, but relatively weak, dependence of microstimulation effects on the difference between the preferred disparity of MT neurons and the stimulus disparity (see Figure 8 ). What accounts for the relatively large variability in these data? For monkeys S and T, microstimulation effects were usually weak at disparity-selective sites, and this could contribute to the scatter seen in Figure 8 . If this were the case, then the correlation in Figure 8 should be stronger for monkey R, given that microstimulation of disparity-selective sites was usually quite effective in this animal. Inspection of Figure 8 reveals that this is not the case, however. In fact, the correlation coefficient between MSR and DTI (see Figure 8 ) was stronger for monkey S ( r = 0.55, p < 0.01) than for monkey R ( r = 0.36, p = 0.15). Another possible source of variability in Figure 8 involves the fact that we tested the effects of microstimulation in different blocks of trials for different disparities (see Materials and Methods ). Given that microstimulation effects frequently wane as a function of time ( Salzman et al. 1992 ) and are sensitive to small perturbations in electrode position ( Murasugi et al. 1993 ), this block design would be expected to add noise to the population data. Another likely source of variability involves the selection criteria for microstimulation sites. We attempted to center our electrode in the midst of a region of constant direction tuning, but we did not select sites based on the consistency of disparity tuning within the neighborhood of the electrode. Thus, even when MU activity at the stimulation site was strongly disparity tuned, our electrode may have been positioned close to a boundary between a near column and a far column, or simply within a region where disparity tuning was changing rapidly ( DeAngelis and Newsome 1999 ). This may have allowed microstimulation to activate a population of neurons that responded well to both stimulus disparities in some cases. Considering these likely sources of variability, the fact that we see a significant overall effect in Figure 8 provides solid evidence that monkeys do monitor more closely columns of neurons with stimulus preferences that match the prevailing stimulus parameters. It is worth noting that our ability to observe this effect may have been aided by the blocked design that we employed. Because the stimulus disparity was fixed within a block of trials, monkeys could selectively monitor MT columns tuned to that disparity. In contrast, microstimulation effects might be less disparity selective if the stimulus disparity varied from trial to trial, such that the animal was uncertain about which disparity columns to monitor. General Implications Many of the standard experimental approaches in systems neuroscience (e.g., single-unit recording, optical imaging, functional MRI) find their utility in exposing correlations between neuronal activity and external stimuli or behavioral states. Of course, finding signals that are correlated with behavior does not prove that those signals underlie the behavior. The value of electrical microstimulation, reversible inactivation, and lesion techniques is that they can establish causal links between neural activity and behavior. In this study, we only microstimulated at sites in MT that had strong directional selectivity; thus, one might assume that all sites would be equally likely to contribute to performance of the direction discrimination task. The central finding of this study is that the contribution of MT direction columns to task performance is modulated by the tuning of the neurons to a stimulus variable that is irrelevant to completion of the task. Thus, even within a single area of the brain, the causal linkage between neurons and behavior may depend on uncontrolled stimulus dimensions, and may be determined by unexpected factors such as task strategy. This result highlights the importance of causal techniques for studying the neural basis of behavior, and suggests that microstimulation studies may be able to reveal how high-level task strategies modulate the read-out of neuronal signals from topographic maps in the brain. Materials and Methods Our standard procedures for surgical preparation, training, and electrophysiological recording from rhesus monkeys (Macaca mulatta) are described elsewhere ( Britten et al. 1992 ). In addition, extensive details of our microstimulation techniques have been published elsewhere ( Salzman et al. 1992 ). Here, we briefly describe our methods, focusing on aspects that are particularly relevant to the present study. Surgical preparation Three adult macaques were used in this study (two males and one female), all of which had previously been subjects in other studies in the laboratory. Each animal had a scleral search coil implanted in at least one eye (monkey S had coils in both eyes) to allow monitoring of eye position. In addition, each subject was equipped with a head restraint post and a stainless-steel recording chamber that was positioned over the occipital cortex. Electrodes were introduced into the visual cortex through a transdural guide tube that was positioned within a square array of grid holes at 1-mm intervals ( Crist et al. 1988 ). Visual stimuli and tasks All visual stimuli used in this study were dynamic random-dot patterns presented on a standard 21-in. color display (Sony 500PS, Sony Corporation, New York, New York, United States). The display subtended 39° × 29° at the viewing distance of 57 cm and was refreshed at a rate of 100Hz. The visual stimuli were generated by a Cambridge Research Systems VSG2/3 board (Cambridge Research Systems Ltd., Rochester, United Kingdom) that was housed in a dedicated PC. Stereoscopic presentation was achieved through the use of ferroelectric shutters (Displaytech, Inc., Longmont, Colorado, United States) that were switched in antiphase for the two eyes. Left and right half-images were presented on alternate video frames, and the shutters were synchronized to the vertical refresh, thus exposing each eye to the appropriate visual stimulus on alternate frames. With this technique, the quality of stereo separation is limited mainly by phosphor persistence. Thus, random-dot stimuli were always presented using the red gun only, since the red phosphor has a much faster decay than either the green or blue phosphors. We achieved a contrast ratio of approximately 40:1 (“open” eye:“closed” eye) using this approach, and “ghosting” artifacts were barely visible, even under dark-adapted conditions. Monkeys performed two separate tasks in these experiments: a visual fixation task, and a direction discrimination task. In the visual fixation task, a small, yellow fixation point (FP) appeared to begin each trial, and the monkeys were required to maintain fixation within a 2° × 2° or 3° × 3° electronic window, centered on the fixation target, until the fixation target was extinguished. The monkeys received a liquid reward for successful fixation, typically 0.1–0.15 ml of water or juice. If the monkey broke fixation before the end of a trial, the trial was aborted, the data were discarded, and the monkey was not rewarded. During the fixation period, a bipartite random-dot stimulus was presented for 1.5 s. It consisted of a central, circular patch of coherently moving dots that could be presented with variable binocular disparity, and which covered the receptive field of the MT neurons under study. To assist the monkey in maintaining binocular convergence on the FP, we filled the remainder of the visual display with zero-disparity dots that were randomly repositioned every fourth video frame (25 Hz), thus producing a twinkling, zero-disparity background. Each dot was approximately 0.1° in size. Dot density was 32 dots/(deg 2 -s) for the central patch and 8 dots/(deg 2 -s) for the background. In the direction discrimination task (see Figure 1 ), each trial also began with the presentation of a FP. Once the monkey fixated, a bipartite random-dot pattern again appeared. The central, circular patch had variable motion coherence. On each video frame, a fraction of the dots (“signal” dots; filled in Figure 1 A) moved coherently in either the preferred or null direction of the MT neurons under study. The remaining dots in this center patch (“noise” dots; unfilled in Figure 1 A) were replotted at random positions in each video frame. Thus, the strength of the motion signal (percent coherence) is determined by the percentage of signal dots in the display (see Britten et al. 1992 for additional details). Signal dots moved in the preferred direction on one-half of all trials and in the null direction on the remaining trials (randomly interleaved). Outside of the center patch, the remainder of the video display was filled with stationary zero-disparity dots to serve as a background. The random-dot motion stimulus ran for 1 s, after which both the FP and the dots disappeared. Two disk-shaped targets then appeared, aligned with the axis of stimulus motion, and the monkey indicated its perceived direction of motion by making a saccade to the target toward which the signal dots moved. Again, the monkeys received liquid rewards for correct choices. Incorrect choices resulted in no reward and a brief time-out period between trials. Dot size and density were as described above for the fixation task. Microstimulation On one-half of the direction discrimination trials, selected at random, electrical microstimulation was applied during presentation of the random-dot stimulus. The microstimulation current was delivered through a stimulus isolation unit (Bak Electronics, Inc., Mount Airy, Maryland, United States) operating in constant-current mode. The current was a train of biphasic pulses with a frequency of 200 Hz and an amplitude of 20 μA. Each biphasic event consisted of a 200-μs cathodal pulse followed by a 200-μs anodal pulse, with a 100-μs gap between the two. Microstimulation parameters were chosen to elicit robust perceptual biases but were well below the current and frequency levels at which stimulation has been shown to flatten the slope of the psychometric function ( Murasugi et al. 1993 ). Microstimulation was applied through the same parylene-coated tungsten electrode (MicroProbe, Inc., Carlsbad, California, United States) that was used to record unit activity in MT. Selection of microstimulation sites We searched for candidate microstimulation sites by examining the tuning properties of MU activity at regular intervals of 100 μm along electrode penetrations through MT. At each recording site, we rated the strength of direction selectivity on a scale from 1 to 3 (3 = strongest tuning), and we carefully estimated the preferred direction of motion (see Figure S3 regarding the accuracy and precision of these estimates). We accepted a site for microstimulation when there was a span of at least 300 μm in which direction selectivity was consistently rated a 3 and the preferred direction of motion varied by no more than 45°. Disparity selectivity had no bearing on our selection of stimulation sites in this study; thus, our sample of stimulation sites should be unbiased in terms of disparity tuning. Once a suitable span of direction tuning was identified, we retracted our electrode to approximately the middle of the span and began quantitative testing. Experimental protocol At each identified microstimulation site, we performed the following battery of tests. (1) First, we carefully mapped the MU RF of the MT neurons by dragging a small patch of moving dots (100% coherence) through the RF with a pointing device. Spike densities were plotted on a Cartesian map of visual space during this process to facilitate visual mapping of the RF. In addition, we mapped the direction and speed selectivity of the neurons by moving a cursor throughout a polar direction-speed domain while spike densities were again plotted on the screen. From this procedure, we determined the location and size of the MU RF, as well as the preferred direction and speed of motion. We also estimated the range of disparities over which the neurons were selective, and these parameters were then used in subsequent quantitative tests. (2) We next measured a disparity-tuning curve for MU activity at the identified stimulation site, while the monkey performed a block of fixation trials. Nine evenly spaced disparities were typically tested within the disparity range determined from our initial qualitative probing (e.g., see Figure 2 A and 2 C). Monocular control conditions were also included, and all trial conditions were block randomized and repeated four to five times. For MU responses in MT, this number of repetitions proved more than adequate to obtain tuning curves with small error bars. The central patch of dots (which varied in disparity) was adjusted to be slightly larger than the MU RF, and all dots within this central patch moved coherently in the neurons' preferred direction of motion (at the preferred speed). Note that in a previous study ( DeAngelis and Newsome 1999 ), we established that these MU measurements of disparity tuning in MT reliably predict the disparity tuning of single units within the neighborhood of the electrode tip. Due to limitations of recording time, we did not measure a quantitative direction-tuning curve at each microstimulation site. (3) We next applied microstimulation during blocks of trials in which the monkey performed the direction discrimination task (see Figure 1 ) along the preferred-null axis of motion. Motion coherence was varied from trial to trial within a range of values that bracketed the psychophysical threshold of each animal, as determined during training. At each site, we collected at least two blocks of discrimination trials: one at the preferred disparity and one at the nonpreferred disparity. The order of these two blocks was counterbalanced across experiments, and statistical analyses revealed no significant effects of block order on any of our results (ANCOVA, p > 0.3). Whenever possible (e.g., see Figure 6 D), we performed a third block of trials at the same disparity tested in the first block. For sites with no clear disparity preference at all (as measured on-line), the choice of disparities for the direction discrimination task was arbitrary. In these cases, we typically performed three blocks of trials with disparities of (approximately) −0.5°, 0°, and 0.5°, although the order in which these disparities were presented was varied from site to site. During training, we attempted to interleave two different disparities within a single block of direction discrimination trials. Although this approach would clearly be superior to a blocked design in some respects, we found that interleaving the disparities resulted in poorer discrimination performance because the monkeys' choices were biased by stimulus disparity when the motion signal was weak. We therefore settled for the block design described above. Data collection Extracellular recordings were made with tungsten microelectrodes (impedance typically 0.5–1.0 MΩ; MicroProbe, Inc.). Neural signals were amplified, filtered (0.5–5.0 kHz), and discriminated using conventional electronics (Bak Electronics, Inc.), and event times were stored on magnetic disk with 1 ms resolution. To record MU activity, we simply set the threshold level of our window discriminator to approximately 1–2 SD above the noise level. Thus, a MU event was defined as any deflection of the analog signal that exceeded this threshold. Since the absolute frequency of the MU response depends heavily upon the event threshold, we attempted to achieve a consistent response magnitude from site to site by adjusting our event threshold such that the spontaneous activity level was in the range from 50 to 100 events/s. This setting typically yielded peak MU responses in the range of 300–500 events/s (mean 378.5 ± 78.3 SD). Horizontal and vertical eye-position signals were low-pass filtered with a cutoff frequency of 250Hz, sampled at 1 kHz, and stored to disk at 250 Hz. Data analysis To construct disparity-tuning curves, we computed the firing rate for each trial during the 1-s stimulus presentation, and we plotted the mean firing rate (± SE) as a function of the horizontal disparity. Smooth curve fits to disparity-tuning curves were achieved using a cubic spline interpolation. To quantify the strength of disparity tuning at each stimulation site, we computed the DTI as follows: where Rmax denotes the response to the preferred disparity, Rmin denotes the response to the antipreferred disparity, and S indicates the spontaneous activity level. Values larger than unity can occur if Rmin is less than S . For the quantification of direction-tuning strength (see Figure S1 ), a Direction Tuning Index was defined in an identical fashion. We analyzed behavioral data by computing the proportion of preferred decisions that the monkey made for each different combination of motion coherence and direction, where a preferred decision is defined as that in favor of the preferred direction of MU activity at a particular microstimulation site. This proportion was plotted as a function of the signed motion-coherence variable (see Figure 2 B), where positive coherences correspond to motion in the preferred direction and negative coherences to motion in the antipreferred direction. The statistical significance of microstimulation effects was determined using a logistic regression analysis, as described by Salzman et al. (1992 ). Supporting Information Figure S1 Relationship between Strength of Direction Tuning and Strength of Disparity Tuning in MT Data are shown from 571 MU recordings (162 from monkey S, shown in red, and 409 from three additional animals, shown in black) in which we obtained quantitative measurements of both direction tuning and disparity tuning. There is no significant correlation between Direction Tuning Index and Disparity Tuning Index (DTI) across the sample. Note also that the data from monkey S overlap completely with the data from the other animals, indicating that monkey S was not unusual. (358 KB EPS). Click here for additional data file. Figure S2 Analysis of Direction Preference Variability at Microstimulation Sites in Monkey S and Monkey T Monkey S is shown in black; monkey T in red. (A) The strength of the microstimulation effect is plotted against the SD of direction preferences within a 400-μm window centered on each stimulation site (five recording sites, 100 μm apart). There is no significant correlation between these variables, indicating that variability in direction preferences (within the observed range) did not determine the efficacy of microstimulation. Note, however, that all stimulation sites were chosen to have a small range of preferred directions; we did not apply microstimulation at locations in MT where the direction preference changed rapidly over short distances. (B) There is also no significant correlation between the DTI of MU activity at each stimulation site and the SD of direction preferences. This shows that disparity-selective microstimulation sites did not have larger variations in direction preferences. (216 KB PS). Click here for additional data file. Figure S3 Comparison of Direction Preference Estimates Obtained from Post Hoc Gaussian Fits of Direction-Tuning Curves Versus Online Estimates of MT Preferred Directions See Materials and Methods . Data were obtained from 409 single units in MT of three animals that were not part of the present study. For 68% of neurons, the two direction preference estimates differ by less than 20°. By comparison, the mean directional bandwidth (full width at half-maximal height) for this population of neurons was 121° ± 54° SD; hence, the error in hand-mapped estimates of direction preference is quite small relative to the breadth of tuning. (320 KB EPS). Click here for additional data file. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368171.xml |
544830 | Homozygosity for a missense mutation in the 67 kDa isoform of glutamate decarboxylase in a family with autosomal recessive spastic cerebral palsy: parallels with Stiff-Person Syndrome and other movement disorders | Background Cerebral palsy (CP) is an heterogeneous group of neurological disorders of movement and/or posture, with an estimated incidence of 1 in 1000 live births. Non-progressive forms of symmetrical, spastic CP have been identified, which show a Mendelian autosomal recessive pattern of inheritance. We recently described the mapping of a recessive spastic CP locus to a 5 cM chromosomal region located at 2q24-31.1, in rare consanguineous families. Methods Here we present data that refine this locus to a 0.5 cM region, flanked by the microsatellite markers D2S2345 and D2S326. The minimal region contains the candidate gene GAD1 , which encodes a glutamate decarboxylase isoform (GAD 67 ), involved in conversion of the amino acid and excitatory neurotransmitter glutamate to the inhibitory neurotransmitter γ-aminobutyric acid (GABA). Results A novel amino acid mis-sense mutation in GAD 67 was detected, which segregated with CP in affected individuals. Conclusions This result is interesting because auto-antibodies to GAD 67 and the more widely studied GAD 65 homologue encoded by the GAD2 gene, are described in patients with Stiff-Person Syndrome (SPS), epilepsy, cerebellar ataxia and Batten disease. Further investigation seems merited of the possibility that variation in the GAD1 sequence, potentially affecting glutamate/GABA ratios, may underlie this form of spastic CP, given the presence of anti-GAD antibodies in SPS and the recognised excitotoxicity of glutamate in various contexts. Table 4 GAD1 single nucleotide substitutions detected on mutation analysis and occurring in sequences submitted to NCBI SNP database and in the literature. This is not a definitive list, but includes those described at the time of the mutational analysis. * Nucleotide positions were not provided by Maestrini et al . [47]. Source SNP position in mRNA, from the translational start site (bp) Gene position of SNP(bp) Amino acid change (A)Lappalainen et al . (2002) A(-478)Del Exon 0 (73) No substitution (B)Lappalainen et al . (2002) G(-147)A Exon 0 (404) No substitution (C)Lappalainen et al . (2002) A(-39)C Exon 1 (25) No substitution (D)Spastic CP patients family B G(36)C Exon 1 (97) Ser(12)Cys (E)NCBI collated resource G(48)C Exon 1 (104) Pro(17)Ala (F)Control samples & family A NCBI collated resource T(110)C Exon 2 (29) No substitution (G)Kure et al . (1998) T(315)C Exon 4 (14) No substitution (H)Bu and Tobin (1994) Kure et al . (1998) A(407)G Exon 4 (105) No substitution (I)Maestrini et al . (2002)* G/C Intron 4 No substitution (J)NCBI collated resource C(696)T Exon 6 (56) No substitution (K)Lappalainen et al . (2002) T/Del Intron 7 (35) No substitution (L)In control samples Lappalainen et al . (2002) T/C Intron 8 (185) No substitution (M)Maestrini et al . (2002)* C/T Intron 9 No substitution | Background Cerebral palsy (CP) is a term used to define a group of disorders [ 1 ] characterized by a non-progressive abnormality of posture and movement, resulting from defects in the developing nervous system [ 2 ]. Approximately 1 in 250 to 1000 live births presents with CP, making it one the commonest congenital disabilities [ 3 ]. Many different aetiological factors have been implicated. Among preterm infants, the incidence of CP generally increases with decreasing gestational age and the origin in most cases may be traced to post/peri-partum periventricular leukomalacia and intraventricular/periventricular haemorrhage [ 4 ]. Conversely in term infants perinatal causes can only confidently be attributed where there is documented perinatal hypoxia/acidosis and clinical encephalopathy in the early neonatal period [ 5 ]. Prenatal risk factors in the aetiology of CP include low birth-weight, intrauterine infection and exposure to teratogens during pregnancy [ 6 , 7 ]. The cause in a large proportion of cases remains obscure. Depending on the overall clinical picture, CP can be sub-classified into a number of phenotypic groups [ 8 , 9 ]. Dyskinetic CP accounts for ~20% of all cases, which may be further divided into choreoathetotic (5%) and dystonic (15%) forms. Ataxic CP (~10% of all cases) can also be sub-divided into two forms, simple (congenital) ataxia (5%) and ataxic diplegia (5%). Spastic CP is the most prevalent sub-type (~70%) and was the phenotype of the probands in this study [ 10 ]. It is characterised by muscular hypertonicity and pronounced rigidity of the affected limbs. Spastic CP can be sub-classified according to the topography of the affected limbs as hemiplegic (20%), monoplegic (<1%), diplegic (40%), or quadriplegic (10%) [ 11 ]. Kuban and Leviton [ 3 ] suggested that CP could be genetic in origin, as well as the result of environmental insult at any point during CNS development. Most estimates place the proportion of CP cases with a genetic aetiology at between one and two percent of the total [ 12 ]. Among infants and children with spasticity, symmetry of neurological signs has been identified as a strong indicator of a probable genetic aetiology [ 13 , 14 ]. The proportion of cases demonstrating Mendelian inheritance varies among the different sub-types of CP [ 2 , 13 , 7 ]. X-linked, autosomal dominant and recessive inheritance patterns have been described for non-progressive CP. An ataxic diplegic autosomal recessive trait (OMIM:605388) [ 15 ] has been mapped to chromosome 9p12-q12. Progressive spastic paraplegia (SPG) has a similar pathology to CP. SPG displays autosomal dominant (SPG3A at 14q11-q21 encoding the atlastin GTPase; SPG4 at 2p21-22 encoding spastin, an AAA family ATPase/chaperonin; SPG6 at 15q11.1; SPG8 at 8q23-q24; SPG9 at 10q23-q24; SPG10 at 12q13; SPG12 at 19q13; and SPG13 at 2q24 encoding the HSP60 mitochondrial chaperonin), recessive (SPG5A at 8cen; SPG7 at 16q24.3 encoding paraplegin, an AAA family ATPase/inner mitochondrial membrane chaperonin; SPG11 at 15q13-q15; SPG14 at 3q27-q28; SPG15 at 14q22-q24; and SPG17 at 11q12-q14), or X-linked inheritance patterns (SPG1 at Xq28 encoding the L1CAM adhesion molecule; SPG2 at Xq22 encoding proteolipid protein-1; and SPG16 at Xq11.2). A non-progressive, autosomal recessive, symmetrical spastic CP locus has been mapped to a 5 cM region between D2S124 and D2S333, at 2q24-31.1 (LOD score of 5.75) in consanguineous families originating from the Mirpur region of Pakistan (OMIM:603513) [ 10 ]. Affected individuals had no identifiable perinatal cause of CP, or underlying diagnosis and presented with developmental delay, mental retardation and sometimes epilepsy as part of the phenotype. We initially performed detailed physical mapping of the 5 cM region, so as to accurately define the marker order and to refine the linkage interval. The positions of a large number of genes and ESTs were defined accordingly, allowing the rapid identification of candidate disease genes. The minimum region of homozygosity was reduced to 0.5 cM by typing large numbers of microsatellite markers in the families. Subsequently, portions of this region have been sequenced in the human genome project. Within the region we have concentrated on the positional candidate GAD1 , which codes for the 67 kDa isoform of L-glutamate decarboxylase (GAD EC:4.1.1.15). GAD requires the cofactor pyridoxal 5'-phosphate (PLP) and catalyses the production of Gamma-aminobutyric acid (GABA) from glutamate [ 16 ]. Two separate, independently-regulated genes, GAD1 and GAD2 (at chromosome 10p11, encoding a 65 kDa GAD isoform), have presumably arisen by duplication and been conserved during evolution, as indicated by their sequence homology [ 17 ] and the retention of common intron-exon boundary splice sites [ 18 ]. Their N- termini demonstrate ~23% homology, but their C- termini, which contain the catalytic site, have ~73% amino acid sequence identity between the isoforms [ 19 ]. GABA and glutamate are the most abundant amino acid neurotransmitters in the brain. GABA, an inhibitory neurotransmitter, and excitatory glutamate, both play important roles in synaptic plasticity and neuroendocrine function [ 20 ]. Both isoforms of GAD are also involved in intermediary metabolism, participating in the GABA shunt, which bypasses two steps of the TCA cycle [ 21 ]. GAD activity of both isoforms, is ubiquitous, but highest in the brain and pancreatic islets of Langerhans. We therefore performed detailed mutational screening of GAD1 in familial spastic CP probands and unaffected family members. Methods Features and pedigrees of ascertained families Family A (4718/4719) The oldest affected male diagnosed with non-progressive, spastic CP, demonstrated global developmental delay, with no associated neurological abnormalities and moderate mental retardation. His affected younger sister was also diagnosed with spastic CP, global developmental delay and moderate mental retardation. Family B (4578/4579/4581/4679) The oldest non-progressive, spastic CP female has severe mental retardation, and is confined to a wheelchair. The next oldest spastic CP male has severe mental retardation, mild hypertonia and ataxia of the upper limbs. The next oldest spastic CP male is a dizygotic twin born by Caesarean section. This patient on presentation demonstrated developmental delay, mild hypertonia and ataxia of the upper limbs. The youngest affected female is not able to walk or stand unaided and has severe developmental delay. Details of the clinical picture in these pedigrees have been described previously [ 10 , 14 ]. Physical mapping of candidate region ICI and CEPH YAC libraries were screened by PCR amplification of STSs that were mapped between D2S2157 and D2S385. The positive clones (CEPH human mega YAC clones: 761-G10, 797-G4, 842-G1, 842-G3, 910-G12, 945-C12; ICI human YAC clones: 13I-E10, 13I-G11, 14I-G12, 16F-H2, 1E-F6, 21E-G5, 30A-D10, 30H-D2, 33D-C4, 35B-D2, 18B-E3, 31H-A4, 40D-E8, 8D-E12, 9H-F10) were obtained from the UK HGMP Resource Centre . Clones were grown up in casamino acid selective broth overnight and harvested by centrifugation. The pellet was then washed twice in 0.5 ml 100 mM Tris-HCl, pH7.5, 0.5 M EDTA buffer. After a second round of centrifugation the pellet was resuspended in molten 1% LMP agarose in 5 mM Tris-HCl, pH7.5, 0.05 M EDTA, 10 mM NaCl with 100 μg of Zymolase. The agarose was cooled and the resultant plugs were incubated overnight at 37°C in 50 ml of 0.5 M EDTA, 10 mM Tris-HCl, pH7.5, 10 mM NaCl. The buffer was replaced with fresh solution to which 100 μl of 40% Sarkosyl NL30 and 50 μl Proteinase K (1 mg/ml) was added and the plugs were incubated overnight at 50°C. The YAC chromosomal DNA was purified and separated for sizing by CHEF electrophoresis. The switching angle was 120°, using a CHEF™ electrophoresis tank (Bio Rad), run for 16 hours at 6 V/cm, 10°C with an initial pulse time of 30 sec to a final pulse time of 90 sec. DNA was stained with (20 mg/ml) ethidium bromide solution (BDH) for 2 hours and visualized under ultra-violet illumination. Southern blotting and membrane hybridisation of CHEF gels were performed on Hybond-N™ membranes (Amersham). DNA was immobilised by heating the membrane to 80°C in vacuum for 1 hour in a gel dryer (Bio-Rad). Radio-labelled YAC vector-specific probes were generated using the Megaprime random primer kit (Amersham) as described in the manufacturer's instructions, using PCR products as a template. Sizes were estimated based on comparisons with the known sizes of the native yeast chromosomes. Genetic mapping The microsatellite markers: Cen-D2157, D2S124, D2S2330, CHLC.GATA71B02 (D2S1776), D2S2345, CHLC.GATA71D01, D2S294, AFMA109YC1, D2S376, D2S2284, D2S2177, D2S2194, D2S333, D2S2302, D2S2381, D2S326, AFMA304WB1, D2S138, D2S148, D2S300-Tel, were amplified using fluorescently labelled primers (Lifetech) previously designed by the Whitehead Institute or on the GDB database , , . These primers were used to amplify microsatellite marker alleles from individuals by PCR. Individual alleles were identified by denaturing polyacrylamide gel electrophoresis on an ABI Prism 377 sequencer and analysed using Genescan™ and Genotyper™ (version 1.1.1) software (Applied Biosystems). Single-strand conformational polymorphism analysis GAD1 exon sequences were amplified by PCR using the primers described in Table 1 . SSCP was performed on GeneGel Excel (Amersham), using a 12.5/24 gel (14°C, 600 V, 25 mA, 15 W for 80 min) and the DNA was visualised by silver staining as per the manufacturer's instructions. Table 1 Oligonucleotide primer used in the amplification of GAD1 exons. Primer Forward Reverse Exon 1 dGCCCCATTTATTTCCCAGCC dGCACAGCTCTCGCTTCTCTT Exon 2 dGAAAACCATTGTCCTCCACC dGCCTGTCGGCTCACAGATT Exon 3 dACCAGCTTCTTGTGCCATAG dATCTACTGGCTAGCATGGGG Exon 4 dATTCCATGTCTGAGCAGCCT dACTGTTACTGCCCAAGCTTG Exon 5 dGCCGTTTGCCTTCAAGATAG dAGAACCACTGGGACTGAACT Exon E dACCAGTATCTCCTCGCCATG dTTGGGAGGCCCCTGGAAATT Exon 6 dACCCAACTACAAATACTAAACC dAATAGGAAGTCAGGGTATCC Exon 7 dGAGACACCAGCTCAGCGTTC dCTGCAACAAACAGAGGCTCG Exon 8 dGTCGGGGATGCTTTCTCCATG dCTCAGTACATTGTGCCAAGC Exon 9 dCAAGCTGCTAATGGTCTGTT dGTCTCATATTATCAAGGACTG Exon 10 dCACAATTCTTCTTCCTGTGA dTGGGGAGGAGCTTGAGGCAA Exon 11 dACAATCAGTGTGGGCTGAAC dGAAGCAAACTTAGACCGAAA Exon 12 dCTTGAGTTGGAATGGGTGTT dACTGCAAAGAGACCCCACGT Exon 13 dTCCTTCCAAGCAGCCTAGTT dGTGATATATCTTTGCCCCTC Exon 14 dGACAGCATAGCCTTCCCAAA dCATGTTGCCAGAAGCTTCAG Exon 15 dGGTTTGGGAACAGCTTTCTC dTTCCCCCACTAGAAAGGCAC Exon 16 dGTTAAAAAGAGAGGGTGTTC dCCCTCAATGAAATGGCCTGT Sequencing of GAD1 exon sequences Primers used to amplify the exons of GAD1 were designed from the sequence of BAC RP11-570c16 and obtained from Lifetech (Table 1 ). PCR products were purified from agarose gels using QIAquick gel extraction kits (Quiagen), sequenced using ABI PRISM Big Dye Terminator Cycle Sequencing Ready Reaction Kits (Applied Biosystems) and then analysed using an ABI Prism 377 automated sequencer. Results Physical map of the spastic CP locus An integrated YAC (ICI and CEPH mega YAC libraries) and RP-9 PAC (HGMP Resource Centre) contig for the interval D2S2157 to D2S385 was constructed (Figure 1 ). This map provided physical continuity connecting 25 loci from centromere to telomere spanning the entire 2q24.3-31.1 cytogenetic band region. These data were combined with BAC contigs, constructed at Washington University , in an attempt to form an ordered BAC/YAC contig across the minimum region of interest. Selected YACs from this contig were sized (Table 2 ) enabling the physical length of the region to be estimated. The partial contig map included 3 identified CEPH mega-YAC contigs (contig 1: 945-C12; 912-B6; 744-G6; 797-G4; 761-G10; contig 2: 752-G9; 757-E1; 807-H5; 842-G1; 842-G3 and contig 3: 964-H5; 935-E10; 855-H2; 785-G8; 963-D11; 751-H3). The size of the region incorporating the three contigs was estimated to be at least 2870 kb. The sizes of the ICI YACs were estimated to encompass a minimum locus of 2940 kb. Microsatellite markers, ESTs and known genes, mapped to this region by NCBI, were then located on the physical contig by PCR and BLAST sequence homology searches of the Washington University BAC contigs. The expression profiles of unidentified EST clusters were determined and used to form EST "bins". These contained groups of ESTs, which mapped to adjacent locations and showed common expression profiles, suggesting that they might represent different exons of the same gene. This placement of known genes and ESTs onto the physical map provided an annotation of the gene content of the region, at the time was constructed before any such facility was available from the HGP, as the focus for candidate disease gene selection. Figure 1 An integrated physical YAC contig spanning the human chromosome 2 spastic CP locus. This was constructed against a framework of microsatellite and STS markers, to incorporate the region of linkage identified by genotyping data. The positions of microsatellite and STS markers are represented numerically left to right from centromere to telomere. These loci 1–25 were mapped arbitrarily equi-distant onto the contig, in the following order: Cen-(1) D2S2157; (2) D2S382; (3) WI-18792; (4) D2S124; (5) D2S111; (6) D2S2384; (7) D2S2330; (8) D2S399; (9) D2S2345; (10) D2S294; (11) D2S2188; (12) D2S2284; (13) D2S2177; (14) D2S335; (15) D2S326; (16) D2S2381; (17) D2S2302; (18) D2S2307; (19) D2S2257; (20) D2S2314; (21) D2S138; (22) D2S148; (23) D2S2173; (24) D2S300; (25) D2S385-Tel. Table 2 Approximate sizes of YAC clones spanning the 2q24-31.1 autosomal recessive spastic CP disease gene locus, used to estimate the minimum physical size of the region (kb). The CEPH MEGA and ICI YACs were sized using CHEF PFGE compared against the native yeast chromosomes. This confirmed the estimated size ranges of the YAC inserts, predicted by the Whitehead Institute (WI) database of YAC clones. CEPH human MEGA-YAC clones ICI human YAC clones Clone Size (kb) Clone Size (kb) 910-G12 1630 40D-E3 290 744-G6 1120 35B-D2 260 912-B6 1190 33D-C4 120, 480 945-C12 1540 30H-D2 250 842-G3 1330 30A-D10 260 797-G4 1000 18B-E3 120 807-H5 1680, 1290 16F-H2 220 752-G9 1740 13I-G11 230 785-G8 690, 1060 13I-E10 460 842-G1 1380 8D-E12 280 757-E1 1100 812-G1 1540 863-H12 1550 935-E10 1360 785-G8 1060 751-H3 1780 963-D11 1670, 890 Genetic mapping data From the PAC/YAC contig, 20 polymorphic microsatellite markers were identified that span the chromosome 2q24-31.1 CP critical region. These were then used, with informed consent and local research ethics committee approval, in the detailed mapping of previously linked families [ 10 ] (Figure 2 ). These data did not support the presence of a founder mutation for autosomal recessive spastic CP, in that families did not share a common haplotype across the minimal homozygous region between D2S2345 and D2S326. Figure 2 Annotation of two pedigrees of spastic autosomal recessive CP families and corresponding linkage mapping data . The markers shown are those that demonstrate the minimal homozygous region between the affected individuals of both families. Sequence analysis of GAD1 GAD1 was sequenced in affected and unaffected individuals in both families ascertained. In order to differentiate possible disease-causing mutations from polymorphisms, 100 control individuals were screened by SSCP to detect any GAD1 sequence variations in the normal population. SSCP variants were then sequenced to identify the underlying nucleotide substitutions. An homozygous G(36)C (Figure 3A,3B ) nucleotide change was observed in 4 affected patients, which generated a Ser(12)Cys amino acid substitution. No obligate carriers were identified for this mutation. This variant has not been previously described and was not present in 200 normal chromosomes. A number of other sequence changes were detected, but none of these resulted in amino acid changes. These variants and all those recorded previously in the literature are presented in Table 4 and Figure 4 . For those rare variants in the databases, which result in amino acid changes, no homozygous or compound heterozygous individuals have yet been described. Figure 3 Electropherograms of the sequence of the exon 1 SNP of GAD1 identified in the process of mutational analysis . (A) and (B) show the normal C variant in the forward and reverse directions, respectively. (C) and (D) show the alternative G variant in the forward and reverse directions, respectively. This variant was only found in affected individuals of family B. No heterozygous individuals were identified for this nucleotide variant. Table 3 Autozygosity mapping data generated by genotyping eight members of the two autosomal recessive spastic CP families. Subjects 4718, 4719, 4720 and 4722 represent family A; subjects 4578, 4579, 4581 and 4679 represent family B as demonstrated in Figure 2. This Table is organised according to the definitive marker order determined from current databases and the physical contig mapping undertaken. The minimum homozygous region is highlighted. * Denotes an unaffected family member . Marker Base position 4718 4719 4722* 4720* 4578 4579 4581 4679 D2S2157 AFMA119YH5 166029867 145 145 145/147 145 145/147 145/147 145/147 145/147 D2S124 AFM094ZC9 166347755 160 160 160 160 160/163 160/163 160/163 160/163 D2S2330 AFMC015YD9 166900134 156 156 156/158 156/158 160/168 160/168 160/168 160/168 CHLC.GATA71B02 167624503 240/256 240/256 240/256 240/256 240/256 240/256 240/256 240/256 D2S2345 AFM080XG9 168922932 156 156 150/156 150/156 152 152 152 152 CHLC.GATA71D01 169848018 193 193 193 193 193 193 193 193 D2S294 AFM205XF12 170579380 186 186 186 186 208 208 208 208 AFMA109YC1 171576976 256 256 254/256 256 254 254 254 254 D2S376 AFM319XG1 171576985 235 235 235 235 235 235 235 235 D2S2284 AFMB314YE1 171696071 166 166 166 166 166 166 166 166 D2S2177 AFMA155TF9 171790203 118 118 118 118 128 128 128 128 D2S2194 AFMA222XB9 171884139 141 141 141 141/143 145 145 145 145 D2S333 AFM2702E9 172592103 189 189 189/191 189/191 189 189 189 189 D2S2302 AFMB342ZD9 172758604 204 204 199/204 199/204 204 204 204 204 D2S2381 AFMA082TF5 172861090 222 222 226 222/226 224 224 224 224 D2S326 AFM266VE1 173299492 92 92 92 92 92 92 92 92 AFMA304WB1 176057526 130/132 122/132 130/132 122/132 124 124 124 124 D2S138 AFM176XD4 177947395 108 108 113 108/113 111/117 111 111 111 D2S148 AFM200WA11 178434054 184/188 184/188 184/194 184/194 188/190 186 186 186 D2S300 AFM214XC3 178826338 87/89 87/89 87/89 87/89 87/89 89 89 89 Figure 4 An annotation of the distribution of single nucleotide substitutions identified in the open reading frame of GAD1. The approximate positions with respect to intron-exon of the open reading frame structure are illustrated. These were determined by sequencing of the probands in this study, from published data and from the NCBI collated database of SNPs. The letters refer to the SNPs listed in Table 4. Upper case letters refer to SNPs in the cDNA and lower case letters indicate SNPs in the genomic DNA. A : G(36)C, B : G(210)A, C : G(253)C, D : T(315)C, E : A(407)G, F : C(696)T, G : C(1506)T, H : C(1575)T, i : T(1625)G, J : C(1654)T, k : A(1659)G, l : G(1799)A, m : C(1899)A. Discussion CP is a term used as a collective definition for a group of neurological disorders [ 3 ]. The pathophysiology in most cases is poorly understood, but includes genetic syndromes, congenital malformation, infective intra-uterine encephalitis, cerebral haemorrhage or infarction, ischemic damage, periventricular leukomalacia (PVL), and non-infarctive telencephalic leukomalacia [ 11 ]. The contribution of Mendelian inherited cases of CP accounts for approximately 2% of the total number [ 2 , 22 ]. A non-progressive form of autosomal recessive spastic CP has been identified [ 13 ]. McHale et al . [ 10 ] succeeded in identifying a 5 cM region on chromosome 2q24-31.1, which segregated with disease in consanguineous families. Linkage analysis identified a locus between markers D2S124 and D2S333, which produced a LOD score of 5.75, sufficient to warrant the further investigation described herein. To refine and confirm the genetic marker order across a region, which was incompletely sequenced at the time, we used YAC and PAC clones to construct a physical framework and performed PCR to map ESTs and microsatellite markers to clones within the partial contig (Figure 1 ). When this contig was integrated with the BAC sequence contigs, rearrangement of the BAC order was necessary. With each subsequent DNA sequence update, the degree of inconsistency was reduced and this led to revision of microsatellite order compared with that used previously [ 10 ]. Using the YAC sizes, the sizes of gaps in the BAC contig could be estimated. Having generated a detailed map spanning the region, we selected microsatellite markers at evenly spaced intervals across the locus. These markers were used to refine the minimum region homozygous by descent in linked families, to between the markers D2S2345 and D2S326. The physical size of the region between these markers is approximately 0.5 cM. There was no suggestion of a founder haplotype common to the two families (Figure 2 ). The Goldenpath Human Genome Working Draft Assembly 2001, is an annotation of the Washington BAC contig, combining sequence data of BACs, ESTs, known genes and hypothetical genes. We mapped ESTs and known, uncharacterised or hypothetical genes on the basis of sequence homology (NCBI , Whitehead and Goldenpath databases), onto our YAC/PAC contig. ESTs were then collated according to their expression profiles to produce a "binned" EST map, on which candidate gene selection could be based. This reduced the number of hypothetical genes in the region and allowed the combination of genetic, physical mapping and expression data, into a single comprehensive map. One interesting candidate within the minimal region was GAD1 , which encodes GAD 67 . Expression of its transcript is ubiquitous, including the CNS. The main function of GAD 67 is to catalyze the conversion of the excitatory amino acid and neurotransmitter glutamate to GABA, the main inhibitory neurotransmitter in the CNS [ 23 ]. In the developing CNS, GABA has an important role in neuronal differentiation and the control of plasticity [ 21 ]. GABA has also been implicated in the pathogenesis of various seizure and movement disorders [ 20 ]. Vertebrates have two separate genes coding for GAD, which produce distinct forms of the enzyme. GAD1 and GAD2 have diverged relatively recently in evolution, as indicated by their degree of sequence homology and the retention of common intron-exon boundary splice sites [ 17 ] (Figure 5A ). The variants of GAD differ in molecular weight, cellular and sub-cellular localisation, and their interaction with the cofactor PLP [ 18 , 20 , 24 ]. Figure 5 Three illustrations of the genomic, protein and comparative sequence homologies of the different species of GAD. (A) The genomic structures of GAD1 / GAD 25 / GAD2 and Drosophila Gad1 . (B) Comparative protein domain structures of GAD 65 /GAD 25 /GAD 67 and Drosophila Gad1. (Numbers represent approximate amino acid residues). (C) Schematic illustrating the relative homology of the protein structures of GAD 67 /GAD 65 and Drosophila Gad1. GAD2 , located at 10p13-p11.2, is transcribed to produce a 5.6 kb mRNA in islets and brain, encoding a 65 kDa protein (585 AA residues). The 67 kDa (594 AA residues) form [ 17 ] is localised to 2q25-26 and encoded by a 3.7 kb transcript ( GAD1 ) [ 23 ]. There is also evidence for a 25 kDa inactive protein (GAD 25 ) produced from an alternatively spliced GAD1 transcript of 2 kb that contains an in-frame stop codon. This GAD1 splice variant has only been found in human islets, testis and adrenal cortex, although the homologue is present in fetal mouse brain [ 25 ]. GAD 67 and GAD 65 consist of two major sequence domains (Figure 5B ). The N -termini (AA residues 1–94 in GAD 65 and 1–101 in GAD 67 ) demonstrate ~23% homology. These N -terminal domains are thought to be responsible for sub-cellular targeting and the formation of GAD 65 –GAD 67 heterodimers [ 26 ]. The C -terminal domains (AA residues 96–585 in GAD 65 and 102–594 in GAD 67 ) contain the catalytic site, with ~73% sequence identity between the isoforms [ 19 ] (Figure 5 ). In the CNS, GAD 65 appears to be preferentially distributed in axon terminals and the associated synaptic vesicles, whereas GAD 67 is also located in the cell bodies and more uniformly distributed throughout the neuron [ 24 ]. This suggests that each GAD isoform is involved in the synthesis of GABA in different sub-cellular compartments [ 21 ]. This is supported by the discovery that GAD 65 is the main source of apoGAD (an inactive reservoir), which responds to short-term changes in neuronal activity and is more responsive to levels of PLP [ 18 ]. On the other hand, GAD 67 predominantly exists bound to the PLP cofactor (holoGAD), providing a constitutive level of GABA production [ 20 ]. Bond et al . [ 27 ] showed that GAD 25 is expressed in a temporally controlled manner, in the developing striatum and cortex in rodents, suggesting this may provide a mechanism of regulating GABA production in differentiating neurons. Asada et al . [ 28 ] undertook the selective elimination of each GAD isoform in order to determine their respective roles. Gad2 -/- mice are slightly more susceptible to seizures, consistent with an excitatory increase in the relative ratio of glutamate/GABA. However, they showed no obvious overall change in neuronal GABA content. Therefore GAD 67 alone appears to produce sufficient GABA for effective neurotransmission [ 21 ]. Gad1-/- mice demonstrated a decrease of ~20% in total glutamate decarboxylase activity at birth. This was assayed by the conversion of 14 C-labelled glutamate to 14 CO 2 in the presence of PLP. There was also a marked (7%) reduction in total GABA content in cerebral cortex homogenate measured by liquid chromatography [ 28 ]. Unfortunately, these mice died neonatally of severe cleft palate, masking any potential neurological dysfunction and also illustrating a role for Gad 67 in non-neural tissues [ 21 ]. It is of interest that mice with mutations in the β-3 GABA receptor (GABRB3) at the Angelman syndrome (OMIM:105830) locus, also display cleft palate, implying a key role for GABA signalling in normal palate development [ 29 , 30 ]. Pyridoxine-dependent epilepsy (PDE) is a rare autosomal recessive disorder (OMIM:266100), characterized by generalized seizures during the first hours of life. The associated pathology may result from an alteration in the binding of the co-factor PLP to GAD. Interestingly epilepsy is commonly associated with CP and grand mal epilepsy developed at age six months in the two linked pedigrees described here [ 10 ]. GAD1 mutation was previously suspected of being the cause of PDE. Linkage of pyridoxine-dependent epilepsy has however been reported to 5q31.2-31.3, with GAD1 and GAD2 excluded [ 31 ]. Decreased levels of brain and CSF GABA, increased levels of CSF and cortical glutamate, and decreased levels of PLP in the frontal cortex, have been described in this condition. GAD 65 and GAD 67 have been identified as auto-antigens in "Stiff Person Syndrome" (SPS, OMIM:184850), and in cerebellar ataxia [ 32 - 34 ]. GABA-mediated synaptic transmission is thought to be functionally impaired by the production of autoantibodies to GAD 65 and GAD 67 [ 35 - 37 ]. This results in a reduction in brain levels of GABA, prominent in the motor cortex, which can be demonstrated by Magnetic Resonance Imaging (MRI) in SPS patients. SPS is a disabling disorder characterised by muscle rigidity and episodic spasms of the musculature, thought to be due to autoimmune-mediated dysfunction of supraspinal GABAergic inhibitory neurons [ 38 ]. Hyperexcitability of the motor cortex in SPS has been demonstrated by transcranial magnetic stimulation [ 39 ]. Anti-GAD 65 auto-antibodies in the CSF of ataxic and SPS patients selectively suppress GABA-mediated transmission in cerebellar Purkinje cells, without affecting glutamate-mediated transmission [ 37 , 40 ]. Low CSF levels of GABA have been reported in patients with Kok disease (OMIM:149400 also known as hyperexplexia/exaggerated startle reaction/startle disease) [ 41 ]. The exact mechanism by which autoantibodies target these intracellular GAD antigens is not clear. However, it is interesting that SPS may also arise in individuals with autoantibodies to gephyrin, a cytosolic protein concentrated at the postsynaptic membrane of inhibitory synapses where it is associated with GABA A receptors [ 42 ]. This provides a further example of chronic rigidity and spasm possibly secondary to disruption of the inhibitory synapses. Mutations in the CLN3 gene are thought to be responsible for the neurodegenerative disorder Batten disease (OMIM:204200). In cln3 -knockout mice autoantibodies to GAD 65 have been reported to be associated with brain tissue and result in inhibition of GAD activity [ 43 ]. These mice also demonstrate elevated brain glutamate levels as compared with controls, which may have a causative role in the astrocytic hypertrophy evident in cln3 -knockout mice and along with anti-GAD 65 autoantibodies in Batten disease patients may contribute to the associated preferential loss of GABAergic neurons. Drugs, which potentiate the action of GABA, such as benzodiazepines and baclofen, ameliorate muscle rigidity and spasticity. These GABA agonists are thought to counter disinhibition of the velocity-dependent increase in skeletal muscle during stretch reflexes, observed in spasticity, which is the result of inadequate presynaptic inhibition of the muscle spindles [ 44 , 35 , 37 ]. γ-Vinyl-γ-aminobutyric acid (GVG) is used to treat neurological disorders including epilepsy, tardive dyskinesia and spasticity. It has been reported that it is the GABA-elevating effect of this compound that is responsible for its anti-convulsive properties [ 20 ]. We have identified a GAD1 sequence change G(36)C, which segregates with autosomal recessive spastic CP in 4 affected siblings. This nucleotide substitution causes a missense mutation, changing serine (12) to a cysteine in the N -terminal domain. This serine residue is conserved between all mammals (human/mouse/rabbit/pig) for which data are available. The association of GAD 67 with membranes requires formation of heteromeric links with GAD 65 , which are mediated via their N -terminal domains. The N -terminus of GAD 65 is palmitoylated and binds to the cellular membrane. The first 27 amino acids appear to be essential in this function [ 32 ]. The palmitoylation of cysteines 30 and 45 of GAD 65 , and the inability of residues 1–29 of GAD 67 , to substitute for this region, highlights the potential impact on cellular localisation of a nucleotide substitution in this domain [ 20 ]. GAD 65 also undergoes phosphorylation of the first four serine residues in the N -terminal domain. These post-translational modifications highlight the importance of the flexibility and accessibility of this domain. N -terminal epitopes of GAD 65 , in the region corresponding to the residue, which undergoes mutation in GAD 67 , are particularly prominent autoantigens [ 45 ]. S(12)C amino acid substitution may thus produce subtle effects on cellular localisation, protein-protein interactions and/or protein processing, with a subsequent effect on GABA production. This is not inconsistent with the mouse Gad1 knockout where complete loss of Gad1 enzymatic function (~20% reduction of total Gad activity in the cerebral cortex) resulted in a cleft palate phenotype and neonatal death [ 28 , 30 ]. There is redundancy of GABA production as a result of the presence of two GAD proteins, and the precise function of each isoform may differ between man and mouse. It is interesting to note that the GAD 25 splice variant of GAD 67 , also contains the S(12)C amino acid substitution in affected CP patients. This truncated variant is identical to the first 213 amino acids of GAD 67 , with the addition of an extra 11 C -terminal residues. It lacks the binding site for the cofactor PLP and is believed to lack any GAD activity [ 25 ]. The function of GAD 25 is not known, but it may compete with GAD 67 for incorporation into protein complexes. Therefore the presence of an N -terminal mutation would affect both GAD 25 and GAD 67 , and may disrupt a complex regulatory mechanism for GAD 67 . Conclusions This study illustrates the difficulty of gene cloning in rare autosomal recessive diseases mapped in small, consanguineous pedigrees. Identification of an ancestral haplotype allows refinement of the locus, but this has not been possible in this example. Within the minimal linkage region, any sequence change will segregate with the disease phenotype. Detection of a nonsense mutation leading to a protein truncation would provide compelling support for a mutation as causative. However, in the present example we have not seen such a mutation in the candidate gene so far examined. We are now expressing the variant forms of GAD 67 (S12C) and GAD 25 (S12C), as recombinant proteins, to assess catalytic activity and binding properties with respect to their normal counterparts. However, it may well prove difficult to detect subtle effects based on sub-cellular localisation changes in the mutant proteins, or changes in post-translational modification patterns. Stability of the mRNA transcripts from these variants will be assessed by transfection studies in neuronal cells. Eventually, it would be of interest to attempt knock-in experiments with GAD1 (G36C), into the Gad1-/- mouse to see if this can rescue the cleft palate phenotype and reveal a CP-like picture. These experiments will be reported elsewhere. However, the possibility that reduced GAD 67 activity may cause CP in the patients studied herein, in a manner reminiscent of that seen in SPS, leads us to report our findings at this stage. The success reported in treating SPS with intravenous immunoglobulin [ 40 , 46 ], suggests further evaluation of GABA agonists in the management of this difficult clinical problem. Abbreviations BAC Bacterial artificial chromosome BLAST Basic local alignment search tool CEPH Centre d'Etude du Polymorphisme Humain CHEF Contour-clamped homogenous electric field CNS Central nervous system CP Cerebral Palsy CSF Cerebrospinal fluid DNA Deoxyribonucleic acid EST Expressed sequence tag GABA Gamma-aminobutyric acid GAD L-Glutamate decarboxylase GVG Gamma-vinyl-gamma aminobutyric acid HGMP Human genome mapping project IDDM Type 1 Insulin-Dependent Diabetes Mellitus MRI Magnetic resonance imaging NCBI National Centre for Biotechnology Information PAC Plasmid artificial chromosome PCR Polymerase chain reaction PDE Pyridoxine-dependent epilepsy PFGE Pulse field gel electrophoresis PLP Pyridoxal 5'-phosphate PVL Periventricular leukomalacia SPG Spastic paraplegia SPS Stiff Person Syndrome SSCP Single-strand conformational polymorphism STS Sequence tagged site YAC Yeast artificial chromosome Competing interests The author(s) declare that they have no competing interests. Authors' contributions CNL carried out the molecular genetic studies, sequencing and drafted the manuscript. The YAC mapping work was undertaken by JPL and CNL. AFM, DTB and IMC conceived the study and participated in the design and coordination, they also secured financial sponsorship from the Wellcome Trust and MRC. RA, SM, ERM and CGW recruited and gained consent from the families detailed in this study. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544830.xml |
423129 | Topology and Robustness in the Drosophila Segment Polarity Network | A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network) was robust ( von Dassow et al. 2000 ). As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability) corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network. | Introduction The network responsible for segment polarity in the Drosophila melanogaster embryo has been extensively studied. The segment polarity pattern emerges from a sequence of developmental events that each refine the pattern produced by the previous event. During the early cell cycles of the embryo, cell division is suppressed and maternal morphogens induce a transcriptional cascade of genes (the gap and pair-rule genes). These in turn create a prepattern of local expression of the segment polarity genes, genes that encode a collection of signaling molecules and transcription factors whose expression specifies the location and polarity of parasegment boundaries in the embryo. After cellularization, interactions amongst the segment polarity genes maintain narrow boundaries between parasegments as the embryo grows through cell division ( Figure 1 A shows how the structure of the parasegment is related to that of the morphologically defined segment). Diffusible signals from the boundaries also influence cell fates across the parasegment. Figure 1 The Segment Polarity Pattern and the Behavior of Different Cells (A) Parasegments in the segment polarity pattern. The prepattern, with stripes of wg and en expression, and the final segment polarity pattern are shown. The parasegment is the basic developmental unit in the segment polarity pattern, but segment boundaries within the adult insect are offset from the parasegment boundary. (B) A simple set of rules sufficient to achieve segment polarity patterning. Cells expressing wg must continue to express wg, en -expressing cells must continue to express en and begin expressing hh , and cells expressing neither wg nor en cannot begin expressing either. (C) The behavior of isolated cells for parameter sets that form the segment polarity pattern. These are like the simple rules in (B), but en expression depends on a wg -expressing neighbor. Many of the qualitative interactions between the components of the segment polarity network are known, but there is little quantitative information about the abundance of the components or the parameters that govern the reactions amongst them ( DiNardo et al. 1994 ; Gilbert 1997 ; Hatini and DiNardo 2001 ; Sanson 2001 ). The existing, qualitative knowledge has been used to develop a variety of mathematical models. Some have employed Boolean idealizations ( Albert and Othmer 2003 ), while others, including von Dassow et al., have used systems of ordinary differential equations to simulate concentrations of proteins and mRNAs ( von Dassow et al. 2000 ; von Dassow and Odell 2002 ). The model requires 50 quantitative parameters such as rate constants and affinities. The equations and parameters, together with the initial conditions, specify how the protein and mRNA concentrations change over time. Von Dassow et al. tested pattern formation by picking thousands of randomly chosen parameter sets and following the evolution of the pattern from a fixed set of initial conditions. Given the large number of variables, they found that a remarkable fraction (0.5%) of parameter sets converted the prepattern into the correct, stable segment polarity pattern and concluded that the network was surprisingly robust. I asked what general features of the model yield this robustness. As defined by von Dassow et al., the task of forming the segment polarity pattern is simple. Embryos in the model begin with a prepattern composed of a repeating unit of three stripes that encompasses four rows of cells. The first stripe expresses wingless (wg), the second stripe expresses engrained (en), and the third stripe, which is two cells wide, expresses neither. The prepattern is produced by the transient expression of gap and pair-rule genes, but maintaining and elaborating this pattern depends on the activity of wg and en and of genes that interact with them ( Hatini and DiNardo 2001 ; Sanson 2001 ). For example, the en -expressing stripe must start to express hedgehog (hh), as shown in Figure 1 A There is no initial hh expression, but the target pattern as defined by von Dassow et al. requires it to be expressed in the en stripe. Because EN protein induces hh expression, simply maintaining the initial pattern of wg and en expression suffices to produce the desired final pattern ( Figure 1 B) ( Tabata et al. 1992 ). Thus, stable maintenance of wg and en expression levels within each individual cell will produce the segment polarity pattern. Systems in which genes induce their own expression can display multiple stable expression states, a phenomenon known as bistability, though they only do so under certain conditions ( Novick and Weiner 1957 ; Glass and Kauffman 1973 ; Keller 1994 ; Hasty et al. 2000 ; Thomas and Kaufman 2001 ). To produce mathematical models that succeeded in converting the prepattern into the final pattern, von Dassow et al. added two interactions to their initial model of the segment polarity network. As they later noted, these created two positive feedback loops, one including en and the other including wg ( Figure 2 A) ( von Dassow and Odell 2002 ). I asked whether parameter sets that can generate the segment polarity pattern are the ones that produce bistability. Figure 2 The Regulatory Networks in the Segment Polarity Models (A) The regulatory network used in the von Dassow et al. (2000) model. Dashed lines indicate interactions added by the original authors in order to achieve proper patterning, while solid lines indicate interactions based on experimental observations. The positive feedback system including wg is in blue, while the one involving en is green and red. The en feedback involves mutual inhibition of en and ci, so one side of the mutual inhibition scheme is drawn in green while the other is drawn in red. When the green species are active, they will repress the red ones, and vice versa. Adapted from von Dassow et al. (2000) . (B) The regulatory network of the model developed here. The positive feedback systems are colored as in (A). The en feedback involves mutual inhibition of slp, however, and ci does not play a role in the en feedback system. To address this question, I asked two questions: could modeling the behavior of individual cells reproduce the overall behavior observed by von Dassow et al., and could I produce simple rules that predicted how the individual cells would behave. When I simulated the behavior of individual cells using the von Dassow et al. model, I found that individual cells in their model can adopt three different stable states of wg and en expression. The overall pattern, and its robustness, can be simply explained as a consequence of single cells maintaining one of these expression stable states, which correspond to the three stripes of gene expression. I also devised tests that determine whether a given parameter set allows positive feedback to stably produce the desired pattern of gene expression in these cells. These allowed us to show that parameter sets that do not produce bistability almost never yield the correct pattern, whereas those that do are much more likely to produce the right segment polarity pattern. I also investigated the role of the prepattern and found that more biologically reasonable initial conditions can dramatically reduce the fraction of parameter sets that obey the bistability rules but fail to form the segment polarity pattern. Finally, I noted that the interactions of these loops do not maintain the observed segment polarity pattern after cell proliferation ( Figure 3 A). I modified the von Dassow scheme to incorporate recent experimental evidence and produced a model that both forms the segment polarity pattern and maintains it during cell proliferation with many random parameter sets. Figure 3 The Segment Polarity Pattern After Cell Proliferation (A) Parasegments in the segment polarity pattern during cell proliferation. During cell proliferation, each cell duplicates into two cells that initially have identical gene expression. This yields wide stripes of wg and en expression at parasegment boundaries immediately after cell proliferation. Subsequently, differences in intercellular signaling cause the stripes of wg and en narrow. (B) A simple set of rules sufficient to maintain narrow boundaries after cell proliferation. These are like the simple rules in Figure 1 C, but wg expression also depends on a hh -expressing neighbor. Results I began by asking if the von Dassow et al. model could be decomposed into the properties of individual cells. The simplest hypothesis is that parameters that allow individual cells to maintain their initial state of wg and en expression will maintain the overall pattern. At the level of the cell, the parameters must allow all three types of cells to evolve from the initial conditions to the final state, and the final state must be stable. The isolated cell rules are: (1) cells that initially express wg must continue to do so, (2) cells that initially express en must continue to do so, and (3) cells that express neither wg nor en must not turn on either gene. I began by studying the properties of wg -expressing cells, as WG protein is modeled as controlling en expression, but not vice versa (data not shown). I used the equations of von Dassow et al. to model the dynamic behavior of an individual cell, starting from the standard prepattern ( von Dassow et al. 2000 ). I tested the isolated cell rules by simulating an individual cell in the context of signals that it would receive from its neighbors in the actual segment polarity pattern, computed assuming constant expression levels of segment polarity genes in those cells. Each parameter set that produces the overall pattern gives two behaviors that depend on the initial state of the cell; cells that are initially wg -expressing remain so, whereas cells that lack wg expression never acquire it. Thus, the wg -expressing stripe could retain wg expression while other cells in the field would not begin expressing wg . The precise expression levels in these two states were generally unaffected by the signals from their neighbors; in particular, HH signaling generally had no effect on wg expression in nearby cells (data not shown). In the segment polarity pattern, cells on the posterior side of the wg stripe maintain en expression while cells on the anterior side of the stripe do not begin expressing en despite experiencing the same level of WG signaling as their neighbors on the other side of the stripe (see Figure 1 A). This asymmetry requires bistability in en expression, at least in the context of a neighboring stripe of wg expression. I found that such bistability existed in working parameter sets, as long as extracellular WG exceeded a threshold concentration. Above this threshold, cells expressing en continue to do so, but cells that lack en expression do not start to express en . This threshold was always less than the amount of extracellular WG signal received from a neighboring stripe of high wg expression, which presents two wg -expressing cells. In a very small fraction of parameter sets, additional WG signal above the threshold could switch cells from not expressing to expressing en . However, when this switch was present in working models, it required WG signal from at least three wg -expressing neighbors. Such a switch is not seen in life, however, nor is it seen in most working parameter sets. Behaviors of isolated cells are summarized in Figure 1 C. To determine how well the isolated cell rules captured the requirements for patterning, I generated random parameter sets and tested them against the single-cell behavior rules, as well as determining whether they formed the segment polarity pattern, to see how well these correlated. Around half of randomly generated parameter sets that conform to the rules actually achieve the desired segment polarity pattern ( Table 1 ), and parameter sets that do not satisfy these rules cannot generate the desired final pattern (with a single exception in 10,000 trials). Since the rules require cells to reach the states they exhibit in the final segment polarity pattern, it is not surprising that they are necessary. However, the strong agreement between predictions based on individual cell behavior and the observed performance of the whole system argues that the model functions because individual cells adopt one of three stable expression states to form the segment polarity pattern rather than because of the complex, collective behaviors of groups of cells. Table 1 Pattern Formation and Predictive Rules in the von Dassow et al. Model Random parameter sets were generated and tested for segment polarity patterning using the stripe threshold scoring scheme as described in von Dassow et al. (2000) . Isolated cell rules: Isolated cell behavior was tested for 10,000 parameter sets. The dynamics of expression in a single cell was simulated using different prepatterns found in the segment polarity network. First, low or high initial wg expression was used to test the stability of a wg -expressing state and a wg -repressed state. Second, the level of extracellular WG signal to a cell adjacent to two wg -expressing cells was used to test the stability of an en -expressing state and an en -repressed state. A cell complying with both of these tests was accepted as obeying isolated cell rules. Bistability rules: Parameter sets were tested for agreement with four parameter rules that should predict bistability ( n = 25,000). Pattern formation was also assessed from a modified initial condition. The steady-state levels of CI, CN, PTC, ci , and ptc were computed for a particular parameter set, and these were used as initial levels for these components outside the stripe of en expression a The predictive value of one of our rules is the fraction of its predictions that are correct. The positive predictive value is the fraction of parameter sets that satisfy our rules which actually form the segment polarity pattern. Similarly, the negative predictive value is the fraction of parameter sets that do not satisfy the rules which do not form the segment polarity pattern Asking whether mathematical expressions can predict the behavior of single cells and the parasegment as a whole is a more stringent test of the idea that the bistability of positive feedback loops explains these stable expression states. Whether a positive feedback loop shows bistability depends on the quantitative values of its parameters. Thus, if I can predict which sets of parameters produce bistable expression of wg and en, I can ask whether bistability in the two feedback loops is both necessary and sufficient to maintain the segment polarity pattern. The parameter sets must meet certain conditions: positive feedback must be sufficient to maintain the high-expression state, while basal or external activation must not overwhelm the low-expression state (see Protocol S1 for details). These conditions can be expressed analytically, and I devised tests to determine whether a parameter set would yield the desired bistability in both the en and the wg positive feedback loops. For instance, the amount of WG present in a cell in the high- wg -expression steady state was compared to K WG→wg , a parameter indicating the amount of intracellular WG needed for half-maximal activation of wg expression. I selected subnetworks within a single cell that could be largely isolated from other parts of the model (for example, see Figure 4 A). I solved for approximate steady-state concentrations of components in subnetworks and compared these levels of signaling molecules to those needed to induce or repress target genes. Our derived constraints were the following. Figure 4 Inequalities Necessary for Bistability Are Satisfied by Working Parameter Sets (A) Subnetwork responsible for wg expression bistability. Levels of intercellular WG in a cell with full wg expression and in an adjacent cell can be computed from the transfer rates Endo WG , Exo WG , LMxfer WG , and Mxfer WG ; and the decay rates H EWG and H IWG , using the linearity of WG transport processes. (B and C) Intercellular WG levels in a cell expressing wg (green) and in an adjacent cell (red) were plotted against K WG→wg , the threshold level of intercellular WG protein needed for wg autoactivation. In (B), parameter sets that maintain the segment polarity pattern were used, while in (C) random parameter sets were used. (D) Levels of extracellular WG signalling to a cell adjacent to two with full wg expression were computed as described above. These were plotted against K EWG→ en , the threshold level of extracellular WG signal needed to activate en expression. (E) Steady-state levels of CN in the absence of en expression plotted against K CN┤ en , the threshold level needed to repress en expression. (1) For high wg expression, the net level of intracellular WG must be above K WG→wg , the amount needed for half-maximal activation of wg. To maintain the pattern, expression of wg must be bistable, such that cells beginning with high levels of wg expression maintain this “on” state while those with low levels of wg expression remain “off.” Expression of wg is regulated principally by intracellular WG protein. To achieve bistability, the level of WG protein in a cell with high wg expression must be sufficient to activate wg expression. After being produced, WG protein is lost from the intracellular compartment by transport and decay processes ( Figure 4 A). The production and loss rates balance at a steady state, whose intercellular WG concentration I compared to K WG→wg ( Figure 4 B). (2) Transport of WG from a neighbor with high levels of wg expression cannot raise the concentration of intracellular WG above K WG→wg . Similarly, levels of WG protein that accumulate in cells with low wg expression by transport processes and basal transcription must not be high enough to activate wg expression in these cells. In particular, the steady-state concentration in a cell producing wg must exceed K WG→wg , but the concentrations in its non- wg -expressing neighbors must be below this value. Parameter sets achieving the segment polarity pattern satisfy these inequalities, as shown in Figure 4 B, while randomly-generated parameter sets do not ( Figure 4 C). (3) Extracellular WG from two neighbors with high levels of wg expression must be greater than K EWG → en , the amount of extracellular WG signal needed for half-maximal induction of en expression. Extracellular WG signaling must be sufficient to activate en in the absence of Cubitus Interruptus (CI) repression. The parameter K EWG → en indicates the amount of extracellular WG signal needed for half-maximal en activation. The WG signal produced by cells in the high- wg -expression steady state must be strong enough to activate en and thus greater than K EWG → en . Working parameter sets satisfied this constraint ( Figure 4 D), while random parameter sets typically did not (data not shown). (4) The steady-state level of the CI amino-terminal fragment (CN) must be greater than K CN┤ en , the amount of CN needed for half-maximal repression of en expression. Repressive CI must also be sufficient to block en expression in cells that are near the WG stripe, but which lack en expression. In the absence of en expression, levels of CN are governed by transcriptional regulation of Patched (PTC). The equations in the model give a single steady-state level of CN. This must be greater than K CN┤ en , the amount of CN needed for half-maximal repression of en . As shown in Figure 4 E, this inequality holds for all parameter sets that form the segment polarity pattern. The interpretation of this constraint is more complicated because interactions of CI and PTC can cause persistent limit-cycle oscillations of CN about its steady-state level according to both simulations and analysis. However, this does not seem to affect our results, probably because the average level of CN across the oscillations is typically close to the steady-state level. Mutual inhibition provides two stable states, one in which en is expressed and represses ci , and one in which ci is expressed and maintains en repression. Through such comparisons, I found that of the 0.61% of parameter sets that produced the segment polarity pattern, more than 90% were predicted to produce bistable behavior in both the wg and en positive feedback loops (see Table 1 ). From another perspective, the fraction of parameter sets that maintain segment polarity is enriched more than 10-fold amongst those obeying the bistability rules: 0.61% of all parameter sets form the desired pattern, but 6.8% of the parameter sets that obey the bistability rules do so. Most likely, the small fraction (0.05%) of parameter sets that form the pattern but do not obey our bistability criteria fail to do so because of approximations used in these tests. In all 12 cases, they violate only a single rule, whereas the median parameter set that does not form the segment polarity pattern violates three of the four constraints. While 8.2% of all random parameter sets are consistent with the above restrictions, only 0.56% actually form the segment polarity pattern (see Table 1 ) whereas 7.6% do not. These parameter sets should maintain the segment polarity pattern, but cannot form it from the prepattern. Though the prepattern does have en and wg stripes, it lacks any expression of three regulators (hh , ptc, or ci) that are expressed in the final segment polarity pattern. Because the initial conditions are substantially different from the stable segment polarity pattern, there are initially large, rapid changes in the concentrations of the components that can drive the collection of cells towards a different final pattern. These early dynamics are complicated, and I could not determine simple rules that predicted which of the parameter sets that satisfied our bistability criteria would generate the segment polarity pattern starting from the initial conditions used by von Dassow et al. The predictive value of the bistability rules is in marked contrast to the performance of the isolated cell rules, for which half the parameter sets that satisfied the rules produced the correct segment polarity pattern. I believe that the methods differ because the isolated cell rules address the dynamics by using simulations in which early expression dynamics actually occurred, at least in individual cells, rather than the steady-state comparisons of parameters used in the bistability rules. To test this possibility, I asked if I could improve the predictive value of the bistability rules by choosing different initial conditions. I focused on initial levels of CI, PTC, and CN outside the stripe of en expression. Increasing the initial concentrations of CI and PTC is biologically reasonable, as ci and ptc are both expressed before en induction ( Motzny and Holmgren 1995 ). These two regulators constituted one of the isolated subnetworks used above. I solved for the steady-state expression levels of ci and ptc in each parameter set and used this in the initial condition for dynamic simulations with this parameter set. This change brought the prepattern in the model into better agreement with experimental results. The new initial conditions yielded a 6-fold increase in the number of parameter sets achieving the segment polarity pattern. This meant that 41% of the parameter sets meeting the bistability parameter rules actually formed the pattern from the modified prepattern (see Table 1 ), supporting the idea that many parameter sets obeying the bistability rules are able to form the segment polarity pattern but fail to do so from the initial pattern used by von Dassow et al. This suggests that the expression pattern of ci and ptc established by the pair-rule genes is biologically significant and plays a role in the robust formation of the final segment polarity pattern. This early expression of ci and ptc generates a prepattern that is more similar to the desired stable state. Maintaining the narrow parasegment boundary after cell division is an important role of the segment polarity network. Even at the level of the isolated cell rules, there is a discrepancy between the behavior of the model and experimental results. Experimentally, the maintenance of wg expression depends on HH signal from a neighboring stripe of en expression, but the wg “on” state is unconditionally stable in the von Dassow et al. model (compare Figure 1 C and Figure 3 B) ( Hatini and DiNardo 2001 ). This difficulty manifested itself when I incorporated cell division into the model. The stripe of wg expression should remain one cell wide as the segment widens by cell division. The daughters of cells in the wg stripe further from the en stripe will not be exposed to HH signaling and will therefore lose wg expression, leaving only one cell in the wg “on” state after each division. In the von Dassow et al. model, the independence of wg expression from HH, and thus en expression, allows both daughters of a cell in the stripe of wg expression to retain the wg “on” state. Thus, the stripe grows wider over repeated rounds of cell division rather than maintaining a narrow border at the segment boundary. Indeed, I found no parameter sets which maintained the physiological segment polarity pattern after cell division. I wanted to modify the model so that it succeeded at this patterning task as well. Principally, I needed to make wg expression dependent on HH signaling (see Figure 2 B). All effects of HH signaling are believed to be mediated by CI in its activating or repressive forms ( Methot and Basler 2001 ). These regulate wg in the von Dassow et al. model, but CI plays another role in the en positive feedback loop. Constraints imposed by this second role may limit its effectiveness in regulating wg in response to HH signaling. Recent evidence suggests that, while EN does repress ci expression, sloppy-paired (slp) is the second factor involved in a mutual inhibition loop with en . I therefore removed the repression of en by CN and introduced mutual inhibition of slp and en , with slp mediating the positive effect of EN on hh expression ( Alexandre and Vincent 2003 ). As all other signal transduction systems had been removed in the original model, I also removed ptc and allowed HH to directly inhibit the conversion of CI into CN. The interactions in this model are shown in Figure 2 B. The specific equations were similar to those used by von Dassow et al., but some details were modified; for example, the exact form of the effect of CI and CN on wg expression was changed to account for the fact that they compete for binding to the same DNA sites ( Muller and Basler 2000 ). I also simplified the transport processes for the intercellular signaling molecules WG and HH, which I showed play only a minor role in the original model. This modified model can robustly form the segment polarity pattern. Taking the same approach of testing random parameter sets, I found that 9.6% could generate the segment polarity pattern. This is an 8-fold higher fraction of successful parameter sets than that seen for the von Dassow et al. model or any subsequent variants ( von Dassow and Odell 2002 ). In order to test whether this was a result of bistability in wg and en expression, I developed bistability rules for the modified model. These rules require the following: (1) the amount of intercellular WG in a cell with high wg expression must be enough to activate wg expression; (2) the amount of intracellular WG in a cell with low wg expression, but receiving strong HH signaling, must not be high enough to activate wg expression; (3) the amount of EN in a cell with low slp expression and high WG signaling from neighbors must be enough to repress slp expression; and (4) the amount of EN in a cell with high slp expression, but high WG signaling from neighbors, must not be sufficient to repress slp. Nearly all working parameter sets obeyed these rules, as I found for the von Dassow et al. model (see Figure 5 A). They were even better predictors of working parameter sets than the parameter rules in the original model; nearly half of random parameter sets that are consistent with these rules form the proper pattern ( Table 2 ). Figure 5 Inequalities Necessary for Bistability in the Modified Segment Polarity Model (A) Intercellular WG levels in a cell that expresses wg (green) and that does not express wg (red) were plotted against K WG→wg for each parameter set that forms the segment polarity pattern, as in Figure 4 B. In both cases, cells are receiving maximal HH signal from two neighbors. (B) Intercellular WG levels in a cell that is expressing wg but is no longer receiving HH signal from any neighbors were plotted against K WG→wg . Parameter sets that can produce the proper pattern after proliferation, including narrow stripes of wg expression, are shown in green while those that fail to do so are shown in red. Table 2 Pattern Formation and Predictive Rules in the Modified Model Random parameter sets ( n = 100,000) were generated and tested for segment polarity patterning in the new model, using the stripe threshold scoring scheme as described in von Dassow et al. (2000) . Frequency: The fraction of random parameter sets that display the indicated behavior. Parameter sets that display proper four-cell patterning are subdivided based on whether they properly form narrow expression stripes after cell proliferation. Four-cell Bistability: Parameter sets were tested for agreement with four parameter rules that should predict bistability necessary for patterning the four-cell-wide segment. Eight-cell Maintenance: Parameter sets were tested for their ability to maintain the postproliferation expression pattern. The initial conditions were an eight-cell-wide segment with adjacent one-cell-wide stripes of wg and en expression. Gene expression dynamics were simulated, and the final expression pattern was tested with the stripe scoring scheme as modified to test patterning after cell proliferation. Postproliferation Bistability: Parameter sets were tested for agreement with two parameter rules that should predict when removal of WG or HH signaling abolishes bistability in en or wg expression, respectively. Positive predictive value and negative predictive value: As in Table 1 . The four-cell bistability rules were tested for their prediction of four-cell patterning. The eight-cell maintenance and postproliferation bistability tests were checked for their prediction of postproliferation patterning amongst cells that formed the proper four-cell pattern. Predictive values are reported as fractions Rules 1 and 2 are exactly analogous to bistability rules for the original model that ensure bistability in wg expression. The only change is the inclusion of HH signaling, which regulates wg expression in the modified model. Because ci is responsible for transducing the HH signal, I needed to find a different mutual inhibition partner for en ; recent experiments implicated slp in this process. Rules 3 and 4 are similar to the bistability rules that ensure mutual repression of en and ci expression in the original model. They require high en expression to be strong enough to repress slp and vice versa. This ensures that either of the two states of the mutual inhibition switch is stable, and so en expression is bistable. In addition to maintaining the initial segment polarity pattern, the modified model is also capable of producing the proper pattern after cell division. Fully 1.7% of random parameter sets yielded the desired narrow stripes of gene expression after division, showing that this feature of the modified model is also robust (see Table 2 ). I investigated whether bistability of wg and en expression also explained which parameter sets could produce the proper pattern after cell proliferation. Achieving this pattern requires two steps: as cells proliferate, half of the daughters of wg - or en -expressing cells must turn off these genes, and the resulting pattern must be stable over time. The criteria for the stability of the pattern after proliferation are quite similar to those for the original pattern. In fact, nearly all parameter sets that form the original pattern can also maintain the eight-cell-wide segment pattern with one-cell-wide stripes if this pattern is used as an initial condition (see Table 2 ). Thus, parameter sets that fail to generate this pattern after cell proliferation must have difficulty reaching the proper pattern rather than maintaining it once produced. The more important constraint, as discussed above, is that wg and en expression must fade as cells move away from the mutual reinforcement at the boundary. I devised two additional rules based on this mutual dependence: (5) the amount of intracellular WG in a cell with high wg expression, but receiving no HH signaling, must not be sufficient to maintain wg expression ( Figure 5 B); and (6) the amount of SLP in a cell with initially high en expression that stops receiving strong WG signaling must be enough to repress en expression. Only one row of cells on either side of the parasegment border will be receiving WG or HH signals across the boundary. Rules 5 and 6 ensure that this signaling is necessary to maintain en and wg expression, so daughter cells born away from the boundary lose en or wg expression. This dependence is the mechanism by which the modified model maintains narrow stripes of segment polarity gene expression after cell division. These rules are reasonable predictors for proper behavior during cell proliferation. However, there are a substantial fraction of parameter sets that work despite breaking one or both rules, as well as many which obey them yet cannot produce the proper pattern after one round of cell division. Some of these difficulties probably result from the dynamic nature of the underlying process. As discussed above, bistability rules such as these can determine when a particular expression state is stable, but it is much harder to determine which stable state will be reached for a given initial condition. Thus, it is possible to predict when a parameter set will be able to maintain the final postproliferation pattern, but it is much harder to determine when it will reach this pattern from the expression state immediately following proliferation. This does not explain why there are parameter sets that do not obey rules 5 and 6 but nonetheless give narrow stripes of gene expression after cell division. Those parameter sets expose limits in the approximations used to develop the cell bistability rules. There may be small but important interactions between different feedback loops within a single cell, or perhaps some aspect of intercellular signaling is more complicated than the simple binary model employed in the bistability rules. Discussion I have shown that individual cells in the segment polarity model can adopt three distinct expression states, influenced by signals from their neighbors. I have also presented evidence that positive feedback in the model produces these states. The importance of autoregulation in establishing distinct expression states has been recognized in this system before ( Heemskerk et al. 1991 ). In general, positive feedback can produce discrete stable expression states which are insensitive to small changes in parameters or initial conditions ( Thomas and Kaufman 2001 ). This explains the robustness of the segment polarity patterns in the models. The ways in which intercellular signals impinge on autoregulatory loops will determine which expression patterns are possible. In a field of cells with bistable expression states, the overall pattern is just a specification of a particular expression state for each cell in the field. When signals produced by cells in the pattern are consistent with the states of neighbors receiving them, then this pattern will be a stable steady state. In the segment polarity pattern, there is a stripe of high en expression posterior to the stripe of wg expression, but one with low en expression anterior to it. The stripe of wg expression produces a signal that is strong enough to maintain the high en expression state, but does not induce en expression in cells that do not initially express it. Thus, the states of the cells neighboring the stripe of wg expression are consistent with the signals it produces. Our modifications to the model changed the effect of HH on the wg autoregulatory loop. This destabilized the pattern of wide stripes of wg expression resulting from cell proliferation, retaining the desired pattern with narrow wg expression as a stable pattern. Because the wide-stripe pattern was no longer stable, the model did not become trapped in this state following cell division. Many parameter sets instead progressed to the narrow-stripe pattern. The approach I have taken can be generally applied to models of complicated genetic or biochemical networks. I isolated small subnetworks, chosen to be maximally insulated from the rest of the system, and studied their behavior in isolation. This let us understand the principles that allow the entire network to function. I verified this understanding by creating tests for the behavior of the subnetworks and showing that these were powerful predictive tools for the performance of the entire network. This sort of decomposition is also useful in combination with quantitative phenomenological descriptions of subnetwork behaviors. Recent experimental studies provide such descriptions for a number of biological systems, including vertebrate homologues of the wg signal transduction system ( Bagowski and Ferrell 2001 ; Bhalla et al. 2002 ; Lee et al. 2003 ). These could replace subnetworks in a larger model, tying the model more closely to biological evidence and showing how the subnetwork affects the larger system in which it functions. The robustness of the segment polarity network is a result of the fact that the desired pattern is a stable steady state. In a system of ordinary differential equations, such as the models described here, such states correspond to stable fixed points. These are generic features of such systems; small changes in parameters or initial conditions will not change them qualitatively. This can be seen in the bistability rules I developed. They are inequality constraints, so they carve out a volume of parameter space in which parameter sets can maintain the segment polarity pattern. In our analysis, I focused on robustness against changing parameters, which correspond to genetic alterations that change quantitative values of reaction parameters. In the real world, stochastic and environmental perturbations in the system may play at least as large a role. One important question is the extent to which the behavior of a network is determined by its topology, as opposed to quantitative details. The network topology is just the set of interactions in the network, along with their signs. This information is accessible to standard, qualitative biological experiments. Topology limits the possible behaviors of a regulatory network. Positive feedback, which is a topological property, is necessary for multiple stable states ( Thomas and Kaufman 2001 ). Without such autoregulatory loops, all cells would eventually return to the same state after inducing signals are removed. Thus, positive feedback is particularly important in development and differentiation, when many different cell fates are permanently specified. However, quantitative details still have a large influence on network behavior. I held network topology constant while testing random parameter sets, which corresponds to changing quantitative details. Most random parameter sets did not form the segment polarity pattern because they did not display the proper stable states, despite having a topology that was capable of forming the segment polarity pattern. Quantitative details select a particular behavior from the repertoire of behaviors that are accessible from a given network topology. This same phenomenon has been shown experimentally in synthetic genetic networks, where a single topology can give rise to different behaviors when transcription factors and their binding sites are varied ( Guet et al. 2002 ). These examples show how changes in the quantitative details of a regulatory network can result in qualitatively different behaviors. This could explain how pattern formation can be evolvable; mutations which cause large shifts in a critical parameter could cause a network to form a different pattern corresponding to a new stable state. The altered pattern would still correspond to a stable fixed point, so it would also be robust against various kinds of perturbations. This offers a mechanism that could produce new patterns without nonfunctional intermediates and without events such as the creation of a new protein–protein interaction. Materials and Methods The model employed a system of differential equations described by von Dassow et al. (2000) . The correspondence between variables and parameters in our model and theirs is in Table 3 . Simulations and numerical approximations were performed using the GNU Scientific Library ( Galassi et al. 2002 ). Table 3 Variables in This Work and von Dassow et al. (2000) Isolated cell rule simulations Isolated cell rules were tested by simulations in which the dynamics of an individual cell were modeled using the same equations that govern each cell in the segment for the full segment polarity network. Since WG protein diffused between cells as well as moving into and out of a given cell, it was important to account for the diffusion of WG even in isolated cell simulations. The level of wg mRNA in a cell is represented by w i . Once translated from wg mRNA, WG protein diffuses between the intracellular pool, represented by I i , and extracellular pools on each face j of the cell, E i , j . Extracellular WG can exchange between faces of the same cell and between opposing faces of adjacent cells. The parameters H IWG and H EWG are the half-lives of WG in the intracellular and extracellular pools, respectively. The diffusion parameters K out,WG , K across,WG , K around,WG , and K in,WG are the rate constants for the first order of exchange of WG between the intracellular and extracellular pools and between different cell faces. These are linear equations, so it is possible to solve for the steady-state levels of I i and E i,j as a function of the w i s , which control WG production, by inverting a matrix of transport and decay rates. In the segment polarity pattern, particularly, there is just one wg -expressing cell in the periodic pattern of four cells. So, I take w on for one cell and w off for the other three in the periodic unit. All WG protein is initially intracellular, but it moves to extracellular faces by a roughly first-order process with time constant k = K in,WG + H −1 EWG . Therefore, I used E i,j ( t ) = (1 − e kt ) · E˜ i,j as the amount of WG protein on neighboring cells for the isolated cell simulations. To verify bistability of wg expression, I simulated a single cell with no HH signaling from its neighbors. I calculated the amount of WG protein expected to be present on neighbors by an iterative process. Starting with w on,0 = 1 and w off,0 = 0, I computed the steady-state extracellular WG protein E˜ i,j ( w on , w off ) presented by the neighbors of the cell expressing wg and used these in simulating a cell with initial w = 1. Similarly, I computed the amount of WG protein on neighbors of a cell next to the stripe of wg expression and used this in simulating a cell with initial w = 0. The final values of w in those two cells were used as w on,i +1 and w off,i +1 to compute the levels of extracellular WG protein for the next iteration. This process quickly converged, and I took the resulting w values as w on and w off . I verified that w on was above 0.1, the expression level threshold used in scoring pattern formation, and that w off was below 0.1. I then used the same levels of extracellular WG protein, computed from w on and w off , to simulate a cell next to a stripe of wg expression. I used initial en mRNA and protein levels of 1 or 0 and ensured that, at the end of the simulation period, the former cell had en expression levels over the threshold but the latter did not. Finally, I verified that a cell with high initial wg mRNA but low initial en mRNA, receiving signals as if it were in the stripe of wg expression, still had low en expression at the end of the simulation. Bistability parameter rules These equations make repeated use of a particular equation form representing saturable and cooperative action of a protein, for instance as a transcriptional activator. In general, the amount of activation, Φ, as a function of the concentration of activator, x , is Here, K indicates the concentration of activator needed for half-maximal activation; it is essentially an affinity of the activator for its target. The parameter ν controls the degree of cooperativity in activator function, with large values of ν giving stronger cooperativity. The function produces sigmoidal curves which asymptotically approach 1 when x is large relative to K . In the model, there is a different Φ for each instance of transcriptional regulation controlled by an affinity parameter K and a cooperativity parameter ν for that interaction. For instance, the activation of en by extracellular WG is controlled by K EWG → en , which indicates the amount of extracellular WG needed for half-maximal activation, and by ν EWG → en , which determines how cooperative the activation is. ci and ptc subnetwork I designed parameter rules for bistability by analyzing different subnetworks in the model and solving for steady states consistent with bistability from positive feedback. I solved for the stationary state of the ptc and ci subnetwork in the absence of en expression. The concentrations of ptc and ci mRNAs are p and c , and the concentrations of PTC protein, activating CI protein, and repressive CN are P , C act , and C rep . The equations governing this system, entirely contained within a single cell, are The affinity and cooperativity parameters for each Φ have been suppressed for clarity. The parameters H ci and H ptc are the half-lives of ci and ptc mRNAs, and similarly the parameters H Ptc , H Ci , and H CN are the half-lives for the protein species. The level of Bicoid, a constitutive activator of ci expression, is indicated by the parameter B . Finally, C 0 is an affinity parameter for the cleavage of CI by PTC. To find the stationary state, I solve for the simultaneous zero of all five equations. Two variables, c and P , can be trivially eliminated. The remaining three equations in three variables always yielded a unique stationary state. The level of CN at this state, C˜ rep , was compared to K CN┤ en , the amount needed for half-maximal repression of en expression (parameter rule 4). The levels of CI and CN were also used to compute their influence on wg expression. The strength of this activation was indicated by β, a single term encompassing activation by CI and repression by CN. The only parameters in this expression are the affinity and cooperativity parameters for each Φ. WG and its effect on en Levels of wg mRNA in the i th cell, w i , are governed by β, which indicates the influence of CI and CN on wg expression, and by I i , the amount of intracellular WG in the cell. In addition to affinity and cooperativity parameters for each Φ, and H wg , the half-life of wg mRNA, there are scalars α CI → wg and α WG → wg , which determine the relative strengths of CI/CN and WG influences on wg expression. When I i > K WG → wg , then Φ( I i ) will be large and wg expression high. I computed steady-state intracellular and extracellular WG protein levels as a function of wg expression as described above for the isolated cell rules. Bistability requires that intracellular WG levels in a wg -expressing cell remain high enough to maintain wg expression. I computed successive approximations to steady-state levels of wg mRNA and protein. I found I˜ w =1 = I i ( w i =1) by setting and then found w˜ on = w i ( I i = I˜ w =1 ) by setting . I then required that I˜ on = I i ( w i = w˜ on )> K WG → wg , meaning that the level of intracellular WG is sufficient to maintain wg expression (parameter rule 1). I found no cases in which this much faster test gave different results than actually solving the self-consistent equations for . Bistability also requires that a cell not initially expressing wg must not be activated by WG from a neighboring cell. I used w˜ on to compute the amount of intracellular WG in a cell next to the wg stripe but not itself expressing wg , I˜ nbr = I i +1 ( w i = w˜ on , w i +1 =0), and found w˜ off = w i +1 ( I i +1 = I˜ nbr ) and I˜ off = I i +1 ( w i +1 = w˜ off ). I then verified that I˜ nbr + I˜ off < K WG → wg , meaning that the sum of intracellular WG transported into a wg “off” neighbor and the intracellular WG produced by the wg “off” neighbor is not enough to activate wg expression (parameter rule 2). Finally, I find levels of extracellular WG signaling E˜ on , j and E˜ off , j in the same manner as I˜ on and I˜ off , respectively. These are used to ensure that the level of extracellular WG signal received by a cell in the en stripe is Σ E˜ > K EWG → en (parameter rule 3). Modified initial conditions The modified initial conditions were generated by solving for the steady state of the CI and PTC subnetwork as described above. This yielded steady-state values c˜ , C˜ rep , C˜ act , p˜ , and P˜ , which were used for the initial conditions in the stripe of wg expression and in the stripe expressing neither wg nor en . Initial conditions for components of the CI and PTC subnetwork in the stripe of en expression were kept at 0. The modified initial conditions also used steady-state levels of intracellular and extracellular WG protein. The steady-state I˜ i and E˜ i , j values were computed as described above under the assumption of a single column of cells with maximal wg expression and three columns with no wg expression. This latter change had a very modest impact on the fraction of parameter sets which formed the segment polarity pattern, and I did not pursue it further. Modified model The equations governing the modified model were similar in form to those in the original model. In addition to using the functional form Φ( x ), I employed a related functional form Ψ( x r , x a ) that represents the effects of an activator and a repressor that compete with equal affinity for a common binding site. Again, K is essentially an affinity parameter and ν controls the cooperativity of the process. The a 0 term indicates the basal expression level, seen when neither activator nor repressor is acting. This functional form is used to express the effect of repressive CN and activating CI on wg expression. I also used it to represent the effect of intracellular WG activator with basal wg transcription, setting the repressor term x r =0. In addition to the dynamic variables described above, levels of en mRNA and EN protein are given by n and N , and levels of slp mRNA and SLP protein are given by s and S , respectively. The affinity, cooperativity, and basal transcription parameters are suppressed throughout for clarity. As nearly all dynamic variables are in the same cell, subscripts that index concentrations within a given cell are also omitted. In the two equations that involve intercellular signaling, a term E¯ Nbr or H¯ Nbr indicates the sum of extracellular WG or HH on neighboring cells, respectively; this is equivalent to the average without a normalization for the number of cells. Initial conditions were n = N =1 in the stripe of en expression, w = I =1 in the stripe of wg expression, and s = S =1 in the two-cell-wide stripe expressing neither en nor wg . As in the original model, cell proliferation was accomplished by doubling the grid size and copying the dynamic variables from each cell into two adjacent cells in the new grid. Bistability parameter rules Steady-state levels I˜ on and I˜ off were computed similarly to the way described for the original model. I assumed maximal ci expression, c =1, and maximal HH signal from two neighbors, H¯ Nbr =2, in computing the steady-state levels C˜ act and C˜ rep . As there was no intercellular transport of WG in the modified model, I needed to worry only about basal and activated wg expression in a single cell and did not need to consider intercellular transport. To check parameter rules 1 and 2, I simply compared the two steady-state levels I˜ on and I˜ off to K WG → wg . I computed E˜ w =1 for c =1 and H¯ Nbr =2 to account for WG signaling in en expression. I then found N˜ S =0 using E¯ Nbr =2 E˜ w =1 to represent maximal WG signaling from two neighbors and S =0, no slp expression, in the steady-state equation n˜ = N˜ =Φ( E¯ Nbr )·(1−Φ( S )). I used this to compute S˜ off using the steady-state equation s˜ = S˜ =(1−Φ(N)). Finally, I used S˜ off and E˜ w =1 to find N˜ on in the en steady-state equation. I compared N˜ > K EN ┤ slp to ensure that steady-state levels of EN were sufficient to repress slp expression. Similarly, I found N˜ S =1 using the steady-state en equation and used this to find S˜ on using the steady-state slp equation. The S˜ on was then used to find N˜ off , and I required that N˜ off < K EN ┤ slp . This ensured that repressed levels of en expression were not sufficient to repress slp expression. To test that wg expression was dependent on HH signaling, I first found I˜ on as described before. I also computed C˜ act and C˜ rep using c =1 but H¯ Nbr =0, representing a loss of HH signaling. I then used I˜ on and the new C˜ act and C˜ rep to find w˜ H =0 and I˜ H =0 with the steady state wg equation. I then found w˜ on → off and I˜ on → off using the steady state wg equation, the new H =0 values for C˜ act and C˜ rep , and I˜ H =0 . Finally, I verified that I˜ on → off < K WG → wg , which ensure that wg autoactivation is not sufficient to maintain its expression after HH signaling is removed. To check whether en expression was dependent on WG signaling, I started with N˜ on and S˜ off as described above. I found E˜ off in the same way in which I found I˜ off and used E¯ Nbr , off =6 E˜ off . I used this new level of WG signaling to find N˜ on → off with the steady state en equation, and then used this value to find S˜ off → on with the steady-state slp equation. To verify parameter rule 6, I checked that S˜ off → on > K SLP ┤ en , ensuring that the unrepressed level of slp expression can block en expression. Supporting Information Protocol S1 Bistability in wg Expression Additional background and explanation of bistability in gene expression. (109 KB PDF). Click here for additional data file. Accession Numbers The FlyBase ( http://flybase.bio.indiana.edu/ ) accession numbers for the genes discussed in this paper are ci (FBgn0004859), en (FBgn0000577), hh (FBgn0004644), ptc (FBgn0003892), slp (FBgn0003430 and FBgn0004567), and wg (FBgn0004009). | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC423129.xml |
514544 | Arrhythmia-provoking factors and symptoms at the onset of paroxysmal atrial fibrillation: A study based on interviews with 100 patients seeking hospital assistance | Background Surprisingly little information on symptoms of paroxysmal atrial fibrillation is available in scientific literature. Using questionnaires, we have analyzed the symptoms associated with arrhythmia attacks. Methods One hundred randomly-selected patients with idiopathic paroxysmal atrial fibrillation filled in a structured questionnaire. Results Psychic stress was the most common factor triggering arrhythmia (54%), followed by physical exertion (42%), tiredness (41%) coffee (25%) and infections (22%). Thirty-four patients cited alcohol, 26 in the form of red wine, 16 as white wine and 26 as spirits. Among these 34, red wine and spirits produced significantly more episodes of arrhythmia than white wine (p = 0.01 and 0.005 respectively). Symptoms during arrhythmia were palpitations while exerting (88%), reduced physical ability (87%), palpitations at rest (86%), shortage of breath during exertion (70%) and anxiety (59%). Significant differences between sexes were noted regarding swollen legs (women 21%, men 6%, p = 0.027), nausea (women 36%, men 13%, p = 0.012) and anxiety (females 79%, males 51%, p = 0.014). Conclusion Psychic stress was the commonest triggering factor in hospitalized patients with paroxysmal atrial fibrillation. Red wine and spirits were more proarrhythmic than white wine. Symptoms in women in connection with attacks of arrhythmia vary somewhat from those in men. | Background Atrial fibrillation (AF) is nowadays divided into three different forms; paroxysmal, persistent and permanent [ 1 ]. Even if the pathological, electrical and physiological phenomena leading to AF have been described in ever more detail, the mechanisms underlying these changes remain largely unknown. The relative occurrences of paroxysmal atrial fibrillation (PAF) and other forms of this arrhythmia in the population are also not well known. In a material based on hospital observations, 35% of all fibrillation was described as being of paroxysmal type [ 2 ]. Despite being common, surprisingly limited information about possible triggering factors and symptoms at the onset of arrhythmia in larger groups of patients is available [ 3 ]. Our aim in this investigation was to throw further light on the factors believed by patients to have caused their arrhythmia and on the symptoms experienced at the onset of attacks of AF. Methods A group of one hundred patients suffering ECG-verified PAF and whose symptoms prompted hospital care were asked to fill in a structured questionnaire with 58 questions covering arrhythmia-triggering factors, time at which the attack starts and symptoms during attack. All patients completed the data by personal interviews by one of the authors. The vast majority of all patients were recruited during two periods of totally 14 months. In some questions, extra information could be supplied by the patients in their own words. (The complete questionnaire could be seen in additional file 1 : AHansson_enkat.pdf). All patients had earlier had attacks of AF which stopped either spontaneously or following medication. Most of them had earlier been treated in hospital for the arrhythmia. Patients who previously had myocardial infarction, pericarditis, diseases of the thyroid or diabetes were not included since these diseases may be the underlying cause of the arrhythmia [ 4 - 10 ]. Our group of patients thus had idiopathic PAF. Permission for the investigation was obtained from the local Ethical Committee and all patients were informed about the investigation both orally and in writing. Statistics Data were compared using Fisher's Exact Test and Mann Whitney U-test. Values of p < 0.05 were considered significant. Results Material One hundred completed questionnaires were filled in by 72 men and 28 women. Twenty-four of these had on some occasion been treated for hypertension. The median (range) age of the entire group was 59.9 (22.4–79.2) years. Patients with previous histories of hypertension were significantly older than those without 65.0 (46.6–78.6) years as against 58.6 (22.4–79.2) years respectively. The women in the group were significantly older than the men 67.9 (54.1–78.6) years and 58.2 (22.4–79.2) years respectively, p = 0.02 (Fig. 1 ). Since patients with hypertension differed from the others only as regards age, the ensuing analyses were made without respect to its incidence. Seventy six of all patients were given genuine antiarrhythmic drugs, sotalol being the most common. Twenty four of the patients were not taking any antiarrhythmic pharmacological treatment (Table 1 ). Figure 1 Age-distribution by sex. In the group investigated, the median age was 59.9 (22.4–79.2) years median (range). The women were significantly older than the men. Table 1 Current pharmacological antiarrhythmic treatment Sotalol 40 Disopyramid 13 Digoxin 13 Metoprolol 5 Flekainid 5 Propranolol 3 Atenolol 3 Verapamil 3 Bisoprolol 1 Amiodaron 1 No antiarrhythmic medication 24 Attacks of arrhythmia Seventy-two patients believed that their attacks usually started at about the same time of day, typically starting in the evenings or at night (Fig. 2 ). The time of onset appeared not to depend on sex. Figure 2 Time at which palpitations started. Seventy-two patients thought that arrhythmia always started at the same time of day, typically in the evening or at night. Some, however, gave more than one time-interval. For most patients (64%), attacks typically lasted less than one day, while a further 17% gave 1–7 days. No attack lasted more than one week. Thirty-five percent of the entire group woke up with episodes of fibrillation, 34% stated that attacks began with psychic stress, as defined by the patients. Thirty one percent of the episodes started during rest and 22% of the attacks followed physical exertion. Twenty-five percent could not think of any special factor initiating attacks. No differences in the onset of attacks between men and women could be established. Eighty-five percent of the group succeeded in identifying some sort of triggering-factor (Table 2 ). The most common of these was psychic stress followed by physical exertion, tiredness and infection. As regards foodstuffs, 25% thought that coffee was the triggering-factor. Those who cited sympathetic tone anamnesis with stress as the triggering-factor usually stated that the onset of arrhythmia was in the evening or at night. Table 2 Possible arrhythmiatriggering-factors as identified by patients with paroxysmal atrial fibrillation Triggering factor % Mental stress 54 Physical effort 42 Tiredness 41 Any alcohol 34 White wine 16 Red Wine 26 Liquor 26 Coffee 25 Infections 22 Cold drinks 8 Large meal 3 Food 18 Onions 5 Nuts 4 Chocolate 3 Ice cream 2 Spiced food 2 Cream 1 Strawberries 1 Fish 1 Sweets 1 Beans 1 Shellfish 1 Garlic 1 No triggering-factor 15 Alcohol was named as a triggering-factor by 34 patients, in 26 cases in the form of red wine, in 26 as spirits and in 16 white wine. Some patients named more than one kind of alcohol as a triggering factor. Two of those who reacted to red wine did not drink spirits and hence could not say whether spirits, too, trigger arrhythmia. In the alcohol-triggered group, red wine and spirits triggered more episodes of arrhythmia than white wine (p = 0.01 and p = 0.05 respectively). There were no significant differences in the arrhythmia-provoking effects of spirits and red wine nor between men and women (Table 2 , Fig. 3 ). Time delay between onset of trigger and subsequent onset of the AF episode was not explored in the questionnaire. Figure 3 Any alcohol as a pro-arrhythmic factor. Thirty-four patients cited various forms of alcohol as a factor triggering arrhythmia. Some patients named more than one kind of alcohol. Twenty-six cited red wine, 26 spirits and 16 white wine. In this group, red wine and spirits caused significantly more episodes of arrhythmia than white wine. Foodstuffs such as onion, nuts, chocolate and ice-cream were cited as agents producing fibrillation by a few patients (Table 2 ). Seventy-four percent considered that the episodes of AF they experienced affected their lifestyles, while 26% thought this was not the case. Among answers in their own words, a common reply was that they did not dare to exercise as much as they would have liked (13 patients). Eight patients did not dare to travel. Sixty-six percent stated that their episodes of AF affected their relatives, while 32% answered this question in the negative. In their own words, they remarked that the main problem was their relatives' uneasiness. During attacks of AF, the most common symptoms were palpitations in connection with strain, reduced physical performance, palpitations when at rest, breathlessness during exertion and anxiety (Table 3 ). Females showed significantly higher frequencies of swollen legs (p = 0.02), indisposition (p = 0.012) and anxiety (p = 0.014) than males. Table 3 Symptoms in association with the onset of paroxysmal atrial fibrillation by gender Symptoms Total n = 100 Males n = 72 Female n = 28 p-value Pre-symptoms 32 20 (28%) 12 (43%) 0.159 Pains in the chest 25 14 (19%) 11 (39%) 0.070 Dizziness 52 33 (46%) 19 (68%) 0.074 Syncope 7 4 (6%) 3 (11%) 0.396 Breathlessness when resting 41 32 (44%) 9 (32%) 0.365 Breathlessness when working 70 53 (74%) 17 (61%) 0.230 Swollen ankles 10 4 (6%) 6 (21%) 0.027 Palpitation at rest 86 62 (86%) 24 (86%) >0.999 Palpitation at exercise 88 59 (82%) 23 (82%) >0.999 Nausea 19 9 (13%) 10 (36%) 0.012 Vomiting 2 1 (1%) 1 (4%) 0.484 Abdominal pain 5 2 (3%) 3 (11%) 0.312 Loss of appetite 31 20 (28%) 11 (39%) 0.336 Anxiety 59 37 (51%) 22 (79%) 0.014 Reduced physical capacity 87 62 (86%) 25 (89%) >0.999 Polyuria* 40/75 25/52 (48%) 15/23 (65%) 0.213 *this question was put to only 75 patients. Discussion Although PAF is one of the most common heart-disturbances causing patients to get in touch with medical care centres, surprisingly little information is available about the factors which trigger it and the symptoms associated with the onset of arrhythmia in larger groups of patients. This study has therefore been undertaken to determine which factors patients consider responsible for triggering arrhythmia and the symptoms that occur in connection with episodes of arrhythmia. What provokes arrhythmia? From observations of heart-rate in sinus rhythm shortly before its onset, a separation of PAF into sympathetically-mediated and vagal forms has been suggested [ 11 ]. Earlier studies have shown a degree of daily variation in the onset of AF. Thus, attacks are more common in the morning and at night [ 12 ], but higher frequency has also been reported during daytime [ 13 ]. A possible explanation is that arrhythmia often starts in younger patients at night and in older ones during the day [ 14 ]. A weekly variation has also been reported, with fewer attacks on Saturdays [ 12 ]. An annual variation with fewer attacks during the last months of the year has also been reported [ 12 ]. In our study, the 72 patients who thought that their attacks of arrhythmia usually occurred at about the same time of day gave this as the evening or at night. Hence a large fraction of those investigated should have vagal PAF since this often starts at night [ 11 ]. Despite this, the majority of the patients considered that the triggering-factor was some kind of situation in which increased levels of catecholamines can be discerned. Even those with positive stress-related anamnesis (triggered by physical exertion and psychic stress) had often attacks starting in the evening or at night. However, this need not imply an absolute correlation in time, but rather the probable existence of a certain latent period between stress and the onset of arrhythmia. In earlier studies, it has been proposed that attacks of PAF are often due to variations in the tonus of the autonomic nervous system. Arrhythmia is stimulated particularly when an initial adrenergic increase is followed by an abrupt change to vagal dominance [ 15 ]. Alcohol has long been considered to play an etiological role in PAF, a correlation underlined in the expression "holiday heart" [ 11 ]. Since temporary enhanced alcohol consumption is frequent, it is difficult to prove a direct correlation [ 8 , 16 ]. Episodes of AF have been triggered by the acute effects of alcohol on atrial refractoriness and conduction, but also by the effects of chronic misuse of alcohol leading to subclinical heart dysfunction [ 17 ]. Other mechanisms have also been discussed [ 18 ]. Every third patient in our study considered alcohol to be a triggering-factor, but white wine was blamed less than red wine and spirits. Why arrhythmia should be triggered less frequently by white wine than by red wine or spirits remains unclear. It is now generally accepted that most attacks of PAF are induced by ectopic impulses originating in the pulmonary veins [ 19 , 20 ]. Both automaticity and triggered automaticity in these cells have been demonstrated in experimental conditions [ 19 , 20 ]. The influence of the autonomic nervous system, alcohol and other factors inducing arrhythmia on this mechanism is, however, uncertain. Symptoms at the onset of fibrillation Although a number of patients with PAF are without any symptoms [ 21 ], in general patients with this form of arrhythmia show more symptoms than those with permanent AF [ 22 ]. Studies with telephone-transmitted ECG have, however, shown a sensitivity of symptomatic registrations of up to 89% with PAF [ 23 ]. There is thus good correlation between the symptoms and ECG-verified AF. The limited amount of literature on the symptomology of PAF includes Quality of Life investigations, Case Reports and quantification of a few symptoms [ 24 ]. Investigations based on "Quality of Life" forms have earlier shown that patients with PAF have lower scores for physical function, emotional function, vitality and general health [ 24 ]. The symptoms commonly reported include palpitations, giddiness, dyspnoea, tachycardia, perspiring, chest pains, coldness, anxiety [ 23 - 25 ], tiredness, weakness, indisposition, vomiting and epigastrical discomfort [ 26 ]. The most frequent symptoms in periods of AF reported by our group of patients included palpitations, reduced physical performance, palpitations when at rest, breathlessness when exerting oneself and anxiety. In an earlier report, the most pronounced symptoms were palpitations and anxiety as well as giddiness [ 24 ]. That females showed significantly higher frequencies of swollen legs, indisposition and anxiety than males has not previously been reported. These differences can possibly be accounted for since earlier studies have reported that attacks of AF in women last longer and cause higher heart-rates [ 27 ]. We could not, however, establish any significant differences in the lengths of attacks between men and women in our material. Swollen legs can also be accounted for due to right-sided cardiac failure in some patients. That most patients experience definite symptoms following acute but transient attacks of AF can possibly depend on the increased activity of the sympathetic nervous system triggered by an attack of AF [ 28 ]. It is plausible to assume that the autonomic nervous system plays a considerable part in both the genesis of and the symptoms observed during a period of AF [ 24 ]. Limitations This material was taken at a hospital and is thus not representative of all patients with PAF. The symptoms of our patients are so far advanced that hospitalization or a visit to a hospital was required. Ongoing treatment can have modified patients' recollections of anamnestic factors. The material was not taken consecutively, but randomness was favoured by lack of a systemic inclusion mechanism. Patients with hypertension are not excluded, even if subtle diastolic changes in the left ventricle and hence the left atrial performance could be caused by hypertension [ 29 ]. Although symptoms associated with the onset of PAF may be age related, the present material is too limited to allow exploration of this relation. Conclusions Most of the patients in a group being treated at a hospital for PAF consider psychic stress to be the factor triggering their arrhythmia. Red wine and spirits seems more prone to trigger attacks of AF than white wine. The symptoms of PAF are many and occur frequently. In women, PAF leads to significantly higher frequencies of swollen legs, indisposition and anxiety than in men. Competing interests None. Authors' contributions Author AH designed the investigation, collected all patient data, performed the statistical analysis and interpretation of the results, as well as the preparation of the manuscript. Author BMH assisted with the statistical analysis and the preparation of the manuscript. Author SBO supervised and designed the investigation as well as participated in the preparation of the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 The complete questionnaire. The structured questionnaire with 58 questions covering arrhythmia-triggering factors, time at which the attack starts and symptoms during attack. 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528732 | Modeling of cell signaling pathways in macrophages by semantic networks | Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" ( i.e . individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed investigation of connections among various essential molecules and reflected the cause-effect relationships among signaling events. The simulation demonstrated the dynamics of the semantic network, where a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system. | Background Interactions among genes, gene products and small molecules regulate all cellular processes involving cell survival, cell proliferation, and cell differentiation among others. Such interactions are organized into complex lattice structures conventionally divided into cell signaling, metabolic and gene regulatory networks in a cell [ 1 ]. In recent years, large amounts of information and knowledge on cell signaling networks have been accumulated in the literature and databases [ 2 , 3 ]. Conventionally, this information is highly compartmental: various individual signaling pathways are mostly stored in separated and non-linked diagrams. Traditional pathway diagrams, where molecules are represented as nodes and their interactions are depicted as lines and arrows have significant limitations as they lack spatial and temporal context [ 4 ]. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Not surprisingly, the current state of pathway representation does not allow of complex investigation of qualitative or quantitative changes in cell signaling networks in response to external perturbations such as bacterial infections. Thus, an adequate computational environment for modeling cell signaling networks is needed for proper biological data integration as well as for simulation and prediction of cellular behaviors [ 5 ]. Recently, many models have been proposed for representing, storing and retrieving interactions among various biological entities. BIND [ 6 ] and IntAct [ 7 ] focus on protein-protein interactions and their resulting complexes. BioCyc [ 8 ] developed models for metabolic events and curated metabolic pathways from many organisms. The model developed by aMAZE [ 9 ] combines interactions in cell-signaling, metabolic and gene regulatory pathways. In addition, the System Biology Markup Language (SBML) has been developed for representing biochemical reaction networks and for communicating models used for various simulation programs [ 10 ]. Programs such as E-cell [ 11 ], Gepasi 3 [ 12 ] and Virtual Cell [ 13 ] use differential equations to represent molecular interactions, and their simulation results are obtained by solving these questions numerically [ 14 ]. It should be noted, however, that many cellular processes are sensitive to the stochastic behavior of a small number of molecules, and therefore, the assumptions in differential-equation methods can often be compromised [ 15 ]. Several studies have attempted to address the stochastic property of a cell. Vasudeva and Bhalla [ 16 ] proposed a hybrid simulation method that combined both deterministic and stochastic calculations. In addition, a stochastic simulator, StochSim [ 15 ] represented molecules as individual software objects that interact according to probabilities. Thus, it is feasible to suggest that useful cell signaling simulators should be capable of representing each molecule individually and reflecting the stochastic behavior of molecular interactions in a cell. Semantic networks Recently an artificial intelligence approach known as semantic networks (SN) have gained the attention of the biological community as a potentially powerful tool for organizing and integrating large amounts of biological information [ 17 ]. For instance, the semantic network in the Unified Medical Language System (UMLS) was designed to retrieve and integrate biomedical information from various resources [ 18 ]. The UMLS semantic network has also been applied and expanded to include information and knowledge from other domains such as genomics [ 19 ]. In addition, other studies have suggested a semantic approach where proteins are viewed as "adaptive and logical agents", whose properties and behaviors are affected by other agents in their spatial organization including intracellular compartments and protein complexes [ 20 , 21 ]. Defining the semantics among agents could characterize both local and global behaviors of a system, and therefore, it is potentially useful to apply such approach to study cell signalling in biological systems [ 21 ]. A semantic network is a method to represent information or knowledge by nodes and edges in a graphic form, where a node represents a concept and an edge represents a relationship [ 22 ]. A semantic network, which can exist abstractly in a human mind or be implemented by applying computer technology, can model many real-world problems [ 22 ]. Figure 1 illustrates a semantic network, where a concept such as a protein, a chemical reaction or a subcellular location is modeled by a semantic agent, and its relationships with other agents are represented as arrows. A proper semantic network implementation allows the identity and properties of an agent to arise from its relationships with other agents, not from descriptions or labels [ 23 ]. Hence, within a semantic network "things are what they do". Previously an application development environment known as Visual Knowledge (VK) has been created, and VK is capable of different formalizations and implementations of semantic networks for various knowledge domains [ 23 ]. Visual Knowledge has been applied successfully to model and manipulate complex "interactomes", including corporate enterprise systems, flight scheduling networks, hardware maintenance simulators, and integrated currency exchange boards [ 23 ]. It has been anticipated that Visual Knowledge can address many of the current limitations on modeling cell signaling pathways. Using the latest VK-based environment, BioCAD [ 24 ], specifically designed for biological applications, we have developed a semantic model for cell signaling pathways occurring in human macrophages. Bacterial invasions in macrophages It is the current knowledge that many pathogenic bacteria are capable of entering and surviving within mammalian macrophages by modulating the host signaling pathways [ 25 ]. One well-studied example is the activation of the Fcγ macrophage receptor by the IgG antibody, which binds to the surface of bacteria such as Mycobacterium tuberculosis [ 26 ]. Activation of the Fcγ receptor induces phagocytosis of M. tuberculosis and the formation of a phagosome within the macrophage. These processes are mediated by the class I phosphoinositide 3-kinase (PI3K) – one of the most well-characterized enzymes to date [ 27 ]. The class I PI3K is a heterodimer composed a p110 catalytic subunit and a p85 regulatory subunit, which maintains a low-level activity of p110 [ 28 ]. The p110 subunit is activated when p85 binds at a phosphotyrosine site on a receptor or an adaptor protein, or by direct binding to activated Ras [ 29 ]. Activated PI3K-p110 phosphorylates phosphatidylinositol-4,5-bisphosphate (PIP2) into phospatidylinositol-3,4,5-trisphosphate (PIP3), which is an essential signaling molecule that stimulates many downstream proteins, including PDK1 and Akt [ 30 ]. The formation of a phagosome is normally followed by the phagosome maturation process, which is responsible for intracellular killing of bacteria and is regulated by the class III PI3K [ 31 ]. However, it has been hypothesized that phosphatidylinositol analogs, such as ManLAM, produced by M. tuberculosis can inhibit the activity of the class III PI3K, arresting phagosome maturation process, and ensuring the survival of M. tuberculosis inside the macrophage [ 27 , 32 ]. In addition to their role in phagocytosis, PI3Ks are essential proteins that regulate cell survival, cell growth, cell cycle and other cellular processes [ 33 ]. Although, it is clear that PI3Ks play an important role in bacterial invasions, the knowledge of PI3K-mediated interactions is scattered in a number of literature and pathway databases. A coherent picture of detailed molecular interactions that link receptors to PI3Ks and to various cellular responses has yet to be constructed before bacterial invasions can be fully understood. To address this goal, a cell signaling network of the human macrophage was reconstructed with the semantic model, and qualitative changes in the network were investigated with a SN-simulator. Results A semantic model for cell signaling pathways In the paper, the word "model" refers to a set of rules in two different but related contexts. In the context of the semantic network, the model refers to a set of rules that specify how a biological concept is mapped to one or multiple semantic agents/relationships. In the context of cell signaling pathways, the model is a set of rules that specify what, how, and when molecules interact with each other. The model has been formalized and implemented, using BioCAD software system, and it is presented in the following sections. Overall classification of biological structures and their relationships Within the semantic network, all biological structures are modeled by semantic agents that are members in one of the 6 different prototypes. Table 1 shows the 6 types of structures in the order of their hierarchy. From the highest to the lowest level, they are "Cell", "Subcellular Compartment", "Macromolecule", "Domain/Site", "Small Molecule/Molecular Fragment", and "Atom". A structure agent can be composed of multiple structures of the same prototype or a lower-level prototype, and the agent is connected to its components by the composition relationship in the SN. Thus, a human macrophage has been modeled as a semantic agent of the "Cell" prototype, and it was composed of various "Subcellular Compartment" agents, including plasma membrane, cytosol, nucleus and others. In addition, each compartment such as nucleus contained various agents of the "Macromolecule" prototype including proteins, DNA and RNA. A macromolecule such as a protein was further composed of "Domain/Site" agents like catalytic domains and phosphorylation sites, and a DNA was composed of sites such as promoters and gene regulatory sites. Modeling interactions among biological structures To create an adequate semantic model, we have postulated that structures of different levels in the cellular hierarchy can interact with one another. One example of such interactions is the movement of a molecule from one subcellular compartment (e.g. cytosol) to another (e.g. plasma membrane). This is referred to as a translocation event, and it is demonstrated on the left panel of Figure 2 . Table 2 shows that translocations have been modeled as one the five major "event" prototypes in the SN. Every translocation event has been connected to three structure agents: a molecule to be moved (macromolecule or small molecule), an original location (subcellular compartment), and a destination (subcellular compartment). Hence, the construction of translocation events has enabled us to confine all possible movements of molecules in a cell. Interactions that occur by non-covalent or covalent forces have also been modeled as two distinct "event" prototypes as shown in Table 2 . The right panel of Figure 2 illustrates a general case of a molecular interaction between a protein A and a protein B occurring via non-covalent forces. Such interaction can cause changes of the forms and functions of the interacting molecules, and these changes have been accommodated within the developed SN model by specifying two distinct types of states: "conformational states" and "binding states", also represented by semantic agents. All hypothetical spatial changes occurring in the three-dimensional structure of a given macromolecule have been modeled within the SN as switches in the corresponding conformational states, and the changes do not lead to the creation of new semantic agents. Domains or sites for every protein encoded into the SN model have been assigned to either "Functional" or "Non-functional" conformational states. The "Functional" state represents that a domain/site is currently in a conformation that enables a certain interaction. On the other hand, a "Non-functional" state implies a domain/site is in a conformation that prevents an interaction. To illustrate this construct we have graphed the semantic agents and their relationships created within the developed SN. It should be noted that within the SN, all semantic agents are visualized as icons, and their relationships are depicted as connecting arrows. In addition, all agents are related by pairs of reciprocal relationships, and for simplicity, only one direction of each pair of the relationships was visualized. The left panel of Figure 3 features a p110 subunit of the class I PI3K that has been modeled as a "macromolecule" agent and contains a binging site for a Ras protein and a catalytic domain. The Ras binding site has been assigned a state of "Functional", depicted as a check symbol (square) on Figure 3 . The "Functional" state enables the PI3K-p110 to bind to a Ras protein. On the other hand, the catalytic domain is "Non-functional', depicted as a cross symbol. Figure 8 shows the description of icons used in this paper. In addition to the conformational states, a protein domain or site has been assigned one of the two binding states: "Bound" or "Not-bound". A "Bound" state implies that this domain/site currently associates with a domain/site of another molecule through a non-covalent interaction. On the other hand, a "Not Bound" state indicates such an association does not exist. Since ligand bindings can affect the conformation of a macromolecule through allosteric regulations, two types of such regulations have been implemented within the SN. A positive allosteric regulation event has been assigned to the scenario when a "Bound" binding state of a domain/site causes the conformational state of another domain/site to switch to "Functional". The right panel of Figure 3 shows that when the PI3K-p110 has bound to a Ras by a non-covalent interaction, the binding state of the Ras-binding site on p110 has switched to "Bound". As a result, the conformational state of the catalytic domain has switched to "Functional" due to a positive allosteric regulation. The "Functional" catalytic domain now enables the PI3K-p110 to phosphorylate its substrate. On the other hand, a negative allosteric regulation event has been attributed to those cases when a "Bound" state of a domain/site causes the conformational state of another domain/site to switch to "Non-functional". It should be noted that the semantic model stores the information that specifies the non-covalent event between the prototypic Ras and the prototypic PI3K-p110, and the condition for the event to occur. Figure 3 illustrates an instance of the Ras-binding event occurred during a simulation. The PI3K-p110 is an instance of the PI3K-p110 prototype, and it is the same agent before and after it binds to the Ras. A more complex allosteric regulation event can be specified for mapping the binding states of multiple domains/sites (the condition or the input) to the conformational states of multiple domains/sites (the response or the output). Hence, a domain is switched to "functional" only if a certain combination of ligand bindings has occurred. The utilization of the states on domains/sites and allosteric regulation events in the SN has enabled us to express the cause-effect relationships among various signaling events explicitly. In the developed semantic model, any molecular complex formed due to non-covalent interaction has been treated as a transient state of these two molecules, and a complex was not represented by a new semantic agent. Instead, the existence of a protein complex is inferred from the non-covalent interaction event. Thus, Figure 3 illustrates a protein complex of the PI3K-p110 and the Ras existed because of the occurrence of the non-covalent interaction event, which connected the two molecules. Conventionally, there is often some inconsistency between representing chemical modifications of small molecules in metabolic pathways and modifications of proteins in signaling pathways. In the developed model, two molecules that interacted by covalent forces have resulted the creation of distinct semantic agents within the SN. This rule has been implemented consistently for both macromolecules such as proteins and small molecules such as ATP. As one example, Figure 4 features the phosphorylation of an Akt protein by an enzyme PDK1, yielding a distinct Akt-phosphate (Akt-P) agent and a free ADP. Within the SN, the Akt and the ATP are related to a covalent interaction event by "Substrate" relationships, depicted as arrows. In addition, the Akt-P and the ADP are related to the event by "Product" relationships, while the PDK1 is related by the "Enzyme" relationship. The PDK1 enzyme in this example contains a catalytic domain (not shown on the figure), which must be "functional" for the reaction to occur. The state of this domain is under the regulation of the binding of a ligand and an allosteric event as previously defined. In addition, new properties can be assigned to the modified protein. In this case, the phosphorylation by PDK1 switched the catalytic domain in Akt-P to "functional", while this domain was "non-functional" in Akt, the dephosphorylated form. Figure 4 illustrates that a covalent interaction event also applies to metabolites, and a metabolite such as glucose is phosphorylated into a glucose-6-phosphate by an enzyme Hexokinase. Other types of modifications including methylation, acetylation and glycosylation can also be modeled in a similar manner but involve different substrate types. In the semantic model, a molecule can participate in different sets of interactions in different locations. The translocation events define all possible localizations of molecules, and therefore, an interaction can only occur if the participating molecules can be present in the same location at the same time. Alternatively, an interaction (non-covalent or covalent) can directly associate with a subcellular compartment, and this interaction is only available to molecules in that location. In addition, all qualitative cellular responses such as cell survival and phagosome formation have been implemented within the SN under a distinct "event" prototype. They have been implemented in a way that the formation or the activation of certain signaling molecules such as PIP3 can trigger the occurrence of these cellular response events in a simulation. As it has been mentioned previously, the behavior of any semantic agent can be clearly defined by its relationships or connections to other agents. Thus, the formalization of the five types of events, which are translocations, non-covalent interactions, covalent interactions, allosteric regulations and cellular responses, has enabled us to model the behaviors of molecules depicted in conventional pathways and to reconstruct a cell signaling network of the human macrophage. Case study: a reconstruction of a cell signaling network in the macrophage Data source The molecular composition of human macrophages and information of known intracellular interactions have been extracted from various research articles [ 26 , 27 , 32 , 34 - 47 ], review articles [ 25 , 28 - 31 , 33 , 48 - 52 ] and pathway databases [ 2 , 3 ]. Translation and integration of pathway information into the semantic model A pathway diagram in the literature or an electronic database, in principle, represents some scenario of what may happen in a call if every depicted molecule is expressed in the correct location, at the correct time and with the correct states. Hence, the aggregation of multiple pathway diagrams describes some, if not all, possible molecular events that can potentially occur in a cell under the right conditions. To utilize such information and build a cell signaling network, we have decomposed conventional pathways into individual pieces of information such as subcellular localization of a protein, a pairwise protein binding, a chemical reaction or a cellular response. Then, using the sets of semantic rules described in the model, we have represented and integrated each piece of those information in the form of semantic agents and their relationships. Table 3 illustrates the overall SN model for the cell signaling network contained a total of 93 prototypical macromolecules localized in several subcellular compartments. It included several cell receptors (such as Fcγ, CR3, CD 14, CD18, TLR2) relevant to the process of bacterial internalization of macrophages. Two distinct classes of PI3Ks have been modeled: the class I PI3K composed of p85 regulatory and p110 catalytic subunits, and the class III PI3K composed of p150 and Vps34p subunits [ 28 ]. The model also included various kinases such as Lyn, PDK1 and Akt, small GTPases including Ras, Rac1 and Rab5, and adaptor proteins like Gab2. Events of various prototypes have also been extrapolated from the literature and pathway diagrams. Visualization and analysis of the cell signaling network The defined semantic agents have been connected in the semantic network and can be visualized at different levels. Figure 5 shows one example of how various non-covalent and covalent interactions have been integrated into a unified cell signaling network. The longest path in the cell signaling network we have created contained 24 consecutive molecular interaction events, linking Fcγ receptor to the class I PI3K enzyme and further through class III PI3K to various cellular responses. Such detailed semantic reconstruction of the cell signaling network has allowed thorough investigation of biochemical relationships between essential proteins. One such example is presented on Figure 5 featuring the connections among cell receptors Fcγ and CR3, and tyrosine kinase Lyn which they both activate. It has also been reconstructed by the SN model that both of these receptors can activate the class I PI3K via an adaptor protein, Gab2. The corresponding finding will now be subjected to testing in an experimental lab. Another example of successful SN reconstruction is the relationship between CD14 macrophage receptor and the class I PI3K; such a relationship was previously suspected but not clear [ 39 ]. By incorporating the available literature data [ 35 , 45 ] into the semantic environment we were able to reconstruct the scenario where CD14 activates the class I PI3K by the association of Toll-like receptor 2 (TLR2), as it is illustrated in Figure 5 . Such model will also be tested experimentally. Simulation of changes in the cell signaling network during bacterial invasions In the implemented semantic model, the "possible" behaviors of a molecule are defined through its relationships to other agents (for example a non-covalent event), and all instances of that prototypical molecule will inherit the same behaviors. However, the action of a molecule at any given time is affected by factors including its current states and its current location with respect to other molecules in the system. Hence, we have built an application that enabled us to produce instances of molecules in various locations and to observe the "current" action of a molecule qualitatively under different biological scenarios. We refer such scenario-play as simulation in this paper. The application or the SN-simulator allows the molecules to move among various locations, to interact with each other and to create events when the conditions are met. In addition, every instance of a molecule has been represented as an individual agent while every instance of a molecular interaction has also been implemented as an individual event agent. Thus, the simulator provides a traceable "trajectory" of all the events that have happened on every molecule during a simulation. As illustrated in Figure 6 , the macrophage cell has been generally divided into four subcellular compartments or locations within the simulator. We have specified what molecules to be present initially in each subcellular location in the beginning of a simulation, and the simulator synthesized molecules in each location accordingly. At the very first simulation step, the simulator has created a translocation event moving a molecule (the current target) from one location to another. The initial translocation has been specified as the movement of an IgG molecule from the extracellular space to the plasma membrane as shown in the pathway-viewer on Figure 6 . The occurrence of this initial event allowed the simulator to trigger a search and advanced to the next step. The search looked for other potential molecules (with the correct states) that can interact with the target molecule in the same location. If multiple instances of potentially interacting molecules were present in that location, a single molecule would be randomly selected to interact with the target. Because an Fcγ receptor was the only interacting molecule (for the IgG) present at plasma membrane in the simulation, it has bound to the IgG by a non-covalent interaction event, as illustrated in Figure 7 . This non-covalent interaction has switched the state of the Fcγ receptor's binding site for a Lyn kinase to "Functional", and thus it enabled the Fcγ receptor to bind to a Lyn. However, the Lyn was not initially present in plasma membrane, but it was localized in cytosol in the beginning of the simulation, as shown in Figure 6 . Thus, when the Lyn has been translocated from the cytosol to the plasma membrane, a non-covalent interaction between the Lyn and the "Functional" Fcγ receptor occurred in the following step as shown in Figure 7 . The search was iterated and the simulation continued until all interacting molecules have been depleted in the macrophage. Figure 7 demonstrates the consecutive events in this simulation scenario where the Lyn protein phosphorylated a Gab2, which then bound to a class I PI3K. When activated, the PI3K phosphorylated a PIP2 into a PIP3, which in turn caused a phagosome formation response. Different setups of the initial localization of molecules have affected the outcome of the simulation. For instance, an initial presence of a Rab5 (a downstream protein of the PIP3) and a class III PI3K in the cytosol extended the previous pathway from the PIP3. This localization setup stimulated a PIP3-mediated activation of the class III PI3K, which led to phagosome maturation response in the simulation. However, if a phosphatidylinositol analog, ManLAM, of M. tuberculosis was initially present in the plasma membrane, it would inhibit the class III PI3K and thus arrest the phagosome maturation response in the macrophage. Table 4 shows that the activation of PI3Ks-mediated pathways by M. tuberculosis has caused several known cellular responses as well as additional responses such as cell survival of the macrophage, cell cycle entry, increase of protein synthesis and increase of intracellular glucose level in the simulation. We suspect that some of these responses have not yet be appreciated in previous studies of bacterial invasions. Further experiments can be formalized to test the simulation results. In this study, the SN-simulator has enabled us to "play" different scenarios and observed their effects in the macrophage. It allowed us to investigate how changes on one molecule caused changes of another molecule in the cell signaling network during bacterial invasions. Discussion Features of the semantic model In the present work we have developed a semantic model to represent the properties and the behaviors of molecules and their interactions in the context of cell signaling pathways. The proposed model offers some additional features, compared to other existing pathway models. Those features are essential for characterizing the complex behaviors of biological entities, and they include: Specify the spatial organization of molecules The semantic model has specified the hierarchical relationships among the different biological structures, from cells to compartments, molecules and domains/sites. The hierarchy between subcellular compartments and molecules has allowed us to specify the spatial organization of molecules, model the translocation events and represent the effects of locations on the different interactions among molecules. Model proteins as integrating and logical devices The hierarchy between molecules and their domains/sites has enabled us to explicitly model the relationship between forms and functions for proteins. Through the allosteric regulation events, proteins have been modeled and implemented as integrating and logical devices in the semantic network, and their conformational states (outputs) are switched by the combination of non-covalent ligand bindings or covalent modifications (inputs). Provide a direct communication from models to simulations Through the prototyping system in the semantic network, any rule or interaction specified on a prototypical molecule automatically define the properties and behaviors of all its instances. As demonstrated by the simulator, the semantic network provided a direct communication from the interaction model to an application where the actions of molecules can be observed under different scenarios. Therefore, the semantic network is dynamic as a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system. Reduce the need for labels In addition, the current semantic model is different from the previous models in BioCAD. An essential difference is the representation of functional labels or roles on proteins. The meanings of functional descriptions or association words such as "enzyme", "activator/activates" or "inhibitor/inhibits", which are often used to characterize the behaviors of proteins in most pathway models, have been represented explicitly through events and relationships in the developed semantic network. For example, a protein acts as an "enzyme" if 1) the protein participates in a "covalent interaction event", 2) the presence of a "functional" catalytic domain on the protein is required for the occurrence of the event, and 3) the protein itself is not modified after the event. Similarly, a protein A "activates" a protein B if a non-covalent binding event from protein A turns on the "functional" state of a domain/site on protein B. Hence, the model has reduced the need for labels, which are often confusing or misleading on conventional pathway representation. Future directions The use of non-covalent and covalent events has enabled us to model protein-protein interactions and chemical modifications on molecules including proteins and metabolites. The next challenge is to model the complex interactions that govern gene regulations. The current construction of non-covalent interaction events can model the binding of an individual transcription factor to a particular site of a gene, and the covalent interaction event can represent the transcription process that leads to the production of an mRNA, and the translation process that produces a protein. However, a successful transcription in a eukaryotic cell requires the formation of a protein complex that involves more than one hundred subunits, and the complex may be assembled in various orders [ 53 ]. We anticipate the improvement of the current allosteric regulation model to characterize the more complex logic in gene regulation. The semantic network representation can be exploited for performing analysis of cell signaling pathways. The examples of Fcγ receptor, CR and the class I PI3K demonstrated that connections can be queried and analyzed among different biological entities. The semantic model is also compatible with other pathway models. Therefore, the number of biological entities and interactions in the semantic network can be greatly increased as pathway data from existing databases is integrated. Previous study has shown the value of combining gene expression profiles with protein-protein interaction networks for identifying active subnetworks [ 54 ]. Similarly, data from gene and protein expression experiments could be integrated with the semantic network for "pathway filtering". For instance, within a particular cell, there could be multiple paths that connect two proteins, while each path consists of different number of nodes. When the cell receives a signal, the shortest path, the one with the least number of nodes that require activation, is more likely to be "walked" than a longer path. Hence, the gene/protein expression data will provide some estimation of an overall protein expression and activation states to identify "active" pathways in a cell under a given condition In this study, the proposed semantic model has been applied to cell signaling pathways in the macrophage as a case study. The model is not limited to those pathways. The hierarchical classification of the biological structures and the events can model other cell signaling pathways for different cells and organisms. An interactive website is currently under development. We anticipate that through the web, researchers can utilize the semantic network approach for creating pathways in cells of their interest and for analyzing any existing pathways including the PI3K pathways of the human macrophage presented in the paper. The current capability and applicability of the SN simulator In this study, we have developed a simple simulator to demonstrate the dynamics of the semantic network and to observe the actions of molecules qualitatively. In order to perform a realistic cellular simulation in the future, three components need to be improved. First, quantitative factors should be integrated into the model. For example binding affinity, directly associated with non-covalent events, will affect the probability and the duration of the binding of molecules. Reaction kinetics, associated with covalent events, will determine the rate of production. Second, the two parameters, the population of molecules and their localization, which influence the simulation outcome, could be initialized and supported by experimental data. For instance, gene expression data from microarrays supports the relative abundance of transcripts, and protein expression data supports the relative abundance of proteins. Computer algorithms such as PSORT [ 55 ] can assist in predicting the localization of proteins. Third, the proximity of molecules has been represented by subcellular compartments in the simulation. This approximation can be improved in two different ways. First, a compartment can be further divided into smaller sub-locations. Increasing the number of locations and reducing the size of each location will improve the accuracy of the simulation. Second, the occurrence of non-covalent events in the simulation has allowed us to identify molecular complexes and their members effectively. Hence, the proximity can be approximated through molecular complexes, such that molecules in a complex have higher probability to interact with members of the same complex. The simulator has demonstrated that a biological pathway can emerge from the creation of semantic agents and their relationships in the SN, and such a pathway represents a series of consecutive events resulting from the activation of a single molecule. It is anticipated that further development will improve our ability to track and visualize different instances of molecules participated in multiple pathways. Hence, the occurrence of a cellular response event can be triggered by the accumulation of certain molecular species with particular states. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. Utilizing the semantic agents and the relationships in the model, information on biological structures and their interactions at different levels has been properly represented and integrated in the hierarchical and spatial context. The reconstruction of the cell signaling network in the macrophage has allowed qualitative investigation of connections among various essential molecules and reflected the cause-effect relationships among the events. The simulation demonstrated the dynamics of the semantic network, where actions of molecules are affected by their current states and locations, and the history of events can be traced and analyzed. In addition, changes caused by the invading M. tuberculosis in the macrophage were investigated by the simulator. As a result, the simulation identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions. Methods The Visual Knowledge environment Visual Knowledge (VK) is an application development environment, and its implementation has been influenced by the theory of semantic networks as well as other approaches including set theory, frame system, object-oriented modeling theory and systems based on networks of active software agents [ 23 ]. Different from other passive knowledge representation technology, VK is dynamic and scalable, and it is capable of active representation and integration of different domain knowledge. By manipulating a number of fundamental classes of semantic agents like "physical thing", "event" and "trigger", models of various complexity can be constructed with VK. In addition, VK allows the creation of "prototypes" within each basic class of agents, and therefore it enables any classification of agents based on their common characteristics and behaviors. The BioCAD software BioCAD, a Visual Knowledge-based development environment, is developed by Upstream Biosciences, Inc. and customized to model biological systems [ 24 ]. The BioCAD software provides tools for managing large-scale biological data and for visualizing and editing biological pathways and networks. BioCAD currently contains millions of biological concepts and hundreds of pathways that have been integrated and curated from publicly available data sources. A locally installed client program allows semantic agents to be created, stored and queried from a remote central server. The BioCAD software is available commercially, and a collaborative modeling server will be publicly accessible soon. Authors' contributions The semantic model was developed jointly by all authors and implemented by MH, JLB and CS. MH implemented the simulation, collected and analyzed data, constructed pathways in the macrophage and drafted the manuscript. JLB, CS, AC developed general concepts, provided scientific support, participated in the manuscript writing and coordinated the study. All authors read and approved the final version of the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC528732.xml |
546216 | Structural equation model testing and the quality of natural killer cell activity measurements | Background Browne et al. [Browne, MacCallum, Kim, Andersen, Glaser: When fit indices and residuals are incompatible. Psychol Methods 2002] employed a structural equation model of measurements of target cell lysing by natural killer cells as an example purportedly demonstrating that small but statistically significant ill model fit can be dismissed as "negligible from a practical point of view". Methods Reanalysis of the natural killer cell data reveals that the supposedly negligible ill fit obscured important, systematic, and substantial causal misspecifications. Results A clean-fitting structural equation model indicates that measurements employing higher natural-killer-cell to target-cell ratios are more strongly influenced by a progressively intrusive factor, whether or not the natural killer cell activity is activated by recombinant interferon γ (rIFN γ). The progressive influence may reflect independent rate limiting steps in cell recognition and attachment, spatial competition for cell attachment points, or the simultaneous lysings of single target cells by multiple natural killer cells. Conclusions If the progressively influential factor is ultimately identified as a mere procedural impediment, the substantive conclusion will be that measurements of natural killer cell activity made at lower effector to target ratios are more valid. Alternatively, if the individual variations in the progressively influential factor are modifiable, this may presage a new therapeutic route to enhancing natural killer cell activity. The methodological conclusion is that, when using structural equation models, researchers should attend to significant model ill fit even if the degree of covariance ill fit is small, because small covariance residuals do not imply that the underlying model misspecifications are correspondingly small or inconsequential. | Background Browne, MacCallum, Kim, Andersen and Glaser [ 1 ] employed a measurement model of natural killer cell lysis as an example of testing structural equation models. Their model failed to fit the data, though the authors judged the degree of covariance ill fit to be "negligible from a practical point of view"[ 1 ]. One of us (Hayduk) was engaged in a SEMNET [ 2 ] discussion of model fit testing, and objected to the close-yet-failing structural equation model being described as adequate. We re-examined the relevant measurement procedures and subsequently located a cleanly fitting model which provided evidence of important systematic effects coordinated with the effector to target ratios used during the measurement of natural killer (NK) cell activity. This article summarises the Browne et al. [ 1 ] data, discusses the clean-fitting model, and investigates alternative models in an attempt to better characterise the factor that produces the progressive measurement interference. Methods The immune system measurements Browne et al. [ 1 ] analysed the correlation matrix for eight measures of immune system function of 72 females with breast cancer, recorded during investigation of the physiological consequences of a psychological intervention [ 3 , 4 ]. Four 51 Cr-release measures of natural killer cell lysis were obtained using effector (NK cell) to target cell (K562 human myeloid cell) ratios of 100:1, 50:1, 25:1 and 12.5:1. Following Browne et al. [ 1 ] we designate these measures by their effector to target (E:T) ratios, NK100, NK50, NK25 and NK12 respectively. Similarly, natural killer cell lysis measured in the presence of recombinant interferon gamma (rIFNγ) using E:T ratios of 50:1, 25:1, 12.5:1 and 6.25:1, are designated IFN50, IFN25, IFN12, and IFN6 respectively. Lower E:T ratios are used in the presence of rIFNγ because rIFNγ increases NK cells' ability to rupture target cells. The correlations reported in Browne et al.'s [ 1 ] Table 1 indicate that the four NK measures correlate highly with one another (average r = 0.852), and that the four rIFNγ enhanced NK measures also correlate highly with one another (averaging 0.960). However, the low correlations between the sets of NK and rIFNγ measurements (averaging only .111) indicate that the two sets of measurements reflect relatively distinct aspects of natural killer cell functioning. Browne et al. [ 1 ] viewed this as justifying the use of an exploratory two-factor model (Figure 1 ) which, unfortunately, was significantly inconsistent with the data (χ 2 = 103.59, degrees of freedom ( df ) = 13, and probability p < 10 -15 ). The small but significant residual differences between the data correlations and the correlations implied by the two-factor model were dismissed by Browne et al.[ 1 ] as "negligible from a practical point of view". SEMNET discussion of this model prompted Hayduk to investigate whether some unrecognized measurement feature was producing the significant, even if seemingly slight, ill fit. Table 1 Maximum likelihood estimates for the Browne et al [1] two-factor, and the progressive impact, models Browne et al.[1] Model ++ Progress ive Impact Model NK Activity Factor IFN Activity Factor Indicator R 2+++ NK Activity Factor IFN Activity Factor NK Progressive Factor IFN Progressive Factor Indicator R 2 Proportion of indicator variance explained by NK Activity Factor Proportion of indicator variance explained by IFN Activity Factor NK100 .842 .003 .709 .705** -- -80.1** -- .958 .50 -- NK50 .936 -.005 .876 .851** -- -50.0+ -- .918 .72 -- NK25 .943 .015 .892 .920** -- -25.0+ -- .874 .85 -- NK12 .964 -.013 .927 .922** -- -12.5+ -- .995 .98 -- IFN50 .030 .942 .893 -- .897** -- -50.0+ .972 -- .80 IFN25 -.019 .996 .988 -- .977** -- -25.0+ .996 -- .95 IFN12 .005 .995 .990 -- .988** -- -12.5+ .988 -- .98 IFN6 -.018 .991 .977 -- .944** -- -6.25+ .990 -- .99 Factor Variance 1.0+ 1.0+ 1.0+ 1.0+ .000069 § ** .000069 § ** + a fixed coefficient * beyond 2 standard errors ** beyond 3 standard errors § constrained to be equal ++ Identifying Browne et al's [1] exploratory two-factor model requires excluding one indicator from loading on each factor. Repeated emails to both Browne and MacCallum were unable to elicit a statement of precisely which two loadings had been set to zero. There are 16 different ways of excluding one IFN indicator from loading on the NK activity factor and simultaneously excluding one NK indicator from the INF activity factor (see dashed loadings in Figure 1). The loadings in column 1 and 2 are the average of the estimated loadings calculated across these 16 exclusion possibilities. Each of the 16 models provided a χ 2 = 103.8, df = 13, p = 0.000, with the slight difference from the reported fit being easily attributed to the three figure accuracy of the correlations published in Browne et al.[1]. +++ These values are for the version of the Browne et al. [1] model that excludes the effects leading from the NK latent to IFN6 and from the IFN latent to NK100 for identification of the model. Figure 1 The Browne, MacCallum, Kim, Andersen and Glaser (2002) two-factor model The dashed arrows correspond to weak effects. Statistical identification of the model's coefficients requires exclusion of one dashed arrow from each factor as explained in Table 1. Andersen, Farrar, Golden-Kreutz, Kutz, MacCallum, Courtney & Glaser [ 3 ] provide a description of the reasonably standard procedures used to obtain the Browne et al. [ 1 ] data. Peripheral blood leukocytes (PBLs) were obtained from 60 mL of venous blood, counted so that a known number of PBLs could be suspended in medium and incubated with either additional medium or additional medium plus rIFNγ. K562 target cells (a human myeloid cell line sensitive to NK cell activity) were labelled with 51 Cr and aliquoted with the effector cells (either the NK, or the rIFNγ activated NK cells) in the ratios reported above. The cell mixture was centrifuged to ensure cell surface contact, and incubated to provide an opportunity for the NK cells to bind and rupture the target cells, thereby releasing the radioactive target cell cytoplasm. Gamma radioactivity of the supernatant collected from a second centrifuging indicated the effectiveness of the NK or rIFNγ-activated-NK cells at lysing the target cells, with larger measurements corresponding to more effective NK cell activity. An alternative model Browne et al. [ 1 ] modelled the measurements made at the various E:T ratios as replicate measurements. Hayduk suspected that the progressively varying E:T ratios might have introduced systematic measurement interference. Higher E:T ratio measurements might result in systematically less NK cell effectiveness, not because of differential NK activity but because of some progressive complication subsumed within the measuring procedures. For example, higher E:T ratios might decrease the ability of NK cells to contact and lyse target cells due to competition for cell surface contact area. Or multiple NK (or other leukocyte) cells might block some NK cells from attaining sufficient surface contact with the K562 cells, and thereby render them seemingly ineffective – not due to lack of potency, but as a result of competition for surface contact. Alternatively, the lysing of a single target cell by multiple attached NK cells, which becomes more likely at higher E:T ratios, might make the NK cells appear comparatively ineffective on a "per cell" basis. The amount of target cell cytoplasm released per effector cell would be disproportionately small because multiple NK cells might have to "share the credit" for participating in lysing a single target cell, and not because of lower NK cell effectiveness. Competition for attachment sites, and multiple simultaneous NK attacks on single targets, would increase as the effector NK cells more radically outnumbered target cells, and hence should be more pronounced at higher E:T ratios. These considerations led to the model of E:T-progressive interference depicted in Figure 2 . This model postulates two latent factors, paralleling the factors in the Browne et al. [ 1 ] model (an NK activity factor causing the NK indicators' values, and an rIFNγ activity factor causing the IFN indicators' values), plus two progressively interfering factors (one spanning the NK indicators, the other spanning the IFN indicators). The effects of the interfering factors are progressive in proportion to the E:T cell ratios, and negative because we anticipated progressive reduction in the per-cell radioactivity readings, as discussed above. The negative signs are purely for ease of expression, since progressive positive values result in an equivalent model that merely interchanges the high and low ends of the underlying factor's scale. One progressive factor is postulated as acting within each measurement series, and these factors are postulated as being independent of one another, and also independent of the true scores on the NK and rIFNγ-enhanced activity factors. The variances of the two methods factors were constrained to be equal because the procedural similarity in the measurement series initially led us to suspect that routine within-series laboratory variations might propagate proportionally. We originally saw no reason to anticipate that rIFNγ would alter the mechanisms initially postulated as providing the progressive interference. Later consideration of multiple potential mechanisms led us to investigate the possibility of variance differences, as reported below. Figure 2 The model with progressively influential factors Results This model contains 18 estimates: four loadings of the NK indicators on the NK activity factor, four loadings of the IFN indicators on the rIFNγ activity factor, the correlation between the two activity factors (whose variances are fixed at 1.0), eight measurement error variances (one per indicator), and the single variance applied or assigned to both the separate interfering factors. This model fits, but a negative measurement error variance estimate for NK100 suggested a ceiling had been reached for the largest E:T ratio. Freeing the loading for the NK100 indicator results in clean fit (χ 2 = 11.97, df = 17, p = 0.802) and an estimate of -80.1, rather than a strictly proportional value of -100. The alternative of constraining the offending measurement error variance to be non-negative while maintaining the -100.0 loading, also results in a fitting model (χ 2 = 14.72, df = 18, p = 0.681) having very similar estimates, so whether the interfering effects are "nearly proportional" or "strictly proportional" is equivocal. The progressive and nearly-proportional model (see Figure 3 for program details) provides the estimates in Table 1 . The clean fit of this model convinces us that something is indeed interfering with the NK cell activity measurements, and "that something" is acting progressively and nearly in proportion to the E:T ratios. Figure 3 LISREL (Joreskog and Sorbom [6]) program syntax for the Figure 2 progressive factors model Further characterising the interfering entity Additional models were estimated in attempts to further characterize the entity providing the progressive interference. The lowest inter-item correlations, and the greatest ill-fit of the Browne et al. [ 1 ] model, appeared for the NK measurements, so we checked whether a single methods factor spanning only the NK measures would be consistent with the data. This model is similar to Figure 2 model, except that the progressive methods factor spanning the IFN measures is eliminated. This model fails significantly (χ 2 = 62.5, df = 17, p < 0.001) and thereby informs us that even the seemingly cleaner IFN measurements are influenced by some progressively interfering factor. Are two similar, yet separate, factors required for the NK and IFN measurement series, or might it be possible that one E:T-coordinated progressive factor spans all eight measurements? That is, could the progressive interfering factor be something common to an individual, rather than something set for each individual once within the NK measurement series and reset independently (or be some other interference) within the IFN measurement series? To check this, we specified a model having a single progressive methods factor leading to all eight indicators. The same E:T ratio dictated loadings were used, and the NK100 loading freed. This model also fails convincingly (χ 2 = 75.5, df = 17, p < 0.001) and thereby speaks against the progressive entity being something connected to each case as a whole. That is, no single feature common to the full set of measurements (e.g. the time of blood sampling, or the person's age, or their cancer progression, or mistaken cell counts), could be progressively applied across both measurement series to account for the data. Such factors might constitute the entity spanning the items within one series, but the other measurement series would have to be progressively influenced by something else. Together, these two failing models require that the entities providing the progressive interference are features connected exclusively to either the NK series or the IFN measurement series, or are something that is set independently within each of the NK and IFN measurement series for any given case. We next attempted to check the requirement for equal progressive-factor variance incorporated in the Figure 2 model. Attempting to estimate a separate variance for each progressive factor resulted in signs of under-identification, and hence these data should be heard as being consistent with, but not necessarily as requiring, equal variances for the progressively interfering factors. In response to the comments of Reviewer-2 (Professor Mulaik), we attempted to check whether the progressive methods factors were necessarily independent of the corresponding true NK activity factors, by freeing the corresponding covariances (which were constrained to be equal). This also resulted in signs of underidentification. Hence these data should be heard as being consistent with, but not necessarily as demanding, the independence of the methods factors from the corresponding true NK activity factors. Forcing even a modest correlation between true NK activity and progressive methods factors results in substantial suppression of effects, and standardized effects exceeding 1.0 – which is not "impossible" but which would certainly "confront" anyone inclined to postulate a coordination between true NK activity and the progressive methods factors on substantive rather than "exploratory-statistical" grounds. It might be tempting to interpret these underidentified models as signs of insufficient power due to the rather small N of 72 provided by Browne et al. [ 1 ] but we think it would be more reasonable to see these underidentified models as artifacts of the limited variety of variables in the Browne et al. [ 1 ] data. The N of 72 provided sufficient power to speak strongly against the Browne et al. model, and sufficient power to speak strongly against several of the alternative models we considered above. The models that became underidentified did so largely because the structure of these models resulted in the freed coefficients having no unique (freed-coefficient dependent) implications which could potentially be found to be more/ less consistent with the data. Anyone wishing to investigate the ideas contained in the underidentified models would be better advised to add a wider variety of variables into their data and model structure, rather than merely increasing N while maintaining the current style of measurements and models. The parameter estimates We have basically two sets of estimates to consider: the estimates for the failing Browne et al. [ 1 ] two-factor model (Figure 1 , and Table 1 columns 1, 2, and 3), and the estimates for the fitting progressive measurement interference model (Figure 2 , and Table 1 columns 4 through 10). The loadings of the measures on the NK-activity and IFN-activity factors, namely the estimated effects of "true" NK-activity and "true" IFN-activity on their respective sets of four measures, differ importantly between these models. The Browne et al. [ 1 ] estimates are relatively uniform and large, in contrast to the loadings for our fitting model which display a definite progression from smaller to larger loadings as one moves from higher to lower E:T ratio measurements. It is no coincidence that the weakest loading estimates appear where the progressive interference is the greatest, namely for the highest E:T ratio measurements. As more variance in a measure is accounted for by the progressively interfering factor, less variance is left to be accounted for by the true NK or IFN activity factor. According to the fitting progressive model, only about half the variance in the NK100 indicator arises from true variability in NK activity, while the "other half" of the variance arrives primarily from the progressive methodological factor, with a minimal amount of error variance contributed by features unique to the NK100 measurement. Given that the latent variables have variance 1.0, the variance the NK activity factor contributes to an NK indicator can be calculated as the square of the appropriate loading. The Browne et al. [ 1 ] model, therefore, claims true NK activity contributes .71, .88, .89 and .93 to the variance in NK100, NK50, NK25 and NK12 respectively. In contrast, squaring the effects leading from our NK activity factor to the indicators provides values of .50, .72, .85 and .98. These values make it clear that Browne et al.'s [ 1 ] overlooking of the progressive methodological interference results in their model claiming that too large a portion of the variance in the high E:T ratio measures arises from true NK activity, while too small a portion of the variance in the lowest E:T ratio measure arises from true NK activity. (A similar, but less pronounced, pattern appears if corresponding calculations are made for the contribution of IFN activity to the IFN indicators.) That is, the bias in the Browne et al. [ 1 ] estimates systematically obscures the substantial and progressively stronger measurement of true NK activity by the lower E:T ratio measurements, whether viewed from the perspective of the estimates themselves or the variance accounted for by those estimates. The squared multiple correlation coefficient R 2 (column 3 of Table 1 ) is usually interpreted as a "proportion of explained variance" but the above observations require that we reconsider this for the Browne et al. model. The Browne et al. model fails to fit with the data, and hence confronts evidence of causal misspecification, and it also confronts evidence of bias in its estimates. Is it reasonable to claim that a misspecified model containing biased estimates "explains" or "accounts for" variance in the indicators? Even biased estimates can be put through the mathematical formula providing model-implied variances and R 2 (see Hayduk [ 5 ] pages 106–116, 184; and notice that the first four entries in column 3 correspond closely to the model-implied variance contributions reported in the preceding paragraph), but can mathematically-clean manipulations of biased, non-world-matching, coefficients be reasonably described as providing an "account of" or an "explanation for" indicator variances? That is, if biased estimates from a wrongly specified model are put through the perfectly-adequate mathematics providing variance implications, are the resultant variances "explained" or "accounted for"? Our view is that claims to "explaining variance" and "accounting-for variance" are rendered unconvincing if there is evidence indicating the model that supposedly provides the "explanation or account" fails to correspond to a proper representation of the external world. Hence, we view the R 2 values in column 3 of Table 1 as properly calculated, yet fundamentally dubious, because the calculations are based on biased estimates from a misspecified model. These R 2 values constitute "dubiously explained or accounted-for proportions" of indicator variances. Our Figure 2 model does not confront evidence of misspecification, and hence it would seem that the R 2 values in column 8 of Table 1 could be more comfortably described as proportions of explained variance. But these R 2 values have a different kind of uncertainty attached to them because the identity of the progressive latent variable is currently unascertained, as we discuss in the next section. The final two columns of Table 1 provide the proportions of variance in the indicators that are most confidently "explained" because these values come from a model that fits the data, and report the proportions of variance originating in latent variables whose identity is most confidently known. Let us next consider the loading estimates from the perspective of the correlations between two pairs of indicators, specifically the correlation between the NK100 and NK50 measurements (0.902) and the correlation between NK25 and NK12 (0.930). The Figure 2 model accounts for the 0.902 NK100-NK50 correlation via the action of two common causes: the true NK activity factor which contributes (0.705)(0.851)(1.0) (namely, the product of two loadings and the variance of the relevant common factor; Hayduk [ 5 ] pages 26, 106), and the progressively interfering factor which contributes (-80.1)(-50.)(0.0000695), for an overall correlation of 0.600 + 0.278 = 0.878 (with the remaining 0.023 residual being within the range of sampling fluctuations). The 0.930 NK25-NK12 correlation is similarly accounted for by a true NK activity contribution (0.920)(0.992)(1.0) and a progressive methods factor contribution (-25.)(-12.5)(0.0000695), for a total of 0.912 + 0.022 = 0.934 (which leaves a residual of -0.004). Notice that while the correlations are not radically different (0.902 vs 0.930) the contribution to the correlation provided by the causal actions of true NK activity differ substantially (0.600 versus 0.912). A substantial portion of the correlation between the NK100 and NK50 measurements is being provided by the progressively interfering factor, and when this is taken into account, there is a substantial reduction in the degree of coordination that can be attributed to both these measures causally responding to true NK activity. This is the classic distinction between reliability and validity. The NK100 and NK50 measures seem to possess substantial reliability (the basic 0.902 correlation) but much less validity since a substantial portion of the stability, or inter-measure reliability, is arising from a stable, and in this instance progressively-influential interfering entity. The small variance estimate for the progressively interfering factor (0.0000695) is partially an artifact of the large absolute values used in setting the proportional methods effects (-100, -50, -25, etc.). If each of these effects is rescaled by dividing by 100, the effects become -1.0, -0.5, -0.25, -0.125 for NK and -0.5, -0.25, -0.125 and -0.0625 for IFN, and the proportionality of the effects is preserved but the estimated variance of the progressive factor is increased 100 2 fold, to 0.695, while the other estimates remain unchanged. One additional model estimate is worth noting. The Figure 2 model permits a correlation between the NK and IFN activity factors, but the corresponding estimate is small (0.090) and insignificant. The insignificance of this correlation implies that it is reasonable to view all four of the factors in Figure 2 as being basically independent of one another. Two independent entities account for the NK measurements while two additional entities that are independent of one another and also independent of the NK-measurement-producing entities account for the IFN measurements. What is producing the progressive interference? Let us first consider features capable of producing progressive interference within each series. Multiple simultaneous lysings of a single target cell provide several possibilities. With higher E:T ratios it becomes progressively more likely that any given target cell will be simultaneously attacked by more than one NK cell. The 51 Cr "credit" for having lysed a target cell will be shared among the multiple attacking NK cells, and hence will reduce the seeming per-NK-cell effectiveness of the NK cells. Individual differences in the mechanisms of cell recognition, strength of attachment, delay in NK cytoplasmic reorganization, or energy supply, which are separate from whatever rate-limit constitutes "true NK cell activity", could provide individual differences constituting the variance in the "progressive factor". From this perspective, the independent progressive factor within the rIFNγ series might constitute a rIFNγ induced switch to a different rate-limiting component associated with multiple NK lethal attachments. Alternatively, the progressive interference might arise from the blocking of some effector NK cells by physical presence of scrimmage-line NK or lymphocyte cells. If an NK cell is obstructed or delayed in making contact with a target cell by: a) the physical obstruction created by other cells between this NK cell and the target, or b) the NK cell wasting time discovering that the adhered cell is merely another NK or lymphocyte cell rather than a valid target, this progressively reduces the apparent 51 Cr-producing effectiveness of that cell – again a phenomena which should coordinate with the E:T ratio. The "multiple simultaneous attacks" and "blocking" scenarios might be supplemented by individual differences in the ability of NK cells to lyse multiple sequential targets. At higher E:T ratios fewer pristine targets are available and hence fewer NK cells have the opportunity to deliver second-lethal-doses, or may end up sharing their second-dose credits. Or, if lethal doses from multiple NK cells reduce the time to ion-gradient-induced cell membrane rupture, multiple-simultaneous-NK activity might instantiate the positive-valued model reported above. Yet other possibilities arise from NKT-cells and T-cell suppression of NK cells. At higher E:T ratios, there may be greater suppression of NK cells by higher concentrations of suppressor chemical signals. Similarly, NKT-cells may become progressively activated or deactivated by E:T-concentration-dependent signals from other T cells in the medium. If an individual's NK cells are not uniformly active, but rather display a within-individual gradient of activity (some NK cells being more active than others), and if this gradient is set independently of the features underlying "true NK activity" this would provide another form of explanation. Yet another possibility arises from the uptake of 51 Cr by NK cells or other lymphocytes following its release from lysed target cells. At higher E:T ratios more cells are present to re-uptake 51 Cr released from lysed target cells, and hence less 51 Cr will appear in the centrifuged supernatant. Clearly, there are multiple possibilities for what might be providing the E:T ratio coordinated variations in lysing ability, and any independent pairing of these possibilities potentially constitute the interference in the NK and IFN measurement series. Discussion and Conclusions This study was prompted by fortuitous use of NK cell activity measurements in a debate over the testing of structural equation models. According to Browne et al. [ 1 ], even though the two-factor model of NK and rIFNγ activity they proposed (Figure 1 ) was significantly at odds with their correlation data, the residual differences were small enough to be "negligible from a practical point of view". Our view was that the small size of the correlation residuals did not imply that the reason for the ill fit was correspondingly small or unimportant, and this prompted our reexamination of what might be producing the ill fit. These reconsiderations led to the Figure 2 model in which the measurements reflect both the "true" degree of NK or rIFNγ induced NK cell activity along with the influences of features that progressively impact these measurements in proportion to the E:T ratios. Introducing a progressive, and nearly proportional, interfering factor within each measurement series resulted in a cleanly fitting model whose residuals are small enough to be easily attributable to chance sampling fluctuations, and whose estimates imply that true NK or rIFNγ-induced activity is most accurately measured at low E:T ratios. The impact of the progressively interfering feature is sufficiently pronounced that at the highest E:T ratio of 100 only half of the variance in the NK measurement can be attributed to "true" NK activity. The "other half" of the variance in this measurement seems to arise primarily from the progressive factor. Thus the small residuals of the Browne et al. [ 1 ] model seem to have obscured major influences in the data. Consideration of the methodology underlying the NK and rIFNγ measurements locates several possible identities for the progressively effective feature, including multiple simultaneous lysings, cell occlusion or blockage, within-individual NK activity gradients, and 51 Cr reuptake. One important consequence of the fitting model is that it provides evidence indicating the lowest E:T measures provide the most valid measures of NK and rIFNγ induced lysing activity. The NK or rIFNγ measurements made at higher E:T ratios correlate highly with one another, but a substantial portion of these correlations appears to result from the progressive interfering factor and not "true" NK and rIFNγ activity. The higher E:T ratio measures remain reliable in the sense of being stable, but they are not as valid as measurements of "true" lysing activity. Given that nearly half the variance in the NK100 measurements is connected to the progressive factor, we have encountered something that is substantial and probably routinely noticed in practice, and is just being mislabeled or overlooked. A second important consequence of the Figure 2 model is that it suggests that there may exist some "third-causal-source" of lysing ability. If we think of natural lysing ability as a first source, and rIFNγ activation as a second source of lysing ability, the progressive factor may constitute a third and independent causal source. That is, just as rIFNγ-induced NK cell activity can therapeutically supplement NK activity, whatever constitutes the progressive factor may also be able to therapeutically supplement both the NK and rIFNγ-induced activities. If the interfering factors turn out to be something like blocking of access to the target cells by other cell bodies, this will be viewed as merely "the reason" lower E:T ratios provide more trustworthy measurements. But if the interfering factor turns out to be something connected to a chemical concentration (e.g. magnesium stores) then this could constitute a potential third and independent causal route to therapeutic enhancement of killer cell activity. The fact that the progressive factors are tightly connected to E:T ratios makes differential NK activity at various E:T ratios an obvious point of investigative departure. The fact that one of the progressive factors contributes about half the variance in the highest E:T ratio NK measurements implies we are not confronting issues at the limits of measurement, but rather are confronting issues of measurement confounding. Incorporating measures of variables connected to the "candidate explanations" in an expanded version of Figure 2 could effectively screen the explanatory options. Competing interests The author(s) declare that they have no competing interests. Authors' contributions LAH developed and ran the structural equation models, and prepared multiple drafts of the manuscript. HPR discussed, and suggested changes to, the various manuscript drafts; prepared the figures, and arranged for consultation with outside experts. GGC discussed, and suggested changes to, the various drafts; and arranged for consultation with outside experts. MJDL discussed, and suggested changes to, the various drafts; and prepared the table. MAB discussed, and suggested changes to, the nearly final manuscript drafts. All the authors read and approved the final version of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546216.xml |
545051 | The risk of hemorrhagic complications in hospital in-patients who fall while receiving antithrombotic therapy | Background The use of antithrombotic agents and falls are independently associated with an increased risk of hemorrhagic injury. However, few studies have delineated the risk of fall-related hemorrhagic complications in persons who are taking antithrombotic therapy. The objective of this study was to compare the rates of fall-related hemorrhagic injury in hospital in-patients who are taking and not taking antithrombotic therapy. Methods A 4-year retrospective chart review of consecutive patients who fell during admission to a 500-bed tertiary-care teaching hospital was conducted. Major hemorrhagic injuries including subdural hematomas and major bleeding/cuts, patients' use of antithrombotic medication (warfarin, aspirin, clopidogrel and heparin) and their anticoagulation status at the time of their fall were recorded. Results A total of 2635 falls in 1861 patients were reviewed. Approximately 10% of falls caused major hemorrhagic injury. One fall resulted in a subdural hematoma. Persons taking warfarin were less likely to suffer a fall-related major hemorrhagic injury compared with persons not taking antithrombotic therapy (warfarin, 6%; no therapy, 11%; p = 0.01). Logistic regression showed that fall-related major hemorrhagic injury was associated with female gender (odds ratio 1.6; 95% CI 1.3, 2.1), use of aspirin (odds ratio 1.4; 95% CI 1.1, 1.8) and use of clopidogrel (odds ratio 2.2; 95% CI 1.1, 4.8), but not with the use of warfarin or heparin, or the intensity of anticoagulation. Conclusions In this study, compared with persons taking no antithrombotic therapy, those taking warfarin had lower rates of fall-related hemorrhagic injuries. The absolute rate of the development of fall-related intracranial hemorrhagic injury such as subdural hematomas was low, even in persons taking warfarin. These counter-intuitive results may be due to selection bias, and suggest that physicians are very conservative in selecting patients for warfarin therapy, choosing only those who are sufficiently healthy to be at much lower than average risk of suffering fall-related hemorrhagic injuries. This phenomenon may lead to physicians overestimating the potential for fall-related major hemorrhagic injury in persons taking antithrombotic therapy, with the possible denial of warfarin therapy to many of those who would benefit. This perception may contribute to the care gap between the number of patients who would theoretically derive overall benefit from warfarin therapy and those who are actually receiving it. | Introduction Antithrombotic agents such as warfarin, aspirin, clopidogrel and heparin have proven efficacy and are widely prescribed in the prevention and treatment of many cardiovascular and cerebrovascular diseases [ 1 - 3 ]. However, a significant disadvantage of the use of these therapies is an increased incidence of major hemorrhagic episodes [ 4 ]. Compared to younger persons, those over the age of 65 years are at higher risk of these antithrombotic-related complications [ 5 ]. Falling, which is also more common in older persons, can also lead to an increased risk of hemorrhagic injury [ 6 ]. Thus, at least two studies [ 7 , 8 ] have attempted to delineate the risk of fall-related hemorrhagic complications in older persons who are taking antithrombotic therapy. Stein et al [ 7 ] examined 400 consecutive falls in stroke patients admitted to a rehabilitation center. They found no excess risk of hemorrhagic complications in those who were taking warfarin compared with those who were not. More recently, a study [ 8 ] using decision analytic modeling also determined that the risk of fall-related hemorrhagic complications was low, even in those taking warfarin. It concluded that the risk of falling should not influence the choice of antithrombotic therapy in older persons with atrial fibrillation. However, many clinicians continue to perceive that older persons who are at increased risk of falling have an unacceptably high risk of antithrombotic-related major hemorrhage [ 9 ]. Thus, some continue to withhold antithrombotic therapy in patients who could potentially derive significant benefit from treatment [ 10 ]. The objective of this retrospective study was to determine whether there is a difference in hemorrhagic complications in hospital in-patients who fall and are taking antithrombotic therapy compared with those who are not. Methods The protocol was approved by the Ottawa Hospital Research Ethics Committee and is in compliance with the Helsinki Declaration. Since implementation of a fall prevention program in 1991, the Ottawa Hospital – Civic Campus, a 500-bed tertiary care teaching hospital, has had a formal policy of documenting the pertinent details of all patient-related falls occurring within the hospital. Using its dedicated falls database, the records of consecutive falls occurring over a 4-year period (January 1, 1997 to December 31, 2000) were identified. The hospital policy requires completion of an incident report when patients fall. Information collected includes the time and circumstances of the fall, the type of injury (including head injury) that occurred and a categorization of its severity, and the need for subsequent follow-up. A member of the physician team must eventually review all fall incident reports, follow-up any significant injury from the fall and document this information in the hospital record and incident report. Hemorrhage (i.e. cuts or bruising) was classified as major if the immediate attention of a physician was required, or a clinically apparent intracranial hemorrhage subsequently occurred. All other hemorrhage was classified as minor. Since patient falls can be seen as a reflection of sub-optimal nursing care, the hospital has adopted a non-punitive approach to the completion of reports in order to focus on improving the process that led to the falls. The hospital recognizes that the value of the falls database is predicated on maximum completion of incident reports, leading to the assignment of nurse practitioners dedicated to ensuring the completion of the falls reports. Therefore, it is unlikely that falls leading to an injury would not be captured. During the study period, the hospital had no formal policy or guidelines governing the use of antithrombotic therapy in patients. For all identified falls, the hospital records of the corresponding in-patient admission were retrieved. Data extraction from these charts included pertinent patient demographic information, and the use of antithrombotic therapy (warfarin, aspirin, clopidogrel and/or heparin) at the time of the fall. The indications for the use of the particular antithrombotic therapy were also recorded. Using computerized laboratory reports, the international normalized ratio (INR) and partial thromboplastin time (PTT) values that were closest to the time of the fall were also recorded. Patients' INR values at the time of the fall were determined as follows: 1. If an INR had been done within 12 hours pre- or post-fall, this was accepted as the INR value at the time of the fall. For patients with both 12 hour pre- and post-fall INRs, these values were averaged. 2. For patients not receiving warfarin, if an INR had not been done within 12 hours of the fall and the closest temporal INR was within the normal range (INR<1.2), this was accepted as the INR value occurring at the time of the fall. If the INR values were abnormal, then the pre- and post-INR values temporally closest to the time of the fall were averaged. 3. For persons receiving warfarin at the time of the fall, if no 12 hour pre- and post fall INRs were available, then the pre- and post-fall INR values done temporally closest to the fall were averaged. 4. For persons who did not have an INR while in hospital and were not receiving warfarin, their charts were reviewed for possible reasons to have an elevated INR (e.g. liver disease, coagulapathies). If these were not present, their INR were deemed to be normal (INR 1.0). For patients taking heparin, an identical approach was used for determining the PTT values at the time of their fall. The discharge summaries, nursing notes and medical notes of the hospital records were also reviewed for any immediate and subsequent complications due to the fall including head trauma, subdural hematoma, intracerebral hemorrhage, fractures, major and minor hemorrhage. Multiple falls by the same person were considered independent events. Data extractors were not blinded to the exposure status of patients or their outcomes. Statistical analysis was performed using SPSS software version 10 (SPSS, Chicago, IL). Chi-square testing was performed to determine the relationship between individual demographic and clinical factors, and the occurrence of major hemorrhage. Step-wise forward logistic regression analysis was then performed with variables that had p-values < 0.20 on univariate analysis. Given that multiple statistical comparisons were performed, a p-value < 0.01 was considered statistically significant. Results For the 4-year period, there was a total of 2664 recorded falls in 1861 patients. Despite numerous attempts, the corresponding hospital records could not be located for 29 (1.1%) of the falls. Thus, pertinent data were available and extracted regarding 2635 falls. A significant percentage (29.4%) of patients fell more than once during their admission. The average age of the patients was 71.5 years (SD 15.2; range 16–104), with most being male (55.2%). Antithrombotic use persons who fell Table 1 (see additional file 1 ) shows the details of the antithrombotic therapy use of the patients who fell. Approximately 50% of the patients were taking some form of antithrombotic therapy (warfarin, aspirin, clopidogrel or heparin) at the time of their fall. Approximately 20% of patients had INR values that were higher than the normal range, with a similar number having PTT values outside the normal range. The most common reason for patients to be taking warfarin was stroke prevention in atrial fibrillation. The most common reasons for taking aspirin and heparin were prevention of myocardial infarction and deep vein thrombosis prophylaxis respectively. No patients with high INRs due to reasons other than warfarin use (e.g. liver failure) were found. Fall-related injuries Table 2 (see additional file 2 ) shows the subsequent injuries due to the falls. Major hemorrhage (i.e. bruising and/or cuts requiring immediate attention from a physician) occurred with 10.7% of falls (n = 282). Only one fall resulted in the development of a subdural hematoma. This person was an 89 year old male who was taking warfarin 2 mg and aspirin 81 mg daily (both for stroke prevention in atrial fibrillation) at the same time. His INR and PTT at the time of the fall were 4.3 and 77 seconds respectively. It was documented that he suffered head trauma during the fall. The subdural hematoma was confirmed by CT scan of the head, and he subsequently died from his injuries. There was also one fall possibly resulting in an intracerebral hemorrhage occurring in a 60 year old female. She also suffered head trauma from her fall, but was not taking any antithrombotic therapy, and her INR and PTT values were in the normal range at the time of the fall. She recovered from this injury, with no apparent sequelae. The absolute rate of major hemorrhagic injury (i.e subdural hematoma, intracerebral hemorrhage and major bruising) was lower in persons taking warfarin, compared with those taking no antithrombotic therapy at all (warfarin, 6.2%; no therapy, 11.3%; p = 0.01). A comparison of major hemorrhagic injury between those with normal INR values (INR = <1.3) and those in the therapeutic range (INR 2–3) showed a strong trend towards fewer complications in the group with therapeutic INRs (normal INR, 10.1% (209/2066); INR 2–3, 6.9% (15/218); odds ratio 0.65, 95% CI; 0.38, 1.13; p = 0.15). A similar comparison between those with normal INRs and those with INRs between 3–5, showed no statistical difference in hemorrhagic complications between the two groups (normal INRs, 10.1% (209/2066); INR 3–5, 11.4% (9/79); odds ratio 1.14, 95% CI; 0.56, 2.32; p = 0.70). Univariate analysis demonstrated a very strong relationship between gender and the occurrence of fall-related major hemorrhagic injury (i.e. subdural hematomas, intracerebral hemorrhages and major bruising), with females being much more likely to suffer one of these complications compared with males (13.3% (157/1181) versus 8.7% (126/1454); p < 0.001). Univariate analysis also showed that there were trends towards an increase in the occurrence of major hemorrhagic injury with increasing age (p = 0.04), increasing INR values at time of fall (p = 0.04), and the use of clopidogrel (p = 0.05) or aspirin (p = 0.20). There was no relationship between major hemorrhagic injury with PTT values at time of the fall (p = 0.27), the use of warfarin (p = 0.42) or the use of heparin (p = 0.62). Similar analyses using major bruising/cuts alone (and excluding subdural hematomas and intracerebral hemorrhages) yielded almost identical results. This was due to the occurrence of only one subdural hematoma and one intracerebral hemorrhage. Logistic regression analysis showed that the factors important in the development of major hemorrhagic injury due to falls were female gender (odds ratio 1.6; 95% CI 1.3, 2.1), the use of aspirin (odds ratio 1.4; 95% CI 1.1, 1.8) and the use of clopidogrel (odds ratio 2.2; 95% CI 1.1, 4.8). Of note, increasing age was not an independent risk factor and there was no interaction between warfarin and aspirin use. Repeating the analyses with exclusion of all recurrent falls in individuals (n = 1861) resulted in no significant differences in the results reported above. Of note, fractures occurred in 1.4% of falls (n = 38), with 20 of these being hip fractures. Discussion Falling is a common phenomenon in both hospitalized [ 11 ] and community-dwelling [ 12 ] older persons, with many falls leading to major hemorrhagic injury. Many physicians perceive that the concomitant use of antithrombotic therapy (especially warfarin) increases the chance of fall-related major hemorrhagic injury. This study documents the frequency of these injuries due to falling in hospitalized persons taking antithrombotic therapy and compares them to those who are not. Numerous studies [ 13 - 15 ] have shown that the frequency of hemorrhagic injury is directly proportional to the intensity of anticoagulation. This study found a significant trend (p = 0.04) towards higher intensity anticoagulation status (as measured by INR values) leading to an increasing chance of the development of fall-related major hemorrhagic injury. However, when compared to persons with INRs in the normal range (INR <1.3), there was no trend suggesting that persons with INRs in the therapeutic range (INR 2–3) suffer more frequent major hemorrhagic injury. This suggests that persons with INRs in the therapeutic range are not at increased risk of suffering fall-related major hemorrhagic injury, with excess risk only in those with INRs above the therapeutic range. The overall results of this study found that persons taking warfarin were less likely to suffer a fall-related hemorrhagic injury, compared to those taking no antithrombotic therapy. This counter-intuitive result may be due to selection bias. That is, physicians were very conservative in selecting patients for warfarin therapy, choosing only those who were robust enough to be at very low risk of suffering a fall-related hemorrhagic injury. Thus, physicians possibly overestimate the potential for major hemorrhagic injury in persons taking antithrombotic therapy, leading to the possible denial of warfarin therapy to many of those in whom warfarin would otherwise be indicated. This practice may contribute to the well-documented care gap between the number of patients who would theoretically derive overall benefit from warfarin therapy and those who are actually receiving it. [ 16 , 17 ] However, it must be remembered that other reasons for this care gap may exist. For example, since the risk of stroke from atrial fibrillation more of a long-term, rather than short-term clinical decision, the in-hospital physicians may have had a tendency to defer decision-making about anticoagulation to the primary care physicians of these patients. In this study, only 1 SDH occurred as a result of the more than 2500 falls. Therefore, it was not possible to perform meaningful statistical analyses regarding the contributors to this complication. However, the results confirm that fall-related subdural hematomas are not common in older hospitalized persons, even if they are taking antithrombotic agents. That being said, the development of the single SDH found in this study was almost certainly related to the concomitant use of warfarin and aspirin, with an associated INR of greater than 4.0. The reason(s) for this study finding that female patients have a greater risk of developing fall-related hemorrhagic injury is unclear. Age was not a factor as the mean age of female patients (71.6 years) was similar to male patients (71.5 years). Also, the percentages of female and male patients taking warfarin, heparin, clopidogrel or aspirin in this study were very similar. Other studies [ 18 , 19 ] have shown that females are more likely to suffer fall-induced injuries compared with males, though these studies included non-hemorrhagic injuries such as fractures. The relationship between gender and fall-related fractures is explainable by the higher prevalence of osteoporosis in the older female population. The use of aspirin or clopidogrel is generally considered to be less likely to lead to major hemorrhagic injury when compared with the use of warfarin or heparin. Therefore, it was surprising to find that there was a weak, but statistically significant association between fall-related major hemorrhagic injuries and the use of aspirin or clopidogrel, but no such relationship with the use of warfarin or heparin. Again, this result may be due to selection bias, with physicians favoring the use of aspirin or clopidogrel over warfarin or heparin in persons who are less healthy and more prone to serious hemorrhagic injury if they fall. There are a number of limitations to our study. Due to the retrospective design, it was not possible to apply standardized definitions and measures when determining the occurrence, severity and consequences of falls. Also, we examined the injuries related to hospital-based falls. Therefore, it is unclear whether our results are generalizable to other settings. However, the 10.7% rate of major fall-related hemorrhagic injury (SDH, ICH or major bruising/cuts) in this study is similar to previous hospital- and community-based studies [ 6 , 12 ] that found that approximately 5%–10% of falls result in serious injury. In our database, there were fewer falls causing minor hemorrhagic injury compared with major hemorrhagic injury. This suggests that there was likely underreporting of minor hemorrhagic injury due to falls. This may have occurred because, despite hospital policy, nurses were less inclined to complete incident reports for patients whom they believed had no potential sequelae to their falls. Many falls that resulted in little to no injury may not have been captured. Therefore, the results of our study are likely to overestimate, rather than underestimate, the rate of hemorrhagic injury in persons who fall. The methodology of this study would have been strengthened by reviewing all hospital admissions over the study period for the risk of fall-related injuries. The rate of falling in those receiving and not receiving antithrombotic therapy could then be determined. If those receiving warfarin were less likely to fall, then the conclusion that clinicians were reluctant to prescribe antithrombotic agents (especially warfarin) to patients they deemed at risk for falls would be strengthened. Unfortunately, resource considerations prevented us from taking this approach. It also would have been advantageous to have collected further information regarding potential confounders related to bleeding risk such as the presence of previous falls or fractures, and the amount of time patients were in hospital. However, some of this information was not or could not be reliably collected from the charts. This is because most primary care physicians often defer to the specialists to make these decisions. Finally, since there were persons who fell multiple times, one could argue with our assumption that each fall was an independent event. However, reanalysis of the data by including only the first recorded fall from each individual resulted in no significant changes to the results. The study also has an important strength. Not all fall-related major hemorrhagic injury (especially subdural hematomas) is identifiable immediately after a fall. We were able to follow-up the sequelae of falling throughout the course of the patients' hospital admission. Therefore, it is unlikely that we failed to identify any serious consequences of falling in our study population. Conclusion This study provides evidence that the absolute rate of the development of fall-related subdural hematomas is low, even in persons taking warfarin. Also, the lower than expected rate of fall-related hemorrhagic injury in persons taking warfarin suggests that physicians may overestimate the potential for fall-related major hemorrhagic injury in older persons taking antithrombotic therapy, leading to an overly conservative approach to assessing the risk of anticoagulant-related bleeding. This information may help close the care gap between the number of patients who would theoretically benefit from anticoagulant therapy and the number that actually receive it. Further study is necessary to delineate the characteristics of patients who are at high risk of developing fall-related hemorrhagic injury when taking antithrombotic therapy. Competing interests The author(s) declare that they have no competing interests. Authors' contributions MM and FM proposed the study. All authors participated in the design of the study and contributed to the drafting and revision of the manuscript. AB and ML conducted the chart reviews. Supplementary Material Additional File 1 TABLE1Aug04revised.doc : this is Table 1 entitled, "Fall-related antithrombotic use" Click here for file Additional File 2 TABLE2Aug04revised.doc : this is Table 2 entitled, "Consequences of falls" Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545051.xml |
546202 | Allergens of the entomopathogenic fungus Beauveria bassiana | Background Beauveria bassiana is an important entomopathogenic fungus currently under development as a bio-control agent for a variety of insect pests. Although reported to be non-toxic to vertebrates, the potential allergenicity of Beauveria species has not been widely studied. Methods IgE-reactivity studies were performed using sera from patients displaying mould hypersensitivity by immunoblot and immunoblot inhibition. Skin reactivity to B. bassiana extracts was measured using intradermal skin testing. Results Immunoblots of fungal extracts with pooled as well as individual sera showed a distribution of IgE reactive proteins present in B. bassiana crude extracts. Proteinase K digestion of extracts resulted in loss of IgE reactive epitopes, whereas EndoH and PNGaseF (glycosidase) treatments resulted in minor changes in IgE reactive banding patterns as determined by Western blots. Immunoblot inhibitions experiments showed complete loss of IgE-binding using self protein, and partial inhibition using extracts from common allergenic fungi including; Alternaria alternata , Aspergillus fumigatus , Cladosporium herbarum , Candida albicans , Epicoccum purpurascens , and Penicillium notatum . Several proteins including a strongly reactive band with an approximate molecular mass of 35 kDa was uninhibited by any of the tested extracts, and may represent B. bassiana specific allergens. Intradermal skin testing confirmed the in vitro results, demonstrating allergenic reactions in a number of individuals, including those who have had occupational exposure to B. bassiana . Conclusions Beauveria bassiana possesses numerous IgE reactive proteins, some of which are cross-reactive among allergens from other fungi. A strongly reactive potential B. bassiana specific allergen (35 kDa) was identified. Intradermal skin testing confirmed the allergenic potential of B. bassiana . | Background Microorganisms are currently under intensive study for use as biopesticides [ 1 - 3 ]. Several fungal species including Metarhizium anisopliae , Verticillium lecanii , and Beauveria bassiana are being used as biocontrol agents for a number of crop, livestock, and human nuisance pests [ 4 - 7 ]. Strains of B. bassiana have been licensed for commercial use against whiteflies, aphids, thrips, and numerous other insect and arthropod pests. B. bassiana fungal formulations are being spread onto a range of vegetables, melons, tree fruits and nuts, as well as organic crops. As alternatives to chemical pesticides these agents are natural occurring and are considered to be non-pathogenic to humans, although a few cases of B. bassiana mediated tissue infections have been reported [ 8 , 9 ]. Airborne mold spores are widespread, and many have been identified as inhalant allergens eliciting type I hypersensitive reactions in atopic individuals [ 10 - 14 ]. Common allergenic moulds include the anamorphs of ascomycetes and constitute many species within the Alternaria , Aspergillus , and Cladosporium genera [ 15 - 19 ]. The genes encoding for numerous fungal allergens have been isolated, and their protein products expressed and characterized. Purified fungal allergens have been shown to be bound by human IgEs and to elicit allergic reactions in atopic individuals using skin prick tests. Patients with mould allergies often display IgE-mediated responses to multiple fungi, a phenomenon typically thought to result from the presence of common cross-reactive allergen(s) [ 15 , 20 - 22 ], although parallel independent sensitization to multiple fungal allergens can also occur. In this regards, identification of genus and/or species specific allergens would provide useful tools in differentiating allergic reactions due to primary sensitization and those mediated by cross-reactive epitopes. In the present study, we demonstrate Beauveria bassiana crude extracts contain numerous allergens capable of being recognized by human serum IgEs. The allergens were proteinaceous in nature, and immunoblot inhibition experiments revealed the presence of shared epitopes between Beauveria and several other common fungal moulds. Potential Beauveria-specific allergens were also identified, including a strongly reactive ~35-kDa protein band. Intradermal skin testing using B. bassiana extracts resulted in allergenic reactions in several individuals, including some who have had occupational exposure to the fungus. Methods Strains and cultures Beauveria bassiana (ATCC 90517) was grown on Sabouraud dextrose + 0.5–1% yeast extract or Potato dextrose (PD) media on either agar plates or in liquid broth. Plates were incubated at 26°C for 10–12 days and conidia were harvested by flooding the plate with sterile dH 2 O containing 0.01% Tween-20. Liquid cultures were inoculated with conidia harvested from plates at 0.5–1 × 10 5 conidia/ml. Extract preparation Alternaria alternata , Aspergillus fumigatus , Candida albicans , Cladosporium herbarum , Epicoccum purpurascens , and Penicillium notatum were acquired from Greer Laboratories inc., (Lenoir, NC). Extracts were resuspended in TE (40 mM Tris-HCl, pH 8.0, 1 mM EDTA) to a final concentration of 2 mg/ml. Beauveria bassiana was grown in Sabouraud's broth containing 1% yeast extract with aeration at 25°C for 3–5 d. Cellular mass was harvested by centrifugation (10,000 × g, 10 min) and freeze-dried. Cells were resuspended in TE containing 0.1% phenylmethylsulfonyl fluoride (PMSF) and homogenized using a bead-beater apparatus. Precipitations Crude extracts of B. bassiana were subjected to three successive precipitations before use in Western blots. Acetone precipitation Homogenized B. bassiana extracts (50 ml) were mixed with 8 × volume (400 ml) of acetone (kept at -20°C), with rapid stirring, and incubated overnight at -20°C. The precipitate was collected by centrifugation (30 min, 4000 × g), and the pellet was air dried (10 min) before being resuspended in TE containing 0.1% PMSF. Streptomycin precipitation (removal of DNA) Streptomycin sulfate (5 ml of 10% solution) was added dropwise to resuspended acetone precipitated extracts (40 ml) at 4°C with rapid stirring. Samples were incubated for an additional 30 min on ice before being centrifuged (15 min, 10,000 × g) in order to remove the precipitate. Proteins in the resultant supernatant were precipitated using ammonium sulfate. Ammonium sulfate The proteins present in the streptomycin sulfate treated supernatant were precipitated using ammonium sulfate (75%, final concentration). Saturated ammonium sulfate (120 ml) was added dropwise to the Beauveria extract (40 ml) at 4°C with rapid stirring. The solution was allowed to stir overnight at 4°C and precipitated proteins were harvested by centrifugation (30 min, 100,000 × g). The protein pellet was resuspended in TE containing 0.1% PMSF (40 ml) and extensively dialyzed against the same buffer before use. SDS-Polyacrylamide gel electrophoresis (PAGE) Protein samples (30–40 μg) were analyzed by sodium-dodecyl-sulphate-polyacrylaminde gel electrophoresis (SDS-PAGE, 10% Bis-tris gel, Invitrogen, Carlsbad, CA) using standard protocols. Gels were stained with Gelcode blue stain reagent (Pierce, Rockford, IL) and subsequently de-stained with dH20. Western blotting Protein samples were separated under reducing conditions using 10% Bis-tris polyacrylamide gels (Invitrogen Mops system) and transferred to polyvinylidene-fluoride (PVDF) membranes (Invitrogen) as described. Immunoblot experiments were performed using individual and pooled human sera as the primary antibody solution as indicated. Typically, sera were diluted 1:5 with Tris-HCl buffered saline (TBS) containing 5% dry milk + 0.1% Tween-20. IgE-specific reactivity was visualized using a horseradish peroxidase (HRP) conjugated goat anti-human IgE (polyclonal) secondary antibody (BioSource International, Los Angeles, CA). Membranes were washed with TBS containing 0.1% Tween-20 and bands were visualized using the Immuno-Star HRP detection system (Biorad, Hercules, CA). Enzyme Treatments The ammonium sulfate fraction of B. bassiana crude extracts was treated with Proteinase K (ICN-Biomed, Aurora, Oh) following standard protocols. Typically, samples (36 μl) were incubated with 4 μl Proteinase K solution (10 mg/ml in 50 mM Tris-HCl, pH 7.5) for 2 hr at 37°C before analysis. Samples were also treated with endoglycosidase-H (EndoH, New England Biolabs, Beverly, MA) and peptide: N-Glycosidase F (PNGaseF, New England Biolabs) according to the manufacturer's recommendations. For EndoH and PNGaseF treatments, samples (36 μl) were denatured in 4 μl 10 × denaturing buffer (0.5% SDS, 1% β-mercaptoethanol) at 100°C for 10 min prior to the addition of the EndoH (5 μl of 10 × G5 Reaction Buffer, 50 mM sodium citrate, pH 5.5) and PNGaseF reaction buffers (50 mM sodium phosphate pH 7.5) and enzymes (5 μl), respectively. Reactions were incubated at 37°C for 2 h before being analyzed by SDS-PAGE and Western blotting. Immunoblot inhibition IgE binding to B. bassiana proteins were competed with proteins of other fungal extracts. SDS-PAGE resolved B. bassiana proteins were electroblotted to PVDF membranes as described above. Membranes were blocked with TBS containing 5% dry milk + 0.1% Tween-20 and strips were incubated with pooled human sera (1:5 v/v in same buffer) containing 100–500 μg of the indicated fungal crude protein extract. Skin sensitivity profiles to fungal extracts Patients were tested with 9 common fungal extracts for allergy diagnosis using a skin prick assay. The following extracts were obtained from ALA-Abello (Round Rock, TX); Alternaria tenius , Aspergillus fumigatus , Cephalosporium ( Acremonium strictum ), Curvularia spp. Bipolaris , Epicoccum nigram , Fusarium spp., Helminthosporium sativum , Hormodendrum horde , Penicillium (mixed, P. chrysogenum and P. notatum ). Extracts were tested using a 1:10 dilution of the 20,000 PNU/ml stock solution, and skin sensitivity was recorded on a relative scale from 0–4 reflecting the size of induration or weal (4 representing the highest reactivity) and using histamine (0.1 mg/ml) reaction scored as a 3 if no interference was present. Intradermal skin testing B. bassiana crude extracts were prepared as described above but were extensively dialyzed against 0.15 N NaCl and filtered through a 0.22 μm filter before use. Subjects were given intradermal injections of 0.1 ml crude extract ranging in concentration from 0.01–1 mg/ml. Control injections included saline and histamine (0.1 mg/ml). Allergenic reactions were allowed to develop for 15–30 min before the height and width of the reactions were recorded. Results Identification of IgE reactive bands An ammonium sulfate fraction of B. bassiana proteins was resolved on SDS-PAGE (Fig. 1 , lane B) and transferred to PVDF membranes as described in the Materials and Methods. Membranes were probed with sera from individual patients who were reactive to various moulds (Table 1 ), which was pooled and used to demonstrate IgE reactivity against antigens present in B. bassiana extracts (Fig. 1 ). Serum mix-I represents pooled sera derived from patients E, J, K, L, and M, as well as three additional patients that were only tested (skin prick) against Aspergillus and Penicillium , displaying test scores of 3–4 for each. These data demonstrate human IgE binding of allergens present in B. bassiana extracts. Initial blots showed 12–15 distinct reactive protein bands, ranging in molecular mass from 12 kDa to >95 kDa (under denaturing conditions); with the most prominent bands located around 64, 45, and 35 kDa. Control experiments omitting either the primary or secondary antibody incubation steps resulted in complete loss of signal. Proteinase K digestion of samples also resulted in loss of all signal (Fig. 1 , lane 4), indicating the proteinaceous nature of the IgE reactive bands. Since the carbohydrate moieties of several protein allergens are known to play a role in their allergenicity and even cross-reactivity [ 20 - 22 ], samples were treated with the deglyocosylating enzymes EndoH and PNGaseF. Control experiments incubating samples in the EndoH denaturing buffer without any enzyme altered the IgE-reactive signals (Fig. 1 , lane 5), however, samples treated with EndoH did not appear any different than control reactions (Fig. 1 , lane 6). Similar results were obtained in PNGaseF digests (data not shown). These data appear to indicate that the B. bassiana IgE-antigen profiles observed on Western blots are proteins with minimal contributions due to glycosylation. Figure 1 SDS-PAGE and immunoblot analysis of Beauveria bassiana crude extracts. SDS-PAGE, Gelcode blue stained, lanes A) 5 μg protein standards, and B) 40 μg B. bassiana crude extract. Immunoblots probed with pooled serum mix-I (patients displaying mould allergies), lanes 1), 5 μg protein standards, 2) 20 μg B. bassiana crude extract, 3) 40 μg crude extract, 4) 40 μg crude extract, Proteinase K treated, 5) 40 μg crude extract, denaturing buffer control (no EndoH), 6) 40 μg crude extract, EndoH treated Table 1 Allergic profile of patients A–G, obtained by skin prick testing. Patient ID Individual Skin Reactivity to Fungal Extracts* Alt † Asp Cep Cur Epi Fusa Helmin Hormo Pen A 3 2 0 3 2 2 0 0 3 B 3 2 0 2 3 2 2 2 0 C 4 0 0 3 0 2 0 0 0 D 0 0 2 2 0 2 0 2 2 E 3 2 0 3 2 3 3 0 0 F 4 1 1 2 4 0 2 0 0 G 3 0 0 4 3 0 2 0 0 *Skin test scores were registered using a relative scale from 0–4 with 4 representing the highest reactivity as described in the Materials and Methods. † Abbreviations used; Alt , Alternaria tenius ; Asp , Aspergillus fumigatus ; Cep , Cephalosporium ( Acremonium strictum ); Cur , Curvularia spp. Bipolaris ; Epi , Epicoccum nigram ; Fusa , Fusarium spp.; Helmin , Helminthosporium sativum ; Hormo , Hormodendrum horde ; Pen , Penicillium (mixed, P. chrysogenum and P. notatum ). Immunoprint Analysis of B. bassiana : Reactivity with Individual Sera In order to determine the variation and distribution of serum IgEs reactive to B. bassiana extracts, individual sera from patients displaying mould allergies (Fig. 2 , lanes A–G) as well as random sera from the general population (Fig. 2 , lanes H–M) were used as probes for Western blots (Fig. 2 ). The reactivity of pooled sera from patients A–G (termed serum mix-II) is also shown (Fig. 2 , lane 2). Skin prick test results for patients A–G are shown for comparative purposes (Table 1 ) and represent the clinically determined reactivity of each patient to extracts of the tested fungal species. Patients (A–G) were selected based skin prick reactivity to at least 4 different fungi with scores of 2 or greater. Identical concentrations of B. bassiana extract (40 μg) were resolved by SDS-PAGE, blotted to PVDF membranes, and the lanes were cut into separate strips. Each strip was treated with a 1:5 dilution of each respective serum as described in the Materials and Methods (Fig. 3 , lane 2 is the sera pool). A total of 16 individual sera were tested, with the sera from three patients displaying no IgEs reactive to proteins present in the B. bassiana extracts. The results for the remaining 13 sera are shown in Fig. 2 . The data show a large individual variation in serum IgEs capable of binding epitopes present in B. bassiana extracts, both in terms of banding distribution and the intensity of the reaction. No correlation was observed between measurements of total IgE and the observed binding to B. bassiana allergens. Some patients displayed strong reactions to multiple bands, whereas others to a more limited set of epitopes. Distinct strongly reactive bands ranging from 40 kDa to approximately 200 kDa could be seen in sera A, E, and to a lesser extent L. A strongly reactive 35 kDa band was visible in sera C, G, E, and L. Several sera displayed IgEs that bound to only a limited set of 2–3 allergens (C, F, G, weak bands in B, I, J, K, and M). Blots probed with one serum (H) resulted in a large smear ranging from ~30 kDa to 55 kDa. The reason for the observed smear is unknown and efforts to distinguish separate bands by manipulating the concentrations of either sera or extract were unsuccessful. A number of bands (based upon molecular mass) appeared to be common to several sera including proteins of approximately 35, 42–48, and 60 kDa. A number of allergens of high molecular weight (~100–200 kDa) were also visible; however the resolution in this range on the Western blots is poor. Figure 2 Immunoprint analysis of B. bassiana extracts (40 μg crude extract/strip) probed with individual sera. Lane 1) 5 μg protein standards, 2) pooled serum mix-II (patients displaying mould allergies). Lanes A)–G) membrane strips treated with individual sera, Lanes H)–M) membrane strips probed with individuals having had occupational exposure to B. bassiana and other fungi (see intra-dermal skin test results for individuals J–M, Table 2). Figure 3 IgE immunoblot inhibition with fungi. B. bassiana protein strips (40 μg crude extract) were blocked and incubated with mix containing (500 μl) pooled sera (mix-II) and 2) no additions, 3) 40 μg Alternaria alternata crude extract, 4) 400 μg Alternaria alternata , 5) 40 μg Aspergillus fumigatus , 6) 400 μg Aspergillus fumigatus , 7) 400 μg Cladosporium herbarum , 8) 400 μg Candida albicans , 9) 400 μg Epicoccum purpurascens , and 10) 400 μg Penicillium notatum protein. Intradermal Skin Testing A total of ten individuals were tested for allergenic reactivity to B. bassiana crude extracts using an intradermal delivery procedure. Data using 1 mg/ml B. bassiana crude extract and histamine controls are presented in Table 2 . Seven out of the ten individuals (ID #s, J–O, and Q) displayed skin reactivity reactions to the B. bassiana extracts (Table 2 , also see corresponding Western blot results for individuals J, K, L, and M; Fig. 2 ). It is interesting to note that 4 (J–M) of 5 individuals (plus S) that have had occupational exposure to B. bassiana displayed skin reactivity as well as bands on Western blots. A preliminary correlation was observed between the B. bassiana /histamine ration and the in vitro reactivity of individual sera in Western blots. Individuals J, K, and M, displayed B. bassiana /histamine control ratios <1, also showed weak bands in Western blots (Fig. 2 ), whereas individual L who had a B. bassiana /histamine ratio = 1.65, reacted against numerous epitopes in the extract and with a higher intensity. Table 2 Intradermal skin test results using B. bassiana extract Patient ID Histamine control 1 (0.1 mg/ml) B. bassiana Extract (1 mg/ml) B. bassiana /Histamine Induration 2 Erythema 2 Induration 2 Erythema 2 Induration ratio 3 J 4,5 7 × 6 12 × 16 8 × 8 12 × 13 0.65 K 4,5 20 × 15 55 × 50 13 × 12 14 × 13 0.52 L 4,5 11 × 10 16 × 33 13 × 14 26 × 28 1.65 M 4,5 15 × 16 36 × 44 10 × 12 10 × 12 0.30 N 16 × 14 38 × 58 10 × 11 21 × 17 0.49 O 21 × 16 39 × 59 9 × 8 18 × 21 0.21 P 15 × 17 44 × 45 5 × 4 5 × 4 0.08 Q 15 × 14 36 × 38 9 × 12 10 × 13 0.51 R 15 × 15 55 × 38 4 × 4 11 × 13 0.07 S 4 20 × 19 38 × 43 4 × 4 4 × 4 0.04 1 In all instances saline control injections produced indurations of 3–4 mm × 3–4 mm. 2 Values recorded in mm × mm. 3 Induration ratio expressed as B. bassiana reaction area (mm 2 )/histamine reaction area (mm 2 ). 4 Individual with occupational exposure to Beauveria bassiana . 5 See Western Blot results for individual, Fig. 2. Cross-reactivity among different fungi In order to determine the extent of cross-reactivity of B. bassiana allergens with other fungi, immunoblot inhibition experiments were performed. Identical concentrations of B. bassiana crude extract (40 μg) were resolved by SDS-PAGE, blotted to PVDF membranes, and lanes were cut into separate strips. Each strip was treated with a 1:5 dilution pooled sera (serum mix-II) as the primary antibody supplemented with concentrations of fungal crude extracts as described in the Materials and Methods. Fig. 3 shows Western blots in which the binding of human IgEs to allergens present in B. bassiana extracts were competed with: excess crude extracts from Alternaria alternata (Fig 3 , lanes 3, 4), Aspergillus fumigatus (lanes 5, 6), Cladosporium herbarum (lanes 7) , Epicoccum purpurascens (Lane 8) , Penicillium notatum (lane 9) , and Candida albicans (lane 10). There was complete loss of all signals using 2-fold excess B. bassiana extract as the competitor (data not shown). These data indicate that while Beauveria possess many epitopes in common with several other fungi, notably Alternaria and Penicillium , a 35-kDa major reactive band was not inhibited by any extract tested. Discussion Although it is well known that fungi are important triggers of respiratory allergies, the potential allergenicity of entomopathogenic fungi used in biocontrol has largely been untested. Aerobiological surveys of conidial fungi and skin sensitivity tests to fungal extracts performed in the 1980s in the Netherlands revealed that although Beauveria could barely be detected in airborne samples, and represented less than 0.1% of the airborne fungal "flora", the incidence of allergic skin test reaction to Beauveria was the highest of all fungal species tested [ 10 , 23 , 24 ]. In rural areas, the use of fungi in agricultural pest management practices can greatly increase the potential for human exposure to these agents. Likewise, in urban settings, the commercialization of fungal products for household use may potentiate a much wider problem since indoor air concentrations of the moulds can greatly increase. For these reasons, an examination of the allergenic potential of Beauveria bassiana is imperative. The present study demonstrated the allergenic potential of B. bassiana directly by intradermal skin testing of individuals and in vitro by revealing the presence of serum IgEs capable of binding allergens present in fungal crude extracts. Over 20 different IgE binding proteins were observed using Western blots probed with sera from patients displaying mould allergies. Results using individual sera revealed a wide variation in IgE-binding proteins between sera, although several common bands, including a protein with an apparent molecular mass of 35 kDa were visible among the sera of several patients. Our in vitro observations were confirmed by intradermal skin testing on individuals using B. bassiana extracts. While the testing sample population was small, these results indicated that our extracts were able to elicit allergic reactions in individuals, including some that have had occupational exposure to the fungus. Concentrations of ~1 mg/ml of B. bassiana extracts were required to elicit indurations equivalent to 0.1 mg/ml histamine in most individuals, indicating the possibility of potent allergens in the Beauveria extract. Interestingly, not all individuals specifically exposed to B. bassiana displayed allergic reactions and individuals J, K, and M (who did display mild allergic reactions, Table 2 ) did not react to the 35 KDa protein based upon Western blotting results (Fig. 2 ). We do not, however, have any quantifiable index of exposure for the individuals in our sample and any interpretations should be made with some caution. Numerous studies have revealed the presence of cross-reactive proteins among fungal species between genera [ 15 , 20 - 22 , 25 - 27 ]. In our experiments, (excess) crude extract from a test organism was added during the primary antibody (human sera) incubation. Common or shared epitopes between B. bassiana and the test fungus would result in a loss of signal due to competition for reactive IgEs. However, IgEs reactive to Beauveria-specific allergens would not be affected, resulting in no change in the corresponding reactive bands on a Western blot. Loss of a signal would indicate that a homolog or shared epitope (IgE-reactive) exists between the two fungal species, implying that primary sensitization by one organism can result in an allergic reaction when exposed to the homologous allergen of another organism. Competitive immunoblot inhibition experiments revealed significant epitope homology between B. bassiana and several clinically important fungi responsible for IgE-mediated allergic reactions in atopic individuals. Thus, an allergic reaction to Beauveria exposure may arise in patients sensitized to other fungi. Extracts from A. alternata and E. purpurascens almost completely competed with allergens present in the B. bassiana extract with the notable exception of the ~35 kDa allergen. Competition experiments using A. fumigatus , C. herbarum , C. albicans , and P. notatum extracts also indicated the presence of many shared epitopes, although distinct (non-competed) IgE-binding B. bassiana proteins of 35 kDa, 64 kDa, and >200 kDa molecular mass were detectable. These proteins, particularly the 35 kDa allergens may represent B. bassiana specific allergens. Experiments are underway to characterize the 35 kDa allergen, which may lead to a diagnostic assay for B. bassiana sensitization. Finally, our analysis of potential B. bassiana allergens was limited to cell extracts grown under specific conditions and did not include the culture filtrate. Extracellular proteases, an important class of fungal proteins that can elicit allergenic reactions, have been characterized from a number of fungal species [ 28 - 31 ], and are likely to be present in B. bassiana . A careful examination of culture growth conditions is also warranted in order to provide a standardized reagent for testing purposes. Conclusions Although Beauveria holds promise as an arthropod biological control agent, there have been few reports on the allergenic potential of these organisms. Identification of B. bassiana specific allergens can lead diagnostic methods for determining sensitization to this organism and may provide a rational basis for allergen attenuation in order to yield safer biocontrol products. The observed cross-reactivity among proteins of B. bassiana and the fungi tested, highlight the importance of considering the possibility that multiple fungal sensitivity can occur due to exposure to a single fungus. Further testing should be performed to determine the scope, severity, and range of allergenic reactions to B. bassiana . Competing Interests The author(s) declare that they have no competing interests. Authors' contributions GSW carried out the immunoassays and other in vitro experiments. SWH performed the clinical experiments and participated in the design of the study. NOK conceived of the study, and participated in its design and coordination, and drafted the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546202.xml |
517501 | No evidence for involvement of SDHD in neuroblastoma pathogenesis | Background Deletions in the long arm of chromosome 11 are observed in a subgroup of advanced stage neuroblastomas with poor outcome. The deleted region harbours the tumour suppressor gene SDHD that is frequently mutated in paraganglioma and pheochromocytoma, which are, like neuroblastoma, tumours originating from the neural crest. In this study, we sought for evidence for involvement of SDHD in neuroblastoma. Methods SDHD was investigated on the genome, transcriptome and proteome level using mutation screening, methylation specific PCR, real-time quantitative PCR based homozygous deletion screening and mRNA expression profiling, immunoblotting, functional protein analysis and ultrastructural imaging of the mitochondria. Results Analysis at the genomic level of 67 tumour samples and 37 cell lines revealed at least 2 bona-fide mutations in cell lines without allelic loss at 11q23: a 4bp-deletion causing skip of exon 3 resulting in a premature stop codon in cell line N206, and a Y93C mutation in cell line NMB located in a region affected by germline SDHD mutations causing hereditary paraganglioma. No evidence for hypermethylation of the SDHD promotor region was observed, nor could we detect homozygous deletions. Interestingly, SDHD mRNA expression was significantly reduced in SDHD mutated cell lines and cell lines with 11q allelic loss as compared to both cell lines without 11q allelic loss and normal foetal neuroblast cells. However, protein analyses and assessment of mitochondrial morphology presently do not provide clues as to the possible effect of reduced SDHD expression on the neuroblastoma tumour phenotype. Conclusions Our study provides no indications for 2-hit involvement of SDHD in the pathogenesis of neuroblastoma. Also, although a haplo-insufficient mechanism for SDHD involvement in advanced stage neuroblastoma could be considered, the present data do not provide consistent evidence for this hypothesis. | Background Neuroblastoma (NB) is the most frequent extra-cranial solid tumour in children, originating from immature neural crest cells of the sympathetic nervous system [ 1 ]. The tumours show remarkable differences in clinical presentation ranging from localized to highly metastatic. Although age and clinical stage are strong prognostic indicators, particular genetic aberrations, i.e. MYCN amplification and 17q gain, also have a profound predictive power [ 2 , 3 ]. Presently, three major clinico-genetic NB patient subgroups have been recognized (subgroup 1, 2A and 2B) [ 4 ]. Subgroup 1 consists of NB patients with favourable disease stage (stage 1, 2 and 4S), most often infants younger than one year of age presenting with tumours with a near triploid DNA content and a characteristic pattern of chromosomal instability including the consistent presence of an extra chromosome 17. The two other NB patient groups represent mainly older children with high-stage disease (stage 3 and 4) and poor prognosis. Both NB subgroups present with 17q-gain, but are distinguished by presence of MYCN amplification and 1p-deletion in subgroup 2B and 11q-deletion often in combination with 3p-deletion in subgroup 2A [ 3 , 5 - 9 ]. The first evidence for the occurrence of 11q-deletions in NB was obtained in 1991 [ 10 ]. However, it was not until recently that a specific patient subgroup with this particular genetic defect was recognized, representing approximately 20% of cases [ 5 - 9 , 11 - 13 ]. The recurrent finding of 11q-deletions in NB suggests the presence of a tumour suppressor gene residing on the long arm of chromosome 11. Additional functional evidence for this hypothesis came from the observation that differentiation of NB cells can be induced by transfer of an intact chromosome 11 into a NB cell line [ 14 ]. Although both comparative genomic hybridization (CGH) and loss of heterozygosity (LOH) studies indicate that the majority of the 11q-deletions are distal losses encompassing a large portion of the long arm [ 5 - 9 , 12 , 13 , 15 , 16 ], detection of rare small or interstitial deletions allowed the provisional localization of an SRO (shortest region of overlap) at 11q23.3 between markers D11S1340 and D11S1299, encompassing a distance of approximately 3 Mb [ 16 ]. When a single tumour with two small interstitial deletions is not taken into consideration, the SRO is defined by a small subset of tumours and spans 18 Mb between markers D11S898 and D11S1299 (according to UCSC Genome Browser, freeze version July 2003). This region harbours SDHD , which encodes the small subunit D (cybS, cytochrome b558) of the mitochondrial respiratory chain complex II (succinate-ubiquinone oxidoreductase) [ 17 , 18 ] and was recently recognized as a prototype tumour suppressor gene [ 19 ]. The first evidence for a role of SDHD in tumour development was obtained by the discovery of germline mutations in this gene as the cause for familial paraganglioma (PGL) [ 19 ]. Somatic and occult germline SDHD mutations were also detected in patients with apparently sporadic pheochromocytoma (PC) [ 20 , 21 ]. It seems that most of the individuals with PC possess SDHD mutations in the 5' portion of the gene causing complete disassembly of complex II, whereas PGL are associated with mutations in the 3' region of the gene causing partial inactivation of its catalytic activity [ 19 - 28 ]. PGL and PC are histologically related to NB as they are all neural crest derived. NBs consist of immature neuroblasts, whereas PGL and PC contain mature chromaffin cells. Of further interest is the fact that, in addition to the well established role of SDHD in oxidative phosphorylation, SDHD has also been presumed to contribute to the function of the mitochondria as oxygen sensors. It was shown that SDHD inactivation leads to a pseudo-hypoxic state and upregulation of hypoxia responsive genes, possibly through increased production of reactive oxygen species (ROS) [ 23 ]. A hypoxia-induced shift toward a neural crest-like phenotype has been shown to result in more aggressive NB cells with increased potential to metastasize [ 29 ]. Consequently, inactivating SDHD mutations or reduced activity of SDHD might lead to impaired oxidative phosphorylation and hypoxia and thus contribute to NB oncogenesis. In view of the above, we considered SDHD as a positional and functional candidate for the presumed NB tumour suppressor gene on 11q23. In order to search for evidence for involvement of SDHD in NB development, an extensive series of investigations was performed on the DNA, RNA and protein level. Methods NB patient and cell line samples Neuroblastoma (NB) tumour samples (at least 70% tumour cells) were collected at the Ghent University Hospital (Ghent, Belgium) (n = 32) and in the Molecular Oncology Unit (Lyon, France) (n = 35). Ethical approval was obtained for the collection of the tumour samples. The latter group includes selected patients with stage 3 or 4 NB without MYCN amplification. For all NB patients constitutional leukocyte DNA was available. In addition, 31 NB cell lines were included in the analysis of which karyotypes were available. For 20 of these cell lines, comparative genomic hybridization (CGH) data and/or M-FISH (multicolour fluorescence in situ hybridization) results have been published [ 30 - 32 ]. For screening of sequence variants in a normal population, leukocyte DNA from 135 unrelated healthy individuals was used. DNA was extracted as previously described [ 33 ]. Cultures of NB cell lines N206, SK-N-AS, SK-N-SH, NMB, SK-N-FI, CLB-GA, LA-N-2 and NGP were treated with puromycine (100 μg/ml) during 6 hours in order to prevent possible nonsense mediated RNA decay of variant SDHD transcripts. RNA of the cell line pellets (treated and untreated) was extracted with the RNeasy Mini kit (Qiagen) according to the manufacturer, followed by RNase free DNase treatment on column (Qiagen). A fraction of the untreated NB cell line cultures was also used for functional enzyme assays. 11q23 status of samples Determination of the 11q23 status in NB cell lines and tumours with LOH or FISH The 11q status of the cell lines was evaluated using FISH. FISH was performed using the LSI MLL (11q23.3) SpectrumOrange probe (Vysis) and BAC clone RP11-93E4 for the CRTAM gene (11q24.1) in combination with a centromeric probe for chromosome 11. Labelling and FISH was performed as described [ 34 ]. For each case at least twenty metaphase chromosomes and 100 interphase nuclei were screened. All NB patients were analyzed with 4 microsatellite markers on 11q23: D11S1986 (11q23.1), D11S1998 (11q23.3), D11S1356 (11q23.3) and D11S1299 (11q23.3), of which D11S1986 and D11S1998 are immediately flanking the SDHD gene. In order to discriminate between whole chromosome loss, and unbalanced 11q loss (= partial 11q loss), two microsatellite markers on 11p (D11S922 on 11p15.5 and D11S1324 on 11p14.1) were analyzed in patients that showed allelic imbalance for all 11q markers (positions of the markers are according to the UCSC Genome Browser, freeze version July 2003). Scoring of loss of heterozygosity (LOH) was performed by calculation of the allelic imbalance factor (AIF) [ 35 ], whereby AIF > 2 denotes allelic imbalance, and AIF > 5 denotes LOH. Experimental conditions for the fluorescent based LOH screening can be obtained from the authors upon request. Homozygous deletion screening in NB cell lines Real-time quantitative PCR primers were designed in the four exons of SDHD using Primer Express v2.0 (Applied Biosystems) (Table 1 ). Exon 1 was too small for primer design in the exonic region; therefore primers flanking the exonic region were designed. Real-time quantitative PCR and quantification was performed as described [ 33 ]. MSP On the 31 NB cell lines and on another series of 50 NB tumours of which 15 were included in the mutation analysis, methylation-specific PCR (MSP) was performed as described, with minor modifications [ 36 ]. MSP primers were designed using the web-based MSP design software MethPrimer [ 37 ] and checked for specificity using the methBLAST software (Pattyn et al., in preparation). Primers were designed in a CpG island close to the start of the gene (putative SDHD promotor) (chr11: 111495002–111495330: UCSC Genome Browser freeze version July 2003) (methylated forward 5'GTAGTCGGGATCGAGTATTAGTGAGTC3', methylated reverse 5'AATAAACCGAAAATCGAAAAACGAT3', unmethylated forward 5'AGTTGGGATTGAGTATTAGTGAGTTGT3', unmethylated reverse 5'ACTAAATAAACCAAAAATCAAAAAACAAT3'). Amplification mixtures (50 μl) for the PCR reaction contained 50 ng template DNA, 1× Platinum Taq PCR reaction buffer (Invitrogen), 6 mM MgCl 2 , 200 μM of each dNTP, 1.25 U Platinum Taq polymerase (Invitrogen), 3% DMSO and 300 nM of each primer. The cycling conditions comprised 4 min polymerase activation at 93°C, 40 cycles with denaturation at 93°C for 30 sec, annealing at 64°C (methylated primers) or 65°C (unmethylated primers) for 30 sec and extension at 72°C for 30 sec, and a final extension for 5 min at 72°C. SssI methylase (New England Biolabs) treated DNA, following the manufacturer's instructions and normal human genomic DNA were used as a positive and negative control respectively after bisulfite modification. Mutation analysis DHPLC analysis Intronic primers flanking the SDHD exons were designed using Primer Express v2.0 (Applied Biosystems), based on the publicly available SDHD genomic sequence (accession number AB026906) (Table 2 ). PCR reactions were performed on a PTC-200 DNA engine (MJ Research). Amplification mixtures (25 μl) contained 10 ng template DNA, 1× Platinum Taq PCR reaction buffer (Invitrogen), 2.5 mM MgCl 2 , 200 μM of each dNTP, 1 U Platinum Taq polymerase (Invitrogen) and 500 nM of each primer. The cycling conditions comprised 3 min polymerase activation at 94°C, 35 cycles with denaturation at 92°C for 20 sec, annealing at 60°C for 20 sec and extension at 72°C for 2 min, a final extension for 5 min at 72°C and a slow decrease in temperature to 25°C over 30 minutes. One μl of the PCR products was analyzed on a Ready-To-Run Agarose Gel (1.2%) (Amersham Biosciences). Denaturing high-pressure liquid chromatography (DHPLC) was performed using the Wave system (Transgenomic). The melting profile of each fragment was determined using the Wavemaker software v4.1 (Transgenomic). Crude PCR product was injected into a preheated, fully equilibrated chromatographic column for the DHPLC analysis. Exon 1 fragments were eluted at a temperature of T m (= 62.1°C)+0.7°C and T m +1.5°C. Exon 2 fragments were eluted at a temperature of T m (= 55.7°C)+4.8°C. Exon 3 fragments were eluted at a temperature of T m (= 57.4°C)-0.4°C, T m +1.1°C and T m +3.8°C. Exon 4 fragments were eluted at a temperature of T m (= 56.4°C)-0.4°C, T m +1.6°C and T m +3.2°C. Elution of the fragments was performed using standard conditions according to the manufacturer. Elution profiles were analyzed using the Wavemaker software. Sequencing Sequencing was performed on all cell lines and on tumour samples with aberrant DHPLC elution peaks (except from the noncoding region of exon 4 that was sequenced in all NB cell lines without preceding DHPLC mutation screening). Amplified fragments were purified using the Montage PCR96 filter plates (Millipore) or by excision of the fragment of interest from a 1.5% TBE-agarose gel and purification on a GenElute Minus EtBr Spin Column (Sigma-Aldrich). Cycle sequencing was performed using purified amplicons (3–10 ng), the above-mentioned primers (Table 2 ) at a concentration of 80 nM and the ABI PRISM BigDye Terminators v3.0 Cycle Sequencing Kit (Applied Biosystems), with the following thermocycling conditions: 25 cycles at 92°C for 10 sec, 55°C for 5 sec and 60°C for 3.5 min. The products were run on an automated sequencer ABI3100 (Applied Biosystems) after isopropanol precipitation. Sequence analysis was performed with the SeqScape v1.1 software (Applied Biosystems). Allelic discrimination screening for 2 sequence variants using MGB probes PCR primers and minor groove binder (MGB) probes for sequence variant IVS4-32T>C were designed using Primer Express v2.0 following the user bulletin guidelines for the design of MGB probes (Applied Biosystems): forward primer 5'TTTTTTGCAGCCAAGTTATCTGTATAG3', reverse primer 5'TGTCCAAGGCCCCTAAAGAA3', MGB probe allele 1 5'TGTGGTTTTTtATTGATG3' labelled with 6-FAM and MGB probe allele 2 5'TGTGGTTTTTcATTGAT3' labelled with VIC. To address the frequency of the sequence variant g.7876A>G (Y93C) in a normal population, the following primers and probe were designed: forward primer 5'GGCTGCTTATTTGAATCCTTGCT3', reverse primer 5'ACTTGCCAGTGACCATGAAGAGT3' and MGB probe variant allele 5'ATGGACTgTTCCCTG3' labelled with VIC. The reaction mixture contained 10 ng of DNA, 100 nM of each MGB probe, 300 nM of each primer and 1× qPCR Mastermix (Eurogentec). For the screening of the g.7876A>G variant, multiplex PCR was performed using primers and probe of the normal allele of the above-mentioned SNP (IVS4-32T>C) and primers and probe for the variant allele g.7876A>G. Reactions were performed on the iCycler Thermal Cycler (Bio-Rad) with the following thermocycling conditions: an initial activation step at 95°C for 10 min, 50 cycles of 95°C for 15 sec and 60°C for 1 min. Allelic discrimination data analysis was performed on the iCycler IQ Optical System Software v3.0a (Bio-Rad). The SNP info for the IVS4-32T>C variant was submitted to NCBI's SNP database (sn#5606973, SDHD _IVS4-32). Full-length SDHD mRNA amplification In order to investigate predicted or putative splice variants caused by the 4 bp-deletion in NB cell line N206 and SDHD sequence variants present in other cell lines, the coding region of the full-length SDHD mRNA was amplified for cell lines N206, SK-N-AS, SK-N-SH, NMB, SK-N-FI, CLB-GA, LA-N-2 and NGP, before and after puromycin treatment. RNA extraction, DNase treatment and cDNA synthesis were performed as described [ 38 ]. Subsequent PCR was performed with forward primer 5'AGGAACGAGATGGCGGTTCTC3' (exon 1) and reverse primer 5'GCTTCCACAGCATGGCAACA3' (exon 4). PCR products were run on an agarose gel, purified and sequenced using the above-mentioned protocol. The sequence information also provided evidence on the allelic mRNA expression status of SDHD . Quantification of SDHD expression using real-time quantitative RT-PCR Relative SDHD expression levels were determined using an optimized two-step SYBR Green I RT-PCR assay [ 38 ] with minor modifications in 31 cell lines, 7 normal control samples (human brain, trachea, lung, heart, breast, kidney, liver) and in laser capture microdissected foetal neuroblast cells [ 39 ]. The comparative C T method was used for quantification. PCR reagents were obtained from Eurogentec as SYBR Green I mastermixes and used according to the manufacturer's instructions. Primers in exon 3 were designed using Primer Express (see Primers Exon 3 in Table 1 ). Reactions were run on an ABI5700 (Applied Biosystems). Gene expression levels were normalized using the geometric mean of the 4 most stable internal control genes in NB (i.e. UBC , HPRT1 , SDHA and GAPD ) as reported previously [ 40 ]. Complex II activity and protein assays Enzyme activities were determined spectrophotometrically as previously described [ 41 ]. Protein amount was determined with immunoblot analysis of complex II Fp fragment as previously described [ 42 ]. Relative protein amounts of complex II compared to complex IV were measured using the TotalLab software (Amersham Biosciences). Ultrastructural analysis of mitochondria in NB cell lines Mitochondria of NB cell lines LA-N-2, SK-N-AS, CLB-GA, NGP, CHP-901, SK-N-SH, SK-N-FI, N206, SJNB-12, SJNB-8, NMB, SJNB-10 and IMR-32, breast carcinoma cell line MCF-7 and, Ewing sarcoma cell line SK-N-MC were analysed by electron microscopy. Monolayers from these cell lines were briefly rinsed twice in PBS and then immersed at room temperature in 3 % glutaraldehyde buffered with Na-cacodylate at pH 7.3 for 1 h. After rinses in this buffer with 1 % bovine serum albumin, cells were scraped off with a rubber policeman, and centrifuged with 3 % glutaraldehyde. After washing, the pellets were postfixed in 2 % buffered OsO 4 for 1 h at 4°C. Block staining in uranylacetate (UAc) in 70 % ethanol was followed by dehydration in ethanol and propylene oxide, and embedding in Epon. Ultrathin sections were counterstained with UAc and lead. At least 2 cells in each culture were photographed at a magnification of 20,000 in a Zeiss electron microscope operating at 50 KV. Per culture, 25–63 mitochondria were examined. Their projected length (largest straight distance) was measured and matrix electron density was compared to the surrounding cytosol. Electron microscopic files were made on 11 archived neuroblastic tumours. In addition, previously published cases were examined for mitochondria morphology. Results SDHD deletion, mutation and methylation analysis 11q23-deletion screening Previous karyotyping, comparative genomic hybridization (CGH) and/or M-FISH revealed 11q-deletions in 9 out of 31 neuroblastoma (NB) cell lines (CLB-GA, GI-ME-N, IMR-32, LA-N-6, NBL-S, NGP, SK-N-AS, NMB, N206) [ 30 - 32 ]. In this study, the presence of 11q23-deletions was confirmed by FISH in all these cell lines except N206 for which the deletion was located distal to the MLL locus (11q23.23) (not shown) (Table 3 ). Sequencing analysis of SDHD on 11q23 demonstrated that the allelic imbalance in NMB does not cause loss of heterozygosity (see later). No previously unnoticed submicroscopic 11q23-deletions were detected. Screening for homozygous deletions in all SDHD exons was negative for the 31 NB cell lines. In 20 of the 67 NB tumour samples, loss of heterozygosity (LOH) or allelic imbalance (AI) (AIF > 2) in the 11q23 region was found (Table 3 ): unbalanced 11q LOH (i.e. partial allelic loss of the long arm of chromosome 11) in 2/32 patients of the Ghent University Hospital (Ghent, Belgium) and in 7/35 patients of the Molecular Oncology Unit (Lyon, France) and loss of markers on both chromosome arms (indicating whole chromosome 11 loss, or co-occurrence of 11q and 11p allelic loss) in 3/32 patients of the Ghent University Hospital and 8/35 patients of the Molecular Oncology Unit (Table 3 ). The higher frequency of chromosome 11 LOH in the patient subgroup of the Molecular Oncology Unit can be explained by the selection for patient samples of high stage without MYCN amplification, in contrast to the other patient subgroup for which samples were unselected. Mutation analysis Denaturing high performance liquid chromatography (DHPLC) analysis and subsequent sequencing of the SDHD gene in 31 NB cell lines and 67 NB tumour samples revealed the presence of sequence variants in 5 NB cell lines and 4 NB tumour samples (Table 4 ). Two variants were considered as bona fide mutations (Figure 1 ). The first, a Y93C missense mutation in cell line NMB, was not detected in 135 unrelated healthy individuals. The second variant detected in NB cell line N206, represented a 4 bp deletion on the exon-intron boundary causing an exon 3 skip leading to a premature stop codon. Interestingly, both effects are located within regions that are frequently affected in paraganglioma (PGL). Unfortunately no normal or primary tumour material of the patients from which the N206 and NMB cell lines were derived was available to test whether these are germline or somatic mutations. In one patient without 11q allelic loss (F11) we observed in both tumour and constitutional DNA a TCTA insertion at position IVS2+37. However, no additional tumour material nor parental material was available for further analysis. So, it remains unclear whether this is a true mutation or a rare polymorphism. In addition, 1 new and 4 known polymorphisms were observed. The H50R variant found in cell line LA-N-2 was described as a polymorphism in several studies [ 43 - 45 ]. This is also true for the G12S change found in tumour and constitutional DNA of patient F18 [ 21 ]. The previously reported polymorphisms IVS3-29A>G [ 25 ] and S68S [ 25 , 27 , 28 , 44 , 46 , 47 ] were detected in cell lines NGP, NMB and SK-N-FI, in both tumour and constitutional DNA of patients F18 and F35, and in constitutional DNA of patient F22. In all cases, these last two polymorphism (IVS3-29A>G and S68S) were present together with the IVS4-32T>C variant, previously described by Taschner and colleagues [ 28 ]. Allelic discrimination screening in 135 unrelated individuals revealed an incidence of the IVS4-32T>C polymorphism of 4.4% (= 6/135; allele frequency 2.2%). This is similar to the incidence found in NB cell lines (3/31 = 9.7%) and NB patient constitutional DNA (3/67 = 4.5%, allele frequency = 2.2%). The presence of the IVS3-29A>G, S68S and IVS4-32T>C variants in a cell line (NGP) and two tumours (F18 and F35), in which one of both SDHD alleles has been deleted, indicates that all three variants are located on the same allele, representing a low frequent haplotype. MSP analysis SDHD promotor hypermethylation was tested for 31 NB cell lines and 50 NB patients using methylation-specific PCR (MSP). No evidence for methylation was obtained in any of the analyzed NB cases. Analysis of the 4 bp deletion in the cell line N-206 Amplification of the full-length SDHD cDNA showed that a 4 bp deletion in the intron-exon boundary in cell line N206 caused skipping of exon 3 leading to a premature stop codon. No alternative transcripts could be detected in cell lines NMB, SK-N-FI, NGP and LA-N-2 carrying basepair variants (and 3 control cell lines without sequence variants SK-N-SH, SK-N-AS and CLB-GA) when grown with or without puromycin (Figure 1 ). The above-mentioned cDNA transcript sequencing revealed that SDHD is bi-allelically expressed, thus supporting recent observations in lymphoblastoid cell lines, adult kidney and adult and fetal brain [ 19 , 22 ], but in contrast with the initially reported paternal mono-allelic expression in PGL tissue [ 22 ]. SDHD mRNA expression analysis SDHD expression levels were measured using real-time quantitative PCR in 31 NB cell lines, normal foetal neuroblast cells (16, 18 and 19 weeks gestational time) and 7 normal adult tissues (brain, heart, kidney, liver, lung, trachea and breast) (Figure 2 ). The SDHD mRNA level was significantly lower in NB cell lines compared to both normal neuroblast cells (Mann-Whitney test: P = 5.31E-06) and normal adult tissue mRNA samples (Mann-Whitney test: P = 1.49E-05). SDHD mRNA levels were significantly reduced in cell lines with 11q allelic loss and SDHD mutated cell lines (i.e. NMB and N206) (N = 9) compared to cell lines without 11q allelic loss (N = 22) (Mann-Whitney test: P = 1.49E-03). SDHD functional analysis As the SDHD gene encodes the small subunit D of the mitochondrial respiratory chain complex II we decided to assess the effect of the basepair variants on the activity of complex II of the respiratory chain by spectrophotometrical measurements in 5 NB cell lines (N206, NMB, SK-N-FI, NGP and LA-N-2) and 3 control NB cell lines without sequence variants (SK-N-SH, SK-N-AS and CLB-GA). No significant differences in complex II enzyme activity could be demonstrated. Although, in LA-N-2 a slight decrease of complex II activity was observed (data not shown). On above-mentioned cell lines and NB cell lines CHP-901, SJNB-12, SJNB-8, SJNB-10 and IMR-32, breast cancer cell line MCF7 and Ewing sarcoma cell line SK-N-MC, immunoblotting of the Fp fragment of complex II showed no significant variation in abundance among the tumour cell lines (data not shown). Ultrastructural morphology of mitochondria in NB cell lines Electron microscopic analysis of NB cell lines revealed that the morphology of the mitochondria is heterogeneous between the different cell lines, with respect to length, dilated intracrista spaces and condensation of the matrix (Table 5 and Figure 3 ). In most of the cell lines the electron dense matrix granules are absent. A striking observation are dilations of the mitochondrial intracrista spaces in most of the NB cell lines including N206 (Figure 3A ), but not NMB (Figure 3B ). Cell line LA-N-2 shows very large mitochondria (Figure 3D ). However, these observations are not the same as described for PGL, where swollen mitochondria are seen with an empty matrix and short or absent cristae [ 48 ]. In order to examine whether dilated mitochondrial cristae are a feature of many, or all NBs, we studied the mitochondria in electron micrographs from 11 archived and 22 previously published neuroblastic tumours [ 49 - 53 ]. Dilated cristae were seen in 11 tumours but they were limited to a minority of the mitochondria (2–23%), in contrast to several of the cell lines of which most mitochondria are altered. In several of the analyzed NB tumours, partially vacuolated matrices were occasionally observed. Discussion In this study, we investigated the possible involvement of SDHD in neuroblastoma (NB) tumourigenesis. In a first step, mutation and methylation analyses were performed on a large panel of NB cell lines and tumours. A total of seven sequence variants (in nine different samples) were detected of which two could represent bona fide mutations, i.e. missense mutation Y93C in cell line NMB and a 4 bp deletion in cell line N206. The Y93C sequence variant has not been reported previously and screening of 135 unrelated healthy individuals for this variant was negative. The substituted amino-acid is located within a region of the SDHD protein frequently altered due to germline mutations in paraganglioma (PGL) families (loss of Y93 [ 22 ] and two missense mutations, i.e. D92Y [ 19 , 28 , 46 ] and L95P [ 28 ]). These residues are part of the third transmembrane helix of the SDHD protein [ 54 ]. The second mutation has not been reported either. This mutation results from a 4 bp deletion in the 3' exon-intron boundary of exon 3 resulting in skipping of exon 3 leading to a transcript with a premature stop codon. The predicted truncated protein has another carboxyterminal amino-acid sequence from H56 on and its normal function is assumed to be impaired as carboxyterminal amino-acids involved in ubiquinone and heme b binding are missing (H71, D82 and Y83) and consequently the structure of the transmembrane subunit and/or association of the catalytic domain subunits SDHA and SDHB to the membrane would be disrupted [ 54 ]. The functional consequence of one sequence variant located within an intronic sequence (IVS2+37ins(TCTA)) is more difficult to evaluate due to lack of fresh tumour material, and parental DNA. Further analysis is needed in order to reveal a possible effect on splicing or RNA stability. Finally, one new and 4 known polymorphisms were detected in 5 NB cell lines and 3 tumour samples. Additional screening for homozygous deletions in all cell lines and methylation in cell lines and tumours were negative. Based upon these results, we can exclude a role for SDHD as a classical tumour suppressor gene in NB. However, the finding of two apparently bona fide SDHD mutations in NB without allelic loss of distal 11q leaves the possibility open that the gene contributes to NB oncogenesis due to haplo-insufficiency, rather than functional inactivation of both alleles. In order to investigate this possibility, we decided to perform further studies at transcript and protein level. Interestingly, SDHD expression was shown to be consistently lower in cell lines with 11q allelic loss versus NB cell lines without loss and also significantly decreased in NB cell lines as compared to normal foetal adrenal neuroblast cells of 16, 18 and 19 weeks gestational time with a mean fold difference of 3.61 between neuroblast cells and NB cell lines. A similar correlation between 11q LOH and reduced SDHD expression was recently described in colorectal and gastric cancer [ 55 ]. Our findings at mRNA transcript level, however, did not match with results obtained from further analysis at protein level. Complex II activity and quantitative protein analysis revealed no significant difference between cell lines with or without 11q allelic loss or SDHD mutation. However, measurement of complex II activity might only reflect part of the functional properties of SDHD. Also, measurement of differences in protein quantity is far less sensitive than Q-PCR at transcript levels. Therefore, these observations at present do not fully exclude SDHD involvement in NB. Finally, we also looked at the morphologic characteristics of the mitochondria as a possible clue to SDHD dysfunction. In keeping with, at best, partial loss of function of SDHD , we did not observe similar gross morphologic changes as reported for PGL with SDHD mutations (swelling with loss of matrix density and generalized rarefaction of cristae), the latter being characterized by destabilization of complex II with loss of enzymatic activity [ 48 ]. However, most of the cell lines showed dilated mitochondrial cristae. It has been demonstrated that this is a reversible phenomenon, and parallels arise in intracellular ADP/ATP ratio or low energy state [ 56 ]. Subsequent combined ultrastructural and biochemical studies from several authors indicated that dilation of cristae follows a decrease in mitochondrial membrane potential that can be provoked by various experimental procedures [ 57 , 58 ]. This configuration was detected in only a small percentage of mitochondria in archived sections of NB tumours and in sections published earlier. Morphologic analysis of mitochondria in NB thus far received little attention. The true significance of the observed mitochondrial morphological changes in NB is intriguing, but does not appear to be related to the mutations we have found. Conclusions In contrast to previous findings in PGL and PC, this study excludes a classical two hit Knudson model for SDHD involvement in NB. However, the finding of, albeit rare, bona fide mutations and reduced expression of SDHD in NB with 11q allelic loss hints at a possible haplo-insufficient contribution to tumour development. A better understanding of the different functions of SDHD, in particular its possible contribution to energy independent apoptosis involving the release of cytochrome c and procaspases, will allow further functional assays to asses how this gene contributes to tumour development in general, and the high stage NB phenotype in particular [ 59 , 60 ]. Evidence for contribution to a cancer phenotype through haplo-insufficiency has recently been obtained for a number of loci, including CDKN1B (p27 Kip1 ) [ 61 , 62 ], TP53 (p53) [ 63 ], DMP1 [ 64 ], PTEN [ 65 ], APC [ 66 ] and NKX3.1 [ 67 ]. In mouse models for some of these genes, loss or mutation of one allele increased tumour susceptibility despite expression of the remaining wild-type allele [ 68 ]. Although the present data on protein and functional level do not provide consistent evidence for the haplo-insufficient involvement of SDHD in NB, a bipartite mechanism as tumour suppressor gene for the SDHD gene, as described for the APC gene can at present not be fully excluded. Following this hypothesis, germline mutations in SDHD would predispose to PGL or PC development. Rare somatic mutations and more typically loss of one allele could contribute to the metastasizing NB tumour phenotype (and possible also other tumour types), not as an initiating step but rather as later event in tumour development. However, further evidence is needed to support the haplo-insufficient involvement of SDHD in cancer. Ultimately, knockout mice for the SDHD gene leading to haplo-insufficiency for SDHD in neuroblast progenitor cells, would be the appropriate test to evaluate this hypothesis. List of abbreviations AIF = allelic imbalance factor CGH = comparative genomic hybridization DHPLC = denaturing high performance liquid chromatography LOH = loss of heterozygosity MGB = minor groove binder MSP = methylation specific PCR NB = neuroblastoma PC = pheochromocytoma PGL = paraganglioma ROS = reactive oxygen species SDHD = succinate dehydrogenase, subunit D SNP = single nucleotide polymorphism SRO = shortest region of overlap Competing interests The authors declare that they have no competing interests. Author's contributions KDP carried out the genomic and transcriptomic studies, and drafted the manuscript. JH performed the methylation studies. JS carried out the immunoblottings and spectrophotometric analysis that was evaluated by RVC. AN performed the ultrastructural analysis that was screened and discussed by CV, FR and MP. GL and NVR collected the tumour material. JV and FS participated in the study's design and coordination. All authors have reviewed the manuscript and FS and ADP were the final editors of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517501.xml |
517717 | HER2 expression in cervical cancer as a potential therapeutic target | Background Trastuzumab, a humanized monoclonal antibody against the HER2 receptor is currently being used in breast and other tumor types. Early studies have shown that a variable proportion of cervical carcinoma tumors overexpress the HER2 receptor as evaluated by diverse techniques and antibodies. Currently it is known that a tumor response to trastuzumab strongly correlates with the level of HER2 expression evaluated by the Hercep Test, thus, it seems desirable to evaluate the status of expression of this receptor using the FDA-approved Hercep Test and grading system to gain insight in the feasibility of using trastuzumab in cervical cancer patients. Methods We analyzed a series of cervical cancer cell lines, the primary tumors of 35 cases of cervical cancer patients and four recurrent cases, with the Hercep Test in order to establish whether this tumor type overexpress HER2 at level of 2+/3+ as trastuzumab is currently approved for breast cancer having such level of expression. Results The results indicate that only 1 out of 35 primary tumors cases overexpress the receptor at this level, however, two out of four recurrent tumors that tested negative at diagnosis shifted to Hercep Test 2+ and 3+ respectively. Conclusions The low frequency of expression in primary cases suggests that trastuzumab could have a limited value for the primary management of cervical cancer patients, however, the finding of "conversion" to Hercep Test 2+ and 3+ of recurrent tumors indicates the need to further evaluate the expression of HER2 in the metastatic and recurrent cases. | Background Cervical carcinoma is a leading cause of death in women of reproductive age worldwide, particularly in developing countries. While curable in early stages, the treatment results of locally advanced disease are unsatisfactory. The current standard of treatment -cisplatin-based chemoradiation- fails to cure at least 15% to 45% of bulky IB to IIIB patients, and in addition, multimodality treatment incorporating chemotherapy, surgery and radiation at its best is unlikely to substantially increase the cure rate. Because of this, the logical step to follow is the testing of molecular targeted therapies trying to improve the prognosis of cervical cancer patients [ 1 ]. Human papillomavirus infection is recognized as the stronger etiological factor for the development of this tumor; however, overexpression of the epidermal growth factor receptor family members is also common and seems to play an important oncogenic role [ 2 ]. HER2 (also known as c-erbB-2) is a transmembrane receptor protein with tyrosine kinase activity that belongs to this family and it is overexpressed in a number of solid tumors. Its overexpression and prognostic significance in breast cancer led to the development and approval of the use of trastuzumab (Trastuzumab, Genentech, South San Francisco, CA), a recombinant monoclonal antibody to HER2, for the treatment of patients with metastatic breast carcinomas overexpressing HER2 [ 3 ]. Until more recently, poor standardization in HER2 status evaluation precluded reliable comparison of overexpression rates in different tumors. A source of variability in results not only comes from methodological variations in tissue processing (time to fixation, duration of fixation, denaturation, heating, antigen retrieval, the staining procedure) and grading scores but also from the antibody used. This issue was addressed by Press et al., who showed extremely variable results in 187 breast cancer specimens evaluated with 7 polyclonal and 21 monoclonal antibodies [ 4 ]. However, standardized methodologies have been introduced recently for these analyses, and have identified frequencies of 51%, 44%, 26% and 25% in Wilm's tumor, bladder, pancreatic and breast carcinoma, respectively. Other tumors tested had frequencies below 20% [ 5 ]. Before the introduction of the Hercep Test, it was known that a variable subset of cervical carcinomas ranging from 8% to 77% express HER2 as evaluated by diverse methods [ 6 - 14 ] and that in some studies its overexpression has shown to confer a worse prognosis [ 7 - 9 , 13 ]. Because these results on HER2 expression in cervical cancer were obtained before the standardization required in breast cancer, we wanted to investigate the expression status of HER2 using the Hercep Test in a series of cervical carcinoma cell lines, primary tumors of locally advanced cervical cancer cases and in four recurrent tumors of these patients. Methods Tumor specimens Thirty-five paraffin-embedded tumor tissues from patients FIGO staged as IB2 to IIIB, treated with standard radiation concurrent with weekly cisplatin. Diagnosis was made on the basis of routine hematoxilin-eosin examination under light microscopy according to the World Health Organization criteria. Tumor specimens at diagnosis were taken before any treatment was instituted whereas the tumors samples from the four recurrent cases were also taken before patients received any second line therapy. Cell lines and reagents DMEM culture media and Fetal Calf Serum were purchased from Gibco BRL Life Technologies (Grand Island, New York). HeLa, CasKi, SiHa and C33A carcinoma cell lines were obtained from the ATCC. The cell line ViBo established from a Mexican patient with cervical cancer was kindly provided by Dr. Monroy (FES Zaragoza, UNAM, Mexico City). Cells were grown in DMEM supplemented with 10% FCS at 37°C and 5% CO 2 . Cell lines were grown on two-chamber polysterene vessel Falcon ® (Becton Dickinson, NJ.) and subsequently formalin-fixed for 24 hrs at room temperature, then rehydrated in graded ethanol. Afterwards immunochemistry was performed as below described. Hercep test Hercep Test was performed following the manufacturer's guidelines of HER2 protein expression as follows. Sections were deparaffinized in xylene and rehydrated through graded ethanols to distilled water. The sections were immersed in Dako Epitope Retrieval Solution (10 mM citrate buffer, pH6) that had been preheated to 95°C in a water bath and then heat-treated at 95°C for 40 min. After a 20-minute cooldown period at room temperature, the sections were washed with Dako Wash Buffer, a procedure that followed every subsequent incubation. Endogenous peroxidase was blocked with Dako Blocking Buffer (0.3% hydrogen peroxide containing 15 mM sodium azide) for 5 min at room temperature. The sections were incubated with the primary polyclonal antibody, an affinity-purified rabbit antihuman HER2 antibody supplied in the kit, for 30 min at room temperature. Bound primary antibody was labeled by incubating the slides with the Dako Visualization reagent (horseradish peroxidase-labeled dextran polymer conjugated to affinity-purified goat antirabbit immunoglobulins in Tris-HCl) for 30 min. Color development was achieved with 3,3'-diaminobenzidine (DAB) for 10 min. The sections were counterstained with hematoxylin and eosin. To confirm validation of the staining run, control cell slides, which were provided in the kit and consisted of three pelleted, formalin-fixed, paraffin-embedded human breast cell lines with known HER2 positivity (MDA-231: 0; MDA-175: 1+; SK-BR-3: 3+), were also stained simultaneously. In the negative controls, the primary antibody was replaced by normal rabbit serum (Dako Negative Control Reagent) for the HER2 primary antibody. The antibody used in Hercep Test did not exhibit cross-reactivity to HER3 and HER4 in western blot analysis. Following the FDA scoring guidelines for breast carcinomas, only membrane staining intensity and pattern were evaluated using the 0–3+ scale as illustrated in the Hercep Test kit scoring guidelines (0 for no staining at all or membrane staining in less than 10% of the tumor cells; 1+ for only partial, weak staining of the cell membrane of more than 10% of the tumor cells; 2+ for moderate staining of the complete cell membrane in more than 10% of the tumor cells; 3+ for intense staining of the complete membrane in more than 10% of the tumor cells). The analysis was performed by a pathologist (VP-S) familiarized in the use of Hercep Test for breast cancer patients. In accordance with the Hercep Test kit guide, HER2 overexpression was assessed as negative for scores of 0 or 1+ and positive for scores of 2+ and 3+. FISH in the four recurrent cases Amplification of Her-2/neu was evaluated using the Path-Vysion DNA Probe Kit (Vysis), which uses a dual-color probe for determining the number of copies of both Her-2/neu (orange) and the chromosome 17 centromeres (green). The kit was used following the manufacturer's instructions with a few minor modifications. Slides containing 5μ thick paraffin-embedded tissue sections of studied cervical tumor cases and a known Her-2/neu amplified breast tumor were placed on a slide warmer overnight at 58°C, followed by deparaffinization in Xilol, dehydration in 100 ethanol, and drying on a slide warmer at 45 to 50°C. Slides were then pretreated with 0.2 N hydrochloric acid for 20 minutes, followed by washes in purified water and immersion in Vysis wash buffer. They were subsequently immersed in Vysis protease solution at 37°C for 10 minutes, washed in Vysis wash buffer, and dried on the slide warmer. The slides were then immersed in 10% buffered formalin at room temperature for 10 minutes, immersed in Vysis wash buffer, and dried on the slide warmer. Sections were denatured by placing the slides in formamide for 5 minutes at 72°C followed by dehydration in 70, 85 and then 100% ethanol. Slides were then dried on a slide warmer, and 10 μl of probe was applied. They were then coverslipped, sealed and placed in a prewarmed humid incubation chamber at 37°C for 21 hours. This was followed by immersion in prewarmed postwash solution at 72°C for 2 minutes. The slides were air-dried, and a 4',6-diamidino-2-phenylindole (DAPI) counterstain was applied. The scoring system used is described in detail in the manufacturer's instruction. A minimum of 60 nuclei were scored by each of 2 observers using a Zeiss Axioskop-2 fluorescent microscope with V.2 filter. The ratio of Her-2/neu signals (orange) to chromosome 17 centromere signals (green) was determined with ratios of <2.0 considered nonamplified and those ≥ 2.0 amplified. Results The immunohistochemical expression of HER2 in the primary tumors of 35 patients at diagnosis was evaluated. Accordingly, these patients had no received any previous anticancer therapy; their mean age was 40.8 years; 5 were staged as IB2-IIA, 14 as IIB and 16 as IIIB; 31 and 4 were histologically classified as squamous and adeno/adenosquamous respectively. Overexpression of HER2 was demonstrated in only one out of 35 cases, which had a score of 3+ (not shown). The remaining cases were interpreted as negative [score of 0]. The case with HER2 overexpression at diagnosis was a 56-year old woman diagnosed with a FIGO stage IIB large cell poorly differentiated squamous cell carcinoma, who received treatment with 6 weekly courses of cisplatin concurrent with external beam radiation and brachytherapy. She is currently free of disease at 44 months of follow-up. At a median follow-up time 40 months, seven patients have relapsed. HER2 expression at recurrence could only be analyzed in four of these seven relapsed patients in whom whose recurrent disease was histopathologically confirmed. Two of these four tested positive with a staining intensity of 2+ and 3+ respectively, (Figures 1 and 2 ), both cases were squamous cell carcinomas and tested negative in the pretreatment surgical specimen The five cervical cancer cell lines were negative. None of the four recurrent cases tested by FISH were HER2 amplified (Figure 3 ). Discussion Molecular targeted therapies are currently being tested in a variety of tumor types with promising results. Because HER2 overexpression occurs and is related to a worse prognosis in cervical cancer, [ 7 - 9 , 13 ], its blockade with trastuzumab could potentially have therapeutic value. This monoclonal antibody is currently widely used in metastatic breast cancer and is being evaluated in an adjuvant setting as well as in a variety of tumor types [ 3 , 15 - 17 ], Based on the fact that the efficacy of this antibody is strongly associated to the level of HER2 expression in the primary tumor, the FDA approved the Hercep Test in the aim to grade the expression level so that only those patients whose tumors exhibit a 2+/3+ levels are candidates to trastuzumab therapy, though currently in most centers, tumors expression of 2+ is considered undeterminate therefore these cases are also evaluated by FISH analysis [ 18 ]. Previous reports on cervical cancer using non-standardized methods for HER2 expression showed that up to 77% of cases express the receptor and that in general HER2 expression predominates in adenocarcinoma and adenosquamous carcinoma histologies [ 6 - 14 ] In this work, using the Hercep Test with its corresponding guidelines for evaluation, we found contrastating results as none of the cell lines expressed HER2 and only a single tumor of squamous histology (1 out of 35) expresses this oncoprotein at a level of 3+. Such a discrepancy does not seem to be limited to this tumor type. For instances, in ovarian clear cell carcinoma a 43% of overexpression was reported utilizing systems other than Hercep Test [ 19 ], however, when evaluated with this standardized test, only 1 out of 17 tumors expressed 3+ [ 20 ]. Likewise, the proportion of patients with 2+/3+ expression level of HER2 with the Hercep Test is uniformly low in tumor such as lung [ 21 ], colorectal carcinomas [ 22 ], gallbladder [ 23 ], and melanoma [ 24 ]. A variety of factors such as the kind of antibody used, the technique per se, and scoring criteria may explain such phenomenon and its clarification requires further studies. A recent paper by Bellone et al., have reported that a substantially higher proportion of cervical cancer cells lines either established from fresh tumors or commercial ones (including CasKi, SiHa, HeLa and C33A which are negative by immunochemistry) express the receptor when evaluated by flow-cytometry and are growth inhibited when incubated with trastuzumab or trastuzumab plus IL-2 [ 25 ]. These data led them to suggest the targeting the HER in cervical cancer could be more effective than the indicated by low immunohistochemical expression [ 25 ]. However, it is largely known that in breast [ 26 ] and more recently in lung cancer [ 27 ], tumor responses are almost confined to those with a 3+ level of expression. For instances, in a recent published study in 111 assessable breast cancer patients, the response rate to single agent trastuzumab for those expressing 3+ versus 2+ was 35% and 0% respectively [ 26 ], while in lung cancer, a phase II trial of gemcitabine-cisplatin with or without trastuzumab in HER2-positive patients, yet there was not overall differences in response between both arms, the benefit was limited to those with 3+ of expression with the Hercep Test. Accordingly, five out of six patients with such level of expression receiving trastuzumab plus gemcitabine-cisplatin showed response [ 27 ]. These data argue against the potential usefulness of trastuzumab in cervical cancer patients with HER expression that can only be detected by flow cytometry [ 25 ]. On the other hand, the HER2 expression in breast cancer is relatively stable, with 95% concordance between the HER2 status of primary and metastatic lesions, being rare a shift from positivity in the primary to negativity in the metastases [ 5 ]. Conversely, 6% of breast cancer patients whose primary tumors are HER2 negative, convert to high expression (Hercep Test 3+) in their metastases [ 28 ]. Such behavior is in line with experimental observations that receptor activation potentiates tumor cell motility, protease secretion and invasion, and also modulates cell cycle checkpoint function, DNA repair, apoptotic responses and multidrug resistance [ 29 , 30 ]. The findings of "conversion to positive" in cells of recurrent cervical tumors showed by us and other authors [ 25 , 31 ] strongly suggest that expression of HER2 may have a role in tumor resistance and progression as shown in experimental models, and therefore its targeting in recurrent cervical cancer could have therapeutic value. It is remarkable the finding that none of the four recurrent cases, including the two that converted to IHC positive analyzed by FISH showed HER2 gene amplification. This result is unlikely to be a false negative as the green signal was perfectly observed in most of the cells. Previous studies in cervical cancer have shown that the frequency of gene amplification as determined by FISH is low irrespective of tumor histology. Mark et al., reported only 2 out of 23 cases amplified using the Her-2/neu FISH probe (Vysis, Inc., Downers Grove, IL) both of which were adenocarcinomas [ 32 ]. In a more recent study looking at DNA copy number of cervical adenocarcinomas, it was found that despite more than 50% of patients had chromosome 17q copy number gains, only 9% (2 out of 22) of these tumors showed an HER-2/neu protein over-expression at the level of 2+ with the Hercep test. These findings suggest that amplification of HER-2/ neu is rare in cervical adenocarcinomas and that low level chromosome 17q copy number gains are not associated with HER-2/ neu overexpression [ 33 ]. Such overexpression without gene amplification could result from transcriptional deregulation leading to increased receptor expression [ 34 ] and is not a rare phenomenon in breast carcinoma [ 35 ]. Conclusions In conclusion, our study suggest that the clinical usefulness of anti-HER2 antibodies in the primary treatment of cervical cancer patients may be limited due to the low frequency of HER overexpression, nevertheless, it is desirable to further test a larger number of recurrent cervical cancer patients by IHC and FISH analyses regardless of the histological type, as a start point for clinical trials design using trastuzumab. Competing interests None declared. Authors'contributions A C-B, AG-F, carried out the tissue culture work and immunohistochemical analysis; VP-S and T V-C interpreted the histological data; MC critically analyzed and participated in manuscript; CP, contribute with the clinical data; SV performed the FISH analysis; and AD-G conceived the study and wrote the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517717.xml |
545079 | The genetics of ray pattern variation in Caenorhabditis briggsae | Background How does intraspecific variation relate to macroevolutionary change in morphology? This question can be addressed in species in which derived characters are present but not fixed. In rhabditid nematodes, the arrangement of the nine bilateral pairs of peripheral sense organs (rays) in tails of males is often the most highly divergent character between species. The development of ray pattern involves inputs from hometic gene expression patterns, TGFβ signalling, Wnt signalling, and other genetic pathways. In Caenorhabditis briggsae , strain-specific variation in ray pattern has provided an entrée into the evolution of ray pattern. Some strains were fixed for a derived pattern. Other strains were more plastic and exhibited derived and ancestral patterns at equal frequencies. Results Recombinant inbred lines (RILs) constructed from crosses between the variant C. briggsae AF16 and HK104 strains exhibited a wide range of phenotypes including some that were more extreme than either parental strain. Transgressive segregation was significantly associated with allelic variation in the C. briggsae homolog of abdominal B , Cb-egl-5 . At least two genes that affected different elements of ray pattern, ray position and ray fusion, were linked to a second gene, mip-1 . Consistent with this, the segregation of ray position and ray fusion phenotypes were only partially correlated in the RILs. Conclusions The evolution of ray pattern has involved allelic variation at multiple loci. Some of these loci impact the specification of ray identities and simultaneously affect multiple ray pattern elements. Others impact individual characters and are not constrained by covariance with other ray pattern elements. Among the genetic pathways that may be involved in ray pattern evolution is specification of anteroposterior positional information by homeotic genes. | Background A fundamental problem of morphological evolution is how does microevolution relate to macroevolution [ 1 ]. Are variation and selection within species sufficient to account for genetic divergence between species? One approach to this problem has been comparative developmental genetic studies in closely related species. This approach is complicated by developmental redundancy and cryptic variation [ 2 - 4 ]. Developmental redundancy occurs in species pairs in which similar adult morphologies are attained through distinct developmental processes. For example, in the nematodes Caenorhabditis elegans and Oscheius tipulae , cells in the vulval equivalence group that do not participate in vulval development are eliminated through fusion with the multinucleated syncytial epidermis [ 5 - 8 ]. In Pristionchus pacificus , that same outcome is achieved through apoptosis [ 9 ]. Cryptic variation occurs in species pairs in which the same developmental process is regulated through divergent genetic mechanisms. For example, Drosophila melanogaster and D. simulans have similar numbers and patterns of bristles. Hybrids have fewer bristles than either parental species [ 10 , 11 ]. Thus, the conserved bristle phenotypes of D. melanogaster and D. simulans mask cryptic variation in the genetic regulation of bristle pattern. Another approach has been the study of morphological variation within species. In the butterfly Bicyclus anynana , expression patterns of distalless ( dll ), engrailed ( en ), and spalt ( sal ) coincide with eyespot coloration patterns [ 12 , 13 ]. Moreover, allelic variation in distalless has been associated with size variation in eyespots [ 12 ]. Thus, evolution of eyespot patterns may have resulted from selection for variant alleles of dll , en , and sal . Consistent with this model, conservation of the expression patterns of these genes in developing eyespots has been demonstrated in multiple butterfly species [ 13 ]. Developmental variation also has been characterized in several nematode species. For example, variant patterns of cell division in the ventral epidermis have been described in C. elegans , C. briggsae , and O. tipulae [ 14 ]. Another promising model for microevolutionary studies of morphological evolution is ray pattern variation in rhabditid nematodes. The rays are male-specific peripheral sense organs that mediate mating behavior [ 15 - 17 ]. In most rhabditid species there are nine bilateral pairs of rays embedded within the copulatory bursa of the tail [ 17 ]. The pattern of rays; their anteroposterior placement and the dorsoventral position of their sensory endings, generally are constant within species but often are the most divergent character between species [ 18 ]. Ray pattern in adult males is determined by cell contacts that form between ray structural cells and the surrounding cells of the lateral epidermis in L4 larvae [ 19 , 20 ]. These contacts in turn are determined by the specification of 'ray identities' [ 21 ]. In Caenorhabditis elegans , ray identities are specified through the integration of several regulatory inputs including: positional information from homeotic genes [ 22 - 26 ]; TGF-beta-like signalling [ 27 - 29 ]; Wnt signalling [ 25 ]; and ephrin/semaphorin signalling [ 30 ]. The ray pattern of Caenorhabditis briggsae differs from that of C. elegans in the placement of ray 3 [ 31 , 32 ]. In C. elegans males, ray 3 is located at the cloaca and is separate from from all other rays. In the canonical C. briggsae ray pattern, ray 3 is located in a posterior cluster of rays 3–6 and frequently is fused with ray 4. The C. elegans ray pattern is shared with several other Caenorhabditis species and is ancestral to the Elegans-group [ 33 ], a monophyletic clade that includes C. briggsae [ 34 - 36 ]. The C. briggsae ray pattern is mimicked by several C. elegans mutations including mutations in homeotic genes or in genes that regulate homeotic gene expression patterns [ 21 , 22 , 26 , 37 , 38 ]. Thus, the derived C. briggsae ray pattern may have arisen through changes in the specification of anteroposterior positional identities. It now is possible to address this hypothesis as variant C. briggsae strains that express an ancestral ray pattern at high frequencies have been identified [ 39 ]. In this paper, the segregation of ray pattern phenotypes in crosses between C. briggsae strains is described. Results The elements of ray pattern The male-specific rays of rhabditid nematodes are embedded within a lateral fold of cuticle called the bursa or tail fan [ 19 ] (Figure 1 ). The sensory endings of most rays are attached to and open through the surface of the bursa. Ray pattern refers collectively to the anteroposterior positions of each ray, the surface (dorsal, ventral or medial) through which their sensory endings are exposed, and whether or not individual rays are fused with each other. Rays also differ in regard to neurotransmitter usage [ 5 , 21 , 40 ]. Mutations that affect ray pattern also affect neurotransmitter usage indicating that multiple properties of rays arise through the specification of 'ray identities' [ 21 , 24 ]. Figure 1 Ray patterns of C. briggsae and C. elegans . Ventral views of a) C. elegans and b) C. briggsae male tails. Anterior to the left. Left side up. Bilateral pairs of rays are numbered from anterior to posterior. a) C. elegans pattern in which ray 3 is separate from all other rays. This pattern is referred as a 2(1)3+3 pattern. b) C. briggsae pattern in which ray 3 is clustered with rays 4 – 6. This pattern is referred to as a 2/4+3 pattern. In this pattern ray 3 may be either free (right side) or fused with ray 4 (left side). The 2(1)3+3 pattern is ancestral to the Elegans-group, a monophyletic clade that includes C. elegans and C. briggsae [34]. The derived ray pattern of C. briggsae entails the posterior displacement of ray 3 from a position level with the cloaca to the post-cloacal cluster of rays 4 – 6 and the frequent fusion of ray 3 with ray 4 [ 31 , 32 , 34 ]. This ray pattern is exhibited in nearly all males of C. briggsae strains AF16 and VT847 [ 39 ]. Ray pattern in C. briggsae strains HK104, HK105, and PB800 is more variable. These strains exhibit the derived and ancestral ray patterns at approximately equal frequencies [ 39 ]. Segregation of C. briggsae ray pattern phenotypes The genetic basis of ray pattern variation in C. briggsae was characterized through the segregation of ray pattern phenotypes in a set of recombinant inbred lines (RILs). These RILs were constructed from a cross between strains AF16 and HK104. Individual RILs were established from F2 progeny of this cross. RILs were inbred, one hermaphrodite per generation, through F11. Based on this degree of inbreeding, 99.9% of loci in each RIL should be homozygous. RILs were scored for two aspects of ray pattern; the position of ray 3 and the fusion of rays 3 and 4 (Figure 2 ). Figure 2 Segregation of ray pattern phenotypes in C. briggsae RILs. a) Scatter plot comparing frequencies of derived character states for the position of ray 3 (Y-axis) and fusion of rays 3 and 4 (X-axis) in RILs. Each point represents an individual strain for which a minimum of 100 sides were scored for ray pattern. Parental strains, AF16 and HK104 represented by red square and red diamond, respectively. RILs represented by closed circles. Correlation coefficient, r, for ray position and fusion equaled 0.80. b) Frequency distributions for derived character states of ray 3 position (black bars) and ray 3–4 fusion (red bars) among RILs. Several RILs exhibited ancestral or derived phenotypes at frequencies more extreme than either parental strain (Figure 2a ). This was true for both the position of ray 3 and for fusions of rays 3 and 4. For ray 3 position, one quarter of the RILs exhibited phenotypes more extreme than either parental strain. For ray fusions, half of the RILs were more extreme than the parental strains. Such transgressive segregation is best explained through the presence, in both AF16 and HK104, of alleles at some loci that promoted ancestral character states and alleles at other loci that promoted derived character states. The high frequency of RILs with extreme phenotypes indicated that both parental strains likely were fixed for antagonistic alleles at multiple loci. A relatively strong correlation was observed between variation in the position of ray 3 and its fusion with ray 4 (r = 0.797; Figure 2a ). This correlation was highly significant (p = 2.5 × 10 -23 ). This was expected as rays 3 and 4 could not have fused unless they were adjacent to each other [ 19 ] and because the placement of rays and fusion between rays have been considered to be pleiotropic phenotypes derivative of the specification of ray identities [ 19 , 22 - 25 , 27 - 30 ]. If anything, it was surprising that the correlation was not stronger. Based on the observed correlation coefficient, approximately one third of the variation in ray fusion frequency was independent of variation in the position of ray 3. This was readily apparent when the frequency distributions of these two ray pattern elements were compared (Figure 2b ). The frequency distribution for the placement of ray 3 was highly skewed toward the derived phenotype. The frequency distribution for fusions of rays 3 and 4 was much broader and was only slightly skewed. The differences in the shapes of these distributions were significant (Kolmgorov-Smirnov, D = 0.4396, p < 0.001). Neither the frequency distribution for the placement of ray 3 nor that for the fusion of ray3 to ray 4 were normal (p = 0.00 and p = 0.03, respectively; Figure 2b ). The frequency distribution for the placement of ray 3 was highly skewed toward the derived phenotype. This result was inconsistent with the placement of ray 3 being governed strictly by additive affects. More likely, the placement of ray 3 was regulated by epistasis. Twentynine per cent of RILs exhibited the most extreme phenotype (Figure 2b ). Fixation of derived alleles at as few as two major-effect genes could have been sufficient to ensure a posterior localization of ray 3 at this frequency. The frequency distribution for fusions of rays 3 and 4 was very broad and and only slightly skewed. This was consistent with ray fusion being a complex character with inputs from multiple developmental processes. At least one of these processes was shared with ray positioning; rays 3 and 4 could not have fused if they were not adjacent. Association of ray pattern with allelic variation in homeotic genes The derived C. briggsae ray pattern may have evolved through changes in homeotic gene expression patterns [ 33 , 39 ]. The homeotic genes most likely to affect ray pattern are mab-5 and egl-5 . These genes are expressed in the posterior body and tail regions of C. elegans [ 40 ] and mutations in them can alter ray pattern [ 22 ]. Allelic variants that affect the size of the first intron of Cb-egl-5 have been identified (Figure 3 ). The AF16::HK104 RILs were genotyped for these variants to test Cb-egl-5 for association with ray pattern variation [see Additional File 1 ]. Figure 3 Allelic variation of Cb-egl-5 . Cb-egl-5 amplification products of 1) AF16; 2) PB800; 3) HK104; 4–17) selected RILs; 18) an HK104/AF16 heterozygote. The expected amplification product size based on the C. briggsae AF16 genome sequence was 1,723 bp. m) Marker DNA, sizes of selected markers as indicated. Significant associations were observed between Cb-egl-5 allelic variants and both the position of ray 3 and the fusion of ray 3 to ray 4 (Table 1 ). These associations were transgressive; the HK104 allele of Cb-egl-5 cosegregated with derived phenotypes, the AF16 allele with ancestral phenotypes. Allelic variants in Cb-mab-5 have not been identified. However, the Cb-mab-5 (=CBG00029) and Cb-egl-5 (=CBG00023) are located within 60 kb of each other [ 41 , 42 ]. Because of this close physical linkage, allelic variants in these genes very likely cosegregated. Thus, allelic variation in Cb-mab-5 , Cb-egl-5 , and/or other linked loci may have been responsible for observed transgressive associations. Table 1 Cosegregation of Cb-egl-5 with ray pattern phenotypes. allele 1 phenotype AF16 HK104 p value ray position 0.81 0.90 6.2 × 10 -4 ray fusion 0.42 0.68 4.2 × 10 -5 1 Mean frequency of derived character states exhibited in RILs homozygous for either parental Cb-egl-5 allele. mip-1 marker-assisted introgression The segregation of phenotypes in the RILs indicated that multiple major-effect and additive loci were involved in ray pattern variation in C. briggsae . Because a high density recombination map for C. briggsae has not yet been constructed, it is not possible to identify these loci through QTL analyses. However, a limited number of mutations with visible phenotypes have been mapped to C. briggsae chromosomes [B. Gupta, pers. comm., [ 43 ]]. These mutations all were generated in an AF16 background. One such mutation defines the gene mip-1 . mip-1 very likely is the C. briggsae homolog of C. elegans unc-22 [D. Baillie, pers. comm.]. In C. elegans , unc-22 is located on chromosome IV and is linked to several genes known to regulate homeotic gene expression patterns, e.g. lin-49 which encodes a bromodomain protein thought to be involved in chromatin remodeling [ 26 ]. mip-1 marker-assisted introgression was used to determine if any genes linked to it were involved in ray pattern variation in C. briggsae . Four C. briggsae strains were constructed in which HK104 DNA, in the region of mip-1 , has been introgressed into an otherwise AF16 background. This was accomplished through a series of backcrosses that were initiated by mating HK104 males to mip-1 (AF16) hermaphrodites. For each introgressed strain, F1 through F6 males were crossed to mip-1 (AF16) hermaphrodites. Wild-type F7 hermaphrodites were selected and propagated by self-fertilization. From each F7 hermaphrodite, multiple wild-type F8 hermaphrodites were picked. Homozygous strains were established from F8 hermaphrodites that segregated only wild-type progeny. From each set of backcrosses, a single introgressed strain was retained. These introgressed strains were scored for the position of ray 3 and for ray 3–4 fusions (Figure 4 ). The ray patterns of all four introgressed strains differed significantly from AF16 both in the placement of ray 3 and in the frequency with which ray 3 fused to ray 4 (Table 2 ). Significant differences also were apparent between some pairs of introgressed strains, most notably between PB1060 and PB1065. PB1060 and PB1065 did not differ in the placement of ray 3 but only in the frequency with which ray 3 fused to ray 4 (Figure 4 ; Table 2 ). Thus, it appears that allelic variation in at least two genes linked to mip-1 is involved in ray pattern variation. One of these genes affects the position of ray 3 and possibly the frequency of ray fusion. The HK104 allele of this gene was present in all mip-1 introgressed strains. The other gene affects only the frequency of ray fusion. The HK104 allele of this gene was present in PB1065 but not in PB1060. As more C. briggsae mutant strains become available, it should be possible to identify these genes through additional introgression studies coupled with genotypic characterizations of introgressed DNA. Table 2 Comparison of mip-1 introgressed lines. p values for reciprocal chi-squared tests 1 AF16 PB1060 PB1061 PB1062 PB1065 ray pattern 2 AF16 --- 9.6 × 10 -30 3.3 × 10 -54 6.5 × 10 -32 5.3 × 10 -46 PB1060 7.9 × 10 -4 --- 0.031 0.093 1.2 × 10 -5 PB1061 2.2 × 10 -7 0.026 --- 0.367 0.011 PB1062 2.8 × 10 -6 0.092 0.293 --- 0.091 PB1065 2.3 × 10 -9 1.3 × 10 -4 0.038 0.151 --- ray position 3 AF16 --- 6.9 × 10 -4 1.5 × 10 -5 3.6 × 10 -4 3.2 × 10 -4 PB1060 1.32 × 10 -29 --- 0.068 0.72 0.67 PB1061 6.4 × 10 -53 0.053 --- 0.12 0.14 PB1062 8.3 × 10 -30 0.73 0.16 --- 0.95 PB1065 1.65 × 10 -36 0.66 0.14 0.95 --- ray fusion 4 AF16 --- 0.13 5.3 × 10 -3 3.1 × 10 -3 9.8 × 10 -6 PB1060 0.013 --- 0.061 0.033 3.1 × 10 -5 PB1061 4.74 × 10 -6 0.057 --- 0.80 0.029 PB1062 9.37 × 10 -7 0.030 0.80 --- 0.052 PB1065 1.33 × 10 -16 1.59 × 10 -6 0.013 0.028 --- 1 Probabilities in each column were determined using frequencies of different ray patterns in each strain (column head) as the null hypothesis. 2 p values for the complete ray pattern (3 posterior and fused, 3 posterior not fused, 3 anterior). 3 p values for ray placement (anterior vs posterior). 4 p values for fusion of rays 3 and 4 when ray 3 is in a posterior position. Figure 4 Comparisons of ray pattern phenotypes in mip-1 introgressed strains. Frequencies of ray pattern phenotypes exhibited in AF16 and four mip-1 introgressed strains. Black bars represents ray 3 in a posterior position and fused with ray 4. Red bars represents ray 3 in a posterior position but not fused with ray 4. White bars represents ray 3 in an anterior postion. Discussion Ray pattern in C. briggsae varies with respect to the placement of ray 3 and fusions of ray 3 to ray 4. Ancestral states for these characters in the Elegans-group of Caenorhabditis are an anterior location, level with the cloaca, and the absence of ray fusions [ 34 ]. Derived states are a posterior location, clustered with rays 4 through 6, and fusion of rays 3 and 4. An unexpected result was the incomplete correlation between the position or ray 3 and its fusion with ray 4. In C. elegans , mutations that alter ray position have been accompanied by ray fusion. For this reason, ray position and ray fusion were thought to be pleiotropic phenotypes that arose from the specification of ray identities [ 19 , 22 - 25 , 30 ]. Because of this, it was expected that ray pattern evolution would involve changes in suites of covariant characters rather than independent modification of individual ray pattern elements. However, only two-thirds of variation in ray fusion resulted from variation in ray position (r 2 = 0.635). Moreover, evidence for a gene affecting only ray fusion was obtained from comparisons of ray patterns exhibited by the mip-1 introgressed strains. Hence, variation in ray pattern evolution is not wholey constrained by the specification of ray identities and other ray pattern elements, such as neurotransmitter usage, also may vary independently. A similar pattern of partial constraint and flexibility has been observed for variation in eyespots size in the butterfly Bicyclus anynana [ 12 ]. Two haplotypes of C. briggsae have been described [ 44 ] and variation in ray pattern follows haplotype structure [ 39 ]. Strains in haplotype 1, including AF16, exhibit almost exclusively a derived ray pattern. Strains in haplotype 2, including HK104, exhibit derived and ancestral ray patterns at equal frequencies. One interpretation of these results is that full expression of the derived ray pattern never became fixed within haplotype 2. However, a C. briggsae -like ray pattern also has been reported for C. clavopapillata [ 45 ], another species within the Elegans-group. C. clavopapillata has not been observed since its first description and some authors have considered it and C. briggsae to be synonymous [ 34 ]. If C. clavopapillata is distinct from C. briggsae , the posterior position of ray 3 and its frequent fusion with ray 4 may be ancestral for these two species. This would make the C. elegans -like ray pattern in haplotype 2 an atavistic character. It should be possible to discriminate between these two models either through the characterization of additional C. briggsae strains or through the redescription and molecular characterization of C. clavopapillata . Regardless of their evolutionary history, haplotypes 1 and 2 provided an entrée to the genetics of morphological variation of ray pattern in C. briggsae . The relatively slight difference between the AF16 and HK104 phenotypes hid a wealth of genetic variation. This was evident in the nearly continuous variation exhibited in RILs for both the position of ray 3 and its fusion with ray 4. This variation included many RILs with phenotypes more extreme than either parental strain. Such transgressive segregation is common in both plants and animals and is thought to arise through fluctuating selection and/or through stabilizing selection at minor QTL when directional selection at major QTL overshoots a phenotypic optimum [ 46 ]. The transgressive segregation of ray pattern phenotypes may have resulted from selection on homeotic gene expression patterns. In C. elegans , ray 3 precursor cells are born at the junction of the mab-5 and egl-5 expression domains [ 23 , 47 ]. These homeotic genes are required for the specification of positional identities in the posterior body and tail regions, respectively [ 47 , 48 ] and some mutations in them cause the C. elegans ray pattern to phenocopy that of C. briggsae [ 22 , 26 ]. We have demonstrated a significant transgressive association between allelic variation at Cb-egl-5 and variation in ray pattern. As Cb-egl-5 and Cb-mab-5 are closely linked, variation in either or both of these genes may be responsible for the observed association. Alternatively, linkage to Cb-egl-5 may be coincidental, and ray pattern variation in C. briggsae may not result from variation in homeotic gene expression patterns. The best test of these alternative models will be the high resolution mapping of the allelic variants responsible for ray pattern variation. Loci not linked to the homeotic gene cluster also must be involved in ray pattern variation. Direct evidence for this was obtained from the mip-1 marker assisted introgression studies. The C. elegans homolog of mip-1 , unc-22 , is not linked to the the homeotic gene cluster and linkage of mip-1 to Cb-egl-5 and Cb-mab-5 is unlikely. There appear to be at least two loci that affect ray pattern linked to mip-1 . One of these affected both the placement of ray 3 and its fusion with ray 4. The other affected only ray fusion. These associations were not transgressive, i.e. the allelic variants linked to mip-1 antagonized the allelic variants linked to Cb-egl-5 . If the transgressive segregation linked to Cb-egl-5 does result from allelic variation in one or more homeotic genes, then the antagonistic variation linked to mip-1 may be in genes that regulate homeotic gene expression patterns. A direct test of this hypothesis is possible. Several genes required for proper regulation of homeotic gene expression patterns have been identified in C. elegans [ 25 , 26 , 37 , 38 , 49 ]. C. briggsae homologs of these genes could be tested for association with ray pattern variation in the RILs. Ideally, these tests would be integrated into a genome wide screen for variant loci with effects on ray pattern. This will require the enhancement of genetic resources available for C. briggsae . Conclusions Ray pattern in Caenorhabditis provides a powerful model for the study of morphological evolution. Macroevolutionary comparisons between species and microevolutionary analyses of variation within species are possible. Augmenting these approaches is a detailed understanding of the genetic and cellular basis of ray pattern development in C. elegans . In C. briggsae , intraspecific variants have been characterized that affect the expression of ancestral and derived ray patterns. These variants have a complex genetic basis involving multiple genes. Some of these genes exhibit transgenic segregation, some affect all of elements of ray pattern, and some that affect only a subset of ray pattern elements. At least one gene that affects ray pattern variation in C. briggsae is linked to the homeotic gene cluster. Thus, ray pattern variation may result from altered expression patterns of homeotic genes. Further characterizations of the genetics of ray pattern variation will test this model and will address interactions between different genes that impact ray pattern in C. briggsae . Methods Strains and strain maintenance C. briggsae strains AF16, and HK104 are available from the Caenorhabditis Genetics Center [ 50 ]. These strains were maintained on agar plates seeded with E. coli strain OP50. Recombinant inbred lines (RIL) were constructed starting with HK104 males mated to sperm-depleted AF16 hermaphrodites [ 15 ]. Each RIL was initiated with a single F2 hermaphrodite and propagated through F11, one hermaphrodite per generation. Microscopy Ray pattern phenotypes were scored using differential interference contrast optics at a magnification of 400× [ 5 ]. Right and left sides were scored independently [ 39 ]. Microscopic images of worms anethesized in 0.2% sodium azide were digitally captured using a Spot Camera and Software (Diagnostic Instruments, Inc., Sterling Heights MI). PCR amplification Forward and reverse primers for PCR amplifications Cb-egl-5 , CAGGGAGCGGACAACTTCAAAGG and GGACACAGCCCAGGATTAGCGAC, respectively, were designed based on genome sequence data from C. briggsae strain AF16 [ 41 ]. Amplification products were size fractionated by electrophoresis through 1% agarose. Statistical analyses Pearson's product moment correlation cofficients between ray pattern elements in RILs and Wilcoxon nonparametric tests of the association between Cb-egl-5 allelic variation with ray pattern variation were determined online at [ 51 ]. Frequency distributions of the segregation of ray 3 positional and fusion phenotypes were compared using the Kolmogorov-Smirnov tests as implemented at [ 52 ]. Ray pattern phenotypes of mip-1 introgressed strains were compared using reciprocal chi-squared tests using Excel v10.1.0 (Microsoft, Inc., Redman WA). Abbreviations RIL = recombinant inbred line; QTL = quantitative trait loci; dll = distalless ; en = engrailed ; sal = spalt Author's contributions SEB : Planned and supervised all research activities. Participated in construction and genotyping of RILs. Reviewed all statistical analyses. Wrote manuscript. CRD : Constructed, genotyped, and characterized ray pattern phenotypes of RILs. Statistical analyses of the segregation of ray pattern phenotypes and association of Cb-egl-5 variation with ray pattern variation. Reviewed manuscript. JCB : Constructed and characterized phenotypes of mip-1 -assisted introgressed lines. Statistical analyses of ray pattern phenotypes of mip-1 introgressed lines. Reviewed manuscript. Supplementary Material Additional File 1 AF16 × HK104 RIL ray pattern data. Cb-egl-5 genotypes and ray pattern phenotypes of RIL derived from AF16 × HK104. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545079.xml |
544401 | Dynamic in vivo imaging and cell tracking using a histone fluorescent protein fusion in mice | Background Advances in optical imaging modalities and the continued evolution of genetically-encoded fluorescent proteins are coming together to facilitate the study of cell behavior at high resolution in living organisms. As a result, imaging using autofluorescent protein reporters is gaining popularity in mouse transgenic and targeted mutagenesis applications. Results We have used embryonic stem cell-mediated transgenesis to label cells at sub-cellular resolution in vivo , and to evaluate fusion of a human histone protein to green fluorescent protein for ubiquitous fluorescent labeling of nucleosomes in mice. To this end we have generated embryonic stem cells and a corresponding strain of mice that is viable and fertile and exhibits widespread chromatin-localized reporter expression. High levels of transgene expression are maintained in a constitutive manner. Viability and fertility of homozygous transgenic animals demonstrates that this reporter is developmentally neutral and does not interfere with mitosis or meiosis. Conclusions Using various optical imaging modalities including wide-field, spinning disc confocal, and laser scanning confocal and multiphoton excitation microscopy, we can identify cells in various stages of the cell cycle. We can identify cells in interphase, cells undergoing mitosis or cell death. We demonstrate that this histone fusion reporter allows the direct visualization of active chromatin in situ . Since this reporter segments three-dimensional space, it permits the visualization of individual cells within a population, and so facilitates tracking cell position over time. It is therefore attractive for use in multidimensional studies of in vivo cell behavior and cell fate. | Background Macro- and microscopic imaging are pivotal readouts in the field of biology both for determining the normal (baseline) course of events and for observing the effects of experimental perturbations and natural aberrations [ 1 ]. Recent advances in microscopic imaging make it possible to routinely gain visual access to samples hundreds of microns thick [ 2 ]. The emergence of green fluorescent protein (GFP) as a reporter has opened up many new experimental approaches that were not previously possible [ 2 - 4 ]. GFP and other genetically-encoded autofluorescent protein reporters have a number of properties that make them ideal for multidimentional imaging of living specimens: no substrate (except photons) is required to generate signal, they have a high signal-to-noise ratio, are non-toxic, stable at 37°C and resistant to photobleaching. Moreover they are available in an increasingly large compendium of spectrally-distinct variants. To construct high-resolution anatomical models of normal, mutant and pathological situations, we must establish technologies to identify and follow individual cells in three-dimensional (3D) space and in 3D over time, in four-dimensions (4D). Unfortunately, native fluorescent proteins permit tracking the position of any given cell over time only if the population of tagged cells is distributed among non-expressing cells by virtue of lineage or in a mosaic experimental situation [ 5 - 9 ]. In situations where groups, or all cells in a 3D field of view express a fluorescent protein label, information on the behavior of individual cells cannot be discerned. Therefore an approach is required where 3D space is segmented at cellular resolution. This is most easily achieved if each cell can be marked with an easily identifiable tag that is visible at subcellular resolution [ 10 , 11 ]. Since it exhibits low autofluorescence, and is a single, universal and volumetrically constrained cellular organelle, the nucleus is ideal for such labeling [ 12 - 14 ]. Our goal was to take advantage of this feature and to develop a non-invasive fluorescent protein marker of the nucleus for in toto imaging (all cells within the multidimensional space being imaged – discussed in Ref. [ 11 ]) of individual cells in situ in living mice [ 10 - 12 ]. For the unequivocal identification of individual cells, we sought a developmentally neutral, genetically-encoded autofluorescent protein-based marker that labels DNA during all phases of the cell cycle while preserving cell morphology and behavior. As the principal structural proteins of eukaryotic chromosomes, histones are attractive targets for fluorescent nuclear labeling. Histone tagged fluorescent protein fusions have previously been shown to incorporate into chromatin without any adverse effects on the viability of cells in culture [ 15 ]. When compared to reporters containing nuclear localization sequences (nls), histone fusions exhibit an improved signal-to-noise ratio and have the distinct advantage of signal remaining bound to the target even during cell division when the nuclear envelope has broken down. In contrast nls-tagged markers (both GFP and lacZ) become dispersed throughout a cell during division, making it difficult to distinguish individual cells during mitosis. To date GFP fusions to several histones have been generated and used for labeling nuclei in live transgenic animals, including nematode worms, fruit flies and zebrafish [ 13 , 14 , 16 , 17 ]. One of these is a fusion between EGFP and human histone H2B which was developed in order to label active chromatin and used to follow the segregation of double minute chromosomes in cancer cells [ 15 ]. We have investigated the expression and germline transmission of this type of fusion in mice and established its usefulness not only for imaging cell cycle dynamics [ 18 ], but also for tracking cells in living specimens. Moreover unlike native GFP variants this subcellularly localized histone fusion was found to withstand fixation while retaining both fluorescence and subcellular localization. Results To evaluate histone-tagged fluorescent protein fusions in embryonic stem (ES) cells and mice, we generated constructs comprising an N-terminally positioned human H2B sequence followed at the C-terminus by sequences for various fluorescent proteins both GFP and DsRed-based. We previously reported that DsRed1 was not amenable to use in ES cells or mice [ 22 ], however several improved DsRed variants have recently become available [ 10 ]. We therefore chose to evaluate DsRed2 and DsRedExpress as part of this study. The H2B-fluorescent protein fusions we generated were introduced into vectors utilizing the CAG promoter [ 19 ] designed to drive high-level constitutive gene expression in ES cells, embryos and adult mice [ 20 ]. Standard protocols were used to establish stable lines of ES cells constitutively expressing an H2B fusion [ 20 - 22 ]. Several transgenic ES cell lines were generated each expressing H2B-EGFP at strong homogenous levels [ 23 ]. However, even though we did recover lines with H2B-DsRed2 and H2B-DsRedExpress expression [ 24 ], subsequent maintenance of these lines in culture revealed a continued reduction and heterogeneity in fluorescence. We were unable to establish lines with sustained homogenous H2B-DsRed2 or H2B-DsRedExpress fluorescence. Moreover our recent data suggest that mRFP1 [ 10 , 25 ], a rapidly-maturing monomeric form of DsRed, is amenable to use in mice, both in its native form and as a part of functional fusion proteins (AKH unpublished observations). H2B-EGFP expressing ES cells are shown in Fig. 1 . It noteworthy that with this histone fusion we observed a high signal-to-noise ratio and so could achieve high-resolution imaging of mitotic chromosomes (pink arrowheads), various states of interphase chromatin and nuclear debris (yellow arrowheads). Moreover for cells undergoing mitosis we could also discern the stage of mitosis and the plane of cell division (Fig. 1 b inset). Previous work indicated that a similar fusion protein expressed in HeLa cells did not affect cell cycle progression [ 15 ], and accordingly not only could we visualize nuclear dynamics and identify the various phases of mitosis in live ES cells [ 26 ] (Fig. 2 ), but in doing so, we did not observe any change in growth rate or mitotic index in the transgenic ES cells compared to non-transgenic parental ES cells (data not shown). By imaging several CAG::H2B-EGFP transgenic ES cells undergoing mitosis ( n = 30) we calculated the progression from early prophase to cytokinesis to take less than one hour (Fig. 2 ). Furthermore imaging of embryoid bodies demonstrated that individual nuclei could be discerned from a three-dimensional population of densely packed cells all of which were expressing the H2B-EGFP marker (Fig. 1 c). No loss of fluorescence was observed with prolonged in vitro passage of the ES cells expressing the H2B-EGFP fusion in the absence of positive selection in the presence or absence of LIF ( t > 3 months in the presence of LIF). Figure 1 Imaging chromatin in living transgenic ES cells constitutively expressing a H2B-EGFP fusion protein. ( a ) Bright-field and ( b ) dark-field micrographs of a CAG::H2B-EGFP ES cell colony. The inset shows a detail with three nuclei in metaphase (pink arrowheads) with the metaphase plates orientated differently. The mitotic spindle of the cell at the top is closely aligned to the z - y plane whereas those for the lower two cells are more closely aligned with the x - z planes. ( c ) Rendered stack (3-D reconstruction) of sequential optical slices acquired using spinning disc confocal methodology, projected as a fixed angle view of an embryoid body comprised of ES cells constitutively expressing a H2B-EGFP fusion. Pink arrowheads indicate two nuclei in late-anaphase – telophase. Yellow arrowhead points to the nuclear remnant of a cell that has necrosed or apoptosed. ( d – f ) High-power sequential optical sections each (1 μm apart) through ES cells constitutively expressing the H2B-EGFP fusion, taken using laser scanning confocal methodology showing interphase nuclei, a mitotic nucleus (pink arrowhead) and a pycnotic nucleus (yellow arrowhead). Figure 2 Live imaging the progression through mitosis. Laser scanning confocal x - y images taken at a single z -plane at five minute intervals for one hour. Note that not all green fluorescence (corresponding to nuclear material) will be represented in the plane being imaged. A cell progressing from anaphase to cytokinesis (pink arrowheads). A cell progressing from prophase to telophase (blue arrowheads). The average time taken to transition from early prophase to cytokinesis was calculated to be approximately 1 hour ( n = 30). We next tested the effects of widespread expression of an H2B fusion protein in mice. We generated germ line chimeras and established transgenic lines of mice constitutively expressing H2B-EGFP. We were able to breed this transgene to homozygosity, resulting in viable and fertile animals exhibiting widespread expression with no overt morphological abnormalities. The transgene has been maintained for over three years in a breeding colony of homozygous mice with no apparent effect on viability, breeding performance or lifespan. We therefore infer that this fusion protein is developmentally neutral and does not interfere with either mitosis or meiosis. Wide-field microscopic analysis of both mouse embryos and adult organs demonstrates widespread expression of the H2B-EGFP fusion in all types of nucleated cells. We used laser scanning confocal microscopy [ 10 , 11 ] to image this constitutively expressed transgenic reporter at subcellular resolution in live mouse embryos. Such non-invasive visualization of chromatin in living preparations allowed us to acquire high-magnification sequential optical sections ( z -stacks) that can be used to generate high-resolution anatomical volumetric (3-dimensional) images with details of interphase chromatin in addition to mitotic chromosomes and fragmenting nuclei. To do this, stacks of sequential optical sections are reconstructed into 3-dimensional projections. This methodology can be used to generate 3-dimensional (3D) image sets not only of cells propagated in culture but also of cells in situ in living animals and is illustrated here by imaging whole mouse embryos at the 4-cell stage, the blastocyst stage, and the pre-gastrula stage (Fig. 3 and Additional Files 1 and 2 ). These data sets can be computationally manipulated in various ways, for example for the visualization of individual xy slices from a z -stack, rendered images from the full, or part of a z -stack, and color-coded depth projections of a z -stack (Fig. 3 ). Figure 3 Live embryo imaging of preimplantation and early postimplantation mouse embryos hemizygous for a constitutively expressed H2B-EGFP fluorescent fusion. (a) Single confocal optical section fluorescence overlay on a bright-field image of a 5-cell stage pre-implantation embryo. Two of the blastomeres are dividing synchronously and are in metaphase (pink arrowheads in b). (b) Dark-field projection of the entire rendered z -stack of x - y sections (n = 19), through the entire embryo shown in panel a . (c) Color-coded depth projection of the entire z -stack of x -y images for the embryo shown in the previous panels. ( d ) Single confocal optical section fluorescence overlay on a bright-field image of a blastocyst stage embryo. Inner cell mass (ICM) is to the top left corner and second polar body is on the bottom left, juxtaposed to the edge of the ICM. ( e ) Dark-field projection of half the rendered z -stack of x - y sections ( n = 40, sections 1–19 were used for generating the projection), spanning half the embryo shown in panel d . Condensed chromosomes of nuclei in prophase (pink arrowheads) can be seen in three cells of the mural trophectoderm. Cells of the polar trophectoderm (green arrowhead) and inner cell mass (blue arrowhead) can also be distinguished by position within the half-blastocyst reconstruction. ( f ) Color-coded depth projection of the entire z -stack of x -y images for the embryo shown in the previous two panels. ( g - h ) Saggital views and rendered z -stacks of x - y images of an E5.75 (pre-streak stage) embryo. ( g ) Single optical confocal section fluorescence overlay on a bright-field image positioned half the way through the embryo. The brackets on the left illustrate the position of the embryonic (Em) and extraembryonic (Ex) regions of the embryo. ( h ) The same optical section with only the fluorescence image. Cells of the epiblast (blue arrowhead) and visceral endoderm (green arrowhead) can clearly be distinguished on the basis of position and nuclear morphology. Cells in mitosis can readily be distinguished within the embryo (pink arrowhead). ( i ) Color-coded depth projection of the stack of serial sections ( n = 60), part of the series of which is shown in the previous two panels. Color-coded z -scale (upper right) applies to all projections and denotes distances along the z -axis (0–120 μm). Data on older embryos and adult organs illustrates that larger specimens can be imaged, however not in their entirety given current limitations in optical imaging capabilities. Instead of imaging the whole specimen, larger samples are positioned so that data can be acquired from regions of interest, which can then be acquired in a tiled manner and computationally re-aligned in image acquisition and processing software. Our data demonstrates that nuclear morphology afforded by the H2B-EGFP fusion can be used to identify different cell types. In both the raw data, and a rotated rendered stack of an embryonic day (E) 7.5 embryo, cells of the definitive endoderm, mesoderm and embryonic ectoderm can be distinguished solely on the basis of nuclear morphology and orientation in addition to their expected position (Fig. 4 b–h and Additional File 3 ). Low magnification rendered z -stacks taken from a transversely cut section through the head of an E10.5 embryo (Fig. 4 i) reveal the stereotypical 3D organization of nuclei within the region imaged (Fig. 4 j), and electronically magnified views of this image illustrate a characteristic apposition of nuclei both in and around the notochord, and within the mesenchyme and endoderm of the pharyngeal region (Fig. 4 k and 4 l and Additional Files 4 and 5 ), in addition to providing information on cell division and cell death (pink and yellow arrowheads, respectively in Fig. 4 l). Figure 4 Live imaging H2B-EGFP in postimplantation mouse embryos. (a) Lateral view of the embryonic region of an E7.5 embryo (anterior to the left) with box depicting the region imaged in b and double-headed arrow depicting the x - y layering of the z -stack. ( b - d ) single optical x - y sections of fluorescence overlayed on bright-field images acquired at the same focal plane. Each panel is 60 μm apart from the preceding panel. These panels comprise x - y images in the z -stack depicted in panel a . The different layers of this stage of embryo including the epiblast, mesoderm, visceral endoderm and node can be distinguished on the basis of both position and nuclear morphology. ( e - h ) projection of a rendered z -stack of ( x - y ) sections ( n = 90) of the dark-field component of the sections taken in the series schematized in a and of the raw data shown in b . ( e ) 0° rotation, ( f ) 60° rotation, ( g ) 120° rotation, and ( h ) 180° rotation views. ( i ) low-magnification frontal view of an E11 embryo that has had a transverse cut made to remove the head. The box depicts the region (at the ventral hindbrain and 1 st branchial pouch) subject to laser scanning confocal imaging, with the double-headed arrow depicting the x - y layering of the acquired z -stack. ( j ) rendered ( z -) stack of sections ( n = 200, i.e . 400 μm depth) taken through the boxed region. ( k ) rendered stack of top 50 x - y sections (100 μm depth) taken from the region imaged around the notochord (comprising axial mesoderm and mesenchyme cells). ( l ) rendered stack of top 50 sections (100 μm depth) taken around the branchial pouch region (comprising endoderm and mesenchyme cells). The sections used to generate the rendered stacks in panels k and l were electronically magnified. Pink arrowheads, mitotic nuclei; yellow arrowheads, pycnotic nuclei; ect, ectoderm, en, endoderm, hf, headfold, mes, mesoderm, noto, notochord. Wide-field microscopic examination of organs from adult animals revealed widespread fluorescence as has been reported for animals expressing native fluorescent proteins under the regulation of the CAG promoter [ 20 , 22 , 27 ]. Laser scanning confocal imaging of various organs obtained from adult animals was used to generate high-resolution images revealing stereotypical nuclear positions, reflecting different cell types and revealing other subcellular details, such as mitosis and nuclear fragments, also observed in embryos (Fig. 5 and Additional Files 3 , 4 , 5 ). Figure 5 High resolution live imaging of the organs of CAG::H2B-EGFP adult mice. Confocal images of freshly isolated organs from a 6 week old adult male hemizygous CAG::H2B-EGFP Tg/+ animal illustrate the widespread nuclear localized expression of the histone fusion. A transverse cut was made through each organ and the cut surface was placed closest to the objective lens and imaged. Cell tracker orange was used as a vital cytoplasmic counter stain. The panels show rendered confocal z -stacks imaged through 80 μm of the brain using a 20x plan-apo objective ( a - c ), 568 μm of the heart using a 5x fluar objective ( d - f ), 142 μm of a lung lobe using a 5x fluar objective ( g - i ) and 346 μm of a kidney using a 5x fluar objective low power view ( j - l ), and high power view ( m - o ). Insets in panels a and d show the region of the brain and heart imaged, respectively. High resolution images of the kidney ( m - o ) illustrate electronic magnification of the data shown in j - l . Bron, bronchus; glom, glomeruus; med, medulla; sept, septum; ub, ureteric bud; ven, ventricle. Areas of increased fluorescence in the red channel are an artefact due to saturated pixels in regions of the sample closest to the objective. Finally we investigated whether we could follow cell movement, division, and death in time-lapse experiments using various imaging modalities. We cultured ES cells and embryos on the stages various each of which had been modified to permit culture under physiological conditions. The different types of data routinely generated using different optical imaging modalities that are widely used and commercially available are illustrated in Figure 6 . Spinning disc confocal microscopy [ 1 ] was used for short-term high-resolution 4D imaging of CAG::H2B-EGFP ES cells (Fig. 6 and Additional File 6 ), wide-field microscopy was used for long-term low-resolution imaging of CAG::H2B-EGFP preimplantation stage embryos (Fig. 6 and Additional File 7 ). Note that development proceeds normally in most embryos, and that some of the embryos imaged are undergoing cavitation to form blastocysts [ 28 ] (arrowheads). Two-photon excitation microscopy [ 10 , 29 , 30 ] was used to image cells in a whole gastrula-stage mouse embryo without perturbing the morphogenetic movements associated with gastrulation (Fig. 6 and Additional File 8 ). Cells can clearly be followed through the successive time points in each of these experimental situations ranging from a few minutes (short-term) to 24 hours (long-term) time-lapse duration. These studies reflect the range of resolutions at which information can be acquired using a marker of this type. We observed normal cell proliferation throughout the course of these imaging experiments and no excessive nuclear fragmentation. Also, because the on-stage cultures were comparable to parallel cultures maintained in a tissue culture incubator, we conclude that the outcome of the cultures was not affected by the various imaging modalities. Figure 6 Dynamic time-lapse imaging of mouse CAG::H2B-EGFP transgenic ES cells, preimplantation and postimplantation embryos using different imaging modalities. ( a ) Rendered confocal stacks of transgenic ES cells constitutively expressing a CAG::H2B-EGFP transgene representing a 25 minute time-lapse recording of images acquired using a spinning disc confocal scan head. x - y sections with a z -interval of 0.2 μm were taken at a rate of 10/second over a total z -stack of 40 μm. Cells can be traced through the 4D rendered stack. Cells entering or completing mitosis (pink arrowheads) and the nuclear remnant of a cell that has either undergone apoptosis or necrosis (yellow arrowhead) are clearly visible. ( b ) Wide-field imaging of CAG::H2B-EGFP transgenic preimplantation embryos. This 24 hour image sequence illustrates cavitation leading up to the formation of the blastocyst in several embryos (violet arrowheads). ( c ) Rendered two-photon stacks of CAG::H2B-EGFP transgenic gastrulation stage postimplantation embryos. This 40 minute time-lapse sequence illustrates cell division and tracking within the visceral endoderm (green arrowhead) and epiblast (blue arrowheads) and the movement of mesoderm emanating from the primitive streak, which is positioned to the right, out of the field of view. Scale bar in a = 10 μm, b = 100 μm and c = 50 μm. Discussion Here we report the evaluation of a chromatin localized histone fusion fluorescent reporter in vivo through the generation of transgenic embryonic stem (ES) cells and mice having widespread expression of this reporter. The transgenic mice that we have generated provide a new tool for high-resolution live imaging of a genetically tractable mammalian model organism [ 10 , 11 ]. They represent a resource for analyzing development and disease at the subcellular level in cells, embryos and adult tissues. The marker used facilitates the acquisition of in vivo data and allows it to be integrated onto a high-resolution anatomical framework. This type of multidimensional data is complex and thus difficult to digitize and compile into a standardized and integratable format. In toto imaging of fluorescent protein expressing specimens on a large-scale could be used for generating high-resolution digitally recorded anatomical databases where the baseline (wild-type) cell behaviors and cell fates can be contrasted to those observed in mouse mutants. However, developing in toto imaging technologies for acquiring large amounts of data will necessitate improving the speed and throughput of microscopic image acquisition and analysis. This would also be coincident with the ongoing development of improved computational approaches to mine and integrate this type of data [discussed in ref. [ 11 ]]. Much of the information generated using a fluorescent fusion reporter such as the H2B-EGFP fusion is analogous to conventional histology [ 21 , 31 ] except that this mode of data acquisition optically sections a sample (circumventing the need to physical section), excels in permitting computational 3D reconstructions of spatial information, and can additionally be coupled to time-lapse imaging for the capture, processing and quantitation of 4D information (Fig. 6 and Additional Files). Also, unlike conventional GFP-based reporters [ 20 , 22 ], the histone H2B-EGFP fusion is resilient to fixation, so samples can be processed and stored for extended periods of time without compromising signal integrity or specificity (Fig. 7 ). Figure 7 High-resolution 3-dimensional imaging of fixed CAG::H2B-EGFP transgenic embryos. Confocal images of an E8.5 CAG::H2B-EGFP transgenic embryo fixed in 4% paraformaldehyde for 72 hours, then washed, stored and imaged in PBS. Low-magnification views and reconstructions of whole embryo ( a - c ). Boxes in a designate region imaged in d and g . High-magnification views of the headfolds ( d - f ) and posterior primitive streak and proximal allantois ( g - i ). Single xy images ( a , d and g ) from the z -stacks used to computationally render the data sets. These images are overlayed onto the bright field channel so as to display the outline of the embryo. Rotations through the rendered z -stacks displayed at 45° intervals ( b , e and h ). Color-coded depth projections of each of the z -stacks ( c , f and i ). The future development and availability of mouse strains constitutively expressing spectral variant histone H2B fusions should prove useful for visualizing anatomy and tracking different populations of cells in multiple dimensions at high-resolution in mice as has previously been demonstrated in other organisms which are classically perceived as being more amenable to in vitro culture and optical imaging [ 13 , 16 ]. They can also be used as tagged populations of cells in chimeras [ 8 ], in addition to transplantation and cell isolation experiments [ 32 ]. Also, since fluorescence is proportional to genome content and the fluorescence intensity reflects chromosome condensation state, the reagents we have generated should permit the study of alterations in ploidy and chromosomal condensation including determination of phases of mitosis [ 26 ]. Additionally, real-time analysis of chromatin fragmentation as well as the effects of mutations on chromosome stability during disease processes can be investigated using CAG::H2B-EGFP transgenic mice. Conclusions The CAG::H2B-EGFP strain that we have generated takes in vivo imaging using genetically-encoded reporters in mice to sub-cellular resolution. The development of additional strains permitting spectrally-distinct high-resolution live cell in vivo imaging, coupled to advances in optical imaging modalities and the development of improved computational methods to mine imaging data should pave the way for a multidimensional understanding of biological processes. It is anticipated that in the future, in vivo imaging approaches using transgenic animals expressing genetically-encoded fluorescent proteins will not only provide high-resolution information on cell behavior in specific biological processes [ 12 , 33 ], but more importantly it may lead to an exponential increase in the available multidimensional in vivo biological information which could mirror the recent explosion of available genomic data. Therefore recent advances in live imaging will need to be paired with developments in computational biology, as appropriate informatics methods will need to be developed and implemented in order to mine, present and integrate this type of in vivo biological data. Methods The coding sequence for the human histone H2B gene (X57127) was amplified from genomic DNA by PCR using Pfx Polymerase (Invitrogen). The resulting product was cloned into pCR4 TOPO (Invitrogen) to generate pH2B. The H2B fragment was then cloned into plasmids pEGFP-N1, pDsRed2-N1 pDsRedExpress-N1 (BD Biosciences, Inc) in order to generate plasmids pH2B-EGFP, pH2B-DsRed2 and pH2B-DsRedExpress (oligonucleotide sequences are available upon request). The resulting fusions were then re-amplified by PCR and cloned into the XhoI site of pCAGGS [ 19 ] to generate pCX-H2B-EGFP, pCX-H2B-DsRed2 and pCX-H2B-DsRedExpress. All vectors were tested by transient transfection of Cos-7 cells and R1 ES cells using Fugene 6 Transfection Reagent as per manufacturer's recommendations (Roche) and electroporation respectively. The H2B-DsRed2 and H2B-DsRedExpress fusions failed to produce sustained homogenous levels of fluorescent signal, however the H2B-EGFP fusion gave strong nuclear-localized fluorescence throughout the extended culture period without perturbing cell morphology, the rate of proliferation, or the mitotic index (Fig. 2 and data not shown). Transgenic ES cell lines constitutively expressing H2B-EGFP were generated by co-electroporation of the linearized reporter construct and a circular PGK-Puro-pA plasmid [ 34 ] conferring transient puromycin resistance. Puromycin selection was carried out as described previously [ 20 , 22 ]. Briefly, drug selection was initiated 24–36 hours after electroporation, maintained for 5 days, after which time it was replaced with non-selection media for a further 24–48 hours. Fluorescent colonies were identified and picked under an epifluorescence microscope (Nikon SMZ1500). Clones were passaged in 96-well plates, and scored for maintenance and extent of fluorescence. Those exhibiting homogeneous and robust transgene expression in vitro under both stem cell conditions and conditions employed to promote their differentiation were maintained further. For stem cell conditions ES cells were grown on gelatin in the presence of LIF. For differentiation, ES cells were grown on bacteriological Petri dishes in the absence of LIF for 2–5 days to promote embryoid body formation. Thereafter embryoid bodies were re-plated onto tissue culture dishes in the presence of factors promoting directed differentiation. To assess whether an H2B fusion can continue to be widely expressed and transmitted through the germline of mice we used H2B-EGFP expressing ES cells for chimera generation by injection into C57BL/6 blastocysts using standard procedures [ 21 ]. Chimeras were bred to outbred ICR and inbred 129/Tac mice (Taconic, Germantown, NY) for germline transmission and subsequent maintenance of the lines. Two independent clones were taken germline giving indistinguishable results. We therefore focused on one of the transgenic lines. After germline transmission, this transgene was maintained at homozygosity, suggesting that the site of integration is not perturbing essential gene function. All animals retained widespread homogenous fluorescence for at least five subsequent generations. Homozygotes were distinguished from heterozygotes either by increased fluorescence in newborn (unpigmented) animal tails, by breeding, or by intensity of an EGFP hybridizing fragment on a Southern blot. Embryos and organs were dissected in HEPES buffered DMEM media containing 10% fetal calf serum, then cultured either in a standard tissue culture incubator or on a microscope stage under standard conditions promoting the culture of mouse embryos [ 35 , 36 ] in 50% rat serum: 50% DMEM buffered with bicarbonate and maintained under physiological conditions in a closed temperature-controlled, humidified and oxygenated (95% air, 5% CO 2 ) chamber (Bioptechs Inc. or Solent Sci Ltd. or home-made). For cytoplasmic staining, samples were incubated in Cell Tracker Orange (Molecular Probes; 1:500 dilution in dissecting or culture media) for 10–20 minutes. Embryos were kept in a standard tissue culture incubator at 37°C during staining. Samples were then washed twice with warm dissecting or culture media prior to imaging. All images shown (except Fig. 7 ) are of living hemizygous (Tg/+) embryos or freshly dissected (unfixed) tissues obtained from Tg/+ adults and maintained under physiological conditions. Increased fluorescence and a higher signal-to-noise ratio was observed in homozygous (Tg/Tg) specimens. The embryo presented in Figure 7 was fixed in 4% paraformaldehyde at 4°C for 72 hours, then washed, stored and imaged in PBS. Similar results were obtained in embryos fixed for up to two weeks. Wide-field images were acquired on a Nikon SMZ1500 stereo-dissecting microscope or Nikon Eclipse 5000 inverted microscope equipped with epifluorescent illumination. Spinning disc confocal data was acquired on an UltraView RS3 (Perkin-Elmer Systems) fitted on a Zeiss Axiovert 200M microscope with illumination from a 488 nm Argon laser (Melles Griot). Laser scanning confocal and multiphoton excitation data were taken on a Zeiss LSM510 NLO on a Zeiss Axioscop 2 FS MOT microscope. Objective lenses used on the Axiovert 200M and Axioscop 2 were plan-apochromat 63x/NA1.4, C-apochromat 40x/NA1.2, a plan-apochromat 20x/NA0.75 and a fluar 5x/NA0.25. For laser scanning microscopy GFP was excited using either a 488 nm Argon laser (Lassos, Inc) at 488 nm (for single-photon excitation) or a Titanium:Sapphire laser (Coherent Mira 900F with Verdi 5W pump laser) tuned between 860 and 890 nm (for two-photon excitation). Cell Tracker Orange was excited using a 543 nm HeNe laser (for single-photon use). Images were acquired as z -stacks comprising sequential x - y sections taken at 0.1–2 μm z -intervals. Raw data was processed using a variety of packages including Zeiss AIM software (Carl Zeiss Microsystems at ), Image J (NIH at ) and Volocity (Improvision at ). Each image series was re-animated using software to make the time-lapse movies that are available as additional files. Both rendered volume and time-lapse movies were assembled in QuickTime Player (Apple Computer, Inc at ). Appendix The CAG::H2B-EGFP strain of mice generated in this study will be made available through the Jackson Laboratories Induced Mutant Resource (JAX IMR at ). Supplementary Material Additional File 1 Rotating 3D projection of a whole live CAG::H2B-EGFP Tg/+ blastocyst. Supplementary to stills presented in Fig. 3 . This file was assembled at 6 frames/second. Click here for file Additional File 2 Rotating 3D projection of a (electronic) half blastocyst. Generated from the same raw data set used to compile Supplementary File 1. Supplementary to stills presented in Fig. 3 . This file was assembled at 6 frames/second. Click here for file Additional File 3 Rotating 3D projection the node region of a live CAG::H2B-EGFP Tg/+ E7.5 embryo. Supplementary to stills presented in Fig. 4 . This file was assembled at 6 frames/second. Click here for file Additional File 4 Rotating 3D projection of the notochord of a live CAG::H2B-EGFP Tg/+ E10.5 embryo. Supplementary to Fig. 4 . This file was assembled at 6 frames/second. Click here for file Additional File 5 Rotating 3D projection of the branchial region of a live CAG::H2B-EGFP Tg/+ E10.5 embryo. Supplementary to stills presented in Fig. 4 . This file was assembled at 6 frames/second. Click here for file Additional File 6 Time-lapse sequence of CAG::H2B-EGFP Tg/+ ES cells. Supplementary to stills presented in Fig. 6 . This file was assembled at 12 frames/second. Click here for file Additional File 7 Time-lapse sequence of CAG::H2B-EGFP Tg/+ preimplantation embryos. Supplementary to stills presented in Fig. 6 . This file was assembled at 6 frames/second. Click here for file Additional File 8 Time-lapse sequence of a CAG::H2B-EGFP Tg/+ postimplantation embryo. Supplementary to stills presented in Fig. 6 . This file was assembled at 6 frames/second. Click here for file Additional File 9 Rotating 3D projection of a fixed CAG::H2B-EGFP Tg/+ E8.5 embryo. Supplementary to stills presented in Fig. 7 . This file was assembled at 6 frames/second. Click here for file Additional File 10 High-magnification rotating 3D projection of the headfold region of the same fixed CAG::H2B-EGFP Tg/+ E8.5 embryo as shown in Movie 7. Supplementary to stills presented in Fig. 7 . This file was assembled at 6 frames/second. Click here for file Additional File 11 High-magnification rotating 3D projection of the allantois and posterior tail region of the same fixed CAG::H2B-EGFP Tg/+ E8.5 embryo as shown in Movie 7. Supplementary to stills presented in Fig. 7 . This file was assembled at 6 frames/second. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544401.xml |
524487 | Variation suggestive of horizontal gene transfer at a lipopolysaccharide (lps) biosynthetic locus in Xanthomonas oryzae pv. oryzae, the bacterial leaf blight pathogen of rice | Background In animal pathogenic bacteria, horizontal gene transfer events (HGT) have been frequently observed in genomic regions that encode functions involved in biosynthesis of the outer membrane located lipopolysaccharide (LPS). As a result, different strains of the same pathogen can have substantially different lps biosynthetic gene clusters. Since LPS is highly antigenic, the variation at lps loci is attributed to be of advantage in evading the host immune system. Although LPS has been suggested as a potentiator of plant defense responses, interstrain variation at lps biosynthetic gene clusters has not been reported for any plant pathogenic bacterium. Results We report here the complete sequence of a 12.2 kb virulence locus of Xanthomonas oryzae pv. oryzae (Xoo) encoding six genes whose products are homologous to functions involved in LPS biosynthesis and transport. All six open reading frames (ORFs) have atypical G+C content and altered codon usage, which are the hallmarks of genomic islands that are acquired by horizontal gene transfer. The lps locus is flanked by highly conserved genes, metB and etfA , respectively encoding cystathionine gamma lyase and electron transport flavoprotein. Interestingly, two different sets of lps genes are present at this locus in the plant pathogens, Xanthomonas campestris pv. campestris (Xcc) and Xanthomonas axonopodis pv. citri (Xac). The genomic island is present in a number of Xoo strains from India and other Asian countries but is not present in two strains, one from India (BXO8) and another from Nepal (Nepal624) as well as the closely related rice pathogen, Xanthomonas oryzae pv. oryzicola (Xoor). TAIL-PCR analysis indicates that sequences related to Xac are present at the lps locus in both BXO8 and Nepal624. The Xoor strain has a hybrid lps gene cluster, with sequences at the metB and etfA ends, being most closely related to sequences from Xac and the tomato pathogen, Pseudomonas syringae pv. tomato respectively. Conclusion This is the first report of hypervariation at an lps locus between different strains of a plant pathogenic bacterium. Our results indicate that multiple HGT events have occurred at this locus in the xanthomonad group of plant pathogens. | Background LPS is an important constituent of the outer membrane of gram-negative bacteria. Variation in LPS composition can have profound consequences for these cells by potentially providing resistance against bacteriophages and antimicrobial compounds as well as facilitating evasion of the host immune system in animal pathogens. Extreme variation at LPS gene clusters has been reported in animal pathogenic bacteria. Recently, eleven highly divergent gene clusters were reported to occupy an LPSspecific locus in Pseudomonas aeruginosa , an opportunistic human pathogen [ 1 ]. The acquisition by horizontal gene transfer of a new LPS biosynthetic gene cluster in Vibrio cholerae is considered as a major cause for the cholera epidemic that originated in India in 1992 [ 2 ]. In plant pathogenic bacteria, LPS is an important virulence factor and mutations in the genes involved in LPS production result in severe virulence deficiency [ 3 - 8 ]. LPS has been shown to induce resistance in plants against pathogens [ 9 , 10 ] and in some recent studies, LPS is found to induce expression of plant defense genes [ 11 , 12 ] as well as an oxidative burst reaction in cell cultures [ 13 ]. Since LPS recognition appears to be an important aspect of plant defense responses, variation in lps gene repertoire is to be expected within different strains of plant pathogenic bacteria. The genus Xathomonas includes a number of plant pathogenic bacteria. Two related members of this genus, Xanthomonas oryzae pv. oryzae (Xoo) and Xanthomonas oryzae pv. oryzicola (Xoor) cause diseases of rice [ 14 ]. They exhibit different tissue specificities with Xoo growing in the xylem vessels while Xoor grows within the intercellular spaces of the parenchymatous tissue. Xoo causes bacterial leaf blight, the most serious bacterial disease of rice. This disease is prevalent in many rice growing countries in Asia, extending from the Indian subcontinent to Japan and Korea. DNA fingerprinting studies using multi-locus RFLP and PCR probes have indicated that there is extensive genetic diversity within Xoo strains isolated from various countries [ 15 - 19 ]. In India, multi-locus RFLP profiling has indicated that one lineage of Xoo (called the BXO1 lineage, based on the type strain for this group) is widely distributed within the country. Strains within the BXO1 lineage cluster together at about the 90 % similarity level in a dendrogram. A second group of strains is quite diverse, both at the haplotypic and pathotypic level, and clusters with the BXO1 group at about the 55% similarity level [ 19 ]. In previous research, we have reported a 5.5 kb region in the genome of Xoo strain BXO1 and demonstrated that it encodes three genes that are involved in biosynthesis of LPS and extracellular polysaccharide (EPS) as well as in virulence [ 8 ]. All the three genes have atypical G+C content, as compared to the rest of the Xoo genome. In this study, we have completed the entire sequence of this 12.2 kb genomic locus and indicate that it encodes three additional genes, wxoD , wzt and wzm , that are postulated to be involved in LPS biosynthesis and transport. These newly described genes also have atypical G+C content and all the six genes at this locus exhibit altered codon usage pattern, as compared to other Xoo genes. We present evidence that this locus is present in many, but not all, Xoo strains and that it is absent in Xoor. Our results indicate that there is substantial variation at this locus among various xanthomonads. The possible significance of these results is discussed. Results Genetic organization of a Xoo lps locus In an earlier study, a novel Xoo locus was reported to be required for LPS and extracellular polysaccharide (EPS) production as well as virulence. A 35 kb cosmid, pSD5, that complements mutations in this region was isolated [ 8 ]. Partial sequence (5.5 kb) of this locus indicated that the region has atypical G+C content and contains three genes which encode a predicted sugar nucleotide epimerase and two predicted glycosyl transferases. We report here the complete 12.2 kb sequence and genomic organization of this locus in Xoo strain BXO1 (Fig. 1 ). The insert in the pSD5 cosmid includes 7 Eco RI fragments (0.6, 2.2, 3.5, 4.0, 6.0, 9.0 and 10 kb). We subcloned all the fragments into pBlueScript. Based on the end sequences of the inserts in the subclones and pSD5, the lps locus was mapped to four of these Eco RI fragments (0.6, 4, 3.5 and 9 kb). The previously obtained sequence was found to include all of the 3.5 kb and part of the 4 kb fragment and the remaining sequence of this region was obtained by sequencing the 0.6 kb and the 9 kb fragment (Please refer Methods). A total sequence of 13.18 kb was constituted by joining 6.14 kb of previously obtained sequence [ 8 ] and 7.04 kb of new sequence. The 13.18 kb sequence includes 12.2 kb of the lps locus and some flanking regions. The additional sequence of the lps locus encodes three putative genes which encode a predicted O-antigen acetylase, a predicted ABC transporter permease and a predicted ATP-binding protein and three insertion sequence (IS) elements. All of the putative genes have been named as per Bacterial Polysaccharide Genes Nomenclature (BPGN) [ 20 ]. The first three genes, wxoA (encodes a predicted epimerase), wxoB and wxoC (both encode predicted glycosyl transferases) have been described earlier. The fourth gene is wxoD and encodes a predicted 327 amino acids long protein. A BLAST [ 21 ] search reveals strong homology to acetyltransferases that are involved in LPS modification and the best match is with an acetyltransferase from Mesorhizobium loti (MAFF303099; 34% identity and 46% similarity at amino acid level). Interestingly, no homologs of this gene have been reported in any other xanthomonad. The fifth gene, wzt , encodes a predicted 436 amino acid long protein. A BLAST search reveals homology to functions involved in LPS transport. The best match is with the ATPase component of an ABC-type polysaccharide transport system from Burkholderia fungorum (ZP_00033174.1; 47% identity and 65% similarity at amino acid level). The sixth gene, wzm , encodes a predicted 437 amino acid long protein which is homologous to integral membrane protein components of ABC transporter systems that are involved in LPS transport. The best match is with a permease component of the ABC-type polysaccharide export system from Pseudomonas fluorescens PfO-1 (ZP_00085342.1; 50% identity and 65% similarity at amino acid level). The start codon of wzt overlaps with the stop codon of wzm . Homologs of wzt and wzm are typically present in many lps gene clusters. Interestingly, two complete Insertion Sequence (IS) elements (IS Xo8 and IS 1113 ) and one truncated IS element (IS 1114 ) interrupt this cluster between the genes, wxoD and wzt . IS Xo8 is a novel 1320 bp long insertion sequence and a BLAST search shows homology to transposase of ISRSO 17 encoded by Ralstonia solanacearum (CAD17626; 51% identity and 63% similarity at amino acid level). A complete copy of the IS 1113 element (AF482989) and a truncated copy of the IS 1114 element (AF232058) are also present as indicated in Fig. 1 . The presence of IS elements is a marked feature of many lps loci [ 22 ]. Transcriptional orientation suggests the possibility that ORFs wxoA , wxoB , wxoC and wxoD might constitute one operon and that ORFs wzm and wzt might be transcribed together. The overlap between the start codon of wzt and the stop codon of wzm also suggests that these two genes are co-transcribed. The lps locus is flanked by metB , which encodes a predicted cystathionine gamma lyase, and etfA which encodes a predicted electron transport flavoprotein. The genome sequences of Xanthomonas campestris pv. campestris (Xcc; infects crucifer plants like cabbage, cauliflower, mustard, etc.) and Xanthomonas axonopodis pv. citri (Xac; infects citrus plants) have been obtained [ 23 ]. The Xoo metB gene (a partial sequence of 642 bp is available) exhibits within the sequenced region, 91% and 88% nucleotide identity to metB genes of Xac (AE012010.1) and Xcc (AE012157.1), respectively. The Xoo etfA gene (a partial sequence of 328 bp is available) exhibits within the sequenced region, 93% and 91% nucleotide sequence identity, respectively, with etfA genes in Xac (AE012009.1) and Xcc (AE012159.1). Interestingly, the lps biosynthetic gene cluster of Xcc, which comprises fifteen genes, is also located between the metB and etfA genes [ 24 ]. In Xac, this gene cluster is missing at this locus and is replaced by a set of fourteen genes, several of which are homologous to functions involved in LPS synthesis and transport. The gene clusters present at this locus in Xcc, Xac and Xoo have distinct nucleotide sequences, gene numbers (15 genes in Xcc, 14 genes in Xac, 6 genes in Xoo) and gene organization. The Xoo lps cluster is a genomic island a) Atypical G+C content The average G+C content of Xoo and other Xanthomonads is estimated to be around 65% [ 25 ], while the average G+C content of the lps locus is 50.46% (excluding the IS elements) [Fig. 1 ]. The variation is much more marked among the genes, from as low as 45.0% ( wxoD ) to 56.3% ( wxoC ). Atypical G+C content is a characteristic feature of "genomic islands" that are believed to be acquired by horizontal gene transfer. The transposase genes encoded by IS Xo8 and IS 1113 have a G+C content that is >61%, a value which is typical for the genomes of Xoo and other xanthomonads. The G+C content of metB and etfA genes that flank the genomic island have G+C content of 64.3% and 61% respectively (within the partial sequences that have been obtained) which is typical of the Xoo genome. b) Altered codon usage An additional hallmark of a genomic island is the altered codon usage. Here we present a simple and graphical way of calculating and representing the codon usage differences and refer to it as C odon U sage P attern or CUP (Please refer Methods). Eight aminoacids, i.e., Glycine, Valine, Threonine, Leucine, Arginine, Serine, Proline and Alanine, were selected to study CUP because they have atleast four synonymous codons. The percentage of synonymous codons that end with G or C was calculated for each aminoacid and gene. This analysis was conducted for six genes of the lps island and six genes from elsewhere in the Xoo genome (please refer Methods). We show that CUP of the genes present in the genomic island is dramatically different from the typical Xoo genes (Fig. 2 ). The %G+C at third codon position of synonymous codons for amino acid Glycine is only 52.5 % for genes present in the lps locus, while it is 78 % in case of Xoo genes that are located elsewhere in the genome. Similarly, for amino acids Valine, Alanine, Threonine, Serine, Arginine, Leucine and Proline the values are 46.6, 47, 59, 52, 53, 57 and 34.6 % respectively for genes at the lps locus, while the values are 84, 77.5, 89.5, 79.5, 75.6, 90.3 and 86.16 % for the respective aminoacids in case of the typical Xoo genes. Altered codon usage is a characteristic feature of horizontally acquired genes and CUP clearly indicates that the Xoo lps cluster is a genomic island (Fig. 2 ). The lps locus is present in the genomes of many, but not all, Xoo strains The presence of the genomic island in different Xoo strains was assessed by PCR using gene specific primers, for all the six lps genes, as described in the Methods. The list of strains used in the study is given in the Table 1 and the list of gene specific primers is given in Table 2 . In order to confirm that the genomic island is present at the same genomic location in all strains, PCR was also performed using two primer pairs that are designed to amplify fragments from metB to wxoA and wzm to etfA , respectively. The analysis included nine Indian Xoo strains representing different geographic locations and the BXO1 and non BXO1 groups. The list also includes twelve Xoo strains from different Asian countries and a Xoor strain, BXOR1, from India. Our study revealed that the genomic island is present in the majority (7/8) of Xoo strains that we have examined from India (Fig. 1 ). Four BXO1 group strains (BXO4, BXO7, BXO13 and BXO479) and three of the non-BXO1 strains (BXO5, BXO6 and BXO20) have the genomic island. The genomic island is also present in two strains each from China, Malaysia, Indonesia, Philippines, Korea and one strain from Nepal (Fig. 1 , Table 1 ). The lps locus is present, in all these strains, between the metB and etfA genes. Interestingly, we find that the genomic island is not present (as judged by PCR [Fig. 3A ] and Southern hybridisation [Fig. 3B ]; see Methods) in the genomes of Xoo strains BXO8 and Nepal624, as well as the Xoor strain, BXORI. The results obtained with the probes directed against the wxoA gene are presented but similar results were obtained using probes that are specific for the other five genes. The blots used above were reprobed as a positive control with a metB specific probe and the results gave an expected size band in BXO1 (lane 1), and different sized bands in BXO8 (lane 3), Nepal624 (lane 4) and BXOR1 (lane 2) indicating that the metB gene is present but located in different Eco RI fragments (Fig. 3C ). BXO8 and Nepal 624 have sequences related to Xac at the lps locus What are the sequences present at this genomic location in the Xoo strains that lack the lps locus? Thermal Asymmetric Interlaced (TAIL) PCR is an efficient technique for isolation of target DNA segments adjacent to known sequences [ 26 ]. TAIL-PCR and sequencing using primers directed against the conserved flanking metB and etfA genes suggests that sequences which are significantly similar to the Xac lps gene cluster are present at this genomic location in both of these strains. Next to metB , a wzm homolog is present in BXO8 (a partial sequence of 398 bp is available) and Xac with 69.2% identity at nucleotide level within the sequenced region. Next to etfA , a putative integral membrane protein encoding gene is present in both BXO8 (a partial sequence of 405 bp is available) and Xac with 91.3% identity at nucleotide level within the sequenced region. The BXO8 and Nepal624 strains exhibit 100% nucleotide sequence identity within the sequenced region. TAIL- PCR analysis of the Xoor strain indicates that it has a hybrid lps gene cluster. Next to metB , a unique wzm gene is located (a partial sequence of 548 bp is available) which exhibits 62.8% nucleotide identity to wzm gene of Pseudomonas syringae pv. tomato strain DC3000 (AE016859.1). Next to etfA , a putative inner membrane protein encoding gene is located (a partial sequence of 402 bp is available) which exhibits 97% and 92% nucleotide sequence identity, respectively, with similarly located genes in BXO8 and Xac. Because the BXO8 and Nepal624 strains have different sequences at the lps locus, as compared to other Xoo strains, we inoculated these strains along with appropriate controls onto leaves of the susceptible rice cultivar Taichung Native-1. We find that BXO8 and Nepal624 strains are able to cause typical bacterial leaf blight disease symptoms that are indistinguishable from those elicited by other Xoo strains (data are not shown). Presence of inverse repeats at the 3' ends of metB and etfA genes that flank the lps locus We have performed an alignment using BLAST2 [ 27 ] of the nucleotide sequences derived from the metB and etfA genes in BXO1 and BXO8. The homology breakpoints appear to localise to the 3' regions of metB and etfA genes, exactly 18 bp upstream of their respective stop codons. Upto the break points, within the sequenced region at either end of the lps locus, the nucleotide sequence is identical in BXO1, BXO8 and Nepal624. The DNA sequence immediately preceding the break points was examined manually for presence of direct or inverse repeats. Interestingly, we could find three inverted repeats (I, II and III) within the 3' regions of metB and etfA near the homology breakpoints between BXO1 and BXO8 (Fig. 4 ). The first repeat is the smallest one (5 bp) and the third repeat is the largest (11 bp). The second repeat is 6 bp long and is 7 bp from the first repeat on the metB side and 9 bp from the first repeat on the etfA side. The distance between the second and third repeats is 4 bp in metB and etfA . We also found similarly located inverse repeats in the metB and etfA genes of Xac, Xcc and Xoor. A consensus sequence of the repeats was derived (Fig. 4 ) by scoring a nucleotide if it is present in a majority of repeats. Relationship between BXO8 and Nepal 624 strains The TAIL PCR results indicate that the BXO8 and Nepal624 strains have identical sequences in place of the BXO1 lps locus. As both the strains are from the Indian subcontinent, there is the possibility that these are identical/nearly identical to each other. We therefore performed DNA fingerprinting analysis of the BXO8 and Nepal624 strains using the IS 1112 insertion element as a probe. This probe is highly informative and can clearly differentiate the BXO1 and non BXO1 group of strains in India [ 19 ]. The following strains were also included in the analysis: BXO1, three non BXO1 group strains (BXO5, BXO6, BXO20) and BXORI. The hybridisation pattern revealed that BXO8 and Nepal624 are quite distinct from each other (Fig. 5 ). We could score 42 unique bands and the data generated were used to calculate pairwise similarity coefficients and cluster analysis was performed to generate a dendrogram using UPGMA (please refer Methods). The similarity coefficient between BXO8 and Nepal624 is only 56%. The dendrogram (Fig. 6 ) indicates that BXO8 clusters with BXO#s 5, 6 and 20 at about the 58% similarity level while Nepal624 clusters with all these four strains at about the 53% similarity level. All of the Xoo strains cluster with each other at about the 51% similarity level. Although the bootstrap values for these clusters are low, it is clear that the BXO8 and Nepal624 strains are not closely related to each other. As expected for an outgroup strain, BXOR1 clusters with Xoo strains at the 29% similarity level and the bootstrap value for this cluster is a high 96.8%. Discussion We report here the complete sequence and genomic organization of the lps locus in the BXO1 strain of Xoo. Three of the genes in this locus i.e., wxoA , wxoB and wxoC were shown in an earlier study to be required for lipopolysaccharide production and virulence [ 8 ]. The predicted proteins encoded by the three new genes i.e., wxoD , wzt and wzm described in the present study are homologous to functions involved in lipopolysaccharide modification and transport. The wxoD gene encodes a predicted O-antigen acetylase which is homologous to similar functions encoded in phage genomes and other bacteria. O-antigen is the most variable part of LPS. Acetylation of O-antigen is shown to confer resistance to anitimicrobial peptides in Proteus mirabilis [ 28 ] and determines serotype in many bacterial pathogens [ 29 - 31 ]. The other two genes, wzm and wzt , are typically present in most lps gene clusters [including those of Xac and Xcc][ 23 ] as tandem genes and encode functions involved in LPS transport. The wzm and wzt genes of BXO1 have overlapping ORFs, an arrangement that is also seen in wzm and wzt genes of the lps loci in other bacteria including Xac. IS elements are frequently found interrupting many lps loci [ 22 ] and in BXO1, three IS elements interrupt the gene cluster between wxoD and wzt genes. The complete genome sequences of more than 150 bacteria are now available [ 32 ] and studies have revealed the presence of DNA segments with G+C content and codon usage different from the rest of the genome. These regions are referred to as genomic islands and are believed to be acquired by horizontal gene transfer [ 33 , 34 ]. Another feature of genomic islands is their absence from the genomes of closely related strains. Our study clearly indicates that the lps locus of Xoo strain BXO1 fulfils all of the above criterion and constitutes a genomic island. The G+C content of this lps locus, excluding the IS elements, is 50%. The transposases encoded by IS Xo8 and IS 1113 have a G+C content that is >61%. This value, which is typical for the genomes of Xoo and other xanthomonads [ 25 ], suggests the possibility that these elements have transposed into the lps locus after it's transfer into the Xoo genome. The presence of this genomic island in Xoo strains that are distributed across a vast segment of the Asian continent suggests that it was introduced into the Xoo genome early in the evolution of this pathogen. The BXO8 and Nepal624 strains do not have the lps locus that is present in the other Xoo strains. The related xanthomonad, Xoor, also has an lps locus that is different from the BXO1 lps locus. Also, different gene clusters are present at this locus in Xac and Xcc (Fig. 7 ). This indicates that multiple HGT events have occurred at this locus among xanthomonads. One HGT event occurred early in (or possibly at the time of) the evolution of the Xoo pathogen. This led to the introduction of the genomic island described in Figure 1 . Two separate HGT events are likely to have occurred in the lineages that gave rise to BXO8 and Nepal624 Xoo strains. This is inferred from the observation that BXO8 and Nepal624 are quite unrelated in their genomic background. Another HGT can be inferred to have occurred in the Xoor strain wherein sequences that are most closely related to Pseudomonas syringae pv. tomato have been introduced at one end of the lps cluster. At least one more HGT has occurred to differentiate the lps gene clusters in Xcc and Xac. The presence of invert repeats in the regions that flank the lps locus is likely to be significant. The presence of these repeats in the metB and etfA genes is especially striking as both genes encode completely different functions. The location of the repeats flanking the Xoo lps locus suggests that they might be involved in promoting recombination during HGT and/or gene regulation. A short inverted repeat sequence (GGCCAATCGA) flanking the lipopolysaccharide gene cluster has been reported in Mycobacterium avium subsp. paratuberculosis [ 35 ]. Another conserved sequence, called JUMPstart has been found located in intergenic regions upstream of polysaccharide biosynthetic gene clusters in several animal pathogenic bacteria like Escherichia coli strain K5, Vibrio cholera , etc. This sequence was implicated to be involved in gene regulation and has also been suggested to have a role in recombination [ 22 , 36 ]. As LPS is highly immunogenic, lps loci of animal pathogenic bacteria are under intense host selection and extreme variation is reported in lps specific gene clusters [ 22 ]. The observation that the two Xoo strains have different lps gene clusters suggests that the plant pathogenic bacteria are also under selection to vary their LPS. Alterations in LPS composition might result in resistance against predators like bacteriophages [ 4 , 10 ] or reduced susceptibility to certain anti-microbial compounds [ 7 ] in the host/environment. Most importantly, it might help in evasion of the host defense response. Conclusions These results provide, for the first time, evidence for substantial variation in lps biosynthetic gene clusters within different strains of a plant pathogenic bacterium. The results also indicate that multiple HGT events have occurred at this locus in various xanthomonads and provide a new parallel in the mechanisms that plant and animal pathogenic bacteria can employ to generate variability in cell surface molecules. Methods Complete sequencing of the lps locus in the BXO1 strain of Xoo The lps locus was cloned as part of a 35 kb cosmid clone, pSD5. The insert includes 0.6, 2.2, 3.5, 4.0, 6.0, 9.0 and 10 kb fragments upon Eco RI (New England Biolabs [NEB], Beverly, MA) digestion and all the fragments were subcloned in to pBlueScript (Stratagene, La Jolla, CA). Most of the sequence obtained in this study was generated by sequencing the 9 kb subclone, pBP4, using a modified shotgun sequencing procedure. Here, pBP4 was digested with Eco RI and the 9 kb fragment was gel eluted. Then the fragment was partially digested (1.5–2.5 kb) using a blunt-end cutter, Hae III (NEB) and cloned into pMOS (Amersham Pharmacia Biotech, Buckinghamshire, England). The inserts were amplified from random clones by colony PCR using vector primers and were sequenced using an ABI Prism 3700 automated DNA sequencer (Applied Biosystems, Foster City, CA). After editing, the assembly of the sequence data was done using GeneTools (BioTools, Alberta, Canada) and Blast2 [ 27 ]. Multiple single strand sequences (3–8 X coverage) were generated for each region in the sequence. Contig assembly was confirmed by restriction fragment analysis of a 12.5 kb PCR amplified product containing the lps locus that was obtained using long range PCR (Triple Master™, Eppendorf, Hamburg, Germany) with BXO1 genomic DNA as template. The sizes of the fragments corresponded to the sizes that are predicted by in silico analysis of the sequence (data are not shown). The ORF's were assigned using ORF finder [ 37 ] and genes were named as per Bacterial Polysaccharide Genes Nomenclature [ 20 ]. Two primers, Pbp1 and Pbp2 (Table 2 ), were used to derive the sequence of the 0.6 kb Eco RI fragment which is also a part of the lps locus. The Pbp1 primer binds just after the wxoC ORF (which forms part of the 3.5 kb Eco RI fragment) and Pbp2 binds within the wxoD ORF (which forms part of the 9.0 kb Eco RI fragment). A 0.67 kb PCR amplified fragment is obtained from BXO1 genomic DNA using Pbp1 and Pbp2. The band was gel eluted and was sequenced using Pbp1 and Pbp2. The sequence was found to include the 0.6 kb Eco RI fragment. In addition, the sequences of all six ORFs were confirmed by sequencing of PCR amplified fragments from genomic DNA using specific sets of gene specific primers (see the list of primers in Table 2 ). Codon Usage Pattern For each gene the frequency of codon usage for different aminoacids was calculated using a web based program [ 38 ]. Further, eight aminoacids i.e., Glycine, Valine, Threonine, Leucine, Arginine, Serine, Proline and Alanine that have atleast four synonymous codons were selected and the percentage of synonymous codons that end with G or C was calculated for each aminoacid and gene. The pattern was calculated for a group of genes by plotting mean values ± SD corresponding to a particular aminoacid. The first group was chosen to include genes that encode proteins which participate in diverse functions and are present at different locations in the Xoo genome outside the lps locus. These genes encode: a putative siderophore receptor (AF325732), Xanthomonas adhesin like protein (AF288222), a putative phytase (AY151260), rpfF (AF411962), shikimate dehydrogenase (AF258797) and secreted xylanase (AF331922). The second group comprised the six genes (excluding transposases) encoded in the Xoo lps gene cluster (AF337647). Screening of Xoo strains and Xoor for the presence of the genomic island Specific oligonucleotide primer pairs were designed and used to amplify gene specific fragments for each of the ORFs encoded in the BXO1 genomic island (see the list of primers given in Table 2 ). DNA sequencing was used to confirm the authenticity of the PCR product obtained with each primer pair using BXO1 genomic DNA as template. Southern hybridizations were performed using these gene specific PCR products as probes. Genomic DNA was isolated from Xoo and Xoor strains according to the procedure described by Leach et. al. [ 16 ]. The DNA was then digested with Eco RI (NEB) according to supplier's instructions. Digested genomic DNA was separated on a 0.8% agarose gel and vacuum transferred to a Hybond N + filter (Amersham) using 0.4% NaOH as described by Sambrook et al. [ 39 ]. Probes were labelled with α- 32 P dATP using random primer labelling kit (Board of Radiation Technology, Mumbai, India). Prehybridization, hybridisation and washings were done at 68°C as described by Yashitola et al [ 19 ]. Membranes were then exposed to phoshoimager plates and images captured using a Fuji FLA-3000 phosphoimager system (Fuji, Japan). To screen for the presence of the genomic island in different strains, a procedure for colony PCR was standardized. A portion of a single colony (or 10λ of a saturated culture that has approximately 1 × 10 9 colony forming units/ml) was lysed in 100λ of 0.01 N NaOH by boiling for 10 minutes. After spinning at 13 K for 1 min., 2λ of supernatant was used as template for PCR using the gene specific primers described above. The products were separated by electrophoresis on 1.5% agarose gels and visualized by ethidium bromide staining. TAIL-PCR and sequence analysis Specific primers were designed against the conserved metB and etfA gene sequences (Table 2 ) and the protocol for TAIL-PCR was as originally described by Liu and Whittier [ 26 ]. Sequencing of TAIL-PCR products was done using either the cglL3 or etfL3 primer. Homology searches were done using BLAST [ 21 ] through NCBI [ 40 ] and FASTA [ 41 ] through EMBL-EBI [ 42 ]. BLAST2 [ 27 ] was used to identify the homology break points in the genomic regions that flank the lps locus of BXO1 and BXO8. The sequences that were present upstream of the break points were manually examined and three repeat sequences were identified in the 3' coding regions of metB and etfA genes. Similar repeat sequences were identified in the corresponding regions of BXO8, Nepal624, BXORI, Xac and Xcc. A consensus was derived by aligning these repeat sequences and a particular nucleotide was scored if it is present in a majority of repeats. DNA fingerprinting and data analysis The Xoo IS element, IS 1112 [ 16 ], was used as the hybridisation probe. This probe has been previously used to detect genetic variability in Xoo strains from different countries [ 15 - 19 ]. DNA isolation and Southern hybridisation was done as described in the section on screening of Xoo and Xoor strains for the presence of genomic island. The presence or absence of particular bands was scored as 1 or 0, respectively. The data were analysed using the Dice coefficient option in the program WINDIST [ 43 ] to generate distance matrices. The data were used to construct a dendrogram using the NEIGHBOR program in PHYLIP (phylogeny inference software package; University of Washington, Seattle) using the UPGMA (unweighted pair group method of averages) option. To test the robustness of the dendrogram, bootstrap analysis was carried out using the WinBoot program [ 43 ] with 2,000 iterations. GenBank submissions The nucleotide sequences obtained in this study have been deposited in GenBank with the following Accession numbers: Sequence of lps locus from BXO1 (AF337647); Sequences of TAIL-PCR products from metB end of BXO8 (AY319936), Nepal624 (AY319938) and BXORI (AY319940); Sequences of TAIL-PCR products from etfA end of BXO8 (AY319937), Nepal624 (AY319939) and BXORI (AY319941). Authors' contributions PBP carried out all the aspects of the work and drafted the manuscript. RVS conceived the study, and participated in its design and coordination. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524487.xml |
520811 | Comparative effect of intraoperative propacetamol versus placebo on morphine consumption after elective reduction mammoplasty under remifentanil-based anesthesia: a randomized control trial [ISRCTN71723173] | Background Postoperative administration of paracetamol or its prodrug propacetamol has been shown to decrease pain with a morphine sparing effect. However, the effect of propacetamol administered intra-operatively on post-operative pain and early postoperative morphine consumption has not been clearly evaluated. In order to evaluate the effectiveness of analgesic protocols in the management of post-operative pain, a standardized anesthesia protocol without long-acting opioids is crucial. Thus, for ethical reasons, the surgical procedure under general anesthesia with remifentanil as the only intraoperative analgesic must be associated with a moderate predictable postoperative pain. Methods We were interested in determining the postoperative effect of propacetamol administered intraoperatively after intraoperative remifentanil. Thirty-six adult women undergoing mammoplasty with remifentanil-based anesthesia were randomly assigned to receive propacetamol 2 g or placebo one hour before the end of surgery. After remifentanil interruption and tracheal extubation in recovery room, pain was assessed and intravenous titrated morphine was given. The primary end-point was the cumulative dose of morphine administered in the recovery room. The secondary end-points were the pain score after tracheal extubation and one hour after, the delay for obtaining a Simplified Numerical Pain Scale (SNPS) less than 4, and the incidence of morphine side effects in the recovery room. For intergroup comparisons, categorical variables were compared using the chi-squared test and continuous variables were compared using the Student t test or Mann-Whitney U test, as appropriate. A p value less than 0.05 was considered as significant. Results In recovery room, morphine consumption was lower in the propacetamol group than in the placebo group (p = 0.01). Pain scores were similar in both groups after tracheal extubation and lower in the propacetamol group (p = 0.003) one hour after tracheal extubation. The time to reach a SNPS < 4 was significantly shorter in the propacetamol group (p = 0.02). The incidence of morphine related side effects did not differ between the two groups. Conclusions Intraoperative propacetamol administration with remifentanil based-anesthesia improved significantly early postoperative pain by sparing morphine and shortening the delay to achieve pain relief. | Background Postoperative administration of paracetamol or its prodrug propacetamol has been shown to decrease pain with a morphine sparing effect [ 1 - 4 ]. The effect of propacetamol administered intraoperatively on postoperative pain and early postoperative morphine consumption has not been clearly evaluated. However, for a predictable moderate postoperative pain, intraoperative administration of non-opioid analgesics such as paracetamol and postoperative intravenous administration of morphine are recommended in patients undergoing general anesthesia with remifentanil [ 5 ]. Indeed, remifentanil differs from potent mu agonists by its extremely short elimination half-life [ 6 ]. The elimination kinetics of remifentanil is so fast that its analgesic effect wears off abruptly, thus making the management of postoperative pain critical. In order to evaluate the effectiveness of intraoperative paracetamol administration in the management of postoperative pain and morphine consumption, a standardized anesthesia protocol without long-acting opioid is necessary. Thus, for ethical reasons, the surgical procedure under general anesthesia with remifentanil as the only intraoperative analgesic must be associated with a moderate predictable postoperative pain. Therefore, the present study was designed to evaluate the effect of intraoperative administration of propacetamol during remifentanil-based anesthesia on postoperative pain in patients undergoing reduction mammoplasty. Methods Patients After approval by the Local Ethical Committee and written informed consent, 36 consecutive female patients who underwent elective reduction mammoplasty were included. Exclusion criteria were the preoperative use of analgesic drugs; a body mass index ≥ 35, an American Society of Anesthesiology physical status ≥ 3 and sensitivity to paracetamol. Pain evaluation using a Simplified Numerical Pain Scale (SNPS) was explained to the patients during the preoperative anesthetic visit and the day before surgery. A standardized surgical technique was used for all patients. Anesthetic protocol Hydroxyzine 2 mg.kg -1 was given orally 12 h and 2 h before anesthesia as premedication. Before induction of anesthesia, patients were randomly allocated to either Placebo group or Propacetamol group. Randomization was based on computer-generated codes maintained in sequentially numbered, opaque envelopes. The preparation of the propacetamol or saline infusion was done by a nurse who was not in charge of the patient. The anesthetist, the patient and the nurse's staff caring for the patients in the recovery room were unaware of the treatment group. In both groups, anesthesia was induced with propofol 2.5 mg.kg -1 followed by a slow bolus (1 min) of remifentanil 1 mcg.kg -1 . Tracheal intubation was facilitated by atracurium 0.5 mg.kg -1 . Anesthesia was maintained with remifentanil 0.1 mcg.kg -1 .min -1 and isoflurane (0.5–1.0% end-tidal) with nitrous oxide (N 2 O) in 50% oxygen. Remifentanil infusion rate was increased or decreased by 0.05 mcg.kg.min -1 in order to maintain an arterial systolic pressure of 20% more or less than the baseline value. One hour before the end of surgery, which corresponded to the beginning of the skin closure, patients received either propacetamol 2 g in 50 cc saline (Propacetamol group) or 50 cc saline alone (Placebo group) infused over 10 min. At the end of surgery, administration of isoflurane and N 2 O were withdrawn and the patient was transferred in the recovery room. The anaesthetist, the patient and the nurse's staff caring for the patients in the recovery room were unaware of the treatment group. Remifentanil infusion was interrupted when the patient arrived in recovery room. Tracheal extubation was performed within a few minutes after remifentanil discontinuation. Clinical monitoring included heart rate, blood pressure, pulse oxymetry, respiratory rate, and sedation score (0: awake, 1: drowsy and 2: asleep). From the time of extubation, pain was evaluated on using a SNPS (from 0, no pain to 10 the worse pain) and intravenous 2 mg morphine was administered on request every 5 min until pain relief (SNPS<4). When pain relief was reached, SNPS was subsequently evaluated every 15 min. Morphine was interrupted when the sedation score went up to 1, systemic arterial pressure < 80 mmHg or respiratory rate less than 8/min. During the data collection period, intravenous morphine titration was further administered if SNPS was up to 4. Patients did not receive antiemetic prophylaxis. If post-operative nausea and vomiting (PONV) occurred, metoclopramide 10 mg and ondansetron 4 mg if necessary were intravenously administered. Patients fulfilling Aldrete criteria [ 7 ] were discharged from recovery room. Measurements Morphine requirement, pain and sedation scores were measured every 5 min until pain relief was obtained. When SNPS was below 4 during 15 min, parameters were subsequently recorded every 15 min. Morphine side effects (nausea, vomiting, urinary retention, shivering and itching) and need for supplemental medications (e.g., antiemetics) were also recorded. The total dose of morphine in recovery room was the primary end point. Pain scores after extubation and one hour after tracheal extubation, delay for morphine requirement, delay for pain relief and incidence of morphine side effects were recorded. Statistical analysis Data are expressed as mean (± standard deviation) for quantitative variables normally distributed, or otherwise as median (25th – 75th percentiles) when data were not normally distributed, and as percentage for categorical variables. Data were analyzed using Statview 5.0 software (SAS Institute Inc, USA). For intergroup comparisons, categorical variables were compared using the chi-squared test and continuous variables were compared using the Student t test or Mann-Whitney U test, as appropriate. A p value less than 0.05 was considered as significant. Anticipating a standard deviation of 2.49 [ 8 ], it was calculated that 15 patients at least were necessary to show a difference between groups in morphine consumption of 4 mg (considered as a clinically relevant difference) with a 80% power and a 5% type 1 error. Results Thirty-six patients were included during a 12 months period: 19 in Propacetamol group and 17 in Placebo group (Table 1 ). There was no significant difference between the groups concerning clinical characteristics, anesthesia duration and total amount of remifentanil administered. In all patients, extubation was obtained within 7 ± 3 min (Table 1 ) after remifentanil discontinuation. Table 1 Demographic characteristics and perioperative parameters. Placebo Group ( n = 17) Propacetamol Group ( n = 19) Age (years) 41(16) 34 (14) Body mass index (kg.m -2 ) 26 (4) 25 (3) Duration of anesthesia (min) 245 (55) 245 (80) Remifentanil consumption (μg.kg -1 .min -1 ) 0.150 (0.055) 0.155 (0.040) Final intraoperative corporeal temperature (Celsius) 36.8 (0.4) 36.7 (0.5) Delay before extubation after remifentanil interruption (min) 7 (3) 7 (3) Data are expressed as mean (standard deviation) for age, body mass index, final intraoperative corporeal temperature and delay before extubation. Other data are expressed as median (interquartile). In recovery room, cumulative morphine consumption was significantly lower in the Propacetamol group than in the Placebo group (Table 2 ). Five minutes after extubation, pain scores were similar in both groups (SNPS = 6). Pain scores one hour after tracheal extubation were significantly lower in the Propacetamol group than in the Placebo group (Table 2 ). Moreover, the time to reach a SNPS score less than 4 was significantly shorter in Propacetamol group compared to the Placebo group. All the patients received intravenous morphine titration in the first hour after extubation and three patients (one in Placebo group and two in Propacetamol group) required a morphine titration over one hour after extubation. Once a SNPS value less than 4 was obtained, pain scores remained stable and similar in both groups except in one patient in Placebo group who required an additional 2 mg intravenous bolus of morphine 80 min after extubation. Table 2 Postoperative intravenous morphine requirement and pain scores in recovery room. Placebo Group ( n = 17) Propacetamol Group ( n = 19) p value Morphine consumption in recovery room (mg) 16 [8–34] 10 [6–28] 0.01 Delay between extubation and first morphine administration (min) 5 [5–20] 5 [5–15] NS SNPS score five minutes after extubation 6 [0–9] 6 [0–10] NS SNPS score one hour after extubation 3 [2–6] 2 [0–4] 0.003 Delay between extubation and obtaining a SNPS score < 4 (min) 40 [20–85] 30 [15–70] 0.02 Data are expressed as median [25 th –75 th percentile]. P < 0.05 was considered as statistically significant. Pain score was evaluated on using a Simplified Numerical Pain Scale (SNPS: from 0, no pain to 10 the worse pain). The incidence of morphine adverse effects was similar in both groups: 5 patients had nausea (3 in Propacetamol and 2 in Placebo group, p=NS) and 4 patients had vomiting (2 in each group, p=NS), no other side effects were observed. In one patient receiving placebo, morphine titration was interrupted because of nausea and vomiting. Discussion This study shows that propacetamol administered one hour before end of surgery reduced the morphine dose given over the first four postoperative hours and shortened the elapsed time to obtain a SNPS under 4 in patients undergoing elective reduction mammoplasty. In our study, surgical technique and anesthetic protocol were similar in both groups. Remifentanil was the only analgesic used during anesthesia period and was interrupted before morphine administration. Thus, the beneficial effect on postoperative pain observed is clearly linked to intraoperative administration of propacetamol. In a recent study [ 9 ], Verchère and colleagues failed to demonstrate a postoperative analgesic effect of intraoperative propacetamol administration, after remifentanil anesthesia for supratentorial craniotomy. Pain after supratentorial neurosurgery was too severe and paracetamol was insufficient to relief it. In our study mammoplasty was chosen because postoperative pain is moderate [ 10 ], and intravenous administration of morphine was used in recovery room. Thus, the morphine sparing effect of intraoperative administration of paracetamol could be really evaluated with respect of ethical requirement. Our results are apparently at variance with those of other previous studies. Paracetamol given rectally immediately after induction of anesthesia [ 11 ] or at the end of gynecological surgery [ 12 ] and orally before surgery [ 13 - 16 ] failed to improve early postoperative analgesia. The negative results of these studies may be ascribable to several causes such as the low initial pain score in the control group [ 11 , 12 , 15 , 17 ], and the difference in the route used for paracetamol administration [ 11 - 16 ]. An other hypothesis to consider is the use of long-acting opioid such as fentanyl that might have contributed to the early post-operative analgesia [ 14 , 18 ]. Cobby and colleagues observed a morphine sparing effect when paracetamol 1.3 g was administered rectally at the end of hysterectomy [ 19 ]. One explanation is that plasma concentration after 1.3 g paracetamol was sufficient to achieve opioid sparing effect comparable with that of intravenous propacetamol. This hypothesis is strengthened by the results of another trial showing that after rectal administration of a high dose of paracetamol (40 and 60.mg kg -1 ) pain score and analgesic demand were significantly reduced in the early postoperative period [ 20 ]. The presently observed incidence of postoperative nausea and vomiting was of 25% and was similar to that of a previous study [ 21 ]. Despite the reduced dose of postoperative morphine in the Propacetamol group, the incidence of postoperative nausea and vomiting was not diminished. Our results are in agreement with the recent study of Aubrun and co-workers [ 4 ] who observed that postoperative intravenous propacetamol allowed a morphine-sparing effect but did not reduce the incidence of morphine-related adverse effects in patients undergoing general surgery. Propacetamol was administered at the beginning of skin closure, which corresponds to one hour before the end of surgery. This delay may be insufficient to achieve pain control immediately after tracheal extubation, as the peak effect of intravenous propacetamol was shown to occur only two hours after its administration [ 22 ]. Nevertheless, we considered that it was not feasible to administer propacetamol earlier, as in our practice duration of surgery was unpredictable. In summary, intraoperative propacetamol administration in women undergoing reduction mammoplasty improved significantly early postoperative pain in recovery room, and should be recommended for postoperative pain management. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520811.xml |
524493 | CD155/PVR plays a key role in cell motility during tumor cell invasion and migration | Background Invasion is an important early step of cancer metastasis that is not well understood. Developing therapeutics to limit metastasis requires the identification and validation of candidate proteins necessary for invasion and migration. Methods We developed a functional proteomic screen to identify mediators of tumor cell invasion. This screen couples Fluorophore Assisted Light Inactivation (FALI) to a scFv antibody library to systematically inactivate surface proteins expressed by human fibrosarcoma cells followed by a high-throughput assessment of transwell invasion. Results Using this screen, we have identified CD155 (the poliovirus receptor) as a mediator of tumor cell invasion through its role in migration. Knockdown of CD155 by FALI or by RNAi resulted in a significant decrease in transwell migration of HT1080 fibrosarcoma cells towards a serum chemoattractant. CD155 was found to be highly expressed in multiple cancer cell lines and primary tumors including glioblastoma (GBM). Knockdown of CD155 also decreased migration of U87MG GBM cells. CD155 is recruited to the leading edge of migrating cells where it colocalizes with actin and αv-integrin, known mediators of motility and adhesion. Knockdown of CD155 also altered cellular morphology, resulting in cells that were larger and more elongated than controls when plated on a Matrigel substrate. Conclusion These results implicate a role for CD155 in mediating tumor cell invasion and migration and suggest that CD155 may contribute to tumorigenesis. | Background Metastasis is responsible for greater than 90% of cancer-related deaths [ 1 ]. It is therefore of great importance to develop therapies that limit this process. Cell migration plays a key role in invasion, an early step in metastasis, and proteins that regulate migration are often upregulated in tumor cells [ 2 ]. Cell migration also plays a key role in the dispersal of tumor cells within a tissue. In glioblastoma, the most aggressive form of brain cancer, tumor cells disperse so extensively that common treatment approaches such as resection or radiation therapy are not effective in checking progression [ 3 ]. Both invasion and dispersal are complex processes that require migration of individual cells from the tumor core into surrounding tissue and the extracellular matrix. Cell migration requires a coordinated orchestration of complex events including polarization, protrusion, adhesion, de-adhesion, and retraction [ 4 ]. Many cell-surface proteins are involved in regulating migration. Growth factor receptors receive environmental cues and initiate signaling cascades resulting in polarization and directional migration [ 5 ]. Cell adhesion molecules (CAMs) such as integrins, cadherins, and immunoglobulin family proteins, mediate adhesion and deadhesion between a cell and its neighbors or the extracellular matrix (ECM) and can also contribute to polarization and directional motility in response to soluble ECM proteins. CAMs sit at the top of many signaling cascades that regulate actin and microtubule dynamics through Rho family GTPases [ 2 ]. While many proteins have been described to play a role in cell migration, the mechanisms through which they act remain unclear [ 2 ]. Establishing which of these proteins are required for tumor invasion and migration is an important first step to developing therapeutics aimed at limiting the metastasis or dispersal of tumor cells. In the post-genome era, global strategies are being developed to identify new players in complex biological processes such as tumor cell invasion. Microarray experiments have identified many differentially expressed genes that may contribute to enhanced invasion [ 6 - 10 ], but these correlative expression changes can only suggest functional importance. RNAi screens for cancer-relevant phenotypes have already identified several new gene targets [ 11 , 12 ]. Such approaches are limited, however, by the availability of genome-wide RNAi libraries, the possibility of genetic compensation following chronic inactivation, and the inability of RNAi to knockdown stable proteins with slow turnover. Proteomic screens have the advantage of being able to assess the proteome in high throughput but do not directly address function [ 13 ]. To complement these approaches, we have developed a high-throughput, acute protein inactivation strategy called fluorophore-assisted light inactivation (FALI) that allows for direct assessment of protein function through the systematic inactivation of proteins [ 14 - 16 ]. We have previously applied this approach on a smaller scale to identify surface proteins important for tumor cell invasion and have established a role for extracellular Hsp90 in activating metalloproteinases required for invasion [ 16 ]. Here we used a larger, unbiased functional proteomic screen to demonstrate that CD155, the receptor for poliovirus, contributes to tumor cell invasion by regulating cell migration. Methods Cells HT1080 human fibrosarcoma, Hs27 human fibroblasts, and U87MG human glioblastoma cells were obtained from ATCC. Normal human astrocytes were obtained from Cambrex Bioproducts. Cells were maintained in DMEM supplemented with 10% fetal bovine serum and penicillin/streptomycin (Invitrogen; HyClone). HT1080 cells were additionally supplemented with 0.1 mM non-essential amino acids (Invitrogen). All cells were grown at 37°C under a humidified 7% CO 2 atmosphere. Antibodies Monoclonal antibodies used for FALI were as follows: β1-integrin (JB1, Chemicon); CD155 (D171, Neomarkers; pv404.19, Beckman Coulter). Two additional CD155-specific monoclonal antibodies (5D11, ID8) were generated by fusing specific binding scFvs selected from our library to a human IgG backbone. ScFv 1A2 was used as a negative control in the migration assay. 1A2 was selected for binding to the surface of HT1080 cells (see scFv Library Generation) and was confirmed to bind to the surface of HT1080 and U87MG cells by immunocytochemistry, though its protein target is not known. Antibodies used for immunocytochemistry and immunoblotting were as follows: CD155 (D171; CD155 rabbit polyclonal, gift of Dr. Eckard Wimmer); αv-integrin (AB1930, Chemicon); ErbB2 (06-562, Upstate). Actin was visualized with rhodamine-phalloidin (Molecular Probes). Fluorophore-labeled secondary antibodies were obtained from Molecular Probes; peroxidase-labeled secondary antibodies were from Cell Signaling. scFv Library Generation Spleen RNA was harvested from HT1080 immunized mice as described [ 16 ]. Immunoglobulin cDNA was synthesized using a primer mix and variable regions amplified using specific primers. Products were cloned into the phage display vector pXP10 and transfected into E. coli TG-1 resulting in a library of 10 7 independent clones. HTl080-specific scFvs were selected by immunopanning phage against fixed HT1080 lysate, resulting in 2760 binders. These scFvs were recloned into expression vector pXP7 (containing his- and E-tags) and expressed in TG-1 cells. Bacterial lysates containing scFv were prepared and tested for binding to the surface of fixed HT1080 cells by ELISA. This additional round of selection yielded 595 HT1080 surface binders. These scFvs were confirmed to bind to the surface of HT1080 by immunocytochemistry on live cells. For FALI/screening, his-tagged scFvs were purified from bacterial lysates using Ni-NTA Superflow resin (Qiagen). FALI Antibodies or scFvs were conjugated with FITC (Molecular Probes) at pH 9.5 at room temperature as previously described [ 17 ]. Cells were detached with Versene (Invitrogen) and resuspended in serum-free, phenol red-free HBSS (Invitrogen). Cells were incubated with FITC-conjugated antibodies for 1 h at room temperature with gentle rocking and were then transferred in at least sextuplet to replicate clear, flat-bottomed 96-well plates on ice. One plate was illuminated for 1 h with 300 W (1 × 10 5 lux) blue-filtered light (Brilliant Blue #69, Roscolux) using a high-powered slide projector (Ektagraphic III, Kodak). A replicate control plate was kept in the dark for 1 h. Invasion and migration assays FALI invasion assays with HT1080 cells were done as described previously [ 14 , 16 ] but used the scFv library described above. 1 × 10 5 cells were labeled with cell tracker orange, incubated with 20 μg/ml of FITC-labeled scFv, irradiated (or kept in the dark) with blue-filtered light, and 5 × l0 4 cells were loaded onto matrigel-coated (4 μg, top) polycarbonate membranes (8 μM, 96-well, Neuroprobe). Each sample was assayed in triplicate in at least two independent experiments. scFvs that showed a significant change in invasion (p < 0.01 and change > 2 standard deviations) were assayed a third time with a new scFv preparation. U87MG and HT1080 migration assays were performed essentially as above, but excluded matrigel and used 8μM, 96-well Fluoroblok membranes (BD Biosciences). Cell invasion or migration was quantified using a fluorescent plate reader (SpectraFluor Plus, Tecan) and confirmed by visualization under an inverted fluorescent microscope. Immunoprecipitation and Mass Spectrometry To identify scFv protein targets, candidate scFv genes were re-cloned into expression vector pXP14, containing a strep-tag. Purified scFvs were coupled to StrepTactin Sepharose (50 μg/50 μl resin) and the washed scFv-beads were added to 1 mg HT1080 lysate. The scFv-target complexes were eluted (10 mM D-desthiobiotin, 0.1% Tween 20 in PBS) and the immunoprecipitated proteins were analyzed by SDS-PAGE and silver staining. In a parallel experiment, the immunoprecipitated proteins were subjected to deglycosylation using N-glycosidase F prior to SDS-PAGE analysis. Stained bands were excised and subjected to in-gel tryptic digestion. The peptide fragments were extracted from the gel, desalted on ZipTip μC18, the eluted peptides spotted on a Teflon-coated MALDI target, let dry and overlayed with 1 μl of a 3.5 mg/ml solution of α-Cyano-hydroxycinnamic acid. The samples were analyzed on a STR-DE Voyager MALDI mass spectrometer (Applied Biosystems) and the obtained peptide masses were used for protein identification via peptide mass fingerprint, searching all entries for the species Homo sapiens in the NCBI and SwissProt databases. Alternatively, the extracted peptide fragments were analyzed by nano electrospray mass spectrometry (nanoES-MS) on a Q-STAR QqTOF mass spectrometer (PE SCIEX). Relevant ions were selected for CID (collision induced dissociation)-MS and the obtained fragment ion data used for Peptide Sequence Tag database search. CD155 siRNA A double stranded siRNA oligonucleotide targeting CD155 (5'-CAACUUUAAUCUGCAACGUdTdT-3') was chemically synthesized (Dharmacon Research) and transfected into HT1080 cells using Oligofectamine (Invitrogen) following manufacturers instructions using 200 nM siRNA per 10 cm dish. Cells were incubated with siRNA in OptiMEM (Invitrogen) for 6 hrs after which time normal growth media was added. Cells were then incubated for 48–72 h to achieve >80% knockdown of CD155. Control cells were transfected with a scrambled siRNA oligonucleotide at matching concentration. Cells were then inserted into the migration assay described above or used for morphology experiments. Cell morphology measurements HT1080 cells were co-transfected with siRNA (scramble control or CD155-specific) and fluorescently labeled oligonucleotide (10 nM, Sequitur) for 48 hours. Cells were detached with Versene, and 5–15 × 10 3 cells were loaded onto glass coverslips coated with Matrigel (2μg/ml, BD Biosciences). After 2 hours of incubation at 37°C/7% CO 2 , cells were fixed and immunostained for CD155 using mAb D171. Cells were visualized with a Nikon Diaphot 200 microscope and images taken of >100 transfected cells (containing fluorescent oligo). Analysis of images was performed with OpenLab software (Improvision). Measurements of cell area, perimeter, and shape were made for each condition. Wound healing assay 8-chamber slides (Falcon) were coated with matrigel (2 μg/ml) and blocked with FCS. 100,000 cells were plated in each well and grown to confluency. A 20-gauge needle was used to create a linear wound and cells allowed to recover for 3 h at 37°C. Cells were fixed and processed for immunocytochemistry as described below. Immunocytochemistry Cells were fixed in PBS/4% paraformaldehyde/4% sucrose, blocked in PBS/0.01% triton-x-100/10%FBS, and incubated in primary antibody for 1 h at rt. Appropriate species-specific secondary antibodies conjugated to Alexa 488 or 594 were used to visualize antibody staining on a Leica SP2 confocal microscope using LCS software. Antibodies: CD155 (D171), αv-integrin (AB1930), actin (rhodamine-phalloidin, Molecular Probes), ErbB2 (6562). Secondary antibodies alone were used to control for non-specific staining. For primary tissue, paraffin sections from a human tissue library were stained with biotinylated anti-CD155 human mAb 1D8 at 200 μg/ml and visualized with streptavidin-hrp and NovaRed substrate. For glioblastoma tumors, we used tissue microarrays, made from 20 primary tumors arrayed in quadruplicates of 1 mm cores with a Beecher Instrument arrayer. Positive staining was visualized with DAB substrate. Immunoblotting Pelleted and PBS-washed cells were lysed in NP40 lysis buffer (0.2% NP-40, 150 mM NaCl, 20 mM Tris pH7.5, 10% glycerol) with protease inhibitors (Roche) at 4°C. Lysates were cleared by centrifugation and quantified using the DC Protein Assay (BioRad). 30 μg lysate was separated on a 10% SDS-PAGE gel and transferred to a nitrocellulose membrane. Membranes were blocked in 5% nonfat dry milk in PBS and probed with primary antibody overnight. Antibody binding was detected with peroxidase-conjugated secondary antibodies (Cell Signaling) and visualized using ECL substrate (PerkinElmer). Results Functional proteomic screen reveals a role for CD155/PVR in tumor cell invasion and migration We generated a recombinant single chain variable fragment (scFv) antibody library that recognized proteins on the surface of HT1080 fibrosarcoma cells, a highly invasive tumor cell line. ScFvs were selected from a phage display library generated from mice immunized with fixed HT1080 cells [ 16 ]. Genes encoding the selected scFvs were re-expressed as scFv antibodies and selected by ELISA for HT1080 surface binding. The selected scFvs were conjugated to fluorescein and used to acutely inactivate their protein targets by fluorophore-assisted light inactivation (FALI). The invasiveness of FALI- and control-treated cells was then compared using a 96-well transwell assay incorporating a matrigel-coated 8μM filter above a serum chemoattactant (Fig. 1a ). 338 scFvs were screened in triplicate using this FALI-invasion assay. 15 scFvs caused a significant reduction of invasion compared to non-FALI controls (p < 0.01, unpaired t-test) and an amplitude change of greater than twice the average standard deviation. The majority of scFvs screened (323) had no significant effect on invasion and serve as an internal control. The 15 positive scFvs were re-screened using fresh scFv preparations in triplicate, and six scFvs were selected that continued to satisfy both criteria of significance (Fig. 1b ). Sequencing of the scFv cDNAs revealed two unique groups of clones. The first group (I) contained a single scFv binder while the second group (II) included 5 scFvs with identical or nearly identical variable heavy and light chains. Protein targets of the two scFv groups were immunoprecipitated and identified by mass spectrometry. The target of group I was α3βl-integrin, a promiscuous extracellular matrix binder that plays multiple roles in cell adhesion, morphology, migration, and invasion [ 18 ]. Identifying α3βl-integrin demonstrates the ability of our screen to reveal proteins with a confirmed role in tumor invasion. The target of group II was CD155, the poliovirus receptor. CD155 is a member of the nectin subclass of immunoglobulin domain proteins whose cellular function has not yet been established. To confirm the identification of CD155 as a mediator of invasion, we repeated the invasion assay using a previously characterized monoclonal antibody specific for CD155 (D171). FALI of CD155 significantly inhibited invasion of HT1080 cells by 32% (p < 0.01, t-test; Fig. 2a ), consistent with the screening result. In order to determine whether this result was specific to invasion through matrigel or due to effects on cell migration, we repeated the transwell experiment in the absence of matrigel using several different CD155-specific monoclonal antibodies, either previously characterized (D171, pv404) or newly generated by fusing the variable regions from our CD155-binding scFvs to a human IgG backbone (5D11, 1D8). FALI of CD155 significantly inhibited transwell migration by 20 to 23% (p < 0.01, t-test; Fig. 2b ), suggesting a role for CD155 in cell migration that is responsible for the bulk of its contribution to invasion. FALI in the absence of antibody or in the presence of scFv 1A2, which had no effect in the invasion screen, did not alter migration. FALI of CD155 did not affect cellular viability or proliferation (data not shown). FALI with combinations of CD155 binders did not enhance the inhibition of migration (Fig. 2b ), suggesting that inactivation was maximal or that the antibodies bound and saturated a common epitope. To further validate the role of CD155 in tumor cell migration, we developed a siRNA duplex targeting CD155 mRNA as a complementary, chronic means of protein inactivation. Knockdown of CD155 mRNA yielded ~90% depletion of CD155 protein at 72 h and a 23% reduction in migration compared to control cells transfected with a scrambled siRNA duplex (p < 0.01, t-test; Fig. 2c ). The extent of migration inhibition due to siRNA was equal to the inhibition seen by FALI, supporting the specificity of the antibodies. The observed changes in migration were not due to changes in survival or proliferation as measured by an MTS viability assay (data not shown). Taken together, the results from FALI and siRNA knockdown of CD155 clearly establish a role for CD155 in tumor cell invasion and migration. CD155/PVR protein is highly expressed in cancer cells and primary tumors compared to normal counterparts Since our screen was performed using a library selected for binding to HT1080 surface proteins, and thus might have a tendency to target proteins upregulated in these cells, we profiled CD155 expression in these and other cells. Lysates prepared from normal fibroblasts, fibrosarcoma, normal astrocytes, and GBM cells were tested for expression of CD155 by immunoblot using a polyclonal CD155 antibody (gift of Eckard Wimmer). High levels of CD155 expression were observed in HT1080 and U87MG cells whereas the protein was only weakly expressed in their non-tumor counterparts (Fig. 3a ). Since HT1080 and U87MG cells are highly invasive while hs27 cells and normal astrocytes are not (personal observation), these results suggest that upregulation of CD155 may contribute to an invasive phenotype. Given our finding that CD155 appeared to be overexpressed in our model tumor cell lines, we evaluated CD155 expression levels in normal and cancerous human tissue. We performed immunohistochemistry on paraffin sections taken from a tissue library using mAb 1D8. In normal tissue we observed moderate staining in kidney, plasma cells, liver, lung, theca interna of the ovary, and testis (data not shown). No staining was observed in normal adrenal, bladder, brain, breast, colon, heart, pancreas, placenta, prostate, skin, skeletal muscle, small intestine epithelium, spleen, stomach, thymus, thyroid, or uterus (at least two samples examined per tissue). In cancer tissue, we observed extensive staining in a subset of samples taken from several different tumor types (Fig. 3b ). These included prostate carcinoma (4 out of 10 samples examined), renal cell carcinoma (4/10), pancreatic carcinoma (7/10), colon carcinoma (2/10), ovarian carcinoma (2/10), non-small cell lung carcinoma (1/10), and breast carcinoma (1/10). Since CD155 had previously been suggested to be upregulated in glioblastoma (GBM) tumors [ 19 ], we performed immunostaining on a tissue array to examine CD155 protein expression across twenty different GBM tumor samples. Staining was observed in eight of the samples (Fig. 3c ). Two types of positive staining were evident: scattered positive cells within a predominantly negative sample (5/20), or diffuse staining across many cells in the sample (3/20). Collectively, these data indicate that CD155 expression is frequently elevated in primary tumors. Since normal and cancerous tissue samples were not collected from the same patient, we cannot determine if elevated CD155 expression correlates with tumorigenesis, but speculate that such an association may exist. CD155/PVR is recruited to the leading edge of migrating tumor cells and colocalizes with actin and αv-integrin To address the role of CD155 in migrating cells, we employed a modified wound-healing assay and examined the sub-cellular localization of CD155. HT1080 cells were plated onto chambered tissue culture slides coated with a thin layer of Matrigel ECM substrate and grown to near confluence. A linear wound was made using a 20-gauge needle and the cells were allowed to recover for 3 h. Cells were fixed and immunostained to visualize CD155. CD155 was found to preferentially localize to the leading edge of cells, though some staining in trailing edges and cell-cell contacts could also be seen (Fig. 4a ). In cells plated in isolation, where directionality could not be established, CD155 was consistently observed at some but not all peripheral edges of cells (data not shown). These results suggest that CD155 is recruited to the leading edge of migrating cells where it may be involved in directional motility. Given our findings that CD155 was important for cell migration and that it localized to the leading edge of migrating cells, we asked whether CD155 might co-localize with other proteins known to be involved in motility. We used immunofluorescence and confocal microscopy to visualize CD155 along with actin and αv-integrin. CD155 colocalized extensively with actin ruffles at the leading edge of migrating cells (Fig. 4b ), suggesting a potential link between CD155 and the actin cytoskeleton. CD155 also colocalized with αv-integrin, a known mediator of ECM adhesion [ 20 ], but not the epidermal growth factor receptor family member ErbB2, a mediator of growth factor signaling [ 21 ]. Thus, CD155 is associated with key players in substrate adhesion at the leading edge, and may be working in concert to mediate motility. CD155/PVR influences cellular morphology The previous section showed that CD155 localizes to the leading edge of migrating cells and colocalizes with known mediators of motility. Since cell shape changes are often associated with changes in motility and/or adhesion, we next investigated whether knockdown of CD155 by RNAi affected cellular morphology. HT1080 cells were transfected with either a CD155-specific or scrambled control siRNA (200 nM) along with a fluorescent, non-specific oligo (10 nM) to identify transfected cells. 48 hours after transfection, cells were plated at low density onto coverslips that had previously been coated with Matrigel, fixed, and immunostained for CD155 to confirm protein knockdown. Only cells containing fluorescent oligo were selected for analysis. CD155 knockdown cells had significantly larger perimeters and appeared more irregular in shape than control cells (Fig. 5 ). These findings suggest that CD155 has a role in cell size and shape, perhaps by regulating adhesion of cells to their substrate. CD155/PVR regulates migration of glioblastoma cells Our studies so far have been conducted using HT1080 fibrosarcoma cells. To assess the generality of CD155 function in cancer, we asked whether it could regulate the migration of other tumor cells in vitro . Our expression studies suggested that CD155 was upregulated in a subset of glioblastoma (GBM) tumors for which migratory behavior is poorly understood [ 3 ]. U87MG GBM cells were found to express high levels of CD155 (Fig. 3a ). Knockdown of CD155 protein by FALI in U87MG cells resulted in a significant (16 to 22%) decrease in transwell migration towards a serum chemoattractant (p < 0.01, t-test; Fig. 6 ). FALI in the absence of antibody or in the presence of scFv 1A2, which binds to the surface of U87MG cells, did not alter migration. Cellular viability and proliferation were unchanged (data not shown). These results were consistently reproduced using multiple independent monoclonal antibodies targeting CD155 (D171, pv404, 5D11, 1D8). FALI with combinations of these antibodies did not enhance the inhibition of migration (Fig. 6 ), similar to our observations in HT1080 cells. These results demonstrate a role for CD155 in regulating migration across multiple tumor cell types. Discussion We developed a functional proteomic screen to identify surface proteins involved in tumor cell invasion [ 16 ] and here have expanded it to interrogate a library of 338 single chain phage display antibodies. One of the proteins identified as a mediator of invasion was CD155, the poliovirus receptor. This work reveals a novel role for CD155 as a mediator of tumor invasion that is likely due to its function in cell migration. Knockdown of CD155 by FALI or by RNAi resulted in impaired in vitro migration and a pronounced change in cellular morphology with cells becoming more elongated and irregular in shape. CD155 localizes to the leading edge of migrating tumor cells and co-localizes with actin ruffles and αv-integrin, suggesting that CD155 may act in motility and/or cell-substrate adhesion. We also observed elevated expression of CD155 in a number of different cancer cell lines and primary tumors, suggesting a link between CD155 and tumorigenesis. The endogenous function of CD155 is not well understood. CD155 is a type I transmembrane glycoprotein first identified based on its ability to mediate the binding of poliovirus to host cells [ 22 ]. It is a member of the immunoglobulin (Ig) superfamily and belongs to a subclass that contains three Ig-like domains (V-C2-C2). This subclass includes the nectins and several nectin-like proteins including the rodent Tage4 gene [ 23 ]. Nectins have been implicated in organizing cell-adherens junctions through homo-and heterophillic adhesion [ 24 , 25 ]. While nectins bind to the actin cytoskeleton through afadin, CD155 does not [ 24 ], suggesting that CD155's cellular role is distinct from that of nectins. Several proteins have been found to interact with CD155. The ECM protein vitronectin binds CD155 in vitro suggesting that CD155 may mediate cell-substrate adhesion [ 26 ]. Our findings that CD155 co-localizes with αv-integrin, a receptor for numerous ECM proteins including vitronectin, is consistent with previous reports [ 23 ] and suggests a functional role for CD155 in mediating adhesion. Activation of integrins leads to assembly of focal adhesion complexes that stabilize cellular interaction with its substrate through intracellular signaling and rearrangement of the actin cytoskeleton [ 27 ]. Our experiments showed that loss of CD155 inhibited migration and induced cell spreading. This phenotype is similar to that observed in F397-FAK fibroblasts in which focal adhesions are enhanced and cell spreading is increased [ 28 ]. We speculate that CD155 could be involved in modulating integrin/substrate interactions leading to decreased adhesion or increased turnover of focal adhesions. Another Ig-domain containing protein, CD47, has been shown to bind to αv-integrin and is present in early adhesion complexes at the leading edge of spreading melanoma and human vascular endothelial (HUVEC) cells [ 29 ]. CD47 appears to regulate integrin activation and contribute to integrin-mediated adhesion events [ 30 ]. CD155 has also been shown to interact with nectin-3 [ 23 ], the dynein motor protein Tctex-1 [ 31 ], and also to reside proximal to CD44 [ 32 ]. Future studies will address the importance of these interactions for cancer cell migration. Our results, in which CD155 inhibition reduces migration, are also consistent with a model in which transient interactions between CD155 and ECM result in pro-migratory signals. For example, it is known that binding of integrins to ECM proteins induces pro-migratory signaling through clustering of associated kinases [ 33 ]. CD155 itself may transduce signals when bound to ECM proteins or could be involved in the clustering of larger complexes. During preparation of this manuscript, Oda et al. reported that crosslinking of exogenously expressed CD155 resulted in tyrosine phosphorylation of its cytoplasmic tail, and concurrent reductions in focal adhesion kinase (FAK) and paxillin phosphorylation in NIH3T3 mouse fibroblasts [ 34 ]. Crosslinking of CD155 also resulted in decreased adhesion to fibronectin, a reduction in the number of focal adhesions, and an increase in migration [ 34 ]. It is possible that overexpression of CD155 in cancer cells drives dimerization of CD155 in the absence of ligand, resulting in decreased adhesion and increased migration as well as other signaling events. CD155 expression has been reported widely to be restricted to primates [ 35 , 36 ], but recent work suggests that Tage4 may be a rodent ortholog [ 37 , 38 ]. At the amino acid level, Tage4 shares only 42% homology with CD155 [ 38 ] and rodents are not susceptible to polio virus infection [ 22 , 39 ]. However, Tage4 shares the extracellular structure of CD155 and the two genes reside in syntenic chromosomal regions [ 38 ]. Emerging data suggest functional similarities between the two proteins. Tage4 has been shown to bind to both nectin-3 and vitronectin [ 37 , 38 ] and also appears to colocalize with αvβ3-integrin [ 37 ]. Recently, Tage4 has been implicated in cell migration [ 37 ]. Overexpression of Tage4 led to increased migration of murine L cells in a serum- and integrin-dependent manner while Tage4 mutants inhibited motility [ 37 ]. Furthermore, V12Ras-transformed NIH3T3 cells, which form tumor nodules in the lungs of nude mice, were found to express elevated levels of Tage4 and expression of a dominant-negative Tage4 inhibited the ability of these cells to form nodules [ 37 ]. Due to low sequence conservation and the lack of functional data for CD155, it has been difficult to resolve whether Tage4 and CD155 are true orthologs. Our identification of a role for CD155 in tumor cell migration supports the idea that these proteins are functionally related. Thus, it will be interesting to compare the two proteins in future studies in order to better define the mechanism of action for CD155 both in normal cells and in cancer states. We observed high levels of CD155 protein expression in a subset of several different types of primary tumor. Previously, expression of the CD155 gene had been reported to be upregulated in colon cancer [ 40 ] and possibly glioblastoma [ 19 ]. Here we have extended that observation at the protein level to several additional tumor types, including cancers of the prostate, kidney, pancreas, lung, ovary, breast, and brain, suggesting a much broader role for CD155 in tumorigenesis. A search of the EST and SAGE library databases maintained by the Cancer Genome Anatomy Project (CGAP; ) using the unique identifier AACCACCCAG supports the idea that expression of the CD155 gene may be elevated in several tumor types including colon, brain, kidney, pancreas, lung, and stomach (Table 1 ). Our finding that CD155 is involved in tumor cell migration in fibrosarcoma and glioblastoma cells implicates CD155 as a mediator of metastasis and dispersal. The selective expression of CD155 in tumors compared to normal tissue further supports the idea that targeted inhibition of CD155 could serve as a useful therapeutic approach to limit the spread of tumor cells in vivo . Very recently, Ochiai et al. reported that CD155 expression is upregulated in several breast cancer cell lines and primary breast tumors and demonstrated that an oncolytic poliovirus recombinant delivering a toxic payload could selectively kill breast cancer cells [ 41 ]. Our findings suggest that such a therapeutic approach could also have value in treating other cancer types. Since elevated expression of CD155 was detected in a subset of samples from the examined tumor types, it is possible that CD155 expression may represent a late-stage event in tumorigenesis. It is also possible that CD155 could lie in one of several different oncogenic pathways. Further research is necessary to determine if and how CD155 contributes to cancer progression in vivo . This work extends the utility of our FALI-based functional screening approach in identifying proteins with a role in tumor cell invasion. Our previous screen identified an extracellular role for Hsp90 in regulating tumor cell invasion through regulation of MMP2 activity [ 16 ]. In contrast, this screen has identified a role for CD155 in regulating tumor cell motility. Thus, our approach can yield novel mediators of tumor cell invasion that are involved either directly in invasion or more generally in cell migration. Future applications of this technology will likely yield additional validated targets and open new avenues for research. Conclusions In summary, we have applied a novel, functional proteomic approach to identify proteins that mediate tumor cell invasion and have identified a novel role for CD155 in regulating cancer cell invasion and migration. We suggest that CD155 may control migration by regulating cell-substrate adhesion. We have further shown that CD155 is commonly expressed at high levels in primary tumors and speculate that it may contribute directly to tumorigenesis by enhancing cancer cell migration in vivo . Competing interests KS, BE, JS, MS, JR, DL: none declared CZ, CT, CU, LI, DJ: received funding (research support or salaries) from Xerion Pharmaceuticals, AG. Authors' contributions KS contributed to study design, data interpretation, carried out the migration experiments with FALI and RNAi and the characterization of CD155 expression, and drafted the manuscript. BE contributed to study design, data interpretation, carried out the invasion screen and morphology experiments, and helped revise the manuscript. JS contributed to the invasion screen. CZ and CU generated and characterized the scFv library. CT performed the IP and mass spec to identify CD155. MS helped with the morphology experiments. JR and DL performed the GBM tissue staining and analysis and provided helpful discussion. LI and DJ contributed to study design, data interpretation, and editing of the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524493.xml |
545045 | Current practices in cancer spatial data analysis: a call for guidance | There has long been a recognition that place matters in health, from recognition of clusters of yellow fever and cholera in the 1800s to modern day analyses of regional and neighborhood effects on cancer patterns. Here we provide a summary of discussions about current practices in the spatial analysis of georeferenced cancer data by a panel of experts recently convened at the National Cancer Institute. | Review Background Recently, the North American Association of Central Cancer Registries (NAACCR) formed a Geographic Information Systems (GIS) Task Force that prepared a handbook to aid cancer registry staff in using GIS for the collection, analysis, and presentation of cancer registry data [ 1 ]. The first chapters of the NAACCR handbook provide extensive information on registry data issues, particularly address geocoding and confidentiality. In June, 2002, the National Cancer Institute sponsored a meeting of selected subject matter experts in Bethesda, MD, to expand the analytic overview in the NAACCR effort to focus specifically on spatial data analysis. Invitees (listed in Table 1 ) include individuals with backgrounds in statistics, epidemiology, and geography so as to balance the points of view expressed. Table 1 Panel members, home institutions, and self-selected focus areas for break-out discussions. The following lists all panel members, their home institutions, and each member's top choices of topics for break-out discussions. All panel members contributed significantly to the general discussion and to initial break-out discussions. A subset of panel members expanded on initial discussions to create the reports listed in Table 2. Name Institution Primary topics of collaboration Luc Anselin University of Illinois, Urbana-Champaign Spatial computing, spatial analysis, and exploratory spatial data analysis B. Sue Bell National Cancer Institute, (currently, Food and Drug Agency) Communicating the results of spatial health analyses, features of spatial data, and disease surveillance Francis Boscoe New York State Department of Health Features of spatial data, exploratory data analysis, and limitations of spatial analysis Barnali Das National Cancer Institute Spatial modeling, exploratory spatial data analysis, and spatial cluster detection. Carol Gotway Centers for Disease Control and Prevention Exploratory spatial data analysis, spatial modeling, and features of spatial data William Henriques Agency for Toxic Substances and Disease Registry Features of spatial data, overview of spatial analysis, and communicating results of spatial health analyses Theodore Holford Yale University Disease surveillance, spatial modeling, and exploratory spatial data analysis Richard Hoskins Washington State Department of Health Communicating the results of spatial health analyses, overview, and spatial computing Geoffrey Jacquez Biomedware Limitation of spatial analyses, spatial cluster detection, and overview of spatial analysis. Martin Kulldorff Harvard Exploratory spatial data analysis, spatial cluster detection, and disease surveillance Andrew Lawson University of South Carolina Overview of spatial analysis, and spatial cluster detection. Linda W. Pickle National Cancer Institute Project coordinator, overview of spatial analysis, communication of spatial health analyses, spatial modeling, and exploratory spatial data analysis Peggy Reynolds Environmental Health Investigations Branch, California State Department of Health Spatial modeling, features of spatial data, and disease surveillance Gerard Rushton University of Iowa Exploratory spatial data analysis, features of spatial data, and spatial modeling Lance Waller Emory University Chair of panel, spatial modeling, spatial cluster detection, and overview of panel discussion Mary Ward Division of Cancer Epidemiology and Genetics, National Cancer Institute Features of spatial data, disease surveillance, and overview of spatial analysis Dan Wartenberg University of Medicine and Dentistry of New Jersey Spatial cluster detection, exploratory spatial data analysis, and communicating the results of spatial health analyses Dale Zimmerman University of Iowa Spatial modeling, spatial cluster detection, and exploratory spatial data analysis The purpose of the meeting was to provide guidance from experts in this field who have experience applying these methods to health data, acknowledging that opinion will change as the field continues to evolve. Consensus of recommendations for any technical field is difficult to achieve, but we have attempted to include contributors with a wide-ranging set of backgrounds and experiences in the hope that what is presented represents, if not clear "best practices", at least sound principles for the analysis of spatial health data. This paper introduces motivating ideas and provides a broad overview of an upcoming series of reports by subgroups of the attendees. A listing of initial reports appears in Table 2 , and additional topic-specific reports are in preparation. Table 2 Titles and authors of initial reports by panel members (drafts available upon request). These reports represent summaries and expansions of initial discussions by the panels. The author team took topics and ideas generated by the panel discussions, conducted literature searches, formalized the presentation structure and composed the report. The final reports represent the collective efforts of each author team, building on selected contributions of panel members. Title Author Team Topics Current practices in cancer spatial data analysis: a call for guidance Linda W. Pickle, Lance Waller, Andrew Lawson Introduction to panel discussion and background issues. Communication: reporting spatial health statistics to policy makers and the general public B. Sue Bell, Richard E. Hoskins, Daniel Wartenberg Review of issues involved in communicating results of spatial analyses of cancer data. Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer Francis P. Boscoe, Mary H. Ward, Peggy Reynolds Review of characteristics and sources of spatially-referenced health data. Current practices in the spatial analysis of cancer: flies in the ointment Geoffrey M. Jacquez Unresolved issues lurking behind most spatial analyses of health data. Motivation Interest in and use of GIS for health data has grown tremendously during the past decade. The recognition of local geographic influences on health date back at least to the development of spot maps of yellow fever and cholera in the earlier-to-mid 1800's [ 2 ]. While what is known today as GIS grew out of developments associated with the Canadian Land Inventory in 1963 [ 3 ], there were no articles on GIS and human health included in the National Institutes of Heath's (NIH) MEDLINE bibliographic database as recently as 1993; between 1994 and 2002 the number of GIS articles grew 26% per year, four times the rate of increase for human health articles in general. Consequently, the NIH library first added "Geographic Information Systems" as a MEDLINE indexing term in 2003. What has fueled this increased attention? Most attribute it to the increasing computing power and availability of appropriate software on everyone's desktop, thus moving GIS and other analytic tools from the hands of the geographers and computer specialists to those of the health researcher. For example, when the National Cancer Institute prepared its first cancer mortality atlas in the early 1970s [ 4 ], the maps had to be prepared on National Oceanographic and Atmospheric Administration computer systems, since they were one of the few government agencies capable of preparing high quality maps. Now anyone with a standard personal computer can prepare such maps on their desktop in just a few minutes. Similarly, complex statistical analyses of georeferenced health data also can run on the desktop. While anyone with access to desktop computing and georeferenced health data can make maps, there is no guarantee that such maps provide meaningful insight to the underlying disease and social processes due to potential epidemiologic, cartographic, and/or statistical issues (e.g., confounding variables, poor choice of visual variables, and/or very small local sample sizes). As a result, the need remains for thoughtful application and appreciation of data, analytic, and interpretive assumptions commonly encountered in the analysis of spatially-referenced health data. In addition to the impact of the computer revolution is the increasing recognition that all health data are spatial, i.e., referenced to place. A recent call for more widespread use of GIS in the U.K. National Health Service points out that GIS could "act as powerful evidence-based practice tools for early problem detection and solving" [ 5 ]. Many health outcomes are related to an individual's "environment" at both the personal and community levels. Personal environmental factors include not only the obvious water, soil, and air content and exposure to hazardous materials, but also lifestyle factors, such as exposure to tobacco smoke (personal and environmental), occupation, transportation choices, hobbies, and characteristics of the home. Community effects, referred to as "neighborhood social context" in the social sciences literature, have been shown to impact health care policy, delivery, utilization and outcomes [ 6 - 10 ]. Even within a specific geographic area, health care often varies among subgroups of residents, leading to the important study of health disparities. As another example, we are just beginning to realize how characteristics of our built environment, such as sidewalks or green space, impact health through relationships to individual's physical activity level [ 11 ]. With the increasing interest in and availability of georeferenced health data comes the need for methods to properly analyze them, taking into account the spatial correlation of outcomes in nearby places. Recognition of spatial influences in statistical inference date back to some of the earliest developments of modern statistical methods leading, for example, to notions of randomized plot designs for agricultural field trials [ 12 ]. Development of theoretical methods for spatially referenced data includes point process models [ 13 , 14 ], spatial prediction [ 15 , 16 ], and spatial lattice models [ 17 - 19 ] in fields such as agriculture, entomology, bacteriology, cosmology, mining, and meteorology. Methods for the analysis of measurements taken at fixed point locations as random processes grew from independent developments by Matheron [ 15 ] and Gandin [ 16 ] for analyzing geologic data. While the areas of spatial statistics, statistical computing, and GIS all developed substantially from the 1960's through today, these developments have been and continue to be largely separate and independent of one another. Application of spatial statistical methods is more common now that both GIS and spatial statistical software packages are widely available. While there are several texts focused on statistical methods for spatial health data [ 20 - 25 ], and health applications of GIS [ 26 - 28 ], there is a growing need for guidance in the combination of the two areas, in particular the selection and proper use of the appropriate statistical techniques for different types of georeferenced health data. Complicating factors We specifically focus on spatial and spatio-temporal statistical methods appropriate for observational human health data, not clinical trials or data from other types of designed experiments. A challenging but common problem with this type of data is the difficulty in obtaining accurate exposure and disease outcome data for the time and place most relevant to that disease. Health consequences are the result of a continuum of multiple and varied exposures which often occur over a long period of time and in various places. How can we capture this complex pattern of exposure over decades and, most important for the topic at hand, to what geographic location do we assign the exposure? A subgroup of meeting attendees discussed the problems of defining "place" and locating appropriate data in detail (see Table 2 ). A forthcoming article in the International Journal of Health Geographics by Boscoe, Ward, and Reynolds will address these issues. Another problem with data on human health is that the data required for analysis are typically scattered across many sources and often collected by different groups and agencies. For example, unless we belong to a closed medical system such as a health maintenance organization or military services, each person's medical records are housed in different medical offices. Such records collected for clinical purposes also rarely include demographic information desirable for the data analysis and only include the patient's home address (primarily for billing or other contact purposes), offering no information on previous residences or workplace location(s). Accumulating and validating data required for analysis from these multiple sources usually takes longer than the analysis itself, where data validation plays an essential but time-consuming and often overlooked role. Of increasing concern in this field is protecting the privacy and confidentiality of the study subjects. While all researchers agree that this is important, it is often difficult to reconcile these needs with data needs for a proper analysis. In particular, spatial data analysis and mapping of results are often hampered by the lack of specific addresses. Data collection agencies and medical facilities are imposing increasingly strict requirements for data release and often only identify a place (usually patient's address) to a broad administrative unit. For example, the recently enacted Health Insurance Portability and Accountability Act (HIPAA) often requires removal of geographic subdivisions smaller than the state, and the National Center for Health Statistics only releases death certificate data aggregated to the county level or for places with large populations. The reportable specificity of location is often not good enough to allow the analysis to answer research questions about the spatial patterns of the disease. Methods are currently being explored that would allow use of specific individual information in the analysis but would mask identifying characteristics in the results reported only at an aggregated level. In addition to such federal reporting restrictions, state and local governments may add additional regulatory requirements. This said, such regulations need not prohibit spatial analysis of health data completely, rather they change the context within which such analyses may occur. For instance, mutually agreeable memoranda of understanding between analysts and agencies holding data often allow analysis of data with individual-level identifiers provided all reports include only aggregate results. Such memoranda also specify when, if ever, detailed maps of locations may be reported. As an example, the National Cancer Institute's Long Island Breast Cancer Study Project provides a protected environment (on site or remotely accessible) within which registered users may analyze (but not remove) sensitive georeferenced health data (for more information, see ). In addition to general concerns regarding the analysis of health data, the spatial data analysis of cancer data poses unique challenges. Most cancers develop over a period of 20 to 30 years and are a result of multiple exposures interacting with the individual's genetic susceptibility. Few Americans live in a single place for decades – migration presents the problem of which residential address to use for a case's location. Because latencies differ by cancer type and most likely by an individual's susceptibility, little guidance is available for this question. The rarity of cancer also causes a sparse data problem for analysis, both for detecting clusters in data with high spatial variability and for communication of results without violating confidentiality. John Snow's illustration of his theorized cause of cholera in London via a map of case residences was possible because of the large number of cases in a small geographic area with a single, precisely located exposure [ 29 ]. The detection of clusters of a rare disease such as cancer requires sophisticated statistical tools that filter out potentially confounding effects of age, spatially-varying population density, and mobility. As pointed out by Waller and Gotway [ 25 ], different statistical methods answer different questions and require care in appropriate application and interpretation. Further discussion of these and other limitations of spatial data analysis are addressed in the accompanying article by Jacquez [ 30 ]. Despite such concerns, important discoveries in cancer research do result from spatial data analysis. Although U.S. mortality data had been published in tabular form for many years, it wasn't until mortality rates were mapped in 1975 that spatial patterns emerged, such as the cluster of high oral cancer rates in southeastern states, later found to be due to smokeless tobacco use [ 4 , 31 ]. Later, a number of clusters of childhood leukemia were identified, for example in Seascale, UK, and Toms River, NJ [ 32 , 33 ]. Although environmental, genetic and viral hypotheses have been proposed, the cause of most of these clusters remains unclear [ 34 ]. These studies illustrate the potential impact of spatial data analysis on medical research. Finally, in order to ultimately improve public health, the results of the complex analyses of georeferenced cancer data must be disseminated to those in a position to take action, such as state epidemiologists and local cancer control specialists. This audience often needs to obtain statistical data quickly for rapid response to health problems and cannot be expected to have the technical expertise to understand the statistical detail underlying the methods. Statisticians must consider this audience and design maps and reports in such a way as to be easily accessible by them. A forthcoming article in the International Journal of Health Geographics by Bell, Hoskins, and Wartenberg (Table 2 ) addresses these issues in further detail Conclusion In closing, participants in the NCI workshop addressed a wide range of topics summarized in Tables 1 and 2 . Initial reports address data issues, communication of results, and current limitations and areas for further development. Further discussions examined and reviewed several technical aspects of analysis relating to public health surveillance, cluster detection and spatial models, and additional reports are in preparation. We hope that public health professionals, geographers, epidemiologists, environmental scientists, and statisticians faced with the analysis of georeferenced health data find these articles to be useful as an introduction to current methods and concerns in the area. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545045.xml |
535549 | Susceptibility of different leukocyte cell types to Vaccinia virus infection | Background Vaccinia virus, the prototype member of the family Poxviridae , was used extensively in the past as the Smallpox vaccine, and is currently considered as a candidate vector for new recombinant vaccines. Vaccinia virus has a wide host range, and is known to infect cultures of a variety of cell lines of mammalian origin. However, little is known about the virus tropism in human leukocyte populations. We report here that various cell types within leukocyte populations have widely different susceptibility to infection with vaccinia virus. Results We have investigated the ability of vaccinia virus to infect human PBLs by using virus recombinants expressing green fluorescent protein (GFP), and monoclonal antibodies specific for PBL subpopulations. Flow cytometry allowed the identification of infected cells within the PBL mixture 1–5 hours after infection. Antibody labeling revealed that different cell populations had very different infection rates. Monocytes showed the highest percentage of infected cells, followed by B lymphocytes and NK cells. In contrast to those cell types, the rate of infection of T lymphocytes was low. Comparison of vaccinia virus strains WR and MVA showed that both strains infected efficiently the monocyte population, although producing different expression levels. Our results suggest that MVA was less efficient than WR in infecting NK cells and B lymphocytes. Overall, both WR and MVA consistently showed a strong preference for the infection of non-T cells. Conclusions When infecting fresh human PBL preparations, vaccinia virus showed a strong bias towards the infection of monocytes, followed by B lymphocytes and NK cells. In contrast, very poor infection of T lymphocytes was detected. These finding may have important implications both in our understanding of poxvirus pathogenesis and in the development of improved smallpox vaccines. | Background Vaccinia virus, the prototype of the Poxviridae , is a large DNA virus whose replication takes place in the cytoplasm of the infected cell [ 1 ]. Although well characterized in vitro , little is known about the ability of vaccinia virus to infect different cell types in vivo . Vaccinia virus host range in cell culture is known to be determined by several genes. The importance of host restriction has been highlighted in recent years by the growing use of the Modified Vaccinia Ankara (MVA) virus strain, whose replication is severely impaired in human cells [ 2 - 4 ]. Genes known to influence the ability of vaccinia virus to infect cells, termed host range genes, have been identified, and shown to block productive infection at different points in the replication cycle. Significantly, MVA replication of non-permissive cells proceeds through early and late gene expression, but is blocked at late times in a step of virion morphogenesis [ 5 ]. In addition to host range genes, there are a number of factors that might influence the infection rate of a given cell type, such as the accessibility and amount of receptors, the ability to internalize the virus, and the metabolic state of the cell. In addition to cellular factors, genetic differences in the virus might influence the efficiency and fate of the infection. For instance, cellular nucleotide pools can be one of the factors that, in conjunction with the expression of viral thymidine kinase (TK), may influence the rate of infection. The above considerations led us to hypothesize that, although receptors for vaccinia seem to be ubiquitous, and virus replication is relatively independent from the host cell, virus tropism in vivo may be determined by many complex factors that may be dependent on the cell type and metabolic state. We have focused here on the differences between two widely used strains of vaccinia virus (Western Reserve-WR and MVA), and also to their respective TK(-) mutants, in their ability to infect different cell types in fresh human PBLs. Results Infection of human PBLs by GFP-expressing vaccinia virus Previously, we have shown that GFP expression from a vaccinia virus recombinant can be used to monitor infection by flow cytometry [ 6 ]. Where adequate marker molecules for different cell populations exist, this approach should facilitate the study of the susceptibility of cell types to vaccinia virus infection. With this aim, fresh human PBLs from healthy donors were infected with virus WR-GFP, and analyzed by flow cytometry at different times post-infection. The overall rate of infection, measured as GFP-positive cells, was 4.5%, 7.6% and 10.0% at 1, 3 and 5 h, respectively. Staining with antibodies to CD3, CD14, CD19 and CD56 was performed on infected cells at 5 h.p.i. (Fig. 1 ). A marked preference was noted for the infection of non-T cells, since GFP positive cells amounted to 19% of non-T lymphocytes, while only 1.9% of T cells were infected. Among the non-T lymphocytes, there was a strong bias towards the infection of CD14 positive cells (monocytes), of which up to 77% showed green fluorescence, followed by B lymphocytes (CD19 + , up to 20%) and NK cells (CD56 + , up to 9%). Figure 1 Analysis of vaccinia infected human PBLs . Human PBLs infected with vaccinia WR-GPF for 5 h were subsequently stained with cell-type specific mAbs, and analyzed by flow cytometry. Plots show the level of GFP fluorescence (recorded in the FL1 channel) versus the amount of labeling with the indicated antibody markers (recorded in the FL2 channel). Numbers inside the plots indicate the percentage of cells within the respective regions. Construction of MVA-GFP, WR-TK(-) and MVA-TK(-) Vaccinia virus MVA and TK-deficient viruses have been proposed as improved recombinant vaccines. In particular, the highly attenuated MVA strain has elicited much interest as a safer vaccine vector. We studied the influence of the virus strain and the TK phenotype in the infection of human PBLs. We thus constructed GFP expressing viruses from vaccinia virus MVA strain, by inserting the GFP cassette downstream of the F13L gene, using an intergenic region for the insertion. Additionally, thymidine kinase-deficient virus recombinants WR-TK(-) and MVA-TK(-) were constructed by inserting the GFP cassette within the viral TK locus. Those viruses grew to high titers and produced, upon infection of cell lines, bright GFP fluorescence (not shown). Infection of human PBLs with MVA-GFP The four GFP-expressing viruses were used to infect fresh human PBLs from a different individual, and subjected to flow cytometry analysis at 7 h.p.i. (Fig. 2 ). The results confirmed the above findings with respect to the low infection rate of T cells in comparison with monocytes, B and NK cells. Both CD4 + and CD8 + cells were poorly infected, although there was indication of an increased infection of low-CD8 T lymphocytes in comparison with high-CD8 cells. Notably, this experiment confirmed that most of the monocytes (CD14+) was infected in our experimental conditions, and showed a high level of GFP fluorescence. It was of interest to directly compare the ability of vaccinia MVA to infect PBLs with that of the standard laboratory strain WR. A side-by-side comparison of WR-GFP and MVA-GFP showed that both viruses infected a high percentage of CD14 + monocytes (83 and 70%, respectively), and a low percentage of T lymphocytes (0.46 and 0.2%, respectively). No significant differences were noted in the percentage of CD4 cells infected with both viruses. Although both virus strains were able to infect the majority of monocytes, MVA-GFP produced a lower level of GFP fluorescence than WR-GFP in the infected monocytes. Those differences could be the result of a lower expression level, or a delay in the course of infection, by the MVA strain. Figure 2 Analysis of cell populations infected with different vaccinia viruses. Human PBLs were infected with vaccinia virus strains WR and MVA, or their respective TK(-) mutants. PBL-subsets were identified by staining with the specific mAbs indicated under each plot. Numbers inside the plots indicate the percentage of GFP-expressing cells within each PBL-subset. In addition to increased GFP expression levels, WR-GFP was also more efficient than MVA-GFP for the infection of CD19 + B lymphocytes (7.1% vs 3.5%) and CD56 + /CD16 + NK cells(7.6% vs 4%). Infection with thymidine kinase-deficient viruses As stated above, we constructed recombinant viruses from both WR and MVA by insertion of GFP into the TK locus. Infection of different populations in human PBLs with these viruses was again monitored in paralell using specific antibodies (Fig. 2 ). Infection of PBLs with WR-TK(-) virus resulted in similar percentages of infected CD14 and CD56/CD16 positive cells, although a slight decrease of infection rates was noted in CD19 cells. The level of GFP fluorescence in CD14-positive cells (monocytes) (and to a lesser extent, in all the WR-TK(-) infected lymphoid subsets) was markedly reduced with respect to the WR-GFP virus. Discussion Detection of cells infected by GFP-expressing vaccinia viruses provide a fast and sensitive method to measure virus infection [ 6 ]. In this report, we have taken advantage of this approach to measure infection in freshly prepared human PBLs. In combination with cell-type specific fluorescent antibodies, we have been able to study the rate of infection in different cell subset within the PBL population. It is to note that the approach used in this work only allows the detection of viral gene expression derived from the infection, but does not address whether the infection results in the production of progeny virus. Early reports indicated that vaccinia virus cause cythopathic effect in human leukocytes, although only replicated in mitogen-stimulated cell populations, indicating that active cell replication is required for virus replication [ 7 , 8 ]. In this respect, it has also been reported that vaccinia infection of dendritic cells and monocytes/macrophages is abortive [ 9 - 11 ], and that dendritic cells and macrophages die by apoptosis upon infection [ 9 , 12 - 14 ]. Less clear is the case of transformed B lymphocyte cell lines, where virus infection has been described to be productive [ 9 ] and abortive [ 15 ] in different cell lines. Our results point to a significant preference of vaccinia virus for certain cell types. In particular, monocytes were the most susceptible cells, followed by B cells and NK cells. In contrast, T cells were infected at very low rates. These observations are in broad agreement with previous studies, where different infection rates have been noted between monocytes and lymphocytes [ 16 ] and between B and T lymphocytes [ 17 ]. In our analysis, we have detected different rates of virus infection of different cells but at this point we cannot relate the differences in infection to differential virus binding, internalization or gene expression in different PBL cell lineages. In any event, the consequences of virus tropism in the pathogenicity of poxviruses remains to be further investigated. Comparison of the patterns obtained with the two virus strains and their TK(-) mutants indicate that both the virus strain and the TK phenotype may determine the amount of gene expression, as was revealed by the intensity of GFP fluorescence in infected monocytes. In addition, the ability of the virus to infect certain cell types (CD19) seems to be affected to a certain extent by disruption of the TK gene. While this may be derived from our inability to detect those infected cells because of decreased gene expression, we cannot rule out a more direct requirement of TK activity in those cells. MVA vaccinia virus strain has elicited much interest recently because of its safety record. Because clinical complications and side effects of smallpox vaccination are a critical issue in the event of mass vaccination, understanding the basis of MVA attenuation may lead to the development of better vaccine vectors. In this study, a number of differences were noted between the rates of infection obtained with WR and MVA virus strains. While both viruses were able to infect the monocyte population, WR infected B cells and the NK population (CD56, CD16 positive cells) more efficiently than MVA. Whether these observations have implications on the pathogenicity or immunogenicity of MVA will require further studies. The fact that both WR and MVA showed a strong preference for certain cell populations indicate that, in addition to host range genes, there are other factors that might influence the infection rate of PBL cells. Those might include a variety of such as the accessibility and amount of receptors, ability to internalize the virus, and the metabolic state of the cell. Conclusions Monocytes (CD14+ cells) were the cells in the PBL population that showed a greater susceptibility to vaccinia virus infection, as measured by viral gene expression. On the other hand, T lymphocytes (CD3+ cells) were infected with low efficiency. An intermediate susceptibility was detected in B lymphocytes (CD19+ cells) and NK (CD56+ cells). Both the use of a highly attenuated virus strain (MVA) or the disruption of the thymidine kinase gene lead to decreased gene expression in the infected cells. Those observations highlight the existence of a different degree of susceptibility to infection if PBL subpopulations, a fact that may have important implications in understanding virus pathogenicity and immunogenicity. Methods Cells, plasmids and virus Vaccinia virus strain WR was grown and titrated in BSC-1 or CV-1 cells, grown in minimal essential medium (EMEM) supplemented with 5% fetal bovine serum (FBS) and 2 mM L-Glutamine. MVA virus and recombinants were grown in BHK-21 cells (ATCC CCL10) cultured in BHK medium containing 5% FBS, 3 g/ml tryptose phosphate broth and 0.01 M hepes. All cells were maintained in a 5% CO 2 atmosphere at 37°C. Plasmid pRB21 [ 18 ] contains vaccinia virus gene F13L and flanking sequences, and a synthetic early/late promoter placed downstream of the P37 coding sequence. Construction of recombinant viruses expressing GFP Plasmid pRBrsGFP, designed to mediate the insertion of the gene coding an enhanced version of the green fluorescent protein gene, rsGFP, (Quantum Biotechnologies, Inc.) was constructed as follows. rsGFP gene in plasmid pQBI25 was amplified using oligonucleotides GFP 5' (AATATAAATG GCTAGC AAAGGAGAAGAA) and GFPH3 (TTTA AAGCTT TACTAGTGGATCCTCAG), that include NheI and HindIII restriction sites, respectively. After digestion with NheI and HindIII , the gene was inserted into the corresponding sites in plasmid pRB21 [ 18 ], downstream of a synthetic vaccinia early/late promoter. Plasmid prsGTK, containing the above GFP expression cassette located between recombination flanks for the TK locus, was obtained by cloning the rsGFP cassette from plasmid pRBrsGFP in plasmid pGPTK (Sanchez-Puig and Blasco, unpublished) after digestion with XhoI and BamHI . Viruses WR-GFP and MVA-GFP were obtained by transfection of plasmid pRBrsGFP in cells infected with WR mutant vRB12 [ 19 ] or MVA, respectively. After plaquing of the progeny virus, GFP-positive virus plaques were identified by inspection in a Nikon TE-300 inverted fluorescence microscope, plaque-purified three times and amplified. Recombinant virus VVrsGFPTK, was isolated after transfection of plasmid prsGTK in cells infected with virus WR. Recombinant virus plaques were isolated by plaquing on 143B TK(-) cells in the presence of 25 μg/ml bromodoxyuridine. GFP positive plaques were identified under the microscope, and plaque-purified three times before amplification. Recombinant virus MVA-GFPTK was isolated by transfection of plasmid prsGTK in MVA-infected BHK-21 cells. GFP-positive virus were identified under the microscope, isolated by three consecutive rounds of plaque purification in BHK-21 cells and amplified in BHK-21 cell cultures. Finally, virus recombinants were analyzed by Southern Blot, using digoxigenin-labelled GFP gene sequence as the probe. The analysis demonstrated that the recombinants contained the GFP expression cassette in the desired genome position and that they were stable, double recombinants. Isolation of human PBLs Peripheral blood mononuclear cells from healthy subjects were obtained by density gradient centrifugation of heparinized blood on Ficoll-Paque (Pharmacia, Uppsala, Sweden). Cells obtained from the interface were washed three times in saline solution and then resuspended in complete medium (CM) consisting of RPMI 1640 (Gibco, Life Technologies, Germany) supplemented with 10% FBS (Gibco), 2 mM L-glutamine (ICN, USA), 100 U/ml each of penicillin and streptomycin (Laboratorios Normon, Spain). Viability of the isolated cells always exceeded 95% as determined by trypan blue exclusion. Infection of human PBLs was performed as follows: 2 × 10 5 PBLs were infected with virus recombinants VV-rsGFP, VVrsGFPTK, MVA-GFP, and MVA-GFPTK, at 10 p.f.u./cell, in 0.7 ml of RPMI medium containing 2% FBS. After 1 h adsorption, cells were pelleted and resuspended in 2 ml of fresh RPMI medium containing 2% FBS. At different infection times, the cells were sedimented by low-speed centrifugation, resuspended in 100 μl FACS-FLOW, and labeled with the appropriate conjugated monoclonal antibodies (mAb) for flow cytometric analysis (FCM) (phycoerythrin, PE- peridinil chlorophyll protein, PerCP- and allophycocianin, APC-conjugated mAb directed against CD3, CD4, CD8, CD14 and CD16 were obtained from BD; mAb against CD19 and CD56 from Beckman Coulter). Cells were incubated with the antibodies for 30 min at 4°C in the dark, washed twice with saline solution and finally resuspended in 200 μl Cytofix/Cytoperm (BD Pharmingen). Cells were analyzed in a FACSCalibur (BD Biosciences, San Diego, CA) and data were processed with Cell Quest software (BD). Competing interests The author(s) declare that they have no competing interests. Authors' contributions JMS carried out the isolation of virus recombinants and performed viral infections and participated in the drafting of the manuscript. LS and GR performed the preparation of PBLs, carried out the flow cytometry and elaborated the data. GR participated in the interpretation of the data and helped in the elaboration of the manuscript. RB conceived the study, designed the virus recombinant constructs, supervised the experimental work and drafted the manuscript. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535549.xml |
449864 | Calling the Steps in Development's Genetic Square Dance | null | A single, fertilized egg divides into apparently identical daughter cells. As these twins divide again and again, differences emerge among their progeny, establishing segments that will distinguish back from front and head from tail in the growing embryo. Development of segments—and, later, distinct tissues—requires a carefully coordinated square dance of gene expression machinery. Proteins coded by special genes called transcription factors call out the steps by binding to DNA to block or encourage expression of specific genes. With to-the-minute timing, transcription factors call other genes into action to produce the proteins that will determine cell fate. Developing organisms express different transcription factors at specific times and locations to coordinate the changes that make some cells head, others tail; one, a neuron, another, muscle. Polytene chromosomes (blue) stained for Hairy (green) and Groucho (red) binding A transcription factor called Hairy is one of the first activated during segment development in the fruitfly Drosophila melanogaster . Misregulation of Hairy and related factors is associated with cancer and developmental defects across species. Mutations in the gene that codes Hairy lead to overexpression of genes involved in development, but it is not clear whether Hairy normally represses those genes directly, or through intermediaries. To find the answer, Susan Parkhurst and colleagues at the Fred Hutchinson Cancer Research Center in Seattle, Washington, set out to identify Hairy's direct targets. The researchers found a total of 59 genes bound directly by the Hairy protein in cultured Drosophila cells called Kc cells and in embryos collected at the peak of Hairy expression during Drosophila segmentation. Because they searched approximately half of the expected Drosophila genome, the researchers estimate that they identified roughly half of all Hairy target genes. The list included genes known to act during segmentation, as expected, as well as many others with roles in cell division, growth, and shape. Of the 59 Hairy targets identified, only one appeared in both Kc cells and embryos. The lack of overlap may reflect a difference in developmental stage between the Kc cells, which are thought to be precursors to neurons, and the relatively undifferentiated embryos, and suggests that Hairy's role changes with context, such as the stage of development or tissue type. But Hairy doesn't act alone. Like most transcription factors, Hairy requires assistant proteins, called cofactors, to do its job. The availability of Hairy's known cofactors—Groucho, Drosophila C-terminal binding protein (dCtBP), and Drosophila Sir2 (dSir2)—may help to set the tempo and timing of Hairy's repression of genes. Groucho was thought to be Hairy's main assistant, but Parkhurst and colleagues found that only one of the identified Hairy target genes bound Groucho in Kc cells. The majority of Hairy targets overlapped with those of dCtBP, most often in combination with dSir2. All of the cofactors also bound to non-Hairy targets, suggesting that they assist other transcription factors as well. Next, Parkhurst's lab plans to explore the biological functions of the 59 Hairy target genes, to see how they help Hairy coordinate development. Meanwhile, the list of known Drosophila genes has grown 2-fold to include almost all of the expected genome. Repetition of these experiments with the expanded gene set could identify most or all of Hairy's target genes. The current results suggest that Hairy plays roles in segmentation, cell division, and tissue formation that evolve as an organism develops. Differences in cofactor involvement could help regulate Hairy's repression of genes. This paper demonstrates a powerful technique to explore how developing embryos keep gene expression in step. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC449864.xml |
387822 | Predicting Cancer Patient Survival with Gene Expression Data | null | Cancer specialists often talk about cancer as an umbrella term for over 200 different diseases, each having unique characteristics. But even these categories are too broad, as the same type of cancer can take very different paths in different people. It's not uncommon, for example, for a tumor to grow aggressively in one patient and stabilize or regress in another, even though their tumors are indistinguishable and are treated in the same way. Researchers have traditionally diagnosed and treated cancer based on microscopic analysis of cell size and shape, a method that's especially difficult for very closely related cancers, such as non-Hodgkin's lymphoma, which has 20 subtypes. As scientists learn more about the molecular alterations in cancer, they're beginning to establish cancer subtypes based on the underlying molecular footprint of a tumor. Four years ago, DNA microarray analysis revealed that the most common subtype of non-Hodgkin's lymphoma is in fact two separate diseases. Though the tumor cells of both cancers appear large and diffusely dispersed in a tissue sample under a microscope, each has a distinct genetic profile, possibly explaining why only 40% of patients with this subtype respond to the standard chemotherapy treatment. Selecting expression profiles that can predict cancer outcome Such molecular pathology has led to the discovery of subtypes of several different tumor types and has successfully identified patients with different survival times. But such correlations work best when cancer subtypes based on genetic profiles are already known. If you know that different subtypes exist and which patients belong to which subtype, then you can build a statistical model to diagnose such cancers in future patients. But in most situations, clinicians don't know either of these variables—or even whether such a subtype exists—information that is crucial to developing effective diagnostic and treatment protocols. Statistical methods to identify such subtypes exist, but they can generate classifications that lack clinical relevance. Now Eric Bair and Robert Tibshirani describe a procedure that combines both gene expression data and the patients' clinical history to identify biologically significant cancer subtypes and show that this method is a powerful predictor of patient survival. Their approach uses clinical data to identify a list of genes that correspond to a particular clinical factor—such as survival time, tumor stage, or metastasis—in tandem with statistical analysis to look for additional patterns in the data to identify clinically relevant subsets of genes. In many retrospective studies, patient survival time is known, even though tumor subtypes are not; Bair and Tibshirani used that survival data to guide their analysis of the microarray data. They calculated the correlation of each gene in the microarray data with patient survival to generate a list of “significant” genes and then used these genes to identify tumor subtypes. Creating a list of candidate genes based on clinical data, the authors explain, reduces the chances of including genes unrelated to survival, increasing the probability of identifying gene clusters with clinical and thus predictive significance. Such “indicator gene lists” could identify subgroups of patients with similar gene expression profiles. The lists of subgroups, based on gene expression profiles and clinical outcomes of previous patients, could be used to assign future patients to the appropriate subgroup. An important goal of microarray research is to identify genetic profiles that can predict the risk of tumor metastasis. Being able to distinguish the subtle differences in cancer subtype will help doctors assess a patient's risk profile and to prescribe a course of treatment tailored to that profile. A patient with a particularly aggressive tumor, for example, would be a candidate for aggressive treatment, while a patient whose cancer seems unlikely to metastasize could be spared the debilitating side effects of aggressive anticancer therapies. By providing a method to cull the thousands of genes generated by a microarray to those most likely to have clinical relevance, Bair and Tibshirani have created a powerful tool to identify new cancer subtypes, predict expected patient survival, and, in some cases, help suggest the most appropriate course of treatment. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC387822.xml |
514550 | Genome-wide array comparative genomic hybridization analysis reveals distinct amplifications in osteosarcoma | Background Osteosarcoma is a highly malignant bone neoplasm of children and young adults. It is characterized by extremely complex karyotypes and high frequency of chromosomal amplifications. Currently, only the histological response (degree of necrosis) to therapy represent gold standard for predicting the outcome in a patient with non-metastatic osteosarcoma at the time of definitive surgery. Patients with lower degree of necrosis have a higher risk of relapse and poor outcome even after chemotherapy and complete resection of the primary tumor. Therefore, a better understanding of the underlying molecular genetic events leading to tumor initiation and progression could result in the identification of potential diagnostic and therapeutic targets. Methods We used a genome-wide screening method – array based comparative genomic hybridization (array-CGH) to identify DNA copy number changes in 48 patients with osteosarcoma. We applied fluorescence in situ hybridization (FISH) to validate some of amplified clones in this study. Results Clones showing gains (79%) were more frequent than losses (66%). High-level amplifications and homozygous deletions constitute 28.6% and 3.8% of tumor genome respectively. High-level amplifications were present in 238 clones, of which about 37% of them showed recurrent amplification. Most frequently amplified clones were mapped to 1p36.32 ( PRDM16 ), 6p21.1 ( CDC5L , HSPCB , NFKBIE) , 8q24, 12q14.3 ( IFNG ), 16p13 ( MGRN1 ), and 17p11.2 ( PMP22 MYCD, SOX1 , ELAC27 ). We validated some of the amplified clones by FISH from 6p12-p21, 8q23-q24, and 17p11.2 amplicons. Homozygous deletions were noted for 32 clones and only 7 clones showed in more than one case. These 7 clones were mapped to 1q25.1 (4 cases), 3p14.1 (4 cases), 13q12.2 (2 cases), 4p15.1 (2 cases), 6q12 (2 cases), 6q12 (2 cases) and 6q16.3 (2 cases). Conclusions This study clearly demonstrates the utility of array CGH in defining high-resolution DNA copy number changes and refining amplifications. The resolution of array CGH technology combined with human genome database suggested the possible target genes present in the gained or lost clones. | Background Osteosarcoma (OS) is a primary malignant tumor of bone arising from primitive bone-forming mesenchymal cells and it accounts for approximately 60% of malignant bone tumors in the first two decades of life [ 1 ]. These tumors typically arise in the metaphyseal regions of long bones, with the distal femur, proximal tibia and proximal humerus. A significant number of osteosarcomas are of conventional type which can be subdivided into three major categories based on their predominant differentiation of tumor cells: osteoblastic, chondroblastic, and fibroblastic. Currently, only the histological response (degree of necrosis) to therapy represent gold standard for predicting the outcome in a patient with non-metastatic osteosarcoma at the time of definitive surgery [ 2 ]. Patients with lower degree of necrosis have a higher risk of relapse and poor outcome even after chemotherapy and complete resection of the primary tumor. Therefore, a better understanding of the underlying molecular genetic events leading to tumor initiation and progression could result in the identification of potential diagnostic and therapeutic targets. Chromosomal aberrations in osteosarcoma are highly complex and characterized by high frequency of amplifications. These amplifications may result in the overexpression of genes and contribute to the genomic instability in osteosarcoma. The identification of genes within the amplified sites is crucial for understanding the biology and clinical behavior of osteosarcoma. Until, recently gene amplification has been detected by PCR, southern blot analysis or FISH-based approach using gene specific probes. These techniques are inherently restricted to the previously known amplified genes in the genome. In contrast, genome-wide screening of amplified chromosomal regions with CGH has become an important tool for the detection of amplified regions in the tumor genome. So far published chromosomal CGH studies in osteosarcoma have identified several high-level chromosomal amplifications at 1p22, 1p31, 1q21, 1q23, 2q24, 3p25, 3q26, 6q24.3, 4q12, 5p14-p15, 5q33, 6p12-p21, 6q24.3, 7p21-p22, 8q12-q23, 10p21, 10q11.1, 10q22, 11q13, 11q23, 12p13, 12q12-q15, 17p11.2, 17q21, 18q22, 19p13.1 and 20p11.2 [ 3 - 7 ]. However, conventional CGH has limited sensitivity and resolution (~10–15 megabases) because of its dependence on the morphology of metaphase chromosomes. In addition, extensive follow-up work is required to identify candidate genes after regions of gain or loss have been identified. Recently, novel method termed as array-based comparative genomic hybridization (array CGH) has been described, which enables high throughput quantitative measurement of high-resolution DNA copy number changes throughout the genome [ 8 ]. This method is based on hybridization of differentially labeled test and reference DNAs to an array of mapped human genomic DNA fragments (~100–200 kb) and has been recently applied to human and mouse tumors [ 9 - 14 ]. To identify high-resolution copy number, we used array CGH to the panel of 48 tumors. The resolution of array CGH technology combined with human genome database not only allowed a precise identification of amplicons but also suggested the possible target genes within the amplicons. Methods Patient samples A total of 48 tumors from 42 patients (20 males and 22 females) were collected from the Texas Children's Cancer Center, Houston, TX (tumors 193, 196, 204, 209, 221, 226, 248, 274, 295, 311, 326, 341, 345, 360, 400, 464, 481, 501, 527, 591 and 606) and Memorial Sloan Kettering Cancer Center, New York (tumors 06, 15, 24, 25, 27, 29, 32, 34, 40, 48, 68, 76, 78, 79, 80, 82, 83, 85, 88, 95, 98, 99, 102, 123, 423, 425, and 474). All tissues in this study were obtained after IRB approved informed consents were signed. The age at diagnosis ranged from 5 years to 71 years at diagnosis. The histological information of 42 patients is presented in Table 1 . Array CGH The array used in this study consists of 967 human BACs, which were spaced approximately 3 megabase across the whole genome. These arrays were obtained from Spectral Genomics, Houston, TX. The experiments were performed according to the manufacturer's protocol. Arrays were pre-hybridized with human Cot-I DNA (GIBCO Invitrogen, Carlsbad, CA) and salmon testes DNA to block the repetitive sequences on BACs. One microgram of normal DNA (reference) and tumor DNA (test) was labeled with cy5-dUTP and cy3-dUTP respectively, by random priming. To avoid dye bias, we performed dye swap experiments for each sample. The probe mixture is dissolved in hybridization mixture, denatured, cooled, and mounted with 22 × 60 mm coverslip. Hybridizations were performed in sealed chambers for 16–20 hours at 60°C. After post hybridization washes, arrays were rinsed, dried with compressed air, and scanned into two 16-bit TIFF image files using Gene Pix 4000A two-color fluorescent scanner (Axon Instruments, Inc., Union City, CA) and quantitated using GenePix software (Axon Instruments, Union City, CA). Data processing and analysis After scanning of the slide, the fluorescent intensities of the green and red channels were background subtracted. The resulting values were normalized by intensity based local weighted regression method (Lowess) to correct for systematic bias in dye labeling and fluorescent intensity [ 15 ]. Then the ratio of the red/green channel of each clone was calculated and log base 2 transformed (log ratios). Each experiment was repeated once with dye reversal to addressing the confounding effect of the dye and experiment. The average of the dye-reversal experiment pair was calculated by reversing the sign of one experiment so that the log ratio reflects the tumor versus normal ratio. We developed a new analytical method called invariant analysis to define the significant copy number changes. This method is designed to: i) increase the power of the analysis by combining all the cases in our dataset to define an invariant population (unchanged population); and, ii) to address the signal to noise differences among individual cases due to sample and hybridization variability. Our goal is to define a set of unchanged clones that can be used to calculate the upper and lower bound thresholds of the log ratios for the unchanged population in each experiment. First, we calculated the variance of each clone from all the experiments. We computed the p-values of the each clone by comparing to the clone with median variance using chi-square distribution . The clones that have p-value greater than preset cutoff 0.9 were considered as invariant clone set, i.e. clones that do not vary significantly in all experiments. Then the mean and standard deviation of the log ratios of these invariant clones in each experiment were calculated. The clones with log ratios that exceed mean +/- 2 × SD of the invariant set were considered gains and losses, respectively. For amplification and homozygous deletions, clones were defined to have at least 2 fold of the upper bound threshold and 4-fold of lower bound threshold, respectively. The gene(s) present in the clones were identified using UCSC browser by downloading gene table (refFlat) from human gene assembly, July 2003. We search the candidate genes based on linear mapping position, which include 100 kb up and downstream from the clone center position. The supplemental data for this article is available at: Statistical analysis Significant clones in 6p, 8q, 12q and 17p amplicons were calculated using 2-sample t-test with randomized variance model . The experiments in each of the two groups, amplification and normal, used for comparison were defined based on the invariant analysis (see above). The clones that have p <0.001 were considered as significant. We chose a stringent cutoff to minimize the multiple testing problem. FISH FISH was performed to validate and quantify chromosomal amplicons using clones from 6p12-p21 (RP11-91E11, AL391415, RP11-81F7, RP11-79I2, RP11-90H17 and RP11-79F13), 8q24.3 (RP11-89K10), and 17p11.2-p12 (RP11-64B12, RP11-89K6 and RP11-189D22 on tumors metaphase/interphase cells from cases 274, 364, 425, 426, 527 and 628. We confirmed the map positions of all clones on normal human metaphase cells by FISH. The bacterial artificial chromosome (BAC) clones, and centromeric clone from 6 (pEDZ6) were labeled with Spectrum Red or Spectrum Green (Vysis, Downers Grove, IL) by nick translation. Hybridization and FISH analysis was performed as described previously [ 16 ]. Results To define the gains and losses in our experiments, we used invariant analysis for the first time to describe genomic changes by array CGH. In this method, we defined an invariant clone set that has low variance of log ratios among all the array experiments. After the mean and standard deviation of the log ratios in the invariant set of each experiment were calculated, clones that have higher or lower log ratios than the mean +/- 2SD of the invariant set (upper bound and lower bound) were used to define gains and losses. We chose to use this method because it addresses some of the shortcomings of the modeling method, such as using all information provided in a set of experiment to determine the unchanged population instead of using one experiment at a time. However, the variation of each experiment is accounted for because the thresholds are calculated using the invariant set from each experiment. It also does not require a separate reference set for comparison. Finally, it provides an adjustable cutoff to optimize the thresholds to the training data, if provided. The amplified and homozygously deleted clones were defined to have at least 2 fold of the upper bound and 4-fold of lower bound, respectively. Figure 1 summarizes the high-resolution DNA copy number changes identified by array CGH in 48 osteosarcomas derived from 42 patients. Copy number changes were detected involving small genomic regions, whole chromosomes, and chromosomal arms showing homozygous deletions and high-level amplifications. Overview of genomic profiles Copy number changes excluding clones from sex chromosomes were involved in a significant fraction of most tumor genome. The estimated average genomic distance between clones was ~3–4 Mb. The frequency of clones showing gains (79%) was greater than losses (66%). High-level amplifications and homozygous deletions constitute 28.6% and 3.8% of tumor genome respectively. The most frequently deleted clones were identified from the chromosomal regions 2q31.1, 3p14.1, 4p16.2, 6q12, 6q21, 6q27, 7q35, 10p15.1, 10q22-q23, 10q25-q26, 11q25, 13q12.2, 13q14.3, 13q22.1, 17p13.3 and 17q12 (Table 2 ). Most frequently gained clones were mapped to chromosome 1p36, 4p16, 6p12-p21, 8q21, 8q23-q24, 12q14.3, 16p13.3, 16q24.3, 17p11-p12, 19p13.3 and 21q22.3 (Table 3 ). We explored the possible statistical relationship between copy number alterations and histological and clinical parameters. We found no significant relationship between copy number changes and primary/metastatic disease, or histological type or histological response. This may be due to the involvement of large number of genomic loci and insufficient sample size. Homozygous deletions were noted for 32 clones (3.8%). Recurrent homozygous deletions were noted for 7 clones that are were mapped to 1q25.1 (4 cases), 3p14.1 (4 cases), 13q12.2 (2 cases), 4p15.1 (2 cases), 6q12 (2 cases), 6q12 (2 cases) and 6q16.3 (2 cases). Figure 2A is showing a homozygous deletion at 3p14.1 in tumor 06. Loss of 6q12 region was noted in 35% of the osteosarcomas. This region was covered with four clones spanning ~4.2 Mb. Two tumors (tumor 27 and 345) showed low intensity ratios indicting homozygous deletions in this region, one tumor (tumor 345) showed all 4 deleted clones spanning ~4.2 Mb with RP1-129L7 having the lowest ratio intensity decrease. In another case (tumor 27), two clones (RP1-46B1 and RP1-129L7) showed decreased intensity ratios indicating homozygous deletions. Both these clones spanning approximately 2.6 Mb of 6q12 region. Amplification is a frequent phenomenon in osteosarcoma Previous studies using CGH have identified several chromosomal amplification sites in osteosarcoma. Because of the limitation of the method, it fails to pinpoint the precise site of amplicon. However, the present study by array CGH has identified 238 clones (28.6%) with high-level amplifications. Recurrent amplifications were noted in ~37% of the total amplified clones (Figure 3 ). These amplified clones were mapped to 1p22, 1p31.1 ( ROR1 ), 1p36.1 ( PRDM16 ), 1q21, 1q23 ( TNFF6 ), 2q24, 3p25, 3q26.1, 4p16.3, 5p14, 5q33, 6p11.2-p21, 7p21, 8q12.1, 8q24.13, 10p21, 10q11.1, 10q22 ( KCNMA1 ), 11q13, 11q23 ( GRIK4 ), 12q12, 12q13-q15, 12q21-q21.33, 17p11.2-p12, 17q21 ( NGFR ), 18q22, and 19p13.1 ( NFAT). Of these amplified sites, 6p11.2-p21, 8q12.1, 8q24.13, 12q12, 12q13-q15, 12q21-q21.33, 16p13 and 17p11.2-p12 were frequent. Gain of clones from 6p12-p21 regions was noted in 33/48 (~65%) cases analyzed. High-level amplification of the clones from same region was noted in 25% of the cases by array CGH. We found that most of the cases with amplification of 6p12-p21 displayed either increased or slightly varying degree of copy number increase across the 6p12-p21 region. The combined log ratios from all the cases defined the boundaries of amplification between RP3-329A5 and RP11-79F13. The amplicon spans approximately 9.4 Mb with amplification peak for clone RP11-81F7. Further, we used FISH to validate 6p amplicon on tumor metaphase and interphase cells from cases 274, 364, 426 and 527. Increased copy numbers for clones RP11-91E11, AL391415, RP11-81F7, RP11-79I2, RP11-90H17 and RP11-79F13 were noted in interphase cells with maximum copy number increase for clone RP11-81F7 (Figure 4A ). This was consistent with amplification peak for clone RP11-81F7 in the tumors profiled by array CGH (Figure 2B ). In addition, we used 2-sample t-test with randomized variance model to define significant clones from 6p12-p21 amplicon. By this method, we identified RP11-79F13 (p = 0.00000007), RP11-79I2 (p = 0.00000007) and RP11-81F7 (p = 0.00000007) as statistically significant clones. Most cases with 8q gain, displayed varying degree of copy number increase predominantly from 8q12.1 (16.9%), 8q21.13 (29%), and 8q24.3 (35%). High-level amplifications were also noted from 8q12.1 (RP11-550I15 – 6.3%; Figure 2C ), 8q21.13 (RP11-89H1 – 6.3%), 8q24.3 (RP11-89K10 – 6.3%) and RP11-637F16 (12.5%). FISH using clone RP11-89K10 (p = 0.00049) on interphase cells from case 527 confirmed the amplification (10–12 copies) (Figure 4B ). Amplification of 12q was noted in 14/51 (~27%) tumors analyzed by array CGH. Three distinct amplicons – AMP1 (12q12), AMP2 (12q14.1) and AMP3 (12q21.33) were noted across the entire long arm of chromosome 12 (Figure 2D ). Of these 14 cases, four of them (80, 123, 248, 341) displayed all three amplicons. The AMP1 was noted in 10 cases covering 1.8 Mb region between RP11-91K15 and RP11-90I21 with peak amplification for clone RP11-91K15 (p = 0.00000004). Another amplicon (AMP2) was noted 24.48 Mb distal to AMP1 between RP11-91K23 and RP11-89P15. The AMP3, which was 23.3 Mb distal to AMP2 containing RP11-89F6. Amplification of 17p11.2 was noted in 27% of the cases analyzed by array CGH. The amplicon was composed of three clones RP11-64B12 (p = 0.0000014), RP11-89K6 (p = 0.00000005) and RP11-189D22 (p = 0.0000001) and covering 3.7 Mb region on the short arm of chromosome 17 (Figure 2E ). We used these three clones as FISH probes to validate 17p amplicon in tumors 274, 364, 425 and 628 on interphase/ metaphase cells. The distribution of copy number for this amplicon in all the cases ranged from 4–14 copies with peak amplification for clone RP11-189D22 (10–14 copies), followed by and RP11-89K6 (8–10 copies) RP11-64B12 (6–8 copies) (Figure 4C ). Discussion This study represents the first application of genome-wide copy number changes by array CGH in osteosarcoma. Recent studies in breast, renal and bladder cancer showed the potential assessment of this technology in detecting high-resolution copy number changes [ 9 , 11 , 14 ]. This approach will augment the identification of cancer causing genes by relating the clone information directly with sequence information from human genome database. In this study, we used array CGH to screen for high-resolution DNA copy number changes and precise identification of amplifications in a panel of 48 osteosarcomas. Gene amplification is an important genetic mechanism in human cancers, as it clearly associated with tumor progression and has a prognostic significance and has even provided a target for therapeutics [ 17 , 18 ]. These amplifications are often seen at the cytogenetic level as homozygously staining regions (hsrs) or double minute chromosomes (dms). However, cytogenetic recognition of amplifications doesn't contribute to the mapping and identification of amplified DNA sequences. The advent of CGH points an ever-increasing number of chromosomal amplifications in various tumors. These amplifications contribute to the genomic instability in tumors. We have recently shown that the mutation of p53 significantly correlates with genome-wide DNA instability and seems to represent a major genetic factor contributing to the extremely high levels of genomic instability found in high-grade osteosarcomas [ 19 ]. Our analysis have identified frequently amplified clones from 6p11.2-p21, 8q12.1, 8q24.13, 12q12, 12q13-q15, 12q21-q21.33, 16p13 and 17p11.2-p12. Amplification of clones from 6p12-p21 region was noted in 25% of the cases analyzed. This was consistent with the previously published results by CGH. By array CGH, we refined the 6p amplicon to 9.4 Mb with amplification peak for clone RP11-81F7. We recently demonstrated the origin of 6p amplicon as consequence of tandem duplication of clones RP11-81F7 and RP11-79F13 [ 7 ]. Based on combined array CGH and FISH analysis suggest CDC5L , HSPCB , and NFKBIE , and HGNC and MRPL14 are the target genes from 6p12-p21 amplicon. Of these genes, CDC5L may be an important gene in cancer because of its role as a positive cell cycle regulator for G2/M transition[ 20 ]. Consistent with our analysis, overexpression of HSPCB was shown recently by cDNA microarray studies on osteosarcoma [ 21 ]. This protein was shown to play an important role in assemble/disassembly of tubulin by inhibiting tubulin polymerization. High-level amplifications were also noted from 8q12.1 (RP11-550I15 – 6.3%), 8q21.13 (RP11-89H1 – 6.3%), 8q24.3 (RP11-89K10 – 6.3%) and RP11-637F16 (12.5%). There were no candidate genes present in clones RP11-550I15, RP11-89H1 and RP11-637F16, but clone RP11-89K10 contained NSE2 (breast cancer membrane protein 101 kDa) gene. High-level amplification of clones on 12q revealed three distinct sites of amplifications – AMP1 (12q12), AMP2 (12q14.1) and AMP3 (12q21.33). Pervious studies have shown the amplification GLI, CHOP, SAS, HMGI-C, CDK4 , HDM2, and PRIM1 from 12q13-q15 region in osteosarcoma [ 22 , 23 ]. The present array CGH analysis identified a possible target gene IFNG from AMP2 (RP11-298M11; p = 0.0000001), which is physically mapped close to the HDM2 oncogene locus[ 24 ]. Previous studies demonstrated that T-cell production of IFNG strongly suppresses osteoclastogenesis by interfering with the RANKL-RANK signaling pathway. IFNG induces rapid degradation of the RANK adaptor protein, TRAF6, resulting in strong inhibition of the RANKL-induced activation of the transcription factor NFKB and JNK [ 25 ]. The AMP3, which was 23.3 Mb distal to AMP2 containing RP11-89F6. Our analysis from AMP3 revealed two interesting candidate genes: transcription factor ELK3 and PCTAIRE protein kinase 2 ( PCTK2 ). ELK3 is a member of the ETS-domain transcription factor family and the protein is activated by signal-induced phosphorylation [ 26 ]. The protein encoded by PCTK2 belongs to the cdc2/cdkx subfamily of the ser/thr family of protein kinases and play an important role in the regulation of the mammalian cell cycle [ 27 ]. High-level amplification of three clones from 12p13 was noted in case 27 and the amplicon span 4.6 Mb with peak amplification for clone RP11-89D16. No candidate genes contained with in this BAC. Amplification 12p has been reported previously in 9/19 high-grade osteosarcomas by CGH. Recent FISH analysis has identified the amplification of CCND2, ETV6 , and KRAS2 from 12p region [ 28 ]. Amplification of 17p11.2 was noted in 27% of the cases analyzed by array CGH. Our array CGH analysis has identified three clones with high-level amplifications that spans ~3.7 Mb region on 17p11.2. Several candidate genes were identified within these clones (T PP3A, SMCR5, DRG2, FL11 , MYCD, SOX 17, ELAC2 , and PMP22 ). Recent studies have shown the amplification of some of the genes identified in the present study ( PMP22, and TOP3A ) from 17p11.2-p12 in high-grade OS by semi-quantitative PCR and cDNA microarrays [ 29 , 30 ]. The present array CGH analysis has identified seven recurrent clones exhibiting homozygous deletions from 1q25.1, 3p14.1, 13q12.2, 4p15.1, 6q12, 6q12 and 6q16.3. These chromosomal regions were consistent with previously reported studies by loss of heterozygosity (LOH) and CGH [ 3 - 7 , 31 ]. The clone, RP11-90M15 (13q12.2) contain possible candidate gene MTMR6 , a protein-tyrosine phosphatase gene and shown to be present within a cloned region that encompasses a translocation breakpoint t(8;13) in an atypical myoproliferative disorder [ 32 ]. Homozygous deletions of two clones spanning approximately 2.6 Mb of 6q12 region containing candidate genes – nuclear fragile X mental retardation protein interacting protein 1 pseudogene ( NUFIP1P ) and BAI3 gene (brain-specific angiogenesis inhibitor gene), which is to homologous to BAI1 and shown to suppress glioblastoma [ 33 ]. Conclusions In summary, high resolution array-based CGH revealed large number of chromosomal aberrations previously identified in osteosarcoma by chromosomal CGH and conventional cytogenetic methods. The present study allowed precise identification of smaller DNA copy number alterations, which suggest the presence of specific target genes in osteosarcoma. Although this study suggested several possible target genes from amplified regions from 6p, 8q, 12q and 17p, but these genes should be validated by other molecular and immunohistochemical approaches on well-defined large patient samples. Further, interaction or association studies between small genomic losses and gains will facilitate the identification of new genetic pathways in the pathogenesis of osteosarcoma. Competing interests None declared. Authors contributions TKM and KJ have contributed towards the data analysis. LP, ML, RG, and CL were assisted in sample collection and clinical information of the patients. X-YL has involved in array CGH experiments and data collection. CPH has involved in extracting the gene information from BAC clones. SS has provided the arrays used in this study. PHR was involved in the planning, and organization of the project. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514550.xml |
533879 | No effects of GSM-modulated 900 MHz electromagnetic fields on survival rate and spontaneous development of lymphoma in female AKR/J mice | Background Several reports indicated that non-thermal electromagnetic radiation such as from mobile phones and base stations may promote cancer. Therefore, it was investigated experimentally, whether 900 MHz electromagnetic field exposure influences lymphoma development in a mouse strain that is genetically predisposed to this disease. The AKR/J mice genome carries the AK-virus, which leads within one year to spontaneous development of thymic lymphoblastic lymphoma. Methods 320 unrestrained female mice were sham-exposed or exposed (each n = 160 animals) to GSM like 900 MHz electromagnetic fields for 24 hours per day, 7 days per week, at an average whole body specific absorption rate (SAR) value of 0.4 W/kg. Animals were visually checked daily and were weighed and palpated weekly. Starting with an age of 6 months, blood samples were taken monthly from the tail. Animals with signs of disease or with an age of about 46 weeks were sacrificed and a gross necropsy was performed. Results Electromagnetic field exposure had a significant effect on body weight gain, with higher values in exposed than in sham-exposed animals. However, survival rate and lymphoma incidence did not differ between exposed and sham-exposed mice. Conclusion These data do not support the hypothesis that exposure to 900 MHz electromagnetic fields is a significant risk factor for developing lymphoma in a genetically predisposed species, even at a relatively high exposure level. | Background The use of mobile phones is increasing worldwide, although electromagnetic fields emitted by mobile phones and base stations are a source of great concern. However, so far it is unclear, if non-thermal exposure has a direct influence on public health. French et al. [ 1 ] developed a theoretical model, by which radiofrequency radiation from mobile phones could induce cancer, via the chronic activation of the heat shock response. Non-thermal exposure to electromagnetic fields can result in an increased expression of heat shock proteins (hsp) [ 2 , 3 ]. This is a normal defense response to cellular stress. However, chronic expression of hsp is known to induce or promote oncogenesis, metastasis and/or resistance to anticancer drugs [ 1 ]. Additionally, 72 hours exposure of human lymphocytes to continuous 830 MHz electromagnetic fields caused a linear increase in chromosome 17 aneuploidy with rising specific absorption rates (SAR: 1.6–8.8 W/kg). This is a signal for genetic instability and may thereby lead to cancer development [ 4 ]. In principal agreement, few epidemiological studies suggest a relationship between the use of mobile phones and uveal melanoma [ 5 ] or malignant brain tumors [ 6 - 9 ] However, the overall literature does not provide persuasive epidemiological evidence that mobile-phone-related emissions are carcinogenic, although mobile phones have not been in use long enough to exclude long-term impact on health [ 10 ]. It was suggested that non-thermal exposition to high-frequency electromagnetic fields may rather have a tumor promoter than an initiator effect [ 9 ], since DNA, generally, does not appear to be significantly altered or damaged by electromagnetic fields [ 11 ]. In this respect it was discussed, if a possibly reduced excretion of the oncostatic hormone melatonin by electromagnetic fields may facilitate the development of estrogen dependent tumors [ 12 ]. However, the results of different rodent studies concerning tumor promotion are not consistent. On the one hand, no difference in radiation or chemically induced tumor growth could be found after long-term exposure to electromagnetic fields (860–900 MHz) in rats or mice [ 13 - 15 ] Additionally, exposure of human leukaemia cells to electromagnetic fields failed to induce any changes in apoptosis, micronucleation or differential gene expression [ 16 ]. On the other hand, long-term exposure to pulse-modulated electromagnetic fields similar to those used in digital mobile telecommunication significantly increased in one study the incidence of lymphoma in Eμ- Pim 1 transgenic mice [ 17 ], which are genetically predisposed to develop lymphoma spontaneously, but not in another [ 18 ]. The differences between the studies may indicate that various species or strains as well as cancer types differ in their sensitivity to electromagnetic field exposure. The sensitivity to electromagnetic fields may result from an acquired lower resistance against adverse effects or a genetic predisposition [ 19 ]. Different proportions of a sensitive subpopulation within an epidemiological or experimental study would influence the interpretation of a possible role in carcinogenesis. However, national or international thresholds for electromagnetic field intensities must ensure adequate health protection also for susceptible people. AKR mice are widely used in cancer research for their high leukaemia incidence (60–100%) [ 20 ]. Mice of this strain are viremic from birth and express in all tissues the retrovirus AKV, which is associated with spontaneous leukaemia development in mice [ 21 - 23 ]. Generally, leukaemia induced by a given virus is restricted to a single histopathological type; most common is a lymphocytic leukaemia originating in the thymus. However, the type of leukaemia induced can sometimes be altered by age or experimental manipulation [ 24 , 25 ]. Using AKR mice, we studied the incidence of tumors and survival rates under chronic influence of high-frequency electromagnetic fields. Despite some physiological differences between mice and humans, a good correlation between known or assumed human carcinogens and test results in rodent studies has been described, often with the same organs affected in humans and in rodents [ 26 ]. Therefore, the results of this study shall help to evaluate a possible health risk of mobile phones. Methods Animals and animal husbandry 320 female AKR/J mice were airfreighted from the Jackson Laboratory (Bar Harbor, ME, USA), at an age of 4–5 weeks. After arrival, animals were randomized and housed in groups of 6 or 7 on softwood bedding (Altromin, Lage, Germany) in polycarbonate cages (40 × 25 × 15 cm, W × L × H, Ebeco, Castrop-Rauxel, Germany), enriched with paper. Mice were allowed free access to mice standard food pellets (type 1324, Altromin) and tap-water. Twice a week cages were cleaned and water changed. Temperature was controlled at 21°C ± 2°C. The light was on a 12 hours light-12 hours dark cycle, with light on at 8 am. No sterilization measurements were taken, since AKR/J mice are not especially sensitive for pathogens. However, to prevent a possible transfection from humans to mice or mice to mice, respectively, masks and gloves were worn, which were sterilized between handling of different cages. Animals were inspected daily for signs of moribundity and were weighed (accuracy ± 0.1 g) and palpated weekly. Starting with an age of 6 months, blood samples were taken monthly from the tail. A tattoo in the ear allowed individual identification. The Bremen state commission for animal welfare according to §8a of the German animal welfare legislation approved the experiments (522-27-11/2-0). Exposure setup In order to accomplish whole body exposure of a large number of non-restrained animals, one approach is to design exposure setups based on radial waveguides. Inside the waveguide the animals are kept in cages which are arranged at a constant distance from a radiating antenna in the centre, thus uniform exposure of the cages can be achieved. Another advantage is that the radial waveguide is an electromagnetic shielded system, on that score no costly shielding of any laboratory is necessary. The height of the waveguide is preferably chosen smaller than half a wavelength [ 28 ]. Thereby, single-mode operation of the TEM-mode is possible and by this homogeneous field distribution inside every cage can be guaranteed. However, in the actual study the plate distance of the radial waveguide must be chosen larger than half the wavelength of the exposure frequency due to the prescribed height of the cages of about 16 cm. Consequently, higher order modes are able to propagate in addition to the TEM-wave, which have inhomogeneous field distributions in the waveguide's cross-section. Furthermore, the simultaneous propagation of several modes leads to interference effects and thus to an unstable exposure field. Therefore, special modifications of the fundamental geometry of radial waveguides had to be performed to avoid the propagation of the unwanted higher order modes. In order to produce a well defined field distribution the cage region was excited only by the fundamental TEM-mode in a first step, i.e. for small radii the plate distance was kept below 14 cm and for larger radii the height was increased to the required value of 17 cm (Figure 1a ). Since it was still possible that the additional modes were excited by the field scattered of the mice, metal rib structures were attached to the upper and lower plate between the cages in order to shift the cut off frequencies of these unwanted modes to higher values, so that they could not propagate at the exposure frequency (Figure 1b ). The optimum size of the ribs was determined by numerically solving the eigenvalue problem of the modified waveguide. It yielded that a maximum attenuation of the higher order modes is reached for specific heights and widths of the ribs. Therewith, it was shown that the unwanted modes can be forced to become evanescent and thus a stable field distribution is achievable. Moreover, the rib structure does not alter the propagation constant of the TEM-mode, and the perturbation of the field distribution of the fundamental mode is negligible within the cage volume. Both implemented waveguides (one for exposure, one for sham-exposure) of ca. 4 m diameter and 17 cm vertical plate distance were placed within the same room and carried up to 24 cages measuring 425 mm × 265 mm × 160 mm (L × W × H) each of them housing 6–7 mice. The cage area was covered with trapezoidal lids (3 cages per opening) with wire mesh (Figure 2 ). This design ensured easy maintenance and also that both light and gas could penetrate the lids while electromagnetic radiation was effectively shielded. At the outer boundaries of the units, absorbers were installed which caused minimal reflection and "hot spots". A signal generator (SMT 06, Rohde & Schwarz, Munich, Germany) and an amplifier (HLV-500, BEKO, Munich, Germany) were connected to the cone antenna of one unit via a "black box" so that it could not be seen which group of animals was exposed (blind design). The signal of the generator was modulated (BS 825F, BUGH Wuppertal, Germany) in a way which simulated a situation near a mobile communication base station (downlink) combined with a contribution from an mobile phone DTX operation mode (uplink), thus including 2 Hz, 8 Hz, 217 Hz, and 1733 Hz frequency components (Figure 3 ). For additional details see also [ 27 ]. Animals were exposed 24 hours per day with the exception of approximately 1 hour weekly when animals were weighed and palpated, and during which the cages were cleaned. The experiment was performed at a mean value of 0.4 W/kg of the whole body specific absorption rates. This value, which was stipulated by the financial backer, is five times higher than the limit of whole-body exposure for the general population and is based on the limit value for occupational exposure [ 29 ]. Since the mice can move freely, the whole body SAR varies with their postures and positions inside their cage. Therefore, the specific absorption rates in the mice were analyzed by numerical computations of the electromagnetic field distribution inside the radial waveguide for five different configurations of the animals, which were assumed to be uniformly distributed in time. Configurations account for groups of mice in the front and rear section of the cage as well as mice with head, left/right side toward the incident wave and upright posture. Since only the variation of the whole body SAR is subject of interest, it is sufficient to use simple homogeneous models (ellipsoids, length 6 cm, diameter 3 cm, appr. 32 g) filled with muscle tissue for the mice (Figure 4a ). After evaluation of all absorption rates per rodent it turned out that the standard deviation of the whole body SAR was ± 40%. The assessment of maximum localized SAR was performed by use of an anatomical mice model which was placed into the group of ellipsoids. (Figure 4b ). The required time-averaged input power of the exposure unit was 35 W. The presence of the field was monitored continuously, again via a "black box". In Streckert et. al [ 30 ] features of the exposure facility, which was previously used for experiments with rats, are described in detail. Noise levels provoked by the integrated ventilation system were measured in close proximity to both units and were found to be identical (sound meter model 2218 with 1/3 octave filter set model 1616, Brüel & Kjaer, Naerum, Denmark). The total level was 69 dB (lin), and less than 25 dB at frequencies between 8 and 40 kHz. Thus possible disturbing effects of ultrasound were excluded. Pathology Animals were sacrificed by CO 2 gas when signs of a developing disease became evident or at an age of about 46 weeks, after a last blood sample was taken. A gross necropsy was performed focusing on main tissues of disease involvement (spleen, thymus and lymph nodes) and tumor infiltration (liver, kidney, lung, brain). Tissues were immersion-fixed in Bouin's solution for up to 24 h and subsequently in ethanol (70%), embedded in paraffin and sectioned at 5 μm. Blood smears were stained with Pappenheim's stain and tissue slices using hematoxylin and eosin. When a mouse was found dead in its cage (5 exposed, 7 sham-exposed mice) a necropsy was performed, but no tissues were fixed. Statistics Group mean body weights were tested for a possible exposure influence in dependence of time, using multiple regression analysis (InStat 3.05, GraphPad). An unpaired t-test was applied to compare the loss of weight associated with lymphoma development. Survival curves and lymphoma incidence were plotted according to the method of Kaplan and Meier. Differences between curves were compared using the logrank test, with animals censored, which were still alive at the end of the study (Prism 4.01, GraphPad). Two-way ANOVA was used to test for possible changes in differential leucocytes counts with time and exposure. Statistical significance of differences was tested two-sided at the p ≤ 0.05 level. If not indicated otherwise, data are given as means ± standard error of the mean. The exposure code was broken only after completion of the analyses. Results Body weight and water consumption Chronic exposure to 900 MHz electromagnetic fields had no influence on the absolute body weight of female AKR/J mice; however, its influence on the relative weight change was significant (p < 0.001) (Figure 5 ). The rapid development of lymphoma in this strain of mice was associated with a loss of individual body weight of about 9.2% in exposed and 8.5% in sham-exposed mice, but the group difference was not statistically significant. Water consumption was approximately 4 g per day and mouse, and not different between exposed or sham-exposed animals (data not shown). This value is in accordance to the water intake measurements published by the Jackson Laboratory [ 31 ], and obviously not influenced by the experimental set-up. Survival and incidence of lymphoma Similar survival rates were seen in both groups of AKR/J mice (Figure 6 ). The first exposed mouse died of lymphoma after 60 days and the first sham-exposed animal after 88 days. Median survival time was 183 (sham-exposed) and 190 days (exposed mice), and not significantly different according to the logrank test, with animals censored which were still alive at the end of the study. Patterns of tumor-related mortality in the sham-control group were consistent with those observed in a previous study conducted in this laboratory with AKR/J mice [ 32 ]. As seen in our previous study, essentially all mortality observed in AKR/J mice was related to the development of lymphoblastic lymphomas [ 33 , 34 ] (Figures 7 , 8 ). Exceptions were 3 animals with rectal eczema (2 exposed, 1 sham-exposed), one animal with unclear findings and two sham-exposed animals with protruded vagine. These findings were considered random findings and not related to the exposure. Clinical picture In female AKR/J mice lymphoma developed rapidly, usually associated with lymphadenopathy. In 28.2% (exposed) and 30.3% (sham-exposed) of all animals, lymphomas were restricted to the thymus, followed by respiratory distress and protrusion of the eyes. 13 animals (8 exposed, 5 sham-exposed) died in their cages without any earlier sign of distress, although autopsy revealed enlarged mediastinal mass compressing the thoracic space. The lung was affected in 10% of the exposed and sham-exposed animals; 8 exposed and 6 sham-exposed animals developed macroscopically visible metastatic tumors in the liver or spleen (Figure 9 ). Other clinical observations like splenomegaly and ruffled fur were considered to be associated with neoplastic development and did not correlate with the electromagnetic field exposure. Tumors of other sides such as mammary gland or intestine could not been observed. When the animals reached an age of about half a year, differential counts of leucocytes were performed monthly using blood smears from tail blood. As seen in Figure 10 , exposure to GSM-modulated electromagnetic fields had neither influence on the ratios of lymphocytes to neutrophilic granulocytes nor on counts of monocytes, eosinophilic or basophilic granulocytes. However, the development of lymphoma was associated with changes in the red and white blood picture. Symptoms were changes in the counts of lymphocytes and neutrophilic granulocytes, toxic granulation in neutrophilic granulocytes, the occurrence of juvenile cells or blasts, blastoid or atypical lymphocytes, Gumprecht's shadows, leucopenia, anisocytosis, poikilocytosis or enhanced polychromasia. These changes were not related to the exposure. Discussion The present study was designed to test the hypothesis that 900 MHz electromagnetic fields, modulated according to the global system for mobile communication (GSM), increases the risk of lymphoma incidence in female AKR/J mice. According to the results this hypothesis has to be rejected, since compared with sham-exposed females of this strain, a mean exposition of 0.4 W/kg SAR neither influenced the risk to develop lymphoma, nor the malignancy of the disease, only an influence on the growth pattern of the animals was observed. However, the present experiment does not allow any conclusions about tumor onset or the kinetics of tumor development, since for such type of study animals would have to be sacrificed and examined at fixed intervals irrespective of clinical symptoms. Exposure to electromagnetic fields increased the growth rate in the nematode Caenorhabditis elegans [ 35 ], but decreased the birth weight of albino rat offsprings [ 36 ]. In contrast, the growth pattern of Eμ- Pim 1 mice was not changed due to exposure to electromagnetic fields [ 17 , 18 ]. During the progression of the present experiment, female AKR/J mice showed a tendency to obesity. Accumulation of weight was significantly related to the exposition (see Figure 5 ), leading to a higher body weight gain in exposed compared with sham-exposed mice. Food was available ad libitum , and various studies described effects of electromagnetic fields on the nervous system in humans or rodents [ 37 - 39 ]. It may, therefore, be possible that the exposure to the electromagnetic field influenced the appetite, leading to higher food intake. However, the exposure-independent water consumption does not indicate that major changes in the intake of food occurred. Mitochondrial heat production is one of the main energy consuming processes in endotherms like mice [ 40 , 41 ]. The Interaction of electromagnetic fields with water molecules in cells results also in heat production. Although the continuous exposure in our study should not have increased the mice's body temperatures, it may have contributed in keeping the animal's body temperature above ambient, therewith economizing mitochondrial heat production. If mitochondrial functions were not changed due to the electromagnetic field exposure, unchanged food intake may so have let to increased fat accumulation. In this context it is important to compare the SAR value of 0.4 W/kg with the total energy consumption of mice (approximately 5 W/kg), thus on the order of 10%. Since the electromagnetic energy is absorbed passively (i.e., not originating from metabolizing food), the increased body weight might be a consequence of a shift in energy utilization. This hypothesis, however, must be examined by specific studies of the mice' metabolism. Anyhow, such an effect would be visible only in long-term exposure studies and probably insignificant with only 1 hour exposure per day [ 17 , 18 ]. A demonstration that long-term exposure to electromagnetic fields derived from mobile phones or base stations increases the incidence of tumors in animals would provide direct evidence that such radiation is carcinogenic. The most positive evidence of an effect of exposure to high frequency electromagnetic fields similar to that used by mobile phones was reported by Repacholi et al. [ 17 ], using Eμ- Pim 1 transgenic mice, which are known to develop spontaneous lymphoma with a high incidence rate. Lymphoma risk was found to be significantly higher in the exposed Eμ- Pim 1 mice than in the controls, mostly pronounced for non-lymphoblastic lymphoma. Humans are presently not known to carry an activated Pim 1 gene, but other inherited gene defects are known that predispose carriers to develop cancer [ 19 ]. However, an investigation within the electromagnetic energy program of the National Health and Medical Research Council of Australia, using the same Eμ- Pim 1 mice from the same supplier (Taconic Farms, New York) as Repacholi et al. [ 17 ], did not find a significant effect of 898.4 MHz GSM radiofrequency radiation at SAR values of up to 4.0 W/kg [ 18 ]. Because of the importance of these studies, a replication started according to plan in spring 2002 in Italy. First results are expected 2005. Nevertheless, the inconsistent results already indicated the need of further assessment of the relevance of such findings for human health [ 10 ]. A Japanese study showed that neither 1.5 GHz nor 929.3 MHz electromagnetic field exposure promotes liver carcinogenesis in a medium-term bioassay system, using partially hepatectomised F344 rats [ 42 ]. A monopole antenna close to the constrained animals emitted a "near-field" radiation that resulted in SAR values of 0.45–0.68 W/kg as a whole-body average and of 0.9–1.9 W/kg in the liver. It was suggested that the applied "near-field", which is more in line with the actual exposure conditions of cellular telephone users, explains the differences to the study of Repacholi et al. [ 17 ], who employed a "far-field" and mean whole-body SAR values of 0.13–1.4 W/kg. However, the confinement may also affect the results [ 43 , 44 ], as well as the different animal models: long-term exposure of genetically predisposed animals on the one hand and a medium-term bioassay of chemically induced carcinogenesis on the other hand. Therefore, it is difficult to decide which results are more relevant for human mobile phone users. In the present study non-restrained mice that are genetically predisposed to develop lymphoma with a high incidence were exposed to a "far-field" similar to both Australian studies [ 17 , 18 ], with the difference that our mice were exposed for 24 h, whereas their mice were exposed for 1 hour per day only. In contrast to Repacholi et al. [ 17 ], we could not observe an increased lymphoma risk. However, our study's results are consistent with the investigation within the electromagnetic energy program of the National Health and Medical Research Council of Australia [ 18 ]. The authors also did not find a significant effect of 898.4 MHz GSM radiofrequency radiation at SAR values of up to 4.0 W/kg when compared to sham-irradiated animals. The overall conclusion of the present study as well as of data from the literature is that they lack evidence that electromagnetic field exposure increases the incidence of leukaemia in rodents. Conclusions The present study does not support the hypothesis that chronic exposure to high-frequency electromagnetic fields, similar to those emitted by mobile phones and base stations promote neoplastic development in the hematopoietic system in genetically predisposed mice. However, we cannot rule out that exposure to electromagnetic fields may be risk factors for other neoplastic development. Competing interests The authors declare that they have no competing interests. Authors' contributions AS carried out the study, performed the statistical analyses and drafted most of the manuscript. AL conceived the study, participated in its design and coordination, and drafted some parts of the manuscript. JS, AB and VH developed the technical set up and delivered the dosimetry for the experiment. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533879.xml |
526253 | In vitro pharmacokinetics of anti-psoriatic fumaric acid esters | Background Psoriasis is a chronic inflammatory skin disease that can be successfully treated with a mixture of fumaric acid esters (FAE) formulated as enteric-coated tablets for oral use. These tablets consist of dimethylfumarate (DMF) and salts of monoethylfumarate (MEF) and its main bioactive metabolite is monomethylfumarate (MMF). Little is known about the pharmacokinetics of these FAE. The aim of the present study was to investigate the hydrolysis of DMF to MMF and the stability of MMF, DMF and MEF at in vitro conditions representing different body compartments. Results DMF is hydrolyzed to MMF in an alkaline environment (pH 8), but not in an acidic environment (pH 1). In these conditions MMF and MEF remained intact during the period of analysis (6 h). Interestingly, DMF was hardly hydrolyzed to MMF in a buffer of pH 7.4, but was rapidly hydrolyzed in human serum having the same pH. Moreover, in whole blood the half-life of DMF was dramatically reduced as compared to serum. The concentrations of MMF and MEF in serum and whole blood decreased with increasing time. These data indicate that the majority of the FAE in the circulation are metabolized by one or more types of blood cells. Additional experiments with purified blood cell fractions resuspended in phosphate buffered saline (pH 7.4) revealed that at concentrations present in whole blood monocytes/lymphocytes, but not granulocytes and erythrocytes, effectively hydrolyzed DMF to MMF. Furthermore, in agreement with the data obtained with the pure components of the tablet, the enteric-coated tablet remained intact at pH 1, but rapidly dissolved at pH 8. Conclusion Together, these in vitro data indicate that hydrolysis of DMF to MMF rapidly occurs at pH 8, resembling that within the small intestines, but not at pH 1 resembling the pH in the stomach. At both pHs MMF and MEF remained intact. These data explain the observation that after oral FAE intake MMF and MEF, but not DMF, can be readily detected in the circulation of human healthy volunteers and psoriasis patients. | Background Psoriasis is a chronic inflammatory skin disease characterized by epidermal hyperplasia and infiltration of inflammatory cells into skin lesions. Anti-psoriatic therapies are mainly anti-inflammatory. Long-term use of many of these anti-psoriatic therapies is often hampered by serious adverse effects [ 1 - 5 ]. In this connection it is of interest that already in 1959, Schweckendiek introduced fumaric acid, an intermediate of the citric acid cycle, for the treatment of his psoriasis [ 6 ]. The main adverse effect of fumaric acid therapy, i.e. induction of gastric ulcers, was overcome by application of a mixture of fumaric acid esters (FAE) with great bioavailability [ 7 ]. This mixture, consisting of dimethylfumarate (DMF) and salts of monoethylfumarate (MEF), was formulated as enteric-coated tablets. This systemic therapy, successfully applied by several German [ 8 , 9 ] and Dutch [ 10 , 11 ] dermatologists, can be taken by patients for a long period due to the excellent safety profile [ 12 ]. Adverse effects that do occur are mostly mild and transient and include facial flushing and gastro-intestinal complaints. Pharmacokinetic data of FAE therapy are very limited and mainly based on personal communications [ 8 , 13 ]. For such a pharmacokinetic study, we first developed a highly sensitive method to determine concentrations of FAE in human blood (Litjens et al ., manuscript submitted). In the present study, we investigated the hydrolysis of DMF to its most bioactive metabolite monomethylfumarate (MMF) and the stability of MMF, DMF and MEF in different environments representing various body compartments using this methodology. Results Stability of FAE and hydrolysis of DMF to MMF in buffers of various pH DMF, MMF and MEF remained completely intact in a buffer of pH 1 mimicking the pH in the stomach (Figure 1A and 1F ). However, at pH 8 resembling the pH in the small intestines DMF, the most abundant component of the FAE tablet, was hydrolyzed to MMF (the half-life of DMF amounted to 1.5 hr) (Figure 1B ). Addition of MEF, the other component of the FAE tablet, did not affect the half-life of DMF (1.7 hr) (Figure 1G ). MMF remained intact (Figure 1B ) in this buffer during the period of analysis (6 hr) as did MEF (Figure 1G ). Figure 1 Changes in the concentrations of the various FAE in different environments. DMF at a concentration of 2 mg/L or the combination of 2 mg/L DMF and 1.4 mg/L MEF were placed at 37°C in 0.1 N HCl; pH 1 (A, F), 0.1 M sodium phosphate buffer; pH 8 (B, G), 0.1 M sodium phosphate buffer; pH 7.4 (C, H), normal human serum (D, I) or whole blood (E, J). At various intervals thereafter samples were collected and the MMF (squares), DMF (circles) and MEF (triangles) concentrations were measured using HPLC. Results are a representative experiment of at least 3 independent experiments. To further examine the pH-dependency of the hydrolysis of DMF to MMF, we measured concentrations of DMF and MMF in phosphate buffers (with pH ranging from 6.5–8) supplemented with DMF or the combination of DMF and MEF. The results revealed that the half-life of DMF dramatically decreased with increasing pH values and the maximal hydrolysis of DMF to MMF was seen at pH 8 (half life of DMF was 1.5 hr). For example, at pH 7.4 the half-life of DMF amounted to 12.7 ± 1.0 hr (n = 3) (Figure 1C ). In agreement with these results we observed that the Fumaraat 120 tablet disintegrated completely between 1.5 and 2.5 hr in the alkaline, but not in the acidic, environment. The half-life of DMF in the tablet amounted to approximately 2.3 hr (data not shown). Changes in the concentrations of DMF, MMF and MEF in serum and whole blood Since FAE must enter the circulation to exert their anti-psoriatic effects at the affected skin site [ 14 ], we determined the hydrolysis of DMF to MMF and examined the stability of MMF, DMF and MEF in both normal human serum and whole blood (both with a pH of 7.4). The half-life of DMF in serum (Table 1 and Figure 1D ) is dramatically shorter (p < 0.05) than that in a buffer of the same pH. MMF (Figure 1D and 1I ) and MEF (Figure 1I ) concentrations slowly decreased in serum during the period of analysis (6 hr). Furthermore, the half-life of DMF was even shorter (p < 0.05) in whole blood than in serum (Table 1 and Figure 1E ), indicating that circulating cells are also involved in the hydrolysis of DMF to MMF. Furthermore, concentrations of MMF (Figure 1E and 1J ) and MEF (Figure 1J ) in whole blood decreased steadily during the period of analysis (6 hr), indicating that they may be metabolized by blood cells as well. Table 1 Hydrolysis rate of DMF to MMF and half-lives of DMF in different environments. To analyze under which circumstances DMF can be hydrolyzed to MMF and whether MEF affects the hydrolysis of DMF into MMF, we determined the hydrolysis rates for DMF in different environments. In short, a 0.1 M sodium phosphate buffer, human serum and whole blood (all pH 7.4) were spiked with either 2 mg/L of DMF or with the combination of 2 mg/L of DMF and 1.4 mg/L of MEF and at several intervals thereafter, samples were taken and prepared in order to measure the concentration of DMF, MMF and MEF by HPLC. Subsequently, after calculating the area under the curves for DMF (AUC_DMF) and MMF (AUC_MMF), the following model [16] was used to fit the concentrations of MMF and to estimate the k DMF (rate of hydrolysis of DMF into MMF) in these solutions: [MMF] t = i = (k DMF *AUC_DMF)-(k MMF *AUC_MMF) + [MMF] t = 0. In addition, the half-life was calculated using the following formula: t 1/2 = ln(2)/k. Data are means and SD (n = 3). # and * significant (p < 0.05) different value between buffer and and serum and serum and whole blood, respectively. k dmf (h -1 ) t 1/2 (h) Buffer Spiked with: DMF 0.06 (0.004) 12.72 (1.04) DMF+MEF 0.05 (0.01) 15.17 (1.88) Serum Spiked with: DMF 1.96 (0.47) 0.37 (0.08) # DMF+MEF 2.20 (0.25) 0.32 (0.05) # Whole blood Spiked with: DMF 8.01 (3.78) 0.10 (0.04)* DMF+MEF 10.08 (2.74) 0.07 (0.02)* To find out which blood cell type(s) is (are) responsible for the hydrolysis of FAE in whole blood, hydrolysis of DMF in a buffer of pH 7.4 by purified blood cell fractions was analyzed. The results revealed that monocytes/lymphocytes (Figure 2A ), but not granulocytes (Figure 2B ) and erythrocytes (Figure 2C ), at concentrations present in whole blood effectively hydrolyzed DMF to MMF. Figure 2 Hydrolysis of DMF to MMF by various types of blood cells. Monocytes/lymphocytes, granulocytes, and erythrocytes were purified from blood of healthy volunteers using centrifugational techniques. Next, the various cell types were resuspended in PBS pH 7.4 to concentrations present in whole blood, e.g. 1 × 10 6 /mL monocytes/lymphocytes (A), 5 × 10 6 /mL granulocytes (B) and 5 × 10 9 /mL erythrocytes (C), and then DMF was added to a final concentration of 2 mg/L. At various intervals thereafter samples were collected and the MMF (squares) and DMF (circles) concentrations were measured using HPLC. Results are a representative experiment of 3–4 independent experiments. Discussion A major finding of the present study is that hardly any DMF was hydrolyzed in a buffer of pH ≤ 7.4, whereas at pH 8, resembling the pH of the small intestines, this FAE was effectively hydrolyzed to its active metabolite MMF. It should be noted that MMF (and MEF) remained stable in these buffers. We realize that using acidic or alkaline buffers to mimick the conditions in body compartments, like the stomach and the small intestines, is only a first attempt to investigate the in vitro pharmacokinetics of FAE. For example, no enzymes, e.g. esterases, are present in these buffers whereas they are in these body compartments. In this connection, Werdenberg and collegues [ 15 ] recently showed that in the small intestines, the concentrations of MEF and MMF remained unaffected, whereas concentrations of DMF decreased by the action of esterases, such as carboxyl- and choline-esterases in this compartment. Esterase activity is also present in the liver which can cause a rapid disappearance of the various FAE from the circulation. Absorption of FAE from the small intestines into the circulation is not only dependent on the permeability of the intestinal membrane for the various FAE (permeability increases with increased acyl-chain length and increased lipophilicity), but also on the stabilities of the various FAE in the small intestines and liver. Clearly, hydrolysis of DMF to MMF is not only dependent on the pH of the environment but also on the activities of esterases. Another important finding of this study is that the half-life of DMF in whole blood is considerably shorter than that in serum, although the pH of both blood and serum is 7.4. To explain this difference in hydrolysis of DMF in whole blood and serum we considered the possibility that blood cells also hydrolyze DMF to MMF. Using purified blood cell fractions resuspended in PBS (pH 7.4) we found that monocytes/lymphocytes, but not granulocytes and erythrocytes, at concentrations present in whole blood effectively hydrolyzed DMF to MMF. The rapid removal of DMF from PBS after addition of granulocytes and erythrocytes suggests that these blood cells bind DMF. It should be realized that MMF (and MEF) most likely enter the circulation of psoriasis patients in order to exert their antipsoriatic effects in the skin lesions. In agreement we detected MMF and MEF, but not DMF, in the circulation of healthy volunteers and psoriasis patients after oral intake of Fumaraat 120 ® tablets [[ 16 ], Litjens et al ., manuscript submitted; Litjens et al ., unpublished data]. Our observation that the MMF is more rapidly removed from whole blood than from serum could indicate that MMF (and MEF) is taken up by blood cells and perhaps further metabolized into FA, which subsequently fuels the citric acid cycle, as suggested earlier by Joshi (personal communication). The different interactions between FAE and blood cells may affect their functional activities, as has been reported earlier [ 14 , 17 - 19 ], thus contributing to the beneficial effects of FAE therapy. Conclusions Together, these in vitro data indicate that DMF is almost completely hydrolyzed to MMF at an alkaline pH, but not at an acidic pH, suggesting that this hydrolysis occurs mainly within the small intestines and not in the stomach. Most likely, MMF and MEF are then absorbed in the circulation where they interact with blood cells and perhaps cells in the psoriatic lesions. The different interactions between these FAE and the various cell types may explain the beneficial effects of FAE in psoriasis. Finally, these in vitro experimental data will be key to the pharmacokinetic analysis of oral FAE in human healthy volunteers and psoriasis patients. Methods Fumaric acid esters (FAE) The following FAE were used: dimethylfumarate (DMF; purity > 97%, TioFarma, Oud-Beijerland, The Netherlands), calcium-monoethylfumarate (MEF; purity > 97%, Tiofarma), monomethylfumarate (MMF; purity > 97%, AstraZeneca R&D, Charnwood, Loughborough, UK). In addition, the enteric-coated, magisterial manufactured tablet (named Fumaraat 120 ® ; TioFarma), containing 120 mg of DMF and 95 mg of calcium-MEF was investigated in this study. DMF, MMF and MEF in acidic and alkaline environments To investigate the stability of DMF, MMF and MEF and the hydrolysis of DMF to MMF in several environments representing various aspects of different body compartments, 0.1 N HCl with pH 1 and 0.1 M sodium phosphate buffer with pH 8 were spiked with 2 mg/L of DMF, MMF, MEF or the combination of 2 mg/L of DMF and 1.4 mg/L MEF, to resemble the ratio of these two components in the Fumaraat 120 ® tablet. In addition, to determine the release of the contents of a Fumaraat 120 ® tablet and the hydrolysis of DMF to MMF at pH 1 (0.1 N of HCl) and pH 8 (0.1 M of sodium phosphate buffer), the tablet was placed in these buffers and at various intervals samples were taken and prepared for measurement of the concentrations of DMF, MMF and MEF by high-performance liquid chromatography (HPLC) as described below. To further investigate the effect of the pH on the hydrolysis of DMF to MMF, 0.1 M sodium phosphate buffers with pH values ranging from 6.5–8 were spiked with DMF and the combination of DMF and MEF. At several intervals thereafter, samples were taken, and then prepared for measurement of the various FAE by HPLC. As the current buffers lack proteins, no extraction procedure was necessary and the concentrations of the various FAE in the samples could be directly quantified by HPLC (see below). Concentrations of DMF, MMF and MEF in serum and whole blood As described above, serum and whole blood from 3 volunteers was spiked with 2 mg/L of DMF, MMF, MEF or the combination of 2 mg/L of DMF and 1.4 mg/L MEF. All volunteers were healthy as assessed by a full medical screening. At several intervals, samples were taken, and then prepared for measurement of the various FAE by HPLC. In short, serum and whole blood contained proteins known to interfere with the measurement of FAE. To overcome this problem, the various FAE were extracted from serum and whole blood samples and subsequently the concentrations were measured by HPLC (see below). Effects of purified blood cell fractions on the hydrolysis of DMF in PBS (pH 7.4) The various blood cell fractions were obtained from blood of healthy volunteers using centrifugational techniques as described earlier [ 17 , 19 ]. In short, blood was subjected to Ficoll Amidotrizoate (ρ = 1.077 gm/L; Dept. of Pharmacy, Leiden University Medical Center, Leiden, The Netherlands) density gradient centrifugation (440 g 20 min at 18°C). After resuspension of the cells in the pellet in phosphate buffered saline (PBS; pH 7,4) the granulocytes were purified by plasmasteril (Fresenius AG, Bad Homburg, Germany) sedimentation (1 g) for 10 min at 37°C, washed with PBS and the contaminating erythrocytes were lysed with distilled water. Erythrocytes were obtained after washing the cells in the Ficoll-Amidotrizoate pellet three times with PBS supplemented with 0.1 IU heparin. Cells in the Ficoll-Amidotrizoate interphase (monocytes/lymphocytes) were washed three times with PBS containing 0.5 IU heparin and then resuspended in PBS pH 7.4. Next, suspensions of 1 × 10 6 monocytes and lymphocytes/mL PBS, 4 × 10 6 granulocytes/mL PBS, and 5 × 10 9 erythrocytes/mL PBS were spiked with 2 mg/L DMF. Again, at several intervals samples were taken and concentrations of the various FAE were measured as described below. Sample preparation and HPLC analysis The concentrations of the various fumarates in serum samples were determined as described (Litjens et al ., submitted for publication). Briefly, after precipitation of serum proteins with acetonitrile, DMF in the samples was quantitated by HPLC. The sample preparation for MMF and MEF required a protein precipitation step with metaphosphoric acid followed by extraction with diethylether and additional pH-lowering to pH 0.5. Next, sodium chloride was added before centrifugation at 12,000 g. Thereafter, the ether layer was transferred to a glass vial and after evaporation the residue reconstituted in methanol: 0.1 M potassium phosphate buffer (KH 2 PO 4 /K 2 HPO 4 ; pH 7.5) supplemented with 5 mM tetrabutylammonium dihydrogen phosphate 1:1 (v/v). Concentrations of DMF, MMF, and MEF were determined on a HPLC apparatus (Spectra SERIES P100, Thermo Separation Products, Breda, The Netherlands) equipped with an Alltima C18 (5 μ 250*4.6; Alltech, Lokeren, Belgium) column and an Alltima Guard C18 precolumn (5 μ 7.5*4.6; Alltech, Lokeren, Belgium) using methanol:water 30:70 (v/v) as an eluent for DMF and methanol: potassium phosphate buffer supplemented with 5 mM tetrabutylammonium dihydrogen phosphate 20:80 (v/v) as eluent for MMF and MEF. The limit of detection for all three compounds amounted to 0.01 mg/L, the coefficient of variation for MMF, DMF and MEF was 7%, 8% and 9% at 0.5 mg/L, respectively (n = 4), and the recovery of MMF, DMF and MEF amounted to 75 ± 7%, 98 ± 3%, 67 ± 7% (n = 6). Standard curves constructed with purified FAE in buffers or human serum were used to quantify the concentrations of FAE in the various samples of these buffers and human serum or whole blood, respectively. Authors' contributions NL participated in the design of the study, analysis of the data and drafted the manuscript. ES carried out the optimisation of the HPLC method and performed all HPLC analyses. CvG was responsible for the optimisation of the HPLC method and participated in the design of the study. HM participated in the design of the study and analysis of the data. JvD, HT and PN conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526253.xml |
535575 | Ecology's Big, Hot Idea | Can the emerging field of metabolic ecology explain all life's patterns in one unifying theory, from the metabolic rate of a shark to why biodiversity peaks at the equator? | Life is complicated. It comes in all sorts of shapes, sizes, places, and combinations, and has evolved a dizzying variety of solutions to the problem of carrying on living. Yet look inside a cell and life takes on, if not simplicity, then at least a certain uniformity—a genetic system based around nucleic acids, for example, and a common set of chemical reactions for turning food into fuel. And looked at in broad swathes, life shows striking generalities and patterns. Every mammal's heart will beat about one billion times in its lifetime. Both within and between species, the density of a population declines in a regular way as the size of individuals increases. And the number of species in all environments declines as you move from the equator towards the poles. Wouldn't it be good if there were a simple theory that used life's shared fundamentals to explain its large-scale regularities, via its diversity of individuals? In the past few years, a team of ecologists and physicists have come up with just such a theory. At its heart is metabolism: the way life uses energy is, they claim, a unifying principle for ecology in the same way that genetics underpins evolutionary biology. They believe that energy use, in the form of metabolic rate, can be understood from the first principles of physics, and that metabolic rate can explain growth, development, population dynamics, molecular evolution, the flux of chemicals through the environment, and patterns of species diversity—to name a few. The work, its originators insist, is not a theory of everything for biology, or even ecology. But it can often seem that way. “We're making advances on a broad range of questions almost on a weekly basis,” says James Gillooly, of the University of New Mexico, Albuquerque. “We've been having an awful lot of fun.” Beneath the Surface Metabolic ecology, as it has become known, is still controversial. Some think its mathematical foundations are unsound, and that it explains nonexistent trends. It also divides researchers on philosophical lines—those that see life's patterns as fundamental versus those who think that variation is the key, those who think that simple, general ideas can help us understand nature versus those who think that complicated problems require complicated answers. A lot is riding on the debate: “If the theory is right, it's one of the most significant in biology for a long time,” says ecologist David Robinson of the University of Aberdeen. “It would provide a common functional basis for all biodiversity.” Scientists have known for nearly two centuries that larger animals have relatively slower metabolisms than small ones. A mouse must eat about half its body weight every day not to starve; a human gets by on only 2%. The first theories to explain this trend, developed in the late nineteenth century by the German nutritionist Max Rubner and the French physiologist Charles Richet, were based on the ratio between an animal's surface area, which changes with the square of its length, and its volume, which is proportional to its length cubed. So large animals have proportionately less surface area, lose heat more slowly, and, pound for pound, need less food. The square-versus-cube relationship makes the area of a solid proportional to the two-third power of its mass, so metabolic rate should also be proportional to mass 2/3 . For many years, most biologists thought that it was. But in 1932, Max Kleiber, an animal physiologist working at the University of California's agricultural station in Davis, re-examined the question, and found that, for mammals and birds, metabolic rate was mass 0.73 —closer to three quarters than two thirds. Kleiber looked at animals ranging in size from a rat to a steer. By the mid-1930s, other workers had put together a “mouse to elephant” curve that supported the three-quarter-power law, and by the 1960s, the plot had been extended for everything from microbes to whales, still seeming to show the same relationship. Quarter-power scaling also began to stretch beyond metabolic rate. Biological times, such as lifespan and heart rate, were found to be proportional to mass 1/4 , and fractions related to one-quarter show up in other scaling relationships: the diameter of the aorta and tree trunks is proportional to mass 3/8 , for example. It was, however, much harder to find a theoretical reason for why metabolic rate should be proportional to mass 3/4 —and more generally, why quarter-power scaling laws should be so prevalent in biology. The impasse meant that by the mid-1980s interest in scaling had waned. But it sparked back into life in 1997, when two ecologists—James Brown of the University of New Mexico, Albuquerque, and his graduate student Brian Enquist, now at the University of Arizona, Tucson—and a physicist, Geoffrey West of the Santa Fe Institute, developed a new explanation of why metabolic rate should equal the three-quarter power of body mass. West, Brown, and Enquist's theory is based on the structure of biological distribution networks, such as blood vessels in vertebrates and xylem in plants. The trio assumed that metabolic rate equals the rate at which these networks deliver resources, and that evolution has minimized the time and energy needed to get materials from where they are taken up—the lungs or roots, for example—to the cells. They also assumed that, although organisms vary greatly in size, the terminal units in their distribution networks, such as blood capillaries or leaf stalks, do not. Bigger plants and animals take longer to transport materials, and so use them more slowly. In West, Brown, and Enquist's model, the maximally efficient network that serves every part of a body has a fractal structure, showing the same geometry at different scales. And the number of uniform terminal units in such a network—and so the rate at which resources are delivered to the cells—is proportional to the three-quarter power of body mass. Pattern versus Variation Whether metabolic rate really varies with the three-quarter power of body mass is still debated—some researchers still favor two-thirds, others think that no one exponent fits all the data—but a majority of biologists favor three-quarters. And whether the fractal theory really explains the relationship of metabolic rate to body size is also still contentious. In the most wide-ranging critique so far, published this April, two Polish researchers, Jan Kozlowski, of Jagiellonian University, Krakow, and Marek Konarzewski of the University of Bialystok, claimed that the theory's maths could not simultaneously contain both uniform terminal units and three-quarter-power scaling, that large animals built along such lines would have more blood than their bodies could contain, that biological scaling laws were not built around quarter powers, and that biological networks were not generally branching fractals. “I don't believe there's anything to explain—there's no universal scaling exponent,” says Kozlowski. He is also struck by what is left unexplained when size is accounted for: animals of the same size can still show more than an order of magnitude variation in metabolic rate. “What's striking in nature is the variability,” he says. “There are regularities that call for explanation, but that doesn't mean ignoring the variability is correct.” Kozlowski is the co-author of a theory that relates metabolic rate to cell size and the amount of DNA an organism has, one of several alternative explanations of the scaling of metabolic rate published since West, Brown, and Enquist's model. The criticisms are serious, says Robinson. “The jury is out—questions about the fundamental maths are worrying a few people.” On the other hand, he says, West, Brown, and Enquist's model seems a plausible template for designing an organism, and its predictions fit real-world data remarkably well. Whether this fit truly captures the physical and chemical mechanisms underlying the patterns remains to be seen; Robinson hopes that criticism can strengthen West, Brown, and Enquist's model, perhaps leading to a new, improved theory. The metabolic theory's authors are not budging. “We've yet to see a criticism we feel we can't answer pretty readily,” says Brown. Kozlowski and Konarzewski's arguments are based on a misreading of the work, he says, and criticisms that focus on one aspect, such as the structure of mammalian vascular systems, miss the key point, which is generality: “If we're wrong on quarter powers, why do they keep showing up in everything from life-history processes to evolutionary rates?” From Sharks to Tomatoes After accounting for size, Brown's group turned its attention to the second most important influence on metabolism: temperature. The effect is exponential, and a 5 °C rise in body temperature equals a roughly 150% rise in metabolic rate. The team built an equation for metabolic rate that combined the mass 3/4 term with the Boltzmann factor. The latter is an expression of the probability that two molecules bumping into each other will spark a chemical reaction. The higher the temperature, the greater the probability, and the faster the reaction. Adding temperature explained much of the variation in metabolic rate that remained after adjusting for size. It also explained some of the metabolic differences between groups. For example, a reptile has a slower metabolic rate than a mammal of the same size. But adjusting for its lower body temperature removes much of the difference, suggesting that the two groups share fundamental metabolic processes. The same even goes for plants and animals. “When you correct for size and temperature, the metabolic rates of a shark, a tomato plant and a tree are remarkably similar,” ( Figure 1 ) says Gillooly, who joined Brown's group as a grad student to work on the temperature question. It's not yet clear what the activation energy represents, says Gillooly. It could be a kind of average for all the hundreds of chemical reactions in metabolism, or maybe the energy needed to get over one crucial hump in the path. Figure 1 After Correcting for Body Size and Temperature, the Metabolic Rates of a Shark, a Tomato Plant, and a Tree Are Remarkably Similar (Illustration: Sapna Khandwala) The metabolic theory's third component, resources, is also something of a black box at this stage. Nutrient supply, the team reasons, is the next most important determinant of metabolic rate, and will account for some of the remaining unexplained variation. As with temperature, the overall effect could be a balance of many processes, or it could be due to one limiting element—the growth of lake phytoplankton is often limited by phosphorus, for example, while for marine phytoplankton iron is usually the crucial nutrient. “It's a work in progress,” says Brown. “But our vision for a metabolic theory of life is ultimately going to include material resource limitation.” These three things still do not account for all the variation in metabolic rate, but more detailed knowledge of species can yield more precise predictions. Using body size, altitude, and diet, Brian McNab, of the University of Florida, Gainesville, has explained 99.0% of the variation in metabolic rate for birds of paradise ( Figure 2 ), and 99.4% of the rate variation in leaf-nosed bats. Nevertheless, when McNab sees attempts to explain variation in metabolism using a few parameters applied across a wide range of sizes and taxonomic groups, what isn't explained strikes him as forcefully as what is. Figure 2 Adult Male Raggiana Bird of Paradise ( Paradisaea raggiana ) Body size, altitude, and diet account for 99.0% of the variation in the metabolic rates of birds of paradise. (Photo: Brian McNab) “I have serious reservations as to whether there is a single relationship for body size and metabolic rate,” he says. “I think we will be able to find generalizations in ecology, but they're not going to be simple—there will be a bunch of clauses and restrictions, and animals have a lot of ways to bend the rules.” No theory matches data exactly, Brown points out; having a baseline prediction for metabolism lets you identify exceptional cases worthy of further investigation. Viewed from this angle, the metabolic theory is a kind of null hypothesis of how organisms work. “Until you have a theory that makes a prediction, you don't know how to interpret any of the variation,” says Brown. And, he adds, despite this variation, the underlying trends are also meaningful. “There are themes of life that are deep-seated and fundamental.” All the business of life needs energy. So if you know the rate at which an organism burns fuel—or if you know how big and hot it is, and apply the metabolic theory—you can make a suite of predictions about its biology, such as how fast it will grow and reproduce, and how long it will live. By correcting for mass and temperature, Brown, Gillooly, and their colleagues believe they have revealed underlying similarities in all the rates of life. The hatching times for egg-laying animals, including birds, fish, amphibians, insects, and plankton, turn out to follow the same relationship—if a fish egg were the same size and temperature as a bird egg, it would take equally long to hatch ( Figure 3 ). The same goes for growth: a tree and a mammal of equal size and temperature would gain mass at the same speed. And size and temperature even explain much of the variation in mortality rates between species—which one might have thought to be strongly dependent on external factors such as predators—perhaps through metabolism's influence on aging processes, such as free-radical damage to the genome. Figure 3 Apple Snail Eggs The hatching times for egg-laying animals, including birds, fish, amphibians, insects, and plankton—or even these Apple Snail eggs—turn out to follow the same relationship. (Photo: Gary M. Stolz, U. S. Fish and Wildlife Service) One Rule for All? If all organisms work in the same way, understanding individual biology offers an obvious route to explaining nature's patterns—ecological processes become a kind of meta-metabolism. Indeed, the team has used their theory to predict the flux of carbon dioxide through forests—a measure more usually used to determine individual metabolic rate. They have also found that body size and temperature predict the densities and growth rates of populations. So hotter environments should support lower population densities, as each individual consumes resources more quickly, leaving less to go round. One thing that does not scale with a quarter power of body size is the area of animals' home ranges; this increases more or less linearly with body size. But in October, Brown, along with researchers from Princeton University and the Institute of Zoology in London, published a model that brought this, too, into the metabolic theory. They borrowed another trick from physics, using an equation that describes colliding gas molecules to model the interactions between neighboring animals. Temperature could also explain why biodiversity peaks at the equator, the team believes. Organisms with faster metabolisms have faster mutation rates. So the genomes of smaller, hotter animals change more quickly, and they will also get through their generations more rapidly. One would therefore expect to see more new species created in small organisms and warm environments. The large-scale trend in all these rates—hatching time, individual and population growth, ecosystem metabolism, DNA substitution—is closely proportional to a quarter power of body mass. In the future, Brown's group plans to examine the dynamics of colonial organisms and societies through the lens of metabolic ecology; instead of capillaries, the terminal units of the networks would become ants, or people. There are also many applied problems within the theory's scope, including some of the most significant human impacts on the biosphere. Carbon emissions and the consequent global warming are increasing both the temperature and nutrient supply. And exploited populations, such as fisheries often show a decrease in individual size, as larger animals are preferentially killed. Both these would tend to speed up biological processes. Another team of United States and Italian researchers has found that the same model that describes the growth of individuals can also predict the growth of tumors, hinting that metabolic ecology may have medical applications. Brown hopes that metabolic ecology will one day become an uncontroversial part of researchers' toolkits, like the theories population geneticists use to predict changes in the frequencies of genes. Before that happens, both the theory's proponents and its opponents have years of work ahead of them. Adopting the theory may also require a shift in ecologists' worldview. Most ecologists work by carrying out experimental manipulations on small groups of similar organisms: the warblers in a woodland, for example, or the grasses of a meadow. When they build models, they do so from empirical data, not from physical first principles. The philosophy behind metabolic ecology disconcerts many researchers, says Robinson. “A lot of traditional biologists are uncomfortable with thinking about data in these terms.” Kozlowski doubts that simple theories can make precise predictions about the behavior of biological systems on large scales. He believes that metabolic ecology risks leading the discipline up a blind alley: “If I'm right, and the basic model contains an error, correcting the results will be a very long process. If they're not right, they'll have done a disservice to ecology.” But many ecologists are more optimistic that some unifying principles of nature can be found, and that metabolic ecology, and the debate around it, is a step in the right direction. Some think the theory may be part of an even grander idea. Stephen Hubbell, of the University of Georgia, is one of the architects of another idea causing a stir among ecologists. Called neutral ecology, it proposes a general explanation of how competition between individuals produces the dynamics of birth, death, and migration seen in ecosystems, and its predictions match closely the abundance and diversity of species in the wild. He believes that metabolic and neutral ecology can become elements of some larger theoretical framework. “I've never been more excited in my life,” says Hubbell. “Ecology now is like quantum mechanics in the 1930s—we're on the cusp of some major rearrangements and syntheses. I'm having a lot of fun.” | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535575.xml |
522747 | Microarrays in ecological research: A case study of a cDNA microarray for plant-herbivore interactions | Background Microarray technology allows researchers to simultaneously monitor changes in the expression ratios (ERs) of hundreds of genes and has thereby revolutionized most of biology. Although this technique has the potential of elucidating early stages in an organism's phenotypic response to complex ecological interactions, to date, it has not been fully incorporated into ecological research. This is partially due to a lack of simple procedures of handling and analyzing the expression ratio (ER) data produced from microarrays. Results We describe an analysis of the sources of variation in ERs from 73 hybridized cDNA microarrays, each with 234 herbivory-elicited genes from the model ecological expression system, Nicotiana attenuata , using procedures that are commonly used in ecologic research. Each gene is represented by two independently labeled PCR products and each product was arrayed in quadruplicate. We present a robust method of normalizing and analyzing ERs based on arbitrary thresholds and statistical criteria, and characterize a "norm of reaction" of ERs for 6 genes (4 of known function, 2 of unknown) with different ERs as determined across all analyzed arrays to provide a biologically-informed alternative to the use of arbitrary expression ratios in determining significance of expression. These gene-specific ERs and their variance (gene CV) were used to calculate array-based variances (array CV), which, in turn, were used to study the effects of array age, probe cDNA quantity and quality, and quality of spotted PCR products as estimates of technical variation. Cluster analysis and a Principal Component Analysis (PCA) were used to reveal associations among the transcriptional "imprints" of arrays hybridized with cDNA probes derived from mRNA from N. attenuata plants variously elicited and attacked by different herbivore species and from three congeners: N. quadrivalis, N. longiflora and N. clevelandii . Additionally, the PCA revealed the contribution of individual gene ERs to the associations among arrays. Conclusions While the costs of 'boutique' array fabrication are rapidly declining, familiar methods for the analysis of the data they create are still missing. The case history illustrated here demonstrates the ease with which this powerful technology can be adapted to ecological research. | Background The 'genomics revolution' has provided the information needed to analyze how a genome responds to the environment in the formation of the "transcriptome", the portion of the genome that is transcribed. Microarrays, which offer the ability to analyze the expression ratios (ERs) of thousands of genes simultaneously, represent one of many new tools produced by this effort. However, not all biological disciplines have benefited equally from this technology, and array technology has not been widely adopted by the ecological community for a number of reasons. The large genome-wide arrays are only available for select model organisms, which may not be appropriate for many ecological questions. Moreover, the complexity of their analysis and the costs of the available commercial software solutions prohibit their adoption by small research groups and constrain the number of biological experiments that can be conducted even by large, better-funded groups. 'Boutique' arrays – on which a smaller fraction of the transcriptome, typically representing a selection (hundreds) of genes specific to a class of genetic elements or response types – are readily created for a non-model organism at costs that are affordable for small research groups. However, the problems remain of how best to normalize and analyze array data. A large number of software solutions are available but no clear best solution has emerged [ 1 - 5 ]. A recent review has examined the types of arrays as well as the ecological and evolutionary questions that can be addressed with microarrays [ 6 ]. Here we present a cDNA microarray designed to analyze plant-herbivore interactions in a native plant. A cDNA microarray is a comparative tool, providing relative ERs for multiple genes from two differentially labeled fluorescent cDNA samples prepared by reverse transcription of mRNA extracted from matched plant samples. Hence the procedure is particularly useful for the analysis of plant responses elicited by herbivore attack: the induced defense and tolerance responses of plants [ 7 ]. We examine a number of practical challenges facing the adoption of boutique arrays for ecological research with tools familiar to ecologists, including signal normalization, the use of arbitrary expression thresholds to determine the significance of expression, the use of within-and between-array signal variance in evaluating the effect of probe quality and quantity and array age, as well as data analysis and visualization by cluster and Principal Component Analysis (PCA). The microarray was designed to examine herbivore-induced gene expression in the model ecological expression system, Nicotiana attenuata [ 8 ]. The genes for the microarrays were derived from a series of display (differential display reverse transcriptase-PCR, subtractive hybridization with magnetic beads, and cDNA-AFLP display) experiments that compared the transcriptome of plants attacked by the larvae of its specialist herbivore, Manduca sexta , with that of unattacked plants [ 9 - 11 ]. Two independent and differentially end-labeled cDNA probes of each of 240 genes were spotted in quadruplicate on each array. Hence each gene was represented by 8 replicate probes, which were used to analyze within-array ER variance (array CV). Since the array was composed of genes that were both down-or up-regulated in response to M. sexta attack, an array-specific normalization factor could be readily calculated. The effects of microarray age and cDNA quality on the measures of array CV were estimated. We present a 2-step criterion for determining significant expression based on t-tests of replicate ERs and arbitrary thresholds. We re-examine the use of arbitrary expression thresholds with a 'norm of reaction' analysis of 6 genes derived from the 73 hybridization experiments. The data from microarrays are frequently analyzed with cluster analysis procedures [ 12 ], which deliver a limited analysis of the statistical associations. PCA is frequently used in ecological studies but is not commonly used in the analysis of array data. We present a PCA of 35 hybridized arrays, which visualizes the contribution of ERs from particular genes to the associations among arrays in the PCA. Results and Discussion Array CVs, array age and probe quality The array CV for each of the 73 arrays was strongly correlated with the number of gene ERs that showed higher values than the defined threshold for the variance (R 2 = 0.969, F 69,1 = 2102, P < 0.001). This demonstrates that the array CV corresponds to the number of gene ERs that are outliers and therefore reflects the "quality" of the information derived from the array. We used array CVs to test if array age could explain some of the variance and found no detectable effect (R 2 = 0.025, F 69,1 = 2.73, P = 0.103). The spectrum of the cDNA was recorded between 240 and 700 nm. Shape and maxima of the curves for the particular compounds (DNA, Cy3, Cy5) allowed the evaluation of cDNA quantity and quality. The quantity of the cDNA that was hybridized was estimated by its OD at 260 nm. The quality of the fluorescently labeled probe derived from this cDNA was estimated by the relation of the quantity of the two dyes at 550 nm (Cy3) and 650 nm (Cy5) and the cDNA quantity. These linear regressions revealed that for cDNA quantity (OD 260 values), neither Cy3 nor Cy5 values were significantly correlated with array CVs (all R 2 < 0.007, all Ps > 0.225). There was a negative correlation between array CV and OD 550 values for Cy3 (R 2 = 0.069) and OD 650 values for Cy5 (R 2 = 0.051) with slopes of -7.55 and -5.7, respectively. However, only the Cy3 regression was significant (P = 0.028) whereas Cy5 was not (P = 0.06). A similar pattern was apparent for the probe quality: Cy3 and Cy5 quality parameters were negatively correlated with array CV, but only the regression for Cy3 (R 2 = 0.144, slope = -0.31) was significant (P = 0.001) whereas the regression for Cy5 (R 2 = 0.042, slope = -0.126) was not (P = 0.088). From this analysis, we conclude that the quality of the labeled cDNA sample to be hybridized to an array predicts the quality of the signals produced from the array. PCR product quality The 502 different PCR products (2 for each gene + internal controls) that were spotted on the arrays had the following distribution in the 4 quality categories (Fig 2A ): 1 = single band (426): 2 = single band with slight background (48); 3 = single band with strong background (14); 4 = multiple bands with background or only background (14). Multiple bands were only spotted to determine how low quality PCR products effect the results. To evaluate the association of PCR product quality on the variance of ERs, gene CVs were plotted against the PCR quality class. Gene CVs were found to be significantly different among the 4 PCR categories (Fig. 2B , Kruskal-Wallis ANOVA on Ranks, H 3 = 40.603, P < 0.001). While post hoc tests revealed that PCR quality did not have a directional effect on gene CV, it was lowest for genes with intermediate CVs and increased in genes with high and low CVs. We conclude that the quality of the PCR product spotted on arrays does not have a strong effect on gene CV. Figure 2 A: 2% agarose gel with 1 kb and 100 bp size ladders and examples illustrating the 4 different PCR-qualities classes (1 – 4): 1 = single band: 2 = single band with slight background indicating multiple non-specific PCR products; 3 = single band with strong background; 4 = multiple bands with background or only background. B: Mean coefficient of variance (CV) of expression ratios for 8 replicate cDNA products from 253 genes (array CV) measured from73 hybridized microarrays based on the 4 PCR quality classes described in A. Classes have significantly different CVs (Kruskal-Wallis ANOVA on Ranks, H 3 = 40.603, P < 0.001) Expression patterns All arrays A cluster analysis of 35 arrays (Fig. 3 ) reflected the similarities of the transcriptional patterns observed in arrays hybridized with similar treatments. Arrays hybridized with probes derived from mRNA from N. clevelandii (arrays 12, 13, 14) and N. longiflora (arrays 17, 18, 19, 32) were separated from those hybridized with material from N. quadrivalis (arrays 10, 11) and N. attenuata that had been attacked by aphids or leaf hoppers (arrays 15, 16, 26, 27). These arrays were separated from those hybridized with samples from antisense-transformed N. attenuata plants that had been attacked by Manduca caterpillars (arrays 25, 28, 29, 30, 31, 34, 35), and the cluster they formed was separated from all other arrays that had been hybridized with N. attenuata material elicited by methyl jasmonate treatments (MeJA, arrays 9, 20, 21, 22, 23, 24) or attacked by Manduca , mirid, Heliothis or Spodoptera herbivores (arrays 1 – 8). The 3 replicated arrays hybridized with the same mRNA clustered together (arrays 33, 34, 35). The details of these similarities will not be treated here, as they are discussed in separate publications. The similarity of the elicited transcriptional signatures observed on the arrays hybridized with the N. longiflora and N. attenuata [ 13 ] probes demonstrates the utility of the array in the analysis of samples from congenerics. Figure 3 Cluster analysis (Ward's method, squared Euclidean distance) showing similarities between 35 hybridized microarrays hybridized with probes from wildtype (WT), antisense Lox-3 (AS LOX ) and antisense TD (AS TD ) of the diploid native tobacco species, Nicotiana attenuata plants and from untransformed plants of 3 congeneric Nicotiana species, two of which are allotetraploids N. quadrivalis and N. clevelandii and that are thought to have N. attenuata as a common ancestor as well as the more distantly related, N. longiflora . Arrays were hybridized with probes from plants attacked by different herbivore species or elicited with methyl jasmonate (MeJA). The shaded box represents 3 replicate hybridizations of the same sample of m-RNA from LOX N. attenuata plants. Arrays included in brackets correspond to clusters in the PCA (Fig. 4). A PCA of the same 35 arrays (Fig. 4 ) showed a similar pattern of associations but provided the additional information of which genes contributed most to the patterns observed in the PCA. The vector of the gene coding for proteinase inhibitors ( PI ) was correlated with the first canonical axis that explained 40% of the total variance in the dataset. Moreover, transcripts for PI were up-regulated in the N. attenuata arrays elicited with MeJA or attacked by Manduca , mirid, Heliothis or Spodoptera herbivores. Expression of xyloglucan endo-transglycosylases ( XTH ) and WRKY transcription factor transcripts was also correlated with the first axis and correlated with the location of arrays 1 – 8 in the PCA. These 2 genes were plotted relatively close together in the PCA, reflecting their similar patterns of regulation across all arrays. The vector of allene oxide synthase ( AOS ) transcript expression reveals a correlation with arrays hybridized with mRNA from MeJA-elicited plants. AOS catalyzes a later stage in the biosynthesis of jasmonic acid and is known to be elicited by MeJA treatments [ 14 ]. The response of two unknown genes ( 434 and 540 ) exemplifies genes whose pattern of expression is opposite to that discussed for the genes of known function. The ERs of gene 434 reacted in the opposite direction as those of WRKY and XTH , and the responses were larger in antisense N. attenuata plants. The response of gene 540 was opposite to that of AOS and larger in N. clevelandii and N. attenuata plants attacked by leaf hoppers. Figure 4 Principal component analysis (PCA) of the distribution of mean gene expression ratios of 234 genes (origin of vector is at the intersection of Axes 1 and 2 and the top of vector plotted as triangles) in the 35 hybridized microarrays (plotted as circles and squares) hybridized as described in Fig. 3. Arrays are labeled according to plant species and treatment (see Fig 3). Particular genes are identified with arrows. Clusters of microarrays with similar treatments are connected by lines. Axes 1 and 2 account for 40.1 and 8.3 % of the variation, respectively. Vectors of genes that are relatively long and parallel and, as such, correlated with the first canonical axis explain a large part of the variance. Vectors are strongly (up-or down) regulated in arrays and clusters of arrays lying near the end of a particular gene vector. For example, the WRKY gene vectors (originating at the intersection of Axes 1 and 2 and terminating at the WRKY gene triangle) contribute significantly to the cluster of microarrays hybridized with labeled cDNA derived from MeJA-elicited and Manduca and mirid attacked plants. Or, for example, the AOS gene vectors (originating at the intersection of Axes 1 and 2 and terminating at the AOS gene triangle) contribute significantly to the clusters of microarrays hybridized with labeled cDNA from MeJA-treated plant. Individual genes The expression patterns of 6 genes (4 of known function; 2 of unknown function), as the mean of 2 PCR fragments with differently modified primers across 73 experiments, illustrate the 'norm of reactions' of the transcriptional responses of these genes (Fig. 1 ). The transcriptional responses of these genes were in opposite directions and within various ranges of expression to the different treatments. Genes such as PI and XTH exhibit strong up-regulation (up to 88-fold) in response to herbivore attack and jasmonate elicitation, and are similarly strongly down-regulated (50-fold) when plants transformed to silence endogenous jasmonate biosynthetic enzymes (antisense LOX [ 15 ]) are elicited and compared with untransformed plants on the same array. The inset of the XTH norm of reaction depicts the variance in ERs from a selection of individual arrays to illustrate that treatments (arrays 16 and 6) eliciting very similar mean ERs (both 3.20) can have very different gene standard errors of the mean ER (SE) (0.19 and 0.78 respectively). Shaded areas represent the arbitrary ER thresholds of ± 0.3 for log 2 -transformed values. All 6 genes had numerous treatments in which these thresholds were exceeded, but the genes differed in the magnitude and direction in which the threshold ERs were exceeded. In contrast to the PI and XTH genes, the unknown gene 540 and the WRKY transcription factor had more attenuated 'norm of reactions', being maximally up-and down-regulated by only 6.5-and 5-fold across all 73 arrays. In a majority of the experiments, the AOS gene was up-regulated, while down-regulation was more common for unknown gene 540 . In many experiments, however, ERs did not exceed threshold values. Figure 1 Norm of reaction of expression ratios (ER) for 6 genes from 73 hybridized microarrays of which the 35 presented in the cluster analysis (Fig. 3) are labeled with numbers. Distribution of log-transformed mean expression ratios of 4 genes of known function [proteinase inhibitor ( PI ), xyloglucan endo-transglycosylase ( XTH ), NtWRKY2 ( WRKY ) and allene oxide synthase ( AOS )] and 2 of unknown function ( 540 and 434 ); dotted areas represent the arbitrary ER thresholds of 1.24 and 0.81 (corresponding to ± 0.3 for log 2 transformed values). Genes are organized according to the relative spread of their expression ratios A > B > C. Insert in XTH panel shows error structure (mean ± SE) on a non-log scale calculated from 8 replicate spots from each array. Ecologists are frequently interested in the processes that "fit" organisms to their environment. Adaptation to a particular environment results in part from the phenotypic consequences of hundreds of coordinated changes in gene expression, but because many levels of organization exist between an organism's transcriptome and its phenotype, it is often unclear how best to study the process of adaptation. Array technology has the potential to identify genes relevant to the process of adaptation, regardless of the time scale involved (evolutionary to physiological). However, a number of technical issues remain to be solved before the technology can be fully incorporated into ecological research: the normalization of signals, the within-and between-array variability of ERs, and the general problem of coping with the large amount of data that array studies produce. Many techniques have been discussed but a consensus for a standard solution [ 4 ] has not yet emerged. Normalization Since mRNA samples are labeled with different efficiencies and the different fluorescent dyes have different optical properties, signals from an array require normalization before ERs can be calculated. The literature addressing the problems of normalization has been reviewed [ 1 , 2 ], with the consensus conclusion that there is no single best way to normalize array data and that specific solutions were required for the particularities of each array. When arrays are created with cDNAs that are typically both up-and down-regulated, a total intensity normalization can be used. By adapting a total intensity procedure [ 1 ] we normalized the signals from only the middle 75% of the distribution from a given array which produced values that were highly comparable among arrays, as demonstrated by the similarity of the clustering of the 3 replicate arrays (arrays 33, 34, 35; Fig 3 , Fig. 4 ). Variance ERs from microarrays are derived from two differently labeled but mixed samples that competitively hybridize to immobilized gene-specific probes. The outcome of this hybridization can vary substantially within an array, as measured by the variance in ERs measured across replicate spots. The strong positive correlation between the number of genes above the specified ER-threshold and the array CVs highlights the utility of array CVs to summarize the quality of a given hybridization. Little is known about the factors that influence within-array hybridization or the amount of spot replication that is required to cope with the variance typically found in environmental samples [ 16 ]. However, the 8 replicate spots for each gene distributed across the array provided valuable data on gene and array CVs. From these CVs we were able to determine the quality of ER patterns from single arrays and single genes. Most of the technical parameters tested were not correlated with the variance structure in our dataset. Our measures of PCR product quality did not explain the variance of gene CVs. Similarly, array age did not account for a significant amount of variation in array CVs. In contrast, probe quality was negatively correlated with array CV and explains a part (ANOVA, F 69,1 = 5.046, P = 0.028) of the variance in array CVs. In our data set, a 15-fold increase in OD was associated with a halving of array CV. Therefore the monitoring of this measure of probe quality could save the costly use of arrays for samples that will likely produce low-quality results. Since none of the measured parameters unambiguously explained the pattern of within-array variance in our dataset, we conclude that a combination of several factors including the probe quality determines array variance. Data analysis Cluster analysis revealed groups of treatment that resulted in similar patterns of expression and, in doing so, provided a visual demonstration that the results obtained were reproducible. The PCA proved to be more useful for exploratory data analysis than did cluster analysis, because it provided information on the single gene vectors that contributed to similarities and differences among arrays. PCA allows researchers to quickly visualize similarities in expression patterns between known and unknown genes, and thereby generates hypotheses about the function and regulation of genes of unknown function. For example, in our analysis, a group of unknown genes – from which we chose two ( 434 and 540 ) as proxies – explained a relatively large part of the variance (indicated by long vectors) and was positively correlated to specific treatments and negatively correlated to vectors of genes of known function. Gene 434 was up-regulated in antisense LOX plants and had the opposite pattern of expression compared to that of the WRKY and XTH genes, both of which are strongly up-regulated by herbivore attack and jasmonate elicitation. Gene 540 had the opposite pattern of regulation as did AOS with higher ERs in plants attacked by leaf hoppers, suggesting a role in the plants' response to this herbivore. The PCA of Fig. 4 is a 2-dimensional presentation of a multidimensional analysis and analyses that allow for multidimensional presentations of the associations, provide more accurate information on the contribution of single gene vectors to associations among arrays. Quantitative geneticists have coined the term 'norm of reaction' for the variation in phenotypic expression of a given genotype across a number of different environments. We apply this term to characterize the range of ERs observed for a given gene across a number of different expression experiments. The information provided in a norm of reaction provides a biologically informed alternative to the use of arbitrary thresholds for the determination of significant expression. This would allow researchers to use lower thresholds for genes (e.g. WRKY transcriptions factors) that are known to show low dynamic ranges of expression and higher thresholds for genes with likely larger dynamic ranges, such as those directly involved in defense metabolite production (e.g. PI). Additionally, when comparing many arrays, a norm of reactions provides information that allows researchers to determine if a given array is providing ERs within the normal range of variance found in prior experiments. Conclusions We conclude that the data produced by 'boutique' microarrays can be readily analyzed with inexpensive home-grown procedures that are commonly used in ecological studies. Arrays with sufficient within-array replication allow for the calculation of gene and array CVs that are useful in estimating the quality of the information gathered from a given array. Furthermore, multivariate statistical techniques, such as PCA, can be used to visualize global expression patterns and identify the individual genes that make large contributions to the transcriptional signatures of particular treatments. The costs of boutique arrays are approaching those of many standard ecological procedures, and the information they provide will allow ecological researchers the ability to characterize early stages in an organisms' response to environmental changes. Methods Microarray construction and hybridization The cDNA microarray and its hybridization is described in [ 11 ], and a complete list of cDNAs and their physical location on the microarray can be found at: [ 11 ] (supplemental Table I at ). Briefly, the production of the cDNA microarray started with a set of 234 genes which were cloned by differential display reverse transcription (DDRT)-PCR and subtractive hybridization using magnetic beads (SHMB) of M. sexta larvae-attacked N. attenuata plants [ 9 , 10 ] or by cDNA-AFLP (amplified fragment-length polymorphism) display of N. attenuata plants under simulated M. sexta attack by applying oral secretions and regurgitant to leaf wounds [ 11 ] and 6 well-characterized Manduca -induced genes (putrescine methyl transferase, xyloglucan-8 endotransglycosylase, allene-oxide synthase, hydroperoxide lyase, trypsin inhibitor, WRKY transcription factor). These genes were PCR amplified and for each cDNA, two PCR fragments, with 5'-aminolink on either strand, were synthesized. Each PCR fragment was robotically spotted four times on epoxy coated slides (Quantifoil Micro Tools GmbH, Jena); hence, each gene was represented on the microarray 8 times: by two independent PCR fragments, which, in turn, were each spotted in quadruplicate. The cDNA microarrays were hybridized with fluorescently labeled cDNA prepared by reverse transcription of mRNA isolated from leaf tissues of 73 differently elicited Nicotiana plants belonging to 4 species. Competitive hybridization of 2 samples (treated and untreated plants) with different dyes (Cy3 and Cy5) defined the ratio of transcript abundance in the treatment sample compared to the control sample for each spot on the microarray. A majority of the arrays were hybridized with samples from wildtype or transformed [ 17 ] N. attenuata plants, which were elicited by attack from either various herbivore species (larvae of Manduca , Heliothis , Spodoptera moths, and adults and nymphs of aphids and mirids that attack N. attenuata ), methyl jasmonate (MeJA), or larval regurgitant treatments or UV-B exposure, and compared with plants of the same genotype, age, and developmental stage which were unelicited. To determine the utility of the arrays in the analysis of responses from congenerics, arrays were hybridized with samples taken from two tetraploid species ( N. quadrivalis and N. clevelandii ) that had evolved from independent allopolyploid hybridizations between N. attenuata and another extinct 12-chromosome Nicotiana taxa [ 18 ], as well as the more distantly related, N. longiflora . The details of each hybridization and the specific gene responses of the arrays are either published [ 11 , 13 , 19 ] or are in preparation. Here we present a global analysis of 73 arrays to identify methods of analysis for such boutique microarrays that are useful for ecological research. Normalization and statistics Because the arrays included both up- and down-regulated genes, the calculation of a microarray-specific normalization factor provided a valuable alternative to the use of external reference controls, which may or may not be influenced by the elicitation conditions [ 2 , 20 - 22 ]. The measured Cy5 and Cy3 fluorescence intensities were ranked independently, and after discarding the 12.5% maximum and minimum values, the remaining 75% of the values were summed (adapted total intensity normalization, [ 1 ]). The array-specific normalization factor was obtained by dividing the calculated sum of Cy3 values by those of the Cy5 values. The ratios of normalized fluorescence values for Cy3 and Cy5 of each individual spot (expression ratio = ER) and the mean of the four replicate spots for each cDNA (2 for each gene = ER1, ER2) were calculated. ERs were subjected to a t-test to determine if the values differed significantly from 1. A transcript was defined as being differentially regulated if both of the following criteria were fulfilled: 1) the final ER (ER1+ER2)/2) was equal to or exceeded the arbitrary thresholds [≤ 0.81 (log 2 0.81 = -0.3) for down-regulated genes or ≥ 1.24 (log 2 1.24 = 0.3) for up-regulated genes]; 2) both ER1 and ER2 were significantly different from 1 as evaluated by t-tests to control for ER-variance and ER-sample size. An arbitrary threshold was utilized for two reasons: first, to account for normalization errors, and second, to account for the fact that replicate data did not result from repeated hybridizations with the same RNAs but from repeated probe spotting. To evaluate our criteria, we hybridized three arrays with the same cDNA pools and found that 210 of 234 genes (84%) had the same regulation identified by the criteria described above. Of the 30 genes that did not show consistent regulation between the two repeated hybridizations, 24 had the same direction in mean ER but did not meet the statistical requirements for a significant change. These 3 replicate arrays were located together in both the cluster analysis (Fig. 3 ) as well as the PCA (Fig. 4 ). To further estimate the variance of ERs, the mean coefficient of variation (CV) was calculated for each of the genes (gene CV) and each of the arrays (array CV). Gene CVs were obtained by calculating the mean of the individual CVs for each gene on each array; they were used to evaluate the effects of PCR product quality and the thresholds were used to determine significant expression. The quality for each gene was regarded as too low when its mean CV (mean of all 73 arrays) was higher than 0.3. Gene CVs are not influenced by the absolute expression values and reflect the variation across replicate spots on a given array. Array CVs were calculated as the mean of all individual gene CVs for each array and were used to evaluate array and cDNA quantity and quality that was hybridized to the arrays. Since the 73 arrays analyzed in this study were hybridized over 8 months after the arrays were spotted, we used array CV to assess array ageing. A cluster analysis of 35 arrays was performed based on Ward's method and the squared euclidian distance [ 23 , 24 ]. To evaluate the appropriate model for the description of the gene distribution, a Detrended Correspondence Analysis (DCA) was performed. The given dimensionless value for the length of gradient of the first ordination axis was < 1.8, which indicated that the values were better fitted by a linear (lg < 3) than a unimodal (lg > 4) distribution model [ 25 ]. Therefore, a PCA based on a linear model was chosen to compare gene expression within the microarrays. PCA was performed on log-transformed mean expression ratios of all transcripts from a sample of 35 arrays. Scaling was focused on inter-array distances. Four genes of known function and two of unknown function – from the PCA analysis (Fig. 4 ), these proved to be good discriminators of the arrays – were selected to calculate a gene-specific 'norm of reaction'. For this analysis, mean expression ratios for both PCR-fragments of each of these 6 genes over all arrays were calculated and hierarchically ordered on a log-based scale. For one of these genes ( XTH ), the error structure on a non-log scale is presented (Fig. 1 and inset). To test for differences between the groups of different PCR qualities, Kruskal-Wallis ANOVA on Ranks was used. Test statistics and cluster analyses were performed with SPSS 11.0, PCA was carried out with the Canoco 4.5 package [ 25 ]. Author's contributions MH carried out the analysis of the microarray data, KG supervised the molecular work. ITB conceived of and coordinated the project, and ITB and MH wrote the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC522747.xml |
449866 | When It Comes to Frizzled-Mediated Developmental Pathways, Location Matters | null | The process of morphogenesis has long inspired the wonder and imagination of those who study it. And until the advent of adequate microscopy and lab techniques in the early 19th century, theories based more on imagination—like preformation, which held that sperm harbored fully formed, tiny beings—than observation persisted. But observationally based embryology, it turned out, revealed a notion even more fantastic: the complex higher-order architecture of tissues and organs emerges from a single cell. Patterns and structures arise largely through cell-to-cell signaling, directed by signaling molecules (ligands) and their receptor targets. These signaling pathways control key developmental processes like cell proliferation and orientation (also called polarity). A relatively small cadre of molecules is enlisted over and over again to initiate an equally limited number of pathways to shape a developing embryo. Though the mechanics and effects of many of these pathways are understood, far less is known about the mechanisms that regulate which pathway is activated. One well-studied family of proteins, called Frizzled (Fz), regulates body symmetry and cell polarity, which, among other things, makes sure the bristles on a fly's wing all point in the same direction. In the fruitfly Drosophila , Fz can activate two distinct developmental pathways: the Wnt/β-catenin pathway and the Fz/planar cell polarity (Fz/PCP) pathway. In the Wnt pathway, a Wnt ligand activates the transmembrane Frizzled receptor, which in turn activates the subcellular Disheveled (Dsh) protein, setting off a signaling cascade that ultimately activates genes involved in cell division. The Fz/PCP pathway affects the orientation of wing bristles and the symmetry of the repeating units (ommatidia) in the fly's compound eye. Previous studies suggest no clear association between a particular ligand–receptor combination and the downstream pathway, begging the question of how similarly structured receptors can signal through a common protein (Dsh) to activate different signaling pathways. As Jun Wu, Thomas Klein, and Marek Mlodzik report in this issue, it's all a matter of being in the right place at the right time. Since the same Wnt ligand–Fz receptor combinations can produce different results, the researchers reasoned that signaling specificity might depend on the context and cell type. This notion is supported by evidence that Wnt ligands bind at Fz mainly along the basolateral membrane of developing epithelial cells and that Fz hews to the apical membrane of developing wing epithelia during PCP signaling. (The plasma membrane of epithelial cells contains distinct polar domains—the apical and basolateral domains—with distinct properties.) The researchers investigated whether this location bias affects which pathway is activated by focusing on two members of the Fz family: Fz1 and Fz2. Either can activate the Wnt pathway, but only Fz1 is involved in the Fz/PCP pathway. Wu et al. first confirmed that the proteins congregated in distinct subcellular regions of developing wing epithelial cells. Then they looked for sequences or domains in the proteins that might account for their location preferences by creating Fz1/Fz2 hybrids made of various combinations of three different Fz domains. (One was the ligand-binding domain, the second the transmembrane domain, and the third the cytoplasmic “tail.”) All the hybrids with a Fz1 tail localized along the apical membrane while those with a Fz2 tail preferred the basolateral membrane, indicating that the tail domain of a receptor controls its location. The team went on to correlate apical Fz with higher levels of Fz/PCP signaling, based in part on observations that wing hairs point away from areas of Fz expression, a result associated with PCP signaling. They also showed that increased Fz activity in apical regions results in wing notches and missing bristles—traits associated with reduced Wnt signaling—indicating that apical Fz expression interferes with Wnt/β-catenin signaling. That Fz receptors can elicit distinct responses depending on their subcellular location helps explain how so few molecules can juggle so many tasks, including the miraculous feat of building an organism. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC449866.xml |
517924 | The medical care of patients with primary care home nursing is complex and influenced by non-medical factors: a comprehensive retrospective study from a suburban area in Sweden | Background The reduced number of hospital beds and an ageing population have resulted in growing demands for home nursing. We know very little about the comprehensive care of these patients. The objectives were to identify the care, in addition to primary health care, of patients with primary-care home nursing to give a comprehensive view of their care and to investigate how personal, social and functional factors influence the use of specialised medical care. Methods One-third (158) of all patients receiving primary-care home nursing in an area were sampled, and 73 % (116) were included. Their care from October 1995 until October 1996 was investigated by sending questionnaires to district nurses and home-help providers and by collecting retrospective data from primary-care records and official statistics. We used non-parametric statistical methods, i.e. medians and minimum – maximum, χ2, and the Mann-Whitney test, since the data were not normally distributed. Conditional logistic regression was used to study whether personal, social or functional factors influenced the chance (expressed as odds ratio) that study patients had made visits to or had received inpatient care from specialised medical care during the study year. Results 56 % of the patients had been hospitalised. 73 % had made outpatient visits to specialised medical care. The care took place at 14 different hospitals, and more than 22 specialities were involved, but local care predominated. Almost all patients visited doctors, usually in both primary and specialised medical care. Patients who saw doctors in specialised care had more help from all other categories of care. Patients who received help from their families made more visits to specialised medical care and patients with severe ADL dependence made fewer visits. Conclusions The care of patients with primary-care home nursing is complex. Apart from home nursing, all patients also made outpatient visits to doctors, usually in both primary and specialised medical care. Many different caregivers and professions were involved. Reduced functional capacity decreased and help from family members increased the chance of having received outpatient specialised medical care. This raises questions concerning the medical care for patients with both medical and functional problems. | Background This article describes the situation in a suburban area in Sweden, and concerns the comprehensive medical care of patients with primary-care home nursing, i.e. patients who require regular assistance from nurses in their homes in order to maintain their health and manage their health problems. This does not include hospital-at-home care, where a multiprofessional team is responsible for the medical care. The use of inpatient hospital care in Sweden as in many other Western countries has diminished in recent decades. In combination with an ageing population with greater needs for medical care, this has resulted in an increase in different forms of home care. The overall situation is similar in many countries, although local conditions may vary considerably [ 1 - 4 ]. The shift of care from the hospital to the home "has had an enormous impact on care recipients, their families and friends, and in-home service providers." [ 3 ] and "is changing the meanings, material conditions, spatio-temporal orderings and social relations of both domestic life and health-care work." [ 5 ]. One effect has been "the fragmentation and dispersion of specialised health services from hospitals to alternative locations.".. "especially revealed for people with diminished mobility" [ 4 ]. These changes make the care of patients with home nursing an important area for investigation from the perspectives both of patients and of health care workers. Much is known about the medical care, especially inpatient and outpatient hospital care of older persons, and that factors like age, health problems and socio-economic conditions influence the utilisation of inpatient hospital care [ 6 , 7 ]. Hospital-at-home care has also been the subject of several studies [ 8 - 10 ]. However, most investigations of home care and home nursing, concern care in the patient's home [ 11 , 12 ]. Other studies have focused on home nursing and medical care of patients with specific diseases, and whether care at home influences the risk of rehospitalisation [ 13 , 14 ]. But little is known about the total care of patients with home nursing, which not only includes what takes place in the home, but also the care received in hospitals, out-patient departments, and from doctors in general practice, etc. There is also a lack of knowledge about what factors influence the care of these patients, apart from medical necessities. In view of the expansion of this health care sector, such knowledge should be of value, particularly for planning purposes. In a previous paper [ 15 ] we have presented a picture of the patients with home nursing, in a Swedish suburb, and the primary health care of those patients. The patients were old (median age 83 years, range 46–95), and many had functional problems (e.g. reduced mobility (50%), vision (46%), cognitive ability (33%), hearing (29%)), and symptoms (e.g. musculoskeletal pain (53%), fatigue (46%), anxiety (44%)). Cardiovascular disorders (42%), psychiatric disorders including dementia (27%), and musculoskeletal disorders (21%) were the most common diagnoses in family physician records. Most patients had several symptoms and more than one diagnosis. All had contact with district nurses or assistant nurses, usually once a week or every second week. Ninety-seven percent of the patients had had medical care initiated by their family physician during the study year, but much of the care was carried out without direct contact between family physician and patient, as a significant part of the medical care was performed through collaboration with district nurses. This meant that the patients with home nursing saw their family physicians less often than other patients of comparable age. In view of the lack of knowledge in this expanding field, we considered it important to investigate and describe the comprehensive care of patients with home nursing as a starting point for further research and development. The objectives of the present paper are as follows: To identify the specialised medical care of patients who were receiving primary-care home nursing. To give a comprehensive view of the care of these patients. To investigate how personal, social and functional factors and help by relatives influenced the use of specialised medical care by these patients. Methods The study was performed in a suburban area of Stockholm with 40 000 inhabitants, 18 percent of whom were 70 years of age or older. The care of patients, with primary-care home nursing, who lived in ordinary houses or flats was studied. Patients in the study area who received regular nursing care at home for a period of more than two weeks from the district nurses in primary health care were registered as primary-care home nursing patients (Table 1 ). In Stockholm, patients can choose to go to any of the hospitals (11 emergency hospitals and several smaller geriatric hospitals during the study year) or outpatient departments in the city. Two emergency hospitals, two geriatric hospitals and two wards for psychiatric inpatient care were located in or close to the study area. During the registration week (21 to 27 October 1996), 486 patients in the study area had primary-care home nursing. Using a random table, we selected one-third of the patients of each district nurse for the study. The study was designed as a retrospective study of the comprehensive medical care of patients with primary-care home nursing, including the medical care they received both in their homes and in other places. It was also designed to study whether non medical factors that are common among patients with home nursing may have influenced the care. The data were not obtained from the patients, but from records and from the family physicians and district nurses responsible for the patients' primary health care, i.e. professionals dealing with the patients' medical problems. Data were also obtained from the official statistics of the Swedish County Councils, a source that is generally considered by researchers to be of high quality and well suited for scientific purposes. A description of the patients and the care performed by family physicians, district nurses and assistant nurses was given in a previous article [ 15 ]. The hypotheses were - that care outside the home comprises a substantial part of the total care of patients with home nursing. - that personal, social and functional factors may influence the use of medical care outside the home Information concerning the situation during the registration week was obtained from questionnaires distributed the week following the registration week. Retrospective data from the study year (28 October 1995 to 27 October 1996) were obtained from the official statistics, and the family physician (21 family physicians) and nursing (20 district nurses) primary health care records. The official statistics were used to identify and describe inpatient care and outpatient visits in specialised medical care, and the number of home and practice visits to/by the nurses in primary health care. Notes in the family physician records were used to describe the family physician care (reason for contact, who had been in contact and measures undertaken) as well as the diagnoses of the patients [ 16 ]. Notes in the nursing records were used by the district nurses to identify nursing procedures. The protocol for extraction of information from the nursing records comprised 18 questions with fixed-alternative answers and was designed for the study by the Stockholm Gerontology Research Centre in cooperation with a group of district nurses [ 17 ]. Personal, social and functional data concerning the situation during registration week, as well as patients' symptoms, and help from relatives at that time, were obtained from the questionnaires. When possible, validated questions that had been tested in other studies were used, but some were modified to suit the situation in home nursing. These revisions were made by the Stockholm Gerontology Research Centre in cooperation with a group of district nurses [ 17 ]. Personal and social factors included age and sex, whether or not the patient lived alone, and whether there were one or more relatives who assumed responsibility for a substantial amount of the care. Functional problems concerned cognitive function (difficulty knowing the day of the week, finding the way home and/or recognising relatives/caregivers), mobility (being unable to move about in the immediate surroundings), and ADL capacity. For ADL capacity the different Katz index functions were used and the patients were grouped according to the degree of ADL dependency. Patients in Group 1 were either without functional deficiencies or dependent only regarding cleaning, shopping and/or transport, patient in Group 2 were, in additions, dependent with respect to cooking, bathing and/or dressing, but not eating, and patients in Group 3 were in addition dependent concerning eating. The factor mobility was excluded from the ADL groups, as this was assessed separately using data from other questions. The factors toileting and continence were excluded, as the answers were not consistent when compared with answers to questions concerning the same functions in other parts of the questionnaire. Symptoms were registered in a 23-item protocol originally used in studies of nursing homes, but modified to suit the situation in home nursing. The questionnaires also included questions about how long the patient had had home nursing, and whether the patient had had contact with any private doctor in specialised medical care. The questions were thus chosen so that the district nurses responsible for the care could answer them without additional patients assessments, either because the information would be well known to them since they were responsible for the nursing care or because the answers were based on assessment tools used in the regular care, such as that used for ADL. Questionnaires sent to the home-help providers focused on whether the patient had home help (Table 1 ). From the randomised one-third of selected patients (n = 158), we excluded 42, (16 declined to participate, and for ethical reasons we did not inquire why; ten had been discharged from home nursing, died or had been admitted to hospital; four could not participate for other reasons). Information about all patients from one district nurse was excluded (12 patients), since it was obvious that she had not understood the questions, leaving 116 patients (73%). Information could not be obtained from all sources for all patients. Visits to private doctors in specialised medical care and to private physiotherapists are not included, as they were not included in the official statistics. According to questionnaire responses from the district nurses, 11 patients saw private doctors in specialised medical care on a regular basis. We have no information about private physiotherapists. As the number of visits and care periods did not have a normal distribution, we used non-parametric statistical methods, i.e. medians and minimum – maximum. The Mann-Whitney test and χ2 were used to compare differences between groups. Conditional logistic regression was used to study whether personal, social or functional factors influenced the chance (expressed as odds ratio) that study patients had made visits to or had had inpatient specialised medical care during the study year. We used a case control design where patients with specialised care were cases and patients without this care were controls. The different factors were first tested by univariate logistic regression. The factors that showed significant influences were included in a multiple logistic regression model. One of these factors (home help) showed no significant influence when included in the model, and it was therefore excluded from the main effect model [ 18 ]. The factors without significant influence were also tested and included in the model, but no significant influence was found. The SPSS data-analysing system, version 11.0, was used for the analyses. The study was approved by the Research Ethics Committee at Huddinge University Hospital. This approval included the design of the study as well as the way informed consent was obtained from the individual patients. Results Eighty-nine of the 116 study patients (77%) lived alone, 86 patients (74%) were women and 41 (35%) received substantial assistance from family members according to the district nurses. Sixty-eight patients (65%) had home help. Patients who lived alone were less likely to have assistance from family members than those who lived with a relative (31% compared to 58%, p < 0.05), but on the other hand they were more likely to have home help (76% compared to 29%, p < 0.001). Patients who got help from family members were less likely to have home help (51% compared to 75%, p < 0.05). Specialised inpatient care More than half of the patients had been admitted to hospital during the study year (Table 2 ). Among these, the majority were admitted twice or more and spent more than three weeks in hospital. In all, more than 15 specialities were represented. Geriatric care represented almost 2/3 of all days in inpatient care, but the care by specialists at the different emergency hospitals involved more patients and a greater number of care periods. The most common specialities were general internal medicine (32 study patients and 29% of the care periods), surgery (10 study patients and 6% of the care periods), neurology (nine study patients and 5% of the care periods) and orthopaedics (seven study patients and 4% of the care periods). Almost all inpatient care periods (93%) were spent at the two emergency hospitals, the two geriatric hospitals, and the two local psychiatric wards located in or close to the study area, but six other emergency hospitals and one other geriatric hospital also provided care for these patients. The median values for all study patients were one care period and four days in care. The average number of care periods and days in inpatient care in Stockholm for the persons 75 to 84 years of age, and 85 years of age or older, were 0.6 of a care period and five days in inpatient care and 0.8 of a care period and seven days in inpatient care, respectively [ 19 ]. Specialised outpatient care During the study year a majority of the patients made outpatient visits to hospitals and outpatient departments (Table 3 ). In all, 22 different specialities were represented. Visits to departments of general internal medicine were most common (46% of the study patients, 22% of all visits), followed by visits to departments of surgery (26% of the study patients, 6% of the visits), orthopaedics (22% of the study patients, 6% of the visits) and ophthalmology (21% of the study patients, 9% of the visits). The visits in specialised care took place at eight different emergency hospitals, two geriatric hospitals, and two local psychiatric and one local ophthalmology department. However, 86% of the visits were to the two emergency hospitals located in or close to the study area. Of the 80 patients who made outpatient visits to hospitals 46 percent visited more than one speciality. The median value for visits to doctors in specialised care for all study patients was one visit. The average numbers of outpatient visits to doctors outside primary health care (excluding doctors in private practice) in Stockholm for persons 75–84 years of age and 85 years of age or older were 1.7 and 0.8, respectively [ 20 ]. The comprehensive view In the 104 cases where a family physician record was found, a visit to either their family physician or a doctor in outpatient specialised care, or both, was found for 95 patients (91%) (median 3 visits). Approximately one third (32 %) of the patients saw doctors from two or more specialities, GP care not included. Thirty-eight study patients (33%) had visited a physiotherapist or an occupational therapist (290 visits in all). Of these, 141 visits (49%) took place in primary health care and comprised 23 (20%) of the study patients (Table 3 ). Doctors and physiotherapists in private practice are not included. More detailed examples of the care picture on an individual level are given in Table 4 , where the problems and the medical care provided for two patients are described. The objective is to give a picture of what the care may look like from the perspective of the individual patient, as well as to present a picture of what conditions may be like for the different caregivers with the task of cooperating and coordinating the care. We have chosen one patient with three visits to specialised care, which was the median number among those who had specialised care, and one patient with many visits to specialised care. In both cases, it was possible to obtain data from all sources of information. Patients who did not see a family physician during the study year did not receive significantly more or less care from other caregivers (Table 5 ). Patients with visits to doctors in specialised care made significantly more visits to family physicians, saw the district nurses and other caregivers in specialised care more often, and also had more inpatient care. Patients who had been admitted to the hospital had more contacts with both doctors and other caregivers in outpatient specialised care, but not with the family physicians or the nurses in primary health care. The influence of personal, social and functional factors The influence of personal, social or functional factors on the chance of receiving specialised medical care was tested (Table 6 ). When the groups with different degrees of ADL dependency were tested, we found no difference between groups 1 (30 patients) and 2 (62 patients), but found that both groups 1 and 2 differed from group 3 (23 patients). Therefore groups 1 and 2 were combined into one group (1–2) and compared with group 3 in the model. Patients with severe ADL dependence (group 3) were less likely, and patients who had help from family members were more likely to make outpatient visits in specialised medical care. The same factors were tested to see if they influenced the chance that a patient had had inpatient care, but here we found no significant association. Discussion A majority of the patients with primary-care home nursing also received both inpatient and outpatient specialised medical care. Patients received care from home help, family members, family physicians, nurses in primary health care, and doctors and other caregivers in specialised medical care, thus providing a very complex picture. Many different hospitals and specialities were involved. Almost all patients had seen one or more doctors during the study year. Those who saw doctors in specialised care had more help from all categories of medical care. Patients with severely reduced ADL capacity were less likely, and patients with help from family members were more likely to have made outpatient visits in specialised medical care. The limitations of this paper include that personal, social and functional factors as well as symptoms were recorded by the district nurses and not reported directly by the patients, which means that this is second hand information, sometimes including an assessment. However, all of the participating district nurses had four and a half years of university education as is required, as well as many years of professional experience, which should ensure a sound basis for their assessments. Most of the personal and social factors were of the kind that are readily available concerning any patient and do not need assessments. The exception is participation of family members in the care, where the district nurse with her often longstanding contact with the patient and family is a suitable source of information. The functional factors in the Katz ADL index, mobility and cognitive function, are functions the nurses were used to assessing and reporting in their cooperation with hospitals and home help services. The only inconsistencies found concerned toileting and continence, which were consequently excluded. Further, symptoms could have been underestimated, as the district nurses would only be aware of them if they were obvious, or if the patient reported them, but they have only been used to describe patients, and not for any analysis. The study presents the medical care of patients with primary-care home nursing in one suburban area in one country. There are differences between the health-care systems and the informal and formal networks of care in different countries and sometimes also in different areas in the same country. This means that our conclusions are valid for patients with primary-care home nursing in this area; verifying whether they are valid in other areas would require further studies. However, as the study patients have the same type of problems described in other studies of patients with home nursing [ 21 , 22 ], their care needs are probably not different from those of patients receiving home nursing elsewhere. We have studied the situation in a city with easy access to near-by, specialised care, and with many different hospitals where patients are free to obtain medical services without a referral. This will have increased the number of hospitals and units involved in the care, as well as the number of outpatient visits [ 23 , 24 ]. This part of our results might be representative for other areas with easily accessible specialised care, but to confirm this would require further studies. The strengths of this paper include the following. A randomised third of a population is considered to provide a sufficient basis for conclusions about all patients receiving primary-care home nursing in a population, and a participation rate of 73 % is acceptable. The patients who were excluded were of the same age (median age 83, range 42–98 years) as the participants but might have had more severe conditions, as patients who had died or were admitted to hospital during the registration week were excluded. These patients probably did not receive less medical care than those who were included. Information about a few patients was missing from some sources. All practices had roughly the same proportion of drop-outs and missing data, and the reasons can be considered to be random. The results should then be valid for all patients with primary-care home nursing, in the study area. As the patients are similar to those with home nursing described in other studies, this study may serve as a reference for further investigation of the care of patients with home nursing. These patients who had primary-care home nursing also had many instances of specialised inpatient and outpatient medical care. However, their care did not differ substantially from that of the average population of comparable age in Stockholm County during 1996 [ 19 , 20 ]. This is somewhat surprising, as these patients with health problems could be expected to use more medical care. On the other hand, patients who regard a primary-care physician as their personal physician rather than a doctor in specialised care have lower total health-care expenditures [ 25 ], and patients who identify a doctor outside the hospital as their primary source of care are hospitalised less often [ 26 ]. Practice populations also have a major reduction in hospital care when a nurse is introduced into the primary-health-care team [ 27 ]. Since only patients with primary-care home nursing were included in the study and almost all (97%) received medical care from a family physician, this may explain why they did not use more specialised care than the average population. There was one group with significantly more medical care than the others, i.e. those patients who made outpatient visits to doctors in specialised care. The probable reason is that they had more severe medical conditions, but this is not possible to confirm in the present study. Inpatient care seemed to be strongly associated with more outpatient contacts in specialised care, but not with more contacts in primary health care. It is not possible to say whether this was the result of a greater need for specialised care, or the result of a tendency to keep the patients in specialised care [ 28 ]. Patients with no visits from a family physician received neither more nor less medical or nursing care elsewhere. The rest of the care was apparently not influenced by the low priority this was given by the family physicians. The care of an individual patient often included several caregivers from different organisations. For the individual patient who meets many different persons and goes to many different places, this means a lack of continuity. For this group of elderly patients with complicated medical problems, reduced mobility, reduced cognitive ability and reduced ADL-capacity, the risk that the individual caregiver does not have the proper information when decisions are made must be extremely great, especially taking into account the problems involved in the exchange of information between primary care and specialised care [ 28 ]. On an organisational level, many different caregivers make demands on systems and time for co-operation and the exchange of information. From a health care perspective the risk of inefficiency, low quality and/or high costs is evident, as at one end the same procedures might be done by several caregivers, while at the other end vital measures might not be performed because no one has the total picture. Several Swedish studies describe serious quality problems related to the medication of persons in home nursing, and these may partially reflect this situation [ 29 , 30 ], while other studies describe the lack of co-ordination and of an overall picture in the care of old persons with multiple problems [ 31 , 32 ]. In Sweden, the share of health care expenditures allocated to primary health care is often low (12 – 21 %) compared to other parts of Western Europe, where it is frequently 20 percent or more [ 33 ]. Further, this figure has not increased to any great extent since 1980, even though the inpatient hospital care has decreased dramatically [ 33 - 35 ]. The picture we report, where many patients remain in specialised care, is compatible with this economic situation. We found that functional and social factors influenced the chance of a patient having made outpatient visits to specialised medical care. Severe ADL dependence reduced the chance and receiving help from family members increased the chance. The fact that patients with severe ADL dependence do not make many outpatient visits is not surprising as reduced function limits the possibility to get to locations outside the home. The findings that help from family members increased the chance of having made outpatient visits to specialised medical care is not surprising either, in view of the age and functional problems of the patients. Relatives might be more observant concerning new symptoms, might easier establish contact and assist in transportation of the patients, than professional caregivers. Is the care organised so that old patients with multiple diseases and reduced functions need the help of a relative in order to get outpatient specialised medical care? Or do patients who get help from family members have more severe medical problems, even though there are no differences in primary-health-care diagnoses? Further studies are needed in this area. Conclusions The picture that evolves from our study is that the care of patients with home nursing is more complex than has previously been assumed. In parallel with their primary-care home nursing, all patients had contact with doctors, often from both primary and specialised medical care. The situation resembles that in a hospital ward, where many different caregivers and many different professions are involved in the care of the same patient, but without the ward's geographical and temporal unity. This renders it almost impossible for the individual patient to get continuity in all aspects of care, and the possibility of cost effective care of good quality is diminished. Patients with home nursing have complicated medical problems and both nurses and doctors are involved in their care, contrary to the previous belief that some patients are cared for by nurses alone. Instead, there seems to be one group of patients with home nursing who also need both primary and specialised care, and who have greater care needs than other patients with home nursing. That reduced function decreases and help from family members increases the chance of getting outpatient, specialised medical care raises questions concerning the medical care for patients with both medical and functional problems. Our conclusions are based on a study in one suburban area, and further studies are needed in order to confirm them. List of abbreviations used (if any) ADL Activities of Daily Living ENT Ear Nose and Throat Competing interests None declared. Authors' contributions SM designed and carried out the study, performed the statistical analysis, participated in the interpretation of results, wrote the initial draft of the manuscript and made subsequent revisions. AKF participated in the interpretation of results and made critical revisions of the manuscript. Both authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517924.xml |
521500 | Incidence, risk factors and mortality of nosocomial pneumonia in Intensive Care Units: A prospective study | To determine the frequency, risk factors and mortality of nosocomial pneumonia a prospective study was conducted in the intensive care units. In the study period, 2402 patients were included. The nosocomial pneumonia was defined according to the Centers for Disease Control Criteria. Overall, 163 (6.8%) of the patients developed nosocomial pneumonia and 75.5% (n = 123) of all patients with nosocomial pneumonia were ventilator-associated pneumonia. 163 patients who were admitted to the intensive care unit during the same period but had no bacteriologic or histologic evidence of pneumonia were used as a control group. The APACHE II score, coma, hypoalbuminemia, mechanical ventilation, tracheotomy, presence of nasogastric tube were found as independent risk factors. Crude and attributable mortality were 65% and 52.6%, respectively. The mortality rate was five times greater in the cases (OR: 5.2; CI 95%: 3.2–8.3). The mean length of stay in the intensive care unit and hospital in the cases were longer than controls (p < 0.0001). Patients requiring mechanical ventilation have a high frequency of nosocomial pneumonia. | Background Nosocomial pneumonia (NP) is the most frequent nosocomial infection in the intensive care units (ICU). The reported frequency varies with the definition, the type of hospital or ICU, the population of patients, and the type of rate calculated. In the recent studies, the incidence was reported as 6.8–27% [ 1 - 4 ]. In an one day point prevalence study in European ICUs, ICU-acquired pneumonia accounted for 46.9% of nosocomial infections [ 5 ]. The National Nosocomial Infections Surveillance (NNIS) system reported that NP accounts for 31% of all nosocomial infections in intensive care units [ 6 ]. The risk of pneumonia is increased in the intubated patients receiving mechanical ventilation (MV) and the ventilator associated pneumonia (VAP) frequencies varied between 7–70% in different studies [ 7 - 9 ]. NP developed at a rate of 0.9 cases per 1000 patient-days in non-ventilated patients versus rates of 20.6 cases per 1000 patient-ventilator-days and 14.8 cases per 1000 patient-days in patients who received any MV [ 10 ]. NP is also associated with high morbidity and mortality in ICUs. The increasing incidence of infections caused by antibiotic-resistant pathogens contributes to the seriousness of these infections. The mortality rate reaches to 20–50%, and also NP caused by high-risk pathogens ( Pseudomonas aeruginosa , Acinetobacter spp ., Stenotrophomonas maltophilia ) are associated with higher mortality [ 1 , 11 , 12 ]. Patients with NP, stay 1 to 2 weeks longer than those without NP and result in higher costs [ 13 ]. Studies on NP are mainly reported from the United States and European countries, whereas studies from around the world are missing. The aims of this study were to assess incidence, risk factors and mortality of NP in Eurasian intensive care units. Methods Between February 2001 and February 2002 a prospective study was conducted among intensive care units (ICU) patients of the Erciyes University Hospital. This university hospital is a teaching hospital and full time intensivists care the patients in ICUs. Patients from the surgical ICU (SICU) (24 beds), medical ICU (MICU) (9 beds) and burn unit (7 beds) were included. The SICU consist of 8 neurosurgical (NICU), 8 general surgery (GICU) and 8 cardiac surgery (CICU) beds. Patients older than 16 yr of age were included. The same infection control doctor collected data and intensivist reviewed the diagnosis of pneumonia. Data collection included physical examination findings, APACHE II scores on admission, consciousness, risk factors (intubation, MV, presence of nasogastric tube, enteral nutrition, tracheotomy), prior surgery, immunosuppression, prior antimicrobial and antacid or histamine type 2 (H 2 ) blocker therapy, clinical outcome, length of stay in ICU and in the hospital. 163 patients who were admitted to the ICU during the same period but had no bacteriologic or histologic evidence of pneumonia were used as a control group. In the ICUs infection control doctor collects active surveillance data routinely and empiric antibiotic therapy is directed at the most prevalent and virulent pathogens reported in these data. Appropriate antibiotic therapy included the administration of at least one antibiotic with in vitro activity against the bacterial pathogens isolated from the patient's respiratory secretions, as well as from blood and pleural fluid when applicable [ 14 ]. NP was considered when new and persistent (more than 48 h) pulmonary infiltrates not otherwise explained appeared on chest radiographs. Moreover, at least two of the following criteria were also required: 1) fever >38°C; 2) peripheral leukocyte count >10 000/mm 3 ; 3) purulent endotracheal secretions with a Gram stain showing one or more types of bacteria [ 15 ]. VAP was considered when its onset occurred after 48 h of MV and was judged not to have been incubated before starting MV [ 16 ]. Admission APACHE II score was used to determine the severity of the illness, and attributable mortality was registered, as were laboratory values, electrocardiogram, x-ray, and arterial blood gas values. Extra length of stay was calculated comparing the extra stay after onset of pneumonia in the cases and after a reference date (the mean value of the extra stay after onset of pneumonia in the cases) in the control group. Microbiology Giemsa stains of sputum samples were performed for all patients. Sputum samples, containing more than 25 polimorphonuclear leukocyte (pnl) and less than 10 (×100) epithel were classified as purulent. If necessary, samples were obtained by nasotracheal aspiration. In that case, samples containing more than 10 pnl (×1000) were defined as purulent. Quantitative cultures of all purulent samples were performed using standard methods. Susceptibility testing was performed by disc diffusion method. In the absence of an alternative diagnosis a bronchoalveolar lavage was performed. In some case, pleural fluid was obtained by thoracentesis and examined for cell count, smear, Gram- and Giemsa-staining and microbiological culture. Statistical Analysis All data were evaluated using SPSS. Parameters were compared using univariate and multivariate logistic regression and chi-square tests. Student t test was used to compare the extra length of stay. Data were given as mean ± SD and a p-value of <0.05 was accepted as significant. Results During the study period, 2402 patients were admitted to the ICUs. Distribution of patients by ICU and length of stay in the ICU are shown in table I . Overall, 163 (6.8%) of the 2402 patients developed NP; 105 (5.8%) SICU- and 58 (11.7%) MICU-patients. The demographics of the NP patients and control group are shown in table II . The percentage of NP in NICU, GICU and CICU were 7.8%, 6.3% and 1.2%, respectively. During the study period no burn unit patient developed NP. The incidence of NP in MICU-patients was much higher than in SICU-patients (X 2 = 19.7, p < 0.0001). Length of stay in the MICU was significantly higher than in the SICU, 21.3 ± 21.4 versus 16.2 ± 8.8 days, respectively (p < 0.05). Characteristics of patients who developed NP are shown in table III . Table I Numbers of patients and length of stay in ICU ICU No. of beds Total patient (n) Total length of stay (d) Mean length of stay (d) SICU 24 1806 5594 3.1 NICU 8 767 2213 2.9 GICU 8 636 2132 3.4 CICU 8 403 1249 3.1 MICU 9 495 2086 4.2 Burn Unit 7 111 1765 15.9 Total 40 2402 9445 3.9 Table II Demographic Factors of Study Patients* NP patients (n = 163) Control (n = 163) t p Age 53.30 ± 16.05 51.50 ± 16.87 0,985 >0,05 Admission APACHE II 10.86 ± 3.42 10.18 ± 4.56 1,526 >0,05 Gender 0,454 >0,05 Male 98 (60) 102 (63) Female 65 (40) 61 (37) Diabetes mellitus 22 (14) 32 (20) 1,49 >0,05 COPD 36 (22) 11 (7) 4,027 <0.001 Cardiovascular disease 31 (19) 19 (12) 1,848 >0,05 Uremia 36 (22) 12 (7) 3,823 <0.001 Neoplasia 29 (18) 17 (10) 1,914 >0,05 Immunosuppressive therapy 6 (4) 3 (2) 1,013 >0,05 Coma 143 (88) 23 (14) 19,58 <0,001 Trauma 35 (22) 85 (52) 6,038 <0,001 * Data presented as mean ± SD or No. (%) Table III Characteristics of patients Characteristics MICU NICU GICU CICU Total Age (mean ± SD) 52.9 ± 15.1 50.25 ± 17.57 58.28 ± 14.38 55.00 ± 14.68 53.3 ± 16.1 Admission APACHE II, (mean ± SD) 11.2 ± 3.3 10.43 ± 3.12 11.03 ± 3.67 11.20 ± 6.38 10.9 ± 3.4 NP APACHEII, (mean ± SD) 16.2 ± 5.1 14.73 ± 3.94 16.30 ± 4.79 14.80 ± 6.37 15.6 ± 4.7 Length of stay in ICU (d, mean ± SD) 21.3 ± 21.4 14.42 ± 8.87 19.47 ± 8.20 12.20 ± 3.96 18.0 ± 14.7 Length of hosp. stay (d, mean ± SD) 25.0 ± 22.5 21.60 ± 11.93 24.78 ± 12.13 18.40 ± 8.26 23.5 ± 16.4 Overall, 17% of all patients requiring MV (n-724) developed VAP. Thereby, VAP accounts for 75.5% (n = 123) of all patients with NP (n = 163) during the study period (OR: 5,4; 95% CI: 3,36–8,75; p < 0,001) (Table IV ). Mechanical ventilation was more frequently used in MICU patients than SICU patients (X 2 = 6.6, p < 0.01). Consequently, the incidence of VAP was higher for MICU- than SICU-patients (X 2 = 29.2, p < 0.0001). Furthermore, the length of ventilation was higher for patients admitted to MICU (6.3 ± 4.0) than SICU (5.1 ± 3.7), but the difference was not statistically significant. Table IV Rate of VAP in ICUs ICU No. of patients required MV No. of patients with VAP (%) SICU 550 72 (13.1) NICU 141 38 (27.0) GICU 157 31 (19.7) CICU 252 3 (1.2) MICU 163 51 (31.3) Burn unit 11 0 (0) Total 724 123 (17.0) During the study period patients received 3128 ventilation days, with an average duration of 11.3 ± 10.0 days per ventilated patient. The device-related incidence rate for VAP was 39.3/1000 ventilation days. The incidence per 1000 ventilation days was 41.9 in SICU, 36.6 in MICU, 66.0 in NICU, 38.0 in GICU, and 9.1 in CICU patients. The mean onset day of NP after MV was 4.2 ± 3.9 days. Univariate analysis suggested the following risk factors for the development of NP: the APACHE II score, coma, COPD, uremia, hypoalbuminemia, MV, tracheotomy, enteral feeding, presence of nasogastric tube and previous treatment with broad-spectrum antibiotic (Table V ). However, multivariate logistic regression showed that the APACHE II score (OR: 1.23; 95% CI: 1.13–1.33), coma (OR: 2.83; 95% CI: 1.24–6.47), hypoalbuminemia (OR: 2.23; 95% CI: 1.01–4.93), MV (OR: 3.35; 95% CI: 1.71–6.56), tracheotomy (OR: 6.03; 95% CI: 1.36–26.76) and presence of nasogastric tube (OR: 2.68; 95% CI: 1.33–5.41) were significant independent predictive factors for the development of NP. Table V Results of univariate analysis of potential risk factors for NP Risk Factors OR 95% Confidence Interval p Age 1.0 0.99 – 1.02 ns APACHE II 1.3 1.22 – 1.38 <0.001 Coma 6.6 3.75 – 11.48 <0.001 Trauma 1.7 0.93 – 2.97 ns COPD 3.9 1.91 – 8.01 <0.001 Diabetes mellitus 0.6 0.35 – 1.16 ns Central nervous system disorder 1.1 0.71 – 1.77 ns Uremia 3.6 1.78–7.14 <0.001 Hypoalbuminemia 3.3 1.99–5.61 <0.001 Mechanical ventilation 5.4 3.36–8.75 <0.001 Tracheotomy 12.5 3.75–41.89 <0.001 Enteral feeding 13.9 6.38–30.13 <0.001 Presence of nasogastric 6.3 3.89–10.18 <0.001 Previous antibiotic treatment 3.3 1.94–5.62 <0.001 Immunosupressive therapy 2.0 0.50–8.29 ns Antacids or H 2 antagonist therapy 0.6 0.25–1.36 ns Thoracoabdominal surgery 1.0 0.63–1.69 ns ns: non-significant 187 pneumonia episodes were observed during the study period, resulting in the isolation of 257 microorganisms. The most commonly isolated pathogens were Gram-negative bacteria (85.6%). Among these pathogens, A. baumannii (29.6%), P. aeruginosa (20.6%), Klebsiella pneumoniae (14.4%) were the most common. Empiric antibiotic therapy was based on previous surveillance cultures and the Gram stain results. Therapy was adjusted according to the reports of susceptibility testing. Crude and attributable mortality were 65% and 52.6%, respectively. The mortality in patients without NP was 26.4% (Table VI ). The risk of death was five times higher for patients with NP (OR: 5.2; 95% CI: 3.2–8.3; p < 0,001). The mortality rates were high in high risk pathogens (Table VII ). The appropriateness of the empiric therapy did not contribute to increased mortality (Table VIII ). Table VI Comparisons of outcomes between NP and control group NP group n (%) Control group n (%) X 2 p Mortality 106 (65.0) 43 (26.4) 47.5 <0.0001 Improve 57 (35.0) 120 (73.6) Attributable mortality 52.6% Table VII Mortality rates in high risk pathogens Microorganism Mortality/Total (%) Gram negative 61/97 (62.9) A. baumannii 31/42 (73.8) P. aeruginosa 19/28 (67.9) Gram positive 10/15 (66.7) MRSA 10/14 (71.4) Table VIII Appropriateness of empiric therapy and mortality Appropriate n (%) Inappropriate n (%) X 2 p Survive 43/121 (35.5) 14/42 (33.3) 0.005 >0.05 Death 78/121 (64.5) 28/42 (66.7) The mean length of stay in the ICU and hospital for the patients with NP were 18.04 ± 14.74 days and 23.49 ± 16.44 days, respectively. The mean length of stay in the ICU and hospital for the control group 3.10 ± 3.03 and 9.64 ± 5.08 days, respectively. This difference was statistically significant (p < 0.0001). The extra stay in the control group was 4.36 ± 3.87 and 17.04 ± 14.17 in the patients (p < 0.001). Discussion The incidence of NP was reported different in different studies, which may be justified by the presence of different populations with variable ages, underlying diseases, and other associated risk factors. Incidence ranges from 6.8 to 27% [ 1 - 4 ] and also in this study it was 6.8%. Development of NP varies according to the different type of ICUs. Craven et al. [ 17 ] reported that the rate of pneumonia was higher in MICU but the difference was not significant. In the present study, the rate of NP and VAP was significantly higher in MICU than SICU, possible due to the differences in the proportion of patients that needed MV and the duration of MV. MV increases the risk of NP by 3- to 10-fold [ 1 , 18 - 23 ], resulting in an VAP incidence of 7 to 70% [ 7 - 9 ]. Generally, the duration of mechanical ventilation increases the risk of pneumonia. Cook et al. [ 24 ] reported that the rate of VAP increased 3% per day in the first week of ventilation, 2% per day in the second week, and 1% per day in the third week. In this study, 75.5% of the cases with NP occurred in ventilated patients. From 724 patients who required MV 123 (17%) developed VAP. Accordingly, patients on MV had a 3-fold higher risk to develop NP than the non-ventilated patients. Consequently, the use of non-invasive MV should be preferred whenever possible, since it has lower rates of nosocomial infections [ 25 - 27 ]. Coma was described as another important risk factor for NP. In these patients, local defense mechanisms of the respiratory airway are altered, allowing microorganisms to better attach to and colonize the mucosal surface. Furthermore, depression of the level of consciousness significantly increases the chance of aspiration, and as a result development of NP [ 3 , 28 ]. In our study, comatose patients had a 2-fold increased risk of NP. The causative agents of NP differ by the study population and diagnostic techniques but generally Gram-negative bacteria are the most common ones [ 3 , 4 , 28 - 33 ]. Colonization of the oropharynx, trachea or stomach with Gram-negative pathogens has been identified as a risk factor for NP [ 15 , 31 ]. Also in our study, the most common pathogens were Gram-negative bacteria. Furthermore, prior antibiotic therapy and COPD, leading to colonization with Gram-negative aerobic pathogens, were reported to be risk factors for the development of NP [ 11 , 28 , 30 , 34 ]. In our patient population, univariate analysis suggested that previous antibiotic treatment and COPD increased the risk of pneumonia, but interestingly they were not independent risk factors in multivariate analysis. Furthermore, the presence of a naso-gastric tube was found to be a risk factor in our study population. Naso-gastric tubes impair the function of the gastroesophageal sphincter and increase the risk of maxillary sinusitis, oropharyngeal colonization and reflux, all of which may lead to migration of bacteria [ 35 ]. Accurate evaluation of nutritional status and early initiation of enteral feeding is important in ICUs patients and can aid to preserve the gastrointestinal epithelium and prevent bacterial colonization. However, it may also increase the risk of gastric distention, colonization, aspiration, and pneumonia. Though, to reduce the risk of NP, it is important to avoid unnecessary enteral nutrition [ 30 ]. In univariate analysis, we found enteral feeding as a risk factor, but in multivariate analysis it was not an independent risk factor. For a long time it was assumed that increased gastric pH levels e.g. after the use of antacids, would allow Gram-negative microorganisms to multiply in the stomach, and consequently lead to an increased rate of NP. Our study results confirm what was reported by George et al. [ 36 ], namely that the use antacids or H 2 antagonists did not increase the risk of NP. In the literature, tracheotomy is described as a significant risk factor for NP. Bronchial colonization during the procedure and (prolonged) continuation of sedation after the procedure will furthermore increase the occurrence of NP [ 28 ], a fact that was also seen in our patients. Patients with tracheotomy had a 7-fold increased risk of NP. The role of advanced age and high APACHE II scores as risk factors of NP are still under discussion. While Kollef et al. [ 37 ] report them as significant risk factors, earlier investigations do not support this [ 1 , 30 ]. In our present study, the APACHE II score was a significant risk factor for the development of NP; suggested that the severity of the general condition of the patient was important. Besides, uremia was found as a risk factor in univariate analysis. Patients with NP have a significantly higher morbidity and mortality [ 12 , 35 , 38 ]. Heyland et al. [ 38 ] reported the crude mortality rate of VAP 23.7% and an attributable mortality rate 32.3%. However, numerous studies have demonstrated that severe underlying illness predisposes patients in the ICU to the development of pneumonia, and their mortality rates are, as a result, high. Survival in patients with NP primarily by the degree of severity of illness at the time of diagnosis [ 23 , 39 , 40 ]. On the other hand, this does not exclude the possibility that certain subgroups of patients, such as patients with VAP caused by antibiotic resistant bacteria may have had extra attributable mortality rate [ 1 ]. In our study, the crude mortality rates for cases and controls were 65.0% and 26.4%, respectively and the mortality rates were highest in high risk pathogens. The mortality rate was five times greater in cases and attributable mortality of NP was 52.6%. Recent clinical investigations suggest that patients receiving inappropriate initial therapy have a greater mortality rate compared to patients receiving antibiotics to which the isolated bacteria were sensitive. However, in this study there was no statistically difference between the mortality rates of the patients who received appropriate and inappropriate initial therapy. As a result of the increased morbidity, patients with VAP remain hospitalized for 4–17 days longer than controls [ 35 - 38 ]. This observation was confirmed in the present study. The incidence of NP and VAP in MICU were significantly higher than in SICU patients and consequently the length of stay in the MICU was significantly higher than in the SICU. In conclusion, NP is a major cause of morbidity and mortality in ICU patients. Especially patients on mechanical ventilation are at high risk. Studies determining the impact of "old" and "new" risk factors of NP should repeatedly be performed in order to effectively guide the implementation of preventive measures methods. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521500.xml |
509298 | Unraveling the Molecular Basis for Regenerative Cellular Plasticity | Identifying the molecular basis for the impressive regenerative capacities of some organisms may help us to devise effective methods for enhancing regeneration in mammals | The regeneration of lost body parts and injured organs has captured the human imagination since the time of the ancient Greeks. The deep-seated roots of this early fascination can be seen in Greek mythology. The many-headed Hydra nearly defeated the hero Heracles by growing two new heads for every one that Heracles cut off, and the liver of Prometheus, devoured by a ravenous eagle each night, regenerated every morning. Aristotle, who lived from 384–322 BC, noted that the tails of lizards and snakes, as well as the eyes of swallow-chicks, could regenerate ( Aristotle 1965 ). This fascination became a legitimate area of scientific inquiry in 1712, when the French scientist René-Antoine Ferchault de Réaumur published his seminal work on crayfish limb and claw regeneration ( Réaumur 1712 ). Soon thereafter, several other prominent scientists of the eighteenth century, including Abraham Trembley, Charles Bonnet, Peter Simon Pallas, and Lazzaro Spallanzani, discovered remarkable regenerative abilities in a variety of organisms. Hydra, earthworms, and planarians could regenerate their heads and tails ( Pallas 1766 ; Lenhoff and Lenhoff 1986 ); salamanders could regenerate their limbs, tails, and jaws; premetamorphic frogs and toads could regenerate their tails and legs; slugs could regenerate their horns; and snails could regenerate their heads ( Spallanzani 1769 ). This last discovery caused quite a stir in eighteenth-century France, leading to an “unprecedented assault” on snails as both naturalists and the general public participated in the quest for scientific knowledge by reproducing Spallanzani's intriguing results ( Newth 1958 ). Stem Cells Versus Dedifferentiation During the nineteenth century and for most of the twentieth century, regeneration research primarily focused on the phenomenology of regeneration and its cellular basis. Many important discoveries were made during this period, which led in part to the general conclusion that progenitor cells are required for most regenerative processes. However, the origin of these progenitor cells varies between regenerating systems. In some cases, such as the regeneration of skin, blood, muscle, and bone in mammals and the replacement of lost tissues in the flatworm planarian, the progenitor cells pre-exist as reserve cells or stem cells that only need to be activated in response to injury or tissue depletion. In other cases, the progenitor cells can be created de novo through a process in which fully differentiated cells reverse their normal developmental processes and revert to proliferating progenitor cells. This latter process, known as cellular dedifferentiation, is especially prominent in vertebrates with exceptional regenerative abilities, such as salamanders. For example, during salamander limb regeneration, cells from muscle, bone, cartilage, nerve sheath, and connective tissues participate in the dedifferentiation process to form a pool of proliferating progenitor cells known as the regeneration blastema ( Figure 1 ) ( Chalkley 1954 ; Bodemer and Everett 1959 ; Hay and Fischman 1961 ; Wallace et al. 1974 ; Lo et al. 1993 ; Kumar et al. 2000 ). It has not yet been determined whether pre-existing stem cells or reserve cells also contribute to the pool of progenitor cells—nor whether the blastemal cells are multipotent (capable of differentiating into multiple cell types), are committed to a particular cell lineage, or are a mix of multipotent and committed progenitor cells. Regardless, these blastemal cells will later redifferentiate to form all the internal tissues of the regenerated limb other than the peripheral nerve axons. This extraordinary degree of cellular plasticity distinguishes those vertebrates that can replace entire anatomical structures, such as limbs, from vertebrates with more limited regenerative abilities. Figure 1 Dedifferentiation of Limb Cells During Salamander Limb Regeneration Brown nuclei are a result of BrdU incorporation during DNA synthesis, and therefore mark cells that are progressing through the cell cycle. Abbreviations: e, epidermis; d, dermis; m, muscle; b, bone; bl, blastema; aec, apical epithelial cap. (A) Unamputated right forelimb of a newt and coronal section of the stylopodium. The only cells actively synthesizing DNA are those in the basal layer of the epidermis (bone marrow cells also actively synthesize DNA in the unamputated limbs but are not shown here). Note the long myofibers in the nonregenerating newt limb and the distant spacing between the muscle nuclei. (B) Seven-day limb regenerate and coronal section of the distal regenerating tip. Note that the muscle cells have lost their normal architecture and that the nuclei are more closely spaced and have begun to synthesize DNA. (C) Twenty-one-day limb regenerate and coronal section of the distal regenerating tip. The nuclei of the blastema are spaced closely together, and many nuclei are actively synthesizing DNA. The bone is also being broken down in the vicinity of the blastema. The public has recently exhibited a renewed interest in regeneration research, due in large part to stem cell research, which has provided promising avenues for the field of regenerative medicine. In addition, celebrities such as Christopher Reeve and Michael J. Fox have given a human face to the many people who could benefit from effective regenerative therapies. The political, ethical, and religious controversies surrounding the use of human embryonic stem cells for therapeutic purposes have only served to increase the public's awareness of the promising potential of regenerative medicine. But this interest in using scientific knowledge to enhance the regenerative capacity in humans is not new. Spallanzani closed his 1768 monograph on regeneration, An Essay on Animal Reproductions , with a series of questions— which, except for the antiquated language, could be asked by citizens of the twenty-first century: But if the abovementioned animals, either aquatic or amphibious, recover their legs, even when kept on dry ground, how comes it to pass, that other land animals, at least such as are commonly accounted perfect, and are better known to us, are not endued with the same power? Is it to be hoped they may acquire them by some useful dispositions? [A]nd should the flattering expectation of obtaining this advantage for ourselves be considered entirely as chimerical? Although most of the current interest in regenerative medicine focuses on the potential benefits of either embryonic or adult stem cells, there are several investigators who are now taking an entirely different approach to the problem. These researchers think that although stem cells may offer some benefits in the relatively near future, a more comprehensive approach will be required to meet all of our regenerative needs. To achieve this goal, they must first learn how nature has already solved the problem of regeneration and then use this information to enhance the regenerative capacity in mammals. These studies seek to understand the biology of regeneration, especially the cellular and molecular mechanisms that govern regenerative processes. The experimental systems range from the unicellular protozoa to complex vertebrates, such as salamanders and mice. The Molecular Biology of Regeneration With the technological advances that followed the advent of molecular biology, researchers acquired the basic tools to begin to unravel the molecular basis for cellular plasticity and regeneration. However, progress in this arena has been slow, given that most organisms with marked regenerative abilities are not yet amenable to routine genetic manipulation. Recent advances, such as the application of mutagenic screens to study fin regeneration in zebrafish ( Johnson and Weston 1995 ; Poss et al. 2002b ) and the application of RNAi knockdown technology to study regeneration in planarians ( Sanchez Alvarado and Newmark 1999 ; Newmark et al. 2003 ), are quite promising and could largely ameliorate this deficiency. Nevertheless, results from several recent studies have converged on a set of genes that appear to play an important role in regeneration, and evidence is accumulating that suggests some of these genes may function to control regenerative cellular plasticity. Three such genes are Msx1, BMP4 , and Notch1 . These genes encode, respectively, a transcriptional repressor, a signaling ligand, and a signaling cell surface receptor. Numerous studies over the past three decades have shown that mammals, including humans, can regenerate their digit tips provided the amputation plane is distal to the terminal phalangeal joint ( Douglas 1972 ; Illingworth 1974 ; Borgens 1982 ; Singer et al. 1987 ). However, Msx1 -deficient mice exhibit impaired fetal digit-tip regeneration, a phenotype that can be rescued in ex vivo cultures in a dose-dependent manner by application of exogenous BMP4 ( Han et al. 2003 ). Recently, it has been demonstrated that Xenopus tadpoles are unable to regenerate their tails during a refractory period of development between stages 45 and 47 ( Beck et al. 2003 ). If tails are amputated during this refractory period, genes that are normally expressed during the early stages of tadpole tail regeneration, such as BMP4, Msx1 , and Notch-1 , are not expressed. However, transgenic frogs carrying a hyperactive form of Msx1 or constitutively active ALK3 (a receptor for BMP4) are able to regenerate their tails during the refractory period. Transgenic frogs carrying a constitutively active Notch-1 receptor will regenerate their notochords and spinal cords but exhibit little or no muscle regeneration, suggesting that Notch-1 signaling alone cannot rescue complete regenerative capacity in frog tadpoles ( Beck et al. 2003 ). Results from expression studies in a variety of organisms are consistent with these in vivo gene function studies. Msx genes are upregulated in regenerating salamander limbs and regenerating zebrafish fins and hearts ( Simon et al. 1995 ; Poss et al. 2002a ; Raya et al. 2003 ), while notch-1b and its ligand, deltaC , are upregulated during zebrafish heart and fin regeneration ( Raya et al. 2003 ). Msx1 and Cellular Plasticity Although these functional and expression studies indicate that Msx1, Bmp4 , and Notch-1 are important for a variety of regenerative processes, they do not address the mechanism by which these genes exert their effects. However, several in vitro studies suggest that Msx1 may be involved in regulating cellular plasticity. Ectopic expression of Msx1 can inhibit the differentiation of a variety of mesenchymal and epithelial progenitor cell types ( Song et al. 1992 ; Hu et al. 2001 ), suggesting that this gene may play a role in maintaining cells in an undifferentiated state. Furthermore, Msx1 may be functioning not only to prevent differentiation of progenitor cells but also to induce dedifferentiation of cells that have already differentiated. Ectopic expression of Msx1 in mouse myotubes (differentiated muscle cells that are multinucleated and are able to contract), coupled with serum stimulation, can induce these multinucleated cells to reduce their levels of myogenic proteins and undergo a cell cleavage process that produces proliferating mononucleated cells (a process known as cellularization) ( Odelberg et al. 2000 ). Clonal populations of these dedifferentiated cells can redifferentiate into cells expressing markers for cartilage, fat, and bone cells, as well as myotubes. These results suggest that the combination of ectopic Msx1 expression and serum stimulation can induce differentiated muscle cells to dedifferentiate into proliferating multipotent progenitor cells. Given this degree of cellular plasticity, it is not surprising that Msx1 can also induce muscle progenitor cells, known as myoblasts, to dedifferentiate to multipotent progenitor cells ( Odelberg et al. 2000 ). Cellularization of myotubes and myoblast dedifferentiation can also be induced by at least two synthetic trisubstituted purines. Myoseverin is a trisubstituted purine that binds to and disassembles microtubules, leading to the cellularization of multinucleated myotubes ( Rosania et al. 2000 ). The resulting mononucleated cells proliferate when stimulated with serum and redifferentiate into myotubes following serum starvation. A second trisubstituted purine, reversine, induces myoblasts to dedifferentiate into progenitor cells with adipogenic and osteogenic potential ( Chen et al. 2004 ). Therefore, reversine and Msx1 appear to have a similar effect on mouse myoblasts, although no reports have yet addressed whether reversine might induce dedifferentiation of multinucleated myotubes. In this issue of PLoS Biology , Kumar et al. (2004) present data linking Msx1 function to microtubule disassembly during the process of salamander myofiber cellularization and fragmentation (myofibers are formed from myotubes and represent the completely mature form of the differentiated skeletal muscle cell). Their results suggest that Msx1 expression induces microtubule disassembly, which then leads to myofiber cellularization or fragmentation. If Msx1 function is markedly reduced in salamander myofibers by preventing the efficient synthesis of the Msx1 protein, cellularization or fragmentation of the myofiber is inhibited, suggesting that Msx1 is required for this process. Thus, this study complements previous work ( Odelberg et al. 2000 ) showing that ectopic Msx1 expression, coupled with serum stimulation, is sufficient to induce cleavage, cellularization, and dedifferentiation of mouse myotubes. The two studies point to an essential role for Msx1 in regenerative cellular plasticity and when combined with previous in vivo studies, raise the possibility that BMP or Notch signaling might also play a role in this process. Results from these and other similar studies are beginning to give researchers a glimpse into the molecular mechanisms that control regeneration and cellular plasticity. With the new tools available to identify candidate genes and assess their function, the next few decades appear promising for scientists engaged in regeneration research. Elucidating the molecular basis for regeneration may prove to be an essential step in devising effective methods for enhancing regeneration in mammals and may well usher in a golden era for regenerative medicine. Accession Numbers The Mouse Genome Informatics ( http://www.informatics.jax.org/ ) accession numbers of the genes discussed in this paper are ALK3 (MGI: 1338938), BMP4 (MGI: 88180), Msx1 (MGI: 97168), and Notch1 (MGI: 97363). The GenBank ( http://www.ncbi.nih.gov/GenBank/ ) accession numbers of the genes discussed in this paper are deltaC (NM 130944), notch1b (Y10352), Ambystoma mexicanum Msx1 (AY525844), Danio rerio msxb (U16311; partial sequence), D. rerio msxc (NM 131272), Homo sapiens ALK3 (Z22535), and Mus musculus ALK3 (Z23154). | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC509298.xml |
533886 | On the potential role of glutamate transport in mental fatigue | Mental fatigue, with decreased concentration capacity, is common in neuroinflammatory and neurodegenerative diseases, often appearing prior to other major mental or physical neurological symptoms. Mental fatigue also makes rehabilitation more difficult after a stroke, brain trauma, meningitis or encephalitis. As increased levels of proinflammatory cytokines are reported in these disorders, we wanted to explore whether or not proinflammatory cytokines could induce mental fatigue, and if so, by what mechanisms. It is well known that proinflammatory cytokines are increased in major depression, "sickness behavior" and sleep deprivation, which are all disorders associated with mental fatigue. Furthermore, an influence by specific proinflammatory cytokines, such as interleukin (IL)-1, on learning and memory capacities has been observed in several experimental systems. As glutamate signaling is crucial for information intake and processing within the brain, and due to the pivotal role for glutamate in brain metabolism, dynamic alterations in glutamate transmission could be of pathophysiological importance in mental fatigue. Based on this literature and observations from our own laboratory and others on the role of astroglial cells in the fine-tuning of glutamate neurotransmission we present the hypothesis that the proinflammatory cytokines tumor necrosis factor-α, IL-1β and IL-6 could be involved in the pathophysiology of mental fatigue through their ability to attenuate the astroglial clearance of extracellular glutamate, their disintegration of the blood brain barrier, and effects on astroglial metabolism and metabolic supply for the neurons, thereby attenuating glutamate transmission. To test whether our hypothesis is valid or not, brain imaging techniques should be applied with the ability to register, over time and with increasing cognitive loading, the extracellular concentrations of glutamate and potassium (K + ) in humans suffering from mental fatigue. At present, this is not possible for technical reasons. Therefore, more knowledge of neuronal-glial signaling in in vitro systems and animal experiments is important. In summary, we provide a hypothetic explanation for a general neurobiological mechanism, at the cellular level, behind one of our most common symptoms during neuroinflammation and other long-term disorders of brain function. Understanding pathophysiological mechanisms of mental fatigue could result in better treatment. | Background Mental fatigue with reduced capacity for attention, concentration, and learning, as well as subsequent disturbance of short-term memory, is a common symptom in diseases with general or patchy neuroinflammation, such as multiple sclerosis (MS) and neurodegenerative diseases, such as Ahlzheimer's and Parkinson's diseases [ 1 - 6 ]. The mental fatigue often appears prior to other more prominent mental, cognitive, or physical symptoms from the nervous system in these diseases. Mental fatigue is also common during the rehabilitation after meningitis or encephalitis (postinfectious mental fatigue), stroke or brain trauma (posttraumatic mental fatigue), being especially troublesome when major neurological symptoms have disappeared and the patient is on his way back to work. According to the International Classification of Diseases, 10th revision (ICD-10), mental fatigue is covered by the diagnoses "mild cognitive disorder" or "neurasthenia" and according to the Diagnostic and Statistical Manual of Mental Disorders , 4th edition [ 7 ], mental fatigue is included in the group of "mild neurocognitive disorders". According to the diagnostic classification by Lindqvist and Malmgren [ 8 ], mental fatigue is one of the symptoms of the "astheno-emotional syndrome". Although mental fatigue is not exactly the same as depression, where the patient has a feeling of not being able to do anything, there are overlaps and both disorders have behavioral manifestations such as reduction in motivation that would appear similar in animal models, where affective state is either irrelevant or difficult to assess. Even the "sickness behavior" [ 9 ] contains a component of fatigue. Mental fatigue is also prominent after sleep deprivation. In addition to the fatigue itself, the patient with mental fatigue often suffers from loudness and light sensitivity, irritability, affect lability, stress intolerance, and headaches [ 8 ]. Mental fatigue appears as a decreased ability to intake and process information over time. Mental exhaustion becomes pronounced when cognitive tasks have to be performed for longer time periods with no breaks (cognitive loading). Often, the symptoms are absent or mild in a relaxed and stress-free environment. To explore the possible cellular neurobiology of mental fatigue, we start by looking at some components important for information intake and processing within the central nervous system, namely glutamate neurotransmission, and focus on the clearance of extracellular glutamate ([Glu] ec ). Glutamate neurotransmission is indispensable for information intake and processing within the central nervous system Glutamate neurotransmission is crucial in information intake and information processing within the brain [see [ 10 ]]. Glutamate transmission is also indispensable for long-term potential (LTP) formation, the cellular correlate to memory formation [see [ 11 ]]. In brain, the [Glu] ec has to be maintained at approximately 1–3 μM in order to assure a high precision (high signal-to-noise ratio) at normal glutamate neurotransmission [ 12 ] and also, to avoid excitotoxic actions of glutamate on neurons. The clearance of glutamate from the extracellular space is achieved by high-affinity, sodium (Na + )-dependent electrogenic uptake transporters. The glutamate aspartate transporter (GLAST) and glutamate transporter 1 (GLT-1) are most abundantly located on astrocytes surrounding synapses of glutamate-bearing neurons [ 13 ]. In fact GLAST and GLT-1 have different expression patterns. GLAST is the major transporter for glutamate uptake during development while expression of GLT-1 increases with the maturation of the nervous system. Glutamate transporter 1 expression seems to follow the formation and maturation of synapses and especially synaptic activity [ 14 ]. Even more convincing for the role of astroglia in keeping the [Glu] ec low, it has been demonstrated with knockout techniques in rats that loss of GLT-1 or GLAST produces elevated [Glu] ec and neurodegeneration characteristic of excitotoxicity, while the loss of neuronal glutamate transporter does not elevate [Glu] ec [ 15 ]. Regulation of astroglial glutamate transporter capacity – role of proinflammatory cytokines A large number of factors have been shown to affect the activity and expression of the glutamate transporters GLT-1 and GLAST. For example, GLT-1 is stimulated by phosphorylation by protein kinase C (PKC), while GLAST is inhibited by PKC at a non-PKC consensus site [ 16 ]. The synthesis of GLT-1 has been shown to be stimulated by factors acting via receptor tyrosine kinases and pathways dependent on phosphatidylinositol-3-kinase (PI3K) and the nuclear transcription factor NFκB. One mechanism of regulation of GLT-1 is related to formation of cysteine bridges. Glutamate transporter 1 contains cysteines that are sensitive to oxidative formation of cysteine bridges. Oxidative species such as hydrogen peroxide can readily oxidize the functional sulfhydryl groups of cysteines, to form disulfide bridges which exert an inhibitory effect towards glutamate transports [ 17 ]. Examples of factors or altered conditions that impair astroglial glutamate transport are arachidonic acid, lactic acid, cytokines, and leukotrines, nitric oxide (NO), β-amyloid protein, peroxynitrate, and glucocorticoids. The altered conditions could be disturbed energy metabolism with lowering of adenosine triphosphate (ATP) levels or lowering of pH. Notable is the finding that many of these substances or conditions also decrease astroglial gap junction communication and even disintegrate the BBB, thus impairing the astroglial support of the glutamate neurotransmission [for references, see [ 18 ]]. Proinflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin (IL)-1β and IL-6 have since long been known to impair astroglial glutamate uptake even if the mechanisms are not fully understood. The inhibitory function of TNF-α was established as early as the 1990s, when TNF-α was shown to inhibit astroglial glutamate uptake [ 19 ]. Hu and coworkers [ 20 ] reported a dose-dependent inhibition of astrocyte glutamate uptake by a mechanism involving nitric oxide (NO). In a study from 2001, Liao and Chen [ 21 ] demonstrated that TNF-α potentiates glutamate-mediated oxidative stress, which results in a decrease in glutamate transporter activity. Recently, Wang and coworkers [ 22 ] showed a reduced expression of GLT-1 and GLAST, and also, an impaired glutamate transport in human primary astrocytes, by TNF-α. The nuclear factor NFκB has been suggested to be involved in this regulation [ 23 ]. Even IL-1β and IL-6 have been shown to impair astroglial glutamate uptake capacity by involvement of oxidative stress or NO [ 20 , 24 , 25 ]. Even dysregulation of the blood brain barrier (BBB) is seen early in neuroinflammation, and parallels the release of proinflammatory cytokines [ 26 - 28 ]. Mechanisms for disruption of the BBB in neuroinflammation are incompletely understood, but appear to involve direct effects of cytokines on endothelial regulation of BBB components. Exposure of endothelium to TNF-α interrupts the BBB by disorganizing cell-cell junctions. Furthermore, TNF-α has been shown to depress calcium (Ca 2+ ) signaling between BBB endothelial cells by reducing gap junction coupling and inhibiting triggered ATP release [ 29 ]. Could glutamate neurotransmission be dynamically regulated by extracellular glutamate levels? As stated above, already when the [Glu] ec exceeds some 3–5 μM, the efficiency of the glutamate signaling is considered to be reduced [ 12 ]. There is prolonged postsynaptic and adjacent glial receptor activation [ 30 ], with less precision (with a decreased signal-to-noise ratio) in the glutamatergic transmission. As a consequence, the information taken into the brain will be less distinct. In addition, activation of astroglial networks, with induction of Ca 2+ oscillations, both within and between the gap junction-coupled astroglial syncytia [ 31 - 33 ], and with subsequent astroglial glutamate release [ 34 ] could increase the excitability level in neighboring neuronal circuits. The overall result may be that more, and larger, neuronal circuits would be activated over time [ 35 , 36 ]. This conclusion is further supported by studies demonstrating that inhibition of GLT-1 could facilitate hippocampal neurotransmission [ 37 ] and lead to increased neuronal excitability, as seen in for example hepatic encephalopathy [ 38 ]. Increased [Glu] ec would also lead to astroglial cell swelling, with a resulting decrease in the extracellular space volume, and locally further increased [Glu] ec [ 39 - 42 ]. The astroglial swelling would give rise to relative depolarization of the astroglial cell membrane, with a further decreased astroglial glutamate uptake capacity, and in addition, a decreased capacity of the astrocytes to remove [K + ] ec [ 43 , 44 ]. Even moderately increased (up to 8–10 mM) [K + ] ec levels have been shown in experimental systems to inhibit glutamate release [ 45 ]. Recent data indicate a dynamic and fine-tuning regulation of the glutamatergic transmission. One mechanism by which neurons regulate excitatory transmission is by altering the number and composition of glutamate receptors at the postsynaptic plasma membrane. This has been shown for the NMDA receptor in experimental systems and could have prominent importance for dynamic processes as learning and memory [ 46 ]. Of great importance in this context are also studies where stimulation of metabotropic glutamate receptors (mGluR3 and mGluR5) have been shown to critically and differentially modulate the expression of glutamate transporters [ 47 ] thus creating a substrate for a fine-tuning of the glutamate neurotransmission. Even the proinflammatory cytokine IL-1β could act as a regulator of glutamate transmission, as it was shown recently that this cytokine inhibits glutamate release and reduces LTP as a consequence of the formation of reactive oxygen species [ 11 ]. Furthermore, in states of decreased astroglial glutamate uptake capacity, even astroglial glucose uptake, and consequently the supply of metabolic substrates to the neurons, has been reported to decrease [ 48 - 50 ] and there may be relative energy insufficiency at the cellular level in neuronal circuits. In addition, glutamate release from the presynaptic terminals could decrease due to factors such as a decreased glutamine supply of the neurons. Experimental investigations in the rat and monkey have demonstrated a feedback loop from the left basal frontal cortex, with an inhibitory influence on the locus coeruleus in the brain stem [ 51 ]. If this loop also exists in humans, a slight increase in the neuronal firing due to slightly elevated [Glu] ec in the basal frontal cortex could lead to a decrease in the noradrenaline and serotonin (5-HT) release in the cerebral cortex, which would also decrease glucogenolysis [ 52 , 53 ] and, furthermore, impair metabolic substrates for cortical neurons. Thus, it might be that glutamate neurotransmission could be regulated by changing astroglial glutamate transporter capacity, and thus, increases in [Glu] ec levels could be one factor to impair glutamate transmission. Proinflammatory cytokines and neuroinflammatory and degenerative diseases, major depression, sickness behavior, and sleep deprivation There is an extensive literature on inflammatory response with microglial activation and the production of proinflammatory cytokines (TNF-α, IL-1β and IL-6) in neuroinflammatory/infectious and neurodegenerative diseases as well as in stroke and trauma [ 5 , 54 ]. The inflammatory activation starts early in some neurodegenerative disease such as Alzheimer's and Parkinson's diseases, being prominent for long time in these diseases and also in neuroinflammatory diseases, in meningitis, encephalitis and in trauma or stroke [see [ 54 ]]. Several groups have also described enhanced production of proinflammatory cytokines in major depression [see [ 55 ]] and sickness behavior [ 9 , 56 , 57 ]. This is interesting as there are overlaps between mental fatigue and these disorders. Furthermore, proinflammatory cytokines are activated in sleep deprivation [ 58 ], a state where mental fatigue is often prominent. In states of anxiety and stress, often experienced as secondary to mental fatigue, increased glucocorticoid levels have been demonstrated. Interestingly, long-term increases in glucocorticoids have been demonstrated to result in the production of both TNF-α and IL-1β [ 59 ]. Could mental fatigue be the consequence of a dysfunction in a specific brain region? In the search for pathophysiological correlates to fatigue in MS, Roelcke and co-workers [ 60 ] demonstrated reduced glucose metabolism in the frontal cortex and basal ganglia in MS patients with fatigue. A hypotheses by Chaudhuri and Behan [ 6 ] also focused on basal ganglia as one part of the brain crucial for mental fatigue to appear. Using patients with chronic fatigue syndrome, which is not however exactly the same as mental fatigue, studies have revealed prefrontal and temporal cortices, anterior cingulate and cerebellum as regions possibly involved in fatigue [ 61 ]. Interestingly these later studies also pointed at a possible connection between glutamate transmission and fatigue. Even if the mental fatigue is not the central problem in attention deficit hyperactivity disorder (ADHD), some of the symptoms in this disorder is similar to the symptom complex associated with mental fatigue, and there is some support for glutamate being involved in the disorder and its treatment [ 62 ] and also, at least hypothetically, a deficient astroglial metabolism due to decreased noradrenaline and serotonin levels [ 63 ]. Until now there is no evidence for a specific brain region being affected in mental fatigue. On the contrary, it seems that mental fatigue could appear from disturbances of different neuronal systems. We will therefore present a hypothesis (figure 1 ) where the functional disturbance of mental fatigue at the cellular level is coupled to the fine-tuning of the glutamate neurotransmission. Figure 1 Schematic drawing of cellular regulation of extracellular glutamate concentrations ([Glu] ec ) in normal brain function (left), and in the presence of the proinflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 (right). Possible pathophysiology underlying mental fatigue at the cellular level is outlined below. To the left: Two neuronal cell bodies with processes (white) make contact with each other through a synapse (center). Astrocytic (pink) processes encapsulate the synapse and cover also the abluminal side of the blood vessel wall (right). The endothelial cells covering the luminal (blood) side of the vessel wall and the astrocytic processes make up the blood brain barrier (BBB). An oligodendroglial cell (bluish), with its myelin encapsulating the axon, and a microglial cell (yellow) are seen. The astrocytes, with their high-affinity glutamate transporters, are the main site for keeping [Glu] ec low. Even neurons express glutamate transporters, as do oligodendroglial cells, and endothelial cells at their abluminal side. To the right: TNF-α, IL-1β and IL-6 attenuate astroglial glutamate uptake transport and disintegrate the BBB, allowing glutamate from the blood to enter the brain. The overall result is slightly increased [Glu] ec . Tumor necrosis factor-alfa also decreases oligodendroglial cell glutamate uptake [78], while microglial glutamate uptake has been demonstrated to increase (Persson, M., Hansson, E., and Rönnbäck, L, to be published), though not to levels to compensate for the decreased astroglial glutamate uptake capacity. Due to increased [Glu] ec , astroglial swelling is shown. Below: Hypothetic cellular events underlying mental fatigue. Slightly increased [Glu] ec could make the glutamate neurotransmission less distinct (decrease the signal-to-noise ratio). At the cellular level, there would be astroglial swelling, which in turn would decrease the local extracellular (ec) volume and, as a consequence, lead to further increased [Glu] ec . Astroglial swelling also depolarizes the astroglial cell membrane, which further attenuates the electrogenic glutamate uptake and, in addition, the astroglial K + uptake capacity. As a consequence, even [K + ] ec may rise. The increased [K + ] ec , together with decreased glutamine production and reduced glucose uptake concomitant with the decreased glutamate uptake, could lead to decreased presynaptic glutamate release and thereby decreased glutamate transmission, which, according to our hypothesis, is one cellular correlate to mental fatigue/exhaustion. Increased extracellular glutamate levels in the prefrontal region could lead to inhibition of the brain stem nuclei locus coeruleus (LC) and raphe nuclei and thereby inhibit noradrenaline (NA) and serotonin (5-HT) release in the cerebral cortex resulting in decreased astroglial metabolism and neuronal metabolic supply. Increased neuronal excitability may be part of the loudness and light sensitivity often accompanying the mental fatigue. In addition, the decrease in noradrenaline and serotonin release might be part of decreased attention and the appearance of depression often accompanying the mental fatigue. Mental fatigue – a stereotypical reaction upon brain function disturbance – a hypothesis focusing on impaired glutamate neurotransmission (figure 1 ) It may be that mental fatigue is a stereotypical reaction to disturbance of "higher" brain functions. The brain, with its billions of specialized neurons and supporting glial cells, works as a "whole" organ. Every disturbance of brain homeostasis, no matter where the anatomical localization is, would therefore attenuate brain capacity for information processing and, as a consequence, information intake. One way to diminish information intake and processing at the cellular level would be to impair glutamate neurotransmission by attenuating the glial support and especially diminishing the astroglial capacity to clear [Glu] ec . The initial consequence would be slightly increased [Glu] ec , with less precision in glutamate transmission. This would disintegrate the "filter", which normally selects information and prevents it from reaching the cerebral cortex. We can take the sound from a low-frequency fan as an example. This sound is normally sorted out after hearing it for a while. If this sound is handled with less precision by auditory recognition systems, it will continually be recognized by brain centers as "new" information and be processed in the cerebral cortex as long as the sound is on. The "filter" that normally restrains already recognized information from reaching higher brain centers, has been "opened". From a physiological point of view, it seems appropriate that the individual, and not the brain at the synaptic level, should determine which information should reach, and be processed by, the cerebral cortex. The decreased attention, increased loudness and light sensitivity, and irritability could be physiological ways of avoiding overstimulation of higher cortical centers. In case the individuals cannot protect themselves from too much sensory stimulation, the filter's opening leads to overstimulation of the cerebral cortex. Here, the final shutdown of the glutamate transmission could be one mechanism underlying mental exhaustion (figure 1 ). In line with these theoretical proposals, increased [Glu] ec has in fact been demonstrated in MS, meningitis, and encephalitis, Alzheimer's disease, ischemia and traumatic brain injury [ 64 - 69 ]. Furthermore, it has been shown in experimental studies that even extracellular K + is involved in the post-traumatic hyperexcitability, and a recent study has proposed that the larger extracellular K + increase evoked by neuronal activity is a consequence rather than the primary mechanism underlying post-traumatic hyperexcitability [ 70 ]. The theory also involves the possibility of a disturbed noradrenaline/serotonin turnover in the cerebral cortex due to a slight hyperexcitability in the frontal cortex. Interestingly, increased [Glu] ec in the prefrontal cortex has been reported by Bossuet and coworkers [ 67 ] in asymptomatic simian immunodeficiency virus (SIV)mac251-infected macaques without major brain involvement, being consistent with our theory at least in this set of animal experiments. If valid even in humans, a disturbed noradrenaline/serotonin turnover in the cerebral cortex could be coupled to the disturbed attention and depression often occurring in addition to the mental fatigue [see [ 71 - 73 ]]. Testing of the hypothesis It is not possible at present to ultimately prove whether or not the altered neuronal-glial interactions in glutamatergic transmission induced by proinflammatory cytokines could serve as a model to explain cellular mechanisms underlying mental fatigue. Brain imaging techniques able to determine and follow [Glu] ec and [K + ] ec over time would be important to use in humans suffering from mental fatigue. Today, this is not possible for technical reasons. Instead, we must use experimental systems to learn about glial cell biology and neuron-glia-neuron signaling and interactions, and thus test specific parts of the hypothesis. Neuroactive substances produced by, or altered conditions related to, the production of proinflammatory cytokines could be evaluated with regard to their effects on astroglial support of glutamate transmission, and especially glutamate transport capacity. The role of the intact astroglial network in higher brain functions (cognition and behavior) could be studied in animal models. Effects of astroglial dysfunction with regard to glutamate transport capacity would be of special interest. Even clinical studies with different treatment strategies could be important in casting some light on the accuracy of the hypothesis. Of utmost importance in all such studies would be test batteries making it possible to objectify and even quantify the degree of mental fatigue. Why do the symptoms persist in some patients? Normally, mental fatigue and the associated symptoms disappear when the brain dysfunction is over. In some patients, the symptoms persist. We have at present no explanation for this, but if our hypothesis is correct, there could be a genetic failure preventing astroglial glutamate transporters from upregulating. Another explanation for why the symptoms persist could be that the pathological stimulation by brain plasticity creates new neuronal networks [ 18 , 36 ]. Aspects of treatment Providing information about mental fatigue, its cause and the prognosis, is of utmost importance for breaking the vicious circle, which comes with the risk for secondary anxiety and depression. Furthermore, it is important for the patient to imagine and learn how much sensory stimulation they can tolerate prior to feeling too exhausted. Due to recent results on changes in cell signaling and neuronal plasticity [ 18 , 36 ], it may be important to identify the symptoms and treat them as early as possible to avoid formation of new and functionally disturbing neuronal circuits due to overstimulation of neuronal-glial units. If our hypothesis is correct, it may be possible to further improve the symptoms by suppressing the production of proinflammatory cytokines and, thereby, restoring the normal astroglial glutamate uptake. In this context, xanthine derivatives may be of use [ 74 ]. Another substance, worth considering, may be minocycline, a synthetic tetracycline derivative that has been shown to attenuate microglial activation and, consequently, the production of proinflammatory cytokines [ 75 ]. During recent years substances, which enhances glutamate uptake have been identified. Nicergoline [ 76 ], different growth factors including pituitary adenylate cyclase-activating polypeptide (PACAP) [ 77 ], some low molecular weight factors [ 23 ] as well as metabotropic glutamate agonists [ 47 ] have all been able to stimulate glutamate transport in experimental systems and could be of interest in the pharmacotherapy of mental fatigue. Interestingly, even AMPA receptor modulators have been demonstrated as cognitive enhancers [ 10 ]. List of abbreviations used ADHD attention deficit hyperactivity disorder AMPA alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate ATP adenosine triphosphate BBB blood brain barrier Ca 2+ calcium Ec extracellular GLAST glutamate aspartate transporter GLT-1 glutamate transporter-1 [Glu] ec extracellular glutamate concentration 5-HT 5-hydroxytryptamine ICD-10 International Classification of Diseases, 10 th revision IL-1/-6 interleukin-1/-6 K + potassium [K + ] ec extracellular potassium concentration LC locus coeruleus LTP long term potential MS multiple sclerosis Na + sodium NA noradrenaline NFκB nuclear transcription factor kappaB NMDA N-methyl-D-aspartate NO nitric oxide PACAP pituitary adenylate cyclase-activating polypeptide PI3K phosphatidylinositol-3-kinase PKC protein kinase C Siv mac simian immunodeficiency virus macaques TNF-α tumor necrosis factor alpha Competing interests The author(s) declare that they have no competing interests. Authors' contributions Equal contributions by both authors. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533886.xml |
517930 | Glycogen Synthase Kinase-3 regulates IGFBP-1 gene transcription through the Thymine-rich Insulin Response Element | Background Hepatic expression of several gene products involved in glucose metabolism, including phosphoenolpyruvate carboxykinase (PEPCK), glucose-6-phosphatase (G6Pase) and insulin-like growth factor binding protein-1 (IGFBP-1), is rapidly and completely inhibited by insulin. This inhibition is mediated through the regulation of a DNA element present in each of these gene promoters, that we call the T hymine-rich I nsulin R esponse E lement (TIRE). The insulin signalling pathway that results in the inhibition of these gene promoters requires the activation of phosphatidylinositol 3-kinase (PI 3-kinase). However, the molecules that connect PI 3-kinase to these gene promoters are not yet fully defined. Glycogen Synthase Kinase 3 (GSK-3) is inhibited following activation of PI 3-kinase. We have shown previously that inhibitors of GSK-3 reduce the activity of two TIRE-containing gene promoters (PEPCK and G6Pase), whose products are required for gluconeogenesis. Results In this report we demonstrate that in H4IIE-C3 cells, four distinct classes of GSK-3 inhibitor mimic the effect of insulin on a third TIRE-containing gene, IGFBP-1. We identify the TIRE as the minimum requirement for inhibition by these agents, and demonstrate that the target of GSK-3 is unlikely to be the postulated TIRE-binding protein FOXO-1. Importantly, overexpression of GSK-3 in cells reduces the insulin regulation of TIRE activity as well as endogenous IGFBP-1 expression. Conclusions These results implicate GSK-3 as an intermediate in the pathway from the insulin receptor to the TIRE. Indeed, this is the first demonstration of an absolute requirement for GSK-3 inhibition in insulin regulation of gene transcription. These data support the potential use of GSK-3 inhibitors in the treatment of insulin resistant states such as Type 2 diabetes mellitus, but suggest that it will be important to identify all TIRE-containing genes to assess potential side effects of these agents. | Background Insulin-like growth factors (IGF-I and II) have a broad range of biological activities that include the stimulation of mitogenesis and differentiation, and insulin-like effects on glucose uptake and lipogenesis [ 1 ]. These activities are modulated by a family of six binding proteins, termed the IGF-binding proteins (IGFBPs 1–6) that bind IGF-I and IGF-II with high affinity (for review see [ 2 ]). IGFBP-1 binds and inhibits the activity of IGF-I and IGF-II in plasma, by regulating their bioavailability [ 3 ]. Administration of excess IGFBP-1, or overexpression of IGFBP-1 in transgenic mice, leads to glucose intolerance and hyperinsulinaemia [ 4 , 5 ]. Meanwhile, IGFBP-1 expression can be dynamically regulated by nutritional status, increasing during fasting, malnutrition and diabetes but decreasing upon re-feeding or insulin treatment [ 6 - 8 ]. Hepatic IGFBP-1 gene transcription is rapidly and completely inhibited by insulin [ 9 , 10 ], however, the signalling pathway(s) that mediates this effect is less well defined. Insulin induces multiple intracellular signalling pathways in liver. Stimulation of the small G-protein Ras leads to activation of a protein kinase cascade consisting of Raf-1, MAP kinase kinase-1, p42/p44 MAP kinases and p90Rsk, while the activation of phosphoinositide (PI) 3-kinase promotes the generation of 3-phosphoinositides that induce the activity of protein kinases such as 3-phosphoinositide dependent kinase (PDK1) and protein kinase B (PKB) [ 11 , 12 ]. PKB subsequently phosphorylates glycogen synthase kinase -3 (GSK-3) at an N-terminal serine residue (Ser-21 on GSK-3α and Ser-9 on GSK-3β) rendering it inactive [ 13 , 14 ]. This PKB-mediated inhibition of GSK-3 contributes to insulin activation of glycogen and protein synthesis [ 14 , 15 ]. Studies using inhibitors of PI 3-kinase have demonstrated a requirement for this enzyme in insulin regulation of IGFBP-1 [ 16 ]. Indeed, overexpression of an active mutant of PKB mimics the effects of insulin on the IGFBP-1 promoter [ 16 ]. This effect, at least in part, is mediated through the inhibition of a Thymine-rich Insulin Response Element (TIRE) that lies between residues -120 and -96 relative to the transcription start site of the human gene promoter. Phosphoenolpyruvate carboxykinase (PEPCK) and Glucose-6-Phosphatase (G6Pase), rate-controlling enzymes of hepatic gluconeogenesis, possess a related regulatory element within their gene promoters [ 17 ]. Interestingly, members of the FOX(O) family of transcription factors (FKHR/FKHR-L1/AFX) have been linked to the regulation of the TIRE's found in these promoters [ 18 , 19 ]. The expression of all of these genes, as well as the regulation of FOX(O), is inhibited by insulin through a PI 3-kinase-dependent mechanism [ 20 - 24 ], suggesting that a common signalling pathway is utilised by insulin to regulate these related TIREs. However, insulin regulation of IGFBP-1 but not G6Pase or PEPCK gene expression is sensitive to an inhibitor of the mammalian Target of Rapamycin (mTOR) [ 10 , 25 ]. In addition, agents that strongly induce the MAPK pathway (e.g. phorbol esters) [ 26 ], as well as the protein phosphatase inhibitor okadaic acid [ 27 ], reduce the sensitivity of the IGFBP-1, but not the G6Pase and PEPCK promoters to insulin. Therefore, aspects of the signalling networks used by insulin to repress each of these TIRE containing promoters appear distinct. Recently, we observed that GSK-3 activity was required for both PEPCK and G6Pase promoter activity [ 28 ]. Selective inhibitors of GSK-3 reduce PEPCK and G6Pase gene transcription without requiring the activation of PKB. Indeed, the inhibition of GSK-3 may explain some of the effects of PKB overexpression on PEPCK and G6Pase gene expression. However, it was not clear why inhibition of GSK-3 should repress these promoters, whether inhibition of GSK-3 was actually required for insulin regulation of the genes, and whether the effect of GSK-3 inhibition was mediated through the TIRE. In the present study, we have examined the role of GSK-3 in the regulation of a third TIRE-containing gene promoter, namely IGFBP-1. We demonstrate that four different classes of inhibitors of GSK-3 can mimic the action of insulin and reduce IGFBP-1 gene expression. Furthermore, we find that inhibition of GSK-3 reduces the activity of a heterologous promoter containing the IGFBP-1 TIRE, and propose that this mechanism underlies the repression of all three promoters by inhibitors of GSK-3. Finally, we demonstrate for the first time a requirement for inhibition of GSK-3 in the insulin regulation of the TIRE, and hence IGFBP-1 expression. Results Lithium ions reduce IGFBP-1 gene expression in H4IIE cells Treatment of H4IIE cells with insulin completely inhibits both basal and glucocorticoid-induced IGFBP-1 gene expression. Lithium chloride, an inhibitor of GSK-3 in vivo , reduces both basal and glucocorticoid-induced IGFBP-1 gene expression (Fig 1 ). The effect of 20 mM lithium is not as complete as observed with insulin, resulting in only a 60–70% reduction of IGFBP-1 gene expression. However, treatment of H4IIE cells with the same concentration of potassium chloride has no effect on IGFBP-1 expression. The cyclophilin mRNA levels remain unchanged throughout these experiments. This highlights a role of a target of lithium ions in the specific regulation of IGFBP-1 gene expression. Figure 1 Lithium ions reduce IGFBP-1 gene expression . H4IIE cells were starved overnight prior to a 3 h incubation with insulin,10 nM; lithium chloride or potassium chloride at the concentrations indicated with or without dexamethasone, 500 nM; (A-B). Total cellular RNA was isolated and an RNase protection assay was performed as described in material and methods. Results are presented as percentage gene expression (A) or fold induction (B) relative to control and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments (lower panels) are also shown. ***, p < 0.001, **, p < 0.01 and NS, not significant More selective inhibitors of GSK-3 also reduce IGFBP-1 gene expression SB 214763 and SB 415286 are cell-permeable maleimide compounds that selectively inhibit GSK-3 [ 29 ]. Treatment of H4IIE cells with either compound reduces IGFBP-1 gene expression (Fig 2 ). Expression is more sensitive to SB 214763 than SB 415286 (consistent with its lower IC-50 towards GSK-3 in vitro [ 29 ]). Importantly, cyclophilin mRNA levels remain unchanged in the presence of these compounds. Furthermore, under these conditions the regulatory phosphorylations of PKB and FOXO-1 are unaffected by SB214763, SB415286 or lithium [ 28 ]. In addition, SB214763 or SB415286 do not affect the phosphorylation of Ser-9 (GSK-3β) or Ser-21 (GSK-3α). Similarly, MAPK and S6K activity are not significantly affected by these compounds, as judged by the phosphorylation status of these insulin-regulated signalling molecules (Fig 3 ). Hence, the effects seen with these compounds on IGFBP-1 are likely to be due to the inhibition of GSK-3 rather than as a consequence of down/up-regulation of PKB, FOXO-1, MAPK or the mTOR pathway, which are known to effect IGFBP-1 gene expression. Figure 2 SB216763 and SB415286 reduce IGFBP-1 gene expression . H4IIE cells were starved overnight prior to a 3 h incubation with insulin, 10 nM ; dexamethasone, 500 nM; plus or minus SB216763 (A) or SB415286 (B) at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed, as described in material and methods. Results are presented as fold induction relative to control (serum free) and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments are also shown (lower panels). ***, p < 0.001 and * p < 0.05 Figure 3 Inhibition of GSK-3 does not affect the phosphorylation of MAPK or regulation of the mTOR pathway . H4IIE cells were serum starved overnight prior to incubation with insulin, 10 nM; lithium chloride, 20 mM; SB216763, 30 μM; or SB415286, 100 μM for 15 min (A) or 3 h (B). Cells were lysed, and the lysates subjected to SDS PAGE as described in materials and methods, transferred to nitrocellulose and immunoblotted with antibodies as labelled (Phospho; phosphospecific antibody). Similar results were obtained from two experiments carried out in duplicate Paullones are potent inhibitors of GSK-3 that reduce IGFBP-1 gene expression Paullones are a family of benzazepinones that are potent (IC50; 20–200 nM), ATP-competitive inhibitors of cyclin-dependent kinases (CDKs) and the closely related neuronal CDK5/p25 [ 30 - 32 ]. Subsequently, they have been shown to be very potent inhibitors of GSK-3β [ 33 ]. Two members of this family, kenpaullone and alsterpaullone, reduce IGFBP-1 gene expression in a dose dependent manner (Fig 4 ). Alsterpaullone is much more potent than kenpaullone, reducing IGFBP-1 mRNA levels by 90% at 5 μM compared to a 50% reduction seen with 10 μM kenpaullone (Fig 4 ). Once more, this is consistent with the lower IC50 of alsterpaullone toward GSK-3 in vitro [ 33 ]. Alsterpaullone (like the maleimides) does not affect the phosphorylation of PKB, FOXO-1, MAPK, S6K or S6 (Fig 5 ). Similarly, phosphorylation at residues Ser-9 (GSK-3β) and Ser-21 (GSK-3α) of GSK-3 is unaffected by alsterpaullone treatment (Fig 5 ). Phosphorylation of Thr-308 (PKB) correlates with the activation of PKB while phosphorylation of Ser-9 (GSK-3β), Ser-21 (GSK-3α) and Thr-32 (FKHRL1) is indicative of inhibition of these PKB substrates. Figure 4 Paullones reduce IGFBP-1 gene expression . H4IIE cells were serum starved overnight prior to a 3 h incubation with insulin,10 nM; dexamethasone, 500 nM; plus or minus kenpaullone (A) or alsterpaullone (B) at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed, as described in material and methods. Results are presented as fold induction relative to control (serum free) and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments are also shown (lower panels). ***, p < 0.001 and ** p < 0.01 Figure 5 Alsterpaullone does not affect the regulatory phosphorylation sites of PKB, FOXO-1, MAPK, and components of the mTOR pathway . H4IIE cells were serum starved overnight prior to incubation with 10 nM insulin, or alsterpaullone at the concentrations shown for 30 min (A) or 3 h (B). Cells were lysed, and the lysates subjected to SDS PAGE, transferred to nitrocellulose and immunoblotted with antibodies as labelled (Phospho; phosphospecific antibody). Similar results were obtained from two experiments carried out in duplicate CHIR99021, the most specific GSK-3 inhibitor reported to date, also represses IGFBP-1 gene expression Although alsterpaullone, kenpaullone, SB214763, and SB415286 are potent inhibitors of GSK-3, they also exhibit activity against CDKs. However, the aminopyrimidine CHIR99021 shows 350-fold selectivity toward GSK-3 compared to CDKs (Jenny Bain and Sir Philip Cohen, University of Dundee, personal communication), and exhibits a Ki of < 10 nM in vitro [ 34 ]. It is the most selective inhibitor of this enzyme reported to date [ 34 , 35 ]. Treatment of H4IIE cells with CHIR99201 dramatically reduced basal and glucocorticoid-induced IGFBP-1 gene transcription, at concentrations between 1 and 10 μM (Fig 6 ) Figure 6 CHIR99021 reduces IGFBP-1 gene expression . H4IIE cells were serum starved overnight prior to a 3 h incubation with insulin,10 nM; dexamethasone, 500 nM; 8CPT-cAMP, 0.1 mM; plus or minus CHIR99021 at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed to measure IGFBP-1 and cyclophilin mRNA, as described in material and methods. Representative experiments are shown (A), while results are presented (B) as % expression (after correction for cyclophilin expression), relative to control (serum free) and are means ± standard error of two experiments performed in duplicate. CHIR99021 reciprocally regulates β-catenin activity and IGFBP-1 gene transcription H4IIE cells were transiently transfected with a luciferase-reporter construct containing TCF/LEF binding sites, whose activity is regulated by the GSK-3 substrate, β-catenin. Inhibition of GSK-3 results in the accumulation of β-catenin in the cytoplasm where it can form complexes with TCF/LEF. The complex translocates to the nucleus and activates transcription of target genes. Treatment of transfected H4IIE cells with CHIR99021 results in a dose-dependent increase in luciferase activity, regulated by the β-catenin/TCF complex (Fig 7A ). The β-catenin mediated transcription is induced two-fold by 2 μM CHIR99021, reaching six to seven-fold at 10 μM. Therefore the concentration required to induce β-catenin activity is equivalent to that required for reduction of endogenous IGFBP-1 mRNA (Fig 6 ). Figure 7 CHIR99021 regulates both β-catenin activity and TIRE containing promoter activity . H4IIE cells were transfected with TOPFlash (A) or alternatively with BP-1 WT or BP-1 DM5 (B) reporter constructs. Cells were incubated for 24 h with 10 nM insulin or CHIR99021 at the concentrations shown, prior to lysis and luciferase assays as described in materials and methods. Results are presented as fold induction relative to basal luciferase activity (no inhibitor) (A) or % luciferase activity relative to basal (serum free) luciferase expression (B) and are the means ± standard error of at least two experiments performed in triplicate. The basal activity of BP-1 WT and BP-1 DM5 is not significantly different. Meanwhile, insulin treatment of H4IIE cells previously transfected with a luciferase reporter construct under the control of a thymidine kinase promoter containing the IGFBP-1 TIRE (BP-1WT), reduces luciferase expression by 60% (Fig 7B ). This effect is abolished by a two base pair mutation of the TIRE (BP-1DM5) (Fig 7B and [ 36 ]). Interestingly, 2 μM CHIR99021 reduces BP-1 WT activity by around 50% (Fig 7B ), while 10 μM inhibits luciferase expression by 70%, with no effect on BP-1 DM5 activity. This demonstrates that CHIR99021 reduces TIRE activity, at a concentration that also induces β-catenin-mediated gene transcription (2–10 μM). This strongly argues that the effects of CHIR99021 on TIRE activity are mediated through inhibition of GSK-3. Enhanced expression of GSK-3 reduces insulin regulation of the IGFBP-1 TIRE In order to assess the requirement for inhibition of GSK-3 in insulin regulation of the IGFBP-1 TIRE we over expressed wild-type GSK-3 (GSK-3β-WT), insulin-insensitive GSK-3 (GSK-3β-S9A) or control protein (β-galactosidase) in H4IIE cells using adenoviral vectors. Infected cells were subsequently transfected with BP-1-WT and treated with or without insulin (Fig 8A ). The inhibitory effect of insulin on the BP-1 TIRE was significantly reduced when GSK-3 was over expressed (Fig 8A ), demonstrating that inhibition of GSK-3 is required for full repression of this element by insulin. Both wild-type (p < 0.001) and S9A-GSK-3 (p < 0.001) over expression (around 3 to 5-fold increase in expression) reduced insulin regulation of this element. Meanwhile, adenoviral expression of GSK-3β-S9A also reduced the ability of insulin to repress IGFBP-1 mRNA in the H4IIE cells (Fig 8B ). Figure 8 Overexpression of GSK-3β reduces insulin regulation of the IGFBP-1 TIRE . H4IIE cells were infected with adenovirus expressing either β-Galactosidase (control), GSK-3β (GSK-3wt), or insulin-insensitive GSK-3β (GSK-3S9A). A) Cells were incubated for 16 hours before transfection with 10 μg of BP-1 WT as described under the Methods section. After 24 hours at 37°C +/- insulin (10 nM) cells were lysed and either luciferase assays performed (upper panel) or GSK-3 levels determined by Western Blot (lower panel). Results in the upper panel are presented as % insulin repression of luciferase expression and are the means +/- S.E.M. of at least five experiments performed in duplicate or triplicate. Basal luciferase expression is 3-fold higher in WT and S9A-GSK-3 infected cells compared with control. The lower panels provide a representative analysis of expression of GSK-3 (in triplicate) in each treatment. There was a significant reduction in the effect of insulin on BP-1 WT when either GSK-3 WT (***p < 0.001, control vs WT) or GSK-3 S9A (***p < 0.001, control vs S9A) was overexpressed. There is no significant difference between the WT and S9A data sets (p = 0.160). B) After infection cells were incubated for 24 hr prior to a 3 hr incubation with hormones as indicated. Cells were lysed and IGFBP-1 and cyclophilin mRNA levels assessed by RNase Protection Assay. A representative experiment is shown (lower panel), while relative mRNA levels ± SEM are presented for two experiments performed in duplicate in the upper panel. CHIR99021 does not regulate FOXO-1 transactivation potential BP-1 TIRE activity can be regulated by co-expression of FOXO-1 [ 22 , 36 ]. Therefore, we examined the effect of CHIR99021 on the ability of FOXO-1 to regulate TIRE activity. When FOXO-1 is co-expressed with BP-1 WT in H4IIE cells, the expression of luciferase is induced around 3-fold (Fig 9 ). Insulin inhibits this FOXO-1-induced luciferase activity, while sensitivity to 2 μM CHIR99021 is completely lost in the presence of co-expressed FOXO-1 (Fig 9 ). The concentration of FOXO-1 used is less than maximal for induction of the BP-1 WT. This data suggests that FOXO-1 overexpression desensitises the TIRE to CHIR99021 and therefore that GSK-3 does not significantly regulate FOXO-1 activity. Figure 9 CHIR99021 does not affect FOXO-1 transactivation potential . H4IIE cells were transfected with BP-1WT along with pEBG2T or pEBG2T-FOXO-1. Cells were incubated with 10 nM insulin or 2 μM CHIR99021 for 24 h prior to lysis and luciferase assays as described in materials and methods. Results are presented as % luciferase activity relative to basal (serum free) luciferase expression and are the means ± S.E. of two experiments performed in triplicate. NS; not significant. Discussion GSK-3 activity is required for IGFBP-1 promoter activity through direct regulation of the TIRE This study demonstrates that six agents, of four different chemical classes, which share an ability to inhibit GSK-3 mimic the effect of insulin on IGFBP-1 gene expression. This is reminiscent of the effect of lithium ions, SB216763 and SB415286 on two other insulin repressed gene promoters, PEPCK and G6Pase [ 28 ]. Indeed, a heterologous promoter containing the IGFBP-1 TIRE (a related sequence is common to all three of these insulin-regulated gene promoters), is also inhibited by CHIR99021 (Fig 7B ). Similar promoter sequences are important for the insulin regulation of the tyrosine aminotransferase [ 37 ], aspartate aminotransferase [ 38 ], IRS-2 [ 39 ], and HMG CoA Synthase [ 40 ] gene promoters. Our data would predict that all of these genes, and any other promoters containing a TIRE, are likely to be repressed by treatment of cells with inhibitors of GSK-3. This provides an apparent paradox since we and others have found that insulin does not regulate every TIRE-containing gene promoter by an identical mechanism. For example, insulin regulation of the IGFBP-1 (but not the PEPCK or G6Pase) gene promoter requires mTOR activity [ 10 , 25 , 26 ]. Meanwhile, FOXO-1 is a TIRE-binding protein that has been proposed to regulate these three genes. However, cells that stably overexpress FOXO-1 show increased G6Pase but not PEPCK expression [ 41 ], and genetic manipulation of FOXO-1 has differential effects on these three gene promoters [ 19 ]. These data demonstrate that distinct signalling mechanisms control the regulation of these three TIRE-containing genes. Therefore, each TIRE structure may require GSK-3 activity for function but distinct signalling networks link each gene promoter with the insulin receptor. The common requirement for GSK-3 activity suggests that a GSK-3 substrate is key for the initiation of gene transcription for each TIRE-containing promoter. Inhibition of GSK-3 is required for full inhibition of the IGFBP-1 TIRE by insulin Insulin induces PKB activity, promoting phosphorylation of Ser-21 of GSK-3α and Ser-9 of GSK-3β, thereby reducing total GSK-3 activity by between 20 and 80%, dependent on cell type. Therefore, expression of a mutant GSK-3β with Ser-9 replaced by alanine renders cellular GSK-3 activity insensitive to insulin [ 14 ]. Indeed, expression of this mutant significantly reduces the ability of insulin to repress BP-1 WT (Fig 8A ), or the endogenous gene promoter (Fig 8B ), demonstrating that insulin requires to inhibit GSK-3 for full repression of this gene promoter element. Similarly, four to five fold over expression of wild-type GSK-3β antagonises insulin repression of the BP-1 WT (Fig 8A ). Although insulin will promote phosphorylation and inhibition (50–60% in H4IIE cells) of this recombinant GSK-3 in cells, the overall activity remains higher than un-stimulated control cells. This suggests that insulin must reduce GSK-3 activity below a threshold in order to fully repress BP-1 WT. This is the first demonstration of an absolute requirement for GSK-3 inhibition in insulin regulation of gene transcription. What is the molecular link between GSK-3 and the TIRE? The GSK-3 inhibitors regulate IGFBP-1 gene expression in the absence of regulation of PKB, MAP kinase, FOXO-1 or mTOR ([ 28 ] and Figs 3 and 4 ), known regulators of the IGFBP-1 promoter. This suggests a more direct regulation of this element, possibly of a TIRE-interacting protein itself. There are numerous transcription factors that have been proposed to be substrates for GSK-3 in vitro and in some cases in vivo (for review see [ 42 ]). These include β-catenin, c-jun, CREB, glucocorticoid receptor (GR) and c-myc. The phosphorylation of β-catenin [ 43 , 44 ], c-jun [ 45 , 46 ], GR [ 47 ] and c-myc [ 48 ] by GSK-3 promotes their destruction or reduces their activity, while the phosphorylation of CREB (at Ser-129) is thought to increase CREB activity [ 49 ], although this has been subsequently questioned [ 50 ]. Since inhibition of GSK-3 reduces TIRE activity, one presumes that GSK-3 mediated phosphorylation of a TIRE-binding protein would result in its activation (although possibly a permissive effect allowing activation by an additional mechanism), nuclear localisation or stabilisation. This would seem to rule out β-catenin, c-jun, GR and c-myc in the GSK-3-mediated regulation of the TIRE. Meanwhile CREB does not bind directly to a TIRE in vitro . The only known GSK-3 substrates that have been demonstrated to bind to or regulate the TIRE are members of the CAAT-enhancer binding protein (C/EBP) family of transcription factors. GSK-3 phosphorylates C/EBPα at Thr-222/Thr-226 [ 51 ] while C/EBPβ can regulate TIRE activity and is itself regulated by insulin [ 52 ]. The reported regulation of C/EBPβ by insulin is PI 3-kinase and PKB-dependent but is mediated through phosphorylation of the co-regulator protein p300/CBP [ 52 ]. We are currently examining whether the GSK-3 inhibitors regulate C/EBP and p300 phosphorylation and/or activity. Meanwhile, Granner and colleagues have found that insulin treatment of H4IIE cells increases the cellular levels of LIP (an inhibitory form of C/EBPβ that lacks the p300/CBP binding and activation domain) [ 53 ]. LIP subsequently replaces LAP (the activating form of C/EBPβ) on the endogenous PEPCK promoter. This prevents the recruitment of RNA polymerase II and p300/CBP, eventually leading to the repression of PEPCK gene expression. However, the LIP/LAP interacting elements within the PEPCK promoter are distinct from the TIRE [ 53 ]. Finally, our data suggests that the effect of GSK-3 inhibitors is independent of regulation of FOXO-1 (Figs 4 and 9 ), the best characterised TIRE-binding protein. Therefore, much more work will be required to identify the GSK-3 substrate that regulates this DNA element. GSK-3 inhibitors as therapeutics Agents that mimic the physiological processes that are regulated by insulin have the potential to be of therapeutic value for the treatment of insulin resistant states such as diabetes. Lithium chloride, SB216763, SB415286 and CHIR99021 inhibit GSK-3 and therefore mimic many of the actions of insulin. For instance, lithium chloride stimulates glucose transport and glycogen synthesis in adipocyte and muscle cell lines [ 54 - 56 ], while SB216763 and SB415286 stimulate glycogen synthesis in hepatocytes [ 29 ]. Meanwhile, CHIR99021 potentiates insulin activation of glucose transport and utilisation in vitro and in vivo [ 34 ], and related compounds reduce muscle insulin resistance [ 57 ] in animal models of diabetes. We have found that GSK-3 inhibitors also mimic the ability of insulin to repress key metabolic genes such as PEPCK, G6Pase and IGFBP-1 ([ 28 ] and Figs 1 , 2 and 4 ). Studies in animal models of diabetes suggest that these agents alleviate hyperglycaemia through both activation of glycogen synthesis and inhibition of hepatic glucose production [ 58 , 59 ]. However, a vast number of biological processes are known to be regulated by GSK-3, thereby questioning their long term use as regulators of glucose homeostasis. Importantly, GSK-3 associates with and regulates proteins linked to the development of colonic cancer (APC, axin and β-catenin). Meanwhile, ablation of one of the two genes for GSK-3 (GSK-3β) in mice proved to be fatal due to increased hepatic sensitivity to TNFα-induced apoptosis [ 60 ]. Despite all of the potential problems that may be associated with GSK-3 inhibitors, deleterious effects of such compounds in animals remain to be formally reported. Currently, GSK-3 inhibitors are being investigated for the treatment of numerous psychiatric disorders [ 61 , 62 ], neurodegeneration [ 63 , 64 ] and even hair loss [ 65 ]. Conclusions The work presented herein demonstrates for the first time that inhibition of GSK-3 is required for complete insulin regulation of IGFBP-1, while we have identified the DNA element by which GSK3 targets this gene promoter. As such, GSK-3 inhibition will mimic the insulin regulation of IGF1 bio-availability, as well as reducing the expression of hepatic gluconeogenic genes. It remains to be seen how many other insulin-regulated (and/or TIRE-containing) gene promoters are sensitive to these inhibitors. Methods Materials Radioisotopes were obtained from Amersham, Bucks, UK ({γ 32 P}-ATP) and ICN, Thame, Oxfordshire, UK ({α 32 P}-UTP). Insulin was purchased from Novo Nordisk, (Crawley, West Sussex, UK), kenpaullone and alsterpaullone from Calbiochem (La Jolla, CA) and the RNase Protection Assay Kit II from AMS Biotech/Ambion, (Austin, Texas). All other chemicals were of the highest grade available. Synthesis of CHIR 99021 CHIR99021 (6-{2-[4-(2,4-Dichloro-phenyl)-5-(4-methyl-1 H -imidazol-2-yl)-pyrimidin-2-ylamino]-ethylamino}-nicotinonitrile) was synthesized in 7% overall yield using a convergent approach from 2,4-dichlorobenzoyl chloride and 6-chloro nicotinonitrile respectively ([ 66 ] and refs within). Cell Culture The rat hepatoma cell line H4IIE was maintained in Dulbecco's Modified Eagle's medium (DMEM) containing 1000 mg/l glucose, 5% (v/v) foetal calf serum, as described previously [ 67 ]. Cells were incubated with hormones, at 37°C, for the times and at the concentrations indicated in the figure legends. RNA isolation and RNase protection assay H4IIE cells were serum-starved overnight and treated with hormone/inhibitor for the times and at the concentrations indicated in the figure legends. Total cellular RNA was isolated using TriReagent™ (Sigma) following the manufacturer's instructions. An RNase Protection Assay (RPA) was performed to determine the relative amounts of IGFBP-1 and cyclophilin mRNA in each sample [ 26 ]. Band intensity was quantified on a phosphorimager (Fuji), data calculated as a ratio of IGFBP-1 to cyclophilin mRNA and presented as fold activation (for induced samples) where the intensity of control samples were set at one, or as % gene expression (for non-induced samples) where the level of gene expression in untreated cells is set at 100%. Preparation of cell extract for western blot H4IIE cells were incubated in serum-free medium with hormones and inhibitors for the times and at the concentrations indicated in the figure legends. Cells were then scraped into ice-cold lysis buffer (25 mM Tris/HCl, pH 7.4, 50 mM NaF, 100 mM NaCl, 1 mM sodium vanadate, 5 mM EGTA, 1 mM EDTA, 1% (v/v) Triton X-100, 10 mM sodium pyrophosphate, 1 mM benzamidine, 0.1 mM PMSF, 0.27 M sucrose, 2 μM microcystin and 0.1% (v/v) 2-mercaptoethanol). Cell debris was removed by centrifugation at 13000 × g for 5 min and the protein concentration determined by the method of Bradford, using BSA as an internal standard. Antibodies for western blot analysis Antibodies to phospho ribosomal protein S6 (Ser-235), phospho-FKHR-L1 (Thr-32) and GSK-3β were purchased from Upstate (Lake Placid, USA), while the phospho-specific Ser9/Ser21 GSK-3, Thr-308 PKB, Thr389-S6K1, and Thr-183/Tyr185 p42/p44 MAPK antibodies were purchased from Cell Signalling Technologies (Hertfordshire, UK). H4IIE cell lysates were prepared following incubation with hormones as described in figure legends and analysed by Western blot analysis. Plasmids The plasmids BP-1 WT and BP-1 DM5 were a gift from Dr Robert Hall and Professor Daryl K. Granner (Vanderbilt University, TN, USA) [ 36 ]. The BP-1 WT plasmid represents a luciferase reporter construct under the control of a thymidine kinase promoter containing the IGFBP-1 TIRE wild-type sequence (5'-CAAAACAAACTTATTTTG). Two base pair mutations of the wild-type TIRE sequence at residues equivalent to position 5 of each A and B site (5'-CAAAA G AAACTT C TTTTG) produces a mutant promoter (BP-1 DM5) that is no longer responsive to insulin [ 36 ]. The FOXO-1 constructs have been described previously (10). Transient transfections The TOPflash reporter plasmid kit were obtained from Upstate Biotechnology (Lake Placid, USA). TOPflash has Tcf binding sites driving luciferase expression. Tranfections were performed using the calcium phosphate procedure as described previously [ 10 ]. H4IIE cells were transfected in 10 cm dishes with BP-1 WT (10 μg), BP-1 M5 (10 μg), TOPFlash (10 μg), plus or minus 2 μg of GST-FOXO-1 as indicated. Cells were then incubated for 24 h in serum free media with or without hormones or inhibitors as described in figure legends. Cells were lysed in 300 μl lysis buffer (Promega, UK), the cell debris removed by centrifugation at 13000 × g for 2 min and the supernatant stored at -70°C. Luciferase assays were performed using the firefly luciferase assay system (Promega, UK), as per manufacturer's instructions, with luciferase activity being corrected for the protein concentration in the cell lysate. Adenoviral infection H4IIE cells were infected with virus between a titre of 10 8 and 10 9 plaque forming units per ml, incubated at 37°C for 16 hr. Cells were then transfected with 10 μg of BP-1 WT as described above and incubated for a further 24 hr in the presence or absence of 10 nM insulin. Luciferase was harvested and assayed or cell extracts were prepared for western blot analysis, as described earlier. Statistical analyses As a measure of statistical significance of differences in experimental groups, student t-tests were performed and 5% confidence limits applied. Abbreviations G6Pase, glucose 6-phosphatase; IGFBP-1, IGF-binding protein-1; phosphatidyl inositol 3, kinase, PI 3-kinase; TIRE, thymine rich insulin response element; PKB, protein kinase B; PEPCK phosphoenolpyruvate carboxykinase; GSK-3, Glycogen synthase kinase 3 Authors contributions The majority of the data was obtained in equal measure by D.F. and S.P, the CHIR99021 was synthesised, purified and analysed by N.S. and R.M., the adenoviral vectors were produced and characterised by L.M.D. and C.J.R., while the project was conceived and supervised by C.S. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517930.xml |
545938 | The influence of demographic factors and health-related quality of life on treatment satisfaction in patients with gastroesophageal reflux disease treated with esomeprazole | Background The correlation between treatment satisfaction and demographic characteristics, symptoms, or health-related quality of life (HRQL) in patients with gastroesophageal reflux disease (GERD) is unknown. The objective of this study was to assess correlates of treatment satisfaction in patients with GERD receiving a proton pump inhibitor, esomeprazole. Methods Adult GERD patients (n = 217) completed demography, symptom, HRQL, and treatment satisfaction questionnaires at baseline and/or after treatment with esomeprazole 40 mg once daily for 4 weeks. We used multiple linear regressions with treatment satisfaction as the dependent variable and demographic characteristics, baseline symptoms, baseline HRQL, and change scores in HRQL as independent variables. Results Among the demographic variables only Caucasian ethnicity was positively associated with treatment satisfaction. Greater vitality assessed by the Quality of Life in Reflux and Dyspepsia (QOLRAD) and worse heartburn assessed by a four-symptom scale at baseline, were associated with greater treatment satisfaction. The greater the improvement on the QOLRAD vitality (change score), the more likely the patient is to be satisfied with the treatment. Conclusions Ethnicity, baseline vitality, baseline heartburn severity, and change in QOLRAD vitality correlate with treatment satisfaction in patients with GERD. | Background The inclusion of patients' opinions in the assessment of interventions has gained greater prominence over the last decades. Regulator agencies now call for the inclusion of patient-reported outcomes (PRO) in clinical trials evaluating pharmaceuticals interventions [ 1 - 4 ]. PRO of interest include health-related quality of life (HRQL), symptom assessment, and more recently, treatment satisfaction, in gastroesophageal reflux disease (GERD). Whereas HRQL measures the patient's physical, psychological, and social level of function, treatment satisfaction assesses the patient's attitude towards the treatment, or the extent to which the patient is satisfied or not with the results of the treatment. Thus, treatment satisfaction focuses on the interaction of expectations and preferences for treatments and is defined as the individual's rating of important attributes of the process and outcomes of the treatment experience [ 5 ]. Coyne and co-workers [ 6 ] have summarized a number of patient important domains that describe satisfaction with treatment including symptom relief, flexibility with dosing, and treatment expectations. Treatment satisfaction is also associated with prescription regimens that involve less invasive dosing regimens [ 5 , 7 - 10 ], such as daily versus twice daily use [ 11 ]. Evaluating treatment satisfaction may assist healthcare providers in understanding the issues that influence adherence with therapeutic interventions. In addition, treatment satisfaction can be a useful PRO when treatments show similar efficacy because differences in satisfaction could lead to patient preferences for one treatment over another and greater adherence with various treatment regimens. Demographic variables such as age, ethnicity, and gender may influence satisfaction [ 12 ]. Older people tend to be more satisfied with medical care than younger people [ 13 - 15 ], and Caucasian people on the whole are more satisfied than non-Caucasians [ 16 ]. In contrast, gender does not appear to influence treatment satisfaction [ 17 ]. The objectives of this study were to assess correlates of treatment satisfaction, including demographic factors, symptoms, and HRQL, as well as change scores in PRO instruments in patients with moderate to severe GERD receiving a proton pump inhibitor, esomeprazole. Methods Participants No statistical determination of sample size has been done since the study is of exploratory nature. We enrolled 249 patients with GERD in 13 gastroenterology practices and four general practices across Canada between March 2002 and March 2003. Included patients were 18 years of age or older and had a diagnosis of moderate to severe GERD and presence of symptoms for three months or longer [ 18 ]. Prior to inclusion all patients gave written informed consent in accordance with the Helsinki declaration. Of 249 patients, 217 (87%) completed the study. We excluded twelve patients because upon review they did not meet the initial inclusion criteria. Of the 20 patients who withdrew after the baseline visit, 4 withdrew because of adverse events, 2 were unwilling to continue, 4 were lost to follow-up and 10 were excluded because of improper administration or completion of the questionnaires at one visit. Figure 1 shows the flow of patients through the study. The final group of 217 completed patients received four weeks of therapy with esomeprazole 40 mg once daily, in the morning. Figure 1 Flow chart Procedure Patients completed PRO instruments at the clinic before and approximately 28 days after treatment. The completed PRO instruments included the Quality of Life in Reflux and Dyspepsia (QOLRAD) [ 19 ], the Feeling Thermometer (FT) [ 20 ], a four symptoms scale, the Standard Gamble (SG) [ 21 ], and an upper gastrointestinal (GI) symptom severity scale at baseline and follow-up. Patients completed the Health Utilities Index Mark 2 and 3 (HUI2 and HUI3) [ 22 ], and the Medical Outcomes Short-Form 36 (SF-36) [ 23 ] at baseline only; and the treatment satisfaction item at follow-up only. We describe these instruments below. In addition, trained research assistants collected information concerning demographic data and clinical data. Each visit lasted approximately 80 minutes. Treatment satisfaction Patients rated their satisfaction with treatment on a seven point scale responding to the question: 'How satisfied are you with the study treatment you received?' with the response options: completely satisfied, very satisfied, quite satisfied, no change, dissatisfied, very dissatisfied, and completely dissatisfied. PRO instruments QOLRAD The QOLRAD is a 25-item disease-specific self-administered instrument asking about the impact of heartburn and acid regurgitation on the patient's HRQL during the previous week. The QOLRAD includes questions related to 5 domains; emotional distress, sleep disturbance, problems with food and drink, limitations in physical and social functioning, and lack of vitality. Patients respond to each question on a seven-point scale on which a higher score indicates better HRQL. The psychometric properties concerning validity, reliability, and responsiveness to change are reported elsewhere [ 19 , 24 ]. The minimal important difference (MID) that patients perceive as important is approximately 0.5 on the 1 – 7 scale [ 25 ]. FT The FT is a visual analogue scale that resembles a thermometer. It is divided into 100 segments with a mark to represent each segment. Its anchors are dead (0) and full health (100) [ 21 ]. Patients mark their own health state and/or that of hypothetical patient scenarios or clinical marker states. In this study, three patient scenarios represented mild, moderate, and severe GERD. We developed and tested the clincal marker states with patients and clinicians [ 26 ]. The MID of the FT is approximately 6 on the 0 to 100 scale [ 27 ]. HUI This is a 15 item questionnaire designed to quantify HRQL [ 22 ]. Each item has 4–6 response options. There are 8 attributes in the HUI3 classification system: vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain. In the HUI2 there are 7 attributes: sensation, mobility, emotion, cognition, self-care, pain, and fertility. SF-36 The SF-36 contains 36 items that measure 8 dimensions: physical functioning, role limitations due to physical health problems, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and general mental health. This questionnaire has been extensively tested for validation and reliability [ 23 ]. Each domain is scored on a 0 to 100 scale where higher scores indicate better HRQL. Scores on the SF-36 can also be expressed as two summary measures, the physical component score and the mental component score, which provide a measure of the overall effect of physical and mental impairment on HRQL. Rating of four symptoms To assess common symptoms in GERD, patients evaluated their heartburn, acid reflux, stomach pain, and belching for the past week using a seven-point scale ranging from no discomfort to very severe discomfort. SG The SG involves decision in the face of uncertainty, where in the standard administration the uncertainty involves a risk of death. The SG offers the patients two alternatives from which a choice must be made: Choice A is a hypothetical treatment with two possible outcomes: 1) returning to full health (probability p) for t years, at the end of which they die, or 2) immediate death (probability 1 – p). The alternative (choice B) is a certain outcome that he or she will stay in a health state (their own health state, or a patient scenario) for t years until death. t varies depending on the patient's age. The interviewer used a change board with the ping-pong approach varying the probability p in steps of 0.05 to find the value p where the respondent considered choice A = choice B. This value of p is the utility value for the health state in choice A in the interval from dead (0) to full health (1). The greater a patient's willingness to accept the risk of a worse outcome (e.g. dead) to avoid the health state in choice A, then the lower is the utility of the state in choice A to them. Rating of upper GI symptom severity Patients documented the severity of overall upper GI symptom on a seven-graded scale (1 = no symptoms; 7 = severe symptoms) over the past seven days. At baseline, patients who had no, minimal or mild symptoms were not included in this study. Statistical analyses We calculated the mean and standard deviation of the basic demographic variables. Our multiple linear regression analysis focused on the outcome variable treatment satisfaction, which we treated as a continuous outcome variable. Evaluation of the data with polynomial regression yielded similar results. Potential correlates were demographic variables and baseline scores, as well as change scores for the PRO instruments described in the previous section. We first modelled these variables univariately as correlates of treatment satisfaction and only those that were significant at p < 0.1 entered into the multiple regression model. After having entered the multiple regression model, only those significant at p < 0.05 remained in the final model. Results Table 1 shows the baseline demographic characteristics and frequencies of the included patients. The mean age was 50 years, and approximately 50% of the patients were female. The mean number of months since diagnosis was 86 months. Approximately 70% were full-time or part-time employed, and 88% were Caucasians. Table 1 Demographic characteristics and frequencies at baseline for the study sample (N = 217). Frequency Percentage Gender Male 103 47.5 Female 114 52.5 Age Mean (SD) 49.7 (13.7) Range 20–82 Months since diagnosis Mean (SD) 86.3 (99.4) Range 1–504 Smoking history Never 94 43.5 Yes 38 17.6 Previous 84 38.9 Living alone 23 10.6 Employed: full-time and part-time 149 68.7 Ethnicity Caucasian 191 88.0 Other 26 12.0 Severity of gastroesophageal reflux disease (GERD) Moderate problem 112 51.6 Moderate severe problem 74 34.1 Severe problem 27 12.5 Very severe problem 4 1.8 Table 2 depicts the mean baseline scores for the QOLRAD, the four symptoms scale, the FT, the SG, the HUI, and the SF-36. The mean QOLRAD scores at baseline were lowest for the food/drink domain, indicating worse HRQL for this domain, and the mean scores at baseline for the four symptoms show that patients had most problems with heartburn. Furthermore, the mean SF-36 scores at baseline were lowest (worse) for the bodily pain dimension, and highest (best) for the social functioning domain. Figure 2 shows the distribution of the treatment satisfaction scores. Approximately 50% of the patients were completely satisfied, 25% were very satisfied, and approximately 15% were quite satisfied. About 7% reported no change or dissatisfaction of different severity. Table 2 Baseline scores for Quality of Life in Reflux and Dyspepsia (QOLRAD), four symptoms, Feeling Thermometer (FT), Standard Gamble (SG), Health Utilities Index Mark 2 and 3 (HUI), and Medical Outcomes Short Form-36 (SF-36). Mean SD QOLRAD dimensions Emotional distress 4.5 1.4 Sleep disturbance 4.5 1.5 Food/drink problem 3.8 1.2 Physical/social functioning 5.4 1.4 Vitality 4.3 1.3 Four symptoms Stomach pain 3.9 1.5 Heartburn 4.5 1.2 Belching 3.6 1.6 Acid reflux 4.1 1.6 FT 0.7 0.2 SG 0.8 0.2 HUI2 0.8 0.2 HUI3 0.8 0.2 SF-36 Physical functioning 46.6 9.0 Role-physcial 45.5 11.4 Bodily pain 42.8 9.4 General health 46.2 9.7 Vitality 45.9 9.8 Social functioning 47.7 10.3 Role-emotional 46.5 12.0 Mental health 46.9 10.4 Physial component 45.1 8.7 Mental component 47.6 11.0 Figure 2 Distribution of treatment satisfaction scores Table 3 portrays the results from the multiple linear regression analysis. Ethnicity, baseline QOLRAD vitality, baseline heartburn from the four symptoms scale, and QOLRAD vitality change score remained as independent variable when all variables had entered the model. Caucasian patients were more likely to be satisfied with the treatment than patients of other ethnicity. Higher baseline QOLRAD vitality scores, higher levels of heartburn and larger change on the QOLRAD vitality score were associated with greater treatment satisfaction. Table 3 Results from the multiple linear regression analysis with treatment satisfaction as outcome variable. Correlate variables Parameter estimate (β) SE P-value Ethnicity (Caucasian vs. other) -0.570 0.190 0.003 QOLRAD Vitality baseline -0.628 0.068 <0.001 Four symptoms Heartburn -0.195 0.055 <0.001 QOLRAD Vitality change -0.593 0.071 <0.001 Note. R 2 = 0.34 includes ethnicity, QOLRAD Vitality, heartburn, and QOLRAD Vitality change score Discussion The objective of this study was to assess correlates of treatment satisfaction in patients with moderate to severe GERD receiving esomeprazole. We found that Caucasian ethnicity, greater vitality and more severe heartburn at baseline, correlates with treatment satisfaction. Furthermore, the greater the improvement on vitality change score, the more likely the patient is to be satisfied with the treatment. The strengths of this study include the detailed assessment of a number of demographic characteristics, HRQL and symptoms. However, this study has two important limitations. First, we did not perform a placebo controlled trial limiting our ability to assess satisfaction as a true treatment result versus other reasons for satisfaction. Second, investigators have not conducted a thorough psychometric assessment of the treatment satisfaction instrument we used in this study. Nevertheless, the present study yields four important results. First, in this sample of GERD patients without prior endoscopic evaluation of their symptoms, Caucasian ethnicity was positively associated with treatment satisfaction. Ethnic origin is perhaps one of the most complex demographic characteristics [ 12 ] and it has previously been reported that Caucasian people on the whole are more satisfied than non-Caucasians [ 16 ]. Second, higher vitality scores, as assessed by the QOLRAD, were associated with higher treatment satisfaction. A patient's health status prior to receiving treatment may cause the patient to be either more or less satisfied with treatment. Clearly and McNeil [ 28 ] reported positive correlations between health status and satisfaction. However, it is unclear if satisfaction was correlated with health status before intervention or with health status after intervention. A possible interpretation of the positive association between QOLRAD vitality and treatment satisfaction in our study might be that patients with a high vitality score at baseline are less distressed by their disease, and therefore tend to be more satisfied. The association in our study between higher vitality scores, as assessed by the QOLRAD, and higher treatment satisfaction is in line with Revicki and co-workers [ 29 ] who found that patients reporting greater severity in heartburn symptoms were more likely to report psychological distress and impaired well-being compared with those who reported no or mild symptoms. However, Revicki et al measured HRQL with a generic instrument while we used a disease-specific instrument. Third, higher scores for heartburn, assessed with the four symptoms scale, were related to higher treatment satisfaction. Thus, in our study population, patients with high discomfort from heartburn at baseline perceived a high satisfaction with treatment. Fourth, the higher the improvement on the QOLRAD vitality (change score), the more likely the person is to be satisfied with the treatment. Patients' age is regarded as the most consistent determinant characteristic of satisfaction [ 13 - 15 ]. The results from this study did not reveal that treatment satisfaction was related to age. However, Fitzpatrick [ 30 , 31 ] and Fox and Storms [ 32 ] highlight the lack of consistency of the effect of age in satisfaction studies. Since satisfaction studies focused on a variety of concepts, such as satisfaction with medical care, satisfaction with hospital management, satisfaction with health services, and satisfaction with treatment, it might be that the association between age and satisfaction is dependent on the concept assessed. The lack of an association to age reveals also the possible that our study population was too homogenous with regard to age. Although some studies have reported that patient gender affects satisfaction values [ 33 , 34 ], other studies did not find such association [ 17 , 35 ]. In line with this, in our study population treatment satisfaction was not associated with gender. The current results may be unique to the study sample since no placebo control group was included in the study and, therefore, we were unable to evaluate whether the factors related to treatment satisfaction are related to real treatment effects or patients' need to please and placebo effects. The efficacy, tolerability and safety of esomeprazole versus other proton pump inhibitors has been shown in other studies [ 36 - 40 ]. In this study, patients had moderate to severe symptoms of GERD and some patients had received proton pump inhibitors prior to this study. The latter indicates that our study population is selected with regard to symptom severity, and mixed with regard to previous medication, which might limit generalizability of the findings. Treatment satisfaction in patients with mild GERD symptoms and with no previous experience of proton pump inhibitors remains unknown. Investigators often use several PRO instruments, each with many dimensions and single items that are more or less correlated in clinical studies. This can lead to a large number of statistical tests being carried out and an increased risk of statistically significant findings occurring by chance in the absence of adjustment of P-values. In the present report we did not carry out adjustments for multiple comparisons for two main reasons. Firstly, the analysis of correlations was intended to be exploratory rather than confirmatory. Secondly, there is no consensus on how to adjust in analyses of the nature we conducted in this study. A simple adjustment according to Bonferroni would be too conservative, in part because many of the PRO variables are closely correlated. Different drug therapies may elicit unwanted side-effects, which could compromise the patients' HRQL, and adherence with the treatment. Thus, a challenge in the management of GERD is to achieve as high adherence as possible. In addition, treatment satisfaction can be of use when different drug therapies show similar efficacy since it can lead to a preference for one drug over another and greater adherence. Our study also supports the need for validated treatment satisfaction instruments because the available instruments vary widely in clinical trials [ 41 ] and the majority of studies rely on single items. There is a need for developing and improving psychometric documentation of instruments measuring treatment satisfaction [ 42 ]. Conclusions We examined correlates of treatment satisfaction, including demographic factors, symptoms, and HRQL, as well as change scores in HRQL, in patients with moderate to severe GERD who were not investigated by endoscopy. We observed that Caucasian ethnicity was positively related to treatment satisfaction. Furthermore, higher vitality and more severe heartburn were associated with treatment satisfaction. Finally, the higher the improvement on the QOLRAD vitality (change score), the more likely the patient is to be satisfied with the treatment. Authors' contributions Alessio Degl' Innocenti was the project leader for this manuscript, edited the clinical protocol of the study, interpreted the data, and wrote the final manuscript as well as early versions. Gordon H Guyatt and Holger Schünemann were the principal investigators of the study, wrote the clinical protocol and grant application, are responsible for the study protocol, interpreted data and participated in writing the final as well as early versions of this manuscript. Ingela Wiklund contributed to the study protocol, interpreted the data and edited the manuscript. Diane Heels-Ansdell was responsible for the statistical analysis and edited the final manuscript as well as early versions. David Armstrong was co-principal investigator of the study, revised the clinical protocol, assessed patients, interpreted data and edited the final manuscript as well as early versions. Carlo A Fallone and Sander Veldhuyzen van Zanten revised the clinical protocol, assessed patients, interpreted data and edited the final manuscript as well as early versions. Samer El-Dika, Alan N Barkun, and Peggy Austin revised the clinical protocol, interpreted data and edited the final manuscript as well as early versions. Peggy Austin also co-ordinated the study. Lisa Tanser contributed to co-ordination of the study. All authors read and approved the final manuscript. The AstraZeneca global publications group approved the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545938.xml |
535561 | The "Transport Specificity Ratio": a structure-function tool to search the protein fold for loci that control transition state stability in membrane transport catalysis | Background In establishing structure-function relationships for membrane transport proteins, the interpretation of phenotypic changes can be problematic, owing to uncertainties in protein expression levels, sub-cellular localization, and protein-folding fidelity. A dual-label competitive transport assay called "Transport Specificity Ratio" (TSR) analysis has been developed that is simple to perform, and circumvents the "expression problem," providing a reliable TSR phenotype (a constant) for comparison to other transporters. Results Using the Escherichia coli GABA (4-aminobutyrate) permease (GabP) as a model carrier, it is demonstrated that the TSR phenotype is largely independent of assay conditions, exhibiting: (i) indifference to the particular substrate concentrations used, (ii) indifference to extreme changes (40-fold) in transporter expression level, and within broad limits (iii) indifference to assay duration. The theoretical underpinnings of TSR analysis predict all of the above observations, supporting that TSR has (i) applicability in the analysis of membrane transport, and (ii) particular utility in the face of incomplete information on protein expression levels and initial reaction rate intervals (e.g., in high-throughput screening situations). The TSR was used to identify gab permease (GabP) variants that exhibit relative changes in catalytic specificity (k cat /K m ) for [ 14 C]GABA (4-aminobutyrate) versus [ 3 H]NA (nipecotic acid). Conclusions The TSR phenotype is an easily measured constant that reflects innate molecular properties of the transition state, and provides a reliable index of the difference in catalytic specificity that a carrier exhibits toward a particular pair of substrates. A change in the TSR phenotype, called a Δ(TSR), represents a specificity shift attributable to underlying changes in the intrinsic substrate binding energy (ΔG b ) that translocation catalysts rely upon to decrease activation energy ( ). TSR analysis is therefore a structure-function tool that enables parsimonious scanning for positions in the protein fold that couple to the transition state, creating stability and thereby serving as functional determinants of catalytic power (efficiency, or specificity). | Background Structure-function analysis seeks to elucidate how the structural attributes of a protein serve its function. The function of a carrier protein is to catalyse transmembrane solute translocation. However, without a productive conspiracy among catalysis-promoting residues in the protein fold, transport proteins would be non-catalytic (i.e., unable to enhance transition state stability). Inasmuch as "... catalytic power will always appear as a result of increased transition state stabilization (lower free energy) ..." [ 1 ], a powerful addition to the structure-functionist's arsenal would be a generally applicable method that rapidly identifies sites in the protein fold that control transition state stability (i.e., that control the affinity of substrates for the transition state). What functional characteristics or properties might such a technique probe? The structure-function technique would be required to provide a keyhole through which to view positions in the protein at which structural perturbations affect transition state binding energy, for it is well-appreciated that a catalyst creates transition state stability by binding substrates tightly in the transition state complex [ 2 ]. In fact, binding energy is thought to be significant to the exclusion of all else in carriers that catalyse translocation without any change in the covalent structure of the substrate [ 3 ]. Absent changes in substrate structure, it is implicit that the conformational motions of "alternating access" must produce a transition state complex in which the substrate is more tightly bound than in the initial Michaelis complex. Fundamentally, catalysis could not occur without this realization of additional binding energy in the transition state [ 4 ]. The present contribution demonstrates use of the Transport Specificity Ratio (TSR) as an analytical keyhole to capture an initial glimpse of positions in the protein fold where structural characteristics control the availability of transition state binding energy. Using the Escherichia coli GabP ( gab permease) as a model carrier protein, salient properties and utilitarian features of TSR analysis are demonstrated. The TSR parameter is shown (i) to be calculated from an easily performed dual-label uptake experiment, and (ii) to depend exclusively upon changes in intrinsic substrate binding energy (ΔG b ) realized in the transition state. Together these TSR properties should enable transport structure-functionists to obtain rapid, yet incisive, first-pass view of positions in the protein fold where structure influences transition state stability and catalysis per se. Results Effect of substrate concentration on the TSR TSR analysis as implemented in present examples consists of a dual-substrate transport assay in which [ 14 C]GABA and [ 3 H]NA compete for uptake at the GabP active site. Therefore as a practical matter it is necessary to establish conditions under which an adequate signal may be obtained from both isotope channels. This can be accomplished empirically by mixing the labelled substrates in different proportions (Fig. 1A ). In the range from 1–10 μM (below expected K m for either substrate) the trading of [ 3 H]NA for [ 14 C]GABA is expected to substantially alter the fraction of active sites occupied by GABA versus NA Nevertheless, it is clear that the calculated TSR parameter is indifferent to the precise substrate concentration ratio. Moreover, at a fixed substrate ratio (7 parts NA to 3 parts GABA), the absolute substrate concentrations may also be varied over a wide range (here 17.5-fold) without affecting the calculated TSR parameter (Fig. 1B ). Figure 1 Results from TSR analysis are valid across a broad range of competing-substrate concentration ratios The Transport Specificity Ratio (TSR) is calculated using results from a dual-label competitive uptake assay in which structurally distinct, labelled substrates are allowed to compete for transport at the same active site. Panel A: Mixtures of 10 μM [ 3 H]NA (0.6 μCi/ml) and 10 μM [ 14 C]GABA (0.2 μCi/mL) were prepared such that [NA] + [GABA] = 10 μM. E. coli strains SK105 (GabP-positive) and SK45 (GabP-negative) were exposed in parallel experiments for 10 seconds at 30°C to substrate mixtures containing the indicated concentrations of [ 3 H]NA. The GabP-dependent (SK105 minus SK45) uptake of either [ 3 H]NA (■) or [ 14 C]GABA (▲) may be read from the left-side ordinate. The calculated TSR (Equation. 6) may be read from the right-side ordinate (○). Panel B: The substrate concentrations were varied in constant proportion such that the GABA concentration (ranging from 1.8–31.5 μM) was always 42.9 percent of the NA concentration (ranging from 4.2–73.4 μM). The radiochemical concentrations for [ 3 H]NA and [ 14 C]GABA were 0.23 μCi/ml and 0.03 μCi/ml, respectively. The indicated concentration ranges produce about 50 percent combined active site occupancy (bound GABA plus NA) – since the affinities for GABA and NA are 40 μM and 200 μM, respectively [25]. Although these data (as well as the underlying theory) indicate that there is great latitude in choosing substrate concentrations for TSR measurements, it is nevertheless pragmatic to select robust initial velocity conditions wherein the substrate concentration ratio is such that equal disintegration rates are seen in both isotope channels (broken line) when the control (e.g., wild type) transporter is studied. Variant transporters, exhibiting relative increases or decreases in specificity for the two substrates, will then be easily visualized as an inequality between the disintegration rates seen in the two isotope channels (so that the data are no longer graphically superimposed). Effect of protein expression level on the TSR When distinct transporter variants are studied, it frequently is the case that the strains will express the variants at distinct and unpredictable levels in the plasma membrane, complicating the interpretation of any observed differences in transport velocity. In order to discern how expression-level affects the TSR analysis, IPTG was used to induce to differing levels the lac -controlled expression of the plasmid-borne GabP gene. Growth in the presence of increasing IPTG concentrations caused the uptake of [ 3 H]NA and [ 14 C]GABA to increase in proportion to the GabP expression-level (Fig. 2A ), which was monitored by immunoblot (Fig. 2B , inset). Although single-substrate uptake and expression varied over a 40-fold range, the calculated TSR parameter held steady (Fig. 2B ), indicating that differing expression levels would have a minimal effect on results obtained by TSR analysis. Figure 2 Results from TSR analysis are valid across a broad range of carrier expression levels E. coli strains SK11 (GabP-positive) and SK45 (GabP-negative) were grown to early logarithmic phase as described in Methods except that expression was induced by exposing cultures to the indicated IPTG concentrations. The cells were washed with 100 mM potassium phosphate buffer (pH 7.0), and dual-label competitive transport reactions were initiated by exposing the cells to 7 μM [ 3 H]NA (0.42 μCi/ml) and 3 μM [ 14 C]GABA (0.06 μCi/ml) for 10 seconds (initial rate) at 30°C. Error bars represent the S.E.M. (n = 3). Panel A. GabP-dependent uptake (SK11 signal minus SK45 signal) of either [ 3 H]NA (■) or [ 14 C]GABA (▲). Panel B. Transport Specificity Ratio (GABA/NA). Inset. Immunoblot of plasma membrane vesicle protein (2 μg per lane) probed with an anti-pentaHis mAb and developed with a chemiluminiscent alkaline phosphatase substrate (see Methods ). Lane 1: Membranes from E. coli strain SK45 (GabP-negative). Lanes 2–10: Membranes from E. coli SK11 (GabP-positive) grown in the presence of 2, 5, 10, 20, 50, 100, 200, 500, or 1000 μM IPTG, respectively. Effect of assay end-point on the dual-substrate mole ratio Single-substrate transport velocities may be estimated from the slope of the initial-rate segment of an uptake time course (Fig. 3 ). Unlike single substrate uptakes, which are linearly affected by deviations from the intended stopping time, the dual-substrate "mole ratio" is time-independent across the linear range studied. Thus, mechanical errors affecting the "stop-time" should be largely self-correcting. Indeed, the red arrow (Fig. 3A ) marks the position of an indeterminate error, wherein the single-substrate data points are off the curve suggested by the remaining data. This error is seen to "self-correct" in the dual-label "mole ratio" and TSR calculations (Fig. 3B , red arrow), indicating that dual-label ratio parameters can be more reliably estimated than can single-substrate velocities. In fact, many errors in time and volume will "self-correct" in the TSR calculation (see Discussion section). Figure 3 Results from TSR analysis are valid across a broad range of reaction times E. coli strain SK11 (GabP-positive) was exposed simultaneously to 6 μM [ 3 H]NA (0.42 Ci/ml) and 4 μM [ 14 C]GABA (0.06 Ci/ml) for the indicated times at 30°C. Parallel experiments were carried out in the presence of 2 mM GABA, which was included to block the GabP. Panel A shows the GabP-dependent component of competitive uptake (difference between the parallel experiments) over a 10-fold time range. The red arrow indicates a probable mechanical error, causing low uptake inconsistent with other points on the curve. The Panel B shows the GABA to NA mole ratio (left-side ordinate) calculated from data shown in the Panel A. The associated TSR values may be read from the right-side ordinate. The red arrow has the same meaning as in the Panel A, and serves here to emphasize the reliability of the TSR analysis, which has self-correcting properties that compensate for many routine sample processing problems that may cause inconsistency in times or volumes (see discussion). Assignment of TSR phenotypes to GabP variants When assay conditions conform to recommendations (Fig. 1 ), then transporters serving as the "parental control" will exhibit superimposed initial rate segments on the uptake time courses for accumulation of the [ 3 H] and [ 14 C] labels [ 5 , 6 ]. Clearly, the GabP variants shown in Figure 4 do not exhibit superimposed initial rate segments, indicating in a highly intuitive visual fashion that the TSR phenotype for these variants will differ from their respective parent transporters. Compared to its Cys-less parent (control TSR = 8), the single-Cys variant, N302C, exhibits a relative increase in preference for NA (TSR = 2.5). Compared to its wild type parent (control TSR = 4), the INS Ala 320 variant (with an extra alanine residue inserted at position 320) exhibits a relative increase in preference for GABA (TSR = 16). Figure 4 Variants of the E. coli GabP that exhibit Δ(TSR) phenotypes Using data analogous to Figure 1, the concentrations of competing substrates were adjusted empirically such that the initial rates of label accumulation were superimposed for E. coli strains expressing the "control" gab permease (GabP). As a result, any separation between initial rate uptake curves for [ 14 C]GABA (▲) and [ 3 H]NA (■) provides a highly intuitive visual representation of a Δ(TSR) phenotype. Panel N302C shows TSR analysis of the single-Cys GabP variant, N302C. Compared to the Cys-less GabP control (TSR = 8) for which the initial label accumulation rates are superimposed [5], the N302C shows a relative increase in the specificity for NA with a calculated TSR of 2.5. The Panel INS Ala 320 shows TSR analysis of the GabP variant, INS Ala 320, which has an extra alanine residue inserted at position 320. Compared to the wild type GabP control (TSR = 4) for which the initial label accumulation rates are superimposed [6], the INS Ala 320 exhibits a relative increase in specificity for GABA (i.e., opposite of the Panel N302C) with a calculated TSR of 16. Discussion TSR phenotyping derives from a concrete definition of catalysis In order to initiate development of a structure-function relationship for translocation catalysis by GabP [ 5 , 6 ], it was useful to adopt a formalism that describes catalysis in concrete terms [ 7 ] so that structural perturbations affecting catalysis might likewise be described in terms of a concrete (quantifiable) phenotype – the TSR. Fundamental to TSR analysis is the notion that transport catalysts use substrate binding energy to lower the translocation energy barrier (activation energy) [ 2 ]. Equation 1 states that the catalysed activation energy ( ) is lower than the non-catalyzed activation energy ( ) by an amount equal to the intrinsic substrate binding energy, ΔG b (algebraically negative). Importantly, Equation 1 (justified by Fig. 5 ) tells us that to screen for changes in catalytic power (barrier height) per se, one must find an easily measured signal that reports on changes in the intrinsic substrate binding energy (ΔG b ) used to stabilize the transition state. That the Transport Specificity Ratio (TSR) analysis fulfills this requirement may be shown as follows. Figure 5 Changes in catalytic specificity (k cat /K m ) reflect underlying changes in transition state binding energy (ΔG b ) In this description of catalysis, (i) the magnitude of the non-catalysed activation energy ( ) does not depend on a favourable protein-substrate interaction in the transition state, (ii) the catalysed translocation energy barrier is taken as the Gibbs Energy difference ( ) between the free reactants (C + S) and the transition state complex ( CS ‡ ), and (iii) intrinsic substrate binding energy is recognizable as the decisive factor in transition state stabilization. Thus, translocation catalysts (C) will use intrinsic substrate binding energy (Δ G b ) to stabilize the transition state (CS ‡ ). The role of Δ G b in lowering the transition state energy barrier compared to a non-catalyzed reaction ( ) may be deduced with aid from the accompanying energy diagrams, which emphasize several instances wherein the thermodynamic distance represented by one coloured arrow equals the summed distance represented by two shorter arrows of the same colour. The illustrated thermodynamic relationships are restated (with proper attention to sign convention) in equations A (red), B (green), and C (blue). Substituting A and C into B yields the fundamental relationship, (boxed), which says that the uncatalysed activation energy ( , algebraically positive) is diminished by intrinsic substrate binding energy, Δ G b (algebraically negative), which is the underlying parameter that TSR analysis probes (Eqn. 9). Note: These energy diagrams compare non-catalytic (dots and dashes) and catalytic (solid line) proteins. Imposition of a binding-averse interaction (Δ G R ) is seen to de-stabilize the Michaelis complex (CS, red arrows) in the catalytic protein. Subsequent attainment of favourable transition state complementarity (i.e., via conformational transitions that relieve Δ G R , blue arrows) results in use of binding energy to stabilize the transition state complex (CS ‡ ). This internal ''give-and-take,'' involving Δ G R is reflected in its algebraic cancellation when equations A, B, and C are combined to yield the boxed equation (text Eqn. 1), which says that intrinsic substrate binding energy decreases the energy barrier ( ) for a translocation reaction carried out from solution (i.e., directly from the free carrier and substrate (C + S) to the transition state). When C and S are free in solution, the effective second-order rate constant associated with is k cat /K m , the specificity parameter compared in the dual-substrate TSR analysis (Equation.5). That k cat /K m should be associated with the free reactants may be appreciated by considering the Michaelis-Menten Equation when S << K m , and CS complexes do not exist in appreciable amounts (see Discussion ). The Michaelis-Menten equation in two variables The velocity ( v ) of a simple translocation reaction, carried out from solution (C + S → Products), is governed by a second-order rate law (Equation 2), wherein the apparent second-order rate constant is k . v = k [ C ][ S ] (2) Free carrier and substrate (C + S) are dominant under non-saturating, second-order conditions (i.e., [S] << K m ), wherein the familiar Michaelis-Menten relationship (Equation 3) reduces to the form of a second-order rate law (Equation 4), and the apparent rate constant may be evaluated as k = k cat /K m (units M -1 sec -1 ). Although Equation 4 may appear to be a special case, it is actually a generally valid alternative form of the Michaelis-Menten Equation that is little used because it contains two variables, [C] and [S]. Equation 4 is valid at all substrate concentrations, producing the same saturating substrate-velocity curve as Equation 3 (since [C] goes to zero as [S] goes to infinity). The alternative Michaelis-Menten form turns out to be very useful for analysing the uptake of two labelled substrates that compete for transport at the same active site. Competing substrates equilibrate with the same free carrier concentration Consider the E. coli GabP exposed simultaneously to arbitrary concentrations of its transported substrates [ 8 , 9 ], [ 14 C]GABA and [ 3 H]NA. These competing substrates, present simultaneously in the same reaction vessel, will necessarily be in equilibrium with precisely the same concentration of free carrier (but unknown concentrations of carrier-substrate complexes), allowing algebraic elimination of [C] (Equation 5) when a ratio is taken between two instances of Equation 4 (one for each substrate). Catalytic specificity reflects the translocation energy barrier height That Equation 5 contains the ratio of a pair of (k cat /K m ) values has two consequences. First, since (k cat /K m ) is formally a measure of catalytic specificity [ 7 , 10 ], we may recast Equation 5 succinctly in terms of the Transport Specificity Ratio (TSR) parameter. Secondly, since (k cat /K m ) is an apparent rate constant (see above), transition state theory holds that its value depends upon the height of the translocation energy barrier ( ) as indicated by this logarithmic form of Eyring's Equation (Equation 7), wherein k is the Boltzman constant, h is the Planck constant, R is the gas constant, T is the absolute temperature, and a transmission coefficient of unity is assumed. Specificity ratios depend only upon intrinsic binding energy differences If catalytic specificity (k cat /K m ) depends upon , then by implication the TSR must be related to the intrinsic substrate binding energy – as becomes evident when Equations 1 and 7 are combined, Equation 8 shows that k cat /K m (synonymous with catalytic power, specificity, and efficiency) varies with the amount of transition state stabilization afforded by ΔG b , which is the intrinsic substrate binding energy (algebraically negative). Taking the ratio between two instances of Equation 8 (e.g., for the two competing substrates, GABA and NA), and combining terms, we obtain Equation 9 indicates that an experimentally observed change in the TSR parameter would require a change in the underlying intrinsic substrate binding energies that determine the relative height of the translocation energy barriers for two substrates competing at the same active site. The TSR reflects a change in substrate affinity for the transition state Figure 6 emphasizes that in the comparison of two substrates, the TSR reflects a difference in substrate affinities for the transition state (at the reaction coordinate peak). This contrasts with true equilibrium binding measurements, which reflect substrate affinities in the initial Michaelis complex (at the reaction coordinate bottom). These affinities are characterized by the dissociation constants, K d and , which describe the equilibrium position of reactions leading to formation of free reactants from either the Michaelis complex (CS ↔ C + S) or the transition state complex (CS ‡ ↔ C + S), respectively. Inasmuch as equilibrium constants (e.g., ) are always determined by Gibbs energy differences (e.g., Δ G b = - RT ln ), it follows (Fig. 6 , yellow shading) that a change in transition state binding energy (ΔΔG b ) reflects a change in the midpoint separation ( ) between hypothetical curves that describe binding of two test substrates (A and B) to the transition state. Structural features that affect the "tightness" of transition state binding will alter the translocation energy barrier height (Equation 1), which determines synonymously the catalytic power, efficiency, or specificity of a transporter. Figure 6 Comparison of equilibrium binding versus TSR analysis Envisage a catalytic protein interacting with two substrates (or substrate analogs), one exhibiting high-affinity binding (dashed RED line), and the other low-affinity binding (solid BLUE line). Equilibrium binding to the stable Michaelis complex (LEFT, Panels A and B) would produce concentration-dependent saturation of the binding site (Panel B). From the observed affinity difference (ΔK d ) between the two substrates, one can calculate a corresponding difference in binding energy, ΔΔG S (Panel A), for the two substrates interacting with the stable Michaelis complex at the bottom of the reaction coordinate. In contrast, information on the interaction of substrates at the reaction coordinate peak would require a study of binding to the unstable transition state (RIGHT, Panels C and D). Unfortunately, due to the high energy-level and transient nature and of the transition state (denoted by ‡), the relevant binding experiment (Panel D) is technically impossible. However, TSR analysis allows direct calculation (Equation 9) of the transition state binding energy difference, ΔΔG b (Panel C, yellow) between two competing substrates, A and B. A change in the TSR phenotype, or Δ(TSR), thus provides evidence for a change in the graphical separation distance, (Panel D, yellow), for the "impossible experiment" on substrate binding to the unstable transition state. Thus, observation of a Δ(TSR) phenotype reflects underlying structural changes that affect binding discrimination between substrates A and B in the transition state, which are of interest because transition state binding interactions create transport catalysis [2–4, 7] by lowering the activation energy, , and increasing k cat /K m . In summary, the equilibrium binding experiment depicted on the left does not address catalysis per se , whereas the TSR experiment depicted on the right does. The TSR phenotype is a constant Unlike first-pass analytical methods that rely on the signal from one labelled substrate, the herein described dual-label analysis leads directly to the TSR parameter – a constant (Equation 9). Constants are intrinsically stable and reliable, reflecting fundamental reaction characteristics that survive changes in ambient conditions (provided temperature and pressure can be held constant). The unique stability and fundamental nature of the TSR phenotype will make it particularly valuable for first-pass analysis in high-throughput screening situations, wherein protein expression levels, duration of the initial rate time course, and degree of saturation by the chosen substrate concentration may be inconsistent across large numbers of transporter variants with differing functional characteristics. This reliability is demonstrated using the E. coli GABA permease (GabP) as a model translocation catalyst. Overall the present study makes clear that the dual-label TSR analysis is insulated remarkably well from many uncontrolled variables that can often compromise the validity of assays that use a single label. TSR analysis is valid at arbitrary site-saturation levels Figure 1 shows that the TSR did not change when GabP was exposed to [ 14 C]GABA and [ 3 H]NA in different proportions, or in fixed proportion over a broad concentration range (Fig. 1B ). Indeed, the form of Equation 6 suggests that the velocity ratio should self-adjust continuously with changes in the dual-substrate concentration ratio (since the TSR and its component parts, k cat and K m , are all constants). Thus, arbitrary carrier saturation levels are not expected to compromise TSR measurements. Since uncharacterized mutant collections may be expected to contain transporter variants with highly divergent K m values, the saturation-independence of TSR analysis should be of value in high-throughput screening situations where little kinetic information may be available to guide the choice of assay conditions. However, to be of general value the results obtained with GabP must extrapolate to other transporters. Why the deceptively simple TSR analysis should have broad applicability can be understood from further consideration of Figure 1 . When substrate concentrations are varied, carrier saturation levels change, producing new complexes (e.g., [C· GABA] and [C· NA]) in changing proportions. While manipulating these complexes affects single-substrate uptake velocities significantly (Fig. 1 ), the TSR calculated from these velocities is unaffected because these particular complexes (and complexes of any arbitrary number and description) never have a role in determining the equilibrium – energetic distance ( ) – between the free reactants (C + S) and the transition state (CS ‡ ). This fundamental reality can also be appreciated from the perspective that under non-saturating conditions ([S] << K m ), there are no complexes to consider ([C] = C total ), and thus even complicated mechanisms reduce to the simple case (Equation 4) in which the reaction proceeds directly from the free reactants in solution to the transition state (C + S → Products). Thus, the simple second-order reaction scheme, C + S → Products, will probably never be "too simple" for the purpose of performing the TSR analysis – even though complicated transport kinetics will feature many complexes that TSR analysis seems to ignore. In truth, the missing complexes are merely irrelevant (not ignored) to the value of (Fig. 5 ) since these complexes would always lie energetically between (or below) the free reactants (C + S) and the transition state complex (CS ‡ ). TSR reliability stems from self-correcting properties It is worth mentioning that TSR analysis has "fool-proof" qualities that derive from its inherent insensitivity to several sources of error that can seriously compromise transport measurements that rely upon a single labelled substrate. TSR calculations may be expected to "self-correct" any sources of error that have proportionally the same effect on the measurement of both isotopes – for such errors cannot affect the isotope ratio used to calculate the TSR parameter. Figure 3 , for example, shows that whereas stop-times affect single-isotope uptake signals in linear fashion, the dual-substrate mole ratio (and TSR calculation) is hardly affected meaning that TSR analysis is inherently insensitive to vast timing errors. In the experiment shown, stopping at arbitrary times across 10-fold range would have impacted the TSR calculation very little. Likewise, most sample handling errors (e.g., pipetting, filtering) will tend to affect both isotopes proportionally so that whereas the single isotope uptakes are affected linearly, the TSR calculation is preserved (Fig. 3 , red arrow). Perhaps most importantly, TSR analysis can correct for sample-to-sample variations in protein expression-level (Fig. 2 ). In order to demonstrate the expression-independent nature of the TSR parameter, IPTG was used to simulate the wide range of expression levels (40-fold) that might be encountered in an uncharacterized collection of transporter variants. Whereas the single-isotope signals (Fig. 2A ) are seen to vary directly with GabP expression, the dual-isotope TSR phenotype (Fig. 2B ) varies little. This expression-independent behaviour fully complies with theoretical expectations since (i) the carrier concentration was algebraically eliminated (Equation 5), and (ii) TSR is a "constant" (Equation 9), reflecting fundamental molecular properties of carrier-substrate interaction that do not depend upon the number of carrier molecules expressed in the membrane. The ability to rapidly evaluate a TSR phenotype, formally an expression-independent constant , should be of considerable practical significance for high-throughput screening operations wherein carrier expression levels could be both highly variable and impractical to document in real-time. Since TSR phenotypes are expression-independent, structure-function information gleaned from a rapid first-pass screen will remain valid irrespective of results that might be obtained from a subsequent immunoblot analysis. Immunoblots do not in any event determine C total in the sense desired for meaningful kinetic characterization, which assumes (Equation 3) that C total consists entirely of active molecules. The possibility of partial denaturation precludes assigning a molecular interpretation to shifts in either velocity or V max . In contrast, TSR analysis is unaffected by the presence of inactive molecules, and theoretically will always report reliably on the innate specificity properties of the active site per se – even if the measured signal emanates from a minor fraction of the carrier molecules visualized on an immunoblot. TSR analysis detects "relative" specificity shifts The TSR method is inherently capable of detecting new phenotypes that reflect relative specificity shifts favouring either test substrate (Fig. 4 ). Preliminary to these experiments, dual-substrate ratios were empirically adjusted so that control strains would exhibit superimposed [ 14 C] and [ 3 H] initial rate segments in their uptake time course (shown elsewhere, [ 5 , 6 ]). Plainly, the test cases in Figure 4 do not exhibit superimposed dual-isotope time courses, indicating two distinct Δ(TSR) phenotypes – one relatively favouring NA (Panel N302C), and the other relatively favouring GABA (Panel INS Ala 320). The Δ(TSR) phenotypes illustrated in Fig. 4 are distinct from one another (and distinct from the control) because there are relative differences in transition state binding energies (Equation 9) that can be visually represented as a change in the relative position of (separation between) the hypothetical binding isotherms for either substrate (Fig. 6D ). It is important to emphasize, however, that TSR analysis does not address the absolute magnitude of transition state binding energy shifts, nor the absolute magnitude of shifts in the binding curve midpoint ( shifts). This point is important, and can be illustrated by examining the implications of the figure 4 time courses in more detail. Calculated TSR values for the N302C and INS Ala 320 variants are, respectively about 2.5 and 16. That these numbers are both greater than 1 indicates (Equation 9) that the hypothetical transition state binding isotherm for GABA would lie to the left (i.e., like the red curve in Fig. 6D ) of the NA curve in both variants. If the measured TSR had been unity, then the hypothetical binding curves would be superimposed. If the measured TSR had been below 1, then the NA binding isotherm would lie to the left. Thus, the N302C time course with squares increasing faster than triangles (Fig. 4 , Panel N302C) does not indicate an absolute preference favouring NA over GABA, but rather a squeezing down of separation between midpoints on the hypothetical transition state binding isotherms for GABA and NA (relative to the separation in the Cys-less control–TSR = 8). The INS Ala 320 time course with triangles increasing faster than squares (Fig. 4 , Panel INS Ala 320) indicates an increase in the separation between midpoints on the hypothetical binding isotherms (relative to the separation in the wild type control – TSR = 4). Although the ability to measure only relative changes in specificity has limitations, the reader will appreciate that to a mathematical certainty no relative shift can occur in the absence of one or more absolute shifts. TSR analysis thus provides an analytical keyhole through which to scan [ 5 , 6 ] the protein fold, looking for Δ(TSR) phenotypes indicative of loci at which transition state stability can be controlled by amino acid side-chain structure. This conclusion cuts directly to the essence of what a translocation catalyst does – fairly respectable performance for a first-pass, rapid-screening methodology, which minimally can consist of as little as a single datum point for each variant transporter screened. It is to be noted that since absolute specificity changes can occur in the absence of a relative specificity shift (i.e., equal displacement of the binding isotherms for both substrates), some catalytic residues may be detectable only by more complicated kinetic studies, or possibly through independent TSR experiments with structurally distinct substrate pairs. Since the TSR parameter is a constant that characterizes how the transition state interacts with a particular pair of substrates, different results may be expected with structurally distinct substrate pairs. However, the observation of a Δ(TSR) phenotype always means the same thing – there has been a change in the transition state stability for translocation of one or both substrates. TSR analysis enables a broad search for the seat(s) of catalytic power Apart from its delightful simplicity and self-correcting behaviour, the TSR (or rather the ability to observe Δ(TSR) phenotypes) is also attractive as a facile means of expanding interest in "coupled promoting motions" that are networked together in support of catalysis [ 11 ]. Such networks (i) are evolutionarily conserved, (ii) undergo conformational oscillations on the timescale of (in synchrony with) the catalyzed reaction, and (iii) collectively can make million-fold contributions to catalytic specificity (transition state stabilization) even though their locations are spatially distant from the active site in enzymes of known structure (e.g., dihydrofolate reductase [ 1 , 12 - 14 ]]; aspartate aminotransferase [ 15 ]). Inasmuch as Equation 8 says that specificity (k cat /K m ) is a function of transition state stabilization ( + Δ G b ), phenotypic changes in the TSR phenotype should report on structural perturbations that compromise as yet undiscovered networks that couple energetically to the transition state. Inquiry along this line follows up on a prominent message emerging from recent literature on enzymatic catalysis: structural elements delocalized from the active site can enhance catalytic power (k cat /K m ) by many orders of magnitude [ 1 , 11 ] – so that any understanding of enzymatic catalysis based on consideration of the active site in isolation may now be considered incomplete. This delocalization of catalytic power will in all likelihood be true of transport catalysis as well – but even more so since carriers lack a traditional active site (no covalent change in substrate structure). The catalytic power (specificity) of a carrier must therefore derive entirely from conformational motions that lead to tighter ligand binding in the transition state. This crucial catalytic increment in ligand binding energy could be localized within a binding pocket only to the extent that it is possible for a conformational transition to increase carrier-substrate complementarity without at the same time causing a change in conformational energy (structural stability). If conformational energy changes as the transition state forms, then one expects obligatory partitioning of transition state binding energy among multiple interactions (steric, electrostatic, hydrogen-bonding, or solvation forces) at highly delocalized positions throughout the protein fold. Since plasma membrane transport proteins consist mainly of bundled helices that exhibit rigid-body behaviour [ 16 , 17 ] it is unlikely that conformational remodelling of helix-helix interfaces could occur without changing conformational energy. Thus, localized control of translocation specificity (catalytic power) is also quite unlikely, and instead the determinants of specificity ought to be distributed rather broadly at dynamic interfaces throughout the helix-rich structure (a hypothesis that should be broadly testable by TSR scanning approaches [ 5 , 6 ]). "Alternating Access" vitiates feasibility of localized specificity control Carrier proteins exhibit a compact tertiary structure in which tightly bundled helical segments span the membrane in a serpentine zig-zag fashion with extensive helix-helix contacts throughout [ 18 , 19 ]. The conformational transitions of "alternating access" (i.e., the general mechanism by which carriers expose a binding site alternately to one side of the membrane and then the other) thus proceed with extensive rigid-body remodelling of helix-helix interfaces. At some point in the translocation process the initial Michaelis complex (CS) is converted to a transition state complex (CS ‡ ) with realization of additional binding energy (i.e., a change in the chemical potential of bound ligand), which creates catalysis. But what part(s) of the protein structure may be held to account for this pro-catalytic increment in binding energy? Although not concerned with catalysis per se, Tanford set down clear principles from which we can infer that the binding energy used for transition state stabilization should have two obligatory sources in a helix-rich translocation catalyst – one source being dynamic motions in the protein fold. Tanford understood that with "...both translocation and change in chemical potential [of bound ligand] occurring in synchrony ..." [ 20 ] via helical tilts and twists, "it is not possible to separate free energy changes attributable to direct bonding to the proteins from free energy changes attributable to rearrangement of the protein structure that may accompany the binding process." [ 21 ]. Indeed, Benkovic's recent work on dihydrofolate reductase has provided the first visualization (molecular dynamics simulation) of the dynamic processes by which spatially distal motions in the protein fold can be coupled synchronously with active site rearrangements to create greater transition state stability. Thus when distal, energy-changing, conformational motions occur in synchrony with (i.e., on the same timescale as) reconfiguration of the bound ligand (as with translocation or covalent structural change), then delocalized contributions to transition state stability must occur. Although the details may vary from case to case, the operable mechanisms will probably be conceptually similar to those that now have been visualized in dynamic simulations as "...coupled promoting motions extending throughout the protein and ligands, where promoting motions refer to equilibrium, thermally averaged conformational changes along the collective reaction coordinate leading to configurations conducive to the reaction." [ 1 ]. Importantly, the chance occurrence of a favourable dynamic coupling interaction would be accompanied by an evolutionarily selectable substrate specificity (k cat /K m ) shift, suggesting that delocalized coupled promoting motions should be the rule rather than the exception. Engineered structural manipulations that interfere with the operation of coupled networks should impact k cat /K m such that elements of these networks may be rapidly detectable by TSR analysis. Such use of TSR analysis prompts re-examination of philosophical issues concerning the efficacy of mutagenesis in structure-function analysis. The ambiguity of mutagenesis reflects a truth about catalysis Many, including this author, have cautioned that mutagenesis is associated with built-in thermodynamic constraints that produce confounding ambiguity when the stated desire is to use engineered structural perturbations as a means to identify residues of an active site [ 22 , 23 ]. However, it needs to be emphasized that Nature, also bound by thermodynamic constraints, relies continuously upon natural selection, taking meaningful advantage of the same ambiguity that the structure-functionist traditionally bemoans. This thermodynamic ambiguity provides that spontaneous mutations affecting structure at locations spatially distinct from the active site may nevertheless have pro-catalytic or anti-catalytic effects that become subject to natural selection. The evolutionary accumulation and coupling together of such pro-catalytic sites has produced now recognizable "networks of coupled promoting motions" that exist far from the active site, yet operate in synchrony with it to promote catalysis [ 1 , 11 ]. That catalysis [ 1 , 11 ] and energy transduction [ 20 - 22 ] appear to rely upon coupled motions in the protein fold raises a question as to whether the structure-function field might benefit from a change in its outlook on the ambiguous characteristics of mutagenesis, henceforth treating ambiguity as a friend that can reveal the location of coupled networks. Widely perceived as a shortcoming, this ambiguity turns out to be an accurate reflection of how Nature uses the protein fold to boost catalytic power. It simply is not the case that a kcal of transition state stabilization emanating from a few residues in the active site is worth (by some visceral rationale) more than a kcal of transition state stabilization emanating from the protein fold. Conclusions TSR analysis is a remarkably simple dual-substrate competition assay used to define the TSR phenotype of a translocation catalyst. The TSR phenotype is highly reliable because the TSR parameter is a constant , which renders its value independent of several common variables that, particularly in high-throughput screening, may be poorly controlled or only roughly estimated. A change in the TSR phenotype requires an underlying change in transition state stability (or synonymously an underlying change in catalytic specificity, catalytic power, catalytic efficiency, k cat /K m , or transition state energy barrier) for one or both of the competing substrates. TSR-scanning mutagenesis is thus expected to identify positions in the protein fold that make contributions to transition state stabilization (the essence of catalytic function). The technical simplicity of TSR analysis should enable broad testing of the hypothesis that in carrier proteins the seat of catalytic power will be delocalized along helix-helix interfaces that dynamically enhance structural stability by remodelling in synchrony with transition state formation, thereby promoting translocation catalysis in a manner analogous to recently described networks of coupled promoting motions that allow dynamic interactions in the protein fold to enhance transition state stability in enzymatic catalysis [ 1 , 11 ]. Methods Strains and plasmids E. coli strain SK35 is a gabP-negative host strain [ 8 ]. E. coli SK45 is a gabP-negative strain harbouring the expression plasmid, pSCK380 [ 8 ]. E. coli SK11 expresses a histidine-tagged Cys-less derivative of GabP [ 5 ]. E. coli SK105 expresses the Cys-less GabP as a GabP-LacZ hybrid from the plasmid pSCK380Z [ 24 ]. Materials GABA was from Sigma (St. Louis, MO, U.S.A.); NA was from Research Biochemicals International (Natick, MA, U.S.A.); Miller's Luria Broth medium was from Gibco-BRL (Grand Island, NY, U.S.A.); agar and ampicillin were from Fisher Biotech (Fair Lawn, NJ, U.S.A.); bicinchoninic acid protein determination reagents were from Pierce (Rockford, IL, U.S.A.); cellulose acetate filters (0.45 um; 25 mm) were from either Millipore (Bedford, A, U.S.A.) or MicronSep, (cellulosic; 0.45 um, 25 mm) from OSMONICS Inc. (Minnetonka, MN, U.S.A.); [ 3 H] nipecotic acid (40 Ci/mmol) was a custom synthesis from Moravek Biochemicals (Brea, CA, U.S.A.); [ 14 C]GABA was from Dupont-New England Nuclear (Boston, MA, U.S.A.); Ultima Gold ™ scintillation cocktail was from Packard BioScience (Meriden, CT, U.S.A.); the anti-Penta-His monoclonal antibody was from QIAGEN (Valencia, CA, U.S.A.); the goat anti-mouse alkaline phosphatase antibody was from Kirkegaard and Perry Laboratories (Gaithersburg, MD); isopropyl-β-D-thiogalactopyranoside (IPTG) was from Anatrace (Maumee, OH); Immobilon-P™ transfer membranes (0.45 um) were from Millipore (Bedford, MA, U.S.A.); the chemiluminescence reagent for alkaline phosphatase detections, Western Lightning, was from Perkin-Elmer Life Sciences, Inc. (Boston, MA, U.S.A. E. coli culture conditions E. coli strains were recovered by streaking glycerol stocks (-80°C) to single colonies on LB agar supplemented with ampicillin (100 μg/ml). LB broth supplemented with ampicillin (100 μg/ml) was inoculated by picking from a single colony and then shaken overnight (16 h) at 37°C. Overnight cultures were diluted 100-fold into fresh medium, shaken for 2 hours at 37°C prior to adding IPTG (0.2 mM), and shaking for two hours more. Cells were then harvested by centrifugation, washed twice with ice-cold KPi Buffer (100 mM potassium phosphate, pH 7.0), and resuspended to 2 mg protein/ml in the same buffer (20 percent of the original culture volume). Cultures treated in this manner are hereafter referred to as washed cells . Washed cells were stored on ice, and then equilibrated to 30°C in a heat block (25 minutes) prior to initiating transport reactions. Cultures treated in this manner are hereafter referred to as prewarmed cells. Transport conditions Transport reactions were initiated by mixing 20 μl of a 5-fold concentrated substrate stock solution with 80 μl of prewarmed E. coli cell suspension. TSR analysis of the single-Cys GabP variant, N302C, was performed using a substrate stock containing 35 μM [ 3 H]NA (2.1 μCi/ml) and 15 μM [ 14 C]GABA (0.3 μCi/ml). This solution was found to support equal rates of [ 14 C] and [ 3 H] label accumulation in the Cys-less GabP control strain [ 5 ]. TSR analysis of the GabP variant, INS Ala 320, was performed using a substrate stock containing 20 μM [ 3 H]NA (1.2 μCi/ml) and 30 μM [ 14 C]GABA (0.6 μCi/ml). This solution was found to support equal rates of [ 14 C] and [ 3 H] label accumulation by the wild type GabP [ 6 ], which contain 5 Cys residues. A 60 or 120 Hz metronome was used to time the reactions, which were rapidly quenched with 1 ml of ice-cold Stop Solution ( KP i Buffer containing 20 mM HgCl 2 ), and then vacuum-filtered (0.45 micron pore). The reaction vessel was then rinsed with 1 ml of Wash Buffer ( KP i Buffer containing 5 mM HgCl 2 ) and this was applied to the same filter. Finally, 4 ml of the Wash Buffer was applied to the filter. The filter was then dissolved in Ultima Gold™ scintillation cocktail and the [ 3 H] and [ 14 C] radioactivity (disintegrations per minute, dpm) analyzed with a Packard BioScience Tri-Carb 2900 TR liquid scintillation counter using stored Ultima Gold™ quench curves and automatic quench compensation. Standard curves for GabP-independent uptake The GabP-negative E. coli strain, SK45, was grown and prepared for transport experiments as indicated above except that a series of different cell suspensions were prepared spanning a range from 20 to 125 percent of that described above. Dual-label transport experiments carried out with these different suspensions produced a linear standard curve for GabP-independent "background uptake" of [ 3 H]NA and [ 14 C]GABA as a function of protein content. The protein content of GabP-positive test strains could then be used to obtain the appropriate background subtraction by extrapolation from the standard curve. Test strain protein contents were always similar (within 10 percent) because when cell pellets were resuspended steps were taken to assure approximately equal turbidity levels. Statistics Replicate (n = 3), background-corrected, dual-substrate uptake velocities (moles/time) were inferred from measured disintegration rates for filter-bound [ 3 H]NA and [ 14 C]GABA. The background-corrected velocity replicates were used to calculate replicate TSR values (Equation 6) from which the mean TSR and standard errors (S.E.M.) shown in the figures were obtained. Plasma membrane vesicle preparation and immunoblotting E. coli cells were probe-sonicated to produce plasma membrane vesicles, which were then separated from soluble components and unbroken cells by differential centrifugation as previously described [ 5 ]. Plasma membrane proteins were resolved by SDS-PAGE, and transferred to PVDF membranes, which were blocked and then probed with a primary antibody (anti-polyhistidine monoclonal) and secondary antibody (anti-mouse conjugated to alkaline phosphatase) as previously described [ 5 ]. Immunoblots were developed with a chemiluminescent alkaline phosphatase substrate (Western Lightning™), and imaged with a cooled CCD camera (Kodak Image Station 440 CF). Chemiluminescent intensities were quantified with Kodak 1D software. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535561.xml |
526251 | Inter-residue distances derived from fold contact propensities correlate with evolutionary substitution costs | Background The wealth of information on protein structure has led to a variety of statistical analyses of the role played by individual amino acid types in the protein fold. In particular, the contact propensities between the various amino acids can be converted into folding energies that have proved useful in structure prediction. The present study addresses the relationship of protein folding propensities to the evolutionary relationship between residues. Results The contact preferences of residue types observed in a representative sample of protein structures are converted into a residue similarity matrix or inter-residue distance matrix. Remarkably, these distances correlate excellently with evolutionary substitution costs. Residue vectors are derived from the distance matrix. The residue vectors give a concrete picture of the grouping of residues into families sharing properties crucial for protein folding. Conclusions Inter-residue distances have proved useful in showing the explicit relationship between contact preferences and evolutionary substitution rates. It is proposed that the distance matrix derived from structural analysis may be useful in aligning proteins where remote homologs share structural features. Residue vectors derived from the distance matrix illustrate the spatial arrangement of residues and point to ways in which they can be grouped. | Background The large number of protein crystal structures available has naturally led to statistical analyses of protein folding and protein interaction in the hope that these will point to intrinsic residue characteristics and therefore serve as aids in protein fold and interaction prediction. The first such analysis was performed by Miyazawa and Jernigan [ 1 - 3 ], where a statistical protein folding potential, the MJ matrix, was deduced from residue contact propensities in a set of monomeric protein crystal structures. The MJ matrix has been used in various in silico folding experiments, reviewed by Jernigan et al [ 4 ], and shown to point to the essentially hydrophobic nature of folding interactions [ 5 ]. An analysis of the MJ matrix has enabled the reduction in sequence complexity by grouping residues into families [ 6 ]. A more detailed study of crystal interactions focusing on hydrogen bond distributions has resulted in mean force potentials that have been successfully used in ligand prediction [ 7 ]. It is reasonable therefore to conclude that the statistical approach has pointed to an intrinsic residue:residue potential. In this study we will show that crystal contact statistics can be used to define an inter-residue similarity score that is strongly correlated with an evolutionary substitution cost. As this score is not based on aligning homologous proteins it can serve as a complement to similarity scores derived from substitution matrices when faced with the problem of aligning remotely homologous but structurally similar proteins. The observation that evolutionarily close residues appear to have similar contact propensities leads us to postulate that the extent of similarity between the contact propensities corresponding to two particular amino acids is related to the ease with which these amino acids can be mutated into each other. We define the contact propensity as , where N ij is the number of possible pairings between residue type i and residue type j and C ij is the number of these parings corresponding to residues in contact. Only non-neighbouring residues on the protein chain are considered and a pair of residues is defined to be in contact if any of their side chain atoms are within a given distance of each other. The difference in contact propensities for two amino acid types can be measured by their rms difference and we define as our amino acid difference measure or distance matrix. If we have really got a measure of the distances between residue types then it should follow that residues sharing physical properties are close together. More crucially, we expect that residues that are distant according to D(P) will be difficult to mutate into one another and vice versa. This is because the factors involved in determining mutation rates are dominated by those affecting the structural integrity of the protein. Such factors are residue hydropathy, size, charge and etc. Substitution matrices such as PAM and Blosum are determined from mutation rates in aligned protein sequences [ 8 , 9 ]. We can define an amino acid distance matrix in a similar way to D ij above. That is, , where S is the substitution rate matrix. We show below that D ( P ) is indeed strongly correlated with D ( S ). It must be stressed that D ( P ) and D ( S ) are independently derived, with one based on structure and the other on sequence alignment. Their strong correlation is indicative of the validity of our definition of inter-residue distance. Relating amino acids through a structurally defined distance measure should provide a useful tool for aligning remotely homologous protein sequences. Also, a distance measure naturally leads us to look for a vector representation of the amino acids. In much the same way as average hydropathy plots are useful in structural analysis we expect that average vector profiles will also pick out various structural features. Given a vector for each residue type we can visualise the residues in some abstract space and look for natural groupings of residues and thereby find ways of reducing the effective number of residues. Results A representative set of crystal structures was compiled from the PDBselect25 database [ 10 ], which contains structures sharing at most 25% sequence homology. We made sure that side chain coordinates were defined and restricted chain lengths to be greater than 50 and less than 500 residues long. In short we arrived at 1073 structures and performed the statistical analysis on these. Residues are held to be in contact if any of their respective side chain atoms are within a given distance of each other. Only residue pairs that are not neighbours along the chain are considered in the analysis of intra-molecular contacts. As explained above the contact propensities can be converted to a distance matrix D ( P ). If this matrix is really a measure of residue similarity then we should be able to correlate it with an equivalent matrix constructed from an evolutionary substitution rate matrix. In what follows we will take PAM250 as the substitution matrix. In Figure 1a we show the contour plots of D ( S ) in the top triangle and D ( P ) in the bottom triangle for a contact cut-off of 4.5Å, where the pearson correlation (r) is maximal, with r = 0.82. See additional table 1 for explicit values of P and D ( S ). The correlation can be seen explicitly in Figure 2b . The extent of correlation is roughly constant over a large range of cut-offs (4~8Å) and only drops when the cut-off is small and contacts are rare or when the cut-off is so big that non-interacting residues are scored, see Figure 1c . We expect that, due to the wide range of side chain sizes, a full atom representation is more accurate than a centroid representation and we find that the centroid D ( P ) is consistently less well correlated with D ( S ), peaking at r = 0.64 for a cutoff of 8Å, see Figure 1c . We have defined inter-residue distances and this implies that there must be a vector representation for the residues. In this case the distance matrix will be , where are the residue vectors. Explicitly, the vectors are defined such that is minimal. When these vectors are derived it becomes clear that Cysteine is quite separate from the other residues in this property space and this maybe due to the unique role played by Cysteine in stabilising folds. Though it must be made clear that the distance matrix is independent of the frequency of an amino acid contacting its own kind and therefore does not count Cysteine bridges in the structures. Without Cysteine the distance matrix can be projected onto a plane i.e. the vectors can be taken to be two-dimensional and this vector space is illustrated in Figure 2a . It is a reasonable postulate that neighbouring residues share physical characteristics and we see similar residue groupings in a standard amino acid Venn diagram [ 11 ]. Indeed the vector grouping may serve as a way of reducing the effective amino acid number [ 6 ]. It is illuminating to compare vector spaces derived from other statistical analyses. The substitution rate vector space Figure 2b is, as expected, similar to that of the contact propensity vector space, though in D ( P ) residues with opposite hydropathies tend to be further apart. This is consistent with hydropathy playing a pivotal role in protein folding. In contrast, the MJ energy matrix vector space is shown in Figure 2c and here the residues effectively lie on a line, which is in accordance with Li et al [ 5 ], where the MJ matrix was shown to be dominated by its principal eigenvector reduction. However, for the contact propensity and evolutionary substitution rate spaces, a lot of information is lost in such a linear projection and our analysis clearly points to a higher dimensional representation of the residues. Nonetheless, to make a concrete comparison of our vectors with existing scalar representations of amino acid properties we are forced to project our vectors onto a line. See additional table 2 for the explicit vector components of the contact propensity, substitution rate and MJ energy matrices. The dominant driving force of folding, at least in defining the crude fold, is hydrophobicity and it is apparent that residues with similar hydrophobicities are grouped together. It also seems that residues of similar size tend to be close in this space. To make a direct comparison between existing residue scales and our vectors we can project the residue vectors onto a line. Here the amino acid scalars, one-dimensional vectors, d i are defined such that is minimal. We find that these distance matrix derived scalars have a correlation of 0.65 with the Kyte-Doolittle hydrophobicity scale [ 12 ] and a correlation of 0.53 with an amino acid volume scale [ 13 ]. It is clear therefore that the residue vectors capture a combination of factors determining protein folding. It is worth noting that a scalar reduction of the distance matrix can be got by a principal eigenvector analysis. In a principal eigenvector reduction of the contact propensity matrix we have P ij = λ e i e j , where λ is the principal eigenvalue and e i is the principal eigenvector, and consequently our distance matrix has a scalar representation, . It is not surprising that the eigenvector is closely related to our scalar, in fact r ( e , d ) = 0.98. There are many hydrophobicity scales in the literature [ 14 ] and some are remarkably similar to our scalar amino acid representation, for example r = 0.95 for Wertz & Scheraga scale [ 15 ]. However, the highly correlated scales are derived from residue burial statistics in protein structures and are therefore not independent of our statistic. Discussion We have generated full atom residue:residue contact propensity profiles for intra-molecular interactions from a non-redundant crystal structure database. Recasting the contact propensity matrix as a distance matrix we see that close residues are those with a low evolutionary substitution cost. The structure derived distance measures can serve as additional scores when aligning proteins where remote homologs share structural features. The distance matrix led us naturally to derive effective residue vectors. We found that residues sharing similar physical characteristics, such as hydrophobicity and volume, are grouped together. In contrast to the MJ matrix analysis, we find that a scalar representation for the residues is inadequate to capture the complexity of the propensity distance matrix. The most successful scalar representation for the amino acid residues has been the hydropathy scale. Representing a sequence as a smoothed hydropathy profile through wavelet analysis or simple averaging has resulted in many effective analytical tools, such as periodic structure prediction [ 16 ], remote homology analysis, helix prediction [ 14 ], transmembrane prediction [ 17 ] etc. It is then probable that a higher dimensional vector representation of the amino acids may lead to a more subtle sequence analysis. The distance matrix may also serve as an additional tool in sequence alignment as it gives one a measure of the structural cost of residue mutation and this is an idea we hope to pursue in a future study. Conclusions In this study we have shown that inter-residue distance matrices and residue vectors allow us to make an explicit connection between amino acid interaction preferences observed in protein structures and amino acid evolutionary substitution costs. When problems are encountered with aligning structurally related proteins that are remote homologs then the structurally defined distance matrix may prove to be an effective supplement to existing substitution rate derived matrices. The distance matrix leads naturally to an amino acid vector representation. Projecting the vectors onto a two-dimensional plane illustrates ways in which the amino acids can be grouped and their effective number thereby reduced. Methods The database used in the present study was compiled from the PDBselect25 [ 10 ] list of representative proteins with known crystal structure that share less than 25% sequence homology. The structural coordinates were downloaded by automated ftp from the NCBI protein data bank. All programmes were written in C, compiled with Metrowerks CodeWarrior and run on a PC. In brief, the contact propensity statistics were compiled by reading the amino acid sequence and atomic coordinates for the specified chain of each pdb structure file in turn. The number of possible pairings of amino acid type i with amino acid type j , N ij were counted together with the number of these pairings corresponding to a pair with side chain atoms within a given distance of each other, C ij . The contact propensity matrix is given by . The residue vectors were defined such that is minimal. The minimisation was carried out by a standard Newton-Raphson steepest descent iteration. Supplementary Material Additional table 1 Contact propensities and distance matrix derived from the structural database with contact cut-off set at 4.5Å. Click here for file Additional table 2 Two dimensional residue vector components derived from the contact propensity distance matrix, the PAM250 distance matrix and the MJ distance matrix. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC526251.xml |
544398 | New approaches to eliciting protective immunity through T cell repertoire manipulation: the concept of thymic vaccination | Conventional vaccines afford protection against infectious diseases by expanding existing pathogen-specific peripheral lymphocytes, both CD8 cytotoxic effector (CTL) and CD4 helper T cells. The latter induce B cell maturation and antibody production. As a consequence, lymphocytes within the memory pool are poised to rapidly proliferate at the time of a subsequent infection. The "thymic vaccination" concept offers a novel way to alter the primary T cell repertoire through exposure of thymocytes to altered peptide ligands (APL) with reduced T cell receptor (TCR) affinity relative to cognate antigens recognized by those same TCRs. Thymocyte maturation (i.e. positive selection) is enhanced by low affinity interaction between a TCR and an MHC-bound peptide in the thymus and subsequent emigration of mature cells into the peripheral T lymphocyte pool follows. In principal, such variants of antigens derived from infectious agents could be utilized for peptide-driven maturation of thymocytes bearing pathogen-specific TCRs. To test this idea, APLs of gp 33–41 , a D b -restricted peptide derived from the lymphocytic choriomeningitis virus (LCMV) glycoprotein, and of VSV8, a K b -restricted peptide from the vesicular stomatitis virus (VSV) nucleoprotein, have been designed and their influence on thymic maturation of specific TCR-bearing transgenic thymocytes examined in vivo using irradiation chimeras. Injection of APL resulted in positive selection of CD8 T cells expressing the relevant viral specificity and in the export of those virus-specific CTL to lymph nodes without inducing T cell proliferation. Thus, exogenous APL administration offers the potential of expanding repertoires in vivo in a manner useful to the organism. To efficiently peripheralize antigen-specific T cells, concomitant enhancement of mechanisms promoting thymocyte migration appears to be required. This commentary describes the rationale for thymic vaccination and addresses the potential prophylactic and therapeutic applications of this approach for treatment of infectious diseases and cancer. Thymic vaccination-induced peptide-specific T cells might generate effective immune protection against disease-causing agents, including those for which no effective natural protection exists. | Introduction Vaccination has improved healthcare by providing the most cost effective means to prevent disease on a global basis [ 1 , 2 ]. Since the first safe vaccine against smallpox infection was introduced by Sir Edward Jenner more than 200 years ago [ 3 ], a myriad of killed or live viral and bacterial vaccines as well as subunit (i.e. component) vaccines have been developed and proven to be highly effective [ 2 ]. The traditional approach to vaccine development from the early 1950's until today has been based most commonly on administration of weakened versions of disease-causing agents or certain of their components with appropriate adjuvants. In this way, successful vaccines against key viruses that cause acute infectious diseases of childhood (e.g. poliovirus, measles virus, mumps, rubella, chicken pox, etc.) have been developed. These vaccines induce peripheral T and B lymphocyte memory responses, affording protection against any future attack by disease-causing agents should it occur. To date, the fundamental principles of vaccination have remained unchanged. The overriding concept for each vaccine has been the establishment of protective immunity largely due to antigen-specific T cell expansion, facilitating subsequent proliferation and differentiation of CD8 cytotoxic effector T cells and CD4 helper T cells capable of producing antiviral cytokines and chemokines (Fig. 1A ). CD4 T cells activate B cells to generate neutralizing antibodies, offering protection against viral attachment/translocation or bacterial toxins, etc. [ 4 , 5 ]. As neutralizing antibodies have been the subject of recent reviews [ 6 - 9 ], they will not be considered further here. Figure 1 Thymic vaccination versus conventional vaccines. A. Conventional vaccines act on the mature peripheral lymphoid pool, in particular expanding existing T cells directed against the immunogen (blue square) derived from the disease-causing agent. Following subsequent infection, the T cell recognizes the pathogen, proliferates, mediates effector function and cytokines leading to immune response and elimination of the disease. For simplicity, the B lymphocyte response is not shown. B. Thymic vaccination offers a way to alter the primary T cell repertoire through exposure of immature thymocytes to APL with reduced TCR affinity relative to cognate antigens recognizing those TCRs. Thymocyte maturation (i.e. positive selection) is enhanced by the low affinity interaction between a TCR and an MHC-bound APL (green ribbon) in the thymus, with subsequent emigration of mature cells into the peripheral T lymphocyte pool. Those peripheral T cells can respond to cognate antigen (red triangle). Thus, variants of cognate antigens derived from infectious agents, tumors, etc. could be employed for peptide-driven maturation of thymocytes bearing pathogen-specific TCRs. However, conventional vaccines have their pitfalls. Microorganisms including HIV and malaria, among others, may alter their antigenic proteins through rapid mutagenesis, thereby hindering cytotoxic T lymphocyte (CTL)-based immunity, exploiting holes in the T cell repertoire, and/or misdirecting both cellular and humoral responses away from key cell-binding receptors to pathogen components which cannot provide epitopes for neutralizing antibodies [ 10 - 13 ]. The fundamental ways in which the immune system recognizes and responds to antigen are identical, irrespective of the source of molecules; microbes, allografts, allergens, autoantigens, or tumor antigens are approached in a similar manner. It follows that immune-based therapies that focus on promoting the quantity and quality of the immune response should be beneficial in the treatment of a range of diseases, especially persistent viral infections and cancer. Finding ways to increase the pool of mature, primed T cells that are able to fend off disease is a goal for future vaccine development. In this respect, a novel strategy for vaccine design, termed "thymic vaccination" has been considered to alter the T cell antigen receptor repertoire centrally via altered peptide ligands (APL). APL derived from infectious agents or tumor antigens, with low affinity to the TCR could, in principle, mediate positive selection and export of specific T cells from the thymus [ 14 ]. As such, these APL might be candidates for manipulating the thymic repertoire in vivo , controlling the generation of naive T cells and hence, subsequent memory development within the peripheral lymphoid compartment. Through repertoire manipulation, it should be possible to sculpt the specificity and diversity of disease-fighting cells. This thymic vaccination approach aims to deliver, by parenteral administration, positively selecting APL of cognate antigens into the thymus, eliciting maturation of thymocytes with desired TCR specificities at the level of thymic repertoire development (Fig. 1B ). Note how engendering T cells with anti-viral specificity requires administration of an APL, a weaker affinity ligand for a given TCR to encourage maturation and emigration from the thymus. Expanding T cell repertoires has enormous potential in aiding the organism's fight against infections or in affording tumor immunity. This strategy is principally different from conventional "peripheral" vaccination, which leads to proliferation of pre-existing mature T cells but does not alter the repertoire through creation of T lymphocytes with new T cell specificities. Thymic vaccination, by contrast, will alter the thymic repertoire to create desired T cell specificities. Moreover, a key feature of thymic vaccination is that it should be capable of directing the immune response towards those non-mutable components of proteins derived from infectious agents and tumors and away from misguiding cues that are part of pathogen or cancer chicanery. The rationale for this approach and the advantages over traditional vaccines are described below. Discussion Generation of T cell repertoire T cells bearing a highly diverse αβ T cell receptor (TCR) repertoire develop in the thymus from stem cells originating in the hemopoietic tissues [ 15 - 17 ]. On entering the thymus through the cortico-medullary junction, these cells migrate to the subcapsular epithelium and undergo a complex differentiation process in the thymic cortex and then in the medulla, involving proliferation, expression of accessory molecules, rearrangement of TCR genes and selection of the TCR repertoire (reviewed in [ 18 , 19 ]). T cell development does not occur autonomously but requires signals from non-hematopoietic stromal cells including various types of thymic epithelial cells (TECs) which show profound phenotypic differences between cortex and medulla. The thymic epithelium provides a broad spectrum of signals for thymocyte proliferation, differentiation and selection. Thymic nurse cells, expressing high levels of MHC class I and II molecules and also containing antigen processing machinery, are involved in thymocyte selection, mediated by peptide/MHC (pMHC) ligands. Pools of self-peptides bound to MHC molecules control both positive and negative selection (reviewed in [ 20 ]). Thymocytes that carry TCRs having low-affinity interactions with MHC-bound self-peptides are positively selected, and are exported into the pool of mature peripheral lymphocytes. In contrast, thymocytes bearing those TCRs that recognize self-peptides with "high" affinity are eliminated primarily upon interaction with dendritic cells [ 19 , 21 ]. A schematic representation of thymocyte development [DN (CD4 - CD8 - double negative) → DP (CD4 + CD8 + double positive → SP (CD4 + CD8 - , CD4 - CD8 + single positive)] is depicted in Fig. 2 . Figure 2 General scheme of thymocyte selection and emigration to the peripheral lymphoid compartment. CD4 - CD8 - (DN) cells expressing pre-TCR undergo divisions and become αβTCR + CD4 + CD8 + (DP) at which stage they interact with self-peptides presented by class I and II MHC molecules expressed on thymic stromal cells. Those thymocytes whose TCRs interact with high affinity to pMHC undergo apoptosis, while those bound to pMHC with low affinity mature to become MHC class I-restricted CD8 + SP or class II-restricted CD4 + SP cells. These mature thymocytes then emigrate to the periphery aided by different egress-related mechanisms. TCR/MHC/peptide interactions control thymocyte selection The avidity of pMHC/TCR interactions plays a major role in T cell recognition [ 14 ]. Crystal structure analyses have revealed fine details about peptide conformation inside the peptide binding groove of MHC molecules and the amino acid residues interacting with the TCR Vα and Vβ domains including their CDR3 loops [ 22 - 25 ]. Peptide analogs of antigenic peptides with substitutes at amino acid residues, APL, have been shown to generate qualitatively different T cell responses compared with those produced by the antigenic peptides themselves [ 26 ]. Some APL act as TCR antagonists capable of positively selecting [ 27 , 28 ], negatively selecting [ 29 ], or otherwise altering [ 30 ] selection of thymocytes. TCR-transgenic mice provide useful tools for studies of peptide-based thymocyte selection. For example, in N15 transgenic mice carrying a TCR specific for the vesicular stomatitis virus nucleoprotein octapeptide N 52–59 (VSV8), VSV8 triggers negative selection of DP thymocytes in the context of H-2K b . In contrast, a weak agonist peptide variant, identical to the VSV8 peptide except for substitution of leucine for valine at the p4 peptide residue, termed L4, induces positive selection [ 31 ]. Similarly, in the P14 TCR transgenic mouse which expresses a TCR specific for the D b -restricted immunodominant LCMV epitope gp 33–41 [ 32 ], the cognate gp 33–41 peptide causes negative selection due to high affinity pMHC/TCR interactions. However, certain mutations of amino acid residues in the gp 33–41 peptide affects the fate of thymocyte development in fetal thymic organ culture (FTOC) leading to positive selection P14-bearing thymocytes [ 33 , 34 ]. In yet a third TCR transgenic mouse model, F5, where the TCR recognizes a nucleoprotein peptide of the influenza virus NP 366–379 in the context of H-2D b , a peptide antagonist mediates positive selection in FTOC [ 35 , 36 ], whereas the cognate peptide itself leads to deletion of DP thymocytes [ 37 ]. Positive selection and emigration of antigen-specific thymocytes in vivo is mediated by APL of viral CTL epitopes Design and initial characterization of APL derived from the viral epitopes gp 33–41 and VSV8 To experimentally test the concept of thymic vaccination, we have designed variants of gp 33–41 and VSV8 peptides with substitutions at residues interacting with the TCR aimed at reducing TCR-pMHC affinity via diminution of the number of atomic contacts between the peptide and the TCR. Subsequently, we examined the effects of these APL on thymocyte maturation and emigration in vivo in two well-defined TCR-transgenic mouse systems. In the case of gp 33–41 cognate peptide, amino acids at the peptide positions p4 (Tyr, Y) and p6 (Phe, F) were modified to Ser (S) and Ala (A), respectively, based on the crystal structure of the gp 33–41 /H-2D b complex showing exposure of the side chains of these amino acid residues to the solvent and hence, TCR accessibility [ 38 , 39 ]. No change was made in the peptide anchor residues that occupy the binding pockets of H-2D b , thus ensuring proper peptide presentation in the context of MHC. In the other less extreme peptide variant of gp 33–41 , Ala (A) at p7 was substituted with Glu (E). For the VSV8 peptide, the weak L4 agonist with the substitution of Leu (L) for Val (V) at the p4 peptide residue has been employed. The crystal structure of the N15 TCR-VSV8/K b complex as well as the space-filling models of K b in complex with VSV8 and L4 peptides are shown in Fig. 3 . The centrally positioned p4 peptide residue, whose atoms are shown in green in the space-filling model, faces up to the solvent and interacts with the N15 TCR. In spite of the subtle differences in the structure of VSV8/K b as compared to L4/K b , these focal changes (p4 and Lys 66 on the α1 helix of H-2K b ) determine the outcome of thymic selection [ 31 ]. In a similar way, D b / gp 33–41 vs. APL in which amino acid residues at p4 and p6 are altered, differentially affect development of thymocytes expressing the P14 TCR (data not shown). Experimental data using these APL (Y4S/F6A and A7E) for studies of thymocyte selection and emigration as applied to the thymic vaccination approach are summarized below (for the original work, see [ 40 ]). Figure 3 Structural basis of APL design. Crystal structure of N15 TCR-VSV8/K b (left panel) [57]. The figure was rendered in MOLSCRIPT [58]. The TCR β chain is shown in gold, the TCR α chain in blue, K b in magenta and β2M in red. Note the VSV8 peptide in green with the arrow pointing to the p4 valine side chain. Space-filling models of K b in complex with VSV8 peptide and with its L4 variant (right panel) [31]. The K b is shown as a GRASP surface [59] in magenta with peptide in CPK format and p4 residue atoms in green. The binding of the APL to the MHC class I molecules using RMA-S cells confirmed that amino acid substitutions at peptide residues interacting with the TCR did not affect peptide binding and, by extension, peptide presentation to T cells. A series of experiments was next performed to evaluate the functional potential of the APL to stimulate peripheral T cells in mice injected with the variant peptides. Results of both proliferation and cytokine secretion assays using mature T cells from P14Rag2 -/- lymph node and spleen showed a response to the high TCR affinity cognate peptide gp 33–41 , but not to the Y4S/F6A variant peptide. In support of this observation, tetramers of H-2D b in complex with the Y4S/F6A peptide did not bind to SP CD8 thymocytes from P14 Rag2 -/- mice at any tetramer dilution, as judged by immunofluorescence analysis, whereas high fluorescence intensity staining was detected using tetramers of H-2D b in complex with the gp 33–41 peptide. The A7E/H-2D b tetramer gave intermediate staining. These data suggested that the Y4S/F6A mutant must interact with the P14 TCR with extremely weak affinity, if at all. Effect of APL administration on thymocyte development in vivo Injection of the cognate viral peptides gp 33–41 and VSV8 leads to negative selection of P14- and N15TCR-bearing thymocytes, respectively, due to relatively high affinity pMHC/TCR interactions [ 31 , 34 ]. In vivo administration of gp 33–41 in P14Rag2 -/- mice and VSV8 injection into N15Rag2 -/- mice resulted in pronounced depletion of DP thymocytes. Surprisingly, injection of P14 Rag2 -/- mice with the Y4S/F6A peptide mutant resulted in a significant increase in the total number of thymocytes as well as the DP thymocyte subpopulation, while the A7E variant had no effect on thymocyte counts. As with Y4S/F6A in the P14Rag2 -/- system, injection of L4 in the N15Rag2 -/- mouse preserved the DP thymocytes and led to an increase in total thymocyte counts. The unusual increase in the number of DP thymocytes following exposure to Y4S/F6A peptide was not due to cellular proliferation and attendant DNA synthesis as examined by in vivo BrdU incorporation assay. Rather, Y4S/F6A peptide administration prevented apoptosis as confirmed by staining of thymocytes with anti-Annexin V mAb. To more directly test this hypothesis, we injected P14 Rag2 -/- mice with mixtures of the negatively selecting cognate peptide gp 33–41 plus the Y4S/F6A APL. Increasing the amount of Y4S/F6A peptide in the injection mixture resulted in a higher number of total and DP thymocytes. Thus, we infer that the Y4S/F6A variant may compete with other endogenous negatively-selecting peptides for binding to H-2D b molecules expressed on thymic stroma either by binding to "empty" surface MHC class I molecules or, perhaps, by a cross-presentation mechanism [ 41 ]. That A7E fails to afford positive selection and interacts significantly with the P14 TCR in D b /A7E tetramer binding assays suggest that this APL does not reduce TCR binding affinity sufficiently to stimulate positive selection. Y4S/F6A and L4 peptides mediate positive selection and emigration of thymocytes in irradiation chimeras The numerically small population of antigen-specific recent thymic emigrants (RTE) makes thymic selection/emigration studies difficult even with the use of TCR transgenic mice. To resolve this issue, we employed irradiation chimeras of congenic mouse strains (expressing the CD45.1 marker in B6 and CD45.2 in P14 and N15 transgenic mice) to determine whether interactions between the low affinity ligands, Y4S/F6A and L4, and their specific TCRs would result in thymic positive selection and subsequent emigration from the thymus. For this purpose, lineage-minus BM precursors of P14 – or N15- TCR transgenic Rag2 -/- mice (donor) were injected into irradiated congenic B6 mice (recipient) and the development of donor-type cells was monitored weekly by immunofluorescence staining and multicolor FACS analysis [ 40 ]. Following determination of the parameters related to the time period of appearance and the number of donor-type T cells in the chimeric thymus we administered the APL to the recipients at 3–4 wks after donor BM injection and assessed whether such exposure might influence the subsequent selection and emigration processes of donor thymocytes. The numbers of donor DP and SP CD8 + thymocytes in irradiation chimeras injected with Y4S/F6A were greatest, suggesting that this ligand mediated positive selection of P14 Rag2 -/- -specific T cells. Similarly, in N15 Rag2 -/- -B6 irradiation chimeras injected with L4, the numbers of both DP and SP CD8 donor thymocytes were highest, consistent with positive selection. In contrast, injection of either gp 33–41 or VSV8 cognate viral peptides into irradiation chimeras led to thymocyte depletion by negative selection. Analysis of the peripheral lymphoid organs in these chimeras by triple color immunofluorescence with anti-CD45.2, anti-CD8α and anti-TCR-specific mAbs showed the greatest number of donor-type CD45.2 + CD8 + Vα2 + T cells in the lymph nodes of Y4S/F6A -injected chimeras (2–3 fold over PBS-injected control mice), suggesting that donor-type thymocytes expressing the P14 TCR had developed in the presence of Y4S/F6A, matured and emigrated to the lymph nodes. A similar increase in the donor cell numbers were observed up to 9 weeks after injection of Y4S/F6A peptide. Positive selection was also evident in N15 Rag2 -/- -B6 irradiation chimeras injected with the L4 variant. In this case, higher CD8 + Vβ5.2 + N15 TCR transgene donor-type T cell numbers were observed both in lymph nodes and spleens. The functional analysis of donor-type CD8 + lymph node T cells in irradiation chimeras injected with the positively selecting Y4S/F6A or L4 peptides showed approximately two-fold higher proliferation levels in response to the cognate peptides gp 33–41 and VSV8, respectively, in vitro , compared to cells from PBS control-injected chimeric mice, reflecting the two-fold difference in the number of donor-type CD8 + T cells in lymph nodes of chimeras injected with the APL. However, importantly, these mature donor-type T cells did not proliferate in response to Y4S/F6A or L4 variant peptides in vivo . Injection of the viral peptides and their APLs in vivo led to reduction of CFSE + staining in the case of gp 33–41 and VSV8, suggestive of proliferation and/or activation-induced cell death (AICD). In contrast, no change in CFSE + staining was observed upon injection of Y4S/F6A or L4 peptides, implying that these APLs do not facilitate T cell expansion per se . In sum, the cognate peptide ligands gp 33–41 and VSV8 which interact with the TCR with relatively high affinity compared to their respective APL, induce activation of peripheral T cells, whereas peptide variants Y4S/F6A and L4, which bind TCR with low affinity and mediate positive selection, do not stimulate mature T cell divisions. Significance of APL-driven T cell emigration for the thymic vaccination approach The data described above and previously [ 40 ] represent the first examination of the direct effects of amino acid substitutions at the P14 and N15 TCR contact residues on thymocyte selection and emigration in vivo . In addition, we show that thymocyte emigration is dependent on the affinity/avidity of pMHC/TCR interactions. These results suggest that although the low affinity pMHC/TCR interactions are insufficient to trigger cell divisions in mature cells, differentiation of immature thymocytes nevertheless follows. Affinity measurements support the idea that positively selecting peptide ligand affinities are lower than those of negatively selecting ligands for TCRs, but additionally linked to their MHC binding/stability properties [ 42 ]. Our report is consistent with the notion that weak pMHCI/TCR interactions promote positive selection of SP CD8 thymocytes. Certainly the 10,000 fold weaker functional stimulation of N15-bearing T cells by L4 versus VSV8 peptide is in line with the view [ 14 ]. Two recent studies in class II MHC-restricted TCR transgenic mouse systems also argue that weak pMHC ligands may foster positive selection [ 43 , 44 ]. Collectively, our data show that cognate peptides can be modified at key TCR recognition positions to create variants that result in selection, directly or indirectly, of desired TCR specificities at the level of thymic development. This exogenous peptide administration offers a potential of expanding repertoire generation in vivo in a manner useful to the organism. Whether these peptide-specific T cells generate stronger defense mechanisms to fight viral infection or tumors in normal, non-transgenic mice remains to be investigated. The magnitude of the APL-driven increase in thymocytes and subsequent egress is only 2–3 fold, however. This level of change likely reflects the tightly regulated thymocyte egress process. In this respect, exploring peptide-based means of enhancing differentiation of thymocytes bearing desired TCRs together with the modulation of mechanisms controlling thymocyte emigration to the periphery would be of a great importance. To this end, various pathways regulating egress from the thymus are described below and should be considered as potential targets for such manipulation in conjunction with APL administration. Although not discussed further here, thymic vaccination followed by conventional cognate antigen immunization may be the best way to insure a robust memory T cell response. Regulation of thymocyte egress Lymphocyte migration plays an important role in regulating the localization and orchestration of immune responses. As thymocytes progress through the developmental stages, they migrate from the cortico-medullary junction, the site of entry of T cell progenitors from the BM, to the subcapsular region of the thymus, then to the cortex and to the medulla [ 18 , 19 ]. Finally, functionally mature thymocytes exit the thymus and seed the peripheral lymphoid tissues. The processes that regulate trafficking of lymphoid precursors to and within the thymus, and that mediate emigration of mature T cells from the thymus to the periphery remain poorly understood. Several mediators, including chemokine receptors [ 45 ], adhesion molecules [ 46 ], extracellular matrix proteins [ 47 ], neuroendocrine factors [ 48 ] and G-protein coupled receptors (GPCR) [ 49 ] have been shown to regulate thymocyte export (Fig. 2 ). Recently, a role for the early activation marker CD69, transiently expressed on activated mature T cells and on thymocytes undergoing positive selection, in controlling thymocyte export, has also been suggested [ 50 ]. Cellular mechanisms involved in thymocyte egress are discussed in the following sections. Chemokine pathways (reviewed in ref. [ 45 , 51 , 52 ]) Chemokines are basic polypeptides of about 100 amino acids, usually containing four Cys residues linked by disulphide bonds, which are produced by certain thymic stroma cells and are abundantly expressed in the thymus. Specifically, thymic epithelial, medullary epithelial and dendritic cells have been shown to secrete various chemokines. Growing evidence suggests that chemokines and their receptors, expressed differentially on thymocytes during discrete maturational stages, control homing of T cell progenitors to the thymus, their intrathymic migration, and exit to the periphery. Chemokines deliver signals for lymphocyte proliferation and survival, and regulate thymocyte trafficking by functioning in concert with other adhesion molecules such as selectins and integrins. Chemokines stimulate responding cells by activating pertussis toxin-sensitive G i α protein-coupled seven-transmembrane receptors (GPCR), leading to activation of intracellular secondary mediators which control directional cell migration. To date, 43 human chemokines have been identified, acting via binding to 19 different GPCR. Some chemokine receptors are expressed in DP and SP thymocytes, e.g. CCR9, with its ligand CCL25 secreted by TEC and DC. Others, e.g. CCR5 and CCR8, expressed on mature SP thymocytes, have been suggested to play a role in mediating thymocyte emigration. In particular, CCR7 has been demonstrated to mediate homing of naïve T cells to peripheral lymphoid organs via ligands CCL19 and CCL21. Extracellular matrix proteins (reviewed in [ 47 ]) Extracellular matrix (ECM) proteins laminin and fibronectin are produced by TECs, fibroblasts and MHC class II + macrophages in the thymus. Other ECM proteins including nidogen, associated with laminin, and galectins -1, -3, and -5 as well as glycosaminoglycans are produced by thymic epithelium. ECM proteins form molecular bridges between thymocytes and the thymic microenvironment, mediating adhesion of thymocytes via their ECM receptors VLA-4, -5 and -6, and their disassembly from the cell complexes. In the absence of ECM proteins, normal thymocyte development and migration are severely perturbed, both in in vitro cultures of TEC and in in vivo knockout mouse models, suggesting a crucial role of the ECM protein network in the thymic function. S1P pathway (reviewed in [ 53 , 54 ]) Sphingosine 1-phosphate (S1P), a member of sphingolipid family, is an important signaling molecule present in high concentrations in body fluids. SIP binds to members of a family of G protein-coupled receptors (S1P 1–5 /Edg) with up to nanomolar affinity, triggering diverse effects, including proliferation, survival, migration, morphogenesis, adhesion molecule expression, and cytoskeletal changes. S1P receptors are widely expressed during embryonic development and in the adult. The tissue distribution shows that lymphoid organs express high levels of S1P 1 and S1P 4 . Thus, these receptors may be potential targets for pharmacological drug design aimed at effecting thymocyte migration. The expression of S1P 1 on T cells controls their exit from the thymus and entry into the blood, and, thus, has a central role in regulating the numbers of peripheral T-cells [ 55 ]. Interestingly, S1P 1 knock-out mice show a block in the egress of mature T-cells into the periphery. The regulated expression of S1P 1 receptor levels, which is increased in mature SP thymocytes and peripheral T cells, may control responsiveness to the high levels of sphingosine 1-phosphate in the blood, which selectively induces mature T-cell migration to the periphery. Recently, S1P 1 receptors have been implicated in lymphocyte trafficking and homing based on studies using FTY720, a potent immunosuppressive agent, which is an agonist ligand for S1P 1,3,4,5 receptors blocking egress of T cells from the thymus. Studies of thymocyte egress mechanisms through the S1P receptor pathway may aid in facilitating emigration from the thymus to the periphery and provide additional means of enriching the mature T cell pool with desired specificities. Therapeutic applications of thymic vaccination Currently available vaccines unquestionably represent a success story in modern medicine and have had a dramatic effect on morbidity and mortality worldwide. Nonetheless, it is clear that improvements are required to enable the development of vaccines against infectious diseases that have so far proven difficult to control with conventional approaches (HIV-1, malaria, tuberculosis, etc.). Thymic vaccination might offer promising clinical applications as a way of immunization against these infectious diseases and cancers, enabling "designer" thymic development to produce suitable and long-lasting protective T cell immune specificities. In a converse role, deletion of unwanted T cell specificities in the case of autoimmunity by agonist administration early in life could be considered. Assuming thymic vaccination proves clinically viable, immune responses against invariant components of infectious agents, such as HIV and malaria, which otherwise utilize their intrinsic mutational capacity to evade human immune recognition, can be targeted. Design of novel vaccines based on the thymic vaccination approaches will benefit from the information gained in the recently completed Human Genome Project, particularly as genetic polymorphism associated with high risk of developing certain diseases later in life including cancers, infectious disease susceptibility and autoimmunity are uncovered. For example, the ability to manipulate the T cell repertoire to elicit anti-tumor responses early in life may prevent clinical disease evolution later. Powerful bioinformatic tools such as computer-based identification of HLA-allele specific binding epitopes and structural insight into TCR-pMHC interactions will aid in the epitope-based APL design process [ 56 ]. Conclusions A thymic vaccination strategy has been conceived based on the current knowledge of thymocyte differentiation and repertoire generation. This approach differs substantially from conventional vaccination since it aims to shape T cell responses through thymic repertoire manipulation, exposing developing thymocytes to positively selecting APL derived from infectious agents or tumors. Experimental data to date suggest that this strategy is possible in in vivo mouse models using irradiation chimeras reconstituted with bone marrow progenitors from TCR-transgenic animals. Increasing emigration of antigen-specific T cells from the thymus to the periphery is a challenging goal. In the future, a combined approach of exposing the subject to a positively selecting APL plus a thymic export-enhancing agent might generate practical and efficient protective repertoire manipulations. Potential applications may include design and administration of APL against cancer, infectious and autoimmune diseases. List of abbreviations APL, altered peptide ligand; BM, bone marrow; CMJ, cortico-medullary junction; DC, dendritic cells; DN, double negative; DP, double positive; GPCR, G-protein-coupled receptors; HEV, high endothelial venule; MMP, matrix metalloproteinases; RTE, recent thymic emigrants; SP, single positive; S1P, sphingosine 1-phosphate; TCR, T cell receptor; TEC, thymic epithelial cells. Competing interests The author(s) declare that they have no competing interests. Authors' contributions MFH carried out the study, including experimental design and data acquisition, drafted and revised the manuscript. ELR conceived of the study, participated in its design and coordination, and helped to draft and revise the manuscript. The authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544398.xml |
539359 | Chinese herbal recipe versus diclofenac in symptomatic treatment of osteoarthritis of the knee: a randomized controlled trial [ISRCTN70292892] | Background Duhuo Jisheng Wan (DJW) is perhaps the best known and most widely used Chinese herbal recipe for arthralgia, but the clinical study to verify its efficacy is lacking. The purpose of this study was to compare the efficacy of DJW versus diclofenac in symptomatic treatment of osteoarthritis (OA) of the knee. Methods This study was a randomized, double-blind, double-dummy, controlled trial. The 200 patients suffering from OA of the knee, were randomized into the DJW and diclofenac group. The patients were evaluated after a run-in period of one week (week 0) and then weekly during 4 weeks of treatment. The clinical assessments included visual analog scale (VAS) score that assessed pain and stiffness, Lequesne's functional index, time for climbing up 10 steps, as well as physician's and patients' overall opinions on improvement. Results Ninety four patients in each group completed the study. In the first few weeks of treatment, the mean changes in some variables (VAS, which assessed walking pain, standing pain and stiffness, as well as Lequesne's functional index) of the DJW group were significantly lower than those of the diclofenac group. Afterwards, these mean changes became no different throughout the study. Most of the physician's and patients' overall opinions on improvement at each time point did not significantly differ between the two groups. Approximately 30% of patients in both groups experienced mild adverse events. Conclusion DJW demonstrates clinically comparable efficacy to diclofenac after 4 weeks of treatment. However, the slow onset of action as well as approximately equal rate of adverse events to diclofenac might limit its alternative role in treatment of OA of the knee. | Background Osteoarthritis (OA) is the most prevalent joint disorder characterized by articular cartilage degradation with an accompanying peri-articular bone response [ 1 ]. OA affects many joints, with diverse clinical patterns, but OA of the hip and knee is the major cause of disability [ 2 ]. A clinical manifestation of OA of the knee is pain in and around the joint that is typically worse with weight-bearing and at night. Other manifestations include morning stiffness, stiffness after rest, crepitation on motion, limited joint motion and/or joint deformity [ 3 ]. Although there are many treatment modalities, OA is still widely treated with nonsteroidal anti-inflammatory drugs (NSAIDs) [ 4 ]. Nonetheless, since the inflammatory component of OA is usually minimal, a need for the anti-inflammatory effect of NSAIDs used in this condition is still controversial [ 5 - 7 ]. Moreover, long-term use of NSAIDs is also directly related to many side effects, including gastrointestinal bleeding, hypertension, congestive heart failure, hyperkalemia, and renal insufficiency [ 8 ]. Although some of these disadvantages can be avoided by using paracetamol or selective cyclooxygenase II (COX-II) inhibitors, long-term use of paracetamol possibly leads to hepatotoxicity and chronic renal impairment [ 9 , 10 ]. In addition, the relatively high cost of selective COX-II inhibitors seems to be unsuitable for Thailand's present socio-economic status. The use of Chinese and other foreign patent herbal medicines (pills and tablets) in arthralgia treatment is highly prevalent and increasing in Thailand, but importing these medicines from the People's Republic of China and other foreign countries is usually rather expensive. However, the cost of similar preparations can be minimized by using imported dried herbs available in Thailand as raw materials in the manufacturing process coupled with simple and inexpensive traditional drug manufacturing techniques. Thus, if clinical studies suggest that these herbal medicines are as effective and/or less toxic than conventional treatment, promotion of self-produced recipes in each community will lead to community-directed osteoarthritic treatment in Thailand. The herbal recipe used in this study was "Duhuo Jisheng Wan (DJW)", which means pill of Pubescent angelica root and Mulberry mistletoe combination, and it was quoted from the book Bei Ji Qian Jing Yao Fang compiled by Sun Simiao in the Tang Dynasty (652 A.D.) [ 11 , 12 ]. Although this recipe is perhaps the best known and most widely used formula for arthralgia and also sold as a patent remedy [ 13 ], the clinical study to verify its efficacy (compared with conventional treatment) is lacking. Thus, the objectives of this study were to verify the efficacy of DJW and compare its efficacy versus diclofenac in symptomatic treatment of OA of the knee. Methods Research design This randomized, double-blind, double-dummy, controlled trial was approved by the Medical Ethics Committee of the Faculty of Medicine, Chiang Mai University and was in compliance with the Helsinki Declaration. Subjects Two hundred out-patients of either sex were recruited. They were aged over 40 years, and had been suffering from unilateral or bilateral OA of the knee according to the criteria of the American College of Rheumatology [ 3 ] for more than 3 months. After the use of usual medications had ceased for 7 days, the visual analog scale (VAS) score that assessed pain during the most painful knee movement had to be more than 40, and Lequesne's functional index [ 14 ] had to be over 7 points. Participants had to be able to walk and give both verbal and written information regarding the study. Signed informed consent was obtained prior to entry. Exclusion criteria included an underlying inflammatory arthropathy, hyperuricemia, expectation of surgery in the near future, recent injury in the area affected by OA of the knee, intra-articular corticosteroid injections within the last 3 months, hypersensitivity to NSAIDs, abnormal liver or kidney function tests, major abnormal finding on complete blood count, history of coagulopathies, history of peptic ulceration and upper GI hemorrhage, uncontrolled hypertension, congestive heart failure, hyperkalemia, pregnancy, lactation and malignant tumors. Treatment procedures During a run-in period of 1 week (week 0), patients considered eligible for the study were informed to discontinue all analgesics, anti-inflammatory drugs, and other modalities for the treatment of arthralgia and arthritis. At the beginning of week 1, patients who still met the eligible criteria were randomized into 2 groups (DJW and diclofenac group) and treated for 4 weeks (Table 1 ). Other medications and treatment modalities for OA were prohibited during the study. In addition, a count of unused drugs and placebos was made weekly in order to check for the rates of compliance with medication. Table 1 Treatment in the DJW and diclofenac group. Treatment DJW group Diclofenac group Capsule Placebo Diclofenac Herbal capsule DJW Placebo 1. Diclofenac and its placebo Twenty five mg film-coated tablets of commercially marketed diclofenac sodium (Voltaren ® ) were provided by Novartis (Thailand) Co., Ltd. In order to completely blind the patients, each diclofenac tablet was packed into a capsule with an appearance identical to its placebo. Either diclofenac or placebo was prescribed at 1 capsule, 3 times a day, immediately after meals. 2. DJW and its placebo DJW and its placebo were prepared by the Department of Pharmaceutical Sciences, Faculty of Pharmacy, Chiang Mai University. It consisted of 7.75% each of Radix Angelicae Pubescentis (Duhuo), Radix Gentianae Macrophyllae (Qinjiao), Cortex Eucommiae (Duzhong), Radix Achyranthis Bidentatae (Niuxi), Radix Angelicae Sinensis (Danggui), Herba Taxilli (Sangjisheng), Radix Rehmanniae Preparata (Shudihuang), Rhizoma Chuanxiong (Chuanxiong), Cortex Cinnamomi (Rougui) and Radix Ledebouriellae (Fangfeng), 5% each of Radix Paeoniae Alba (Baishao), Radix Codonopsis (Dangshen), Radix Glycyrrhizae (Gancao) and Poria (Fuling), as well as 2.5% of Herba Asari (Xixin). Xixin, Niuxi, Shudihuang and Rougui were imported from the Shantou Traditional Chinese Medicine Factory, the People's Republic of China (PRC). The remaining herbs were imported from the Qixin Co., Ltd. (Hebei Province), PRC. Each pulverized ingredient was mixed thoroughly together according to the formula mentioned above and prepared into honeyed pills, which were baked in a hot air oven until completely dry, and then pulverized. The pulverized powder was finally filled into capsules of 500 mg per capsule. The quality control and standardization of DJW (i.e., assessment of weight variation, disintegration time, screening for microorganisms and aflatoxin) were conducted by using guidelines recommended by the Food and Drug Administration of Thailand [ 15 ]. DJW and its placebo were prepared in 4 separate lots. Every lot had to pass for quality control and standardization before prescription and they were used within 8 weeks in order to ascertain the stability of active substances, and avoid microorganism and aflatoxin contamination during the study. DJW was prescribed at 6 capsules (3 g) each time, 3 times a day, immediately after meals. Its placebo, with identical appearance, was made from cane sugar and prescribed at the same dosage as the DJW. Assessments Clinical assessments were evaluated for base-line data at the end of a run-in period (week 0) and then weekly for 4 weeks. These assessments included 100-mm VAS that assessed pain (classified into walking pain, standing pain, pain during climbing up and down stairs, night pain, resting pain, total pain, pain during the most painful knee movement), 100-mm VAS that assessed stiffness (classified into morning stiffness, stiffness after rest and total stiffness), Lequesne's functional index that assessed the patient's daily activities (score ranging from 0–24) [ 14 ], and time for climbing up 10 steps. The participants self-rated the VAS and Lequesne's functional index, and they were allowed to view their own previously recorded scores. At the end of week 1–4, 100-mm VAS that assessed the physician's and patients' overall opinions on improvement were also evaluated. The assessment forms were designed so that the patients and evaluator could view their own previously recorded scores, but they were not allowed to view each other's VAS. Clinical assessments were evaluated by the same physician who had been blinded to the treatment. Complete physical examination and non-directive questioning for adverse events were also performed weekly for 4 weeks in order to acquire a safety assessment. Statistical analysis In within the group analysis, the mean VAS and Lequesne's functional index between base-line and the following weeks were compared by a non-parametric Wilcoxon's signed-rank test, whereas, the average time for climbing up 10 steps was compared by the paired t-test. In the analysis between the groups, a non-parametric Wilcoxon's rank-sum test was used to determine whether the two groups differed in the physician's and patients' overall opinions on improvement. In addition, the mean changes in VAS that assessed pain and stiffness, as well as Lequesne's functional index were compared by the same test. The student's t-test was used to compare the mean changes in the time for climbing up 10 steps. Results A total of 429 patients were recruited into this study, of whom 229 were excluded (Figure 1 ). The remaining 200 patients were randomized into the DJW and diclofenac group, 100 patients per group. In the DJW group, 4 patients withdrew from the study due to ineffectiveness (n = 3) and transportation problem (n = 1), 1 patient was lost to follow up and another one had a traffic accident during the study. In the diclofenac group, 3 patients were lost to follow up and 3 were withdrawn due to accidents. Thus, each group comprised 94 completers. The two treatment groups were not significantly different in demographic data e.g., sex, age, weight, height, duration of OA, location of OA (Table 2 ) and base-line data for the major outcome assessment (VAS, Lequesne's functional index and time for climbing up 10 steps). The radiographic findings at entry (Table 3 ) were not different between both groups. During the study, the rates of compliance with medication in the DJW group were 94%, whereas, those in the diclofenac group were 96%. Since few patients withdrew from the trial, the results were not substantially affected, whether the statistical method was performed by an intention to treat (ITT) analysis or an analysis on available completers. Thus, the following data showed the findings from the ITT analysis. Figure 1 Flow chart of patients who participated in the clinical trial. 1 DJW group received DJW plus placebo of diclofenac. 2 Diclofenac group received diclofenac plus placebo of DJW. Table 2 Demographic data and base-line data for the major outcome assessments of participants evaluated at the end of a run-in period (week 0). Treatment groups Characteristics DJW Diclofenac p value n (M:F) 100 (22:78) 100 (19:81) NS Age (y)* 62.66 (9.46) 62.38 (8.22) NS Body weight (kg)* 60.47 (10.34) 60.13 (10.89) NS Height (m)* 1.51 (0.07) 1.51 (0.07) NS BMI (kg/m 2 )* 26.52 (4.38) 26.35 (3.85) NS Duration of OA (y)* 5.46 (5.48) 4.79 (4.24) NS Localization of OA NS Right knee 17 17 Left knee 14 14 Both knees 69 69 VAS the assessed pain (mm)* Walking pain 64.53 (24.92) 64.78 (25.14) NS Standing pain 52.42 (25.87) 53.52 (24.69) NS Pain during climbing up and down stairs 63.08 (20.87) 62.69 (23.21) NS Night pain 50.15 (26.74) 48.45 (28.18) NS Resting pain 38.48 (22.09) 37.12 (26.08) NS Total pain a 268.65 (88.87) 266.55 (89.33) NS Pain during the most painful knee movement 82.25 (16.15) 81.17 (16.56) NS VAS that assessed stiffness (mm)* Morning stiffness 53.53 (27.38) 58.32 (26.40) NS Stiffness after rest 68.52 (22.76) 70.45 (22.32) NS Total stiffness b 122.05 (41.98) 128.76 (42.34) NS Lequesne's functional index* 14.20 (3.13) 14.80 (2.61) NS Time for climbing up 10 steps* 13.44 (4.85) 13.32 (5.10) NS *Data represent mean (SD). a Summation of VAS that assessed walking pain, standing pain, pain during climbing up and down stairs, night pain and resting pain. b Summation of VAS that assessed morning stiffness and stiffness after rest. NS: no statistical significance. Table 3 The radiographic findings at entry into the study. Treatment groups Radiographic findings DJW (169 knees) Diclofenac (169 knees) p value Kellgren and Lawrence X-ray grade [20] NS Grade 2 31 23 Grade 3 71 80 Grade 4 67 66 Knee compartment with most severe changes NS Medial tibiofemoral 131 135 Lateral tibiofemoral 16 8 Patellofemoral 22 26 The VAS that assessed pain and stiffness at the end of week 1–4 decreased significantly when compared to their own base-line values (within the group analysis), as did Lequesne's functional index and time for climbing up 10 steps (Table 4 ). At the end of week 4, the percentages of improvement in VAS that assessed pain and stiffness were higher than 65% in both groups, whereas, the percentages of improvement in Lequesne's functional index and time for climbing up 10 steps were approximately 40% and 20%, respectively. Table 4 Mean VAS that assessed pain and stiffness, Lequesne's functional index and time for climbing up 10 steps in intent-to-treat patients (n = 100/group). Variable Treatment Group Week 0 Week 1 Week 2 Week 3 Week 4 % improvement a VAS that assessed pain (mm) Walking pain DJW 64.53 (24.92) 47.58* (25.33) 37.72* (25.00) 28.00* (23.25) 18.06* (20.76) 72.01 Diclofenac 64.78 (25.14) 44.08* (23.43) 34.99* (22.07) 24.21* (21.00) 14.31* (16.10) 77.91 Standing pain DJW 52.42 (25.87) 39.81* (26.09) 31.61* (24.89) 24.29* (22.98) 16.89* (20.59) 67.78 Diclofenac 53.52 (24.69) 37.60* (24.06) 28.19* (22.40) 21.12* (21.16) 12.86* (16.69) 75.97 Pain during climbing up and down stairs DJW 63.08 (20.87) 46.31* (26.56) 36.40* (25.67) 28.16* (24.03) 18.41* (21.50) 70.81 Diclofenac 62.69 (23.21) 43.90* (22.29) 32.61* (22.42) 24.59* (21.79) 15.83* (19.65) 74.75 Night pain DJW 50.15 (26.74) 33.44* (27.27) 23.56* (22.79) 15.68* (18.14) 9.27* (15.04) 81.52 Diclofenac 48.45 (28.18) 28.93* (22.82) 20.87* (19.56) 15.02* (17.87) 8.65* (14.68) 82.15 Resting pain DJW 38.48 (22.09) 27.25* (21.99) 19.96* (19.98) 12.64* (15.56) 7.42* (13.09) 80.72 Diclofenac 37.12 (26.08) 22.84* (20.62) 16.26* (18.19) 11.30* (16.40) 6.58* (13.96) 82.27 Total pain b DJW 268.65 (88.87) 194.38* (105.06) 149.24* (103.19) 108.76* (92.54) 70.04* (83.94) 73.93 Diclofenac 266.55 (89.33) 177.34* (85.49) 132.91* (84.50) 96.21* (81.94) 58.23* (70.43) 78.15 Pain during the most painful knee movement DJW 82.25 (16.15) 63.31* (26.35) 49.77* (28.70) 37.69* (28.45) 26.81* (27.70) 67.40 Diclofenac 81.17 (16.56) 56.79* (24.87) 43.64* (27.30) 33.10* (27.17) 22.84* (25.85) 71.86 VAS that assessed stiffness (mm) Morning stiffness DJW 53.53 (27.38) 36.61* (25.56) 28.04* (23.86) 19.66* (20.53) 12.34* (17.69) 76.95 Diclofenac 58.32 (26.40) 38.73* (23.87) 28.52* (21.93) 20.19* (20.23) 12.90* (17.34) 77.88 Stiffness after rest DJW 68.52 (22.76) 51.69* (24.93) 39.40* (25.31) 29.05* (24.60) 19.62* (23.06) 71.37 Diclofenac 70.45 (22.32) 49.71* (24.68) 39.54* (24.97) 28.23* (24.17) 18.90* (20.60) 73.17 Total stiffness c DJW 122.05 (41.98) 88.30* (45.93) 67.44* (46.25) 48.71* (42.82) 31.96* (38.84) 73.81 Diclofenac 128.76 (42.34) 88.44* (43.84) 68.06* (43.03) 48.42* (41.97) 31.80* (36.07) 75.30 Lequesne's functional index (score) DJW 14.20 (3.13) 11.60* (4.11) 11.05* (4.04) 9.93* (4.40) 8.92* (4.60) 37.18 Diclofenac 14.80 (2.61) 10.89* (3.38) 10.65* (3.55) 9.59* (3.52) 8.64* (3.83) 41.62 Time for climbing up 10 steps (s) DJW 13.44 (4.85) 11.65* (4.75) 11.42* (4.67) 10.94* (4.73) 10.50* (4.38) 21.88 Diclofenac 13.32 (5.10) 11.26* (5.12) 11.14* (5.72) 10.61* (5.51) 10.18* (4.46) 23.57 Data represent mean (SD). a Calculated by (mean week0 -mean week4 ) × 100/mean week0 . b Summation of VAS that assessed walking pain, standing pain, pain during climbing up and down stairs, night pain and resting pain. c Summation of VAS that assessed morning stiffness and stiffness after rest. * p < 0.05 versus base-line value. When the statistical analysis between groups was performed, the mean changes in VAS that assessed pain during climbing up and down the stairs, night pain, resting pain, total pain, and time for climbing up 10 steps did not differ significantly between both groups (Table 5 ). Nonetheless, the mean changes in VAS that assessed walking pain, standing pain, and stiffness were significantly different during week 0–1, whereas, differences in mean changes in Lequesne's functional index were found during week 0–1 and 0–2. Afterwards, the mean changes in these variables became no different throughout the study. Table 5 Mean changes of VAS that assessed pain and stiffness, Lequesne's functional index and time for climbing up 10 steps in intent-to-treat patients (n = 100/group). Variable Treatment Group Week 0–1 Week 0–2 Week 0–3 Week 0–4 VAS that assessed pain (mm) Walking pain DJW -16.96 (1.68) -26.82 (1.97) -36.54 (2.31) -46.48 (2.41) Diclofenac -20.70 † (1.60) -29.80 (1.95) -40.58 (2.26) -50.47 (2.38) Standing pain DJW -12.61 (1.80) -20.81 (2.23) -28.13 (2.28) -35.53 (2.34) Diclofenac -15.93 † (1.33) -25.33 (1.83) -32.41 (2.04) -40.66 (2.25) Pain during climbing up and down stairs DJW -16.78 (1.95) -26.68 (2.30) -34.93 (2.26) -44.67 (2.22) Diclofenac -18.79 (1.40) -30.08 (1.91) -38.11 (2.04) -46.86 (2.35) Night pain DJW -16.71 (2.32) -26.60 (2.25) -34.47 (2.42) -40.88 (2.59) Diclofenac -19.52 (1.98) -27.58 (2.30) -33.43 (2.51) -39.80 (2.81) Resting pain DJW -11.23 (1.24) -18.52 (1.46) -25.84 (1.86) -31.06 (2.02) Diclofenac -14.28 (1.34) -20.86 (1.91) -25.82 (2.07) -30.54 (2.38) Total pain a DJW -74.27 (6.53) -119.42 (7.42) -159.90 (7.85) -198.61 (8.51) Diclofenac -89.21 (5.25) -133.64 (7.02) -170.34 (7.65) -208.33 (9.03) Pain during the most painful knee movement DJW -18.94 (2.11) -32.48 (2.63) -44.56 (2.77) -55.44 (2.67) Diclofenac -24.38 (2.10) -37.53 (2.51) -48.07 (2.57) -58.33 (2.59) VAS that assessed stiffness (mm) Morning stiffness DJW -16.93 (1.98) -25.50 (2.24) -33.87 (2.46) -41.19 (2.58) Diclofenac -19.59 † (1.69) -29.80 (2.10) -38.13 (2.47) -45.42 (2.63) Stiffness after rest DJW -16.83 (1.97) -29.12 (2.41) -39.48 (2.50) -48.91 (2.54) Diclofenac -20.74 † (1.72) -30.91 (2.07) -42.22 (2.29) -51.55 (2.40) Total stiffness b DJW -33.76 (3.48) -54.62 (4.02) -73.35 (4.21) -90.10 (4.27) Diclofenac -40.33 † (3.05) -60.71 (3.72) -80.35 (4.21) -96.97 (4.47) Lequesne's functional index (score) DJW -2.60 (0.34) -3.15 (0.32) -4.28 (0.37) -5.29 (0.38) Diclofenac -3.92 † (0.31) -4.16 † (0.32) -5.22 (0.36) -6.16 (0.40) Time for climbing up 10 steps (s) DJW -1.79 (0.33) -2.02 (0.31) -2.50 (0.32) -2.94 (0.32) Diclofenac -2.05 (0.31) -2.18 (0.34) -2.71 (0.34) -3.13 (0.33) Data represent mean (SD). a Summation of VAS that assessed walking pain, standing pain, pain during climbing up and down stairs, night pain and resting pain. b Summation of VAS that assessed morning stiffness and stiffness after rest. † p < 0.05 versus the DJW group at the same duration of treatment. The physician's and patients' overall opinions on improvement, as measured on VAS, are shown in Table 6 . The physician's overall opinion on improvement at each time point did not significantly differ between the two groups. However, differences between groups (DJW versus diclofenac group) were found in the patients' overall opinion at week 1 (32.58 ± 23.18 versus 37.48 ± 18.59), but no differences were demonstrated at the remaining time-points. Table 6 VAS that assessed physician's and patients' overall opinions on improvement a during treatment (intent-to-treat data set). Variable Treatment group n Week 1 Week 2 Week 3 Week 4 Physician's overall opinion DJW 98 b 56.69 (11.32) 57.30 (11.32) 60.06 (12.47) 62.55 (11.67) Diclofenac 97 b 59.84 (7.53) 59.63 (7.74) 62.11 (7.57) 63.35 (7.90) Patients' overall opinion DJW 98 b 32.58 (23.18) 45.53 (24.74) 58.10 (26.84) 71.13 (24.68) Diclofenac 97 b 37.48* (18.59) 50.24 (18.79) 62.88 (19.75) 75.30 (17.95) Data represent mean (SD). a 0 = no improvement, 100 = best possible improvement. b 2 patients in the DJW group and 3 patients in the diclofenac group could not be assessed due to loss to follow up or withdrawal during week 0. * p < 0.05 versus the DJW group at the corresponding week. The majority of patients in both groups experienced no adverse events (72% vs. 73% for DJW and diclofenac groups, respectively). All adverse events reported were mild in intensity in both groups. The most common adverse events occurring in the DJW and diclofenac group were raised blood pressure (16% vs. 19%), central nervous system symptoms including dizziness, somnolence and drowsiness (16% vs. 11%), and gastrointestinal symptoms including nausea/vomiting, dyspepsia, diarrhea and constipation (12% vs. 5%). The least common adverse events were increased appetite, cramp, rash and flu. More than one adverse events might be occurred in some patients. However, the percentages of patients who experienced each adverse event in both groups were not significantly different. In summary, the VAS that assessed pain and stiffness, Lequesne's functional index and time for climbing up 10 steps at each time point decreased significantly in the DJW and diclofenac group when compared to their own base-line values. The mean changes in all VAS that assessed pain, except those for walking and standing, did not differ significantly between both groups. The differences in mean changes in the VAS that assessed walking pain, standing pain and stiffness were found only during week 0–1, whereas, those in Lequesne's functional index were found during week 0–1 and 0–2. Discussion Since the preparations and dosages of DJW and diclofenac were different, this study was designed as a randomized, double dummy, controlled trial in order to completely blind both patients and physician (double-blind). Therefore, the placebo of DJW was also prescribed for the patients in the diclofenac group, and vice versa, the placebo of diclofenac was prescribed for the patients in the DJW group. Among the 15 herbs used as raw materials in DJW, Xixin (Herba Asari) seemed to be the most toxic, due to its pungent taste and warm property [ 16 ]. Generally, a large dose of this herb is not recommended in a tropical country (such as Thailand) because of the potential aggravation of internal heat. Thus, the amount of Xixin in the DJW recipe used in this study was reduced from 7.75% to 2.5%. In an ITT analysis (and analysis on completers), the mean changes in some variables between the two groups were significantly different after the first few weeks of treatment, and became no different afterwards. These differences suggest that the onset of DJW is significantly slower than diclofenac for at least 2 weeks (with respect to walking pain, standing pain, morning stiffness, stiffness after rest, total stiffness and patients' overall opinion) or 3 weeks (with respect to Lequesne's functional index). The reason why DJW needs a few weeks to exert its effect may be due to 3 possibilities. Firstly, from the pharmacokinetic point of view, the elimination half-life of the active ingredients in DJW might be too long, and therefore needs weeks to accumulate until a steady state concentration is reached (normally 4–5 half-lives) and its maximal therapeutic effect is evident. Secondly, from the pharmacodynamic point of view, DJW may exert its effects via several probable mechanisms (similar to many novel biologic treatments of arthropathy) involved modifications of cartilage metabolism, normalized viscosity and elasticity of synovial fluid, etc. These mechanisms of action might resemble many symptomatic slow acting drugs in osteoarthritis (SYSADOA) such as glucosamine sulfate, intra-artricular hyaluronan, and others. These interventions always need a period of time to exert their therapeutic action. Thirdly, the major effect of DJW might be the result from placebo effect and/or natural fluctuation of the OA symptoms. It could be simply that diclofenac worked quickly, but patients in both groups got better anyway by 2–3 weeks. Although the last possibility cannot be entirely ruled out, but it seems unlikely because even there is a tendency of OA symptoms to improve after placebo treatment, it has been reported that diclofenac was significantly superior to placebo in relieving pain, improving stiffness, and improving physical function after 4 weeks of treatment [ 17 ]. Furthermore, we also found that oral administration of the ethanol extract of DJW possessed both central and peripheral analgesic activities in animal model, even when the DJW extract was given in the equivalent dose used in human (mg/kg of human dose corrected by intra- and inter-specie variations) [to be published data]. In clinical practice, this slower onset of action and probable need for rescue analgesics (e.g., paracetamol as needed) during the first 2–3 weeks after initiation of DJW should be the important limitations of using DJW as an alternative treatment for OA of the knee. Moreover, the patient's compliance with such a high dosage of DJW (9 g/day or 18 capsules/day) is an important issue to be concerned. Since this study demonstrated that approximately 30% of study subjects in each group experienced adverse events, this data suggest that the toxicity profiles of DJW are similar to diclofenac. Therefore, cautious use of DJW should be considered in the same manner as using diclofenac including other NSAIDs. However, the gastrointestinal adverse effects in the diclofenac group were quite low when compared to other short-term NSAIDs studies [ 18 , 19 ]. This might be due to the exclusion of patients with a high risk of adverse effects from NSAIDs during the screening visit. Since the relief of joint pain afforded by paracetamol is comparable with that achievable with NSAIDs, paracetamol merits a trial as initial therapy, based on its overall cost, efficacy, and toxicity profile [ 3 , 7 ]. In this circumstance, the rather high rate of adverse events from DJW should be another limitation of using DJW as an alternative, especially to paracetamol, in symptomatic treatment of OA of the knee. Conclusion DJW demonstrates clinically comparable efficacy to diclofenac after 4 weeks of treatment. However, the slow onset of action as well as approximately equal rate of adverse events to diclofenac might limit its alternative role in treatment of OA of the knee. Competing interests The author(s) declare that they have no competing interests. Authors' contributions ST carried out the randomization, supervised data collection and analysis, and drafted the manuscript. PK participated in the design of the study and performed the statistical analysis. NR participated in the selection of patients eligible for the study. KS carried out the outcome assessments. SP participated in the report of radiographic findings of knee. SL participated in the preparation of DJW and its placebo. SP carried out the screening for microorganism contamination in DJW and its placebo. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC539359.xml |
517926 | GASP: Gapped Ancestral Sequence Prediction for proteins | Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. | Background Predicting ancestral protein sequences from a multiple sequence alignment is a useful tool in bioinformatics [ 1 ]. Many evolutionary sequence analyses require such predictions in order to map substitutions to a particular lineage ( e.g. [ 2 , 3 ]). In other situations, the predicted ancestral sequence alone may provide a more representative functional sequence than a simple consensus sequence constructed from an alignment. Nevertheless, predicting ancestral sequences is not a simple procedure. It relies on a quality alignment plus an accurate – and correctly rooted – phylogenetic tree. Strict consensus methods are quick but can suffer from over-representation of larger clades of related sequences, which contribute more sequences to the consensus than more sparsely populated clades. Maximum Parsimony (MP) methods [ 4 ] overcome this problem by minimising mutational steps, rather than maximising agreement with the terminal sequences. MP, however, cannot distinguish between several equally parsimonious predictions. More sophisticated likelihood-based methods exist that can give probabilities for different ancestral sequences ( e.g. [ 5 - 8 ]) and implementation such as CODEML [ 5 ] and FASTML [ 7 ] provide a good balance between speed and accuracy. However, many of these programs cannot predict ancestral sequences for columns of the alignment that have one or more gapped residues [ 9 ]. GASP (Gapped Ancestral Sequence Prediction) is an ancestral sequence prediction algorithm that is designed to handle gapped alignments of any size using a combination of MP and likelihood methods. Although probably not as accurate as some of the more sophisticated maximum likelihood approaches, it permits the estimation of ancestral states at residues that are gapped in any sequences of the alignment with comparable accuracy to that of ungapped residues. Implementation The GASP algorithm Input GASP uses input from three sources: a multiple sequence alignment (MSA); an accompanying phylogenetic tree in Newick format [ 10 ]; and a Point Altered Mutation (PAM) substitution probability matrix, such as that of Jones et al. 1992 [ 11 ]. Sequences are read in from the alignment and node relationships established from the tree. The tree may be already rooted or rooted using GASP and must have branch lengths. Bootstrap values are not used by GASP but will be read if present. Sequences in the tree file can be represented by numbers (matching the order of the fasta alignment) or the first word of the sequence name. Details of the input formats can be found at: . Output GASP outputs an alignment in fasta format with both input terminal sequences and predicted ancestral node sequences. Ancestral sequences can either be grouped together at the end of the file or interspersed throughout the terminal sequences to reflect the tree topology (Figure 1(a) ). Three tree files are also output from GASP: (1) Newick format of the original input tree, rooted (Figure 1(b) ); (2) A raw text version of the tree, with internal nodes numbered as for the output sequence file; (3) Newick format tree with node numbers instead of bootstrap values, which can be opened with K Tamura's TreeExplorer program [ 12 ] (Figure 1(c) ). Branch lengths in this last file are replaced with the most likely PAM distance for a given branch, where PAM likelihoods for each branch are calculated as the product of each individual residue: where p X is the likelihood for a PAM distance of X (see 'Ancestral sequences' below), i is the ancestral amino acid at position r , j is the descendant amino acid at position r , p ijX is the substitution probability of i to j in a PAM X matrix, and N is the number of residues in the alignment. Substitutions involving gaps are ignored in this calculation. This allows a visual comparison between the branch lengths of the input phylogeny and the predicted branch lengths given the ancestral sequence predictions. Gaps If the MSA has gaps, GASP will first assign gap status to every residue at every node. Insertions and deletions are assumed to be equally likely, although a gap is assigned in the case of a tied probability (below). For each residue r , GASP starts at the tips and works deeper into the tree, assigning a probability of a gap at each node n , which is equal to the mean probability of a gap at the descendant nodes: where p is the gap probability for residue r at node n. p 1 and p 2 are the gap probabilities for r at the two descendant nodes. Terminal branches are given a probability of 1 if a gap is present or 0 if not. Once the root is reached, the gap status is fixed for the root. If the probability of a gap is greater than or equal to 0.5, residue r is fixed as a gap, otherwise r is fixed as a 'non-gap'. GASP then works back up the tree from the root, this time using the new ancestral gap probability and both descendant gap probabilities to recalculate the gap probability: where p 0 is the gap probability for r at the ancestral node. As with the root, r is fixed as a gap if p ≥ 0.5. This continues until all nodes are assigned as 'gap' or 'non-gap'. Ancestral sequences Once gaps are assigned, ancestral sequences are predicted in a similar fashion. Each residue r is assigned a probability for each amino acid at each node n . At the tips, r has a probability of 1 for the amino acid that is present in the MSA. GASP then works down the tree assigning probabilities based on the descendant nodes, branch lengths and a substitution matrix. By default, the PAM matrix of Jones et al. 1992 [ 11 ] is used. This is a PAM 1 matrix, which represents the probability that a given amino acid will be substituted by each other amino acid when the mean substitution rate is 1 /100 residues. To make a PAM X matrix, which represents a length of evolutionary time where a sequence will have undergone X substitutions per 100 residues, the PAM1 matrix is multiplied by itself X -1 times: where i is the ancestral amino acid, j is the descendant amino acid, k is the 20 possible transitory amino acids, p ijX is the substitution probability of i to j in a PAM X matrix, p ik ( X -1) is the substitution probability of i to k in a PAM( X -1) matrix and p kj 1 is the substitution probability of j to k in a PAM1 matrix. Unless the ancestral node has a gap (as calculated above) at position r , the ancestral probabilities for each amino acid are calculated for the two descendant branches individually, using a PAM X matrix, where X is 100 times the branch length as substitutions per site, i.e. a branch of 0.1 substitutions per site would use a PAM10 matrix: where p i is the probability of amino acid i at residue r of node n , p ijX 1 and p ijX 2 are the probabilities of substitution from amino acid i to each amino acid j in the appropriate PAM matrix for the two descendant branches, p dj 1 and p dj 2 are the probabilities of amino acid j being at position r at the two descendant nodes. Once the root is reached, the most probable amino acid is fixed as the ancestral sequence. As with gaps, GASP then works back up the tree, using the fixed ancestral node amino acid and the descendant node probabilities to give new probabilities for each amino acid. The most probable amino acid is then fixed and the process continues until all residues and all nodes have a fixed sequence. GASP is primarily designed for reasonably small trees (6–30 sequences), although there is no limit on input tree size. For larger trees, probabilities for each amino acid get very small near the root, which can lead to a heavy bias towards the fixed ancestral amino acid when GASP works back up the tree. To counter this GASP arbitrarily reduces any probabilities below a certain exclusion threshold (0.05 by default) to zero, thus reducing the slow accumulation of very unlikely amino acids. Variations To optimise the PAM matrices used for probability calculations, GASP uses the variable branch lengths read from the input phylogeny. There is also an option to fix the PAM distance used for all branches, which would allow the use of trees without branch lengths. Assignment of ancestral amino acids with the GASP algorithm is achieved by combining data from the descendants of a given node n and its direct ancestor n 0 . This ancestor itself is heavily influenced by the descendants of n but also by the 'outgroup' to n , namely those sequences that are descendant to n 0 but not to n . The outgroup information contained by the ancestral node n 0 can be vital in determining the correct sequence for n when the descendants of n are variable. For this reason, the GASP algorithm will, by default, fix ancestral sequences as it moves back 'up' the tree from the root, increasing the relative weighting of the outgroup to the two descendants. Because there is a chance of the wrong amino acid sweeping back up the tree (especially if rare amino acid probabilities are allowed to accumulate by reducing the exclusion threshold), there is an option to use amino acid probabilities from the ancestral node in the last stage of GASP rather than giving the fixed amino acid an ancestral probability of 1. This option should be used with caution. Simulated datasets Basic trees To test the GASP algorithm, a number of artificial phylogenies were simulated. Because there is a practically limitless number of possible tree sizes (in both numbers of sequences and branch lengths) and phylogenies, it was decided to test the algorithm on a set of simulated phylogenies based on real phylogenies that formed a subset of those for which the algorithm was originally written. This set comprised 94 neighbour-joining trees of protein families. Each tree contained at least two subfamilies of at least 3 members each, giving in total between 6 and 127 sequences. (The program used to generate these simulated phylogenies is also available from the author for testing the algorithm on a different set of trees.) Simulations started by creating a random protein sequence 100 amino acids long. Each residue was assigned an amino acid randomly as determined by the amino acid frequencies in all the human sequences of SwissProt-TrEMBL (Release 42) [ 13 ]. Sequences then evolved according to the template phylogeny. For each branch, residues were randomly substituted as described below until the total number of observed changes (ignoring multiple hits) equalled or exceeded the branch length of the phylogeny, which was not corrected for multiple hits. At this point, a new node was created with the new sequence and the tree split into two descendants. This proceeded until the whole phylogeny had been reconstructed. Each template tree seeded ten randomly simulated datasets. Algorithms were then given as input the simulated alignment and the parent phylogeny with 'real' branch lengths as calculated during simulation. (Note that PAML does not use these branch lengths.) Substitution methods Three substitution methods were used. In the first 'PAM Equal Rates' model, the PAM1 matrix of Jones et al. 1992 [ 11 ] was used, giving variable rates of evolution for different amino acids and different substitution likelihoods. For comparison, a purely random substitution matrix was used where every amino acid had an equal probability of evolving into every other amino acid (the 'Random Equal Rates' method). Under these methods, different residues have similar rates of evolution. A further model was used based on the PAM1 method where residues had different probabilities of evolving, before amino acid-dependent PAM effects are considered. Under this 'PAM Variable Rates' model, 40% sites evolved at the 'normal' rate, 20% half-rate, 20% double rate, and 20% almost fixed (1/50 rate). Note that the observed branch lengths remain the same as the normal 'PAM Equal Rates' method but highly variable sites will be more likely to have multiple substitutions under the 'PAM Variable Rates' method. Gapped data Because one of the main advantages of GASP is its ability to deal with gaps, a second test dataset was generated from the 'PAM Equal Rates' set of trees, this time with gaps added. The addition of gaps was kept simple so that the exact same trees could be used for the gap analysis, allowing direct comparison of the results with gaps and without. (See Testing the GASP Algorithm, below.) To do this, gaps were limited to single insertion/deletion ('indel') events per column of the MSA, allowing them to overlay onto the existing simulated 'PAM Equal Rates' data. In addition, no indels occurring next to root were allowed as it is impossible to judge without an outgroup whether such an event would be an insertion or deletion. To make the gaps, each residue r of the simulated sequences was considered in turn and had a probability of 50% of containing an indel. Gaps were all of length 1 (although two gaps may fall side by side, by chance). Although unrealistic for testing multiple alignment or phylogeny reconstruction programs, such a simplification is not a problem for ancestral sequence prediction as each residue is treated independently. The short gaps meant that, for the same total number of gapped residues, there is a higher diversity in the phylogenetic positioning of the indels. Indels were placed randomly with respect to evolutionary time. Each node in the simulated data has an 'age', which is the number of rounds of potential substitution it took to complete the simulation after that node was formed. Each indel occurs at a random age T between the tip (age 0) and the oldest direct descendant node from the root. A random branch (not leading to root) is then selected for which the ancestral node is older than T and the descendant node is no older. This is the branch on which the indel occurred. The indel is randomly assigned as an insertion or deletion event with equal probability. If it is an insertion then the ancestral node plus all nodes outside the descendant clade have residue r replaced with a gap. If it is a deletion then the descendant node and all its descendants have residue r replaced with a gap. Results and discussion Testing the GASP algorithm The simulated trees and alignments were run through the GASP algorithm. Because the 'real' sequence of each simulated node was known, it was then possible to determine the accuracy of GASP predictions. To test the different parts of the GASP algorithm, predictions were also made using modified GASP algorithms with parts of the model excluded. Because prediction for invariant sites is trivial for all methods, the expectation is that accuracy is inversely related to the number of variable sites. Therefore, comparisons of methods are presented as a percentage of the variable sites. In this context 'variable sites' are defined independently for each node as those sites for which not all descendant nodes (including termini) have the same sequence as the ancestral node. The simulated phylogenies are of different sizes. Considering all nodes of all trees would bias results towards the larger trees. To avoid this, each tree was arbitrarily reduced to four representative nodes: 1. 'Root' = The root of the tree. 2. 'Near Root' = A direct descendant node of the root. 3. 'Mid Tree' = A random node approx. midway in the tree. 4. 'Near Tip' = A direct ancestral node of a terminal sequence. To determine whether the GASP algorithm was useful its performance was compared to a crude consensus sequence at each node. Where two amino acids were present at equal frequencies in a column of the MSA, the most frequent amino acid in the total MSA was selected for the ancestral sequence. GASP may be considered crude compared to some existing Maximum Likelihood approaches and so its performance was also compared to that of both ML algorithms implemented by the CODEML program from the PAML package [ 5 ], namely the marginal reconstruction algorithm of Yang et al. 1995 [ 6 ] and the joint reconstruction algorithm of Pupko et al. 2000 [ 7 ]. In addition, the MP method implemented in the PAMP program of PAML [ 9 ] was also tested for comparison. The GASP model marginally out-performs all methods tested for constructing the ancestral sequence at the root of the tree (Figure 2 ). For all other representative node groups of the tree, GASP is comparable to the MP algorithm of PAMP but slightly inferior to both ML algorithms implemented in CODEML. PAMP is inferior to the ML methods at all levels of the tree. (In our hands, CODEML crashed in nearly 8% of cases. The problem was consistent and the troublesome input files crashed CODEML every time. However, there was no obvious difference between input files that presented CODEML with troubles and those that did not (Data not shown). To make a fair comparison of algorithms, data is only shown for datasets that did not cause CODEML to crash.) Although the ML algorithms of Yang et al . 1995 and Pupko et al . 2000 performed better overall for internal nodes, this difference was not seen for every node of every tree. At each level, GASP is sometimes better and sometimes worse than all three other algorithms (Figure 3 ). This is also true when comparing the three other algorithms with each other (Data not shown). GASP variants Four individual elements of the GASP algorithm were explicitly tested by disabling each in turn and comparing the results to those generated by the complete algorithm. The four variants run were: (a) using fixed PAM matrices rather than matrices derived from observed tree branch lengths. (b) fixing ancestral sequences on initial pass towards root without a second pass back up the tree. (c) no filtering of rare amino acid probabilities. (d) using ancestral probabilities when working back up the tree rather than fixed ancestral amino acids. Elements (a) and (b) were chosen for testing because they increase computational time, while (c) and (d) may not intuitively give the best results. For the phylogenies used in these simulations, all four variants performed worse than the standard GASP algorithm (data not shown). Using a fixed PAM distance for all branches rather than approximating the PAM distance using tree branch lengths (a) gives an unfair weighting to long branches and thus increases the probability of substitutions that are, in reality, unlikely. Fixing ancestral sequences on the way 'down' the tree to the root (b) does not use any outgroup information and is therefore significantly worse at distinguishing between two or more amino acids with similar ancestral probabilities. Less intuitive is the effect of reducing low amino acid probabilities to zero (c) and using fixed ancestral sequences when recalculating amino acid probabilities using all three connected nodes (d). Indeed, excluding these two elements have a much smaller effect but still reduce the overall accuracy of the algorithm (data not shown). Using fixed amino acids when working back up the tree increases the influence of the outgroup sequence. As was seen by the difference in accuracy between predictions at the root and nodes near the root (Figure 2 ), outgroup information is very important in predicting the correct sequence. (Predictions at the root are considerably weaker because there is no outgroup to help discriminate between alternative ancestral states.) Filtering out rare amino acids has a small effect in these trees but would be expected to have a larger effect in deeper trees. If rare probabilities are not removed then the most likely amino acid in each position will have an ever-diminishing likelihood, while highly unlikely ancestral sequences will find their probabilities ever-increasing. In very deep trees, this could result in probabilities being homogenised in the deep nodes. When fixed ancestral sequences are used to make predictions back up the tree, the fixed ancestral amino acid would potentially swamp the reduced probabilities in descendant nodes near the root, and sweep the root amino acid up the tree incorrectly. If this filtering is turned off when using larger trees, it is recommended that ancestral node probabilities be used instead of fixed ancestral sequences ( i.e. combining (c) and (d)). A final test was performed to compare the use of 'real' versus 'observed' branch lengths. (This was possible because the simulations kept track of not only what changes really occurred but also how many were 'visible', i.e. not correcting for multiple substitutions.) This is not testing the GASP algorithm per se but does provide information on the importance of using an accurate phylogeny construction algorithm. (The PAML package does not require pre-defined branch lengths and is therefore only affected by errors in supplied topology and not in branch lengths.) In many cases there was no difference. However, nearer to the root, using observed branch lengths rather than the real ones decreased prediction accuracy slightly. This decrease was correlated with total tree age (data not shown). This would imply that branch lengths corrected for multiple substitutions should be used for trees fed into the GASP algorithm, particularly with deep trees containing long branches. Gapped data A central part of the GASP algorithm is its ability to handle gapped alignments. As expected, GASP correctly placed 100% of simple gaps used in this test. (Each column of the alignment has a maximum of one indel, which is descendant of the root branches.) To analyse the effect of gaps on prediction accuracy, pairwise comparisons were made between the gapped datasets and the corresponding ungapped simulations (Figure 4 ). As would be expected, some of the gapped data shows reduced prediction accuracy because, as with the root of the tree, there is no 'outgroup' information directly following an insertion event. In many situations, however, accuracy is increased. This is because a gap is easier to predict accurately (having only two states, present or absent) than an amino acid (which could be one of twenty). The Consensus method shows a similar pattern but with a smaller fraction of trees showing an increase in accuracy (Data not shown). DNA data Although explicitly designed for use with protein sequence alignments and trees, it is relatively simple to convert GASP for use with nucleotide datasets. To do this, a new 'PAM matrix' should be created with substitutions probabilities for A, C, G and T only. This structure would allow the user to fit fairly complex substitution models, with different substitution probabilities for each pair of nucleotides. If the aligned sequence is coding DNA, however, it is highly recommended to use the protein sequences or a different algorithm such as those in the PAML package [ 5 ], as the adjusted PAM matrix would not take any consideration of codon positions. Conclusions We have presented an algorithm for predicting ancestral sequences in gapped datasets. At the root of the tree, GASP marginally outperforms three existing algorithms implemented in the PAML package. For other nodes of the tree, however, the ML algorithms of CODEML [ 5 - 7 ] generally perform better than GASP, while PAMP [ 9 ] gives a similar performance. The main advantage of GASP is its ability to use gapped datasets. Simple indel patterns are accurately predicted by GASP and do not greatly decrease ancestral sequence prediction accuracy. The GASP algorithm can be reliably run on either Windows or UNIX platforms with no discernable instability. For real life datasets, as for all evolutionary studies, predictions are dependent on the quality of input alignments. Gapped residues are, by their nature, often located in regions of evolutionary instability and therefore the interpretations of predictions at such sites require extra care. In many scenarios, however, gaps are introduced into alignments by the missing termini of fragment sequences. In these situations, the complete sequences that form the rest of the alignment may be very well aligned and so it is highly desirable to have an algorithm that can process the gaps introduced by the truncated sequences. Availability and requirements Project name: GASP (Gapped Ancestral Sequence Prediction) Project home page: Operating system(s): Platform Independent. (Tested on PC (Windows 98/XP) and UNIX (Red Hat Linux 7.3)) Programming language: Perl. Other requirements: None. License: None. Any restrictions to use by non-academics: Author's permission required. List of abbreviations GASP. Gapped Ancestral Sequence Prediction. Indel. Insertion or deletion event. ML. Maximum Likelihood. MP. Maximum Parsimony. MSA. Multiple Sequence Alignment. PAM. Point Accepted Mutation. Authors' contributions RE conceived the algorithm, coded the Perl script, designed and performed the accuracy tests and statistical analyses, designed the phylogeny simulation method, generated the simulated datasets and drafted the manuscript. DS helped in the design of test simulations and in drafting the manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517926.xml |
535563 | Reserpine methonitrate, a novel quaternary analogue of reserpine augments urinary excretion of VMA and 5-HIAA without affecting HVA in rats | Background Reserpine, an alkaloid from Rauwolfia serpentina was widely used for its antihypertensive action in the past. In later years, its use has been reduced because of precipitation of depression and extra pyramidal symptoms due to its central action. In the present investigation, reserpine methonitrate (RMN), a novel quaternary analogue of reserpine was synthesised and evaluated biochemically for its central and peripheral amine depleting actions in rats while its influence on the blood pressure was measured in anaesthetized rats in comparison with reserpine Results Reserpine treatment (5 mg/kg) produced a significant increase in the urinary excretion of VMA, 5-HIAA and HVA while RMN at doses of equal to and double the equimolar doses of reserpine (5 and 10 mg/kg) produced significant increase in VMA and 5-HIAA excretion without producing any effect on HVA excretion compared to control animals. Reserpine in the dose range of 0.5 to15 μg/kg produced significant reduction in blood pressure compared to control. RMN was also found to produce significant decrease in blood pressure at doses of 10, 25 and 50 μg/kg body weight in comparison to control. The results indicated peripheral depletion of biogenic amines by RMN without affecting the central stores of the amines. Conclusions The present study clearly indicated that the quaternization of reserpine restricts its transfer across the blood-brain barrier and could be the reason for its selective peripheral action. It is also clear that the hypotensive actions of RMN could be due to peripheral depletion of catecholamines. | Background Reserpine, an alkaloid isolated from Rauwolfia species, was introduced for the treatment of hypertension and schizophrenia in 1950's but was replaced by more effective drugs by the end of 1970's [ 1 - 6 ]. Reserpine is known to act centrally as well as peripherally by depletion of biogenic amines like noradrenaline, dopamine and serotonin. Mostly, its peripheral depletion of amines is responsible for its antihypertensive effect while its central depletion of amines is responsible for its antipsychotic action [ 7 - 13 ]. However, because of its central action it produces sedation and Parkinsonism when used for the management of hypertension for prolonged periods [ 14 - 17 ]. As a result it has reduced usage for chronic treatment in hypertensive patients and its use is limited to selective patient population only [ 18 , 19 ]. Hence there is a need for structural modification of the drug to make it more acceptable therapeutically for the treatment of hypertension. Attempts were made in the past to synthesize derivatives of reserpine with possibly higher and/or modified activities or with fewer side effects [ 20 - 23 ]. Compared to reserpine itself, a number of reserpine analogues were found to exert a stronger influence on the amine concentration in the periphery than in brain [ 24 - 26 ]. Based on the poor ability of quaternary compounds to penetrate the blood-brain barrier, a great deal of research has been devoted towards quaternization of existing drugs to achieve preferential peripheral action [ 27 - 32 ]. Earlier reports have demonstrated the synthesis of quaternary derivatives of reserpine and isoreserpine, however their pharmacology was not studied [ 33 , 34 ]. Previous studies by our group also revealed that reserpine methiodide produced selective depletion of peripheral biogenic amines without affecting their central stores [ 35 ]. In the present investigation, a quaternary analogue of reserpine viz ., reserpine methonitrate (RMN), which was synthesized in our laboratory was evaluated in rats for its amine depleting actions compared to reserpine. For this, the urinary levels of vanillylmandelic acid (VMA), 5-hydroxyindoleacetic acid (5-HIAA) and homovanillic acid (HVA) which are the respective metabolites of noradrenaline, serotonin and dopamine were estimated after reserpine or RMN treatment in rats. The change in the blood pressure response of anaesthetized rats after treatment with RMN was also evaluated in comparison to reserpine. Results Biochemical estimations The main aim of the study was to determine whether RMN was able to deplete the central and peipheral biogenic amines to the same extent as produced by reserpine. Reserpine at a dose of 5 mg/kg body weight produced significant increase in the urinary excretion profile of VMA compared to control animals. The analogue at doses equimolar to reserpine of 5 and 10 mg/kg body weight produced more significant increase in VMA excretion compared to controls and that observed with reserpine (Fig 1 ). However, the higher dose (10 mg/kg body weight) of RMN did not further enhance the excretion of VMA produced by 5 mg/kg body weight dose. Figure 1 Diagram illustrating the effect of reserpine and reserpine methonitrate on the 24 h urinary excretion of VMA in rats. Each bar indicates the mean excretion of six animals. Significant difference from control group: *p < 0.05 Significant difference from reserpine treated group: #p < 0.05 NS-No significant difference between 5 and 10 mg/kg treated groups of reserpine methonitrate Significant increase in 5-HIAA excretion was observed with reserpine at a dose of 5 mg/kg body weight and with the equivalent dose of RMN (Fig 2 ). The amount of 5-HIAA excreted in animals treated with the analogue/reserpine was found to be more than in the control. However the effect was found to be more with analogue compared to reserpine. The enhancement in dose to 10 mg/kg body weight of RMN did not produce any further increase in 5-HIAA excretion. Figure 2 Diagram illustrating the effect of reserpine and reserpine methonitrate on the 24 h urinary excretion of 5-HIAA in rats. Each bar indicates the mean excretion of six animals. Significant difference from control group: *p < 0.05 Significant difference from reserpine treated group: # p < 0.05 NS-No significant difference between 5 and 10 mg/kg treated groups of reserpine methonitrate A marked increase in the HVA excretion was observed in animals treated with reserpine compared to controls while minor change was observed in animals treated with RMN at doses of 5 and 10 mg/kg body weight compared to control (Fig 3 ). Figure 3 Diagram illustrating the effect of reserpine and reserpine methonitrate on the 24 h urinary excretion of HVA in rats. Each bar indicates the mean excretion of six animals. Significant difference from control group: *p < 0.05 Significant difference from reserpine treated group: # p < 0.05 NS-No significant difference between 5 and 10 mg/kg treated groups of reserpine methonitrate Effect on normal blood pressure of anaesthetized rats The effect of reserpine and RMN on the normal blood pressure of anaesthetized rats was shown in Table 1 . Dose dependent hypotension was observed with reserpine as well as with RMN. However, the vehicle (DMSO) also produced hypotension which was approximately 15 mm Hg from basal level. Reserpine at doses of 0.5, 1, 5, 10 and 15 μg/kg produced significant (p < 0.01) reduction in blood pressure compared to control. RMN was also found to produce significant (p < 0.01) decrease in blood pressure at doses of 10, 25 and 50 μg/kg body weight compared to control Table 1 Effect of reserpine and reserpine methonitrate on the mean arterial pressure of anaesthetized rats. Drug Dose (μg/kg) Mean arterial pressure (mmHg, n = 6) Reduction due to drug Before drug After drug Mean reduction Vehicle 0.05 ml 126.2 ± 2.8 110.0 ± 4.1 16.2 ± 1.4 --- Reserpine 0.25 138.3 ± 4.6 119.5 ± 4.2 18.8 ± 1.4 NS 2.6 0.50 134.1 ± 5.5 91.2 ± 5.0 42.9 ± 0.9** 26.5 1 135.2 ± 4.7 80.5 ± 3.8 54.8 ± 1.6** 38.6 5 130.5 ± 5.1 69.0 ± 3.5 61.5 ± 2.8** 45.3 10 130.0 ± 4.2 58.7 ± 3.9 71.2 ± 1.3** 55.0 15 131.5 ± 5.1 41.1 ± 2.9 90.4 ± 3.1** 74.2 Reserpine methonitrate equivalent to reserpine 10 128.8 ± 6.4 90.0 ± 9.1 38.8 ± 3.6** 22.6 25 135.0 ± 8.5 73.0 ± 7.4 62.0 ± 2.8** 45.8 50 136.8 ± 5.3 42.5 ± 3.7 93.0 ± 8.0** 76.8 Significant difference from DMSO treated group: **p < 0.01 NS – No significant difference from DMSO treated group. Discussion The structural modification of existing drugs to achieve selective action is not uncommon in providing better pharmaceutical care to the needy patients. It has been well established that the antihypertensive and tranquilizing actions of reserpine are mediated through the depletion of biogenic amines in the body [ 12 , 13 , 36 ]. The peripheral depletion of amines is responsible for its antihypertensive effect [ 11 , 37 ] while their central depletion plays a role in sedation and depression of reserpine [ 38 , 39 ]. Reserpine exerts its depleting effect by specifically inhibiting the adenosine triphosphate-Mg 2+ -dependent incorporation of biogenic amines into their storage vesicles [ 40 , 41 ]. Since reserpine depletes noradrenaline, 5-HT and dopamine from their storage sites, this results in a consequent increase in their metabolite levels in urine. Previous investigators have demonstrated a marked increase in the urinary excretion of peripheral and central metabolites of biogenic amines in animals treated with reserpine [ 8 , 42 - 44 ]. In the present investigation, a non-invasive biochemical approach was followed to determine the 24 h urinary excretion of VMA, 5-HIAA and HVA in rats treated with reserpine or RMN. Moreover, VMA, the peripheral metabolite of noradrenaline; 5-HIAA, the main metabolite of serotonin; and HVA, the predominant metabolite of dopamine were selected as the biomarkers for evaluation since noradrenaline exists both centrally and peripherally, serotonin exists mainly peripherally while majority of dopamine exists centrally. Since 99% of the total body's content of serotonin is present in the periphery, it is considered that the major part of the excreted 5-HIAA is from the peripheral release [ 45 , 46 ]. Similarly, high levels of dopamine are found in the centre rather than periphery, and any change in the HVA excretion in urine was considered as a corresponding change in dopamine levels at the central regions [ 47 ]. These indices provide an indirect evidence for the peripheral and central monoamine depleting effects of reserpine and its quaternary analogue. The results showed that reserpine increased the urinary excretion of VMA, 5-HIAA and HVA indicating the depletion of peripheral as well as central biogenic amines. These are in agreement with the results observed by previous investigators [ 8 , 35 , 42 - 44 ]. The increase in the urinary excretion of VMA and 5-HIAA with RMN is higher than with reserpine at equimolar dose of 5 mg/kg body weight. The localized distribution of the analogue in the periphery could led to higher level of depletion of peripheral noradrenaline and serotonin hence their metabolite levels were found to be increased much more which also substantiate our previous studies [ 35 ]. The inability of the analogue to increase HVA excretion unlike reserpine could be due to its non-entry across the blood-brain barrier and into the central nervous system to deplete dopamine which is present predominantly in mesolimbic, nigrostriatal and tuberoinfendibular systems [ 48 ]. The increased urinary levels of 5-HIAA observed with RMN could be due to the peripheral release of 5-HT as it is found predominantly at the periphery in enterochromaffin cells. The higher dose (10 mg/kg) of RMN did not produce any further increase in the VMA and 5-HIAA excretion compared to lower dose. The possible reason for this effect could be that 5 mg/kg dose was sufficient to deplete the amines completely from the storage sites. In order to evaluate whether the quaternary analogue of reserpine (RMN) still retains the peripheral blood pressure lowering activity, further experiments were carried out on the blood pressure of anaesthetized rats. Thus far, the results of RMN on the blood pressure response of anaesthetized rats confirmed that the peripheral actions of reserpine molecule are not affected by quaternization. However, in the present study the vehicle (DMSO) also produced minor hypotensive effect on blood pressure of rats when administered alone with the dose used for the administration of the drugs. Earlier workers [ 49 ] also reported hypotension with DMSO supporting the present observations. Reserpine produced dose dependent reduction in blood pressure as demonstrated by previous investigators [ 50 , 51 ]. As indicated in earlier reports [ 9 , 11 , 40 , 52 - 54 ] the hypotensive effect of reserpine observed in rats is due to the depletion of catecholamines from the peripheral stores. The effect of equimolar doses of RMN also indicated hypotension however, with higher doses compared to reserpine. It is further indicated that quaternization of reserpine not only restricted the entry of RMN to central nervous system but also reduced to the target tissue in the periphery. Hence relatively higher doses were required to produce reserpine like effect. Mechanistically, the hypotensive actions of RMN could also be due to peripheral depletion of catecholamines as evident from the positive correlation with the results of previous section on the peripheral depletion of monoamines. Conclusion In conclusion, the present study indicated that the quaternization of reserpine molecule prevents its access into the central nervous system and thereby produces selective peripheral depletion of biogenic amines. Furthermore, the study indicated that quaternization of reserpine had not abolished the hypotensive response but only higher doses were required. Methods Chemistry The synthesis of RMN was done as follows: The solution of reserpine (2 g, 3.3 mmols) in dichloromethane (20 ml) was added to methyl iodide (11 ml, 176 mmols) and the resulting mixture was kept for two days in dark. The solid was filtered and washed with a little cold dichloromethane and dried under vacuum at 70°C for 2 h to yield reserpine methiodide (RMI) [ 33 , 34 ]. Then, to a solution of RMI (0.25 gm, 0.67 mmols) in a mixture of dichloromethane (3 ml) and aqueous ethanol (90%, 2 ml) was added a solution of silver nitrate (56 mg, 0.67 mmols) in aqueous ethanol (90%, 2 ml). The reaction mixture was stirred overnight at room temperature. The solution was filtered and washed thoroughly with chloroform : methanol (1:1). The solid obtained after evaporation of the solvent was passed through a silica gel column and eluted with chloroform : methanol (80:20) to yield RMN, m.p. 292–294°C. Chemicals used Reserpine and thiopentone were generous gift samples from Novartis India Limited and Abbott Laboratories, Mumbai respectively. The standard samples of VMA, 5-HIAA, HVA and iso-VMA (internal standard) were purchased from Sigma-Aldrich, St. Louis, USA. All other chemicals used were of HPLC or analytical grade as appropriate. The solutions of reserpine and RMN under study were prepared in DMSO and the volume of each dose was adjusted to 0.1 ml/100 gm body weight as suggested by Varma et al., [ 49 ]. The doses of RMN were calculated on equimolar basis of reserpine. Animal experiments Albino rats of either sex weighing between 100–150 gm (Charkaborty Enterprise, Kolkata) were used in the study. They were acclimatized to the laboratory conditions for at least 10 days prior to the experiment and were provided with standard diet and water ad libitum with 12 h light and dark cycle. The animal experiments conducted in this research work were approved by the Institutional Animal Ethics Committee and by the government regulatory body for animal research (Regd. No. 516/01/A/CPCSEA). Biochemical estimations Animals were divided into 4 groups of six each and were housed individually in metabolic cages. Funnels of suitable size were arranged at the bottom of the metabolic cages for collection of urine. Perforated plastic discs were arranged in the funnels to retain fecal matter. The animals were maintained at room temperature and acclimatized to metabolic cages for few days prior to drug administration. The treatment given to the groups of animals was as follows: Group 1: Control animals treated with DMSO intraperitoneally at a dose of 0.1 ml/100 gm body weight. Group 2: Animals administered intraperitoneally with reserpine at a dose of 5 mg/kg body weight. Group 3: Animals administered intraperitoneally with RMN at a dose equivalent to 5 mg/kg body weight of reserpine. Group 4: Animals administered intraperitoneally with RMN at a dose equivalent to 10 mg/kg body weight of reserpine. In each group, animals were placed individually in metabolic cages after drug administration and were allowed access to water. The 24 h urine samples from the point of drug administration was collected for each animal in a beaker containing 5 ml of 6 M HCl arranged at the bottom of the funnel. The volumes of the 24 h urine samples collected in the beakers were noted individually and about 2 ml of urine (mixture) from each animal was taken into sample tubes and centrifuged at 3000 rpm for 10 minutes. The supernatants were transferred into another set of clean and dry tubes and stored at -20°C until analysis by HPLC. Simultaneous HPLC determination of VMA, 5-HIAA and HVA in urine The procedure described by Wako-chem. Co.,[ 55 ] was used for the simultaneous determination of the above metabolites. The urine samples were thawed before analysis. To 0.2 ml of each sample, 0.1 ml of internal standard (iso-VMA, 1000 ηg) and 0.7 ml of mobile phase were added. The solutions were mixed well and filtered through 0.4 μm membrane filter. The filtrate (20 μL) was injected into the column (RP C-18, 250 mm × 4.6 mm I.D; particle size 5 μm; YMC Inc., USA). The mobile phase (filtered through 0.4 μm membrane filter) comprised of 10:90 v/v of acetonitrile and 0.1 M KH 2 PO 4 and the flow rate of the mobile phase was maintained at 0.8 ml/min, which yields a column back pressure of 220–230 kgf/cm 2 . Detection was done by UV absorption at 230 ηm. The range of the detector was set at 0.001 a.u.f.s. The peak area ratios of VMA, 5-HIAA and HVA to that of internal standard were calculated and substituted in the respective regression equations to estimate the amount of the metabolite present in the sample. Effect on normal blood pressure of anaesthetized rats The procedure described by Noble [ 56 ] was followed to evaluate the effect of RMN on normal blood pressure of anaesthetized rats in comparison with reserpine. Groups of rats of six each were anaesthetized with an intraperitoneal injection of thiopentone (40 mg/kg body weight). The femoral vein was cannulated for administration of supplementary doses of anaesthetic (if required) and drug solutions. Haemodynamic setup was used to record the blood pressure of rats. The blood pressure of each animal was recorded from left common carotid artery connected to a mercury manometer on kymograph paper. The normal blood pressure of rats was recorded after stabilization for 30 minutes. The different doses of reserpine (0.25, 0.50, 1, 5, 10 and 15 μg/kg body weight) or RMN (10, 25 and 50 μg/kg body weight) were studied in separate groups (n = 6) to determine the change in blood pressure response. Statistical analysis Data are expressed as mean ± standard error of means. Statistical analysis was done using one-way analysis of variance (ANOVA). Post-hoc comparisons were done by using Dunnet's t -test. In all the cases, p < 0.05 was considered statistically significant. Abreviations RMN: Reserpine methonitrate VMA: Vanillylmandelic acid 5-HIAA: 5-Hydroxyindoleacetic acid HVA: Homovanillic acid DMSO: Dimethyl sulfoxide Authors' contributions SN made significant contribution in designing the studies, conducting the experiments, interpretation of the data, conceptualization of statistical analyses and drafting the final manuscript. KMB assisted in experimental work, data analysis and writing of the manuscript. SS conceived the study, made substantial contributions in data analysis, data interpretation, writing of the manuscript and in coordination of the experiments. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC535563.xml |
533884 | Rationale and design of a multicenter randomized controlled trial on a 'minimal intervention' in Dutch army personnel with nonspecific low back pain [ISRCTN19334317] | Background Researchers from the Royal Netherlands Army are studying the potential of isolated lumbar extensor training in low back pain in their working population. Currently, a randomized controlled trial is carried out in five military health centers in The Netherlands and Germany, in which a 10-week program of not more than 2 training sessions (10–15 minutes) per week is studied in soldiers with nonspecific low back pain for more than 4 weeks. The purpose of the study is to investigate the efficacy of this 'minimal intervention program', compared to usual care. Moreover, attempts are made to identify subgroups of different responders to the intervention. Methods Besides a baseline measurement, follow-up data are gathered at two short-term intervals (5 and 10 weeks after randomization) and two long-term intervals (6 months and one year after the end of the intervention), respectively. At every test moment, participants fill out a compound questionnaire on a stand-alone PC, and they undergo an isometric back strength measurement on a lower back machine. Primary outcome measures in this study are: self-assessed degree of complaints and degree of handicap in daily activities due to back pain. In addition, our secondary measurements focus on: fear of movement/(re-) injury, mental and social health perception, individual back extension strength, and satisfaction of the patient with the treatment perceived. Finally, we assess a number of potential prognostic factors: demographic and job characteristics, overall health, the degree of physical activity, and the attitudes and beliefs of the physiotherapist towards chronic low back pain. Discussion Although a substantial number of trials have been conducted that included lumbar extension training in low back pain patients, hardly any study has emphasized a minimal intervention approach comparable to ours. For reasons of time efficiency and patient preferences, this minimal sports medicine approach of low back pain management is interesting for the population under study, and possibly for comparable working populations with physical demanding job activities. | Background Treatment of low back pain in the military setting: a 'minimal intervention approach' For the last ten years, clinical researchers from the Royal Netherlands Army (RNLA) have studied the potential of physical training modalities in preventing and alleviating nonspecific low back pain (LBP) in their working population. Many military and civilian job functions in the RNLA involve heavy manual material handling and, therefore, spine-loading activities. In general, the incidence of back problems is higher in physically demanding tasks than in sedentary activities [ 1 ]. Concordantly, the incidence of LBP in the RNLA is high. Acute LBP is the primary reason for soldiers to visit the general practitioner at a military health center. Chronic nonspecific LBP, defined as having complaints for at least 12 weeks, is one of the three most diagnosed disorders during consulting hours of Dutch military company doctors, and takes on average 15% of their weekly consulting hours time. Currently, there is strong evidence that exercise therapy is more effective than usual care [ 2 ]. Exercise therapy is a major part of the standard treatment by physiotherapists in the RNLA, involving an active role of the patient. In the experience of our health professionals (practitioners and physiotherapists), this active approach fits in well with the attitudes and beliefs of the target population: soldiers are taught to be aware of their physical abilities and limitations from the moment they enlist for the army. After all, recruits who do not successfully complete their basic training cannot progress on to a career as a soldier. The specific character of military tasks nowadays, e.g. (preparation for) crisis management operations abroad, interferes with the schedules of rehabilitation programs for back-injured soldiers which, in general, take several days per week over a considerate number of consecutive weeks. Therefore, the search for effective and (time-) efficient exercise therapy protocols has led us to a specific form of lumbar extension training. Each training session consists of no more than 5 to 10 minutes training of the isolated lumbar extensors on a special training device. Arguments for this study For a number of years, we have experience with high-intensive, isolated training of the lumbar extensors in military personnel with nonspecific LBP, by using a special training device. In this a sports medicine approach is followed, partly according to established exercise protocols [ 3 , 4 ], in which three key principles are emphasized: (1) isolation of the lumbar extensors through fixation of the pelvis and thighs; (2) training in the individual's full range of motion; (3) avoiding 'sticking points' in the training load – i.e. points in the range of motion in which a relatively high resistance is experienced – by tuning the load curve of the weight stack to the individual's strength curve. In individual cases, we observed satisfying to sometimes excellent results in terms of pain relief and functional restoration, when giving a training stimulus of no more than 5 to 10 minutes (1 to 2 training sessions) per week. These findings, however, need to be confirmed in a randomized controlled trial. Four main reasons led to the choice of doing research on the efficacy of this sports medicine approach for our working population with LBP. First, recent systematic reviews indicate that exercise therapy is a successful approach for the restoration of chronic and recurrent LBP, at least in the short term [ 2 , 3 ]. However, higher quality studies generally show a lack of treatment specificity of different exercise modalities, e.g. aerobic exercises, strength and endurance reconditioning or mobilizing exercises [ 4 , 5 ]. Moreover, controversy remains regarding the impact of a training stimulus, in terms of intensity, duration and frequency, on the reduction of LBP. Different explanations for this lack of specificity are given in the literature, such as non-specific, more centrally induced training effects, e.g. a shift in pain perception [ 5 ], or large heterogeneity in the chosen study populations [ 6 ]. If, indeed, no specific dimension or type of exercise therapy is superior to one another in producing optimal therapeutic outcomes, other aspects are more relevant when introducing an intervention program, such as: treatment affinity, expectation and compliance of patient and provider, costs, facilities, and personnel capacity. From this perspective, back strength and endurance training in CLBP patients with the use of training devices is an interesting concept for our military population. RNLA personnel are, from their very first initial military education, used to participate in physical exercise programs, including progressive resistance training on exercise machines. The RNLA is well equipped with an extensive line of modern fitness devices on all major military locations throughout the country, including state-of-the-art lower back machines. Moreover, protocolized treatment sessions with our training device take no longer than 5 to 10 minutes once or twice a week from both patient and provider, compared to (on an average) 30 minutes in regular treatment sessions. We expect this time efficiency to be highly appreciated by our personnel, who work in a typical military culture of "running into extremes": relatively quiet (maintenance) periods on the military base are interspersed with extremely busy periods shortly before and during out-of-area operations. For several target groups, longstanding and time-consuming rehabilitation programs are out of the question. For instance, recruits who drop out of their initial training because of (back) injuries, need to return as quick as possible to prevent a stagnation in their military career. For soldiers standing by for military operations, everything revolves around the mission when being commanded to be prepared within the next weeks. A second reason for our approach is that the majority of studies on LBP management consist of multimodal interventions, which include physical, behavioral, educational and/or ergonomic elements. To obtain a better view on the (relative) efficacy of either of these concepts, unimodal intervention programs like ours need to be evaluated [ 7 , 8 ]. Besides, we strongly believe that exercise as the primary entrance for restoring back function has a wide span of treatment effects, including improvements for cognitive and/pr behavioral variables. Although exercise has a primary goal of improving functioning of targeted tissues, successful completion of exercise protocols in the presence of chronic pain may for example lead to a reduction in pain-related fears. As standardized exercise on a training machine is based on measured performance (number of kilograms and repetitions), patients are continuously given numerical feedback regarding their increasing physical capacities [ 9 ]. An increased awareness of improving physical capacities may draw their attention away from pain and suffering. Third, the choice for a particular intervention approach depends in many cases on the stage and severity of the back problem, the extent to which psychosocial aspects are involved, and the needs and preferences of the patient. For instance, behavioral therapy is mainly focused on issues that are prevalent in chronic patients, such as low feelings of self-control or fear of movement/(re-)injury. Since the population of the present study, military employees of the RNLA, is a working population with mostly short-term, intermittent and moderately severe LBP, we chose to apply a more physical approach. As we have seen in our previous research (see the next paragraph), this links well with the health perceptions of our target population, in which perceived health problems were not severe and much more focused on physical than on mental aspects. Fourth, the efficacy of isolated extension training in chronic back patients has been studied by several other research groups as well [ 10 ]. Although promising results were reported regarding lumbar strength improvements and pain relief, several methodological shortcomings hinder solid interpretation of these findings. Most problems encountered were a small sample size, lack of randomization, lack of long-term follow-up results, variation in study populations (e.g. healthy volunteers, employees receiving worker's compensation), and inadequate or missing control groups [ 7 , 10 - 14 ]. In a review on lumbar extension training with MedX-equipment in LBP patients, Miltner et al [ 8 ] conclude that more controlled studies are needed "to delineate further the role of isolated lumbar extension exercise for the treatment of LBP and to test the efficacy compared to other methods of care." Earlier research on our minimal intervention approach Especially in recent years, we have scientifically studied the potential of our sports medicine approach. In two previous trials we compared the efficacy of a high-intensive, progressive resistance training program of the isolated lumbar extensors, with a low-intensive, non-progressive program of the same extend, in a group of workers with nonspecific LBP. Total intervention time of both 'minimal intervention programs' was limited to 14 sessions of 5 to 10 minutes, over a period of 12 weeks (1 st trial) or 8 weeks (2 nd trial). In the first trial, we were unable to demonstrate that either of the two training programs was superior in alleviating back complaints [ 15 ]. However, the magnitude of the improvements in back function found in this study were in line with those reported in other studies, which used more extended (multimodal) exercise programs. Therefore, it would be interesting to compare the efficacy of our minimal intervention program with the usual care RNLA personnel with nonspecific LBP. Moreover, the results of our first trial indicated that some individuals with LBP might benefit more from an aggressive approach, showing a trend towards a higher improvement rate (self-assessed percentage decrease in complaints) directly after the 'minimal intervention' treatment, as well as a higher compliance to the treatment and a higher willingness to participate in physical exercise on the longer term. In the present multicenter study, we aim at identifying relevant subgroups of patients that show higher success rate due to this training approach. Methods Study design and population In a randomized, single-blinded multicenter trial, we evaluate the efficacy of progressive, isolated resistance training of the lumbar extensor muscles, compared to the usual care. The trial started in April 2002; data will be collected till the end of 2005. The source population (n = 23,000) consists of military employees of the RNLA. Our in- and exclusion criteria are listed in table 1 . Recruitment of participants takes place during regular office hours of the military general practitioner. A brief outline of the study design is presented in Figure 1 . Study sites Almost every military location in the Netherlands has a health center, in which general practitioners, dentists and physiotherapists give primary care to military personnel of the RNLA. For the present study we selected five military health centers on the basis of: (1) representing a major part of the total military population; (2) holding at least two full-time physiotherapists, and (3) the willingness to unconditionally participate in the project. The selected military health centers include the following locations: • Amersfoort, in the middle-east of the Netherlands: approximately 15% younger soldiers on stand-by for military operations abroad (18–25 years), 25% military instructors (35+ years), 10% staff personnel (40+ years), and 46% civilian workers from supporting units (40+ years); • Den Haag, in the west of the Netherlands: approximately 90% older staff personnel (40+ years) at office work; • Oirschot, in the south of the Netherlands: approximately 75% younger soldiers in their initial military education or on stand-by for military operations abroad (18–25 years), 25% military instructors and staff personnel (35+ years); • Schaarsbergen, in the south-east of the Netherlands: approximately 65% younger soldiers in their initial military education or on stand-by for military operations abroad (18–25 years), and 30% staff personnel (35+ years); • Seedorf, in the north-west of Germany (part of the 1 German/Netherlands Corps): approximately 65% younger soldiers on stand-by for military operations abroad (18–25 years), 20% staff personnel (35+ years), and 10% civilian workers from supporting units (40+ years). Study population Recruitment, enrollment, and randomization All general practitioners at each of the selected study centers identify potential subjects from among their clinic's patients, according to the aforementioned criteria. Each subject is submitted to regular history taking and physical examination by the physician; checklists with standard elements for LBP have been provided to all physicians. If eligible, patients are informed about the study. All relevant information from the intake is written down in a referral; a visit to one of the physiotherapists of the center is planned within the next days. At the first visit to the physiotherapist, patients receive further information about the trial. A pre-assessment of the isometric back strength is taken. A written explanation of one of the questionnaires, in which patients have to choose the three most disabled daily activities due to back pain, is given them to take home, which allows them to make a well-considered choice at the next visit. Written informed consent is obtained from all patients who are willing and eligible to participate. At the second visit, participants undergo a baseline measurement consisting of a compound questionnaire and an isometric back strength test. At the third visit, patients are randomized into either the back strengthening group or usual care group. Directly after randomization, the first treatment session starts. Patients are allowed to withdraw from the study at any time, although the importance of full compliance of every participant is emphasized. Randomization is done by means of a computer-generated table of random numbers per study center, using a block size of ten. Prestratification is applied for the duration of the back complaints, with a cut-off point of 12 weeks, suspecting duration of complaints to influence the individual response to the exercise program. One intervention group receives a back-strengthening program; the other group receives a usual care program. The randomization is concealed, which means that the treating physiotherapist obtains the allocated treatment by means of a computer software program, by entering the name and military registration number of the patient. The study protocol was approved by the Medical Ethics Committee of the Netherlands Central Military Hospital. Study interventions Back strengthening program Subjects allocated to the back-strengthening program (BS) undergo a 10-week, progressive resistance-training program of the isolated lumbar extensor muscle groups. The program includes 14 training sessions (2 days per week) and 3 isometric back strength tests (in week 1, 5, and 10). The initial training load is set at approximately 35% of the maximal isometric back extension strength of the participant, measured at baseline. The goal of every training session is to perform 15 to 20 repetitions (reps) on the lower back machine, equivalent to approximately 50% and 70% of the one-repetition maximum (1 RM) respectively. If the subject is able to perform a higher number of reps, 2 1/2 kg weight is added in the next training session. Vice versa, if the participant is unable to perform the minimal number of reps, the subsequent training load is lowered with 2 1/2 kg. This training protocol is partly based on existing protocols [ 5 , 18 ], and partly on our own experiences. A comprehensive training protocol can be obtained from the authors. Training sessions are carried out on a Total Trunk Rehab (Technogym Inc, Italy). This lower back machine is equipped with a knee-lock system and a thigh-restraining belt to immobilize both hips and thighs, allowing the participant only to move the isolated lower back. All training sessions are conducted as much as possible by the same physiotherapist. The physiotherapist pays special attention to the execution of the training in terms of pace and movement. The flexion and extension of the lower back has to be executed in the full range of motion of the participant, and movements have to be slow and controlled (moving in two seconds from maximal flexion to maximal extension when lifting the weight stack, and returning from maximal extension to maximal flexion in four seconds when lowering the weight stack). During this movement, emphasis is put on the hollowing and flattening of the lumbar lordosis. Every training session is preceded by a 5-minute all-body warming-up on an arm/leg ergometer (Schwinn Airdyne Pro, Balans Inc., Nieuwegein, The Netherlands). The weight load used and the number of reps completed during each training session are recorded. Usual care program Subjects allocated to the usual care program (UC) receive regular physical therapy for their lower back for at most 10 weeks, or earlier when the patient indicates to be free of complaints. Based on the physiotherapist's judgment, this could include 'hands-on' treatment (e.g. passive mobilizing and pain-cushioning techniques, manual therapy) and/or 'hands-off' treatment (e.g. exercise therapy, individual education and instruction on the back function). In the RNLA, active therapy forms are favored. To increase the contrast between both intervention programs, physiotherapists are not allowed to use the lower back machine in their usual care. Patients are not allowed to undergo co-treatment beside the interventions programs during the treatment period, nor exercise on equipment that mimics the specific components of the lower back machine. Therapeutic activities in every therapy session as well as the number of sessions are written down on a form. Outcome measurements In this study we have chosen primary outcome measures that are most relevant to the patient and clinician: self-assessed degree of complaints and degree of handicap in daily activities due to LBP. In addition, our secondary measurements focus on several other LBP-related areas, like kinesiophobia or mental health perception. We have included some potential prognostic factors into our measurements, i.e. characteristics of the patient that possibly influence the effect of the intervention: job characteristics, overall health, physical activity, patient satisfaction with the allocated treatment, and attitudes and beliefs of the physiotherapist. This trial is mainly focused on the efficacy of our minimal intervention strategy, and not on unraveling the physiological or psychological working mechanisms of isolated lumbar extension training on LBP. Nevertheless, by including potential prognostic variables, starting points for further research into the 'black box' of this type of intervention could be identified. Baseline characteristics The following demographic variables are registered during the intake: age, time since first episode of LBP, pain radiation, treatment history, and work absenteeism due to LBP in the last year. Moreover, the status of the patient before treatment, in terms of job aspects, overall health and the degree of physical activity, is assessed using a compound questionnaire. Several job characteristics, i.e. content, relation with superior and colleagues, conflicts, and physical aspects of the job, are measured using subscales of a validated Dutch version of the Job Content Questionnaire [ 16 ]. Physical aspects of former jobs are assessed using one item of the Dutch Musculoskeletal Questionnaire [ 17 ]. Overall health is assessed with one item from the MOS 36-item Short Form Health Survey [ 18 ]: "What do you think, in general, of your health?" (1 = bad, 2 = moderate, 3 = good, 4 = very good, 5 = excellent). The degree of physical activity is measured with the Short Questionnaire to Assess Health Enhancing Physical Activity [ 19 ], a validated and fairly reliable 5-item questionnaire. To assess the attitudes and beliefs of the participating physiotherapists about the relationship between low back pain and function before the start of the study, we use the Pain Attitudes and Beliefs Scale for Physiotherapists [ 20 ]. These attitudes and beliefs are believed to influence the physiotherapist's commitment to a certain treatment approach. Primary outcome measures Global perceived effect [ 21 ] is measured by self-assessment on a 7-point scale (1 = completely recovered, 2 = much improved, 3 = slightly improved, 4 = no change, 5 = slightly worsened, 6 = much worsened, 7 = vastly worsened). We defined scores of 1 and 2 as a clinically important change. Patient-specific functional status [ 22 ] is measured by a questionnaire following a patient-specific approach. At baseline, individual patients select three main complaints, i.e. frequent activities which they perceive as important in their daily life, but which are hampered by their back pain. Patients rate the severity of these three complaints on a 100 mm visual analogue scale at each test moment. The responsiveness of the questionnaire is fairly good, with an area under the ROC-curve of 0.82, and with mediate correlations with the Roland Disability Questionnaire (r = 0.69–0.75) and the Visual Analogue Scale (r = 0.70–0.80) [ 21 ]. Low-back specific functional status is measured by the validated Dutch version of the Roland Disability Questionnaire [ 23 , 24 ], a widely used 24-item scale that reflects the functional disability due to LBP. Test-retest reliability of this scale is considered good for three weeks (r = 0.83) and six months (r = 0.72) respectively [ 25 ]. Secondary outcome measures Fear of movement or re-injury is measured by the Tampa Scale for Kinesiophobia [ 26 ], a 17-item scale to obtain a score for the extent to which a chronic back patient fears (new) physical damage due to physical activity. The Dutch version of this questionnaire has been found sufficient reliable and valid [ 27 , 28 ]. Mental health is measured by the Dutch translation of the 12-item General Health Questionnaire [ 29 , 30 ], assessing problems concerning psychological distress, like depression, sleep deprivation, stress coping, and self confidence. Test-retest reliability of the scale is high in a general population, with reported Cronbach's alpha coefficients between 0.86 and 0.90 [ 30 ]. Social health is measured by a subscale of the Impact on Participation and Autonomy Questionnaire [ 31 ], focusing on the influence of the disability on social relationships; Cronbach's alpha for this factor is 0.87. Overall work status is measured by a 4-level item (1 = "currently working full duties and/or able to do all of my regular home duties", 2 = "able to do all work and/or home duties but it causes extra pain", 3 = "on restricted duties at work and/or need help with some of my home duties", 4 = "off work and/or need help with most of my home duties"). Individual back extension strength progression was evaluated using repeated isometric measurements on the lower back training and testing machine. A detailed description of these measurements can be find elsewhere [ 15 ]. Patient satisfaction is measured at the end of the treatment program by two 3-level items and one 5-level item, in which the degree of satisfaction with the allocated treatment is assessed: (a) "Were you satisfied with the allocated treatment at the start of the program?" (b) "Has your opinion about the treatment changed during the program?" (c) "How satisfied are you now about the treatment that was given to you?" Short- and long-term follow-up Beside a baseline measurement, follow-up data are gathered at two short-term intervals and two long-term intervals. Short-term follow-up measurements are at 5 and 10 weeks after randomization. Long-term follow-up measurements are at 6 months and one year after the end of the intervention, respectively. At every test moment, participants fill in a compound questionnaire on a stand-alone PC, and they undergo an isometric back strength measurement on the lower back machine. The content of the questionnaire varies per test moment: parts of the questionnaire referring to potential prognostic variables (job characteristics, overall health, and physical activity) are only displayed at baseline, and at 6 and 12 months of follow-up. Figure 1 presents a flow chart of the different phases of the study. Blinding Double blinding or placebo control is virtually impossible in trials that involve treatment modalities like the ones used in this study, since both patient and provider are inevitably aware of the content of the treatment. Because our physiotherapists are aware of which treatment they provide, there is always the possibility that they may inadvertently convey different expectations to the patients in each treatment program. This could enhance non-specific effects in either of the two groups. Therefore, as mentioned, beliefs and attitude of the physiotherapists towards back treatment in general are evaluated at baseline, as well as at the end of the study period. Another limitation of trials comparing a relatively new treatment to the usual care is the risk of a potential nocebo effect; i.e. patients might feel disappointed after being allocated to the standard therapy. To minimize this effect, both programs are introduced to the patient as potentially equally effective treatments in restoring back function, with the relative efficacy of both programs as the main focus of the study. Moreover, at baseline patients are informed about the opportunity they have to continue with a treatment modality of their choice (e.g. our training device) after finishing the treatment period. Patient satisfaction with the allocated treatment is measured directly after the treatment period. Other efforts to achieve a certain level of blinding within patients, physiotherapists, and data researchers, are: • low back strength training and measurement are done as much as possible by two different physiotherapists; • an independent data manager collects data from all study locations, and recodes patients and locations to unique codes before handing the database to the researchers. Statistics Sample size estimates We attempt to enroll 200 patients at the four military health centers, i.e. 100 patients per treatment group. According to power calculations (α = 0.05 and 1-β = 80%), this sample size is sufficient to detect a 20% difference in our primary outcome measure Global Perceived Effect, between the BS and UC program. In our beliefs, a 20% difference reflects a clinical relevant change in health status. Data analysis Statistical analysis will be performed according to the intention-to-treat principle; i.e. patients will be analyzed in the treatment group to which they were randomly allocated. In addition, a per-protocol analysis will be performed, in which only patients with no major protocol deviations will be analyzed. Comparing these analyses with the results of the intention-to-treat analysis will indicate, to what extend protocol deviations and lack of compliance might have biased the results. In our analyses, we will compare the size of the effect, if any, of isolated back strengthening and of usual care for the low back on our primary and secondary outcome variables. Further analysis will determine whether several potential prognostic variables will influence the magnitude of the treatment responses, and if subsets of patients can be distinguished that can be indicated as good-/bad-responders to our specific back training. Demographic and clinical characteristics, as well as baseline outcome measures will be summarized by descriptive statistics. Longitudinal multilevel analyses will be used to examine differences in all continuous outcome measures at 5 and 10 weeks after randomization, and 6 and 12 months of follow-up. Supervision of the centers In order to obtain full commitment from the participating military health centers, as well as to make sure that every center uses the study protocols in the same way, we organize several feedback and feedforward sessions with all participating physiotherapists. In these sessions, we explain different aspects of the trial design, give instructions on the test and training protocols, and answer remaining questions. After these sessions, we install the required equipment (test/training machine, soft- and hardware) at the four locations. Each center has a practice period of about 8 weeks to become familiar with the instruments, logistics and protocols, by means of ad hoc training and test sessions with non-participating (regular) back patients. Our researchers join these sessions and, if necessary, give correcting feedback during and after a test or training. After this practice period, each location officially starts with the study. Once every two weeks, our researchers visit the centers to monitor progress in recruitment and data handling, and to observe the execution of test and training sessions. Discussion This article describes the rationale and design of a multicenter randomized controlled trial in which the efficacy of a specific type of lumbar extension training and usual care are compared in patients with nonspecific LBP longer than 4 weeks. A substantial number of trials have been conducted that included lumbar extension training in low back pain patients [ 4 , 7 , 11 , 12 , 32 , 33 ]. So far, only the study by Risch et al [ 11 ] has emphasized a minimal intervention approach comparable to ours, which was, however, conducted in a non-randomized study design. Our population at risk can be seen as a selected population of mainly male employees, who work in a dynamic organization with a strong culture of physical fitness. We realize that this selection might limit the external validity of the outcomes of this study. However, results of the trial may be extrapolated to other working populations with a more-than-average degree of physical straining job activities, e.g. policemen and firemen on duty or construction workers. Besides, despite the "fit-and-healthy" image that soldiers have in our society, a large health survey among a cross-section of male military personnel of 30–40 years showed no favorable scores on several cardiovascular and fitness parameters in comparison to other populations of Dutch men [ 34 , 35 ]. In this perspective, the RNLA – with over 30,000 military and civilian employees a major professional organization in the Netherlands – seems to be a good reflection of Dutch society in general with regard to general health parameters. Moreover, for reasons of homogeneity it might be even an advantage to only have a study population of working men with (probably) moderate low back trouble in this study. We hope with this trial to give greater insight to caregivers within and outside the RNLA on treatment options for workers in the sub-acute or chronic phase of their LBP. If, for instance, our minimal intervention approach is equally or more effective than the usual care, medical decision makers may consider implementing this treatment modality in the daily practice of the physiotherapist, by weighing the costs (e.g. price and depreciation costs of materials) and benefits (e.g. reduction of treatment time). List of abbreviations RNLA = Royal Netherlands Army RCT = randomized controlled trial LBP = low back pain BS = Back Strength intervention UC = Usual Care intervention rep = repetition on back extension machine Competing interests The authors declare that they have no competing interests. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC533884.xml |
544359 | A survey of medical students to assess their exposure to and knowledge of renal transplantation | Background Within the field of renal transplantation there is a lack of qualified and trainee surgeons and a shortage of donated organs. Any steps to tackle these issues should, in part, be aimed at future doctors. Methods A questionnaire was distributed to final year students at a single medical school in the UK to assess their exposure to and knowledge of renal transplantation. Results Although 46% of responding students had examined a transplant recipient, only 14% had ever witnessed the surgery. Worryingly, 9% of students believed that xenotransplantation commonly occurs in the UK and 35% were unable to name a single drug that a recipient may need to take. Conclusions This survey demonstrates a lack of exposure to, and knowledge of, the field of renal transplantation. Recommendations to address the problems with the recruitment of surgeons and donation of organs, by targeting medical students are made. | Background With the potential for improved quality of life and increased life expectancy, renal transplantation is the first choice treatment for most patients with end-stage renal failure [ 1 , 2 ]. However, in the UK there is an ever-increasing disparity between the number of patients on the waiting list and those being transplanted [ 3 ]. This is predominantly due to a rise in the incidence of renal failure amongst an aging, racially diverse society in conjunction with a shortage of donated organs [ 4 ]. The field of renal transplantation also suffers from a lack of surgeons. Indeed, it is predicted that by the year 2005 there will a shortage of over twenty consultant renal transplant surgeons [ 5 ]. Any measures to deal with these problems must include educating and attracting the doctors of tomorrow; medical students [ 6 , 7 ]. However, the General Medical Council's core curriculum model for undergraduate teaching has lead to significant changes in the way that specialist subjects are taught [ 8 ]. This survey was conducted to assess the exposure to, and knowledge of, renal transplantation amongst medical students at a single medical school in the United Kingdom. Methods In July 2003 a PRHO job fair was held for final year medical students of Bristol University, which all 140 students within the year attended. An anonymous questionnaire was distributed to every student, after the aims of the study had been explained, at the end of a series of short lectures. (Figure 1 ). The questionnaire consisted of six questions, three to assess their exposure to the field and three to assess their knowledge. The form was collected immediately upon completion, with no opportunity to confer. Figure 1 Questionnaire distributed to the students. The questionnaire had been piloted on a random sample of thirty final year medical students from the year before, whereby the form was distributed electronically to their University email accounts. This confirmed that the length and wording of the questionnaire, and the level of knowledge required to complete it were appropriate for the target population. All statistical analysis was performed using the chi square test, with a p value of 0.05 or less taken to demonstrate statistical significance. Results Questionnaires were completed by seventy-six of the 140 medical students in the year (54%). Of these responding students, thirty-two (42%) had never completed either a general medical or general surgical placement at one of the two centres for renal transplantation within the region, both of which are affiliated to the University of Bristol. National data of renal transplantation activity shows that these two centres differ in the number of transplants performed each year [ 3 ]. Over the 2002/3 and 2003/4 period Southmead Hospital, Bristol performed approximately three times as many transplants per year than Derriford Hospital, Plymouth (2002/3: 101 in Bristol, 36 in Plymouth, 2003/4: 132 in Bristol, 42 in Plymouth). Sixty-five students (86%) had never been in the operating theatre during a renal transplant. Of the eleven students that had witnessed a transplant the majority, seven, had been unscrubbed (9%). One student had been scrubbed and observing and a further three students (4%) had actually assisted with the procedure. Closer analysis of these eleven students demonstrates that only one of the eleven had been on placement at Derriford Hospital (χ 2 , p = 0.006). Thirty-five (46%) of the students had examined a patient with a transplanted kidney but only thirty-three (43%) could accurately draw on a diagram the usual site of surgical incision that would be made on someone undergoing a left sided renal transplant. Interestingly, fourteen of the students that claimed to have examined a transplant recipient were unable to accurately draw the site of incision. Of the students that had examined a transplant recipient twenty-two had been on placement at one of the hospitals with transplant centres and thirteen had not (χ 2 , p = 0.128). Fifty students (66%) were aware that in addition to the use of organs from brain stem dead donors, kidneys could also be transplanted from living donors. Eighteen students (24%) could not name any additional sources of organs and seven (9%) thought that xenotransplantation, using porcine kidneys, is carried out in the UK. None of the students suggested non-heart beating donation. Nineteen students (25%) were unable to name a drug that might be taken by a patient with a renal transplant. Twenty-one students (28%) were able to suggest just one. Discussion This survey highlights both a low exposure to, and a lack of knowledge about, the field of renal transplantation amongst medical students. This is cause for concern as it has implications for the future recruitment of trainees to the speciality and, potentially, to the procurement of organs. Previous work has highlighted the multiple factors that deter surgical trainees from this speciality [ 5 ]. These include the on-call commitment, unpredictable workload and a lack of exposure to the speciality, at an early stage in training. Based on this information, calls have been made to increase the exposure of surgical trainees by the inclusion of transplantation within basic surgical training (BST) rotation programmes [ 5 ]. However, as there are only 23 surgical centres performing renal transplantation within the UK it is unlikely that all trainees would be exposed to the field. In order to gain exposure to the maximum number of doctors, early in their careers, targeting medical students may yield the best results. Indeed, a recent crisis meeting regarding recruitment to renal transplant surgery identified that early positive exposure to the field is vital, and should begin at the undergraduate level [ 6 ]. This survey highlights that the potential for the promotion of renal transplantation within the undergraduate course is currently relatively unexplored. The lack of knowledge regarding sources of organs commonly used within the UK is also of concern. In order to increase the number of kidneys available UK Transplant funds a number of non-heart beating programmes. Such initiatives can potentially increase the transplant rate by 20–40% [ 9 ]. Identifying all potential heart beating and non-heart beating donors is fundamental to providing a successful service, and reducing the gap between donors and patients on the waiting list. However, if future doctors are unaware of the existence of these programmes then such schemes are unlikely to reach their full potential. One of the limitations of this study is the selection bias from a 54% response rate. From talking to some of the students who did not complete the questionnaire it became apparent that those who had no experience or knowledge of the speciality were less likely to participate. This means that the results are probably over reporting the exposure to and knowledge of renal transplantation. A further limitation is that this work only represents the situation at one medical school. We believe that this situation is not unique to Bristol University and recommend that a national study be performed to assess the true extent of the situation. If transplantation rates are to be maximised and recruitment into the speciality improved, then ideally, all doctors should have some exposure to renal transplantation during the early stages of their career. Indeed a recent study has demonstrated that increased knowledge about organ donation is associated with higher levels of medical education, an increased likelihood of holding an organ donor card and feeling more comfortable in approaching relatives of potential organ donors [ 7 ]. Whilst it is realised that teaching time is of a premium at medical school this would be the ideal opportunity to promote transplantation. We believe that conventional methods such as ward based teaching, lectures and tutorials could be supplemented with a more multidisciplinary exposure. For example, involving students in patient education open days or the production of information leaflets/web pages could allow students to see from themselves the improvement in quality of life brought about by transplantation; Such learning experiences may prove more memorable for some students than those of the operating theatre. Conclusions This survey, carried out at a single UK medical school, has highlighted a low level of exposure to, and a lack of knowledge about, renal transplantation amongst medical students. These worrying results may influence the outcomes of any measures put in place to improve the recruitment of surgeons and the procurement of organs. If the trends within these areas are to be reversed then greater emphasis should be placed upon the promotion of renal transplantation within the undergraduate curriculum. Abbreviations UK United Kingdom PRHO Pre-registration house officer Competing interests The author(s) declare that they have no competing interests. Authors' contributions AGE designed the questionnaire, performed the study and was involved in the preparation of the manuscript. ARW and JDM were also involved in the design of the questionnaire and manuscript preparation. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544359.xml |
449870 | Lineage-Specific Gene Duplication and Loss in Human and Great Ape Evolution | Given that gene duplication is a major driving force of evolutionary change and the key mechanism underlying the emergence of new genes and biological processes, this study sought to use a novel genome-wide approach to identify genes that have undergone lineage-specific duplications or contractions among several hominoid lineages. Interspecies cDNA array-based comparative genomic hybridization was used to individually compare copy number variation for 39,711 cDNAs, representing 29,619 human genes, across five hominoid species, including human. We identified 1,005 genes, either as isolated genes or in clusters positionally biased toward rearrangement-prone genomic regions, that produced relative hybridization signals unique to one or more of the hominoid lineages. Measured as a function of the evolutionary age of each lineage, genes showing copy number expansions were most pronounced in human (134) and include a number of genes thought to be involved in the structure and function of the brain. This work represents, to our knowledge, the first genome-wide gene-based survey of gene duplication across hominoid species. The genes identified here likely represent a significant majority of the major gene copy number changes that have occurred over the past 15 million years of human and great ape evolution and are likely to underlie some of the key phenotypic characteristics that distinguish these species. | Introduction Gene and Genome Evolution The evolution of genomes has been primarily driven by single basepair mutation, chromosomal rearrangement, and gene duplication ( Ohno 1970 ; Samonte and Eichler 2002 ), with the latter being the key mechanism for generating new genes and biological processes that facilitated the evolution of complex organisms from primitive ones ( Li 1997 ). These factors are thought to also be important in hominoid evolution and speciation, although a systematic assessment of the relative contribution of each has not yet been possible. Over the past few years, as the human genome sequence has become available, it has become apparent that recent segmental duplications in the human genome are far more frequent than originally believed, comprising approximately 5% of the available sequence ( Bailey et al. 2001 ). Duplicated regions can range from one to several hundred kilobases in size and show very high sequence similarity (90%–100%) ( Bailey et al. 2001 ; Stankiewicz and Lupski 2002 ). While such regions can pose unusually difficult challenges for accurate genome assembly ( Cheung et al. 2003 ), they are also likely to be among the most evolutionarily recent duplications and thus are among the most important to human speciation and evolution. Interspecies cDNA Array-Based Comparative Genomic Hybridization The assessment of DNA copy number changes between different human genomes has been aided by the development of comparative genomic hybridization (CGH), which originally involved cohybridizing differentially labeled test and reference genomic DNAs to normal metaphase chromosomes ( Kallioniemi et al. 1992 ). A cytogenetic representation of copy number variation was obtained by scoring the resulting fluorescence ratios along the length of the chromosome. Increased resolution was obtained through the subsequent use of arrayed sets of either large genomic DNA clones or cDNA clones (array CGH [aCGH]) ( Pinkel et al. 1998 ; Pollack et al. 1999 ), with the latter having the advantage of permitting the analysis of individual genes. While cDNA microarrays, containing sequences derived from tens of thousands of genes, have been used extensively to profile mRNA expression levels ( Schena et al. 1995 ), their use in aCGH is technically more challenging. Human genomic DNA represents at least a 20-fold increase in complexity compared to human cellular mRNA, and the cDNA array elements represent a smaller (e.g., less than 2 kb), generally more discontinuous hybridization target for a genomic DNA sample. These technical issues notwithstanding, highly reproducible aCGH signals can be obtained using human genomic DNA against high-density human cDNA microarrays, and gene changes as small as an increase or decrease of a single copy can be detected ( Pollack et al. 1999 ). Until now, cDNA aCGH studies have been limited to only within-species comparisons, partly due to concerns related to the increased sequence divergence that would come into play with interspecies applications. Such sequence divergence may produce differential hybridization signals that would be difficult to distinguish from those that arose from copy number changes. Fortunately, despite their significant anatomical and physical differences, hominoid species show a strikingly high degree of similarity at the genome sequence level, with the average sequence divergence values estimated as 1.24%, 1.62%, and 1.63% for human–chimp, human–gorilla, and chimp–gorilla, respectively, and orangutan showing approximately 3.1% sequence divergence when compared to human, chimp, or gorilla ( Chen and Li 2001 ). Because of this close sequence conservation, we reasoned that it may be possible to use cDNA aCGH to directly compare the cross-species hybridization signatures of human genes to those of the great apes and to identify genes that have alterations in copy number and/or significant changes in exonic sequence between human and other hominoid species. After we initiated such a cDNA aCGH study, two interhominoid aCGH reports appeared that used arrays containing either cloned or amplified genomic DNAs ( Frazer et al. 2003 ; Locke et al. 2003 ). While these studies provided useful insights into hominoid DNA copy variations, they afforded little direct knowledge of changes in individual gene copy number and covered only limited sections of the genome. In contrast, interhominoid aCGH using human cDNA microarrays, representing more than 29,000 different genes, would allow a level of genomic resolution not previously obtainable and also provide direct data regarding the recent evolutionary history of a significant majority of human and great ape genes. Results/Discussion Identification of Lineage-Specific Gene Duplication and Contraction Interhominoid cDNA aCGH was carried out in a series of pairwise comparisons using microarrays containing 39,711 human cDNAs, representing the majority of all human genes ( Table S1 ). The pairwise comparisons involved using a great ape (or human control) as the test genomic DNA sample (Cy5 red dye) and a sex-matched human as the reference genomic DNA sample (Cy3 green dye) in all comparisons. In each experiment, a test and a reference genomic DNA were simultaneously hybridized to a human cDNA microarray under standard cDNA aCGH conditions ( Pollack et al. 1999 , 2002 ). Specific test/reference DNAs were bonobo/human, chimp/human, gorilla/human, orangutan/human, and, as a control, human/human. After background was subtracted and data normalized, hybridization signals were scored and fluorescence ratios of the test/reference genomic DNAs determined. Using relatively conservative cutoff values (see Materials and Methods ), cDNAs were identified that gave aCGH signatures unique to one or more of the hominoid lineages, permitting such gene changes to be placed within specific evolutionary time frames ( Figure 1 ). The TreeView program ( http://rana.lbl.gov/EisenSoftware.htm ) was used for visualization of aCGH data for each gene as it occurred in the genome, permitting a “gene-by-gene” survey of the data and allowing for easy detection of interspecies copy number variations, whether they occur as single isolated genes or as multigene blocks. Figure 1 TreeView Images of Examples of Great Ape and HLS Gene Copy Number Increases and Decreases Interhominoid cDNA aCGH was carried out as described in the text and Materials and Methods . Specific test DNAs were, left to right, human (H) ( n = 5), bonobo (B) ( n = 3), chimpanzee (C) ( n = 4), gorilla (G) ( n = 3), and orangutan (O) ( n = 3). Each horizontal row represents aCGH data for one cDNA clone on the microarray, while each vertical column represents data from one microarray experiment. Regions shown contain LS genes (vertical black lines) and adjacent flanking genes ordered by chromosome map position using the UCSC Golden Path genome assembly ( http://genome.ucsc.edu ), November 2002 sequence freeze. Arrows denote for which hominoid lineage the copy number change is unique. Note that fluorescence ratios (pseudocolor scale indicated) reflect copy number changes relative to the human genome. For great ape LS changes, red signal is interpreted according to parsimony as increased gene copy number, and green signal as decreased gene copy number in the specific ape lineage, while increased or decreased gene copy number specific to the human lineage is represented by green or red signal, respectively, in all the great ape lineages. Gray signal indicates cDNA comparisons scored as absent. Estimates of the time at which indicated branch points occurred during hominoid evolution are derived from Chen and Li (2001) . Results of the distribution of lineage-specific (LS) aCGH signatures for different individual hominoid species are presented in Figure 2 A. Several lines of evidence indicate that the aCGH signature variations that were obtained are primarily due to gene copy number changes and not to interspecies sequence divergence or highly repetitive sequences ( Figure S1 ; see also Materials and Methods ). Because bonobos and chimpanzees diverged relatively recently and show a striking degree of sequence similarity ( Kaessmann et al. 1999 ; Wildman et al. 2003 ), they were dealt with both as individual lineages as well as a single clade. After collapsing the LS dataset by UniGene cluster to remove redundant cDNAs corresponding to the same gene, 815 different genes were identified that gave aCGH signatures unique to a specific hominoid lineage. Each respective lineage and the numbers of genes identified that showed LS copy number change (increases/decreases) are as follows: human: 134/6; bonobo: 23/17; chimpanzee: 11/4; bonobo/chimpanzee pre-split: 26/11; gorilla: 121/52; and orangutan: 222/188. Figure 2 Number of LS Genes for Indicated Hominoid Lineages Totals of aCGH-identified LS genes are indicated for single lineages (A) and multiple (B) lineages, showing both increases (+) and decreases (–) for each. The numbers reflect totals after collapsing the dataset by UniGene cluster to remove redundant cDNAs corresponding to the same gene. Bonobo represents genes unique to this species; likewise with chimpanzee. “Bonobo and chimpanzee (pre-split)” refers to genes that were changed in both species and therefore likely occurred before these species diverged, and “bonobo and chimpanzee (total)” refers to the sum of the previous three categories, which was chosen to represent the period since the Homo/Pan split. Estimated evolutionary age of each lineage is also plotted for comparison. Letters denoting different great ape species are as in Figure 1 . For (B), bonobo and chimpanzee were grouped together as one lineage (C), but selection criteria had to first be met by both species independently. In (B), no LS genes were identified for the following cases: C(+)G(–); CG(–)O(+); C(–)GO(+); and CO(+)G(–). Several interesting features were evident from these data. First, when increases and decreases were scored separately or combined, the number of LS signatures was generally in proportion to the evolutionary age of that lineage, although not in all cases. Bonobo and chimpanzee, from the time since the Homo/Pan split, showed fewer LS signatures (92) than did human (140), even though they represent the same evolutionary age. As mentioned below, this is due in large part to the significant number of LS gene copy number increases found in human. Second, while all lineages showed more gene copy number increases than decreases, this was most pronounced in humans, with 134 cDNAs representing increases and only six representing decreases. This increase-to-decrease ratio (22.3:1) was significantly greater than that of any of the great apes, which showed ratios ranging from 2.75:1 (chimpanzee) to 1.18:1 (orangutan). It is worth noting that only genes found in the human genome are represented on the cDNA arrays, and if there are genes that are absent in human but present in the great apes, e.g., genes that were lost as the human lineage emerged, those genes would not be part of this analysis. So, while it is likely that the complete loss of both copies of a gene in an LS manner is a rare event, the number of genes identified here as having a reduced copy number specifically in the human lineage may be an underestimate of the true total. Third, as mentioned above, for all lineages tested, the number of genes showing LS increases was greater than those showing LS decreases. Determination as to whether this is due to some, as yet unknown, ascertainment bias of the method or whether this is a real evolutionary tendency favoring gene duplication over gene loss will require further investigation. The favoring of gains over losses is even more striking when two additional factors are considered. (1) The fact that the cDNAs were only from human, while likely to be important to the low number of genes showing human lineage-specific (HLS) losses previously mentioned, does not help explain why, for all lineages tested, the number of LS genes showing increases was greater than the number showing decreases. To the contrary, if there were genes not on the microarray because they were only found in one or more of the great ape lineages, inclusion of such genes would be expected to add to the total number of LS increases, making the disparity between increased and decreased LS genes even greater. (2) If human/great ape sequence divergence was responsible for some of the LS aCGH signals that were obtained, it would, if anything, produce a falsely elevated number of LS decreases. Fourth, while only orangutan had more LS gene copy number increases (222) than did human (134), when the number of genes showing copy number increases was measured as a function of the evolutionary age of the lineage, human showed the greatest number of expansions of any hominoid. When measured as copy number increases per million years of age, the following values were obtained: human, 26.8; bonobo and chimpanzee since the Homo/Pan split, 12; gorilla, 17.3; and orangutan, 17.1. We also identified genes that gave aCGH signatures indicative of great ape gene copy number changes, relative to human, that were present in more than one great ape lineage ( Figure 2 B). For situations in which two great ape lineages showed copy number losses relative to human, there was a general trend that correlated with evolutionary age of the represented species: Pan /gorilla, 16 genes; Pan /orangutan, 27, and gorilla/orangutan, 45. For gene increases, this trend continued, with gorilla/orangutan (17) showing more changes than Pan /orangutan (nine). Interestingly, Pan /gorilla showed a departure from this trend with 28 increased genes, suggesting that gene expansion may have been particularly active in the African great apes as a group. There were also a number of more complex gene copy number changes in the five hominoid lineages, with some species showing an increase relative to human for a particular gene and others showing a decrease. These changes are likely due to more than one event, which may be indicative of a genomic region that is relatively unstable and/or of genes whose copy numbers have been influenced by different selection pressures. We identified 190 genes that showed copy number changes in multiple lineages, bringing the total number of LS genes identified to 1,005, which represents 3.4% of the total number of genes tested on the microarrays. Given the relatively conservative selection criteria used (see Materials and Methods ), this likely reflects an underestimate of the true total. To visualize the effects of relaxing the selection criteria below a log 2 fluorescence ratio of 0.5, a series of HLS datasets were generated using progressively reduced thresholds. Using values of 0.45, 0.4, 0.35, and 0.3 added 27, 31, 31, and 22 cDNAs, respectively, as the cutoff was progressively lowered. As seen in the TreeView image of these data ( Figure S2 ), while some of the additional cDNAs could plausibly be scored HLS, several appeared to give marginal HLS signals. Independent Confirmation of Interspecies cDNA aCGH Data: Fluorescence In Situ Hybridization Analysis A cluster of several genes located around map position 70 Mb in human Chromosome 5q13.3 showed one of the stronger HLS aCGH signatures. Several of these genes (test probe), as well as a set of flanking genes not shown to be increased in human (control probe), were evaluated by interphase and metaphase fluorescence in situ hybridization (FISH) using bacterial artificial chromosome (BAC) probes (see Materials and Methods ). The FISH studies confirmed a duplication of the gene region in human, while the control probe containing a flanking region showed no duplication ( Figure 3 A). Two separate probe signals (and sometimes multiple probe signals) for the test probe could be seen in interphase nuclei with only one signal for the flanking probe; metaphase chromosomes showed a larger signal for the test probe than for the flanking probe. In all of the four great ape species, on the other hand, the FISH analyses showed no duplication of the gene region; all of these experiments showed a single signal for the test probe and a single signal of comparable size for the flanking probe ( Figure 3 B– 3 E). The Golden Path ( http://genome.ucsc.edu ) genome assembly lists multiple Chromosome 5 locations for some of the HLS cDNAs contained on the positive BAC (e.g., BIRC1 ) and therefore it is likely that the multiple, closely spaced signals seen in some of the human interphase spreads ( Figure 3 A) reflect additional copies of these genes. Figure 3 FISH Confirmation of a Human-Specific Duplication of a Gene Cluster on Chromosome 5q13.3 Detected by Interspecies cDNA aCGH (A) Human duplication of a cluster of genes at Chromosome 5q13.3. is shown by two separate, and sometimes multiple, red BAC probe (CTD-2288G5) signals in interphase cells, with only one green BAC probe signal (RP11-1077O1) for a flanking region. Metaphase FISH shows both probes at band 5q13. The third nucleus in (A) shows four signals of the control probe (green) and eight copies of the BAC probe duplicated in the aCGH assay, consistent with the pattern expected in an S/G 2 nucleus. (B–E) Bonobo (B), chimpanzee (C), gorilla (D), and orangutan (E) interphase FISH studies all show no increased signal for the human duplicated gene cluster, with signals of comparable size for the CTD-2288G5 (red) and the flanking RP11-107701 (green) probes. Metaphase FISH analyses show the gene cluster to be in the p arm of Chromosomes 4 (corresponding to the human Chromosome 5) in both the bonobo and chimpanzee, in the q arm of Chromosome 4 (corresponding to the human Chromosome 5) in the orangutan, and in the p arm of the gorilla Chromosome 19 (syntenic regions to human Chromosomes 5 and 17). Metaphase FISH showed both the test probe and the flanking probe to be located in the human 5q13 band. Both probes were located in the proximal q arm of the orangutan (PPY) Chromosome 4 and in the p arms of the bonobo (PPA) and chimpanzee (PTR) Chromosomes 4. In the gorilla (GGO), both probes were located on the gorilla Chromosome 19. All of these primate locations are consistent with described evolutionary chromosomal rearrangements, with the orangutan Chromosome 4 considered to be the ancestral Chromosome V ( Stanyon et al. 1992 ). These rearrangements include a pericentric inversion of the ancestral Chromosome V (Chromosome 5 in human, Chromosome 4 in the great apes), in the bonobo and chimpanzee, and a translocation between the ancestral chromosome for human Chromosome 5 and the ancestral chromosome for human Chromosome 17 to form the gorilla Chromosomes 4 and 19. It is of interest that, considering the orangutan Chromosome 4 as the ancestral Chromosome V, rearrangements at this site have occurred in all of the other three great ape species (pericentric inversion in bonobo and chimpanzee, translocation in gorilla) and in the human (gene duplication). This region is also involved in spinal muscular atrophy (SMA), which is characterized by deletions of one or more genes in this region ( Lefebvre et al. 1995 ). Taken together these data suggest this region is one of high genomic instability that is relevant to both disease and evolutionary processes. Independent Confirmation of Interspecies cDNA aCGH Data: Literature-Based Validation FGF7 -like genes. Some genes we identified as having LS aCGH signatures have been previously studied by others using different methods, which provides a means of independently checking the accuracy of the cDNA aCGH data presented here. One such gene, the FGF7 gene on Chromosome 15, was studied by Zimonjic et al. (1997) using FISH analysis of the same hominoids used in this study. The FISH analysis showed an interhominoid variation in gene copy number with eight copies in human, five in chimp, four in gorilla, and two in orangutan. Interspecies aCGH data presented here mirrored these results (correlation = 0.97), showing an elevation of the human gene number with respect to the chimp, gorilla, and orangutan, with the most pronounced difference being between human and orangutan ( Figure 4 A). Figure 4 Independent Confirmation of Interspecies cDNA aCGH Data for Three Gene Families with Known Species Differences in Copy Number The chromosomal location, IMAGE clone ID, and GenBank accession are provided for each cDNA. The species average log 2 ratios for each cDNA clone and the previously published estimate of gene copy number are shown for the indicated species. Also shown are TreeView images of interhominoid aCGH results for the indicated cDNAs, and a graphical depiction of the correlation between aCGH signal and published estimate of gene copy number (PECN). (A) FGF7 cDNA clone located on human Chromosome 15 was identified using the UCSC November 2002 human genome assembly and FGF7 -like cDNA clones located on human Chromosome 9 were identified based on UniGene cluster sequence similarity to FGF7 reference sequence NM_002009. The correlation between published and aCGH-based copy number estimates is 0.97. (B) morpheus family cDNA clones were identified based on sequence similarity to one morpheus family member ( Johnson et al. 2001 ). As in (A), except data relate to the morpheus genes and published data are from Johnson et al. (2001) . Correlation = 0.97. (C) As in (A), except data relate to the CXYorf1 genes and published data are from Ciccodicola et al. (2000) . Correlation = 0.99. Morpheus genes Recently the identification of a multimember gene family named morpheus on Chromosome 16 was reported and shown to exhibit gene copy number variation between several hominoid species ( Johnson et al. 2001 ). Using a combination of approaches, the investigators estimated copy numbers for the morpheus genes to be 15, 25–30, 17, and nine for human, chimp, gorilla, and orangutan, respectively. In order to provide an independent test of the accuracy of the interspecies cDNA aCGH data we generated, the aCGH signatures of morpheus -like cDNAs were assembled for the same hominoids ( Figure 4 B). The average test/reference log 2 ratios for these cDNAs indicated that chimpanzee had the most copies, gorilla was slightly higher than human, and orangutan clearly had the fewest, results that are in very good agreement (correlation = 0.96) with the copy number estimates reported independently by Johnson et al. (2001) . CXYorf1 genes Ciccodicola et al. (2000) used cross-species FISH to estimate the hominoid gene copy numbers for the CXYorf1 gene family. They found values of seven, two, three, and one for human, chimpanzee, gorilla, and orangutan, respectively. These values closely mirrored the aCGH values that were obtained ( Figure 4 C) (correlation = 0.99). Based on aCGH data, the FLJ22004 gene shows the greatest gorilla-specific copy number increase (average log 2 ratio = 3.94). This gene resides near the fusion region on Chromosome 2q14.1 (see below) and is contained within BAC RP11-432G15. Consistent with the aCGH data, two independent interhominoid FISH studies, by our lab ( Figure S3 ) and by Fan et al. (2002) , using this BAC showed that the copy number was highly elevated (more than 30 signals) in gorilla relative to all other hominoids tested (fewer than or equal to three signals). Further independent support for the accuracy of the aCGH data comes from a comparison of the HLS gene dataset to the segmental duplication dataset generated by Bailey et al. (2002a) , who used whole genome shotgun data to generate a genome-wide database (the Whole Genome Shotgun Segmental Duplication [WSSD] database) of recent (less than 40 million years ago [MYA]) segmental duplications for the human genome (see Table S2 ). The majority of changes in copy number of the HLS gene set we identified are likely to have occurred since the Homo/Pan split (less than 5–6 MYA) and therefore should represent a subset of the segmental duplications found in the WSSD dataset. Results of this analysis confirmed this expectation ( Table 1 ): 80% of HLS genes gave significant basic local alignment search tool (BLAST) scores with the WSSD dataset (as a control, only 13% of a randomly selected set of cDNAs were positive for the WSSD dataset), and 57% (5414/9461) of the segments in the WSSD were positive with the HLS gene list. Table 1 Comparison of HLS Gene and WSSD Datasets The complete HLS clone-by-clone comparison to the WSSD dataset can be found in Table S1 Non-Random Distribution of LS Genes Genes identified as having a variation in copy number specific for one or more hominoid lineages occurred either as single isolated genes or as clusters of genes. This latter category likely reflects LS copy number changes that involved blocks of contiguous genes. In addition, certain specific regions of the genome, while not necessarily composed of contiguously positioned LS genes, showed a marked enrichment for LS genes. Surveying the genome for regions containing contiguous gene clusters of LS genes or for regions highly enriched in LS genes (greater than or equal to eight contiguous or nearly contiguous LS cDNAs) identified 23 prominent sites ( Figures 5 and 6 ; Table 2 ). Most (18) of these are not randomly distributed in the genome, but instead are found near regions thought to be more genomically and evolutionarily dynamic. Among these are heterochromatic C-band regions, pericentromeric and subtelomeric regions, breakpoints of recent pericentromeric inversions, and sites of recent chromosomal fusions. For example, the two cytogenetic regions with the most LS genes represented were 1p13.2–1q21.2 (66 cDNAs) and 9p13.3–9q21.12 (77 cDNAs) (see insets in Figure 5 , regions C and M). Interestingly, these regions are also known to contain C-band regions of heterochromatin which, along with C-band regions at pericentromeric 16 and at the distal end of Yq, are found at these chromosomal locations only in human and are known to be highly polymorphic. (While C-band chromosomal regions contain the alphoid class of repetitive DNA, there are several reasons that argue that the LS signals in these regions are not due to human-specific repetitive DNA. First, several HLS cDNAs were checked and found to contain no repetitive sequences in them. Second, Cot-1 analyses, described earlier, indicated that HLS signals did not correspond to repetitive DNA regions. Third, the genes in these regions showed LS signals for other hominoid lineages in addition to human.). The regions near the C-band regions on 16 (15 cDNAs) and Y (14 cDNAs) also showed an enrichment of LS genes, although to a lesser extent. These regions, as well as the pericentromeric regions of the acrocentric chromosomes, which showed enrichment for LS genes, are known to contain highly repetitive DNA, which may make them especially prone to recombination and duplication. Figure 5 Whole Genome TreeView Representation of Interhominoid cDNA aCGH Data for Five Hominoid Species for Human Chromosomes 1–9 Hominoid species are identified by color bar (see key). Genes along each chromosome are ordered by map position. cDNAs mapping to multiple genome locations (more than 1 Mb apart) are shown at each of the multiple genomic locations. Fluorescence ratios are depicted using a pseudocolor scale (indicated). Megabase positions, cytobands, centromeres (black vertical triangles), and selected genes are indicated. Boxed and lettered regions (A–M) identify clusters of LS genes (greater than or equal to eight per cluster); insets show detailed views of clusters C, F, I, and M. The complete annotated interhomioid aCGH dataset depicted here is available in Table S1 and can be viewed either as a TreeView image (see Protocol S1) or as a tab-delimited text file that can be opened in Excel. Figure 6 Whole Genome TreeView Representation of Interhominoid cDNA aCGH Data for Five Hominoid Species for Human Chromosomes 10–22, X, and Y Data are as described for Figure 5 , except boxed and lettered regions denoting clusters of LS genes are N–W. The complete annotated interhomioid aCGH dataset depicted here is available in Table S1 and can be viewed either as a TreeView image (see Protocol S1) or as a tab-delimited text file that can be opened in Excel. Table 2 Genome Distribution and Repeat Content of Clusters of LS Genes Inspection of the whole genome aCGH dataset identified clusters of genes that showed LS signatures. While a number of smaller (e.g., at Chromosome 13p11.1) or more diffuse (e.g., at 16p13.12–16p11.2) clusters were also present, 23 of the most prominent clusters (A–W) were selected by visual inspection. In general, selection required that at least half of the cDNAs in the cluster be lineage-specific (i.e., changed in one or more hominoid lineage) and that at least eight LS cDNAs be present. Cytogenetic and nucleotide positions were obtained from the UCSC Golden Path genome assembly November 2002 sequence freeze. cDNA totals reflect estimated numbers of LS cDNAs within the indicated interval. Repeat content associated with LS gene clusters and HLS genes was assessed and compared to average repeat content of the genome Previous reports have shown that recent (less than 40 MYA) segmental duplications in the human genome are positionally biased and found more frequently in pericentromeric and subtelomeric regions ( Bailey et al. 2001 ; Mefford and Trask 2002 ; Samonte and Eichler 2002 ). Consistent with this, most of the LS clusters we identified mapped to either pericentromeric (10/23) or subtelomeric (4/23) regions ( Table 2 ). Also, a recent report by Bailey et al. (2002b) showed that a 400 kb HLS duplication transposed from Chromosome 14 to the most proximal pericentromeric region of Chromosome 22 (at approximately 13–14 Mb) and suggested that a pericentromeric gradient of duplications exists in which the most recent duplications transpose nearest to the centromere. Data presented here, showing a cluster of LS genes in this same region with HLS changes occurring nearer to the centromere, are consistent with this view. Additional clusters were also identified at other sites known to be particularly unstable and prone to rearrangement and duplication. For example, the 5q13 region (see inset to Figure 5 , region I) is known to be involved in SMA, and deletions in the BIRC1 gene, which we show is amplified uniquely in humans, are sometimes found in SMA patients. This region and another at 5p14.3–5p13.3 that also contains a cluster of LS genes are near the breakpoint sites of a pericentric inversion that occurred during hominoid speciation ( Yunis and Prakash 1982 ). Another unstable region, the 2q14.1 region (see inset to Figure 5 , region F), is known to be the site at which two ancestral ape chromosomes fused telomere-to-telomere to form human Chromosome 2 ( IJdo et al. 1991 ; Fan et al. 2002 ). This region shows a complex pattern of LS genes, with aCGH gene signatures specific for at least four different hominoid lineage combinations represented within a genomic region of only 400 kb. Enrichment of LS genes was also found in regions associated with other genetic disorders, including Di George syndrome, Williams–Beuren syndrome, and Angelman and Prader–Willi syndromes. Taken together, these data support the view that regions of the genome that are particularly unstable are enriched for LS gene copy number changes and are often disease-associated hotspots of evolutionary change. To assess the frequency and type of repeated sequences associated with the HLS gene and LS gene cluster datasets, the repeat content near these genes was determined. Of known repeat classes surveyed, only the Satellite class showed a major deviation from the overall genome frequency ( Table 2 ). Satellite repeats associated with LS gene clusters and HLS genes were 10-fold and 4-fold enriched, respectively, over the genome average frequency. This may not be unexpected given the known pericentromeric and subtelomeric positional bias of Satellite sequences and their known involvement in interchromosomal duplication processes ( Horvath et al. 2000 ). Relative frequencies of the subclasses of Satellite sequences associated with each cluster can be found in Table S3 . Genes Showing HLS Variation in Copy Number Of the 140 genes showing HLS variation in copy number, 134 represented human gene increases and six represented decreases ( Figure 7 ; Table S4 ). While roughly half of these genes were represented as expressed sequence tags (ESTs) or uncharacterized genes with little or no information as to possible biological function, the remaining cDNAs corresponded to known genes. Among this latter category were a number with interesting predicted functional characteristics. For example, the gene encoding the neuronal apoptosis inhibitory protein (NAIP or BIRC1 ) maps to Chromosome 5q13 and was elevated specifically in the human lineage. NAIP has been implicated in delaying neuronal programmed cell death ( Liston et al. 1996 ) and is known to have at least one duplicated copy in the genome that appears to be functional ( Xu et al. 2002 ). If an increase in gene dosage results in an elevated functional effect, the possibility exists that such an LS increase in NAIP gene copy number may contribute to an increase in neuronal proliferation and/or brain size (either globally or regionally) in humans. Figure 7 TreeView Images of LS Genes for Different Hominoid Lineages and Lineage Combinations Ranked as a Function of aCGH Ratio TreeView representation of cDNAs that exhibit great ape or human LS aCGH signatures are presented. Order of genes within each lineage is based on the average log 2 fluorescence ratios (ordered highest to lowest) of the respective species. The dataset used for this figure was not collapsed by UniGene cluster to minimize the chance that significant LS cDNAs would be missed. Fluorescence ratios are depicted using a pseudocolor scale (indicated). The complete annotated LS dataset depicted here is available as Table S4 and can be viewed either as a TreeView image (see Protocol S1) or as a tab-delimited text file that can be opened in Microsoft Excel. Several other genes implicated in neuronal function showed HLS changes in copy number: a neurotransmitter transporter for γ-aminobutyric acid (GABA) ( SLC6A13 ), a leucine zipper-containing gene highly expressed in brain ( KIAAA0738 ), α7 cholinergic receptor/ Fam7 fusion gene ( CHRFAM7A ), a p21-activated kinase ( PAK2 ), a Rho GTPase-activating protein ( SRGAP2 ), a Rho guanine nucleotide exchange factor ( ARHGEF5 ) that is a member of the rhodopsin-like G protein-coupled receptor family, and Rho-dependent protein kinase ( ROCK1 ). Inhibition of ROCK1 has been shown to prevent long-term memory, and ROCK1 , together with a RhoGEF and RhoGAP, have been recently implicated in a model of long-term memory based on fear conditioning ( Lamprecht et al. 2002 ). Also, members of the ARHGEF, PAK, and RhoGAP gene families comprise a disproportionately high fraction of the genes known to produce syndromic or nonsyndromic forms of mental retardation ( Ramakers 2000 ). Another gene showing an HLS copy number increase, USP10 , encodes a ubiquitin-specific protease, an enzymatic class implicated in learning and memory and in synaptic growth ( DiAntonio et al. 2001 ). Overexpression of the USP10 homologue in Drosophila leads to uncontrolled synaptic overgrowth and elaboration of the synaptic branching pattern ( DiAntonio et al. 2001 ), raising the possibility that the human-specific copy number increase for USP10 could be relevant to expanded synaptic growth in humans. Interestingly, the USP10 gene at Chromosome 16q24 and an unknown gene (integrated molecular analysis of genomes and their expression [IMAGE] 854706) at Chromosome 19q13 that is significantly elevated in human relative to most hominoids map to the two chromosomal regions giving the highest LOD scores in a recent genome-wide scan related to specific language impairment ( SLI Consortium 2002 ). The aquaporin 7 gene ( AQP7 ), which is thought to be involved in water transport across membranes, shows an HLS increase in copy number, while the genes immediately flanking it ( NFX1 and AQP3 ) do not show HLS aCGH signals. Similarly, Bailey et al. (2002a) predict that a 22 kb region containing the AQP7 gene has been recently (less than 40 MYA) duplicated several times while flanking regions show no recent duplication. These data suggest that a series of HLS segmental duplications occurred that focused primarily on the AQP7 gene, which spans 17 kb of the 22 kb duplication. This observation, together with the fact that several of the additional AQP7 copies appear to be potentially functional (see below), raises the possibility that significant selection pressure may have been exerted on AQP7 -like genes specifically in the human lineage. Genes Showing Copy Number Variation Specific to One or More Great Ape Lineages In addition to identifying HLS gene changes, interhominoid cDNA aCGH allows genes to be identified that have changed during other branch points within the past 15 MY of hominoid evolutionary history. In the present study, 865 great ape LS genes were identified ( Figure 7 ; Table S4 ), several of which are mentioned below. Chimpanzees are known to be the original reservoir for HIV and show genetic resistance to progression to AIDS ( Novembre et al. 1997 ; Gao et al. 1999 ), a process likely to be immunologically mediated. Among genes elevated in copy number in chimpanzees are several with possible relevance to immune function, including the BMI1 gene (B-cell lymphoma Mo-MLV insertion region) and, in bonobos and chimps, the FCER2 gene, encoding a lymphocyte IgE receptor, and the IL1RL1 gene encoding an interleukin receptor 1-like protein. Also, it has been shown that chimpanzees can synthesize a form of sialic acid while humans cannot, owing to the loss of function in humans of a specific sialic acid hydroxylase ( Muchmore et al. 1998 ). Interestingly, one of the genes elevated in chimpanzees and bonobos encodes a CMP-sialic acid transporter (SLC35A1). As mentioned previously, of genes specifically amplified in the gorilla lineage, the FLJ22004 gene showed the largest gorilla-specific aCGH signal increase. While the function of this gene is unknown, the encoded protein contains a DUF6 domain, which is found in the Erwinia PecM protein involved in cellulase and pectinase regulation ( Rieder et al. 1998 ). Interestingly, gorillas more than any other hominoid are folivorous. They eat leaves primarily, but also (like other hominoids) fruit, foods that contain energy-rich cellulose and pectin. This fact, together with the observation that FLJ22004 is highly amplified only in the gorilla lineage, raises the possibility that amplification of this gene provides enhanced cellulase and pectinase capabilities, which in turn would facilitate utilization of the two key dietary staples of this species. Another gene specifically increased in gorilla (average log 2 ratio = 2.02) encodes the fibroblast growth factor receptor 3 (FGFR3), which when disrupted in humans causes achondroplasia, the most frequent form of short-limb dwarfism. The SET8 gene is also significantly elevated in copy number only in gorilla (average log 2 ratio = 2.65) and also related to development. The gene encodes a transcription factor and appears to be homologous (protein similarity of 43% over 110 amino acids) to the Drosophila trithorax gene, which functions in segmentation determination through interaction with bithorax and antennapedia complex genes, suggesting that it may serve a role in gorilla-specific development. There were a significant number of genes (28) showing increased copy numbers specifically in the African great apes (bonobo, chimpanzee, and gorilla). Among these were the MSTP028 gene, encoding a voltage gated potassium channel; the PLA2G4B gene, encoding phospholipase A2β, which shows high brain and (in particular) cerebellar expression; and the SPTBN5 gene, which encodes a nonerythroid spectrin. SPTBN5 is immediately adjacent to PLA2G4B at Chromosome 15q15.1 in the genome and, like PLA2G4B , shows high cerebellar expression, raising the possibility that their function(s) in the African great apes may be linked. Finally, while the HLS and LS genes mentioned above have interesting biological implications related to human and great ape differences, each should be viewed as tentatively HLS or LS until the interhominoid copy number differences for these genes are confirmed by independent methods. Functional Classification of HLS and LS Genes Classification of HLS and LS genes according to predicted molecular function was carried out by Gene Ontology (GO) analysis. For the great majority of functional categories, both HLS and LS gene groups gave GO distributions similar to that found with all known genes (UniGene collapsed set), with ligand binding, catalytic activity, signal transducer activity, and transporter activity being the four most highly represented functional categories ( Figure S4 ; Table S5 ). This analysis should be tempered somewhat by the fact that almost half of all HLS and LS genes are unclassified or lack functional information and that some human genes are not present on the microarrays used (e.g., only 20–30 olfactory receptor-related cDNAs were on the microarrays while, in hominoids, this family is thought to be comprised of several hundred functional members [ Gilad et al. 2003 ]). It can be expected that copies arising from gene duplications will be a mix of functional genes and pseudogenes, the exact ratio of which will vary depending on the gene involved. Although definitive assessment of the functional status of the copies of HLS genes identified here requires additional study, a preliminary analysis of several HLS genes, including those mentioned above, found this general trend to be evident ( Table S6 ). For example, analysis of BLAST-like alignment tool (BLAT) hits for the AQP7 gene predicts that of seven closely related (greater than 90%) copies in the genome, at least four appear to be potentially functional. In contrast, the FLJ13263 gene had four closely related sequences, and these all appear to be pseudogene-like. Finally, the fact that it has been shown that pseudogenes can play important functional roles ( Hirotsune et al. 2003 ) implies that one cannot assume that even bonafide pseudogene copies will necessarily be functionally silent or unimportant to evolutionary differences between species. Human and Chimpanzee Genome Sequences A human versus chimpanzee genome comparison is now publicly available, through the University of California, Santa Cruz (UCSC) database's best reciprocal alignment of the July 2003 human genome and the November 2003 Arachne 4X chimpanzee draft genome ( http://genome.ucsc.edu/goldenPath/hg16/versusPt0/ ). Using this comparison, we have determined that genes that gave aCGH signatures indicative of copy number increase specifically in the human lineage, showed a 7-fold increase in the frequency of gaps and absent sequence homology in the chimpanzee draft compared to a randomly selected gene (EST) set ( Table S7 ). Such a pronounced bias would be expected for genes with significant copy number increases in human relative to chimpanzee, independently supporting the accuracy of the HLS gene dataset we have defined. However, a limitation of only comparing the human and chimpanzee genomes is that no out-group analysis is provided, preventing discrimination of ancestral and derived forms and limiting the ability to identify gene copy number changes unique to a specific hominoid lineage. In contrast, the interhominoid aCGH studies described here provide reliable genome-wide data for out-group analysis across five primate species, allowing easy identification of LS copy number differences. In order to provide some perspective on the importance of out-group data when trying to identify LS gene changes, a comparison was carried out between two aCGH clone sets. One set contained 153 genes we identified by cDNA aCGH that were specifically increased in copy number in the human lineage when compared to each of the four great ape lineages (i.e., HLS). The other clone set, while derived from the same aCGH experiments using the same cutoff values, contained 353 genes that showed aCGH signals in which the human copy number was greater than the chimpanzee (i.e., “human > chimp”). Comparison of these two datasets allows one to determine how frequently a “human > chimp” gene is also HLS (i.e., human copy number is greater than each of the four great apes studied). Of the 353 genes that were “human > chimp,” 200 were not found in the HLS set, indicating that over half (57%) of the “human > chimp” genes were not HLS. It has been pointed out that the human genome is a mosaic composed of some regions more closely related to chimpanzee and, less frequently, others more closely related to gorilla ( Pääbo 2003 ). Data presented here contain a number of examples of genes showing such evolutionary histories, but also contains examples of other more complex phylogenetic patterns ( Figure 7 ; see Table S4 ). For example, the significant number of genes showing copy number increases or decreases specifically in the African great apes, in which human and orangutan copy numbers were equivalent to one another, suggests that either more than one event occurred to produce this distribution or the genomic mosaicism found in the human genome extends back to include sequences present at the time the orangutan lineage split. Because of this unusual phylogenetic profile, we tested several such cDNAs by interhominoid real-time PCR (RT-PCR) and FISH as an independent verification of our aCGH results. In all cases, copy number estimates based on RT-PCR analysis showed high correlation (0.94–0.97) to estimates based on our aCGH data ( Figure S5 ). Interestingly, FISH analysis using a BAC probe containing two genes ( PLA2G4B and SPTBN5 ) specifically elevated in the African great apes, showed that, in chimpanzee, signals were widely distributed among many chromosomes, while in gorilla the signals were restricted to two sites, one single copy and the other multicopy ( Figure S6 ). These results indicate that the increase in gene copy number in gorilla and chimp occurred independently of each other and therefore support the view that multiple separate events are likely responsible for the African great ape-specific aCGH signals we obtained. In summary, the dataset presented here, containing over 714,000 aCGH datapoints, represents to our knowledge the first genome-wide survey of gene duplication and loss across five hominoid species. The changes identified likely represent most of the major LS gene-associated copy number changes that have occurred over the past 15 MY of human and great ape evolution. Further analyses of this dataset, of which only a fraction has been highlighted here, should provide additional insights into gene duplication and genome evolution, the relationship of genome instability, evolutionary adaptation, and disease, and the genes that underlie the phenotypic differences among human and great ape species. Materials and Methods Copy Number Variation, Sequence Divergence, and Repetitive Sequences Though discussed above as copy number alterations, changes in cross-species cDNA aCGH signals could be due to changes in gene copy number between species, to pronounced exonic sequence divergence of the gene between species, or to a combination of both. To attempt to distinguish among these possibilities, we took advantage of the fact that, while cDNAs are randomly positioned on the microarrays, for analysis purposes they had previously been computationally grouped into two categories: cDNAs with single known genome locations (i.e., unique location) and cDNAs that mapped to multiple genomic locations (multiple locations). In this latter category, we also included a minority of cDNAs that had no assignable location in the genome assembly. We identified HLS cDNAs that showed stronger hybridization with human DNA (green signals in all great ape/human comparisons) and determined how many of these occurred in each of the two mapping categories. HLS signatures were found for 0.185% of unique location cDNAs (66/35,680) and 2.88% of multiple location cDNAs (116/4,031), a frequency difference of more than an order of magnitude (approximately 1:16). Such a strong enrichment, in the multiple location category, of genes showing increased human aCGH signals specific to the human lineage would be expected if such genes were present as multiple closely related copies with distinct genome locations and, as a result, were placed in the multiple location group. No such gene distribution bias would be expected if the LS signatures were mainly due to sequence divergence. Additionally, we estimated what fraction of LS cDNAs in each species were cDNAs with multiple human map positions. Values of 59%, 10%, 13%, 14%, 10%, and 20% were obtained for human, bonobo, chimp, bonobo/chimp total, gorilla, and orangutan, respectively, providing further support that the increased (i.e., green in all great ape:human comparisons) HLS aCGH signatures that were obtained are likely due to gene copy number increases specific to the human lineage. We also carried out interhominoid FISH using a BAC probe (RP11-93K3) containing a gene (IMAGE 1882505) that gave a reduced signal specifically in the orangutan lineage, which is the lineage where sequence divergence might have its greatest artifactual contribution. Resulting FISH data (see Figure S1 ) showed 10–15 signals in human, bonobo, chimpanzee, and gorilla, while for orangutan only two signals were evident. Finally, further evidence of aCGH data reflecting copy number change comes from the three examples of literature-based validation of aCGH-predicted copy number changes (see Figure 4 ). In all three cases, the orangutan signals were reduced relative to the human signals, and each of these genes were shown in published reports to have fewer copies in orangutan relative to human. Lastly, to address the possibility that such signals might be due to highly repetitive sequences associated with LS genes that were not effectively blocked during hybridization, we examined the cDNA sequences of five cDNAs that showed stronger hybridization with human DNA. In all cases no repeats were found that would account for the HLS aCGH data. In addition, hybridization using labeled Cot-1 DNA (human Cot-1 versus total human DNA) indicated that there was no correspondence between genes hybridizing more strongly to Cot-1 and genes that are LS. DNAs DNAs that were used for this study were derived from human (two females, two males), bonobo (three males), chimpanzee (one male, three females), gorilla (one male, two females), and orangutan (three females). Human and chimpanzee genomic DNA samples were isolated from blood cells using Super Quick-Gene kits from the Analytical Genetic Testing Center (Denver, Colorado, United States). One gorilla and two bonobo samples were isolated from cell lines using DNeasy Tissue kits from Qiagen (Valencia, California, United States). An orangutan sample and a gorilla sample were isolated from blood by other laboratories. Remaining DNAs (one bonobo, one gorilla, and two orangutan) were obtained from the Coriell Institute (Camden, New Jersey, United States) and originally derived from primary fibroblast cell lines. aCGH DNA microarrays used in this study were fabricated by PCR-amplifying IMAGE clones ( http://image.llnl.gov ) and spotting them onto Corning GAPSII aminosilane slides using a custom-built robotic arrayer ( http://cmgm.stanford.edu/pbrown/mguide/index.html ). The labeling of genomic DNA and hybridization to cDNA microarrays were performed as previously described ( Pollack et al. 1999 ). In brief, 4 μg of genomic DNA from test (hominoid DNA) and sex-matched reference (normal human DNA) were DpnII-digested (New England Biolabs, Beverly, Massachusetts, United States) and subsequently purified using Qiaquick PCR purification kit (Qiagen). Purified samples were random-primer labeled according to manufacturer's directions in a 50 μl reaction volume using BioPrime Labeling Kit (Invitrogen, Carlsbad, California, United States), with the exception of substituting the provided dNTP mix with dATP, dGTP, dTTP (120 μM), dCTP (60 μM), and Cy3-dCTP (reference) or Cy5-dCTP (test) at 60 μM. Labeled Cy3-dCTP and Cy5-dCTP products were copurified and concentrated using Microcon YM-30 filters (Millipore, Billerica, Massachusetts, United States) along with 50 μg of human Cot-1 DNA (Invitrogen), 100 μg of yeast tRNA (Invitrogen), and 20 μg of poly(dA-dT) (Sigma, St. Louis, Missouri, United States) to block hybridization to nonspecific and repetitive elements in genomic DNA. We adjusted the final hybridization volume (40 μl) to contain 3.5× SSC and 0.3% SDS. Following sample denaturation (2 min at 100 °C) and a Cot-1 preannealing step (20 min at 37 °C), we cohybridized test and reference samples to a cDNA microarray containing 39,711 nonredundant cDNA clones, representing 29,619 different human genes. Samples were hybridized at 65 °C for 16 h. Following hybridization, arrays were washed in 2× SSC, 0.03% SDS for 5 min at 65 °C, followed by successive washes in 1× and 0.2× SSC for 5 min each at room temperature. aCGH Data Analysis Individual microarrays were imaged with a GenePix 4000B scanner (Axon Instruments, Union City, California, United States) and fluorescence intensities were extracted using GenePix Pro 3.0 software and uploaded into the Stanford Microarray Database (SMD) ( http://genome-www5.stanford.edu ) for analysis. For each experiment, fluorescence ratios were normalized by setting the average log 2 fluorescence ratio for all array elements equal to 0. We included for analysis only those genes that were reliably measured (i.e., fluorescence intensity/background of greater than 1.4 in the reference channel) in greater than or equal to 50% of samples. Genes not meeting these criteria were viewed as absent. Map positions for cDNA clones on the array were assigned using the UCSC GoldenPath assembly ( http://genome.ucsc.edu/ ), November 2002 freeze. Gene copy number ratios were visualized in log 2 colorimetric scale with the genes ordered by chromosomal position using TreeView version 1.6 ( http://rana.lbl.gov/EisenSoftware.htm ). To provide the most accurate depiction of chromosomal gene distribution, cDNAs with multiple genome map positions (more than 1 Mb apart) were represented in TreeView at each assigned map location. Selection Criteria Applied to cDNA aCGH Data Genes showing copy number variation specific to a single hominoid lineage For selection of LS cDNAs, the values considered were the log 2 of the aCGH fluorescence ratio of the test and reference genomic DNAs. Selection of LS cDNAs was based on the following criteria: First, for a given cDNA and a given species, no more than one value out of the species versus human comparisons for that species could be absent (see aCGH methods regarding absent signals). Second, for a gene copy number change to be considered unique to a particular species, at least half of the absolute values of comparisons within that species had to meet or exceed a threshold of 0.5 with all such values in the same direction, i.e., either all positive or all negative, and at least half of the absolute values of comparisons within each of the remaining species had to be below a threshold of 0.5. For example, for a gorilla LS gene, at least half of the gorilla comparisons had to meet or exceed the 0.5 threshold, while at least half of the comparisons within each of the remaining species had to be below the threshold. Third, in order to compensate for missing (i.e., “absent”) values for a given cDNA of all “present” values within each species, no more than one could fall below the threshold (0.5) for each species. Fourth, to ensure sufficiently high signal-to-noise in the identification of altered ratios, for a given cDNA and given great ape species, each absolute value of the average of the species versus human comparison for that species had to be at least 2.5-fold greater than the absolute value of each remaining species average, including human versus human comparisons. For HLS genes, the absolute value of each species average of the great ape versus human comparisons had to be at least 2.5-fold greater than the average of the absolute value of the human versus human comparisons. Genes showing copy number variation unique to more than one hominoid lineage For cDNAs in which the copy number was either increased or decreased in two or more hominoids relative to all the other hominoids, the same criteria were used as before, except the cDNA would have to meet or exceed the 0.5 threshold selection criteria for more than one species. Relationship of aCGH signal to gene copy number It is difficult to establish a precise relationship between gene copy number and interhominoid aCGH ratio because sequence divergence can influence hybridization signal strength and the sequences of additional gene copies are, in almost all cases, not known. However, prior studies by Pollack et al. (1999) showed that, using cell lines containing increasing numbers of X chromosomes, copy number, and aCGH signal exhibited a linear relationship over the copy number range tested, with an increase of a single gene copy corresponding to a ratio of 1.31 (log 2 value = 0.39). In a similar manner, we took advantage of the fact the one of the human-to-human comparisons used in our experiments was between a male and female. In this context, X chromosome genes in the female should be present as two copies while in the male will exist as one copy. Calculation of the average aCGH ratios of 957 such genes in the male/female comparison yielded a log 2 value of 0.21. The different values obtained in these two tests may reflect the fact that in the male/female comparison a Y chromosome was present, while this was not true in the other study, which used XO cell lines. The presence of sequences on the Y that are shared with the X could have produced a compression of aCGH fluorescence ratio values, accounting for the difference in X chromosome-related log 2 ratios described above. Similar compression effects on X chromosome ratios have recently been reported ( Snijders et al. 2001 ). While both the 0.39 and 0.21 values fall below the 0.5 threshold we employed for the selection of LS genes, 0.5 was used to insure that selection of false positives was minimized. In an interhominoid aCGH study, Locke et al. (2003) also determined a threshold of 0.5 to be most appropriate. Finally, the use of this relatively conservative threshold implies that the numbers presented here are likely to be underestimates of the actual number of genes that exhibit LS copy number differences between these hominoids. FISH Analysis Using standard procedures, metaphase spreads and interphase nuclei were prepared from human lymphocytes ( Homo sapiens [HSA]) and from great ape fibroblast cell lines, obtained from Coriell. The four great ape species studied were bonobo ( Pan paniscus [PPA], Coriell #AG05253A), chimpanzee ( Pan troglodytes [PTR], Coriell #AG06939A), lowland gorilla ( Gorilla gorilla [GGO], Coriell #AG05251B), and Sumatran orangutan ( Pongo pygmaeus [PPY], Coriell #AG12256). One BAC clone (CTD-2288G6) containing all or portions of the coding regions for OCLN , GTF2H2 , and BIRC1 was selected as a probe for the region with increased copy number in human. A second BAC clone (RP11-1077O1) flanking the region amplified in human and containing portions of the RAD17 gene was selected as a control probe. BAC clones were obtained from BACPAC Resources at the Children's Hospital Oakland Research Institute and from Research Genetics. Whole-cell PCR was done to verify that the OCLN , GTF2H2 , and BIRC1 genes were on BAC CTD-2288G5 and that the RAD17 gene was on BAC RP11-1077O1. BAC DNAs were prepared using Large Construct Kits (Qiagen). BAC probes were directly labeled with Spectrum Green (Vysis, Downers Grove, Illinois, United States) and Spectrum Orange (Vysis) using the Vysis Nick Translation Kit and protocol. FISH analyses with the BAC probes were performed using standard techniques. Cot-1 DNA was used to block cross-hybridization of high-copy repeat sequences. In each experiment, dual-color hybridization was performed using a probe carrying genes with a predicted increase in copy number specifically in the human lineage (CTD-2288G6 or CTC-790E5) and a flanking probe (RP11-1077O1 or RP11-1113N2) containing a gene not predicted to show an HLS increase in copy number. For each species, two separate hybridizations were performed: one with the probe containing the genes showing increased human copy number labeled with Spectrum Green and the flanking probe with Spectrum Orange, and the other in which the dyes were reversed. For each probe combination for each species, a minimum of 200 interphase nuclei and ten metaphase spreads were examined. A whole chromosome painting probe for human Chromosome 5 (wcp5; Vysis) was used to confirm the gorilla Chromosome 19 to be syntenic with the human Chromosome 5 for the region of interest. The hominoid cell lines used for FISH analysis were grown asynchronously in monolayer culture. Metaphase spreads and nuclei were obtained from a shake-off preparation and thus were somewhat selected for proliferative activity. Similarly, human lymphocyte cultures stimulated with the mitogen phytohemagglutinin contain cells in various stages of the cell cycle. In order to judge the replication state of the nuclei scored, dual-color FISH assays included probes both for DNA sequences that by aCGH showed copy number difference between test and reference DNA and for sequences on the same human chromosome that had the same (diploid) number of copies. Nuclei that showed diploid copy number of this control probe were assessed to be in G 0 . Nuclei that were in S/G 2 demonstrated four copies of the control probe and the test probes were proportionately in multiple copies of the number established in the nonproliferating cells. Similar experimental conditions were used for the additional BAC FISH analyses described. Comparison of HLS Gene and WSSD Datasets Sequences of IMAGE clones for each HLS gene were obtained using NCBI's Entrez ( http://www.ncbi.nlm.nih.gov/Entrez ) sequence retrieval tool and saved locally in FASTA format. Likewise, the random IMAGE clone sequences were obtained by first downloading GI numbers for all human IMAGE clones and then using a random number generator to pick approximately 200 random IMAGE clones from the list of GI numbers. These random IMAGE clone sequences were then downloaded from Entrez in a similar fashion. The April 2002 WSSD dataset was downloaded from the Segmental Duplication Database website ( http://humanparalogy.gene.cwru.edu/SDD/ ). The two IMAGE clone sequence datasets were formatted and “BLASTed” against the WSSD sequences locally using NCBI's stand-alone BLAST executables for Windows. BLASTs were limited to an expect value of e −20 and then the best match was reported by a Perl ( http://activestate.com/ ) script for each query. No restrictions on percent identity of the match or match length were imposed. HLS Gene Repeat Analysis The HLS gene IMAGE clone sequences (see Table S4 ) were compared to the November 2002 build at UCSC using Dr. Jim Kent's BLAT program via the Human Genome Browser Gateway website ( http://genome.ucsc.edu/cgi-bin/hgGateway ). The BLAT hits were parsed such that only hits with a percent identity greater than or equal to 90% were reported. Furthermore, only hits with a match coverage (match length/query length) greater than or equal to 50% were reported. Repeat annotation was downloaded from UCSC ( http://genome.ucsc.edu/goldenPath/14nov2002/database/ ). Using the position data obtained from the BLAT alignments along with a 50 kb buffer on both sides of the alignments, the relative repeat content was determined for each HLS gene region using a Perl script. As a comparison, the relative repeat content was determined for the entire genome. Annotated gaps within the regions and the human genome were subtracted from the percent content calculation so that these content values were not skewed by gaps. Only long interspersed nuclear element (LINE), long terminal repeat (LTR), short interspersed nuclear element (SINE), Simple, and Satellite classes of repeats were included in the analysis. LS Gene Cluster Repeat Analysis The 23 clusters of LS genes were compared to the human repeat database downloaded from UCSC (see HLS gene repeat analysis). Likewise, the Satellite repeat content for the LS genes within the 23 clusters was also determined in a similar fashion. GO Analysis of HLS and LS Genes Primary GenBank accession numbers associated with both the HLS and LS gene lists were parsed into separate lists and stored as tab delimited text files. GenBank accession numbers were used as unique identifiers, and gene lists were annotated and functionally characterized using DAVID (Database for Annotation Visualization and Integrated Discovery) ( http://apps1.niaid.nih.gov/david/upload.asp ) ( Dennis et al. 2003 ). Analyses were performed at level one for DAVID and at a threshold cutoff of 1, which provides high coverage but relatively low specificity and considers all classifications. Analysis was carried out on both lists, first using those genes with GenBank accession numbers, and then only those genes with known gene symbols. The analysis based on gene symbols recapitulates the analysis based on GenBank accessions, but contains correspondingly fewer classified genes. In order to make meaningful comparisons between the LS genes, we identified and the entire genome, a nonredundant list of genome-wide UniGene numbers was adapted from EASE2.0 (Expression Analysis Systematic Explorer, http://apps1.niaid.nih.gov/david/ ) ( Hosack et al. 2003 ), a program that facilitates the biological interpretation of gene lists. This tab-delimited text file, containing 33,655 unique UniGene numbers (updated 2 February 2004), was then uploaded to DAVID for GO analysis. The results for the molecular function analysis are graphically represented in Figure S4 and summarized in Table S5 . GenBank accession numbers were used for the HLS and LS analysis due to nearly half of the genes lacking UniGene numbers, thus making GenBank accession numbers more inclusive of the entire HLS and LS dataset analysis. Alternatively, UniGene numbers were used for the the genome-wide analysis because they provide a nonredundant dataset which is a much closer estimate to the number of genes (33,655) in the human genome versus the human RefSeq accession numbers. When subtracting all computer-based models from human RefSeq, only 20,850 RefSeq accession numbers were available for analysis. Human versus Chimpanzee Comparison The HLS dataset is identical to that previously described. The random dataset chosen for this analysis was determined from UCSC's all_est annotation ( http://genome.ucsc.edu/goldenPath/gbdDescriptions.html ). From the all_est file, 200 random IMAGE clones were picked to ensure that at least one EST per IMAGE clone would map to the human genome. The EST sequences for both the HLS and random datasets were downloaded from GenBank and compared to the July 2003 human genome via a locally installed version of BLAT. BLAT output was parsed so that hits with a score greater than 200 and percent identity greater than 90% were examined for chimpanzee homology. The score and percent identity calculations mimic the calculations performed with the Web-based version of BLAT ( http://genome.ucsc.edu/cgi-bin/hgBlat ); the formula for these calculations was provided by Donna Karolchik. The BLAT hits, as defined as one or more blocks of alignment within score and percent identity cutoffs, were compared to the chimpanzee versus human reciprocal best chain alignment annotation ( http://genome.ucsc.edu/goldenPath/hg16/versusPt0/ ). For each BLAT hit, each block of alignment was compared to the chimpanzee versus human best chain annotation and was scored as follows: “chimp positive” indicates the block is entirely homologous to chimp; “chimp partial” indicates the block is partially homologous to chimp but there are gaps in the homology; “chimp gap” indicates the block is within a gap of the chimp homology; “chimp negative” indicates the block has no homology to chimpanzee. The summary numbers are based on all of the blocks of alignments and how they are scored in reference to chimpanzee homology. The HLS dataset was compared to the “human > chimp” dataset by IMAGE clone identifiers. The “human > chimp” dataset is a redundant set that was not UniGene collapsed; thus, a redundant, non-UniGene collapsed HLS dataset was used for the comparison. RT-PCR Analysis RT-PCR analysis of interhominoid DNA copy number variation was carried out using an ABI Prism 7700 sequence detector (Perkin Elmer Corporation/Applied Biosystems [PE/ABI], Torrance, California, United States) ( Livak et al. 1995 ; Heid et al. 1996 ). Exon-specific primers and probe for PLA2G4B , FLJ31659 , BC040199 , and CFTR genes/cDNAs were designed with the assistance of the Prism 7700 sequence detection software (Primer Express, PE/ABI). The following primer/probe sequences were used: PLA2G4B F 5′-GCAGGTCTGGGTGAGGGTT-3′, PLA2G4B R 5′-GCTGCACCTGATCCCCACT-3′, and the probe 5′-VIC-CAGGAAGTTGCCACACAGGTGAGCA-TAMRA-3′; FLJ31659 F 5′-GCTCAGACATCCAGGGACGA-3′, FLJ31659 R 5′-CGCTTCTCCCAGGATTGGT-3′, and the probe 5′-VIC-CACATTCGTCCAACAGCGGTCGC-TAMRA-3′; BC040199 F 5′-GAGGAAGGTTGGGTGTGGAG-3′, BC040199 R 5′-ACTGGGTGTCCTGCTGGCT-3′, and the probe 5′-VIC-TTGCTTGCTGTGGCCCCAAGCT-TAMRA-3′; CFTR F 5′-CGCGATTTATCTAGGCATAGGC-3′, CFTR R 5′-TGTGATGAAGGCCAAAAATGG-3′, and the probe 5′-6FAM-TGCCTTCTCTTTATTGTGAGGACACTGCTCC-TAMRA-3′. Amplification reactions were performed in MicroAmp optical tubes (PE/ABI) in a 50 μl mix containing 8% glycerol, 1× TaqMan buffer A (500 mM KCl, 100 mM Tris-HCl, 0.1 M EDTA, 600 nM passive reference dye ROX [pH 8.3 at room temperature]), 300 μM each of dATP, dGTP, and dCTP and 600 μM dUTP, 5.5 mM MgCl 2 , 900 nM forward primer, 300 nM reverse primer, 200 nM probe, 1.25 U AmpliTaq Gold DNA polymerase (PE/ABI), and the template genomic DNA. Thermal cycling conditions were as follows: activation of TaqGold at 95 °C for 10 min followed by 40 cycles of amplification at 95 °C for 15 s and 60 °C for 1 min. After amplification, data analysis was carried out using a ratio of test gene to reference gene to obtain a normalized copy number estimate of the test gene ( Bieche et al. 1998 ). The starting copy number in the template DNA was determined by the threshold cycle (C t ), which represents the PCR cycle at which an increase in reporter fluorescence above a baseline signal can first be detected. The starting copy number of each test gene was quantified in the ape samples by determining the C t of the test gene and using a standard curve for copy number. The standard curve for each gene was generated using the fluorescent data from five serial dilutions of human genomic DNA and calculating a single copy of each gene per haploid human genome, as annotated in the current genome build. Copy numbers of the test genes in ape samples were normalized to the copy number of the CFTR gene, which serves as a control representative of a single gene per haploid genome ( Rochette et al. 2001 ). The ratio “N” of the test gene copy number to CFTR copy number in each sample normalized the results with respect to differing starting quantity and quality of the template DNA in each reaction ( Bieche et al. 1998 ). Thus, “N” expresses the estimated copy number for each species using the derived standard curve and normalized to CFTR . RT-PCRs were carried out in triplicate for each gene in each species except human, in which five reactions were carried out for each gene to generate the standard curve. Supporting Information Figure S1 BAC FISH Analysis of Gene Predicted to Be Reduced Only in Orangutan FISH images of BAC probe RP11-93K3 containing sequences from IMAGE cDNA clone 1882505. (A) Normal human control, PHA-stimulated lymphocytes. Multiple (10–12) signals present: 9p12, 9q12, 4q arm, and two acrocentric p arm regions. The Chromosome 9 signals appear to flank the 9q heterochromatin and centromere regions, with the p arm signal a double signal. (B) Bonobo fibroblast culture. Multiple (10–12) signals. (C) Chimpanzee fibroblast culture. Multiple (10–12) signals. (D) Gorilla fibroblast culture. Multiple (12–15) signals. (E) Orangutan fibroblast culture. Two signals present on a pair of homologues (i.e., single copy in haploid genome). Also shown is a TreeView image (pseudocolor scale indicated) for IMAGE cDNA clone 1882505. (3.29 MB EPS). Click here for additional data file. Figure S2 TreeView Image of cDNAs Selected Using Relaxed HLS Criteria Figure shows a TreeView image of blocks of HLS genes selected using increasingly relaxed selection criteria. The top-most group represents HLS genes selected using the standard 0.5 cutoff value described in Materials and Methods , while successive groups (separated by gray bars) represent additional cDNAs that were selected as the cutoff was progressively reduced to 0.45, 0.4, 0.35, and 0.3. (1.9 MB EPS). Click here for additional data file. Figure S3 FISH Analysis with BAC Probe RP11-432G15 Containing the FLJ22004 Gene (A) Normal human control, PHA-stimulated lymphocytes. Signal at Chromosome 2q13 and 22qtel. (B) Bonobo fibroblast culture. Four signals. (C) Chimpanzee fibroblast culture. Four signals. (D) Gorilla fibroblast culture. More than 30 signals. Hybridization to most subtelomeric regions. (E) Orangutan fibroblast culture. No apparent red signal. Probe BAC RP11-1007701 in green included as internal hybridization control. Also shown are aCGH TreeView images (pseudocolor scale indicated) for three FLJ22004 cDNAs. (6.94 MB EPS). Click here for additional data file. Figure S4 GO Categories Pie graphs showing the distribution of GO molecular function categories within HLS, LS, and whole genome gene lists. The top 22 categories are named in the legend in descending order of representation for all three groups. Categories were ranked by normalizing each category value for HLS and LS lists to the genome-wide list and then ranking the sum of these values for each category. Less well-represented categories were omitted from the graphs in order to enhance legibility, and zero values are not listed. (1.1 MB EPS). Click here for additional data file. Figure S5 Interhominoid RT-PCR Analysis RT-PCR was used to provide an independent confirmation of interspecies cDNA aCGH data for three genes in which aCGH signals were different in the African great apes compared to human and orangutan. The chromosomal location, IMAGE clone ID, and GenBank accession numbers are provided for each cDNA. The species average log 2 ratios for each cDNA clone and the copy number ratio of the test gene to the CFTR (control) gene, as determined by RT-PCR, are shown for the indicated species. Also shown are TreeView images of interhominoid aCGH results for the indicated cDNAs and a graphical depiction of the correlation between aCGH signal and copy number ratio to CFTR (RT-PCR). (A) PLA2G4B cDNA clone located on human Chromosome 15 using the UCSC November 2002 human genome assembly. The correlation between RT-PCR and aCGH-based copy number estimates is 0.94. (B) FLJ31659 cDNA clone located on human Chromosome 4 using the UCSC November 2002 human genome assembly. As in (A), the correlation between RT-PCR and aCGH data is 0.97. (C) BC040199 transcript located on human Chromosome 7 using the UCSC November 2002 human genome assembly. As in (A), the correlation between RT-PCR and aCGH data is 0.97. (1.29 MB EPS). Click here for additional data file. Figure S6 FISH Analysis with BAC Probe RP11–23P13 Containing the Human PLA2G4B and SPTBN5 Genes (A) Normal human control, PHA-stimulated lymphocytes. Two signals localized to Chromosome 15q15.1. (B) Chimpanzee fibroblast culture. Two signals on the chromosome syntenic to human Chromosome 15 (at arrows). Multiple additional signals in the subtelomeric regions. (C) Gorilla fibroblast culture. Two signals on the chromosome syntenic to Chromosome 15 (at arrows). Two additional signals on a large metacentric chromosome, which in interphase appear as amplified signals. (D) Orangutan fibroblast culture. Two signals on the chromosome syntenic to human Chromosome 15. (4.39 MB EPS). Click here for additional data file. Protocol S1 How to View aCGH Data Using TreeView (2 KB TXT). Click here for additional data file. Table S1 Genome-Wide Interhominoid cDNA aCGH Gene Dataset Values are provided for genes (cDNAs) queried by interhominoid aCGH. For each IMAGE clone queried, log 2 aCGH values are listed for the human versus human samples ( n = 5), human versus bonobo samples ( n = 3), human versus chimpanzee ( n = 4), human versus gorilla ( n = 3), and human versus orangutan ( n = 3). This table is tab-delimited and can be opened in Microsoft Excel to view the raw numbers or can be browsed using TreeView (see Protocol S1). Column B provides information regarding IMAGE clone number, chromosome, and nucleotide position (UCSC November 2002 freeze), Unigene ID, EST accession numbers, and known gene information. (12.84 MB TXT). Click here for additional data file. Table S2 Detailed Comparison of HLS Gene and WSSD Datasets For each IMAGE clone of the HLS genes, one or more EST sequences were used as a query for a BLAST search against the WSSD dataset. An expect value cutoff of e –20 was used and the best hit is reported in the table. Query refers to the HLS gene EST sequences; subject refers to the WSSD sequences. Score, expect value, and percent identity (ID) are reported for the best BLAST hit, while the start and stop positions and length for both query and subject are also reported. (434 KB DOC). Click here for additional data file. Table S3 Satellite Repeat Subclass Analysis for LS Gene Clusters For each of the 23 LS gene clusters, Satellite repeat subclass analysis was performed. The table lists the cluster's cytogenetic region, the chromosome and start and stop positions, and the adjusted length after accounting for gaps in the genomic sequence. The percent content for 24 subclasses of Satellite repeats is listed for each of the 23 gene clusters. Summary information includes the average content of the 24 subclasses of Satellite repeats for all of the clusters as well as the average for the entire human genome. The difference and fold change are calculated based on comparing the cluster averages to the entire human genome averages. (111 KB DOC). Click here for additional data file. Table S4 LS Gene Datasets Similar to Table S1, but only IMAGE clones with LS characteristics are listed, and each is ranked based on average fluorescence signal (highest to lowest) within each lineage. (269 KB TXT). Click here for additional data file. Table S5 GO Analysis Comparing HLS and LS Genes to the Whole Genome (52 KB DOC). Click here for additional data file. Table S6 Functional Assessment of Copies of HLS Genes Presented are pertinent data from GO analysis with DAVID, including numbers of classified and unclassified genes in each gene list, as well as the data returned for each of the 22 most represented molecular function categories. Listed are GO identification numbers (GOIDs) and names for each of the top 22 categories, as well as raw values and relative percent values for HLS, LS, and genome classifications. Relative percent columns are taken as the ratio of the number of classifications in each category to the number of genes classified in the list. The average percent is also provided as the average of these relative percent values across the three groups. This is intended as a metric to help gauge deviations in group relative percent values from the combined average value. (81 KB DOC). Click here for additional data file. Table S7 Comparison of Human HLS Genes to Chimpanzee Genomic Sequence The table has three sections: a summary showing the percentages of blocks in each respective chimpanzee homology scoring class; a table with the HLS versus chimpanzee data; and a table with the random versus chimpanzee data. The HLS versus chimpanzee and random versus chimpanzee tables have columns derived from both parsing the BLAT PSL data and from the chimpanzee homology comparison. The table lists the IMAGE clone and the EST accession number used as a query, the hit number, the score and percent identities, the start and stop positions in the query, the chromosome and chromosome start and stop positions, the number of blocks of alignment for the hit, the numbers of blocks that fall into each chimpanzee homology scoring class, and finally the respective chimpanzee scaffold(s) for each hit, if available. (3.58 MB DOC). Click here for additional data file. Accession Numbers The GenBank accession number ( http://www.ncbi.nlm.nih.gov/Genbank/ ) for FGF7 is NM_002009 and for morpheus is AF132984. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC449870.xml |
517715 | Histologic assessment of biliary obstruction with different percutaneous endoluminal techniques | Background Despite the sophisticated cross sectional image techniques currently available, a number of biliary stenosis or obstructions remain of an uncertain nature. In these pathological conditions, an "intrinsic" parietal alteration is the cause of biliary obstruction and it is very difficult to differentiate benign from malignant lesions using cross-sectional imaging procedures alone. We evaluated the efficacy of different endoluminal techniques to achieve a definitive pathological diagnosis in these situations. Methods Eighty patients underwent brushing, and or biopsy of the biliary tree through an existing transhepatic biliary drainage route. A subcoort of 12 patients needed balloon-dilatation of the bile duct and the material covering the balloon surface was also sent for pathological examination (balloon surface sampling). Pathological results were compared with surgical findings or with long-term clinical and instrumental follow-ups. Success rates, sensitivity, specificity, accuracy, confidential intervals, positive predictive value and negative predictive value of the three percutaneous techniques in differentiating benign from malignant disease were assessed. The agreement coefficient of biopsy and brushing with final diagnosis was calculated using the Cohen's "K" value. Results Fifty-six patients had malignant strictures confirmed by surgery, histology, and by clinical follow-ups. Success rates of brushing, balloon surface sampling, and biopsy were 90.7, 100, and 100%, respectively. The comparative efficacy of brushing, balloon-surface sampling, and biopsy resulted as follows: sensitivity of 47.8, 87.5, and 92.1%, respectively; specificity of 100% for all the techniques; accuracy of 69.2, 91.7 and 93.6%, Positive Predictive Value of 100% for all the procedures and Negative Predictive Value of 55, 80, and 75%, respectively. Conclusions Percutaneous endoluminal biopsy is more accurate and sensitive than percutaneous bile duct brushing in the detection of malignant diseases (p < 0.01). | Background Bile duct dilatation and increasing jaundice are often onset symptoms of a number of either malignant or benign pathological conditions. In most cases, common cross-sectional imaging techniques such as ultrasonography (US) or spiral-CT or cholangio-pancreatico-biliary magnetic resonance (MRCP) are highly capable of depicting the causes of obstruction by simply showing extrinsic masses in case of infiltrating tumors or benign causes of jaundice, like stones [ 1 ]. These non invasive techniques, however, can still yield uncertain results in some particular benign or malignant pathological conditions. When stones are too small for example, or when bile duct dilatation is limited. For final confirmation or exclusion of endobiliary stones ERCP is unavoidable before the subsequent therapeutic steps. There are also some pathological conditions where an "intrinsic" parietal alteration is the cause of biliary obstruction and it is very difficult to distinguish benign from malignant lesions using cross-sectional imaging procedures alone (figure 4 - 5 ). A biliary dilatation may also occur after surgical interventions involving the biliary system, like bilioenteric anastomoses for gastric or pancreatic neoplasms or cholecystectomies. It is not always possible to distinguish between a recurrent disease or a fibrotic post-surgical stenosis, especially if it occurs early and if inflammatory alterations were already present during surgery. A number of obstructions remains therefore unexplained because the aforementioned imaging modalities do not show any extrinsic compressing or infiltrating mass, nor a calcolous disease. In these cases, only the intrahepatic bile ducts dilation and the level of the obstruction can be determined, but additional diagnostic procedures should be performed for a diagnosis of the real nature of the obstruction [ 2 ]. Patients with obstructive jaundice often undergo percutaneous biliary cholangiography and drainage (PBD) for decompression of the biliary tree. Although relatively invasive, not even PBD allows to achieve a definitive differential diagnosis between malignant and benign pathologies. Tissue sampling becomes therefore essential for the histological characterization of parietal alterations and for planning their appropriate treatment [ 3 ]. Bile cytology, although easily feasible either through a transhepatic or an endoscopic route, does not accomplish adequate pathological diagnoses in most cases [ 5 - 7 ]. In our study, three different endoluminal sampling techniques for the characterization of biliary strictures of uncertain nature have been reviewed and comparatively evaluated with the purpose of determining which one of them is the most accurate for differentiating between benign or malignant pathology. Methods Our investigation was performed on a population of 80 patients who, from January 1992 to September 1999, underwent endoluminal brushing and/or biopsy for biliary stenosis or obstructions of uncertain nature. A retrospective evaluation of the efficacy of these techniques was carried out by comparing the pathological findings on one hand and radiological findings, clinical long-term follow ups, and/or post-surgical specimens, on the other. Patient population included 43 men and 37 women, with a mean age of 62 years (range 37–87 years). All patients presented jaundice as a common symptom, weight loss was present in 20 cases (25%), and itching in 12 cases (15%). At admission, all patients presented biliary dilation, but no masses were identifiable by imaging procedures such as US, CT, MRCP. ERCP had been performed in 23 patients with middle-low common bile duct stenosis but the nature of obstruction could not be determined nor a drainage could be placed. Obstruction were located at the biliary bifurcation in 18 cases (22.5%), the common extrahepatic bile duct in 50 (62.5%), the right (2) and left (2) hepatic duct in 4 cases (5%) Eight patients with bilioenteric anastomoses (10%) were also evaluated in order to determine the nature of the stricture. The patients came to the interventional unit needing for a biliary drainage. PBDs were performed using standard interventional techniques.[ 5 ] The percutaneous approach was right lateral in all patients but 25 of them required also an anterior subxyphoid approach. The procedures for cytological and/or histological samples were performed in any case 3–5 days after placement of the biliary drainage in order to operate on a decompressed biliary system. One hundred and two endoluminal procedures were included in this study. Twenty-one patients underwent cytologic brushing only, 25 endoluminal biopsy only, and 22 both brushing and biopsy. A total number of 43 brushings and 47 biopsies were performed. In 12 additional cases, we obtained cytological and tissue samples from an angioplastic balloon used for the bilioplasty of strictures of uncertain nature (balloon surface sampling) with techniques that will be described. Sixteen patients underwent brushing only, because the cholangioscope was not available yet and five because the diagnosis of malignancy achieved with brushing was considered sufficient, thus not requiring further diagnostic workups to planning the appropriate therapy. All the specimens were collected after PBD thus after translesional advancement of a 10 French catheter; in 12 particularly heavy stenosis a preliminary balloon dilatation was also accomplished. Brushing was performed according to the following technical steps: - the indwelling biliary drainage catheter was exchanged over a guide-wire with a 7/9-F. introducer sheath without valves at the proximal end ("peel-away", William Cook, Europe) - a flexible probe (Fig. 3 ) with a cilindrical brush at the tip, 5 mm in diameter 10 mm in length (Olympus Italia srl. Code number BC20295010), was advanced through the sheath until it was beyond the lesion; the sheath was withdrawn to expose the brush, which was then pulled back and forth and rotated across the lesion several times under fluoroscopic control Figure 3 A metallic flexible probe with a cilindrical brush at the atraumatic tip, 5 mm in diameter 10 mm in length(Olympus Italia srl. Code number BC2029501) brush (approximately 1 cm in length and 5 mm in diameter) - the brush was then carefully pulled back to be removed from the patient into the sheath, to avoid malignant spreading through the transhepatic tract -samples were then placed on a glass slide, fixed with Sprayfix (Surgipath Medical Ind.; Illinois, USA), immediately submitted for cytological examination and stained by the standard Papanicolau technique. Endoluminal forceps biopsy was performed under direct visualization with a 5-mm. cholangioscope (Olympus URF. Type P, Japan) (Fig. 1 ). Sometimes, the site of the lesion endoscopically visible did not correspond to the site of the stenosis fluoroscopically detectable; additional samples were therefore collected under fluoroscopic guidance, according to the following technique: Figure 1 Flexible cholangioscope (5 mm in diameter) (Olympus, URF, type P, Japan) - the biliary catheter was replaced, over a guide, by a 18-F "peel-away" introducer sheath through which the cholangioscope was advanced until it was close to the lesion; - a flexible forceps (5-F. Olympus, FB 185X Fig. 2 ) was passed through the working channel of the cholangioscope to obtain 3–4 specimens for each patient; Figure 2 Alligator forceps (Olympus, FB 195X, Japan). The wire tip is open 25 - the specimens were fixed in a 10%-solution of formaline and sent to the pathologist, included in paraffin, and dissected in slices of 2–4 microns at microtome; subsequently, they were stained by hematoxilyn-eosin, PAS and Mallory techniques; - after completion of the biopsy procedures, all the patients underwent cholangiographic control checking for contrast material extravasation at the biopsy site and monitored for symptoms of hemobilia and/or bacteriemia. All the patients were submitted to antiobiotic therapy before and during the three days following endobiliary procedures. Twelve patients underwent preliminary bilioplasty because of the difficulties in advancing the drainage catheter across the biliary stricture. In this group, a different sampling was performed, based on the examination of those cells and/or tissue remained stuck to the angioplastic balloon after dilatation (balloon surface sampling): - once deflated, the balloon (8–10 mm., Meditech, Boston, USA) was pulled back into the sheath and removed from the patient; - the balloon was then placed in a saline solution with 10% of formalin, inflated and agitated several times to facilitate detachment of samples, which were then immediately delivered to the pathology laboratory. Pathological specimens from 14 patients were compared with open surgery findings and post-surgical pathological reports. The pathologists, hystologists and cytologists, were blinded as to corresponding results. The follow-up of the patients undergone to surgery stopped after the operation. Patients not candidate to surgery were treated with interventional procedures only such as bilioplasty, biliary drainage, interstitial radiotherapy and/or with chemotherapy or just a supportive therapy. This group of unoperated patients was followed-up on the basis of clinical and radiological data obtained by case-record reviews and by correspondence with their referring clinicians and general practitioners. The follow-up period ranged from 3 to 48 months. A minimum of 12 months of healthy negative cytological-histological diagnosis was necessary because either a clinically benign stenosing lesion or a cytohistological diagnosis negative for malignancy must be confirmed by a prolonged survival, as well as by clinical and radiological findings. Calculations of success rate, sensitivity, specificity, positive predictive value, and negative predictive value for each technique were based on the number of biopsy procedures (n = 102) rather than on the number of patients (n = 80), (Table 1 ) since each biopsy was considered as a separate event The success rate is the percentage of biopsy procedures resulting in sufficient material for microscopic evaluation. Table 1 Differentiation of biliary obstruction with different percutaneous endoluminal techniques Technique N. PTS SR TP TN FP FN Brushing 43 * 39/43 11 16 0 12 Biopsy 47 * 47/47 35 9 0 3 Balloon Brushing 12 12/12 7 4 0 1 SR= Success Rate; TP= True Positive; TN= True Negative; FP= false positive; FN= False Negative *22 patients underwent either brushing and forceps biopsy. Confidential Intervals (CIs) were determined for brushing and biopsy groups assuming a P value of .01 by using the Geigy Scientific Table (Geigy, Florence, 1984). The agreement coefficient between biopsy or brushing and final diagnosis was calculated using the Cohen's "K" value using SPSS 8.0 for Windows (SPSS, Chicago, Illinois, 1997). Results and discussion A final diagnosis of malignant disease was confirmed in 56 (70%) cases and a final diagnosis of benign disease in 24 (30%) cases for an overall of 80 patients. Final diagnoses in the malignant group included: cholangiocarcinoma (n = 31), adenocarcinoma (n = 6), metastatic adenocarcinoma (n = 5), pancreatic carcinoma (n = 13) and malignant endocrine tumor (n = 1). Final diagnoses in the benign group included: iatrogenic stenosis (n = 9), sclerosing cholangitis (n = 12) and primary (N = 2) and secondary biliary cirrhosis (N = 1). Thirty-nine of the 43 brushing biopsies procedures were technically adequate for the diagnostic evaluation. Four cases were considered "poorly cellular" by the pathologists, with an overall success rate of 90.7% (Table 1 ). These 4 cases underwent endoluminal forceps biopsy within 15 days from the brushing. Malignant cells were detected by brushing in 11 cases including: adenocarcinoma (n = 2), cholangiocarcinoma (n = 6), pancreatic carcinoma (n = 2), and metastatic adenocarcinoma (n= 1) (table 2 ). Table 2 True positives Type of tumour Brushing Biopsy Balloon-brushing Cholangiocarcinoma 6 18 5 Adenocarcinoma 2 1 1 Metastatic adenoca. 1 5 - Pancreatic carcinoma 2 10 1 Neuroendocrine tumor 1 - Of the 32 patients with negative findings for malignant cells, the 4 cases in whom the samples were considered "acellular" by the pathologists were excluded by the statistical analysis, as just mentioned. Hence, 16 out of 28 had a final diagnosis of benign disease confirmed by long-term clinical follow-up (true negatives) (Table 3 ) and 12 patients had a final diagnosis of malignancy (false negatives) (Table 4 ). Therefore, 11 true positives, 16 true negatives and 12 false negatives were obtained by cytological brushing, with an overall sensitivity, specificity, accuracy, PPV, and NPV in the detection of malignant diseases of 47.8, 100, 69.2, 100, and 57.1 % respectively (Table 1 , 5 ). Table 3 True negatives Type of tumor Brushing Biopsy Balloon-brushing Sclerosing cholangitis 10 4 - Biliary cirrhosis 3 2 - Iatrogenic strictures 3 3 4 Table 4 False negatives Type of tumor Brushing Biopsy Balloon-brushing Cholangiocarcinoma 7 - 1 Adenocarcinoma 2 1 - Pancreatic carcinoma 3 2 - Table 5 Statistical analysis Technique Sensitivity Specificity Accuracy PPV NPV Brushing 47.8% 28.10–69.66* 100% 87.30–100.00* 69.2% 100% 57.1% Biopsy 92.1% 75.56–98.53* 100% 89.34–100.00* 93.6% 100% 75% Balloon brushing 87.5% 52.30–99.96* 100% 64.31–100.00* 91.7% 100% 80% * 99% C.I. (Geigy scientific tables) Endoluminal forceps biopsy was performed in 47 cases. Thirty-five of these were interpreted as containing malignant cells (Table 2 ): cholangiocarcinoma (n = 18), pancreatic carcinoma (n = 10), metastatic adenocarcinoma (n = 5), adenocarcinoma (n = 1), and neuroendocrine tumor (n = 1). Nine of the 12 cases interpreted as containing inflammatory cells were confirmed by clinical and radiological follow-up as follows: sclerosing cholangitis (n = 4), iatrogenic stenosis (n = 3) and biliary cirrhosis (n = 2). Three cases were erroneously interpreted as benign (false negative) but the clinical follow-up revealed 2 pancreatic carcinomas and 1 adenocarcinoma (Table 4 ). With 35 true positives, 9 true negatives and 3 false negatives, endoluminal forceps biopsy showed a sensitivity of 92.1%, a specificity of 100%, an accuracy of 93.6%, and a PPV and NPV of 100 and 75%. CIs were reported in Table 5 . "K" values for biopsy and brushing vs clinical/surgical final diagnosis were 0.613 and 0.404, respectively (Table 6 ). Table 6 Cohen's Kappa value Cohen's Kappa Significance Brushing vs follow-up 0.404 0.001 Biospy vs follow-up 0.613 0.019 As previously discussed, 12 samples were obtained in as many patients with an angioplastic balloon after dilation of biliary strictures (balloon surface sampling). This technique demonstrated malignant cells in 7 (58.3%) cases and benign cells in 5 (41.7%). The final clinical diagnosis of the malignant group included adenocarcinoma (n = 1), cholangiocarcinoma (n = 5) and pancreatic carcinoma (n = 1) (Table 2 ). The final clinical diagnosis of the benign group included four iatrogenic stenosis (Table 3 ). In one case a sclerosing cholangitis was diagnosed by balloon brushing, but clinical follow-up and further investigations revealed a cholangiocarcinoma (Table 4 ). With this technique, we therefore had 1 false negative, 7 true positives and 4 true negatives, with a sensitivity, specificity, accuracy, positive predictive value and negative predictive value of 87.5, 100, 91.7, 100, 80%, respectively (Table 5 ). Twenty-two patients underwent brush cytology together with endoluminal forceps biopsy. By excluding the 4 patients whose specimens were considered "acellular" and comparing each procedure with the clinical follow-up and surgical specimens, we obtained 12 concordant and 6 discordant diagnoses. In the group of 12 concordant diagnoses, 6 benign diseases, such as primary sclerosing cholangitis (n = 3), iatrogenic stricture (n = 1) and biliary cirrhosis (n = 2) and 6 malignant diseases, such as cholangiocarcinoma (n = 3), pancreatic carcinoma (n = 2), and metastatic adenocarcinoma (n = 1) were included. All concordant diagnoses were confirmed by clinical or surgical follow-up. In the group of 6 discordant diagnoses, cholangiocarcinoma (n = 4) adenocarcinoma (n = 1) and pancreatic carcinoma (n = 1), were included. All the 6 malignancies misdiagnosed by brushing were correctly diagnosed by biopsy. Transient hemobilia (spontaneously reversed from 1 to 12 hours after the procedure), was observed in 5/47 (10.6%) patients who had undergone biopsy. In 4 of them, particular angulations of the access route was present and there were difficulties in negotiation of the stricture. No major complications directly related to the brush cytology or the endoluminal forceps biopsy procedures occurred. Discussion The evaluation of patients with biliary tract obstruction without evidence of any intrahepatic or extrahepatic growing mass has traditionally involved a variety of diagnostic imaging techniques [ 1 ]. Ultrasound and CT are often the initial diagnostic investigation to be performed and provide good information about the presence of biliary obstructions and the degree of ductal dilatation [ 8 ]. These imaging modalities, are however limited in depicting intraductal anatomy and, sometimes, in exactly determining the level and the cause of the obstruction [ 1 , 9 ]. Magnetic resonance cholangiography (MRC) is a non-invasive imaging modality providing a good visualization of the biliary. system. The sensitivity of MRC in the detection of choledocholithiasis has been reported as 90–100%, a comparable rate with that of endoscopic retrograde cholangiopancreatography (ERCP) [ 10 - 15 ]. The assessment of the level of obstruction also has been reported as highly accurate [ 16 - 19 ]. However, low-grade strictures or lesions causing biliary dilation may be missed by MRC [ 20 ]. The pathological characterization of presumed malignant strictures can be therefore, difficult, if not impossible, using noninvasive imaging studies alone in some intrinsic lesions causing biliary dilation. As a final diagnosis could radically affect further therapeutic choices histological, an histological characterization is required in the management of patients with biliary strictures [ 1 ]. Fine-needle percutaneous biopsy (FNPB) and fine-needle aspiration (FNA) has been reported poorly valuable in absence of a lesion clearly identifiable [ 21 , 22 ]. The tumor most frequently not identifiable as a true growing mass is cholangiocarcinoma and the differential diagnosis with primary sclerosing cholangitis is of somewhat importance [ 23 ]. The differential diagnosis between some carcinomas of the pancreatic head or small submucosal tumors of the ampulla and cholangiocarcinoma or inflammatory diseases, such as sclerosing cholangitis, can be very difficult in many cases. Patients with bilioenteric anastomoses after tumoral mass resection have a very complex local anatomic alteration that makes extremely difficult any radiological investigation searching for small recurrent neoplastic infiltrations [ 27 ]. Treatment protocols require pathological diagnoses for palliative or possibly curative therapy in almost all these types of conditions. In addition, the surgical technique itself can be different if a malignancy is present or not. Some Authors, when liver transplant is still indicated, suggest a large excision associated with gastrectomy, pancreatectomy and a transverse ascending colectomy [ 25 ]. Although the efficacy of this surgical approach is still under debate, the role of a preoperative diagnosis is extremely important. Malignant cells surrounding the biliary ducts may continuously exfoliated into the bile, especially in the case of tumors which breack through the mucosa, and become available for the cytological examination when the bile is collected either percutaneously or by ERCP. Cytodiagnosis is easy to be performed, atraumatic in nature, with less potential risk and associated with relatively low charges. This technique has shown low sensitivity (15–28%) and accuracy (48–58%) rates, due to an early cellular degeneration after bile collection and to "poorly cellular" specimens. In addition, some pathological aspects can affect the efficacy of the procedure, such as in case of lesions extrinsically compressing the bile duct wall without a complete transmural infiltration or an adequately wide mucosal disruption [ 22 ]. Endoluminal brush cytology was successfully performed either percutaneously, by Radiologists, or endoscopically, by Gastroenterologists [ 26 - 28 ]. In our experience, brush cytology showed a high specificity but low sensitivity and accuracy rate in the detection of malignant diseases. Technical limits were mostly represented by "poorly cellular samples". In our study, in fact, 4 cases (9.3%) were considered "poorly cellular" by the pathologists. In addition to these technical problems, similarly to bile cytology, we have to consider some morphological aspects that can negatively influence the sensitivity of this technique. According also with our cholangioscopic experience, biliary tumors may remain intramural causing an annular constriction of the biliary duct [ 21 , 29 ] without complete transmucosal infiltration, and this condition can mimic sclerosing cholangitis and render brush cytology ineffective. In light of the fact that there is a frequent relationship between sclerosing cholangitis and malignant strictures, the cytological differentiation between inflammatory and malignant changes can be extremely difficult. In addition, these tumors are frequently so well differentiated that their identification as "malignant" can be, even histologically, difficult [ 29 , 30 ]. These are the theoretical explanations that we can give to the fact that cytological diagnosis of cholangiocarcinoma yielded a relatively low sensitivity, verified in our study as well as in the literature [ 1 , 21 - 23 , 26 , 30 ]. At endoscopic sampling, cholangiocarcinoma has a higher sensitivity [ 28 ] In this review only patients not suitable for ERCP or coming from a failed drainage or other type of retrograde endoscopic intervention were evaluated, thus the percutaneous and endoscopic techniques can not be compared. Whenever possible especially if skilled endoscopists are available, retrograde approach could still to be considered the first step, for its potentially high sensitivity especially if repeated sampling are performed [ 27 , 28 ] Percutaneous brush cytology, if compared with bile transendoscopic cytodiagnosis, has the potential risk of a malignant spreading of cells through the transhepatic tract. To overcome this risk, in our opinion, the brush should be pulled back and removed from the patient into the introducer sheath. With this technique, in fact, no spreading along the transhepatic tract was observed in our malignant patients at imaging follow-up. Brush cytology is a easy, safe and at relatively low-cost procedure, similarly to bile collection. A single sampling however has a low possibility of detecting a malignancy. The results can improve with multiple samples. Three consecutive negative samples decrease the probability of a malignancy from more than 55% to less than 5% [ 30 ]. The absence of false positives in our and others, series [ 2 ] means that an intraductal biopsy has no purpose when an exfoliative cytology is positive. Meanwhile, in presence of a negative cytology, other techniques such as percutaneous FNA and endoluminal forceps biopsy should be mandatory. Fine needle aspiration performed either percutaneously or endoscopically has some technical advantages over endoluminal brushing in those lesions extrinsically compressing the biliary duct without deeply infiltrating the ductal wall, since the inner epithelial layer is not involved [ 21 ]. Most of these patients with biliary obstruction, especially with high lesions, however, in our Hospital, usually undergoes percutaneous biliary drainage in the early phases of their clinical work-up. A percutaneous FNA would represent an adjunctive interventional procedure that could be avoided by using the transhepatic route, already available. We had adequate percutaneous biopsy specimens in epithelial lesions, such as cholangiocarcinoma, and inadequate specimens in those lesions with inflammatory and/or necrotic changes. The dense fibrotic and scirrus reaction associated with pancreatic carcinoma may result in poor biopsies specimens [ 31 ]. In addition, pancreatic carcinoma is often associated with pancreatitis, necrotic cellular debris and a dense fibrotic reaction which can further contribute to the disappointing results obtained with even aggressive percutaneous biopsy techniques [ 32 ]. The differentiation degree of a tumor can affect the accuracy of the histological classification. In those cases of extrahepatic and periampullary biliary tumors, in fact, usually highly undifferentiated, the histological characterization can be difficult, although a generic diagnosis of malignancy can be made. Potential complications due to forceps biopsy, such as disruption of the ductal wall with consequent bile leak and bleeding, cholangitis and pancreatitis, are reported [ 33 ]. Endoluminal forceps biopsy especially in patients with hemobilia or cholangitis, should therefore be performed in the remission phase of the disease, and, in any case, at least 5 days after biliary drainage, to avoid the complications related to manipulations into the biliary tree. No major complications were observed in this series, neither from percutaneous brushing nor from forceps biopsy. A transient hemobilia was observed in 5 patients who had undergone biopsy (10.6%). This series, including part of a previously analyzed smaller population [ 33 ] confirms that percutaneous endoluminal forceps biopsy has a very high sensitivity (92.1%), specificity (100%), accuracy (93.6%), PPV (100%), and NPV (75%) in the detection of malignant diseases (Table 2 ). The higher accuracy of biopsy over brushing is very clear, especially analyzing the data obtained in those patients in whom both techniques were performed. On the other hand, biopsy presents some disadvantages, such as the higher costs of the equipment and the difficult trackability across tight strictures or acute angles of the biliary ducts. A high diagnostic value was proven by the simple examination of tissue samplings coming from balloon dilatation of biliary or bilio-enteric anastomotic strictures (balloon surface sampling). Although the number of cases reported in this series is relatively small, it should be considered that it was possible to distinguish benign from malignant diseases in almost all the cases. Our suggestion, therefore is to associate a tissue collection from the balloon to bilioplasty, as a standard procedure when screening for malignant pancreatobiliary diseases is required. In this way. it is possible to save time and avoid risks related to further endobiliary procedures. Conclusion Patients with obstructive jaundice, who are candidates for biliary drainage, often come to the interventional radiologist still without a definitive diagnosis of the real nature of their disease, even after high-level cross-sectional imaging procedures, such as abdominal MR, MRCP or abdominal spiral-CT. When the clinical diagnosis needs to be histologically confirmed for further therapeutic choices, the transhepatic route can be successfully used for the intraductal sampling. Forceps biopsy is highly accurate under cholangioscopic guidance. As an alternative, repeated brushings can be performed under fluoroscopy. If a balloon blioplasty, for any reason, is performed, it is advisable to collect the tissue fragments on the balloon surface and send them for pathological evaluation. Competing interests None declared. Authors' contributions MR carried out the interventional procedures, participated in the design of the study and drafted the manuscript, FMS carried out the interventional procedures, VC defined the design of the study and performed the statistical analysis, LG collected the results of the procedures, LG participated in the histological analysis, AR participated in the design of the study and drafted the manuscript,, GG participated in the imaging evaluations, EP performed the patients follow-up, VD supervised the drafting of the study Figure 4 A 58 year old man, who 8 years ago underwent left hepatectomy and cholecistectomy, for complicated intrahepatic biliary stones, presented with jaundice and weight loss. Enhanced CT scan showed marked intrahepatic biliary dilation. Figure 5 Same patient as fig 4, at lower level, although, an extrinsic mass was not detected, the lumen of CBD appeared replacement by soft tissue mass density (arrows). Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517715.xml |
517932 | Plasticity of histamine H3 receptor expression and binding in the vestibular nuclei after labyrinthectomy in rat | Background In rat, deafferentation of one labyrinth (unilateral labyrinthectomy) results in a characteristic syndrome of ocular and motor postural disorders (e.g., barrel rotation, circling behavior, and spontaneous nystagmus). Behavioral recovery (e.g., diminished symptoms), encompassing 1 week after unilateral labyrinthectomy, has been termed vestibular compensation. Evidence suggesting that the histamine H 3 receptor plays a key role in vestibular compensation comes from studies indicating that betahistine, a histamine-like drug that acts as both a partial histamine H 1 receptor agonist and an H 3 receptor antagonist, can accelerate the process of vestibular compensation. Results Expression levels for histamine H 3 receptor (total) as well as three isoforms which display variable lengths of the third intracellular loop of the receptor were analyzed using in situ hybridization on brain sections containing the rat medial vestibular nucleus after unilateral labyrinthectomy. We compared these expression levels to H 3 receptor binding densities. Total H 3 receptor mRNA levels (detected by oligo probe H 3X ) as well as mRNA levels of the three receptor isoforms studied (detected by oligo probes H 3A , H 3B , and H 3C ) showed a pattern of increase, which was bilaterally significant at 24 h post-lesion for both H 3X and H 3C , followed by significant bilateral decreases in medial vestibular nuclei occurring 48 h (H 3X and H 3B ) and 1 week post-lesion (H 3A , H 3B , and H 3C ). Expression levels of H 3B was an exception to the forementioned pattern with significant decreases already detected at 24 h post-lesion. Coinciding with the decreasing trends in H 3 receptor mRNA levels was an observed increase in H 3 receptor binding densities occurring in the ipsilateral medial vestibular nuclei 48 h post-lesion. Conclusion Progressive recovery of the resting discharge of the deafferentated medial vestibular nuclei neurons results in functional restoration of the static postural and occulomotor deficits, usually occurring within a time frame of 48 hours in rats. Our data suggests that the H 3 receptor may be an essential part of pre-synaptic mechanisms required for reestablishing resting activities 48 h after unilateral labyrinthectomy. | Background In rat, deafferentation of one labyrinth (unilateral labyrinthectomy) results in a characteristic syndrome of ocular motor and postural disorders. These disorders have been divided into two categories : One category of symptoms, called static, includes head rotation in both the frontal and horizontal planes and ocular nystagmus [ 1 ]. The other category, called dynamic, corresponds to a decreased gain of the vestibulo-ocular and vestibulo-spinal refelxes [ 1 ]. Behavioral recovery (e.g., diminished symptoms), encompassing 1 week after unilateral labyrinthectomy, has been termed vestibular compensation [ 2 ]. Moreover, the time course of recovery is very different for static and dynamic reflexes: static deficits disappear in one week but dynamic deficits tend to take several months to normalize. Because unilateral labyrinthectomy results in a permanent loss of vestibular inputs from the lesioned side, the compensatory process is assumed to be attributable to the reorganization of the neural network in the central vestibular system [ 3 , 4 ]. Many brain regions including, the medial vestibular nucleus (MVe), are implicated in this process of recovery [ 5 - 7 ]. The focus of our study is the histamine H 3 receptor that was initially characterized as an autoreceptor controlling histamine synthesis and release [ 8 , 9 ]. Subsequently, as a heteroreceptor, the H 3 receptor was found to mediate presynaptic inhibition of release of histamine, noradrenaline, serotonin, dopamine, glutamate, GABA and tachykinins [ 10 - 13 ], presumably by inhibiting calcium channels [ 14 - 16 ]. The histamine H 3 receptor was recently cloned from human [ 17 ], monkey [ 18 ], rat [ 19 ], mouse [ 20 ], and guinea pig [ 21 ]. Moreover, the receptor was found to have several isoforms [ 21 - 26 ] with differential coupling to second messenger systems and a variation in their distribution in a region-specific manner. The isoforms are formed by alternative splicing of the messenger RNA (mRNA; [ 22 , 24 ]). This study involves analysis of trends observed in mRNA expression levels for the H 3 receptor (H 3X , the oligonucleotide probe detecting all H 3 receptor mRNAs characterized so far) as well as three of the known functionally active isoforms (H 3A , H 3B , and H 3C ), described by Drutel et al. [ 24 ], during the process of post-lesional plasticity in the central nervous system (CNS). The primary source of histamine (e.g., ligand for H 3 receptors) are histaminergic perikarya located exclusively in the tuberomammillary nuclei of the posterior hypothalamus [ 27 , 28 ]; these same neurons send axonal projections to many areas of the brain including the vestibular nuclear complex in rat [ 29 - 32 ]. The fact that the rat vestibular nuclear complex is endowed with the H 3 receptor was established by use of ligand binding [ 33 , 34 ] and in situ hybridization methods [ 34 ]. Evidence suggesting that the H 3 receptor plays a key role in vestibular compensation comes from studies indicating that betahistine, a histamine-like drug that acts as both a partial histamine H 1 receptor agonist and an H 3 receptor antagonist [ 14 , 35 ], accelerates the process of vestibular compensation [ 32 , 36 ]. Furthermore, studies have shown that betahistine treatment results in a reduction of [3H] N -α-methylhistamine labelling in the vestibular nuclear complex [ 37 ]; these findings suggest that betahistine increases histamine turnover and release by blocking presynaptic H 3 receptors and inducing H 3 receptor downregulation [ 37 ]. It is noteworthy that dynamic vestibular functions can be modulated by H 3 receptor ligands, e.g., thioperamide [ 38 ]; moreover, thioperamide can affect tonic vestibular functions as well with its demonstrated ability to attenuate barrel rotation in rats following unilateral labyrinthectomy [ 39 ]. The forementioned studies make tenable the view that further elucidation of H 3 receptor regulation is required to fully understand the process of vestibular compensation. The detailed aim of this study was to characterize the patterning of mRNA expression levels for all possible mRNA splice variants of the H 3 receptor (H 3X ; as described in [ 24 ]) and its isoforms which display different variations of the third intracellular loop (H 3A , H 3B , and H 3C ; as described in [ 24 ]) in the medial vestibular nucleus (MVe) during the process of vestibular compensation. Moreover, in this study, we compared the aforementioned trend in mRNA expression levels with H 3 receptor binding densities to reveal the possible plastic changes in the H 3 receptor which is responsible for significant constitutive activity also in vivo [ 40 ], histamine-mediated regulation of neurotransmitter release, and therapeutic effects of betahistine. Results Expression patterns of total H 3 receptor and H 3 receptor isoforms (H 3A , H 3B , and H 3C ) Changes in mRNA expression levels for H 3 receptor and the three H 3 receptor isoforms (Figure 1A,1B,1C and 1D , respectively) occured bilaterally; that is, there were no significant differences detected between the ipsilateral and contralateral medial vestibular nuclei of animals in all groups studied (e.g., control, 4 h post-lesion, 24 h post-lesion, 48 h post-lesion [n = 4, for each group], and 1 week post-lesion [n = 5]). We compared the total H 3 receptor mRNA expression levels (using probe H 3X ) in ipsilateral MVe of control animals to that of test animals from the four time points (Fig. 1A ). Fig. 2B shows scanned X-ray film depiction of H 3X expression in a representative animal 24 h post-lesion. We found no significant rise in H 3X mRNA levels in the ipsilateral MVe 4 hours after lesioning. Significant increases in H 3X mRNA levels were found to occur at 24 and 48 hours post-lesion. After 1 week post-lesion, H 3 receptor mRNA expression levels (as indicated by probe H 3X ) returned to normal levels. The trend observed was similar when comparing H 3X mRNA levels in contralateral MVe of control animals with that of test animals from the four time points. There was no significant change in total H 3 receptor mRNA levels detected in contralateral MVe 4 hours post-lesion, but we found a significant increase in H 3X mRNA levels detected in contralateral MVe both 24 hours and 48 hours post-lesion. Finally, a return to normal levels in total H 3X receptor mRNA level was detected in contralateral MVe 1 week post-lesion. No significant increases in H 3A mRNA expression levels were detected when we compared ipsilateral MVe in control animals with ipsilateral MVe 4 hours, 24 hours, and 48 hours post-lesion (Fig. 1B ). Fig. 2D shows scanned X-ray film depiction of H 3A expression in a representative animal 24 h post-lesion. On the other hand, a significant decrease of H 3A mRNA levels does occur in the ipsilateral MVe 1 week after lesioning. The trend was identical when comparing H 3A mRNA levels in contralateral MVe of control animals with H 3A mRNA levels in contralateral MVe of animals from the four time points: There was no significant increase in H 3A mRNA levels when comparing to contralateral MVe 4 hours, 24 hours, and 48 hours post-lesion; on the other hand, there is a significant decrease in H 3A mRNA levels when comparing to contralateral MVe 1 week after lesioning. No significant changes in H 3B mRNA expression levels were detected when we compared ipsilateral MVe in control animals to ipsilateral MVe 4 hours post-lesion (Fig. 1C ). Fig. 2F shows scanned X-ray film depiction of H 3B expression in a representative animal 24 h post-lesion. Significant decreases in mRNA levels were found in the ipsilateral MVe 24 hours, 48 hours, and 1 week after lesioning. When comparing contralateral MVe of control animals to contralateral MVe of animals in the other time points, there was a significant increase detected 4 hours post-lesion and this was followed by significant decreases detected at 24 hours, 48 hours after lesion, and 1 week post-lesion. No significant changes in H 3C mRNA levels were detected when we compared ipsilateral MVe in control animals to ipsilateral MVe 4 hours post-lesion (Fig. 1D ). Fig. 2H shows scanned X-ray film depiction of H 3C expression in a representative animal 24 h post-lesion. A significant increase was detected when comparing ipsilateral MVe of control animals to ipsilateral MVe 24 hours post-lesion; moreover, the decrease in H 3C mRNA levels in the ipsilateral MVe 48 hours post-lesion was not significantly different from those of the ipsilateral MVe in control animals. Finally, in comparison to the ipsilateral MVe in controls, there was a decrease in mRNA levels that was found to be significant in the ipsilateral MVe 1 week post-lesion. Results were similar when comparing the contralateral MVe in control animals to contralateral MVe from the other time points: There was no significant increase in H 3C mRNA levels when comparing to contralateral MVe 4 hours post-lesion, there was a significant increase detected when comparing to contralateral MVe 24 hours post-lesion, the decrease was not significant comparing to contralateral MVe 48 hours post-lesion, and a significant decrease was detected when comparing to contralateral MVe 1 week post-lesion. [ 125 I]iodoproxyfan Binding Densities No significant changes were found in H 3 receptor binding densities (Fig. 3 ) between ipsilateral MVe in control animals (n = 3) and ipsilateral MVe of animals of different time points. The results were identical when H 3 receptor binding densities in contralateral MVe in control animals were compared to that of contralateral MVe at different times post-lesion. On the other hand, when comparing the ipsilateral to contralateral MVe 48 hours post-lesion, a significant increase in binding densities occurred on the ipsilateral side (Fig. 4 shows an example of H 3 receptor binding densities in a representative animal 48 h post-lesion). Discussion Knowing that there is no reliable method to determine the efficiency of a probe for its targetted sequence in an mRNA of interest, this study focuses instead on the pattern of expression for the total H 3 receptor (detected by using probe H 3X ) and its isoforms (H 3A , H 3B , and H 3C ) occurring during the process of post-lesional plasticity in the CNS. Moreover, the probes used in this study were designed to detect unique areas in the transcripts (H 3A ), or junctional areas in deletion isoforms (probes H 3B and H 3C ) which would make it highly unlikely for non-specific hybridization would occur. This study also includes a comparison of the aforementioned patterns of expression with binding densities for the H 3 receptor. The prepositus nuclei are delineated and mentioned in legends for figures 2 and 4 . These nuclei are delineated for the sole purpose of giving the reader an idea of the dorsoventral extent of the MVe at the levels depicted in figures 2 and 4 . Noteworthy, is that these nuclei are not included in the main functional projections in the vestibulo-ocular and vestibulo-spinal pathways from the brainstem vestibular nucleus in mammals reviewed by Smith and Curthoys [ 2 ]. There are three previously described types of neurons in the medial vestibular nucleus [ 41 , 42 ]; in vitro, all three types are depolarized by histamine [ 43 , 44 ]. Moreover, this depolarization has been shown to be exclusively mediated through postsynaptic H 2 receptors [ 43 , 44 ] suggesting a presynaptic localization of H 3 receptors in the medial vestibular nuclei [ 38 ]. Consequently, there are three possible locations for H 3 receptors in the MVe: 1) On the histaminergic or other incoming fibers innervating the MVe [ 29 - 32 ]. 2) On terminals of the inhibitory interneurons in the MVe that make synaptic contacts on second order excitatory neurons-defined as neurons in the vestibular nuclei that receive inputs from sensory afferents [ 45 ]. 3) On the terminals of second order excitatory MVe neurons making cross-commissural synaptic contacts on contralateral MVe inhibitory interneurons [ 45 ]. With respect to MVe on the lesioned side, an H 3 receptor mediated inhibition of GABA release from inhibitory interneurons or glutamate release from terminals of second order excitatory MVe neurons may underlie the restoration of resting activity in the deafferentated MVe; more precisely, H 3 receptor action would result in disinhibition of neurons in the deafferentated MVe With respect to the first possible location, it has been established that histamine fibers are endowed with H 3 receptors that function as autoreceptors and inhibit histamine release [ 11 , 13 ]. Support for the notion that H 3 receptors are at the next two possible locations (i.e., either at the terminals of the inhibitory interneurons or at the terminals of second order MVe neurons) comes from work showing that betahistine antagonizes the excitatory effect of histamine on vestibular neurons from in vitro slice preparations of the dorsal brainstem of the rat [ 46 ]. This finding is significant given that H 3 receptors mediate presynaptic inhibition of release of other neurotransmitters including: noradrenaline, serotonin, dopamine, glutamate, GABA and tachykinins [ 10 - 13 ]. Unilateral labyrinthectomy induced changes in expression levels of receptors for glutamate (e.g., NR1 and NR2A-D subunits of the NMDA receptor [ 47 ] and GluR2-4 subunits of the AMPA receptor [ 48 ]) have been studied in the vestibular nuclei. Moreover, the existence of both GABA A and GABA B receptors in the vestibular nuclei and their involvement in vestibular compensation has been demonstrated by either unilateral perfusion or microinjection of GABAergic agonists and antagonists (e.g., GABA, muscimol, and bicuculline) [ 49 ]. Consequently, an H 3 receptor antagonist such as betahistine could either facilitate GABA release from inhibitory interneurons located in the MVe that make synaptic contacts with second order neurons or facilitate glutamate release from terminals of second order MVe neurons that synapse on inhibitory interneurons in the contralateral MVe [ 31 , 45 ]. Either scenario would lead to an inhibition of second order neurons in the MVe and this would explain the observation that betahistine antagonizes the excitatory effect of histamine on vestibular neurons [ 46 ]. On the other hand, betahistine administration is reported to induce recovery with a time benefit of 2 weeks relative to control animals after unilateral vestibular neurectomy [ 32 , 36 ]; this is thought to be due to a bilateral increase in histamine release in the MVe [ 32 , 37 ]. The increased histamine would be bound by H 2 receptors on the perikarya of MVe neurons ipsilateral and contralateral to the lesion resulting in a bilateral increase in activity. This should facilitate behavioral recovery as it is thought that an imbalance in discharge of MVe neurons (30–40 spikes/s in normal animals [ 4 ]) ipsilateral and contralateral to the lesion underlies the static postural and occulomotor deficits triggered by unilateral labyrinthectomy [ 45 ]. Yet, as stated before, the actions of betahistine would also extend to H 3 receptors located on glutamatergic terminals of contralateral MVe neurons or on GABAergic terminals of inhibitory MVe interneurons. Antagonism of H 3 receptors at either site may also act to speed recovery by increasing the amount of GABA output from terminals of inhibitory interneurons and, as a consequence, equalizing neuronal discharge activity of ipsilateral and contralateral MVe. The trends toward bilateral increases (24 h post-lesion) followed by decreases (48 h post-lesion) in total H 3 receptor and H 3A , and H 3C isoform mRNA levels, with H 3B mRNA levels already increasing at 4 hours post-lesion and decreasing at 24 h post-lesion, coinciding with a significant increase in H 3 receptor binding densities in the ipsilateral MVe detected 48 hours post-lesion suggests the occurrence of one or a combination of events in the ipsilateral MVe: 1) an increase in translation has occurred. 2) A change in receptor trafficking between intracellular stores and cell membrane has occurred so that it can be detected as an increase in H 3 receptor receptor binding densities. In either case, an increase in functional H 3 receptor protein coupled with an increase in receptor activity may lead to a restoration of resting activity in the deafferentated MVe by scenarios already mentioned in this section. Conclusions Our findings are significant given that normalization of resting activities in neurons located in the ipsilateral MVe has been shown to occur 48 hours after unilateral labyrinthectomy [ 50 ]. Moreover, by 48 hours post-lesion, commissural disinhibition has been observed to occur [ 51 ]. Placement of H 3 receptors at the terminals of either GABAergic inhibitory MVe interneurons or on terminals of glutamatergic second order MVe neurons with contralateral projections should result in the observed commissural disinhibition as increased H 3 receptor activity would result in an inhibition of synaptic release of neurotransmitters. Our data would thus suggest that H 3 receptors are involved in presynaptic mechanisms resulting in a normalization of resting activities in ipsilateral MVe neurons which would balance discharge activity in MVe on both sides. Methods Animals and surgery This study was approved by the Local Committee for Animal Experiments and the Provincial State Office of Western Finland; in addition, animal experiments were in accordance with the European Convention (1986) guidelines and approved by the Animal Ethics Committee of Abo Akademi Unviversity. Adult male Sprague Dawley rats (200–250 g) were used. Intraperitoneal (ip) injection of pentobarbital (45 mg/kg ip; Mebunat, Orion, Finland) was used as an anesthetic; in addition, local anesthetic Lidocain (Orion, Finland) was infiltrated under the skin and periosteum prior the procedure. Three steps initiated the surgical procedure to left side of the animal's head: retroauricular skin incision, opening of the middle ear bulla with a drill, and removal of the ossicular chain with the aid of a microscope. Unilateral labyrinthectomy was carried out by opening the horizontal semicircular canal duct in the temporal bone, drilling through the horizontal and anterior semicircular canal ampullae and aspirating the contents of the vestibule. 100% ethanol was injected into the opened labyrinth to finalize the procedure; finally, the wound was sutured. The sham operation entailed opening the middle ear bulla and leaving the ossicular chain intact prior to suturing the wound, as described in Cameron and Dutia [ 52 ]; the control animals (n = 4) that underwent the sham operation were killed 4 h later. The method is explained hereafter. All rats included in the experiments displayed symptoms characteristic of animals that have undergone unilateral labyrinthectomy (e.g., barrel rotation, circling behavior, and spontaneuos nystagmus). These symptoms gadually disappeared during the first two or three days and were completely absent within one week. Animals were stunned by CO 2 gas and killed by decapitation 4 h (n = 4), 24 h (n = 4), 48 h (n = 4) and 1 week (n = 5) after labyrinthectomy. Tissue preparation After the mentioned decapitation, brains were removed, frozen in isopentane (-25°C), and stored at -70°C. Tissues were then cut to 20 μm thick cryosections, thaw mounted onto poly-L-lysine coated slides (Menzel-Gläser, Germany), and stored at -70°C until used. In-situ hybridization histochemistry The oligonucleotide probes used for in situ hybridization were designed so that they specifically recognized the different H 3 receptor isoform mRNAs (H 3A , H 3B , and H 3C ; as described in [ 24 ]); an additional oligonucleotide probes was used to detect all characterized H 3 receptor isoforms (H 3X ; as described in [ 24 ]). Sequences for H 3X , H 3A , H 3B , and H 3C probes have been previously published [ 24 ]. It is noteworthy that the isoform-specific probes detect selectively the various deletion forms of the third intracellular loop, but do not differentiate between the possible alternative C-termini of the H 3 receptor isoforms [ 53 ]. However, it has been shown that the differences in the third intracellular loop are significant for coupling to intracellular second messengers [ 24 ]. As a control, we used a normal hybridization mixture with a 100-fold excess of unlabeled specific probes. As an additional control, we used a Staphylococcus aureus chloramphenicol acetyltransferase-specific oligonucleotide probe. The hybridization procedure used has been described before and was used with minor modifications [ 54 , 55 ]. All probes were labeled with [ 35 S]deoxyadenosine 5'-α(-thio) triphosphate (New England Nuclear, USA) at their 3' ends using terminal deoxynucleotide transferase (Promega, USA). Nonincorporated nucleotides were removed by purification through Sephadex G-50 columns. Before hybridization, cryosections were taken from the -70°C environment and kept at room temeprature for 10 min and treated with UV light for 5 min. The hybridization (10 7 cpm/ml) was carried out at 50°C for 16 to 20 hours in a humidified chamber. Posthybridization washes were carried out as described previously [ 55 ]. Brain sections from control animals and animals 4 h, 24 h, 48 h, and 1 week post-lesion were treated simultaneously with their respective oligonucleotide probe. Sections and carbon-14 standards were exposed to Kodak BioMax X-ray films (Kodak, USA) for 10 days. Receptor binding autoradiography Autoradiographic localization of [ 125 I]iodoproxyfan binding sites has been described before [ 56 ]. Briefly, slide mounted tissue sections were preincubated for 15 min in 50 mM Na 2 HPO 4 -KH 2 PO 4 phosphate buffer, pH 6.8, containing 0.1% bovine serum albumin and 1 μM S132 (a 1-substituted imidazole derivative displaying a very low affinity at H 3 receptors and used to decrease non-specific labelling). The sections were then incubated for 1 hour at room temperature in the same buffer containing 15 pM [ 125 I]iodoproxyfan (Amersham Pharmacia Biotech UK Limited, England). Non-specific binding was determined by incubating consecutive sections in the presence of 1 μM (R)α-methylhistamine (Sigma-Aldrich, Germany). At the completion of incubation, the tissues were washed four times (4 min each) in the same fresh ice-cold buffer, dipped into ice-cold water, and dried under a current of air. Brain sections from control animals and animals 4 h, 24 h, 48 h, and 1 week post-lesion were treated simultaneously. Dried sections, along with standards, were exposed to Kodak BioMax X-ray films (Kodak, USA) for 2 days. Image analysis and statistics Autoradiographic films were quantified by digitizing the film images with a computer based MCID 5+ image analysis system (Imaging Research, Canada) and by measuring gray scale pixel values. The relative optic density was converted to integrated optic density (IOD) based on a standard curve derived from standards exposed to films. Gray scale values were determined from four sections for each animal, measurements from white matter of each respective section were subtracted to obtain the final values, and the data were analyzed using either a paired t-test or one-way ANOVA combined with Bonferroni's Multiple Comparison Test as a post-hoc test. Significance was determined when p < 0.05. Authors' contributions AL assisted with the surgeries and tissue collection, sectioned all of the brains, carried out the in situ hybridization and binding studies, performed all of the image and statistical analyses, and participated in the design of the study. AAA performed the surgeries, assisted with tissue collection, assisted with image analyses, and participated in the design of the study. KK established the method of in situ hybridization in the lab, designed the oligonucleotide probes, assisted with surgeries and tissue collection, and participated in the design of the study. HS synthesized and supplied rare chemicals required for the binding study. PP acquired funding, coordinated the study, and participated in its design. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517932.xml |
522751 | Priming nonlinear searches for pathway identification | Background Dense time series of metabolite concentrations or of the expression patterns of proteins may be available in the near future as a result of the rapid development of novel, high-throughput experimental techniques. Such time series implicitly contain valuable information about the connectivity and regulatory structure of the underlying metabolic or proteomic networks. The extraction of this information is a challenging task because it usually requires nonlinear estimation methods that involve iterative search algorithms. Priming these algorithms with high-quality initial guesses can greatly accelerate the search process. In this article, we propose to obtain such guesses by preprocessing the temporal profile data and fitting them preliminarily by multivariate linear regression. Results The results of a small-scale analysis indicate that the regression coefficients reflect the connectivity of the network quite well. Using the mathematical modeling framework of Biochemical Systems Theory (BST), we also show that the regression coefficients may be translated into constraints on the parameter values of the nonlinear BST model, thereby reducing the parameter search space considerably. Conclusion The proposed method provides a good approach for obtaining a preliminary network structure from dense time series. This will be more valuable as the systems become larger, because preprocessing and effective priming can significantly limit the search space of parameters defining the network connectivity, thereby facilitating the nonlinear estimation task. | Introduction The rapid development of experimental tools like nuclear magnetic resonance (NMR), mass spectrometry (MS), tissue array analysis, phosphorylation of protein kinases, and fluorescence labeling combined with autoradiography on two-dimensional gels promises unprecedented, powerful strategies for the identification of the structure of metabolic and proteomic networks. What is common to these techniques is that they allow simultaneous measurements of multiple metabolites or proteins. At present, these types of measurements are in their infancy and typically limited to snapshots of many metabolites at one time point ( e.g. , with MS; [ 1 , 2 ]), to short time series covering a modest number of metabolites or proteins ( e.g. , with NMR [ 3 , 4 ], 2-d gels [ 5 ] or protein kinase phosphorylation [ 6 ]), or to tissue arrays [ 7 ] that permit the simultaneous high-throughput analysis of proteins in a single tissue section by means of antibody binding or MS. Nonetheless, it is merely a matter of time that these methods will be extended to relatively dense time series of many concentration or protein expression values. We will refer to these types of data as metabolic or proteomic profiles and to the time development of a single variable within such a composite profile as trace . The intriguing aspect of profiles is that they implicitly contain information about the dynamics and regulation of the pathway or network from which the data were obtained. The challenge for the mathematical modeler is thus to develop methods that extract this information and lead to insights about the underlying pathway or network. In simple cases, the extraction of information can be accomplished to some degree by direct observation and interpretation of the shape of profiles. For instance, assuming a pulse perturbation from a stable steady state, Vance et al. [ 8 ] present guidelines for how relationships between the perturbed variable and the remaining variables may be deduced from characteristics of the resulting time profiles. These characteristics include the direction and timing of extreme values ( i.e. , the maximum deviation from steady state) as well as the slopes of the traces at the initial phase of the response. Torralba et al. [ 9 ] recently demonstrated that these guidelines, applied to a relatively small set of experiments, were sufficient to identify the first steps of an in vitro glycolytic system. Similarly, by studying a large number of perturbations, Samoilov et al. [ 10 ] showed that it is possible to quantify time-lagged correlations between species and to use these to draw conclusions about the underlying network. For larger and more complex systems, simple inspection of peaks and initial slopes is not feasible. Instead, the extraction of information from profiles requires two components. One is of a mathematical nature and consists of the need for a model structure that is believed to have the capability of capturing the dynamics of the underlying network structure with sufficient accuracy. The second is computational and consists of fitting this model to the observed data. Given these two components along with profile data, the inference of a network is in principle a regression problem, where the aim is minimization of the distance between the model and the data. If a linear model is deemed appropriate for the given data, this process is indeed trivial, because it simply requires multivariate linear regression, which is straightforward even in high-dimensional cases. However, linear models are seldom valid as representations of biological data, and the alternative of a nonlinear model poses several taxing challenges. First, in contrast to linear models, there are infinite possibilities for nonlinear model structures. In specific cases, the subject area from which the data were obtained may suggest particular models, such as a logistic function for bacterial growth, but in a generic sense there are hardly any guidelines that would help with model selection. One strategy for tackling this problem is the use of canonical forms , which are nonlinear structures that conceptually resemble the unalterable linear systems models, but are nonlinear. Canonical models have in common that they always have the same mathematical structure, no matter what the application area is. They also have a number of desirable features, which include the ability to capture a wide variety of behaviors, minimal requirements for a priori information, clearly defined relationships between network characteristics and parameters, and greatly enhanced facility for customized analysis. The best-known examples of nonlinear canonical forms are Lotka-Volterra models (LV; [ 11 ]), their generalizations [ 12 ], and power-law representations within the modeling framework of Biochemical Systems Theory (BST; [ 13 - 15 ]), most notably Generalized Mass Action (GMA) systems and S-systems. Lotka-Volterra models have their origin in ecology and focus strictly on interactions between two species at a time. Well-studied examples include competition processes between species, the dynamics of predators and prey, and the spread of endemic infections. In the present context it might seem reasonable to explore the feasibility of these models for the representation of the dynamics of proteins and transcription factor networks, but this has not been done so far. The strict focus on two-component interactions in LV models has substantial mathematical advantages, but it has proven less convenient for the representation of metabolic pathways, where individual reaction steps depend on the substrate, but not necessarily on the product of the reaction, or are affected by more than two variables. A simple example of the latter is a bi-substrate reaction that also depends on enzyme activity, a co-factor and possibly on inhibition or modulation by some other metabolite in the system. These types of processes have been modeled very successfully with GMA and S-systems. Between these two forms, the S-system representation has unique advantages for system identification from profiles, as was shown elsewhere [ 16 - 24 ] and will be discussed later in this article. In some sense, Karnaukhov and Karnaukhova [ 25 ] used a very simplified GMA system for biochemical system identification from dynamic data, in which all mono-substrate or bi-substrate reactions were of first order. This reduced the estimation to the optimization of rate constants, which the authors executed with an integral approach. The inference of a nonlinear model structure from experimental data is in principle a straightforward "inverse problem" that should be solvable with a regression method that minimizes the residual error between model and data. In practice, however, this process is everything but trivial ( cf. [ 26 ]) as it almost always requires an iterative search algorithm with all its numerical challenges, such as the existence of multiple local minima and failure to converge. Recent attempts of ameliorating this problem have included Bayesian inference methods [ 27 ], similarity measures and correlation [ 28 ], mutual information [ 29 ], and genetic algorithms [ 30 ]. An indication of the complexity of nonlinear estimation tasks and their solutions is a recent pathway identification involving an S-system with five variables, which was based on a genetic algorithm [ 21 ]. The algorithm successfully estimated the parameter values, but although the system under study was relatively small and noise free, each loop in the algorithm took 10 hours on a cluster of 1,040 Pentium III processors (933 MHz). It is quite obvious that such an approach cannot be scaled up to systems of dozens or hundreds of variables. Nonlinear estimation methods have been studied for a long time, and while computational and algorithmic efficiency will continue to increase, the combinatorial explosion of the number of parameters in systems with increasingly more variables mandates that identification tasks be made easier if larger systems are to be identified. One important possibility, which we pursue here, is to prime the iterative search with high-quality starting conditions that are better than naïve defaults. Clearly, if it is possible to identify parameter guesses that are relatively close to the true, yet unknown solution, the algorithm is less likely to get trapped in suboptimal local minima. We are proposing here to obtain such initial guesses by preprocessing the temporal profile data and fitting them preliminarily by straightforward multivariate linear regression. The underlying assumption is that the structural and regulatory connectivity of the network will be reflected, at least qualitatively, in the regression coefficients. D'haeseleer et al. [ 31 ] explored a similar approach for analyzing mRNA expression profiles, but could not validate their results because they lacked a mechanistic model of gene expression. Furthermore, because of the unique relationship between network structure and parameters in S-system models (see below), we will demonstrate that it is possible to translate the regression coefficients into constraints on the parameter values of an S-system model and thereby to reduce the parameter search space very dramatically. Several other groups have recently begun to target network identification tasks with rather diverse strategies. Chevalier et al. [ 32 ] and Diaz-Sierra and co-workers [ 33 , 34 ] proposed an identification approach that is similar to the one proposed here in some aspects, though not in others. These authors also used linearization of a nonlinear model, but based their estimation on measured time developments of the system immediately in response to a small perturbation. These measurements were used to estimate the Jacobian of the system at the steady state. In contrast to this focus on a single point, we are here using smoothed long-term time profiles and do not necessarily require system operation at a steady state. Also using linearization, Gardner et al. [ 35 ] recently proposed a method of network identification by multiple regression. However, they only considered steady-state measurements as opposed to temporal profiles. It is known from theoretical analyses ( e.g. , [ 15 , 36 ]) that different dynamical models may have the same steady state and that therefore steady-state information alone is not sufficient for the full characterization of a network. Mendes and Kell [ 37 ] used a neural network approach for an inverse problem in metabolic analysis, but their target system was very small and fully known in structure. Furthermore, their data consisted of a "large number of steady-state simulations", rather than the limited number of time traces on which our analysis is based. Chen et al. [ 38 ] used neural networks and cubic splines for smoothing data and identifying rate functions in otherwise linear mass-balance models. Methods The behavior of a biochemical network with n species can often be represented by a system of nonlinear differential equations of the generic form where X is a vector of variables X i , i = 1, ..., n , f is a vector of nonlinear functions f i , and μ is a set of parameters. If the mathematical structure of the functions f i is known, the identification of the network consists of the numerical estimation of μ . In addition to the challenges associated with nonlinear searches mentioned above, this estimation requires numerical integration of the differential equations in (1) at every step of the search. This is a costly process, requiring in excess of 95% of the total search time; if the differential equations are stiff, this percentage approaches 100% [ 39 ]. A simplification, which circumvents the problem of integration, consists of substituting the system of differential equations with decoupled algebraic equations by replacing the differentials on the left-hand side of Eq. (1) with estimated slopes [ 16 , 17 ]. Thus, if the system consists of n differential equations, and if measurements are available at N time points, the decoupling leads to n × N algebraic equations of the form It may be surprising at first that it is valid to decouple the tightly coupled system of nonlinear differential equations. Indeed, this is only justified for the purpose of parameter estimation, where the decoupled algebraic equations simply provide numerical values of variables (metabolites or proteins) and slopes at a finite set of discrete time points. The experimental measurements thus serve as the "data points," while the parameters μ ij are the "unknowns" that need to be identified. The quality of this decoupling approach is largely dependent on an efficient and accurate estimation of slopes from the data. Since the data must be expected to contain noise, this estimation is a priori not trivial. However, we have recently shown [ 23 , 39 ] that excellent estimates can be obtained by smoothing the data with an artificial neural network and computing the slopes from the smoothed traces (see Appendix for detail). Different Linearization Approaches The smoothing and decoupling approach reduces the cost of finding a numerical solution of the estimation task considerably. Nonetheless, algorithmic issues associated with local minima and the lack of convergence persist and can only be ameliorated with good initial guesses. To this end, we linearize the model f in Eq. (1) about one or several reference states. As long as the system stays close to the given reference state(s), this linearization is a suitable and valid approximation. We consider four options: (I) linearization of absolute deviations from steady state; (II) linearization of relative deviations from steady state; (III) piecewise linearization; and (IV) Lotka-Volterra linearization. Option (I) is based on deviations of the type z i = X i - X ir , where X ir denotes the value at a reference state of choice. If the reference state is chosen at a stable steady state, the first-order Taylor-approximation is given by where A is the n × n Jacobian with elements a ij = ( df i / dX j ) calculated at X r ( cf. [ 32 - 34 ]). If the reference state is not chosen at a steady state, the equation contains an additional constant term a i 0 , which is equal to f i ( X r ). For option II, we define a new variable u i = z i / X ir . At a steady state, this yields the linear system where A' is an n × n matrix in which a' ij = ( X jr / X ir )· a ij . A general concern regarding linearization procedures is the range of validity of sufficiently accurate representation, which is impossible to define generically. From an experimental point of view, the perturbations from steady state must be large enough to yield measurable responses. This may require that they be at the order of 10% or more. Depending on the nonlinearities in f , a perturbation of this magnitude may already lead to appreciable approximation errors. While this is a valid argument, it must be kept in mind that the purpose of this priming step is simply to detect the topological structure of connectivity and not necessarily to estimate precise values of interaction parameters. Simulations (see below) seem to indicate that this detection is indeed feasible in many cases, even if the deviations are relatively large. In order to overcome the limitation of small perturbations, a piecewise linear regression (option III) may be a superior alternative. In this case, we subdivide the dataset into appropriate time intervals and linearize the system around a chosen state within each subset. Most (or all) reference states are now different from the steady state, with the consequence that Eq. (3) has a constant term a i 0 , which is equal to f i ( X r ). The choice of subsets and operating points offers further options. In the analysis below, we use the locations of extreme values (maximum deviation from steady state) of the variables as the breakpoints between different subsets. Thus, a variable with a maximum and a later minimum has its time course divided into three subsets. The fourth alternative (option IV) is a Lotka-Volterra linearization. In a Lotka-Volterra model, the interaction between two species X i and X j is assumed to be proportional to the product X i X j [ 11 ]. Furthermore accounting for linear dependence on the variable of interest itself, the typical Lotka-Volterra equation for the rate of change in X i is The right-hand side of this nonlinear differential equation becomes linear if both sides are divided by X i , which is usually valid in biochemical and proteomic systems, because all quantities of interest are non-zero. Thus, the differentials are again replaced by estimated slopes, the slopes are divided by the corresponding variable at each time point, and fitting the nonlinear LV model to the time profiles becomes a matter of linear regression that does not even require the choice of a reference state. The quality of this procedure is thus solely dependent on the quality of the data and ability of the LV model to capture the dynamics of the observed network. It is known ( e.g. , [ 11 , 40 ]) that the mathematical structure of LV models is rich enough to model any nonlinearities, if sufficiently many equations are included. However, there is no general information about the quality of fit in particular modeling situations. Regression No matter which option is chosen, the next step of the analysis consists of subjecting all measured time traces to multivariate linear regression and solving for the regression coefficients ( i.e. , v ij 's and w i 's, or α ij 's). The response variable is the rate of change of a metabolite, while the predictors are the concentrations of each metabolite in the network. The different linearization models (I-IV) differ in the transformations of the original datasets, which are summarized in Table 1 . For example, the response variable of the linear model in Eq. (4) is given by y i = / X ir , and the predictor variables are transformed as x i = ( X i - X ir )/ X ir . Table 1 Transformation of data for regression analysis RESPONSE VARIABLE PREDICTOR VARIABLE A. Absolute deviation from a reference state y i = x i = X i - X ir B. Relative deviation from a reference state C. Lotka-Volterra system x i = X i We assume the general linear model is y = a i 0 + Σ( a ij x j ). The X i denote experimental time series data for metabolite i , while the slopes ( ) are estimated from the smooth output functions of the artificial neural network that had been trained on the experimental data. Subscript r denotes the value of the metabolite at a reference state. Linearization options I and II are included in transformations A and B respectively, assuming that the reference state is a steady state. For a piecewise linear linearization (option III), the data may be transformed following either A or B. The result of the regression is a matrix of coefficients that indicate to what degree a metabolite X j affects the dynamics (slope) of another metabolite X i . In particular, a coefficient that is zero or close to zero signals that there is no significant effect of X j on the slope of X i . By the same token, a coefficient that is significantly different from zero suggests the presence of an effect, and its value tends to reflect the strength and direction of the interaction. In either case, the coefficients computed from the linear regression provide valuable insight into the connectivity of the network. Furthermore, the estimated coefficients provide constraints on the parameter values of the desired nonlinear model f . Indeed, if f consists of an S-system model, the coefficients estimated from the regression can be converted into combinations of S-system parameters, as is demonstrated in the following theoretical section and illustrated later with a specific example. Relationships between Estimated Regression Coefficients and S-system Parameters The regression analysis yields coefficients that offer information on the connectivity of the network of interest. It also provides clues about the parameter values of the underlying nonlinear network model f in Eq. (1) if this model has the form of an S-system. To determine the relationships between the regression coefficients and the parameters of the S-system, it is convenient to work backwards by computing the different types of linearizations discussed before for the particular case of S-system models. This derivation is simply a matter of applying Taylor's theorem. In the S-system formalism, the rate of change in each pool (variable) is represented as the difference between influx into the pool and efflux out of the pool. Each term is approximated by a product of power-law functions, so that the generic form of any S-system model is where n is the number of state variables [ 13 , 14 ]. The exponents g ij and h ij are called kinetic orders and describe the quantitative effect of X j on the production or degradation of X i , respectively. A kinetic order of zero implies that the corresponding variable X j does not have an effect on X i . If the kinetic order is positive, the effect is activating or augmenting, and if it is negative, the effect is inhibiting. The multipliers α i and β i are rate constants that quantify the turnover rate of the production or degradation, respectively. If the Taylor linearization is performed at a steady state, the production term of the S-system model equals the degradation term. The absolute deviation of the first option, z i = X i - X is , where the subscript s denotes the value of the variable at steady state, then leads directly to where c ij = g ij - h ij , ( cf . [ 41 ]). The so-called F-factors F ij are always non-negative, while c ij may be either positive or negative depending on the relationship between X i and X j . A common scenario is that a variable X j influences either the production or degradation of variable X i , but not both. In this case, a positive (negative) c ij implies activation (inhibition) of production or inhibition (activation) of degradation. The special case of c ij = 0 permits two possible interpretations: 1) g ij = h ij = 0, which implies that X j has no effect on either production or degradation of X i ; or 2) g ij = h ij ≠ 0, which means that X j has the same effect on both production and degradation of X i . The former case is the more likely, but there are examples where the latter may be true as well, and this is indeed the case in the small gene network in Figure 1 . Figure 1 Test System. a) Gene network [42] used as test system for illustrating the proposed methods. Solid arrows represent material flow, while dashed arrows indicate regulatory signals that either activate (+) or inhibit (-) a process. The network contains two genes, Gene 1 and 2. X 1 is the mRNA produced from gene 1, X 2 is the enzyme for which the gene codes, and X 3 is an inducer protein catalyzed by X 2 . X 4 is the mRNA produced from Gene 2 and X 5 is a regulator protein for which the gene codes. Positive feedback from X 3 and negative feedback from X 5 are assumed in the production of mRNAs from the two genes. b) S-system model of the gene network, according to Hlavacek and Savageau [42] and Kikuchi et al. [21]. Comparing the expression in Eq. (6) with the linear regression results, one sees immediately that each coefficient a ij in Eq. (3) corresponds to the product of F ij and c ij : a ij = F ij c ij . (7) Thus, once the regression has been performed and the coefficients a ij have been estimated, the parameters of the corresponding S-system are constrained – though not fully determined – by Eq. (7). In particular, Eq. (7) does not allow a distinction between various combinations of g ij and h ij , as long as the two have the same difference. For instance, re-interpreting the regression coefficients as S-system parameters does not differentiate between the overall absence of effect of X j on X i ( g ij = h ij = 0) and the same effect of X j on both the production and degradation of X i ( g ij = h ij ≠ 0). This observation is related to the observation of Sorribas and Cascante [ 36 ] that steady-state measurements are insufficient for completely identifying an S-system model. Relative deviations from steady state, u i = ( X i - X is ) / X is , in option II, are assessed in an analogous fashion. In this case one obtains where c ij = g ij - h ij , [ 41 ]. Again, the F-factors F i are positive, while c ij may be either positive or negative. The piecewise linear model for an S-system is easily derived as well. It is given as where X jr denotes the value of the variable at the reference state. This case also includes the situation of a single approximation, which however is not necessarily based on a steady-state operating point. In the case of the Lotka-Volterra linearization, the correspondence between computed regression coefficients and S-system parameters is determined most easily by dividing the S-system equations by the corresponding X i and then linearizing around an operating point. The resulting expressions become especially simple if this point is chosen as the steady state. In this case, the relationship between the parameters of the LV system and the S-system are where c ij = g ij - h ij . Results We applied the methods described in the previous sections to simulated time profiles obtained from the small gene network in Figure 1a . Hlavacek and Savageau [ 42 ] modeled this network as an S-system with five differential equations (Figure 1b ), and Kikuchi et al. [ 21 ] used it recently for exploring computational features of their proposed structure identification algorithm. The benefit of working with a known model is that complete information is available about both its structure and parameter values. In particular, it is possible to perform any number of experiments and to produce data and slopes with predetermined noise levels, which is not typically possible with real data. For this analysis, we thus used simulated noise free "data," which allowed us to skip the neural network step of smoothing [ 23 , 39 ]. To generate time profiles, the system was implemented with the parameter values published by Hlavacek and Savageau [ 42 ], and as in the analysis of Kikuchi et al. [ 21 ], the model was initialized with various perturbations from steady state and numerically integrated over a sufficient time horizon to allow the system to return to the steady state. Preliminary Analysis Quasi as a pre-analysis, we examined the guidelines proposed by Vance et al. [ 8 ]. Indeed, the results show that many of these are applicable to the gene regulatory network. The order of the extrema ( i.e. , the maximum deviations from steady state) of the various variables both in time and size is in accordance with their "topological distance" from the perturbed variable, and variables not directly affected by the perturbed variable have zero initial slopes. As an example, the effect of a perturbation in X 3 is shown in Figure 2 . All variables increase in response, with variables X 1 and X 4 reaching their maximal deviation from steady state before X 2 and X 5 , suggesting that X 1 and X 4 precede X 2 and X 5 in the pathway. The value of the initial slope is different from zero for X 1 and X 4 , implying that these variables are directly affected by X 3 , whereas X 2 and X 5 have zero initial slopes suggesting that their responses are mediated through other variables. Figure 2 Dynamic response of the network after a perturbation in X 3 The response is shown as relative deviation from steady state. The guidelines proposed by Vance et al. [8] indicate that X 1 and X 4 precede X 2 and X 5 because they reach their maximum deviation earlier and the maximal values are larger than those of X 2 and X 5 . All variables respond in a positive manner, which implies either a mass transfer or positive modulation (activation). The system determined from this analysis is essentially the same as in Figure 1a. The only relationship missed is the effect of X 2 on the production and degradation of X 3 . Maximal information about the network is obtained when every variable is perturbed sequentially. Experimentally, such perturbations could be implemented with modern methods of RNA interference [ 43 ] or, for biotechnological purposes, in a chemostat [ 9 ]. In our model case, we can actually identify all kinetic orders that are zero in the original model, and this amounts to determining the connectivity of the pathway. The only relationship this analysis does not pick up is the effect of X 2 on X 3 . This result is not surprising, because the effect of X 2 is the same on both the production and degradation of X 3 , which leads to cancellation. It is noted that this analysis does not necessarily distinguish between transfer of mass and a positive modulation, because both result in a positive effect on a variable. In a realistic situation, biological knowledge may exclude one of the two options, as in this case, where modulation is the only possibility for the effect of X 3 on both X 1 and X 4 , because the former is a protein and the latter are RNA transcripts. For the mathematical model in the S-system form, this is not an issue, as both types of influence are included in the equations in the same way (as a positive kinetic order). Regression Analysis While Vance's method works well in this simple noise-free system, it is not scalable to larger and more complex systems. The next step of our analysis is therefore regression according to the four options presented above and with a number of simulated datasets of the gene network that differ in the variable to be perturbed and the size of the perturbation. Because the illustration here uses a known model and artificial data, it is easy to compute the true regression coefficients through differentiation of the S-system model. These coefficients can be used as a reference for comparisons with coefficients computed from the entire time traces, which mimics the estimation process for (smoothed) actual data. Options I, II and IV The results for three of the options (I, II and IV) can be summarized in the following three points, while the piecewise linear model will be discussed afterwards. (1) The network connectivity is reflected in the values of the regression coefficients. The values of the estimated coefficients provide strong indication as to which variables have a significant influence on the dynamics of other variables. A comparison between computed and estimated coefficients is shown in Table 2 for the linear model with relative deviations (option II, Eq. 8). Most of the coefficients that in reality are zero (for example a 12 and a 24 ) are not estimated as exactly zero, but their values are at least one order of magnitude smaller than the coefficients that are in actuality not zero. Table 2 also indicates that not all coefficients reflect the network correctly. The linear regression gives especially poor estimates for the coefficients associated with variables X 3 and X 4 . A possible explanation for X 3 is that the effect of X 2 is present in the non-linear system, but not in the linear system, and thus the behavior of X 3 must be explained by the other variables. Overall, of the 25 theoretically possible connections, 76% are correctly identified, while 24 % are false positives. Table 2 Comparison of computed and estimated coefficients Computed coefficients Estimated coefficients a10 0 0.0000 a11 -14.6780 -14.3647 a12 0 -0.1466 a13 7.3390 7.3414 a14 0 -0.2165 a15 -7.3390 -7.1723 a20 0 0.0000 a21 14.6780 14.6119 a22 -14.6780 -14.6540 a23 0 -0.0009 a24 0 0.0494 a25 0 -0.0309 a30 0 0.0000 a31 0 -2.3527 a32 0 1.3989 a33 -27.2517 -27.9204 a34 0 1.7491 a35 0 -0.9955 a40 0 0.0000 a41 0 2.0843 a42 0 -1.0925 a43 18.5664 19.0295 a44 -18.5664 -20.2112 a45 -9.2832 -8.3594 a50 0 0.0000 a51 0 -0.4026 a52 0 0.1384 a53 0 -0.0059 a54 18.5664 18.8987 a55 -18.5664 -18.7852 Regression coefficients for the small gene network (Figure 1), linearized about the steady state and based on relative deviations (option II). The first and second columns contain the computed and estimated regression coefficients, respectively. The regression coefficients a ij refer to the influence of variable j on variable i , while a i 0 is the constant term in each regression model. As the table indicates, the correspondence is good, except for the coefficients relating to X 3 and X 4 (see Text for explanation). The dataset consisted of 401 data points in the interval [0,4] and resulted from a simulation in which X 3 was perturbed at t = 0 to a value 5% above its steady-state value. (2) The different linear models give (qualitatively) the same results. A comparison of the results of the three models reveals that the values of the regression coefficients are very similar (see Table 3 ). The same applies to their signs. Most important, all models correctly identify the connections present in the gene network. They also equally infer the same incorrect relationships. As an example, consider the coefficients associated with X 4 : all models infer the net positive effect of X 3 and the net negative effect of both X 4 and X 5 . At the same time, they also suggest that X 1 and X 2 have a significant effect on the dynamics of X 4 . In reality, they do not directly influence X 4 (see Figure 1 ), and it may be that their indirect effect, which is mediated by X 3 , is causing the false positive result. Table 3 Comparison of the different linearization options (I, II and IV) I. Absolute deviation II. Relative deviation IV. Lotka-Volterra a10 0.0000 0.0000 14.4748 a11 -14.3647 -14.3647 -18.9581 a12 -0.1466 -0.1466 -0.6836 a13 5.3878 7.3414 7.3367 a14 -0.1712 -0.2165 -0.4694 a15 -5.6702 -7.1723 -7.4981 a20 0.0000 0.0000 0.0144 a21 14.6119 14.6119 19.8910 a22 -14.6540 -14.6540 -19.9277 a23 -0.0006 -0.0009 -0.0001 a24 0.0390 0.0494 0.0472 a25 -0.0245 -0.0309 -0.0335 a30 0.0000 0.0000 26.4020 a31 -3.2058 -2.3527 2.8725 a32 1.9062 1.3989 -1.7989 a33 -27.9204 -27.9204 -26.6164 a34 1.8842 1.7491 -1.5871 a35 -1.0724 -0.9955 0.9692 a40 0.0000 0.0000 8.0270 a41 2.6365 2.0843 6.3364 a42 -1.3820 -1.0925 -4.1579 a43 17.6654 19.0295 19.0005 a44 -20.2112 -20.2112 -23.1319 a45 -8.3594 -8.3594 -7.7047 a50 0.0000 0.0000 0.0869 a51 -0.5092 -0.4026 -0.6617 a52 0.1751 0.1384 0.4441 a53 -0.0055 -0.0059 -0.0003 a54 18.8987 18.8987 20.2939 a55 -18.7852 -18.7852 -20.2152 Estimated coefficients for three of the linearization approaches: absolute deviation from steady state (left column), relative deviation from steady state (center column) and Lotka-Volterra linearization (right column). The dataset consisted of 401 data points in the interval [0,4] and resulted from a simulation in which X 3 was perturbed at t = 0 to a value 5% above its steady-state value. (3) The greater the perturbation, the less accurate is the estimation of the regression coefficients. The deviation between the estimated and computed coefficients increases as the size of the perturbation increases (see Table 4 ). For the models obtained by linearizing about the steady state (Eqs. (6) and (8)), this is an expected result, as the Taylor-expansion only gives a valid approximation close to steady state. For these systems, "close" may correspond to a perturbation of less than 5–10% with respect to the steady-state value. Nonetheless, the greater perturbations still give a relatively good picture in terms of the connectivity of the system. For a 5% perturbation, the fraction of correctly identified connections is 76% and for a two-fold perturbation it is still 64 %. Perturbations of more than 5–10 % of the steady state also cause problems for the Lotka-Volterra model, from which one might have expected a higher tolerance as the linearization is independent of a reference state. It seems that the dynamics of the true system in our particular example is about equally well modeled by the nonlinear LV-model as by the linear models. Table 4 The effect of the size of the perturbation Computed 5 % 10 % 50 % 200 % a10 0 0.0000 0.0000 0.0001 0.0008 a11 -14.6780 -14.3647 -14.1817 -13.1496 -11.3439 a12 0 -0.1466 -0.1429 -0.0671 0.5735 a13 7.3390 7.3414 7.3438 7.3598 7.3735 a14 0 -0.2165 -0.3673 -1.2462 -2.7619 a15 -7.3390 -7.1723 -7.0780 -6.4846 -5.2501 a20 0 0.0000 0.0000 0.0000 -0.0003 a21 14.6780 14.6119 14.5748 14.4207 14.5029 a22 -14.6780 -14.6540 -14.6623 -14.7503 -15.1862 a23 0 -0.0009 -0.0016 -0.0054 -0.0070 a24 0 0.0494 0.0839 0.2494 0.3462 a25 0 -0.0309 -0.0464 -0.1119 -0.0951 a30 0 0.0000 0.0000 0.0004 0.0038 a31 0 -2.3527 -4.5412 -18.2307 -46.8953 a32 0 1.3989 2.6336 9.8422 24.4004 a33 -27.2517 -27.9204 -28.5955 -34.0204 -54.4047 a34 0 1.7491 3.4009 14.0961 39.3252 a35 0 -0.9955 -1.8949 -7.0627 -15.4759 a40 0 0.0000 0.0000 -0.0001 0.0001 a41 0 2.0843 3.7814 14.7316 41.5863 a42 0 -1.0925 -1.7693 -5.5766 -13.2688 a43 18.5664 19.0295 19.4964 23.2397 37.1866 a44 -18.5664 -20.2112 -21.6608 -31.4631 -58.1065 a45 -9.2832 -8.3594 -7.6404 -3.2226 6.5808 a50 0 0.0000 0.0000 -0.0001 -0.0015 a51 0 -0.4026 -0.6581 -2.5848 -10.1097 a52 0 0.1384 0.0830 -0.1317 0.1582 a53 0 -0.0059 -0.0110 -0.0435 -0.0879 a54 18.5664 18.8987 19.1602 21.0620 27.2722 a55 -18.5664 -18.7852 -18.9201 -20.0013 -24.0836 Overall, the estimated coefficients deviate more strongly from the corresponding computed values as the perturbation increases. However, there are substantial differences between variables. The coefficients associated with variable X 2 , for example, are hardly influenced, while the coefficients associated with X 3 are strongly affected. Overall, the method seems to produce the best results for perturbation up to 10%. The datasets for the regression consisted of 401 data points in the interval [0,4] and the method of linearization was option II. Option III The piecewise linear model was obtained by dividing the whole dataset into three smaller subsets for each variable. The first interval contained the data points from t = 0 to the time of the first extreme value for a given variable (in this case a maximum for all variables). For the perturbed variable (having its first extreme value at t = 0) the first limit point was given by the smallest of the limit points of the other variables. The second interval contained the data points from the first to the second extreme value (a minimum), while the third interval included the remaining data points. The midpoint of each interval was taken to be the reference state. The result of the piecewise linear regression for a 5% deviation in X 3 is given in Table 5 . The first subset does not reflect the interactions of the system especially well, whereas the other two subsets correctly classify 88% and 96%, respectively, of the true connections in the network. It is worth noting that the coefficients associated with X 3 in the two last subsets reflect the variable's connectivity to a much greater extent than the other linearization approaches. As the reference state is different from the steady state, the effect of X 2 is present in the linear system as well, and thus there is no compensation through the other variables. Another benefit is that the piecewise model tolerates larger perturbations. Even for a two-fold perturbation, the fraction of correctly identified coefficients in the last subset is 84%. Table 5 Results for piecewise linear regression Interval 1 Interval 2 Interval 3 a10 0.1315 -0.0419 0.0000 a11 -42.3980 -14.1738 -14.5490 a12 0.0000 -0.8010 -0.0464 a13 8.9105 7.3653 7.6299 a14 12.7757 -0.3340 -0.1386 a15 -3.3476 -6.9121 -7.2940 a20 0.0567 -0.0197 0.0000 a21 -1.1939 14.4913 14.6792 a22 -32.3300 -14.5116 -14.6784 a23 0.6133 0.0057 -0.0205 a24 7.0917 0.1016 -0.0018 a25 7.9313 -0.1047 0.0067 a30 -0.7858 -0.0181 0.0000 a31 -130.3724 -0.2358 0.0021 a32 0.0000 0.3616 -0.0007 a33 -20.7724 -27.6129 -27.2551 a34 62.1525 0.3496 -0.0027 a35 19.1470 -0.1984 0.0006 a40 0.3164 -0.0709 0.0000 a41 -13.6819 1.1412 -0.0115 a42 0.0000 -2.1478 0.0015 a43 19.8295 18.8534 18.6927 a44 -13.3654 -19.5811 -18.5494 a45 -7.2135 -8.0985 -9.2792 a50 0.1617 -0.0393 0.0000 a51 -149.5199 -0.8195 0.0250 a52 -160.3341 0.8175 -0.0074 a53 5.7537 0.0580 -0.0304 a54 85.3050 19.0394 18.5356 a55 53.9745 -19.1183 -18.5623 The complete dataset is divided into three subsets for each variable, where the first and second extreme values serve as breakpoints. The datasets for the regression consisted of 401 data points in the interval [0,4] and resulted from a simulation in which X 3 was perturbed at t = 0 to a value 5% above its steady-state value. Degree of Similarity as a Measure of Reliability If we compare the results of all four linearized models, the degree of similarity may provide a measure of how reliable the estimated coefficients are, assuming that an interaction identified in all models is more reliable than an interaction identified in only one or few of the models. Considering the piecewise linear model as three models, yielding a total of 6 models from one dataset, one may thus determine the most likely connectivity for the small gene network. The result is presented in Table 6 . Of the 25 possible connections, 12 were identified correctly in all models, either as being positive, negative or non-existent, while an additional 6 connections were correctly identified in either 4 or 5 of the six models. For these six, one of the models misidentifying the type of connection was the first subset of the piecewise linear approximation, which does not reflect the connectivity of the network especially well, as was shown in Table 5 . It is also worth noting that only one of the interactions associated with X 3 is identified correctly from comparing the six models. The classification of the remaining four connections varies greatly among the different models, and it is therefore impossible to deduce a type of interaction with sufficient reliability. Table 6 Collective inference of the gene network based on results from all linearizations X 1 X 2 X 3 X 4 X 5 X1 - (100 %) 0 (67 %) + (100 %) 0 (83 %) - (100 %) X2 + (100 %) - (100 %) 0 (100 %) 0 (83 %) 0 (83 %) X3 ? ? - (100 %) ? ? X4 + (67 %) - (67 %) + (100 %) - (100 %) - (100%) X5 - (83 %) 0 (83 %) 0 (83 %) + (100 %) - (100 %) Each minus sign implies a negative influence; a plus sign implies a positive influence, while zero implies no influence. Bold symbols denote correctly identified interactions, and numbers in parentheses give the fraction of models that suggested positive identification. Question marks imply that no type of interaction was identified in more than 50% of the models. Constraining the Parameter Values In addition to reflecting the connectivity, the coefficients provide likely parameter ranges or likely constraints on parameter values of the true model. As an example, consider variable X 1 . Table 6 indicates that the variables having a significant effect are X 1 , X 3 and X 5 . If so, the linear model in Eq. (8) suggests the following: where and the regression coefficients ( a ij ) are taken from the model in Eq. (4). The values of the variables at steady state are known. Because the kinetic orders may be positive or negative and the c ij may result from different combinations of g ij 's and h ij 's, it is not possible to deduce directly which exponent is greater than the other. However, in many cases one may have additional information on the system, which further limits the degrees of freedom ( e.g. , [ 23 ]). In addition, the steady-state equation must be satisfied and provides yet another constraint. Discussion Identifying the structure of metabolic or proteomic networks from time series is a task that most likely will require large, parallelized computational effort. The search space for the algorithms is typically of high dimension and unknown structure and very often contains numerous local minima. This generic and frequent problem may be ameliorated if the search algorithm is provided with good initial guesses and/or constraints on admissible parameter values. Here, we have shown that linear regression may provide such information directly from the types of data to be expected from future experiments. For illustrative purposes, we used artificial data from a known network, but all methods are directly applicable to actual profile data and scaleable to large systems. The coefficients estimated from the different regressions reflect the effect of one variable on another surprisingly well and thus provide a simple fashion of prescreening the connectivity of the network. In addition, the estimated coefficients provide constraints on the parameter values, if the alleged nonlinear model has the form of an S-system. To explore the pre-assessment of data as fully as feasible, we studied four linearization strategies: using an absolute deviation from steady state; a relative deviation from steady state; piecewise linearization; and Lotka-Volterra linearization. Interestingly, all models gave qualitatively similar results for the analyzed example, and this degree of similarity may provide a measure of how reliable the identified connections are. Specifically, of the 25 possible connections in the small gene network studied, 19 were identified correctly in at least 83 % of the regression analyses. A concern of any linearization approach is the validity of the linear approximation. However, as long as the perturbation from steady state remains relatively small, the estimated linear model is likely to be a good fit of the actual nonlinear model, at least qualitatively. This limitation may furthermore be alleviated by fitting the profile data in a piecewise linear fashion. As most reference states in this case are different from the steady state, this strategy has the added benefit that more of the true relationships within the nonlinear model are likely to be preserved. As an alternative, one could explore the performance of the so-called "log-linear" model, which is linear in log-transformed variables [ 44 ]. The Lotka-Volterra linearization did not perform as well as expected with regard to large perturbations. This may be a consequence of the particular example, which was originally in S-system form rather than in a form more conducive to the LV structure, which emphasizes interactions between pairs of variables. Since it is easy to perform the LV analysis along with the other regressions discussed here, it may be advisable to execute all four analyses. The illustrative model used for testing the procedure consisted of a relatively small system with only five variables and relatively few interactions. Nonetheless, one should recall that this very system required substantial identification time in a direct estimation approach [ 21 ]. In order to check how scaleable the results of the proposed linearization method are, the method should be tested on larger systems. Some preliminary analyses suggest that the method works well, but that the likelihood of misidentified connections may grow with the size of the system, as one might expect. At the same time, experience with actual biological networks, for instance in ecology and metabolism, suggests that larger systems are often more robust in a sense that they do not deviate as much from the steady state as smaller systems. If this trend holds in general, the linearization becomes a more accurate representation as larger networks are being investigated and the proposed methods will therefore yield more reliable initial indicators of network connectivity. Independent of these issues, the methods proposed here will very likely be more valuable for bigger systems than other methods that are presently available, because without some preprocessing of the data and effectively priming the search, as it is proposed here, the combinatorial explosion will most certainly gain the upper hand eventually. Competing interests None declared. Authors' contributions SRV performed the analysis and prepared the results. JS developed and implemented the neural network for computation of slopes. EOV developed the basic ideas and directed the project. Appendix It was recently shown that good parameter estimates of S-system models from metabolic profiles might be obtained by training an artificial neural network (ANN) directly with the experimental data. The result of this training is a so-called universal function which smoothes the data with predetermined precision and also allows the straightforward computation of slopes that can be used for network identification purposes. This appendix briefly outlines the procedure; details can be found in Almeida [ 45 ] and Voit and Almeida [ 24 ]. The ANN consists of three layers; one input layer, one hidden layer and one output layer. The input layer consists of the measurement time points, the hidden layer has no direct biological interpretation, and the output layer contains the metabolite concentrations or levels of protein expression that the ANN is being trained to represent. The node values of the ANN in the hidden layer are calculated from a linear combination of input values with different weights according to a multivariate logistic equation. Similarly, the values of the output layer are determined from linear combinations of the hidden node values with different weights, again using a multivariate logistic function. It is known that this type of nested multivariate logistic function has unlimited flexibility in modeling nonlinearities [ 46 ]. Noise and sample size do not have a devastating effect on the results of the ANN-method, as long as the true trend is well represented [ 39 ]. In fact, the ANN approach provides an unlimited number of sampling points, as values at any desired time points may be estimated from the universal output function. Finally, the calculation of the slopes of the smooth output functions is mathematically unwieldy, but computationally straightforward. The use of the entire time course is in stark contrast to earlier methods of parameter estimation and structure identification in metabolic networks. Mendes and Kell [ 37 ] applied their ANN-based parameter estimation to steady-state data, while we are using time profiles. Chevalier and co-workers [ 32 ] first fitted the nonlinear solution with a linear model (as shown in Eq. 3), expressed this solution in terms of eigenvectors and eigenvalues, and then obtained the slopes by numerical differentiation. Sorribas et al. [ 47 ] suggested a variation on this approach, based on discretizing the solution of Eq. (3) as z ( t k + 1 ) = z ( t k )exp( h · A ), (A1) where h is the step size. The problem is thereby reduced to a mulitilinear regression in which the matrix Φ = exp( h · A ) is the output. Instead of estimating the slopes, they obtain the Jacobian directly by expanded in its Taylor-series. This approach yields a faster convergence to the elements of the Jacobian than the one suggested by Chevalier et al . [ 32 ], but the regression of Eq. (A1) is very sensitive to noise and missing data points. Our approach takes advantage of the entire time course and is therefore less sensitive to the particularities of assessing a system at a single point. The ANN itself does not provide much insight, because it is strictly a black-box model, but it is a valuable tool for controlling problems that are germane to any data analysis, namely noise, measurement inaccuracies, and missing data. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC522751.xml |
520813 | PATTERNFINDER: combined analysis of DNA regulatory sequences and double-helix stability | Background Regulatory regions that function in DNA replication and gene transcription contain specific sequences that bind proteins as well as less-specific sequences in which the double helix is often easy to unwind. Progress towards predicting and characterizing regulatory regions could be accelerated by computer programs that perform a combined analysis of specific sequences and DNA unwinding properties. Results Here we present PATTERNFINDER, a web server that searches DNA sequences for matches to specific or flexible patterns, and analyzes DNA helical stability. A batch mode of the program generates a tabular map of matches to multiple, different patterns. Regions flanking pattern matches can be targeted for helical stability analysis to identify sequences with a minimum free energy for DNA unwinding. As an example application, we analyzed a regulatory region of the human c-myc proto-oncogene consisting of a single-strand-specific protein binding site within a DNA region that unwinds in vivo . The predicted region of minimal helical stability overlapped both the protein binding site and the unwound DNA region identified experimentally. Conclusions The PATTERNFINDER web server permits localization of known functional elements or landmarks in DNA sequences as well as prediction of potential new elements. Batch analysis of multiple patterns facilitates the annotation of DNA regulatory regions. Identifying specific pattern matches linked to DNA with low helical stability is useful in characterizing regulatory regions for transcription, replication and other processes and may predict functional DNA unwinding elements. PATTERNFINDER can be accessed freely at: | Background Regulatory regions in DNA are comprised of multiple functional elements that act in cis to control transcription, replication and other biological processes. Types of cis -acting DNA elements include unique sequences that bind specific proteins, spacer elements that provide a proper distance for interaction among protein binding sites, and structural elements that determine the flexibility of the DNA sequence. The structure of DNA is crucial to genetic regulation. The double helix needs to be locally unwound at start sites for DNA replication [ 1 ]. Additionally, DNA unwinding, flexibility and topology are important in regulating gene transcription and other processes [ 2 ]. Little is known about functional elements in most gene regulatory regions. Annotation of regulatory regions lags far behind the annotation of features of coding regions in DNA sequence databases. Best characterized are specific sequences that bind known proteins in vitro and whose functional importance has been determined by mutational analysis in vivo . Not as well characterized, but also important, are less-specific sequences that play roles in determining DNA structure and flexibility. DNA in certain regulatory sequences has a low helical stability as revealed by hypersensitivity to single-strand-specific nucleases and by stable DNA unwinding seen in plasmid topoisomers [ 3 , 4 ]. Helical stability minima computed using thermodynamic properties of nearest-neighbor nucleotides correctly predict the locations and hierarchy of the nuclease-hypersensitive sites [ 5 ]. Mutational analysis has revealed a functional region of low helical stability, called a DNA unwinding element, in replication origins in several species [ 6 - 9 ]. Some regulatory sequences with a low helical stability have been demonstrated to adopt an unwound DNA structure inside cells [ 10 , 11 ]. Low helical stability of DNA is of general importance since it is a feature of regulatory sequences involved in a variety of cellular processes including gene transcription, replication, nuclear matrix attachment and DNA repeat instability [ 6 , 10 , 12 - 14 ]. Progress towards characterizing and predicting regulatory regions could be accelerated by the availability of computer programs that perform a combined analysis of DNA sequence patterns and DNA unwinding properties. Here we present PATTERNFINDER, an easy to use web server that combines the search for specific or flexible sequence patterns with an analysis of DNA helical stability. The output of a DNA pattern search can be linked to THERMOCALC, a new program which ranks the helical stabilities of pattern matches, and an enhanced version of WEB-THERMODYN [ 15 ], which profiles the helical stability of individual matches and finds the most easily-unwound sequence. Below is information on using the PATTERNFINDER web server as well as an example analysis of the multi-functional regulatory region of a human proto-oncogene, c-myc. Results PATTERNFINDER Web Server Web servers offer advantages to the user including platform-independent software that requires no installation and a friendly browser interface for data entry and display. The PATTERNFINDER web server searches DNA sequences for matches to specific or flexible patterns, and analyzes DNA helical stability within or flanking the matches. Examples of specific patterns include sequences known to be recognized by particular proteins or enzymes, or sequences complementary to oligonucleotide primers. Flexible patterns include, for example, consensus sequences containing ambiguous nucleotides and unspecified nucleotides (N's), or multiple specific patterns separated by a variable number of N's, or simple sequences that are repeated a variable number of times. The DNA pattern used in the search can be comprised of A, G, C, T, ambiguous nucleotides (IUPAC-IUB nomenclature), and N's. Tables listing abbreviations of ambiguous nucleotides (e.g., W = A or T) and annotations for patterns using N's and sequence repeats are provided on the home page of the web server [ 16 ]. Mismatches are not permitted. Including N's in a pattern query is useful for retrieving sequences adjacent to a pattern match or known landmark (e.g., N{100}GAATTC = 100 bp sequence 5' to GAATTC) for further analysis. N's can also be used to fix or vary spacing between patterns, as indicated on the home page. The maximum pattern span entry must include the total number of nucleotides in the pattern, including repeats and N's (span = 106 in the example above). The span entry can not exceed the total length of the DNA sequence or region analyzed. Users input the name of the DNA molecule, the shape (linear or circular) and the nucleotide sequence. The sequence can be uploaded from a computer file (≤40 kb) in a various user-selected formats (ASCII text, Genbank, Fasta). Alternatively, the sequence can be pasted (≤30 kb) or typed into the DNA Sequence Query window of the browser. Acceptable characters are A, G, C, and T. Integers used for sequence numbering are permitted. Under the "Analysis Parameters" the user can select to search the whole DNA molecule or a part of the molecule from one position to another. Both DNA strands are searched by default in order to find matches to asymmetric patterns. If desired, the search can be restricted to only the upper (+, input) or lower (-, complementary) strand by selecting the appropriate checkbox. The output displays the molecule name, size in bp, and size of the region analyzed, and the DNA sequence of the upper and lower strands. Note that all DNA sequences in the output are displayed 5'->3' regardless of strand. This is useful for creating sequence alignments. The total number of hits and the pattern query are displayed. Tabulated are the position, strand (+ or -) and sequence of all pattern matches. The data are also output to an ASCII text file for printing, archiving and for any further processing (e.g., in a spreadsheet). A BATCH version of PATTERNFINDER is included to search simultaneously for multiple patterns in a DNA sequence. Entries are pasted or typed into the BATCH query window, one per line. Entries take the form of "Pattern name, Pattern expression, Maximum span". A table of pattern names and expressions that were entered is included in the output. The tabular output of hits is similar to that for PATTERNFINDER (above) except that it also includes the names of patterns that are hit as well as those that are not hit. The ASCII output provides a tabular map of the positions and strands of different pattern matches found in the DNA sequence. In addition to flexible sequence patterns, BATCH lists can include a variety of specific DNA elements and landmarks such as protein binding sequences, restriction sites and oligonucleotide primers. Low helical stability of DNA is often a property of regulatory sequences [ 3 , 5 , 6 ]. A unique feature of PATTERNFINDER is that the output can serve as input for analysis of double-helix stability within or flanking the pattern matches. Selecting the appropriate checkbox on the input page enables THERMOCALC or WEB-THERMODYN to process the output of the pattern search. THERMOCALC is a new program that analyzes multiple DNA sequences in a user-selected, fixed window and ranks the free energy values. WEB-THERMODYN performs a sliding-window analysis of a DNA sequence to profile the helical stability and to identify the most easily-unwound sequence (free energy minimum). The utility of the published WEB-THERMODYN program [ 15 ] has been enhanced. The results of a PATTERNFINDER sequence search are directly output into an new input page for WEB-THERMODYN that accomodates multiple sequence entries, permiting the facile and rapid analysis of multiple pattern hits. The algorithm used to calculate free energy (ΔG) from thermodynamic parameters of nearest-neighbor nucleotides is described on the web server [ 17 ]. Briefly, the standard entropy and enthalpy values for each of the ten possible nearest-neighbor nucleotide interactions present in a DNA sequence are individually summed and then used to calculate the free energy using the equations previously described [ 9 ]. The WEB-THERMODYN program has also been upgraded to include the unified thermodynamic data set of SantaLucia [ 18 ]. This is now the current default data set since it represents a consensus agreement among six independent data sets and has been found to rank the free energies of DNA sequences even more accurately than the previous data set [ 18 ]. A drop down menu permits selection of the current default or the previous data set. Default values for temperature and salt concentration [ 3 ] are present on the input page and these values can be altered by the user if desired. The input value for the start position is used by THERMOCALC to calculate ΔG from that position to the end of the sequence hit. Input values for Start Position, Step Size, Window Size and Number of Markers at minimum energy windows are used by WEB-THERMODYN, which also provides links to the DNA sequences at energy minima and a graphical profile of helical stability. Enabling WEB-THERMODYN also permits further adjustment or variations of the parameters for helical stability analysis on the PATTERNFINDER output page. PATTERNFINDER was designed to be fast and user friendly. No password restriction or registration is required. All entries are error checked before processing and, if errors exist, the user is prompted with specific suggestions to correct the entries. The output is returned directly to the browser in real time, as opposed to a return via e-mail at a later time. The home page of the web server provides a DEMO link [ 19 ] containing sequence and pattern files relevant to the application that follows. PATTERNFINDER analysis of the regulatory region of the human c-myc gene The 5' regulatory region of the c-myc gene resides in the first 2500 bp of an ~11 kb DNA sequence. The sequence contains multiple elements that regulate transcription and replication [ 10 , 12 ], but the locations of the DNA elements are not yet annotated in public databases. The far upstream sequence element (FUSE) acts in cis to stimulate c-myc promoter activity and a 42 bp sequence becomes single-stranded in vivo (HeLa cells) when the gene is actively transcribed [ 10 ]. The single-stranded region is located primarily 3' to a specific Ava I restriction enzyme site. PATTERNFINDER was used to search for specific Ava I sites and any ("n") 36 bp sequences in a 42 bp segment (pattern: CCCGAGn{36}; span = 42) with THERMOCALC enabled to rank the DNA helical stabilities of the segments. The search was restricted to the regulatory region from positions 1 to 2500 (entered under the "Analysis Parameters"). The output is shown in Fig. 1A . The locations and strands of three Ava I sites found and the helical stability ranks (free energy, kcal/mol) of the 42 bp segments are displayed. The site with rank 1 has the lowest free energy and begins at position 789 on the + strand. As shown below, this predicted region of low helical stability contains the single-stranded DNA region identified experimentally in the FUSE. To map the locations of other DNA elements in the 5' regulatory region, the BATCH version of PATTERNFINDER was used to search simultaneously for multiple, specific sequences. The patterns included two separate sequences that interact with the FUSE binding protein (FBP) in domains 3 and 4 [ 20 ], the Ava I site, and sequences of the -10 regions at the P1 and P2 promoters for c-myc transcription [ 10 ]. The BATCH output in Fig. 1B shows the precise locations and strands of the DNA elements in relation to the Ava I sites, providing an informative tabular map of functional elements and landmarks in the regulatory region. In conjunction with PATTERNFINDER, WEB-THERMODYN was used to profile the DNA helical stability of all 42 bp windows in a ~400 bp region containing the binding site for FBP domain 3 at the center. The pattern query used was n{200}TAAAAAATn{200} and the span = 408. This query finds the complementary sequence (+ strand) to the FBP_3 site (ATTTTTTA, - strand) and retrieves the 200 nt sequences 5' and 3' for the WEB-THERMODYN analysis (Step Size = 1, Window Size = 42, Number of Markers = 1[energy minima]). Fig. 1C shows that the sequence with the minimum free energy (ΔG Min) in the 408 bp region analyzed overlaps most of the single-stranded DNA region detected experimentally at FUSE in vivo (FUSE ssDNA), reflecting a reduced helical stability intrinsic to DNA at FUSE. A separate WEB-THERMODYN analysis of the entire 2500 bp regulatory region identified the identical sequence as the ΔG Min, indicating that the low helical stability at FUSE is unique within the entire 5' regulatory region. The location of the ΔG Min sequence (+ strand shown in Fig. 1C ) also overlaps the single-stranded DNA binding sites for FBP_3 and FBP_4 present in the -strand. The values of ΔG Min and ΔG FUSE ssDNA are well below the average ΔG (29.44 kcal/mol) for all 42 bp windows for the entire 2500 bp region. The predicted DNA sequence with the lowest helical stability in the 5' regulatory region contains the single-stranded DNA region detected experimentally at FUSE [ 10 ]. Discussion The PATTERNFINDER web server provides a convenient means to search DNA regulatory regions for specific or flexible sequence patterns and to identify flanking sequences that are easy to unwind. Specific sequence searches permit localization of known protein binding sites and sequence landmarks such as restriction sites and oligonucleotide primers. The capacity to perform BATCH analysis of multiple patterns and generate accurate tabular maps facilitates the annotation of DNA regulatory regions. The latter lags far behind the annotation of protein coding regions in public sequence databases, and individual laboratories must usually draw on their own annotation resources in order to design experiments. The utility of PATTERNFINDER in annotation of known DNA elements can facilitate the design of experiments to further characterize regulatory regions. New DNA elements with potential functions can be predicted using flexible patterns such as consensus sequences containing ambiguous nucleotides and N's as well as using multiple motifs with fixed or variable spacing. Sequences found are displayed 5'->3' regardless of the DNA strand which is useful for creating sequence alignments for position weight matrices and for identifying evolutionary conserved sequences. More sophisticated pattern match and discovery methods exist ([ 21 ], and references therein) and advanced versions of PATTERNFINDER that permit base mismatches and utilize weight matrices are under development. A strength of the current version of PATTERNFINDER is the capacity to identify pattern matches that are linked to DNA sequences of low helical stability. Such a combined search for two different types of DNA elements can lead to predictions of greater specificity than can be obtained by searching for either element alone and may help predict functional DNA unwinding elements associated with specific protein binding sites. The availability of PATTERNFINDER will hopefully stimulate experiments to verify the biological function of predicted DNA elements. The ability to find DNA sequences and to target the flanking regions for helical stability analysis is a unique feature of PATTERNFINDER. This feature is useful in characterizing regulatory regions for gene transcription and DNA replication which require specific protein-binding sequences as well as less-specific flanking sequences in which the double helix is easy to unwind. Helical stability is ranked by the free energy value beginning with the most easily-unwound sequence by enabling a new program, THERMOCALC. Helical stability is profiled to identify free energy minima by enabling an enhanced version of the previously described WEB-THERMODYN program [ 15 ]. As shown in the Results for the transcription regulatory region of the human proto-oncogene, c-myc, the predicted region of minimum helical stability overlaps significantly the FUSE single-stranded DNA region identified experimentally in vivo [ 10 ]. The predicted region of minimum helical stability also overlaps the protein binding sites for FBP domains 3 and 4 [ 20 ]. FUSE is an example of a DNA unwinding element that appears to function through both intrinsic helical instability and binding a protein, FBP, a single-strand-specific DNA binding protein with a non-processive helicase activity [ 10 , 22 ]. Our analysis of helical stability is general and makes no assumptions about the DNA unwinding mechanism. DNA opening at FUSE has been proposed to be induced by torsional stress generated by transcription of the c-myc gene [ 10 ]. Consistent with a role for torsional stress, an independent computer analysis predicted a high probability of DNA opening at FUSE at specific levels of negative supercoiling [ 23 ]. WEB-THERMODYN analysis predicted an overlapping sequence as the helical stability minimum of the c-myc regulatory region (Fig. 1C ). When the DNA opening mechanism is initiated by torsional stress alone, helical stability analysis predicts the site that corresponds to the DNA sequence of lowest helical stability identified experimentally in negatively supercoiled DNA in vitro [ 3 , 5 ]. When the DNA opening mechanism requires prior binding of proteins to duplex DNA, as is the case for replication origins (see below), functional DNA opening in a cell can occur at a low helical stability sequence that does not necessarily correspond to the lowest-stability site that opens in negatively supercoiled DNA in vitro [ 24 ]. In the latter case, consideration of specific protein binding sequences in addition to the helical stability is required, as is done in PATTERNFINDER with THERMOCALC or WEB-THERMODYN enabled. Our computer analysis described here and that of He et al. [ 23 ] provide useful and complementary information about DNA regulatory sequences, and both analyses could be employed to take full advantage of their individual strengths. PATTERNFINDER will also have direct application in the further characterization of DNA replication origins, which are comprised of origin recognition elements, less-specific sequences including a DNA unwinding element, and additional elements such as transcription factor binding sites [ 1 , 6 , 7 , 11 , 25 , 26 ]. Interestingly, the transcription regulatory region of the c-myc gene also contains a replication origin, and a low helical stability region in the vicinity of FUSE has been suggested to function as a DNA unwinding element that facilitates replication initiation [ 12 ]. A functional role in initiation of c-myc replication for FBP, the single-strand DNA binding protein that binds FUSE and has a non-processive helicase activity [ 10 , 22 ], is not known. The function of several well-characterized replication origins requires an initiator protein complex that recognizes double-stranded DNA [ 1 , 11 , 25 ]. Also important is a DNA unwinding element [ 7 ], which must be properly spaced and oriented relative to the sequences that bind initiator proteins in certain origins [ 6 , 9 ]. PATTERNFINDER is capable of searching DNA sequences for all of the features of replication origins: specific sequences, less-specific sequences including those that are easily-unwound, and proper orientation and spacing between multiple types of sequences. Finally, PATTERNFINDER is likely to have applications in studying processes in addition to replication and transcription, such as nuclear matrix attachment and DNA repeat instability, which also involve specific DNA sequences and a region of low helical stability [ 13 , 14 ]. Conclusions The PATTERNFINDER web server will be useful in annotating, predicting and characterizing regulatory regions for replication, transcription and other processes that require specific or less specific sequences recognized by particular proteins and additional sequences in which the double-helix is unstable and functions in localized DNA unwinding. Methods The PATTERNFINDER program was written in Practical Extraction and Report Language (PERL) and HyperText Markup Language (HTML) and uses the Common Gateway Interface (CGI) for input and output to a web browser. The DNA sequence of the human c-myc gene was obtained from GenBank (accession number: X00364). The average ΔG for all windows was determined by analysis of the WEB-THERMODYN output using spreadsheet software. Authors' Contributions YH wrote the program code for PATTERNFINDER and established a web site. DK served as scientific advisor and participated in the program design and development. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC520813.xml |
546200 | Characterization and performance of a toluene-degrading biofilm developed on pumice stones | Background Hydrocarbon-degrading biofilms in the treatment of contaminated groundwaters have received increasing attention due to the role played in the so-called "biobarriers". These are bioremediation systems in which a microbial consortium adherent to a solid support is placed across the flow of a contaminated plume, thus promoting biodegradation of the pollutant. Results A microbial consortium adherent to pumice granules (biofilm) developed from a toluene-enriched microflora in a mini-scale system, following continuous supply of a mineral medium containing toluene, over a 12-month period. Observation by scanning electron microscopy, together with quantification of the biomass attached to pumice, evidenced the presence of abundant exopolymeric material surrounding the cells in the biofilm. Toluene removal monitored during 12-month operation, reached 99%. Identification of the species, based on comparative 16S ribosomal DNA (rDNA) sequence analysis, revealed that Rhodococcus erythropolis and Pseudomonas marginalis were the predominant bacterial species in the microbial consortium. Conclusion A structurally complex toluene-degrading biofilm, mainly formed by Rhodococcus erythropolis and Pseudomonas marginalis , developed on pumice granules, in a mini-scale apparatus continuously fed with toluene. | Background Surface-attached microbial communities, known as biofilms, are traditionally employed in fixed-film reactors for wastewater treatment. More recently, biofilms originating from the indigenous microflora of a contaminated groundwater have received increasing attention due to the possibility to develop in situ bioremediation systems, directly placed across the flow of a contaminated plume, the so-called "biobarriers" [ 1 ]. These are particularly attractive in the case of hydrocarbon contaminated groundwater, since the target contaminants can be destroyed by the attached biomass, leaving potentially non-toxic chemicals as biodegradation products. Indeed, the reactive system of a biobarrier is represented by the biofilm developed on the solid support starting from the autochtonous microbial population of the groundwater, where potentially degrading species are present. In this communication, we report the characterization of a toluene-degrading biofilm developed on pumice granules in two packing mini-columns, employed as a laboratory-scale biobarrier, over a 12-month period. That time was long enough for a mature consortium to establish on a solid support [ 2 ]. The main objective of the work was to analyse the structure and composition of the biofilm established on pumice stones in a mini-scale apparatus and to ascertain its degradative capability towards toluene, as a starting point for potential applications of a pumice-bound microbial consortium in bioremediation. Pumice, a rock of volcanic origin very abundant in Southern Italy, was chosen as a support material for its high-surface-area-for-unit-volume and relatively low price. Results Pumice granules packed mini-columns of two different heights were colonized by a microbial consortium, isolated from a gasoline contaminated groundwater sample and enriched in the presence of toluene as the sole carbon and energy source. Afterwards, the mini-columns (henceforth named columns 1 and 2, see Methods for details) were continuously supplied with a mineral medium containing toluene as the target contaminant, and then sacrificed after 6- and 12-month operation, respectively. Biofilms were characterized with three complementary approaches: observation by scanning electron microscopy, quantification of the attached biomass, and identification of the bacterial species, based on comparative 16S ribosomal DNA (rDNA) sequence analysis. Further, the biodegradative capability of the biofilm developed in column 2 was determined by measuring the efficiency of toluene removal, over a 12-month period. Scanning electron microscopy observation of the biofilm Scanning electron micrographs of Fig. 1 show the surface of the pumice support and the development and microscopic structure of the biofilm. Fig. 1A shows the macroporous structure of pumice stone before colonisation, Fig. 1B shows the surface of the pumice granules after 6 months of operation (column 1): rod shaped cells are evident. After 12 months operation (column 2), a thick layer of extracellular material covered the support, interspersed with a few single bacteria, both at the bottom (Fig. 1C ) and the top (Fig. 1D ) of the column. Quantification of the biomass adhering to pumice Table 1 reports data on the determination of biomass adhering to pumice granules after 6- and 12-month operation (columns 1 and 2). In the case of column 1, the determination of biomass, carried out by burning and total protein assay (see Methods), showed that a biofilm of about 3 mg dry weight of cells per gram of pumice was established after 6-month run of the column with both methods. In the case of column 2, data obtained with the burning procedure clearly showed a significant increase in organic material (calculated as volatile solids, VS), both at the bottom and the top of the column. On the contrary, data based on total protein assay evidenced that the biomass increased only in the lower part of the column. The discrepancy between data obtained with the two procedures could be attributed to the presence of a massive exopolymeric material in the 12 month-old biofilm, presumably of polysaccharidic nature and unavoidably weighed when the burning method is employed. The electron microscopy analysis suggests that this material is present both in the upper and lower part of the column; its production is linked to the biofilm maturation occurring in the second 6-month period. In fact, an abundant extracellular material covering the cells was evident by scanning electron microscopy of pumice granules sampled from both the upper and lower part of the column (Fig. 1 ). These considerations suggest that the protein assay could be a more reliable method to evaluate the actual amount of cells in the biofilm and to measure differences in biomass along the reactor. The different extent of colonization of the upper and lower part of column 2 could be presumably due to a higher nutrient supply at the bottom of the apparatus. Similarly, other authors [ 3 , 4 ] reported larger microbial populations at the inlet of the apparatus compared to the outlet, reflecting in this case a declining gradient of contaminant concentration along the reactor. Identification of the bacterial species Identification of the species based on 16S rDNA comparative analysis revealed that in both biofilms (column 1 and 2) the majority (85%) of the attached cells was represented by Rhodococcus erythropolis (99% of identity), whereas Pseudomonas marginalis (98% of identity) represented only 10% of the entire consortium. On the contrary, in the enriched culture (the microbial consortium employed to start the development of the biofilm), Pseudomonas marginalis was the predominant species (86%) and Rhodococcus erythropolis was only 10% of the consortium. Apparently, adhesion to the pumice support promoted the growth of Rhodococcus erythropolis , modifying the initial ratio between the two species. Less represented species in the three consortia examined (biofilms from column 1 and 2, as well as enriched culture) were identified as Agrobacterium tumefaciens (98% of identity), Hydrogenophaga palleronii (98% of identity), Chryseobacterium scophtalum (98% of identity), Leucobacter komagatae (98% of identity), Brachybacterium articum (96% of identity), Beta proteobacterium (98% of identity), Microbacterium liquefaciens (99% of identities) and Acinetobacter sp. (98% of identity). The biodegradative capability of the biofilm The biodegradative capability of the biofilm developed on the pumice granules over 12 months was evaluated in terms of toluene removal efficiency (RE), calculated as the slope of the line obtained plotting the average toluene elimination rate (ER) vs. the loading rate (LR) applied to column 2 (Fig. 2 ). A linear relationship between the elimination rate and the applied loading rate was obtained over the whole experiment, implying that the column operated below its maximal degradation capacity. An overall toluene removal efficiency of 99 % was calculated from the slope of the line. Toluene oxidation in the presence of nitrate as electron acceptor [ 5 ] may be postulated as the possible mechanism of toluene removal by the attached cells, since nitrate is present in the feeding medium and microaerophilic conditions presumably established along the column. Moreover, analysis of effluent revealed a nitrate concentration reduction (data not shown) consistent with the contribute of denitrifying bacteria in the biodegradation reaction. Conclusions The results obtained in this work demonstrate that a structurally complex toluene-degrading biofilm developed on pumice granules, following their inoculation with a microbial consortium obtained by enrichment of toluene-contaminated water. In the biofilm, Rhodococcus erythropolis and Pseudomonas marginalis were the predominant species. Apparently, the two species, once attached to pumice stone, gave rise to a specialised community by the production of exopolymers functioning as biofilm stabilizers [ 6 ]. Pseudomonas sp. is the most studied single-species, biofilm-forming bacterium [ 6 , 7 ]; differently, the molecular details of biofilm formation by the Gram positive Rhodococcus sp. have not been investigated so far, though the genus Rhodococcus is present in biofilm reactors [ 8 ] for its broad metabolic diversity and ability to degrade hydrophobic pollutants [ 9 ]. Although the microbiological complexity of the consortium established on pumice deserves further investigation in order to clarify the specific role of each species and its contribution to toluene degradation, the results obtained in this work may be relevant for a final design of a biobarrier in which a cheap support as pumice is used for biofilm formation. In particular, the molecular analysis performed revealed the strong impact of immobilization on the structure of the toluene-degrading community, demonstrating the importance of a molecular approach to characterize microbial biofilms. Methods A microbial consortium was obtained following enrichment of a gasoline contaminated groundwater sample and subsequently used to inoculate the packing material in the columns. The enrichment was carried out in 500 ml-flasks, adding 100 ml of groundwater to 100 ml of minimal salt medium (MSM), containing high sulphate and nitrate concentrations [ 10 ] supplemented with 20 mg l -1 toluene (final concentration) as the sole carbon and energy source, sparged with air and incubated at 25°C for two weeks. After this acclimation period, 25% (v/v) of the culture was transferred into fresh MSM medium containing the same toluene concentration and incubated in the same conditions. To allow culture enrichment, the transfer was repeated 10 times, until a biomass (dry weight determination after centrifugation at 3000 g and washing of the collected cells) of 1.2 mg d. w. ml -1 was achieved. To study the biofilm development, two glass columns (2.5 cm in diameter and 1 or 3 cm in height), were packed with pumice granules (0.4–0.6 mm in size, average particle density 0.48 g ml -1 ), respectively previously washed with distilled water, autoclaved (120°C, 20 min) and then soaked in MSM medium containing 20 mg l -1 toluene. The ratio between column and particle diameter was ~50 to reduce wall effects and preferred channelling; the column void volume was 60%. The columns were provided with teflon supports, tubes and connections to prevent abiotic removal of toluene. For each column, the attachment of microbial cells to the support material was carried out by recirculating the enriched culture at a low flow rate (0.008 l h -1 ) for one week. After this period, the two columns, henceforth referred as column 1 (2.5 × 1 cm) and column 2 (2.5 × 3 cm), were continuously fed upwards at a flow rate (Q) of 0.026 ± 0.003 l h -1 , with MSM plus toluene for 6 and 12 months, respectively, and then sacrificed. Operations were carried out at 25°C. MSM was continuously sparged with air and mixed with the solution containing toluene just before entering the columns. The set-up for the continuous operation of the two minicolumns is schematically presented in Fig. 3 . The inlet concentration of toluene (S i ) was changed step-wise every 4 weeks, from an initial concentration of 0.77 ± 0.03 up to 4.42 ± 1.21 mg l -1 , allowing two weeks to achieve culture acclimation before conducting the biodegradation assays in the following two weeks. A total of six values of toluene concentration in the inlet were established, being the highest inlet concentration achieved during the sixth month of operation; then, column 1 was sacrificed, and column 2 was fed with 4.42 ± 1.21 mg l -1 toluene during the remaining 6 months, in order to permit biofilm maturation under constant feeding conditions. In the case of column 2, values of toluene concentration in the inlet (S i ) and in the outlet (S e ) were employed to calculate toluene loading rate (LR) and elimination rate (ER) according to the following equations: ER = Q (S i -S e ) / V and LR = S i ·Q/V, where, Q is the inlet feed flow rate (0.026 l h -1 ) and V is the total volume (0.015 l) of the column, respectively. Toluene determination Toluene concentration in the gas and liquid phase was determined by the headspace method on a gas chromatographic system (HP 6890 Series) equipped with flame ionization detector (FID), calculating the area of the chromatographic peaks. Toluene concentration values in the outlet of column 2 were the average of at least 10 determinations, carried out either after culture acclimation during the first 6-month operation, or every week during the following 6-month period, when column 2 was maintained at the highest LR. Neither evidence of abnormal biomass growth nor loss of mechanical properties of the supports were recorded during the entire time course of the experiment. Scanning electron microscopy analysis To perform scanning electron microscopy analysis, pumice granules collected from both columns 1 and 2, together with not colonised granules were fixed with 2.5 % glutaraldehyde in 15 g l -1 NaCl for two hours at 4°C, processed according to [ 2 ] and analysed with a scanning electron microscope (Cambridge 250 Mark3). Biomass determination The biomass attached to the support was estimated as volatile solids (VS), after drying at 105°C and then burning at 600°C of the colonised pumice granules, collected from both columns. The difference in mass between the dried and the burned samples was the weight of VS (being ash equal to 8 ± 2% of the dry biomass). Biomass was also indirectly determined by total protein assay (Bio-Rad, Richmond, CA, USA) after detachment of the cells from the support by bead-beating in a homogenizer (Fast prep, BIO 101 Thermo Savant) and their lysis (60°C for 90 min with 0.6% w/v SDS), assuming that the average protein content in bacteria is about 50% of cell dry weight [ 11 ]. Since colonization of the top and the bottom parts of column 2 was considerably different to the naked eye, granules were sampled from both ends of the column and separately processed for all the determinations. Identification of the bacterial species To identify the microbial species in the biofilm of columns 1 and 2, cells removed from the pumice granules by bead-beating (see above) were plated on TSA (Tryptone Soy Agar). An average of 100 colonies were isolated after serial dilutions from each consortium, and cultured individually in Tryptone Soy Broth (TSB). In parallel, to identify the microbial species present in the enriched culture employed to inoculate the packing material, an average of 100 colonies from the enriched culture were isolated on TSA and cultured individually in TSB. Chromosomal DNA was extracted from cells of the isolated strains according to standard methods for bacteria [ 12 ] and used as template for PCR amplification performed with 30 cycles, each consisting of 30 s at 94°C for DNA denaturation; 40 s at 52°C for primer annealing, and 90 s at 72°C for elongation. Primers used in PCR reaction were P1 (5'-GCGGCGTGCCTAATACATGC) and P2 (5'-CACCTTCCGATACGGCTACC), annealing to nucleotides 40 to 59 and 1532 to 1513, respectively, of B. subtilis rrnE . These primers are normally utilized as universal primers for eubacteria. After PCR amplification, 1.5 Kbp 16S ribosomal DNA fragments were purified from agarose gels and sequenced. Ribosomal DNA gene sequences of the isolates where compared by BLAST program with those present in the DNA GenBank [ 13 ]. Authors' contribution DLA:carried out biofilm characterization. VM:carried out the identification of species and helped to draft the manuscript. PP: partecipated in the design of the study. VR: partecipated in the design of the study and setting up of laboratory apparatus. BA: performed toluene analysis. SP: partecipated in the setting up of laboratory apparatus. SR: partecipated in the design of the study and helped to draft the manuscript. DAE: conceived of the study, and partecipated in its design and coordination, drafted the manuscript. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546200.xml |
449899 | Doing Science in Uncertain Times | Doing scientific research in post-Soviet Russia is challenging but there are solutions that could prevent the massive brain drain witnessed in recent decades | A scientist living in Russia is often asked two questions: “Why haven't you left?” and “Is it still possible to work there?” The best response to the first question is, “Why should I?”—which either terminates the conversation or leads to a stimulating discussion about the fate of the world. The second question, however, deserves a serious answer. In fact, this is the question that every one of us keeps asking ourselves. There is no simple answer. The biggest problems we face are brain drain, inadequate infrastructure, and lack of money (or perhaps, lack of money, lack of money, and lack of money). In the Soviet Union, fundamental science was supported to a great extent by military expenditure. Thus, it is not surprising that Soviet physics and mathematics were more successful than other fields, such as biology. In the 1990s, military spending on science declined sharply, although the exact numbers are hard to estimate. This year, the direct funding of science constitutes only 1.78% of Russia's national budget (an additional 0.46% is allocated to the space program), although the law stipulates that this figure should be at least 4%. Still, this funding amounts to 46.2 billion rubles (approximately US$1.6 billion), more than twice the amount spent in 2000. Although this figure looks negligible compared with spending on science in the United States and many European countries, it could still be sufficient to support existing actively working groups at a reasonable level. Funding There are several mechanisms for distributing funds for research. The major share comes via Russia's Department of Science and the Russian Academy of Sciences. The Academy, unlike its Western analogs, not only acts as a consulting body of experts, but also has the authority to distribute money ( Figure 1 ). The funds come both as long-term support for scientific institutes and as National or Academy research programs. The former covers base salaries, which are small even by local standards (about US$200 per month for a laboratory chief), and basic infrastructure (water, electricity, etc.). This system of long-term support inherited all the old Soviet ills, such as the lack of correlation between scientific output and the level of funding. As a result, the available resources are spread thinly over hundreds of labs, most of which are just barely alive. The National or Academy research programs can provide funding at a higher level, sometimes even enough to do experimental research. However, the procedure of establishing such programs, though formally competitive, is often not transparent, and a major role is played by the so-called “administrative resource” ( Allakhverdov and Pokrovsky 2003 ). Figure 1 The Golden Brain (the Praesidium of the Russian Academy of Sciences) (Photograph, with permission, by Nataliya Sadovskaya) Figure 2 Papers Published in Nature and Science in Which at Least One of the Coauthors Lists an Address inside the Soviet Union or Russia The actual number of such papers is shown by the solid line. Their “effective number,” into which each paper contributes with the coefficient equal to the fraction of addresses inside the Soviet Union or Russia from all the listed addresses, is shown by the broken line. In recent years, the contribution of ethnic Russians to high-quality research increased, but their work is mostly performed outside Russia. Figure 3 Papers Published in Nature and Science by Researchers with the 15 Most Common Russian Surnames (Ivanov[a], Kuznetsov[a], Smirnov[a], Etc) The number of all papers in which at least one coauthor has a name from this list is shown by the solid line, and the number of such papers that list at least one address inside the Soviet Union or Russia is shown by the broken line. Whereas before 1992 nearly 100% of ethnic Russians doing toplevel science resided inside the Soviet Union and Russia (hardly surprising!), by now, this number has dropped to below 25%. Money is also distributed through the Russian Foundation for Basic Research (RFBR). The decisionmaking mechanism used by RFBR is closer to Western standards, and involves anonymous refereeing followed by board discussions. Although its grants are rather small (at most, several thousand dollars per year for a maximum of three years), they provide important additional support for many small and mediumsized groups that may receive several such grants for different projects. In addition, RFBR supports the publication and translation of books, travel to international conferences, the organization of conferences in Russia, and similar activities. Unfortunately, several programs (in particular, support for young scientists) have recently been transferred from RFBR to a newly established government office, and have thus become less independent. Collaboration International collaboration and research grants are a major source of support for many active research groups ( Table 1 ). Several agencies and foundations have programs for Eastern Europe, Russia, and/or former Soviet republics. Some of them, such as the Howard Hughes Medical Institute (Chevy Chase, Maryland, United States), fund individual groups; others—for example the International Science and Technology Center (Moscow, Russia)—stipulate that projects should be submitted jointly by academic and military researchers; and some agencies—in particular, European INTAS (Brussels, Belgium) and the American John E. Fogarty International Center (Bethesda, Maryland, United States)—support collaboration between Russian and Western laboratories. Table 1 International Agencies Supporting Russian Science a The first three agencies are international organizations, followed by individual programs Another source of financial support is direct collaboration between Western and Russian laboratories. Even after a relatively short visit, the salary of a visiting researcher abroad can be stretched for several months back home in Russia; even more importantly, experimental biologists visiting foreign labs have access to modern instruments and chemicals, which allows them to do modern research. The hosts of such visits are often (although definitely not always) recent immigrants from Russia, and in such cases the collaborations may have roots in older days ( Box 1 ). As well as supporting Russian science directly, international collaboration plays an important indirect role because it is less influenced by local politics. In fact, one of the main positive impacts of the New York–based International Science Foundation set up by George Soros in early 1990s was that it demonstrated the possibility of open competition with clearly defined rules—something unheard of in Soviet times—and thus served as a model for the RFBR, which was organized at approximately the same time. Unfortunately, international ties, especially with the United States, have been adversely affected by recent changes in visa procedures, which have become lengthy (leading to many missed conferences) and, even worse, completely unpredictable (e.g., Brumfiel 2004 ). The grapevine distributes stories of “bad words” that should be avoided when describing one's research area during an interview at the consulate. Examples of such words include the adjective “nuclear” (even within a innocuous terms like “nuclear magnetic resonance”) or, more recently, anything that involves “bacteria.” The demand for fundamental and even for applied biological research from Russian industry is almost nonexistent. The pharmaceutical industry is content to produce generics, while Russian biotech companies are still exploiting old strains developed in the Soviet Union. However, some laboratories are conducting outsourced research, and there are now research outposts of Western and Japanese companies in Russia organized as standard industrial labs. On one hand, this work is a dead end for Russian scientists, because the results of such research normally cannot be published. This is a serious problem, especially for young scientists who want to establish themselves. On the other hand, royalties from patents or commercialization of the products can be used to support further research. One group that has followed this path successfully is Sergey Lukyanov's lab at the Shemyakin Institute of Bioorganic Chemistry in Moscow, Russia. They have developed the subtractive hybridization technique for enrichment of clone libraries by rare transcripts or specific genomic fragments ( Rebrikov et al. 2004 ), and are distributing it via a company called Evrogen ( http://www.evrogen.com/about.shtml ). Infrastructure and Bureaucracy Another major problem is the degradation of infrastructure. Only a few labs can afford modern equipment and instruments, and for many others, even standard chemicals are too expensive. This leads to a vicious circle: without equipment, a lab cannot conduct experiments at the level demanded by highimpact journals—and without such publications, it cannot compete for large grants. Smaller RFBR grants, while simpler to obtain, are insufficient to purchase large pieces of equipment, and funds from several grants or several years cannot be combined due to bureaucratic restrictions. Thus, the only hope for these labs, apart from international collaboration, is a personal connection with senior bureaucrats that might result in an (un)expected windfall. Having the funds to purchase modern equipment abroad is only the first hurdle; the many conflicting rules and restrictions, inefficiency, and corruption within the system can subsequently hold up the process. Some items, such as tissue samples or animals, are virtually impossible to import legally. The process of clearing the shipments through customs is a difficult, timeconsuming job. Grigory Kopelevich, the Howard Hughes Medical Institute's Russian representative, recalls a story of a grantee whose microscope was stopped at customs because the box contained two screwdrivers not specified in the order. Fortunately, to resolve the issue, it was sufficient to present one of the screwdrivers to a customs officer as a gift. Even basic access to journals is a problem, especially outside the main research centers. Indeed, out of a random sample of ten major universities where electronic library catalogs were available via the Internet, only six had subscribed to Nature , and only two to Science . More specialized journals are available only in Moscow and perhaps St. Petersburg. This is partially offset by the proliferating open-access journals from the Public Library of Science and BioMed Central, free electronic versions of older issues provided by some journals, free subscriptions for Russian academic institutes granted by some publishers or purchased by international foundations (e.g., the e-library.ru project organized by the RFBR and supported by the Open Society Institute [the Soros Foundation, based in New York] and the Department of Education) ( Table 2 ), reprints at authors' Web pages, and last but not least, colleagues abroad who break copyright laws by e-mailing PDF files; there is even a popular bulletin board coordinating this activity. However, these are only partial solutions. Russia is not considered a developing country, and thus is excluded from many international efforts that provide free access to journals (such as HINARI). Moreover, many journals have page charges, but no Russian grants cover these, and the cost of publication may be prohibitively high for many groups. Table 2 Journals and Other Resources, Available to Russian Academic Institutes under the elibrary.ru Project ( e-library.ru ) Brain Drain These problems, along with low salaries, have naturally led to a huge brain drain. Entire generations have been decimated ( Box 1 ); the dearth of researchers at the postdoc level, has caused a gap in the teaching and maintenance of scientific traditions. Many labs now consist of older chiefs and senior researchers, and graduate students who plan to leave immediately after getting the candidate degree (the equivalent of a Western doctorate). “Leaving” does not necessarily mean leaving the country; many capable young people go into business. While that might be good for the country in general, it is bad for science, at least in the short term. However, even emigration is not a completely negative thing; it creates a network of collaborators, and in many cases enhances ties with the international community. Despite all this, science in Russia is very much alive. Not-yet-Nobel-prizewinner Alexei Abrikosov's repeated exhorations to the scientific community “to help all the talented scientists leave Russia and to ignore the rest” were met by universal disgust ( Hoffman 1993 ; Leskov 1993 ; Migdal 1993 ). There are several competitive Russian labs doing first-rate research and publishing in the top-tier journals. Old habits die hard; even in these days, very decent results are often published in Russianlanguage journals, the best of which have impact factors that are around 1. Each year, many intelligent and capable students enroll in universities, and competition for admission is steadily increasing from the lows of the mid-1990s. There are also well-attended international conferences in several Russian cities. Prospects What can be done by the international community to support what is left of Russian science? Of course, direct support in the form of competitive grants is important, especially if there are few restrictions on spending; even the most carefully considered procedure cannot foresee all possible situations. But even more useful is the creation of joint research centers, such as the one opened by the international Ludwig Institute for Cancer Research (LICR) based jointly in Zurich, New York, and London, and the Belozersky Institute of Physico-Chemical Biology of Moscow State University in Moscow, Russia. This research center began with limited support for several stronger groups, and is gradually moving toward integration of a research program in Moscow with other LICR projects, and real collaboration between Moscow groups and LICR labs elsewhere. One of the most essential elements of successful research is access to up-to-date information. Consequently, any initiative that provides open access to scientific literature and databases is extremely useful. Seminars, lecture courses (such as the Moscow University [Moscow, Russia] cycle on oncology and immunology sponsored by LICR; www.oncoimmunology.ru/index_e.htm ), and the participation of Western scientists in scientific conferences in Russia are important not only because they provide a fresh understanding of emerging trends, but also because they create personal contacts between Russian and Western scientists that often lead to fruitful collaboration. By contrast, some other types of joint project may be less successful. Artificial programs aimed at creating various participant “networks” usually do not work as expected, and training programs in Western universities often attract potential emigrants rather that those willing to continue active research inside Russia. The contribution of the international community cannot be the sole decisive factor in the future growth of Russian science. Important as it is in this transition period, it is no substitute for a systemic change. The ills of Russian science are not unique; the same issues have been raised by scientists from other Eastern European countries (e.g., Wojcik 2004 ). Even the existing funds could go much further if scientific policies were more open, better structured, and more competitive. Large grants should be provided, on the basis of well-defined criteria, to only the strongest labs doing the best research. An often-heard opinion that no independent review is possible in a small, well-entrenched community is irrelevant, since international boards of experts can be formed—the example of the Soros foundation clearly demonstrates that this is feasible. However, smaller pilot grants are also needed to support young scientists and labs contemplating new projects. This would create competition at all levels and provide doctoral students and postdocs with an incentive to stay in Russia and enroll in a strong lab. But again, the procedure for awarding such grants should be well defined, transparent, and independent from administrative influences. Thus, the traditional model of top-down distribution of funds must be changed, and this may be difficult. The current system of decision making by Russian funding agencies is clearly inadequate. Moreover, the problems of Russian science mirror the problems of Russian society in general, and it would be naive to expect that they will be solved overnight, even given the political will. Still, if successful, this combination should provide both high-level research in established fields and sufficient flexibility to find new directions. Box 1. Top-Level Publications by Russian Scientists The vast majority of papers published in recent years in the best journals by scientists working in Russia have foreign coauthors (who are often Russian émigrés), indicating that international collaboration is the most reliable source of support for top-level research. (Text and figures in this box courtesy of Alexey Kondrashov.) | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC449899.xml |
546228 | Evidence for preferential copackaging of Moloney murine leukemia virus genomic RNAs transcribed in the same chromosomal site | Background Retroviruses have a diploid genome and recombine at high frequency. Recombinant proviruses can be generated when two genetically different RNA genomes are packaged into the same retroviral particle. It was shown in several studies that recombinant proviruses could be generated in each round of HIV-1 replication, whereas the recombination rates of SNV and Mo-MuLV are 5 to 10-fold lower. The reason for these differences is not clear. One possibility is that these retroviruses may differ in their ability to copackage genomic RNAs produced at different chromosomal loci. Results To investigate whether there is a difference in the efficiency of heterodimer formation when two proviruses have the same or different chromosomal locations, we introduced two different Mo-MuLV-based retroviral vectors into the packaging cell line using either the cotransfection or sequential transfection procedure. The comparative study has shown that the frequency of recombination increased about four-fold when the cotransfection procedure was used. This difference was not associated with possible recombination of retroviral vectors during or after cotransfection and the ratios of retroviral virion RNAs were the same for two variants of transfection. Conclusions The results of this study indicate that a mechanism exists to enable the preferential copackaging of Mo-MuLV genomic RNA molecules that are transcribed on the same DNA template. The properties of Mo-MuLV genomic RNAs transport, processing or dimerization might be responsible for this preference. The data presented in this report can be useful when designing methods to study different aspects of replication and recombination of a diploid retroviral genome. | Background Retroviruses are a family of RNA viruses which replicate through a DNA intermediate [ 1 ]. The unique property of retroviruses is that their virions contain two identical genomic RNA molecules noncovalently linked near the 5' ends forming a dimer [ 2 , 3 ]. Thus, the retroviral genome is diploid. The presence of two RNA molecules in each virion seems to be necessary for recombination because there is no pool of viral replicative intermediates in the cells infected by retroviruses [ 4 , 5 ]. Recombination is thought to contribute to the genetic variability of retroviruses and to repair breaks in genomic RNA. It can not be excluded that both RNA molecules are necessary for synthesis of proviral DNA. Reverse transcription entails two DNA strand transfers during minus and plus DNA synthesis. Since the retroviral virion contains two molecules of the viral RNA, the first DNA transfer might be either intramolecular, transferring to the same template, or intermolecular, transferring to the other template. In the model of Spleen necrosis virus (SNV) it was found that the minus-strand DNA transfer is exclusively intermolecular [ 6 ], while another study demonstrated the almost complete preference for intramolecular minus-strand transfer [ 7 ]. However, recombinant proviruses can undergo both interstrand and intrastrand transfers in equal proportions [ 7 - 9 ]. The rate of recombination in these reports was 4% per kilobase per replication cycle [ 4 , 8 ] and it was not significantly increased when the marker distance was extended to the size of the retroviral genome, suggesting that recombination is limited to only a subpopulation of retroviruses [ 10 ]. On the other hand, Human immunodeficiency virus type 1 (HIV-1) was shown to undergo approximately two to three recombination events per genome per cycle of replication [ 11 ] and, similar to the recombinant SNV proviruses, the first DNA strand transfer was either intra- or intermolecular [ 12 , 13 ]. A reason why there are differences in the rates of recombination between HIV-1 and gammaretroviruses (SNV and Mo-MuLV) is not known. It has been suggested that these differences may be associated with the differences in the template switching frequencies of retroviral reverse transcriptases [ 11 ]. A recent study has shown that the rates of intramolecular template switching for HIV-1 and Mo-MuLV (Moloney murine leukemia virus) were very similar, indicating that the replication properties of HIV-1 and Mo-MuLV RTs may not differ [ 14 ]. However, it is not clear whether the same conditions are required when both genomic RNAs are used as the template during reverse transcription. The other possibility is that gammaretroviruses may copackage genomic RNAs produced at different chromosomal loci by nonrandom chance [ 15 ]. In this case, the sizes of heterodiploid and recombining subpopulations of viruses may coincide. In this study, we have investigated whether there is a preference in the formation of homodiploid virions during the mixed retroviral infection. To explore this possibility, we have used the forced recombination system which included two Mo-MuLV-based retroviral vectors containing different selectable markers and one of the vectors having a deletion of the PBS region. These vectors were introduced into the packaging cell line using two different methods, cotransfection, to provide tandem integration, or sequential transfection, and the frequencies of recombination for the vectors have been compared. Results Experimental approach To study whether there was a preference for the formation of homodiploid virions in the mixed retroviral infection we have used two different methods, cotransfection and sequential transfection, to introduce genetically different retroviral vectors into the host cells. Since plasmid DNA transfected into eucariotic cells is usually tandemly integrated in a chromosome [ 16 - 19 ], it is expected that cotransfected vectors will be localized in the same locus of chromosome and RNA transcribed from these templates will form a general pool of molecules. In this case, two genetically different populations of RNA molecules will ideally overlap. On the other hand, it is unknown whether the same conditions exist for reassortment of RNA molecules transcribed at different chromosomal locations. The study of recombination frequencies for retroviral vectors that are introduced by the cotransfection or sequential transfection can help to answer this question. Comparative study of recombination frequencies for retroviral vectors with the same and different chromosomal locations In this study Mo-MuLV-based retroviral vectors were used as partners for recombination. These vectors contained the Mo-MuLV sequences as follows: the 5' and 3' LTRs, ψ region, a part of gag-sequences before XhoI site (position 1560 [ 20 ]), and 140 bp including the polypurine tract before 3' LTR (Figure 1 ). To selectively introduce vectors into the packaging cell line, pDHEneo contained the neo gene that was expressed by transcripts initiated from the long terminal repeat, while pDΔpbsSVpuro contained the puro gene under control of SV40 early promoter region. In addition to the differences in selectable markers, the pDΔpbsSVpuro vector was replication defective due to the deletion of entire PBS. Figure 1 Structures of Mo-MuLV-based retroviral vectors used in this study. U3, R, U5, regions of long terminal repeat; SV, simian virus 40 early promoter region; ψ+, extended packaging signal; Neo, neomycin phosphotransferase gene; Puro, puromycin N-acetyltransferase gene. Δpbs and ΔEP indicate that the entire primer binding site and enhancer-promoter sequences from the U3 region are deleted. Since pDΔpbsSVpuro RNA is impaired at the initiation of reverse transcription, this function can be restored when the cDNA initiated on the copackaged pDHEneo RNA is transferred to the puro RNA template during the first jump; minus-strand synthesis continues through the puro gene, and the template shift occurs within the leader region. Thus, the restoration of retroviral vector containing the puro gene is possible via homologous recombination with the neo-containing construct at the sequence identity in the leader region of the genome. The experimental scheme employed in this study is outlined in Figure 2 . Retroviral vectors pDΔpbsSVpuro and pDHEneo were introduced into GP+envAM12 packaging cells by either the cotransfection or sequential transfection procedure. For sequential transfection pDΔpbsSVpuro was first introduced into helper cells. The transfected cells were placed on puromycin selection and the resistant cell clones were picked. Viral titers generated from these clones were analyzed using NIH3T3 cells. None of the cell clones analyzed produced detectable level of puromycin titer. Two clones were further used for transfection of pDHEneo and the G418 resistant clones were selected. For cotransfection the equal quantities of vector DNA was used for transfection of helper cells. The cells were first placed on G418 selection and the resistant cell clones were further obtained via puromycin selection. After drug selection, the double-resistant helper cell clones were isolated. Figure 2 Experimental scheme to study recombination frequencies for retroviral vectors located in the same or different chromosomal sites. It was expected that plasmid DNA of retroviral vectors pDHEneo and pDΔpbsSVpuro cotransfected into the packaging cell line would be tandemly integrated into the host genome. To study the integration of plasmid DNA, the PCR analysis was performed with the primers hybridizing to the 3' end of neo gene (T1, direct, for pDHEneo) and to the SV40 early promoter region (T2, reverse, for pDΔpbsSVpuro). Using these primers, the specific PCR products could be obtained if the pDHEneo and pDΔpbsSVpuro are located in the same chromosomal site. On the other hand, PCR products could be generated with only one of the primers when identical molecules of plasmid DNA were integrated in the opposite orientation. However, the efficiency of amplification in this case seems to be very low because such sequences will contain inverted repeats. The PCR analysis was performed using chromosomal DNA prepared from different cell clones generated after cotransfection or sequential transfection of vectors. PCR products were separated by gel electrophoresis, transferred onto nylon membrane and hybridized with 3' neo specific probe. An example is presented in Figure 3 which shows that specific PCR products of different size were obtained only for the cell clone generated after cotransfection of two vectors. These data are in agreement with early observations [ 16 - 19 ] and demonstrate that plasmid DNA transfected into the packaging cells is cointegrated into the cellular DNA. Figure 3 PCR analysis of plasmid DNA transfected into the packaging cell line GPenv-AM12. A. Analysis of tandemly integrated plasmid DNA. Amplification was performed with a 5' primer specific to neo sequences (T1, unique for pDHEneo) and a 3' primer specific to SV40 early promoter region (T2, unique for pDΔpbsSVpuro). Membrane was hybridized with 3' neo specific probe generated from a 150 bp SalI-ClaI fragment of pDHEneo. ST is GPenv-AM12 virus-producing cell clone ST2-1 generated by sequential transfection of pDHEneo and pDΔpbsSVpuro, and CT is cell clone CT2 generated by cotransfection of the same vectors. Molecular size markers are indicated on the right of the Southern blot. Similar results were obtained when four cell clones were analyzed. B. Control of amplification. Primers specific to the 5'- and 3'-end of neo gene (CND and CNR, respectively) were used to generate PCR products (1.63 kb) from ST and CT DNA samples. Membrane was hybridized with the same probe as in A . PCR products obtained from 200 and 40 ng of ST DNA sample (line 1 and 2); PCR products obtained from 200 and 40 ng of CT DNA sample (line 3 and 4). The result shows that specific PCR products could be amplified both from ST and CT DNA samples with this set of primers. We also used RT-PCR-based assay to examine the ratios of retroviral virion RNA molecules for cell clones generated by different methods of transfection. Since retroviral vectors differed by localization of EcoRI sites in the leader regions, these restriction sites were used as markers to distinguish the two coamplified PCR products obtained with primers specific to this region (Figure 4 ). EcoRI digestion generated 453- and 148-bp fragments from the pDΔpbsSVpuro PCR products that were readily distinguishable from the 515- and 98-bp fragments generated from the pDHEneo PCR products. Since the only differences between the neo- and puro-containing RNAs are nineteen bases that lie within the polymerized region (PBS was replaced with EcoRI in pDΔpbsSVpuro and one nucleotide was substituted in the leader region of pDHEneo to introduce EcoRI site), these two templates will amplify with equal efficiency. PCR products obtained from virion RNA for the two cell clones generated by sequential transfection and two clones generated by cotransfection of retrovital vectors were digested with EcoRI and the ratio of corresponding DNA fragments was examined. This analysis showed that ratios of retroviral RNAs for different cell clones ranged from 1.6 to 2.5 (pDΔpbsSVpuro/pDHEneo) and were the same for two variants of transfection (Figure 4 ). Figure 4 RT-PCR analysis of virion RNAs. A. Plasmid structures of retroviral leader regions. L1 and L2, primers used for PCR amplification; sizes of DNA fragments and positions of EcoRI sites are indicated. B. Leader sequences in virion RNAs were PCR amplified and analyzed by restriction digestion. PCR products obtained from virion RNAs of ST2-1 and ST2-2 packaging cell clones (lines 1 and 3); PCR products obtained from virion RNAs of CT1 and CT2 cell clones (lines 2 and 4); M, molecular weight markers. The ratios of puro/neo retroviral RNAs for ST2-1, ST2-2, CT1, and CT2 cell clones were 1.8, 2.0, 1.6, and 2.5, respectively. Viral titers generated from three helper cell clones obtained after sequential transfection and four cell clones obtained after cotransfection are shown in Table 1 . In the first case the G418 titers varied from 5.0 × 10 3 to 6.3 × 10 4 CFU/ml and puromycin titers from 5.1 × 10 1 to 8.0 × 10 2 CFU/ml. In the cotransfection experiment, the G418 titers varied from 3.1 × 10 4 to 1.1 × 10 5 CFU/ml and puromycin titers from 1.4 × 10 3 to 3.6 × 10 3 CFU/ml. The frequency of recombination was calculated from the puromycin- and G418-drug-resistant colony titers (Table 1 ). For the sequential transfection experiment the recombination frequencies ranged from 1 to 1.3 %, with an average of 1.1 %, while recombination frequencies for the cotransfection experiment ranged from 3.3 to 4.5 %, with an average of 3.9 %. Table 1 The comparative study of recombination frequencies for cotransfected and sequentially transfected retroviral vectors Method of introduction Clone Viral titer (CFU/ml) Recombination frequency* (%) Puromycin G418 Sequential Transfection: pDΔpbsSVpuro + pDHEneo ST1-1 5.1 × 10 1 5.0 × 10 3 1.0 ST2-1 4.2 × 10 2 4.2 × 10 4 1.0 ST2-2 8.0 × 10 2 6.3 × 10 4 1.3 Mean ± SE 1.1 ± 0.1 Cotransfection: pDΔpbsSVpuro + pDHEneo CT1 3.6 × 10 3 1.1 × 10 5 3.3 CT2 1.4 × 10 3 3.1 × 10 4 4.5 CT3 2.0 × 10 3 5.5 × 10 4 3.6 CT4 3.1 × 10 3 7.4 × 10 4 4.2 Mean ± SE 3.9 ± 0.3 pDΔpSVpuro + pDHEneo CR1 2.5 × 10 1 1.0 × 10 5 0.03 CR2 2.5 × 10 1 4.8 × 10 4 0.05 CR3 0.9 × 10 1 2.9 × 10 4 0.03 Mean ± SE 0.04 ± 0.01 *The frequency of recombination was calculated as the ratio of puromycin- to G418-drug-resistant colony titer. The restriction enzyme marker differences in the leader regions of vectors provided a means to analyze the nature of recombinants in NIH 3T3 cells examined by PCR assay. Cellular DNA was analyzed from eight Puro r NIH 3T3 cell clones obtained after infection with viruses produced by ST2-1 helper cell clone and eight cell clones obtained after infection with viruses produced by CT1 helper cell clone. This assay showed that all analyzed proviruses were recombinants between parental viruses, three of which were generated by template-switching in the 300 nt DLS region, and thirteen which were generated by template-switching in the 1038 nt region of 3' DLS (data not shown). These experiments demonstrated that the frequency of recombination between vectors localized in the same chromosomal site was about four-fold higher than that of vectors with different chromosomal locations. These data suggest that there might be a preference for the formation of diploid retroviral genome from RNA molecules that are transcribed on the same DNA template. On the other hand, it could not be completely excluded that the high frequency of recombination for retroviral vectors in the cotransfection experiments occurred during or after transfection procedure. The use of retroviral vector with the inactivated promoter To study the possibility of recombination between cotransfected vectors during or after transfection, we used the defective vector in which the 5' LTR promoter was deleted. This vector, pDΔpSVpuro, is almost completely homologous to pDΔpbsSVpuro with the exception of 194 bp in the U3 region (Figure 1 ). The efficiency of recombination during cotransfection for pDΔpSVpuro and pDHEneo was expected to be similar to that of pDΔpbsSVpuro and pDHEneo. However, the restoration of pDΔpSVpuro during reverse transcription will be limited by the basal level of cellular transcription since this vector is transcriptionally defective. Thus, the use of vector with the inactivated promoter could distinguish between recombination at the level of DNA and RNA in our experimental system. The introduction of viral vectors into the packaging cell line, GP+envAM12, allowed selection and propagation of individual cellular clones under conditions similar to those in the previous experiments. The resulting viral titers are shown in Table 1 . For three helper cell clones generated after the cotransfection with pDΔpSVpuro and pDHEneo the G418 titers varied from 2.9 × 10 4 to 1.0 × 10 5 CFU/ml, with an average 5.9 × 10 4 CFU/ml, and the puro titers varied from 0.9 × 10 1 to 2.5 × 10 1 CFU/ml, with an average 2.0 × 10 1 CFU/ml. The frequency of recombination for these vectors was 0.04 %. Thus, these results clearly demonstrated that recombination during cotransfection in our experimental system was a rare event and the majority of recombinations between cotransfected vectors occurred during the reverse transcription. Discussion In the present work we have examined whether there was a preference in the formation of homodiploid genomes when two genetically different retroviral vectors were located in the different regions of the host genome. Since plasmid DNA transfected into eucaryotic cells is usually tandemly integrated [ 16 - 19 ], we have compared the frequencies of recombination for two Mo-MuLV-based retroviral vectors introduced into the helper cell line by either cotransfection or sequential transfection. Our results showed that cotransfection yielded about four-fold higher frequency of recombination comparing to sequential transfection, indicating that diploid retroviral genome is mainly formed from RNA molecules transcribed on the same DNA template. To exclude the possibility that recombination between vectors occurred during the cotransfection or/and the integration of plasmid DNA into the helper cell genome, we used a retroviral vector with the deletion of promoter-enhancer sequences as a partner for recombination. The 100-fold lower frequency of recombination for transcriptionally deficient vector, compared to that of the identical retroviral vector with the intact promoter, indicated that recombination during cotransfection was a rare event relative to recombination during reverse transcription. Recent studies using the Moloney murine leukemia virus and the Spleen necrosis virus based vectors demonstrated that the recombination rate did not increase linearly with the increasing of marker distance and the multiple recombination events were observed much more often than could be expected from the frequency of recombination [ 10 , 15 , 21 , 22 ]. From these data it was postulated that the rate of retroviral recombination is restricted by the size of the recombining subpopulation [ 10 , 15 , 21 ]. On the other hand, the rate of recombination obtained for HIV-1 was about two to three crossovers per genome per replication cycle [ 11 , 12 ]. High rate of HIV-1 recombination was also observed in the experimental system where target sequences and experimental conditions for recombination were the same as in Mo-MuLV- and SNV-based studies [ 23 ]. While the rates of intermolecular recombination for HIV-1 and gammaretrovoruses were different, their intramolecular template switching frequencies were similar [ 14 , 24 ]. The preferential formation of homodimers in the mixed retroviral infection can explain the existence of the recombining subpopulation found for avian and murine retroviruses because, in this case, the amount of heterodiploid virions will be less than expected from the randomly distributed genomic RNA. Our demonstration of about 4-fold differences in the frequencies of recombination for the cotransfected and sequentially transfected retroviral vectors seems to agree with the data showing that the maximal recombination rate for Mo-MuLV was 20 % per genome per replication cycle [ 10 , 22 ]. These data also indicate that the difference in the recombination frequencies for gammaretroviruses and HIV-1 could mainly be associated with the ability of these viruses to copackage two different genomic RNAs. The possible mechanism explaining the preferential formation of homodimers, as suggested earlier [ 15 ], may be a local transport of RNA transcribed in the same locus of chromosome from the nucleus to their destination in the cellular cytoplasm. In the cytoplasm, RNA could be quickly bound by viral proteins before two different pools of RNA molecules transcribed in different chromosomal sites will be equally distributed. The gammaretroviruses and HIV-1 could differ in the properties of their RNA transport and distribution in the cellular cytoplasm. For example, HIV-1 encodes the virus-specific protein Rev which selectively transports the unspliced viral RNAs from the nucleus to cytoplasm [ 25 ]. Moreover, unspliced HIV-1 RNAs form a general cytoplasmic pool of molecules which can further participate in the translation of viral proteins and/or be packaged in the virions [ 26 ]. It was recently shown that translation of HIV-1 viral RNAs could precede their packaging [ 27 ]. In this case, the translation of genomic RNAs can provide more time for reassortment of two different viral RNAs. As an alternative, it can be suggested that the dimerization of genomic RNAs of gammaretroviruses occurs immediately after transcription in the cell nucleus and heterodimerization involves only minor populations of RNA molecules left in a monomeric form and/or unstable homodimers. The diploidy of retroviral genome supposes that two molecules of RNA could be necessary for replication of virus. However, it is also possible that diploidy is important for recombination and evolution of virus since retroviruses do not have a pool of replicative intermediates that can undergo recombination [ 5 ]. The preferential copackaging of genetically identical retroviral RNAs further argues in favour of the hypothesis that both RNA molecules are required in each round of retroviral replication. This assumption is also in agreement with the results of previous studies showing the utilization of both HIV-1 RNAs during reverse transcription [ 11 , 12 ]. It can be suggested that two genomic molecules of RNA are necessary to repair frequent breaks in RNAs [ 28 ] or the synthesis of provirus requires involvement of cis-acting elements present in both RNA molecules. Upon completion of our manuscript, an article was published concluding that dimerization of Mo-MuLV genomic RNAs is carried out by nonrandom chance [ 35 ]. There are several differences in these two studies. In the cited report, the RNA dimers were examined in the viruses that were generated by transiently cotransfecting two vectors or were produced by cell clones containing retroviral vectors integrated in different chromosomal sites. A model of nonrandom dimerization has been proposed, where Mo-MuLV genomic RNAs may undergo dimerization cotranscriptionally. In our study, the frequencies of recombination were directly compared for cell clones where retroviral vectors were integrated in the same or different chromosomal sites. While retroviral vectors integrated in the same chromosomal site were expressed as independent transcriptional units, the efficiency the heterodimer formation was increased about four-fold compared to that of retroviral vectors with different chromosomal locations. This argues that dimerization of Mo-MuLV genomic RNAs during cotranscription is not the main reason for the preferential formation of homodiploid genomes in Mo-MuLV. In spite of substantial differences in the methods, the estimations of the efficiency of homodimer formation were similar in both studies. The experimental system presented in our report could be used to study cellular and viral factors that are responsible for the preferential copackaging of genetically identical retroviral RNAs. Conclusions The results of this study provide evidence that the Mo-MuLV genome is mainly formed from RNA molecules synthesized on the same DNA-provirus. This property of Mo-MuLV may explain why only small subpopulations of gammaretroviruses produce recombinants. In this context, the differences in the frequencies of recombination between HIV-1 and Mo-MuLV may reflect differences in the ability of these viruses to randomly copackage genetically distinct RNAs. The preferential formation of homodiploid genomes in Mo-MuLV also implies that both molecules of RNA might be required for replication of the retroviral genome. Methods Plasmid constructions pMOV9 containing the complete copy of Mo-MuLV provirus and retroviral vectors pDneo and pDSVpuro have been described earlier and were used as the progenitor for all the constructions [ 29 , 30 ]. pDneo and pDSVpuro contain upstream long terminal repeat (LTR) and ψ + region before position 1560 of Mo-MuLV sequences [ 20 ], neomycin phosphotransferase gene or puromycin N-acetyltransferase gene under control of Simian virus 40 (SV40) early promoter region, and the Mo-MuLV sequences from position 7674 including downstream long terminal repeat. The nucleotides are numbered for the Mo-MuLV sequences starting from the beginning of R region [ 20 ]. To generate pDΔpbsSVpuro, we first constructed pLTRΔpbs which contains the LTR and the leader region before position 564 of pMOV9 with the deletion of PBS region. For this purpose we used the PCR to amplify two overlapping fragments after joining of which the PBS region was substituted with the EcoRI site. The first PCR fragment was generated with the primers: U3 SalI 5'-CGCGTCGACAGAAAAAGGGGGGAA-3' (sense, positions 7803–7821) and Rir EcoRI 5'-GCGCGAATTCAATGAAAGACCCCCG-3' (antisense, positions 130–144); the second PCR fragment was generated with the primers: 3'PBS EcoRI 5'-GCGCGAATTCCGGGAGACCCCTGCC-3' (sense, positions 164–178) and L2 5'-GACAAATACAGAAAC-3' (antisense, positions 599–613). PCR fragments were digested with EcoRI, ligated, and further digested with SalI and PstI, and cloned into pBluescript KSII + (Stratagene). The amplified region of pLTRΔpbs was analyzed by sequencing. The resulting construct, pDΔpbsSVpuro, was generated by exchanging the KpnI-PstI (nucleotide positions 32 to 564) fragment of pDSVpuro with the corresponding fragment of pLTRΔpbs. pDHEneo is identical to pDneo except the point mutations in the sequences flanking the DLS region. These mutations converted the Mo-MuLV sequences in this region into new restriction sites for HindIII and EcoRI. A description of the cloning steps performed to generate this vector is available upon request. To produce pDΔpSVpuro, the enhancer-promoter sequences of U3 region in pDΔpbsSVpuro were deleted. For this purpose the 3.4 kb SacI-BamHI fragment containing 36 bp of 5' U3 region starting from SacI site and including all other vector sequences of pDΔpbsSVpuro was inserted into the SacI and BamHI sites of pTZ18 plasmid. All DNA manipulations were performed by standard procedures [ 31 ]. Analysis of integrated plasmid DNA Genomic DNA purification and hybridization were performed by standard molecular techniques [ 31 ]. DNA prepared from double-drug-resistant cell clones was used as a substrate for PCR. Integrated plasmid DNA was amplified using a 3' neo-specific sense primer T1 (5'-AGTGCAAATCCGTCGGCAT-3') and an antisense primer T2 (5'-GAGGCGGCCTCGGCCTC-3') within the SV40 early promoter. The sequences of neo gene in proviral DNA were PCR amplified using primers CND (5'-CACGCTGCCGCAAGCACTCA-3') and CNR (5'-TGGGTGGTGAGCAGCTCGCC-3'). PCR was performed in 10 mM Tris (pH 8.3), 50 mM KCl, 2 mMMgCl 2 , 200 μM each dNTP, 1 % DMSO, 100 nM primers for 20 cycles (94°C 1 min, 50°C 1 min, 72°C 8 min). The products were separated on 0.8 % agarose gel, transferred onto nylon membrane (Hybond-N, Amersham), and hybridized with neo-specific probe (150 bp SalI-ClaI fragment of pDHEneo). Probes were generated by the random-primer method with [α 32 P] dATP [ 32 ]. RT-PCR analysis Virion RNA was purified from filtered culture medium from transfected cells and used in RT-PCR assays [ 31 ]. Briefly, RNA samples were reverse-transcribed in a 20-μl reaction with Superscript II (Life Technologies), using an antisense gag-specific primer (L2) beginning at nt 613 (5'-CAAAGACATAAACAG-3'). A third of the resultant cDNA was subjected to PCR (94°C for 1 min, 50°C for 1 min, 72°C for 1 min, for 30 cycles) with AmpliTaq DNA polymerase (Perkin-Elmer), using the same primer that was used in the RT reaction and paired with a sense R-specific primer (L1) beginning at nt 1 (5'-GCGCCAGTCCTCCGA-3'). PCR products were digested with 10 units of EcoRI (Fermentas) according to the manufacturer's recommendations and analyzed by 2 % agarose gel. A GelDoc™ EQ system (Biorad) with SigmaGel v.1.0 software (Jandel Scientific) was used to quantitate the ethidium bromide fluorescence intensity of each band. Cells, DNA transfection, and virus propagation NIH3T3 (murine cell line) and GP+envAM12 (amphotropic 3T3-based packaging cell line with MLV Gag + Pol and Env genes) [ 33 ] were grown in Dulbecco's modified Eagle's medium supplemented with 10 % fetal calf serum. The cell clones producing transfected vectors were established by transfecting GP+envAM12 cells with vector plasmids using the dimethyl sulfoxide-polybrene method [ 34 ]. Puromycin-resistant cells were selected in 2.5 or 1.5 μg/ml puromycin (Sigma) for GPenv-AM12 or NIH3T3-derived cells, respectively. Geneticin selection was performed at 800 μg/ml (GP+envAM12) or 600 μg/ml (NIH3T3) of G418 (Gibco). Viral infection was performed immediately after harvesting the virus. The supernatants were harvested from 90 % confluent stable producer cell clones after 16 hour intervals and filtered through the 0.45 μm filters. Infections were performed in the presence of 8 μg/ml polybrene (Sigma) for two hours at 37°C. Puromycin- and G418-resistant cfu titers were determined using the infection of NIH3T3 cells by end-point dilution. Competing interests The authors declare that they have no competing interests. Authors' contributions SAK carried out most experiments and made substantial contributions to conception and design. AIK and ABO carried out analysis of integrated plasmid DNA by hybridization and participated in the works with cell cultures. IKF conceived of the study, participated in the design and coordination, and drafted the manuscript. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546228.xml |
545047 | Expression of vascular endothelial growth factor (VEGF)-C in preoperative biopsy specimens and metastatic foci of regional lymph nodes in submucosal gastric carcinoma | Background Vascular endothelial growth factor (VEGF)-C is implicated in lymphangiogenesis, however the exact role of VEGF-C in promoting lymphatic spread of cancer cells remains largely unknown. Methods The expression of VEGF-C was immunohistochemically determined in 97 endoscopic biopsy specimens from 46 patients with submucosal gastric carcinoma (SGC). Nodal metastases including micrometastasis and isolated tumor cells (ITC) were evaluated by immunohistochemical staining for cytokeratin in 1650 lymph nodes, and tumor cells in these metastatic nodes were also examined for VEGF-C expression. Results In biopsy samples, VEGF-C was positively detected in 21 (47%) patients. Metastases were identified in 46 (2.8%) nodes from 15 (33%) patients. Metastases were detected in 39 nodes by hematoxylin-eosin (H&E) staining and in additional 7 nodes as ITC by immunohistochemical staining. The rate of lymph node metastases was significantly correlated with VEGF-C expression in biopsy samples (p < 0.05). The positive and negative predictive values of VEGF-C in biopsy specimens for nodal metastasis were 44 %(10/21) and 80% (20/25), respectively. Among the 46 metastatic nodes, tumor cells in 29 (63%) nodes positive patients expressed VEGF-C, whereas those in 17 (37%) nodes did not. VEGF-C expression was high in macronodular foci in medullary areas, whereas more than half of ITC or micrometastasis located in peripheral sinus lacked the expression of VEGF-C. Conclusions Despite the significant correlation, immunodetcetion of VEGF-C in endoscopic biopsy specimens could not accurately predict the nodal status, and thus cannot be applied for the decision of the treatment for SGC. VEGF-C may not be essential for lymphatic transport, but rather important to develop the macronodular lesion in metastatic nodes. | Background The incidence of early gastric carcinoma defined as being confined to the mucosa or submucosal layer has increased. In Japan, endoscopic mucosal resection (EMR) is now generally accepted for intramucosal cancers that are associated with a minimal risk of regional lymph node (LN) metastasis [ 1 - 4 ]. For submucosal gastric carcinoma (SGC), however, conventional gastrectomy with complete lymph node dissection has been performed as standard treatment as the frequency of lymph node metastasis is 10–20%, which cannot be ignored clinically [ 5 - 8 ]. This indicates that the conventional operative procedure provides no benefit for the majority of patients with SGC, and thus criteria to safely avoid unnecessary lymphadenectomy for submucosal cancer need to be determined. VECF-C is known to bind VEGFR-3, which is specifically expressed on lymphatic vessels and stimulates lymphangiogenesis [ 9 , 10 ]. Many previous reports have shown that expression of VEGF-C in cancer tissues has a positive correlation with the risk of lymphatic metastasis in breast [ 11 , 12 ], lung [ 13 ], colorectal [ 14 - 17 ], pancreatic [ 18 ], prostate [ 19 ], esophageal [ 14 , 20 ] and head and neck cancers [ 21 , 22 ]. A similar tendency has been reported for gastric cancer, although a significant correlation between VEGF-C expression and the frequency of nodal metastasis is not always found [ 23 - 27 ]. Recently, small metastatic lesions have been detected genetically or immunohistochemically in various cancers, even though they were diagnosed as negative by conventional examination with H&E staining. Such lesions are designated as micrometastasis or isolated tumor cells (ITC). The biological and clinical significance of such minute nodal invasion of carcinoma cells is still controversial [ 28 - 38 ]. In this study we performed immunohistochemical staining and extensively examined VEGF-C expression in biopsy samples and metastatic lymph nodes including micrometastasis and ITC. From these data, we attempted to determine whether the detection of VEGF-C in biopsy samples could be a clinical predictor of accurate nodal status in SGC. Then, we discussed how the VEGF-C expressed in tumor cells functions in the metastatic process to regional lymph nodes. Patients and methods Forty-six patients with SGC diagnosed and treated by curative gastrectomy with standard lymph node dissection at the First Department of Surgery, Tokyo University Hospital, Tokyo, between 1994 and 2002 were included in this study. These patients were examined endoscopically prior to surgery; several pieces of tissue specimens were then sampled with routine biopsy forceps from various portions of the tumor. Formalin-fixed and paraffin-embedded sections of 97 biopsy specimens and 1650 dissected lymph nodes derived from these 46 patients were evaluated in this study. Additionally, all the resected primary tumors were histologically examined with H&E staining according to the Japanese Classification of Gastric Carcinoma [ 39 ]. Tumors were histologically classified into two types based on the predominant features: differentiated type (well and moderately differentiated adenocarcinoma) and undifferentiated type (poorly differentiated adenocarcinoma and signet ring cell carcinoma). Several discrete histological parameters, including lymphatic invasion, venous invasion and lymph node metastasis, were also evaluated. Immunohistochemical study of VEGF-C and Cytokeratin The expression of VEGF-C was investigated with immunohistochemical staining using affinity purified goat polyclonal antibodies against VEGF-C (IBL, Fujioka, Japan). Sections (3-μm thick) of biopsy samples were deparaffinized in xylene, hydrated through a graded series of ethanol, and then immersed in 3% hydrogen peroxide in 100% methanol for 30 min to inhibit endogenous peroxidase activity. To activate the antigens, the sections were boiled in 10 mM citrate buffer, pH 6.0 for 30 minutes. After being rinsed in phosphate-buffered saline (PBS), the sections were incubated with normal rabbit serum for 10 min, and then incubated overnight at 4°C in humid chambers with the primary antibody to VEGF-C at 1/30 dilution. After three washes with PBS, the sections were incubated with biotinylated rabbit anti-goat immunoglobulin for 20 minute. After washing again with PBS, the slides were treated with peroxidase-conjugated streptavidin for 20 minutes, and developed by immersion in 0.01% H 2 O 2 and 0.05% diaminobenzidine tetrahydrochloride for 3 minute. Light counterstaining with Mayer's hematoxylin was performed. The 46 lymph nodes that showed the presence of carcinoma were also evaluated for the expression of VEGF-C with the same immunostaining method. The dissected lymph nodes were fixed in 10% formalin and embedded in paraffin. From each node, one 3-μm-thick section was prepared for H&E staining, and another three serial 5-μm sections were prepared for immunohistochemical staining with CAM 5.2 (Becton Dickinson, San Jose, CA), a mouse monoclonal antibody that reacts with human cytokeratin numbers 8 and 18 [ 40 ]. The streptavidin biotin immunoperoxidase technique was used. Deparaffinized and rehydrated sections were trypsinized with 1% calcium chloride solution at 37°C for 20 minutes. After nonspecific reactions were blocked with 10% normal rabbit serum, the sections were incubated with CAM 5.2 diluted 1/6, biotinylated rabbit anti-mouse immunoglobulin, and streptavidin peroxidase. Between each two incubation steps, sections were washed carefully in phosphate buffered saline. Definition of lymph node metastasis Metastasis was defined as the presence of tumor cells, whether single or in small clusters detected by H&E or immunohistochemical staining. Metastatic lesions that were more than 2.0 mm in diameter were defined as macrometastasis, while micrometastasis was defined as a tumor deposit larger than 0.2 mm but less than 2.0 mm, and ITC was defined as a tumor deposit less than 0.2 mm in maximum diameter. Statistical analysis All statistical calculations were carried out using StatView-J 5.0 statistical software (SAS Institute, USA). The relationship between clinical and pathological characteristics of patients and the expression of VEGF-C was examined by Fisher's exact test. Differences with a p value of less than 0.05 were considered to be statistically significant. Results Nodal status including micrometastases and isolated tumor cells (ITC) in SGC Metastases were observed in 12 patients (26.1%) and 39 lymph nodes (2.4%) by H&E examination (Fig. 1-c, f ). Among these nodes, cancer cells were detected as micrometastasis (less than 2.0 mm) in 5 lymph nodes and as ITC (less than 0.2 mm) in another 5 nodes. By immunohistochemical staining with anti-cytokeratin antibody, we additionally identified such small metastatic lesions in 7 nodes (Fig. 1-d, g ). All of the 7 metastatic lesions were categorized as ITC. Four nodes were derived from 4 patients who had other metastatic nodes detected by H&E staining. Cytokeratin-positive cells were also identified in other 3 nodes from 3 patients who showed no metastatic nodes by H&E staining and were diagnosed as node negative cases. Thus, the final frequency of lymph node metastasis increased to 15 of 46 patients (33%) and 46 of 1650 lymph nodes (2.8%). Figure 1 Immunohistochemical staining of VEGF-C in biopsied specimens (upper panel) and hematoxylin-eosin (H&E) staining, immunohistochemical staining of cytokeratin and VEGF-C in metastastic lymph node (middle and lower panel). a , VEGF-C positive type in biopsied specimens. b , VEGF-C negative type in biopsied specimens. c , f , hematoxylin-eosin (H&E) staining in metastastic lymph node. d , g , immunohistochemical staining of cytokeratin in metastastic lymph node. e , VEGF-C positive type in metastastic lymph node. h , VEGF-C negative type in metastastic lymph node. Table 1 show the relationship between the exact nodal status and other clinical/pathological features. Metastases were frequently observed in tumors with deep submucosal invasion or lymphatic involvement, which were consistent with previous reports. Table 1 Nodal metastasis, including nicrometastasis/ITC and clinical and/or pathological findings Patients with lymph node metastasis positive(15) negative(31) p value Age 60< 6 16 <59 9 15 0.46 Sex Male 11 22 Female 4 9 0.87 Tumor size (cm) 3.0< 11 19 2.9> 4 12 0.42 Macroscopic type elevated 2 1 depressed 13 30 0.19 Depth of invasion sm1 3 18 sm2,3 12 13 0.02 Histological type differentiated 8 14 undifferentiated 7 17 0.6 Lymphatic involvement positive 4 2 negative 11 29 0.05 Venous involvement positive 2 2 negative 13 29 0.44 Immunohistochemical analysis of VEGF-C in biopsy and surgical specimens The biopsy specimens were divided into two categories by the staining pattern of VEGF-C, diffuse or focal staining of carcinoma cells as described previously [ 26 ]. When distinct staining of the cytoplasm was observed in the majority of tumor cells, whether diffuse or focal, these samples were categorized as VEGF-C positive in this study (Fig. 1-a ). Whereas other cases in which only a few carcinoma cells stained faintly were classified as VEGF-C negative (Fig. 1-b ). Among the 97 biopsy samples from 46 patients, carcinoma cells were contained in only one biopsy sample in 14 patients, and in 2, 3 and 4 biopsy samples in 16, 13 and 3 patients, respectively. In all of the latter cases, carcinoma cells in biopsy samples derived from different places showed exactly the same staining pattern of VEGF-C, and thus VEGF-C-positive and -negative tumors could be clearly distinguished. In biopsy specimens, VEGF-C was positively detected in 21 (46%) cases. As shown in Table 1 , the expression of VEGF-C in biopsy samples showed a significant correlation with that in surgically removed specimens (p = 0.005). However, 15 (60%) of 25 cases that were classified as VEGF-C negative in biopsy samples showed positive expression of VEGF-C in surgical specimens. In contrast, 20 of 21 cases with VEGF-C-positive biopsy samples also expressed VEGF-C in surgical specimens, indicating that positive expression of VEGF-C was mostly consistent between biopsy and surgical specimens. Thus, the immunodetection of VEGF-C in biopsy sample showed 95% of positive predictive value and 40% of negative predictive values for VEGF-C expression in primary tumor. Immunohistochemical detection of VEGF-C in biopsy specimens Nodal metastasis was detected in 10 (48%) of 21 VEGF-C-positive tumors, and the rate was significantly higher than that in VEGF-C-negative tumors as evaluated by biopsy specimens (5/25, 20%) (p = 0.047). However, the positive and negative predictive values of VEGF-C in biopsy for nodal status were 44% (10/21) and 75% (20/25), respectively, and 5 (20%) of 25 VEGF-C-negative tumors were accompanied with lymph node metastasis. Expression of VEGF-C in tumor cells in metastatic lymph nodes Table 3 shows the expression pattern of VEGF-C of tumor cells in 46 metastatic lymph nodes as well as in 23 biopsy samples in 15 patients. Interestingly, the expression of VEGF-C in metastatic tumor cells in lymph nodes was not necessarily correlated with that in biopsy samples. In 15 cases with nodal metastasis, VEGF-C was positively detected in 18 biopsy samples from 10 (67%) patients. On the other hand, VEGF-C was positive in metastatic tumor cells in 29 nodes derived from 7 (47%) patients (Fig. 1-e ), while tumor cells metastasized in 17 (37%) lymph nodes derived from 11 (73%) patients were negative for VEGF-C (Fig. 1-h ). Table 3 The location of tumor cells in metastatic nodes and VEGF-C expression in 15 node positive patients. Case VEGF-C expression definition of metastasis** Detection method* location of tumor cells biopsy specimens# metastatic nodes 1 - - ITC H.E. marginal 2 - + macrometastasis H.E. medullary + ITC H.E. marginal + macrometastasis H.E. medullary 3 - - macrometastasis H.E. marginal - macrometastasis H.E. marginal - ITC I.H.C. marginal 4 - - macrometastasis H.E. marginal - macrometastasis H.E. marginal 5 + + + macrometastasis H.E. marginal - macrometastasis H.E. marginal - macrometastasis H.E. marginal 6 + + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary - ITC I.H.C. marginal 7 + + micrometastasis H.E. medullary + ITC H.E. marginal + ITC H.E. marginal 8 + + + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + micrometastasis H.E. medullary + micrometastasis H.E. medullary 9 + - ITC H.E. marginal - ITC I.H.C. marginal 10 + + - micrometastasis H.E. marginal 11 + + + + macrometastasis H.E. medullary - micrometastasis H.E. medullary - ITC I.H.C. marginal 12 + + + + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary + macrometastasis H.E. medullary 13 - - ITC I.H.C. marginal 14 + + - ITC I.H.C. marginal 15 + - ITC I.H.C. marginal *:IHC means immunohistochemical staining with anti-cytochelatin mAb. **:Micrometastasis is defined as tumor deposit larger than 0.2 mm but less than 2.0 mm, and ITC (isolated tumor cell) is defined as tumor deposit less than 0.2 mm in the maximum diameter. Larger deposits were classified as macrometastasis. #: The number of +/- means the number of examined biopsy specimens obtained from different parts of the tumor. Among 36 nodes from 10 patients who were determined as VEGF-C-positive in biopsy samples, tumor cells located in 10 (29%) nodes from 4 (40%) patients totally lacked the expression of VEGF-C. This finding clearly indicates that carcinoma cells that highly express VEGF-C are not always preferentially transported to the regional lymph nodes, even though the expression of this lymphangiogenic factor had a positive correlation with lymph node metastasis. More interestingly, the expression of VEGF-C was strongly correlated with the size of metastatic foci and the location of carcinoma cells in metastatic nodes (Table 3 ). When carcinoma cells invaded the medullary area of lymph nodes, most of the tumor cells positively expressed VEGF-C (25/26, 96%). In contrast, the rate of VEGF-C-positive cells was markedly lower (4/20, 20%), when the carcinoma cells remained in the peripheral area of lymph nodes. Also, 22 (79%) of 28 macrometastases expressed VEGF-C, while 3 (60%) of 5 micrometastases and only 3 (25%) of 12 ITC were positive for VEGF-C. It is especially notable that all of the 7 ITC detected by immunostaining lacked expression of VEGF-C. Discussion Many cancers metastasize to regional lymph nodes, and a positive nodal status often correlates with a poor prognosis of patients. However, the mechanisms of lymphatic metastasis have not been investigated in detail. Recent studies have demonstrated that the expression of VEGF-C is enhanced in various solid tumors, suggesting the possible contribution of VEGF-C to nodal metastasis, possibly through lymphangiogenesis [ 41 , 42 ]. Number of clinical studies has shown a positive correlation between VEGF-C expression and risk of lymph node metastasis in various cancers including gastric cancer [ 11 , 12 ]. However, all of the data were obtained in surgically resected specimens, and thus can not be used for preoperative information to determine the treatment. In this study, therefore, we evaluated the expression of VEGF-C in biopsy samples in SGC. Our initial hypothesis was that VEGF-C expression can predict the accurate nodal status including micrometastasis/ITC, and thus may be useful to avoid the unnecessary gastrectomy in some SGC. Our results suggest that VEGF-C expression in biopsy specimens correlate with lymph node metastasis in SGC. However, the positive and negative predictive values were 44% and 80% respectively, and 20% of VEGF-C-negative tumors were node positive. This suggests that the immunodetection of VEGF-C in biopsy samples can not be used as clinical indicator to decide the treatment of SGC. Present study provides some interesting findings on the possible role of VEGF-C in nodal metastasis. Biopsy samples were obtained at preoperative endoscopy, fixed with formalin immediately after biopsy, and thus appear to reflect the in situ expression level of VEGF-C more precisely than surgically resected specimens. In our results, VEGF-C expression in biopsy samples showed a significant correlation with that in surgical specimens with 57% sensitivity and 91% specificity. However, more than half (60%) of the tumors categorized as VEGF-C negative in biopsy specimens were positive in surgical specimens, although VEGF-C-positive tumors in biopsy samples showed a good consistency with those in surgical specimens. This raises the possibility that VEGF-C expression may be somewhat upregulated by surgical manipulation. VEGF gene expression is regulated by a variety of stimuli, and hypoxia is known to be one of the most potent inducers of VEGF-A [ 43 , 44 ]. VEGF-C expression has also been reported to be enhanced by hypoxia in some reports [ 45 , 46 ], but not in others [ 47 , 48 ]. Although the detailed regulatory mechanisms of VEGF-C gene activation are not well understood, our results suggest a possibility that VEGF-C in surgical specimen may be induced by hypoxia during gastrectomy at least in some cases. This point should be included for the evaluation of the results in previous studies showing the positive correlation with nodal status. Nonetheless, our data showed a significant correlation of VEGF-C expression in biopsy specimens with nodal metastasis, supporting a possible role of VEGF-C in lymphatic metastasis. As with hematogeneous metastasis, lymphatic metastasis of cancer cells is considered to be divided into several steps: invasion to lymphatic capillaries, movement into the lymphatic lumen with the lymphatic stream, attachment to the subcapsular sinus of lymph nodes, and invasion into the cortex. Lymphangiogenesis means the development and proliferation of new lymphatics from host vessels, but the ability of tumor cells to induce lymphangiogenesis and the presence of intratumoral lymphatic vessels are controversial. However, most malignant tumors are known to be associated with an increased number of lymphatic vessels in the peripheral area [ 42 ]. In fact, in vivo experiments using VEGF-C-transfected tumors have shown the same histological findings [ 49 , 50 ]. Since intratumoral interstitial fluid pressure is known to be higher than that in normal tissues, the hydrostatic pressure difference appears to transport the tumor cells from inside of the tumor to the peritumoral area. Therefore, the metastasis-promoting effect has been attributed to an increase and dilatation of peritumoral lymphatic capillaries. VEGF-C may facilitate metastasis by increasing the surface area of lymphatic vessels in contact with interstitial tumor cells in the area around the primary tumor site, and thus increase the chance of these cells entering the lymphatic system. In regional lymph nodes, tumor cells are thought to reach the peripheral sinus from afferent lymphatics. In fact, many metastatic cells were detected around the sinus area unless they developed into a macronodular lesion. Recently, small lesions have been divided into two categories; micrometastasis and isolated tumor cells (ITC), which are distinguished based on their size [ 51 ]. Micrometastasis is defined as a tumor deposit larger than 0.2 mm but less than 2.0 mm, while ITC is defined as a tumor deposit less than 0.2 mm in maximum diameter. Although the biological features of these categories have not been fully clarified, they are now pathologically defined as pN1m1 and pN0, respectively. In our study, the metastatic lesions did not always express VEGF-C, and such small metastatic foci often lacked the expression of VEGF-C. Especially, ITC identified only with immunohistochemical staining are totally negative for VEGF-C. In addition, in 4 tumors with lymphatic invasion, none of the tumor cells located in the lymphatic vessels in the primary tumor expressed VEGF-C (data not presented). These unexpected results suggest that expression of VEGF-C in tumor cells is not relevant to the transportation to regional nodes once they enter lymphatic vessels. In contrast, most of the macrometastases or cancer cells invading the medullary area of metastatic nodes highly expressed VEGF-C. This phenomenon was quite interesting, though not fully explained by today's knowledge. This may suggest that proliferation and invasion in the internal area of metastatic nodes may partially require VEGF-C expression in tumor cells. Thus far, there is no definite report on the effects of VEGF-C on tumor cells. The VEGF-receptor 3 (VEGFR-3), a specific ligand of VEGF-C, was expressed only on certain tumor cells [ 52 - 54 ] and not on others. We tried to examine the expression of VEGF-C receptor in these gastric cancers using a polyclonal antibody to VEGFR-3, but could not detect positive staining in any case (data not shown). Thus, it seems to be unlikely that VEGF-C directly affects the behavior of gastric cancer cells. However, it remains a possibility that VEGF-C secreted from tumor cells may act on intranodal lymphatic endothelial cells or other interstitial cells and create favorable conditions for tumor cell growth or invasion in lymph nodes. In summary, our retrospective study demonstrated that VEGF-C expression in tumor cells in biopsy specimens was significantly correlated with lymphatic metastasis in SGC, although the accuracy was not high enough to be used for clinical indicator. Metastatic tumor cells in micrometastasis or ITC located in marginal sinus often lacked the expression of VEGF-C, whereas macrometastasis located in the medullary area in metastatic nodes highly express VEGF-C. This suggests a possibility that expression of VEGF-C is not essential for lymphatic transport from primary tumor, but rather important to develop the macronodular lesion in metastatic lymph nodes. Competing Interests The author(s) declare that they have no competing interests. Authors' contributions MI . Conceived of the study and wrote the original version of the manuscript. JK . Carried out the literature search and helped in drafting the manuscript. SK . Collected clinical and pathologic data and participated in manuscript preparation HN Helped to shape the idea for the study coordinated the study and edited the manuscript. All authors have read and approved the final manuscript. Table 2 Relationship between the expression of VEGF-C in surgical and biopsy specimens Surgical specimens Nodal metastasis positive (35) negative (11) p value positive (15) negative (31) p value Biopsy specimens positive (21) 20 1 10 11 negative (25) 15 10 0.005 5 20 0.047 Table 4 The expression of VEGF-C in surgical specimens and nodal metastasis Positive (35) Negative (11) p value Lymph node metastasis positive 14 1 negative 21 10 0.05 | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545047.xml |
544403 | Scaling Up AIDS Treatment: What Is the Potential Impact and What Are the Risks? | Lamptey and Wilson discuss the implications of a new study showing that combining treatment with prevention is the best approach to tackling the HIV pandemic. | There has been a recent and dramatic rise in global funding for HIV/AIDS, from US$2.1 billion in 2001 to US$6.1 billion in 2004 [ 1 ], thanks to several new funding mechanisms ( Box 1 ). These funds, coupled with reduced drug costs, make it feasible to roll out antiretroviral therapy (ART) even in resource-poor settings. Nevertheless, the total number of people living with HIV rose in 2004 to reach its highest level ever: an estimated 39.4 million people are living with the virus, including 4.9 million who acquired it in 2004 [ 1 ]. Therefore, the debate over the appropriate distribution of money between prevention efforts (such as voluntary counseling and testing [VCT], or behavior change) and treatment efforts (the provision of ART) is now more topical than ever. Box 1. Initiatives to Fund ART The WHO “3 by 5” Initiative: This initiative aims to place 3 million people in low- and middle-income countries on ART by the end of 2005. The US President's Emergency Plan for HIV/AIDS Relief: This initiative aims to treat 2 million HIV-infected people with ART, to prevent 7 million new infections, and to care for 10 million HIV-infected individuals and AIDS orphans in five years (2004–2009). The Global Fund to Fight AIDS, Tuberculosis, and Malaria: In the five years following its inception (2002–2007), the Global Fund aims to provide 1.6 million people with ART and 52 million people with VCT, and to support more than 1 million orphans with medical services, education, and community care. Balancing Prevention and Treatment The scale of the proposed increase in the number of patients receiving ART raises numerous questions about the treatment itself. Which drugs will be used? How much will it cost? How will their quality be monitored and assured? How will they be distributed? Who will be eligible? How will the desired level of treatment be sustained? Is there adequate infrastructure and human resources to support the expanded services? The commitment of substantial funding to treatment in resource-poor countries also has implications for the prevention efforts in those same countries. In many Western countries and Brazil (the sources of the majority of the available data on the subject), the impressive drop in mortality due to HIV following increased access to ART is coupled with a disheartening rise in the number of new cases of HIV, as emphasis and funding are shifted from prevention to treatment [ 2 ]. Countries in which this pattern has been seen are evidence of the pitfalls of failing to adapt prevention efforts once life-extending treatment becomes widely available. Of course, prevention and treatment are not mutually exclusive. Successful prevention efforts mean fewer patients will need the costly drug treatment programs, helping extend the sustainability of ART. In turn, the success of ART in prolonging healthy living helps prevention efforts by reducing the stigma associated with self-education and responsible behaviors. Measuring Prevention and Treatment Effects In their study in the January 2005 issue of PLoS Medicine , “Integrating HIV Prevention and Treatment: From Slogans to Impact,” Salomon and colleagues use mathematical modeling to assess the epidemiologic impact of treatment and prevention efforts, and to quantify the opportunities and potential risks of large-scale treatment roll-out. Using a variety of different scenarios, they propose methods for establishing the most effective balance between spending on prevention and spending on treatment. Modeling is a technique used by many scientists, including epidemiologists and statisticians, to create a mathematical equation that can be used to determine which variables affect an outcome of interest, and to what extent. Once the influential variables are determined, a baseline model is established that includes those variables and reflects their relative importance to the outcome. The effect of changing the value of any of these variables, or several of them, can then be tested, and new outcomes projected. HIV modeling is inexact and requires far better data but can nevertheless provide important insights. Salomon and colleagues used mathematical modeling to assess the effect of changing aspects of the HIV/AIDS “equation” on the future course of the HIV/AIDS epidemic. First, a baseline model was created to fit expected HIV/AIDS projections for the year 2020 if there were to be no change in the current epidemiologic trends—no ART scale-up, and no changes in prevention efforts or behavior. Heterosexual contact is the predominant mode of HIV transmission across Africa, and Salomon and colleagues' study modeled the disease only within the heterosexual population. The model was also tailored to take into account epidemiologic, demographic, and sociologic patterns in the eastern, central/western and southern regions of Africa. Using the baseline models tailored to each region, the effects of prevention and treatment efforts were then measured. Two treatment-centered scenarios were tested in which the World Health Organization's “3 by 5” initiative (see Box 1 ) was achieved. In these treatment-centered scenarios, the reduction of transmissibility, the number of partners of each patient, and condom use were either optimal (reduced transmissibility, reduced partners, and increased condom use) or less than optimal. The prevention-centered scenario tested the impact of a comprehensive package of 12 prevention tools (such as VCT and peer counseling for sex workers), modeling only partial effectiveness at the population level, to reflect weaker political and social support for HIV control efforts. Finally, combined response scenarios were tested. In the first scenario, treatment efforts strengthened prevention efforts as, for example, when the availability of ART increases people's willingness to undergo testing. In the second, an emphasis on treatment led to less effective implementation of prevention efforts. Baseline projections in Salomon and colleagues' study showed that without any behavioral change or ART scale-up, the HIV/AIDS prevalence rate would remain relatively stable, but the number of new infections would increase by 52.3 million by 2020. Treatment-centered scenarios reduced the total number of new infections through 2020 by a maximum of 3 million, or 6%, while indicating that the number of AIDS deaths through 2020 would decline by 13%, to 32.4 million. A prevention-centered strategy would provide greater reductions in incidence (36%) and similar mortality reductions by 2020, but more modest mortality benefits over the next five to ten years. The scenarios in which all of these statistics were most improved, however, were those that combined both prevention and treatment efforts. In the scenario in which treatment enhanced prevention, Salomon and colleagues projected 29 million averted infections (55%) and 10 million averted deaths (27%) through the year 2020. However, if a narrow focus on treatment scale-up leads to reduced effectiveness of prevention efforts, the benefits of a combined response would be considerably smaller—9 million averted infections (17%) and 6 million averted deaths (16%) ( Figure 1 ). Figure 1 Projected New Adult Infections and Total Adult Deaths, in Millions, to 2020 This graph represents projections through 2020, and, when there was a choice, highlights the more successful iteration of a model. The treatment-centered response, therefore, shows data from the optimal-effects model, and the combined response data reflect the optimistic model. Combining treatment with effective prevention efforts could reduce the resource needs for treatment dramatically in the long term. In the various scenarios the numbers of people being treated in 2020 ranges from 9.2 million in a treatment-only scenario with mixed effects, to 4.2 million in a combined response with positive treatment–prevention synergies. Moving Forward The authors have demonstrated through mathematical modeling that the integration of treatment and prevention is epidemiologically sound. However, an integrated and comprehensive program ( Figure 2 ) is not only logical but makes sense from the service delivery point of view: it can be cost-effective and ideal for the community. Figure 2 Components of an Integrated Comprehensive HIV/AIDS Program PMTCT, prevention of mother-to-child transmission; STD, sexually transmitted disease. Effective prevention makes treatment more affordable and sustainable. Effective prevention can lead to a substantial reduction in the number of new infections and therefore ultimately will lead to a reduction in the number of people who will need treatment. The reduction of adult HIV/AIDS prevalence in Uganda from 18.5% to 6% over the last several years has reduced the number of those eventually needing treatment by nearly 68% [ 3 ]. Unless the incidence of HIV is sharply reduced, HIV treatment will not be able to keep pace with all those who will need therapy [ 4 ]. Salomon and colleagues' reaffirmation that only effective prevention will make treatment affordable is critically important. Successful treatment and care can make prevention more acceptable and effective. Widespread access to treatment could bring millions of people into health-care settings, providing new opportunities for health-care workers to deliver and reinforce HIV prevention messages and interventions [ 4 ]. Improved access to HIV testing provides an entry point to both prevention and treatment services and provides a unique opportunity to identify and target the infected, vulnerable, and uninfected with more appropriate interventions. All health-care settings, including HIV treatment sites, should deliver HIV prevention services [ 4 ]. Prevention can make treatment more accessible. The early establishment of community-based prevention services in rural Ghana was instrumental in reducing the stigma of AIDS and improving the knowledge and attitude of the community prior to the development of ART and VCT services (K. Torpey, personal communication). This process also made it easier for community and implementing agencies to identify and refer patients needing treatment services. Expanded care and prevention activities have synergistic effects. Continued effective treatment, care, and prevention programs will reduce the number of orphans and vulnerable children, reduce mother to child transmission of the virus, and improve the lives of families and the strength of communities. Integration ensures that prevention activities are not neglected. The world has a unique opportunity, as ART services are launched and expanded, to simultaneously bolster prevention efforts [ 4 ]. Experience in the United States indicates that availability of treatment can lead to increased risk behavior [ 5 ]. In addition, the improvement in the health, well-being, and longevity of people living with AIDS could increase the opportunities for HIV transmission. Integration can help reduce these potential negative impacts of treatment. Integration can provide opportunities to address vulnerable groups more effectively. A commitment to providing large-scale treatment helps to focus attention on communities at greatest risk, particularly in lower prevalence contexts. This provides an opportunity to address the prevention and treatment needs of vulnerable groups more effectively. Treatment resources can help improve infrastructure for prevention and other health services. The training of health providers and improvements in laboratory services, pharmacy, logistics, commodity management, and health information systems can benefit both treatment and prevention services. Further, in many countries, a large number of health-care workers are themselves infected. Treatment can help to preserve the lives and productivity of these critically needed AIDS prevention and treatment workers, as well as those of other health professionals. A long-term decline in AIDS deaths may be preventing new infections. The short-term decline in AIDS deaths is driven by effective care and treatment programs, but a long-term decline may be driven by the prevention of new infections. Integrated and comprehensive strategies are more likely to lead to affordable, sustainable programs. Success requires dramatic expansion of both ART and prevention. Globally, fewer than one in five people at high risk of infection have access to proven HIV prevention interventions [ 6 ] and less than 10% have access to ART [ 1 ]. Unless there is a substantial increase in commitment and resources for both prevention and ART, efforts to control HIV/AIDS and mitigate its impact will only meet with partial and limited success. In addition, to increase resources, intensified commitment is required to ensure every opportunity is taken to integrate prevention and treatment. Future analysis and debate should move from comparisons of prevention and treatment priorities to a sustained analysis of how we can reciprocally integrate and strengthen prevention and care and use every opportunity provided by one to reinforce the other. We must focus on the development of training, monitoring, and quality assurance systems that ensure that prevention and care are integrated whenever possible. The results of Salomon and colleagues' model need to be validated. Further operational research is needed to validate the findings of this study. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544403.xml |
545053 | Protein secretion in Lactococcus lactis : an efficient way to increase the overall heterologous protein production | Lactococcus lactis , the model lactic acid bacterium (LAB), is a food grade and well-characterized Gram positive bacterium. It is a good candidate for heterologous protein delivery in foodstuff or in the digestive tract. L. lactis can also be used as a protein producer in fermentor. Many heterologous proteins have already been produced in L. lactis but only few reports allow comparing production yields for a given protein either produced intracellularly or secreted in the medium. Here, we review several works evaluating the influence of the localization on the production yields of several heterologous proteins produced in L. lactis . The questions of size limits, conformation, and proteolysis are addressed and discussed with regard to protein yields. These data show that i) secretion is preferable to cytoplasmic production; ii) secretion enhancement (by signal peptide and propeptide optimization) results in increased production yield; iii) protein conformation rather than protein size can impair secretion and thus alter production yields; and iv) fusion of a stable protein can stabilize labile proteins. The role of intracellular proteolysis on heterologous cytoplasmic proteins and precursors is discussed. The new challenges now are the development of food grade systems and the identification and optimization of host factors affecting heterologous protein production not only in L. lactis , but also in other LAB species. | Introduction Lactic Acid Bacteria (LAB) are anaerobic Gram positive bacteria with a GRAS (Generally Regarded As Safe) status. They are also food grade bacteria, and therefore, they can be used for the delivery of proteins of interest in foodstuff or in the digestive tract. A last advantage compared to other well-known protein producers is that L. lactis does not produce LPS or any proteases as Escherichia coli or Bacillus subtilis do, respectively. In the last two decades, genetic tools for the model LAB, Lactococcus lactis , were developed: transformation protocols, cloning- or screening-vectors [ 1 , 2 ], and mutagenesis systems [ 3 ] are now available. Moreover L. lactis genome is entirely sequenced [ 4 ]. Many protein expression- and targeting-systems have also been designed for L. lactis [ 5 - 7 ]. These systems have been used to engineer L. lactis for the intra- or extra-cellular production of numerous proteins of viral, bacterial or eukaryotic origins (Table 1 ). To produce a protein of interest in fermentors, secretion is generally preferred to cytoplasmic production because it allows continuous culture and simplifies purification. To use L. lactis as a protein delivery vehicle in the digestive tract of humans or animals, secretion is also preferable because it facilitates interaction between the protein (e.g. enzyme or antigen) and its target (substrate or immune system). Table 1 Heterologous proteins produced in Lactococcus lactis . Proteins Gene Origin Location References Reporter Nuc nuc Staphylococcus aureus Cytoplasmic / secreted / anchored [6, 16] β-lactamase bla Escherichia coli secreted [44] β-galactosidase β - gal Clostridium acetobutylicum cytoplasmic [45] lactamase lacL , lacM Leuconostoc mesenteroides cytoplasmic [46] α-amylase amyS Geobacillus ( formerly Bacillus ) stearothermophilus secreted [47] [18] α-amylase amyL Bacillus licheniformis secreted [48] Chloramphenicol Acetyl Transferase cat - 86 Bacillus pumilus cytoplasmic [49] M6 Streptococcus pyogenes anchored [12] Green fluorescent protein gfp Aequoria victoria (jellyfish) cytoplasmic [50] luciferase luxAB Vibrio harveyi cytoplasmic [51] luciferase Vf lux Vibrio fischeri cytoplasmic [52] Streptavidin SA Streptomyces avidinii anchored [11] β-glucuronidase gus Escherichia coli cytoplasmic [53] Bacterial antigens L7/L12 L7/L12 Brucella abortus Cytoplasmic/secreted/anchored [19] Urease subunit B Helicobacter pilori secreted [54] TTFC ttfc Clostridium tetani secreted [55] Eukaryotic antigen GLURP-MSP3 fusion protein Plasmodium falciparum secreted [56] Viral antigens E7 E7 HPV type-16 cytoplasmic/secreted/anchored [20] [57] NSP4 NSP4 Bovine coronavirus cytoplasmic [29] BCV epitope BCV Bovine coronavirus secreted [58] VP8 subunit of VP4 VP8* rotavirus secreted [59] Interleukins IL-2 IL-2 Mouse secreted [60] IL-6 IL-6 Mouse secreted [61] IL-10 IL-10 Mouse secreted [21] IL-12 IL-12 Mouse Secreted [22] IFN-ω IFN-ω Ovine secreted [5] Allergens BLG Blg Bovine cytoplasmic/secreted [13, 30, 36] Epitope Blg41–60 Bovine secreted Virulence factors Fibronectin binding protein A fnbpA Staphylococcus aureus anchored [62] Clumping factor A clfA Staphylococcus aureus anchored [63] Clumping factor A and B clfB Staphylococcus aureus anchored [64] serine-aspartate repeat protein sdrE Staphylococcus aureus anchored [64] Protein A spA Staphylococcus aureus anchored [11] Enterotoxin A sea Staphylococcus aureus secreted C. Charlier (a) Unpublished results Aggregation substance asc10 Enterococcus faecalis anchored [65] Capsular polysaccharides cps genes Streptococcus pneumoniae CPS excreted [66] Internalin inlA Listeria monocytogenes anchored V. Guimarães (b) Unpublished results Bacteriocins ABP-118 abp118 Lactobacillus salivarius subsp. salivarius secreted [67] Enterocin A ent genes Enterococcus faecium secreted [68] Pediocin PA-1 ped genes Pediococcus acidilactici secreted [68] colicin V Escherichia coli secreted [69] Enzymes heat-stable alpha-glucosidase malA Sulfolobus solfataricus cytoplasmic [70] Bacteriophage lytic enzyme ply 118 Listeria monocytogenes bacteriophage secreted [71] lysozyme hel Hen egg white cytoplasmic [72] Neutral protease npr Bacillus subtilis secreted [73] Aminopeptidase N pepN Lactobacillus helveticus secreted [74] Cell Surface Protease prtB Lactobacillus delbrueckii subsp. bulgaricus anchored [13] Dextrane sucrase dsrD Leuconostoc mesenteroides secreted [28] Streptodornase sdc Streptococcus equisimilis secreted [75] prochymosin PC Bovine secreted [76] lipase lip Staphylococcus hyicus secreted [77] plasmin Bovine secreted [78] others F18 fimbrial adhesin (receptor binding domain) fedF Escherichia coli Secreted / anchored [27] S-layer protein slpH Lactobacillus helveticus cell wall associated [79] (a) : Laboratoire de Microbiologie UMR1253 INRA Agrocampus, 65 rue de Saint Brieuc CS84215, 35042 Rennes cedex (b) : Unité de Recherches Laitières et de Génétique Appliquée, Institut National de la Recherche Agronomique, Domaine de Vilvert, 78352 Jouy en Josas Cedex, France In LAB, like in other Gram positive bacteria, secreted proteins are synthesized as a precursor containing an N-terminal extension called the signal peptide (SP) and the mature moiety of the protein. Precursors are recognized by the host secretion machinery and translocated across the cytoplasmic membrane (early steps). The SP is then cleaved and degraded, and the mature protein is released in the culture supernatant (late steps). Sometimes, secreted proteins require subsequent folding and maturation steps to acquire their active conformation [ 8 ]. In most of the works describing heterologous protein production by recombinant lactococci, only one cellular-location (i.e. cytoplasm, external media or surface anchored) is described. Only a few works report the production of a given protein in different locations using the same backbone vector, the same induction level and or promoter strength, allowing thus a rigorous comparison of the production yields of cytoplasmic and secreted forms. Here, six examples of different heterologous proteins produced in L. lactis in both secreted and cytoplasmic forms are reviewed and discussed. Our major conclusion is that the best production yields are observed in most of these cases with secretion (up to five-fold higher than with cytoplasmic production). Moreover, engineering the expression cassette to enhance the secretion efficiency (SE, proportion of the total protein detected as mature form in the supernatant) resulted in increased overall amounts of the protein. L. lactis is able to secrete proteins ranging from low-(< 10 kDa) to high-(> 160 kDa) molecular mass through a Sec-dependant pathway. Altogether, these observations suggest that i) heterologous proteins produced in L. lactis are prone to intracellular degradation whereas secretion allows the precursor to escape proteolysis, and ii) conformation rather than protein size is the predominant feature that can impair SE. New perspectives are now opened in the studies of heterologous protein production in L. lactis . Indeed, there is a need for food grade systems and for a better understanding of the host factors influencing heterologous protein secretion in L. lactis . For example, HtrA-mediated proteolysis (HtrA is the unique housekeeping protease at the cell surface) is now well-characterized in L. lactis [ 9 ] and can be overcome by use of a htrA L. lactis strain designed for stable heterologous protein secretion [ 10 ]. However, intracellular proteolysis (involving Clp complex -the major cytoplasmic housekeeping protease-, and probably other cellular components) remains poorly understood and is also discussed here. Get out to get more Genetic tools to target a given protein in different cellular compartments were developed using several reporter proteins [ 6 , 11 - 13 ] (Table 1 ). The staphylococcal nuclease (Nuc) is a well-characterized secreted protein whose activity is readily detectable by petri plate assay and it has been used as a reporter protein for secretion studies in several Gram positive hosts [ 14 - 16 ]. In L. lactis , Nuc was used to develop protein targeting- [ 6 ] and SP screening-systems [ 1 , 2 ]. Nuc was chosen to develop the pCYT and pSEC vectors for controlled production in L. lactis of cytoplasmic or secreted forms of a protein of interest, respectively (Fig. 1 ) [ 5 ]. The pCYT and pSEC plasmids, where expression is controlled by a nisin inducible promoter, should be used in L. lactis NZ9000 (hereafter referred to as NZ) strain bearing a nisR , K chromosomal cassette, required for the nisin signal transduction [ 17 ]. In each case described below, protein sample concentration was adjusted to the cell density of the producing culture (for details see [ 18 ]). At similar induction levels in lactococcal strains containing pCYT:Nuc and pSEC:Nuc vectors, the highest production yields were observed with the secreted Nuc form (Table 2 ). Similar results were obtained with constitutive nuc expression cassettes for cytoplasmic and secreted forms. Nuc was the first heterologous protein where highest protein yields were obtained with the secreted form. Figure 1 Schematic representation of Nuc cassettes for controlled and targeted production in L. lactis. For details about plasmid constructions and contents see Bermúdez-Humarán et al. (2003) [5]. Plasmid backbone is a derivative of the rolling circle plasmid pWVO1, an E. coli -Gram positive shuttle vector. Arrows (1) indicate the presence of the nisin-inducible promoter (P nisA ); solid vertical bars (2) indicate the Ribosome Binding Site of the usp45 gene; the striped bar indicate signal peptide of the usp45 gene (SP Usp ); the white bar indicates the insertion of LEISSTCDA synthetic propeptide [18]; dark gray bars indicates Nuc mature coding sequence; stem-loop structures indicate trpA transcription terminators (not to scale). A Nsi I restriction site comprises the ATG start codon (in pCYT) or the last two residues of SP Usp (pSEC) and allows a simple and one-step cloning of the cassettes corresponding to the mature proteins for cytoplasmic production (pCYT) or secretion (pSEC). Table 2 Comparison of the protein yields in secreted vs cytoplasmic production. Protein Quantification of the secreted form 1 Quantification of the cytoplasmic form 1 Ratio sec/cyto References Nuc 20 mg/L 3 mg/L 6 [5] L7/L12 3 mg/L 0.5 mg/L 6 [19] E7 (expo)* nd nd 2 to 3 [20] E7 (stat)* nd nd > 10 [20] IFN-ω 309 mg/L 159 mg/L 2 [5] 1: protein samples were adjusted to the cell density and protein quantification was performed as described in the references either by western blot or by ELISA. *: E7 was not quantified but ratio was calculated by scanning the western blot signals and comparing their intensity as described in the corresponding reference. nd: not determined Similar results were obtained for the production of a Brucella abortus ribosomal protein. B. abortus is a facultative intracellular Gram negative bacterial pathogen that infects human and animals by entry through the digestive tract. The immunogenic B. abortus ribosomal protein L7/L12 is a promising candidate for the development of oral live vaccines against brucellosis using L. lactis as a delivery vector. L7/L12 was produced in L. lactis using pCYT and pSEC vectors [ 19 ]. Similarly to Nuc production, the production yield of secreted L7/L12 was reproducibly and significantly higher than that of the cytoplasmic form (Table 2 ). Another example of higher protein yields in secreted vs cytoplasmic form is the production the human papillomavirus type 16 (HPV-16) E7 antigen, a good candidate for the development of therapeutic vaccines against HPV-16 induced cervical cancer. The E7 protein is constitutively produced in cervical carcinomas and interacts with several cell compounds. E7 was produced in a cytoplasmic and a secreted form in L. lactis [ 20 ]. Using similar induction level in exponential phase cultures, E7 production was higher for the secreted form than for the cytoplasmic form (Table 2 ). This difference was even higher when induction occurred in late-exponential phase, where intracellular E7 was detected at only trace amount whereas secreted E7 was accumulated in NZ(pSEC:E7) culture supernatant (see below). Thus, production of E7 clearly illustrates the fact that secretion results in higher yields in L. lactis . Production of ovine interferon omega (IFN-ω) further illustrates this observation. In the case of poorly immunogenic antigens, co-delivery of an immuno-stimulator protein can enhance the immune response of the host. In order to optimize the use of lactococci as live vaccines, the production of cytokines was investigated in L. lactis [ 5 , 21 , 22 ]. IFN-ω is a cytokine able to confer resistance to enteric viruses in the digestive tract by reduction of viral penetration and by inhibition of intracellular multiplication of the viruses. Delivery of ovine IFN-ω in the digestive tract by recombinant L. lactis strains could therefore induce anti-viral resistance and could protect the enterocytes. Ovine IFN-ω cDNA was cloned into pCYT and pSEC plasmids for intracellular (pCYT:IFN) and secreted (pSEC:IFN) production respectively [ 5 ]. Induction of recombinant NZ(pCYT:IFN) and NZ(pSEC:IFN) strains were performed at equal level and IFN-ω production was measured. The levels of IFN-ω activity showed that i) an active form of IFN-ω was produced in both strains, and ii) the activity of IFN-ω found in the supernatant and cell fractions of NZ(pSEC:IFN) strain was about two-fold higher than that observed for the cytoplasmic form (Table 2 ). Similarly to what was observed for Nuc and E7, secretion leads to higher heterologous protein yields. Better secretion for better yields L. lactis has been engineered to secrete of a wide variety of heterologous proteins from bacterial, viral or eukaryotic origins (Table 1 ). There are reports about secretion bottlenecks and biotechnological tools for heterologous secretion in model bacteria such as Escherichia coli and Bacillus subtilis [ 23 , 24 ], but only few data are available concerning this aspect in L. lactis . Protein size, nature of the SP and presence of a propeptide are parameters that may interfere with protein secretion. Some data available about these features are compiled here. To optimize secretion and thus production yields, the nature of the SP was the first parameter to modify on heterologous precursor as previously shown using Nuc as a reporter protein. The replacement of the native staphylococcal SP Nuc by the homologous lactococcal SP Usp45 to direct the secretion of Nuc in L. lactis led to an increased SE [ 25 ] (Table 3 ). On the other hand, the replacement of SP Nuc by SP Usp45 did not enhance the SE of NucT (a truncated mature moiety of Nuc devoid of N-terminal propeptide) suggesting the importance of the propeptide in the SE for Nuc [ 25 ] (Table 3 ). However, in several cases, the use of a homologous SP (and especially SP Usp45 ) allows a better SE compared to a heterologous one. Screening vectors were thus developed to search for new homologous secretion signals in L. lactis [ 1 , 2 ]. These screening works offer now a panel of SPs that are suitable for heterologous secretion. However, when compared to SP Usp45, the newly described SPs were less efficient to direct secretion of Nuc [ 1 ]. Even after a direct mutagenesis on SP310, one of these new SPs identified using a screening strategy [ 1 ], the enhanced SE was still lower than the one measured with SP Usp45 [ 26 ]. However, a recent study by Lindholm et al. showed that a Lactobacillus brevis SP (originated from a S-layer protein) drove the secretion of the E. coli FedF adhesin more efficiently than SP Usp45 [ 27 ]. High SE might thus result, at least in part, from good adequacy between the mature protein and the SP used to direct secretion. Table 3 Effect of the signal peptide and of the insertion of the LEISSTCDA synthetic propeptide on the secretion efficiency. Protein SE a with SP Nuc SE with SP Usp45 Reference Nuc 60 % >95 % [25] NucT 30 % 30 % [25] Protein SE without LEISS SE with LEISS Reference Nuc 60 % 80 % [18] NucT 30 % 90 % [25] L7/L12 35 % 50 % [19] AmyS b + +++ [18] a : SE, secretion efficiency is the proportion of total protein which is present in the mature secreted form. b : SE was not determined by western blot and immuno revelation and thus could not be quantified but the activity plate assay demonstrated a clear secretion enhancement (+ to +++) with LEISS. The fusion of a short synthetic propeptide between the SP and the mature moiety is another innovative biotechnological tool to enhance protein secretion. One such propeptide (composed of nine amino acid residues, LEISSTCDA) was developed and was shown to enhance the SE of several heterologous proteins in L. lactis : NucB, NucT, (Table 3 ) [ 18 ], the B. abortus L7/L12 antigen (Table 3 ) [ 19 ], and the α-amylase of Geobacillus stearothermophilus (Table 3 ) [ 18 ]. Directed mutagenesis experiments demonstrated that the positive effect of LEISSTCDA on protein secretion was due to the insertion of negatively charged residues in the N-terminus of the mature moiety [ 25 ]. Furthermore, the enhancement effect does not depend on the nature of the SP, since the secretion of NucB fused to either SP Nuc or SP Usp45 was enhanced by LEISSTCDA insertion [ 25 ]. Strikingly, the enhancement of SE was reproducibly accompanied by an overall increase of protein yields as determined in Western blot experiments. This observation suggests that heterologous precursors are degraded by intracellular proteases when they are not efficiently secreted and that a higher secretion could be a way to escape proteolysis. Protein conformation rather than protein size can impair the heterologous protein secretion in L. lactis Proteins with molecular mass ranging from 165 kDa (size of DsrD, the Leuconostoc mesenteroides dextransucrase, [ 28 ]) to 9.8 kDa (size of Afp1, a Streptomyces tendae anti-fungal protein; Freitas et al., submitted) have been successfully secreted in L. lactis . This suggests that protein size is not a serious bottleneck for heterologous protein secretion in L. lactis . In contrast to protein size, conformation may be a major problem for heterologous secretion in L. lactis as illustrated by some recent examples. The first example is the production of the non-structural protein 4 (NSP4) of the bovine rotavirus, the major etiologic agent of severe diarrhea in young cattle. In order to develop live vaccines against this virus, the NSP4 antigen was successfully produced in L. lactis [ 29 ]. Derivatives of pCYT and pSEC plasmids were constructed to target NSP4 into cytoplasmic or extracellular location. The highest level of production was obtained with the secreted form. However, no secreted NSP4 was detected in the supernatant and both SP Usp45 -NSP4 precursor and NSP4 mature protein were detected in the cell fraction. Two degradation products were detected in addition to the NSP4 precursor and mature protein. These results suggest that the cytoplasmic form of NSP4 was probably totally degraded inside the cell whereas fusion to the SP Usp45 protected NSP4 protein against intracellular proteolysis. Similar results were obtained when pCYT and pSEC vectors were used to produce the B. abortus GroEL chaperone protein: only pSEC:GroEL plasmid was obtained and subsequently the fusion SP Usp45 :GroEL was detected in Western blot experiments (V. Azevedo, unpublished data). In this case, B. abortus GroEL is likely to interact with lactococcal cytoplasmic proteins leading to severe cellular defects and thus to a lethal phenotype. On the other hand, fusion of SP Usp to GroEL might keep the chimeric protein in an unfolded and/or inactive state allowing thus its heterologous production. Another example is the production of the bovine β-lactoglobulin (BLG) in L. lactis [ 30 , 31 ]. BLG, a 162 amino acid residues globular protein, is the dominant allergen in cow's milk and was produced in L. lactis to test the immunomodulation of the allergenic response in mice when BLG is delivered by a bacterial vector [ 30 ]. Western blot and ELISA showed that BLG production was significantly higher when BLG was fused to SP Usp45 although the SE was very low, with no detectable BLG in the supernatant of pSEC:BLG strains [ 30 ]. Further studies revealed that a fusion between the LEISS propeptide and BLG could not enhance the SE of BLG above ~5%, as determined by ELISA [ 31 ]. For rotavirus NSP4, B. abortus GroEL, and BLG (which are medium-sized compared to DsrD or Afp1), either very low secretion yields or absence of secretion was observed in L. lactis . In all cases, fusion to a SP stabilizes heterologous protein production even though they are not efficiently secreted. These results could be due either to the SP itself that reportedly acts as an intramolecular chaperone or to the protection of the chimeric precursor from intracellular proteolysis by the cytoplasmic chaperones of the Sec-machinery. GroEL (a cytoplasmic chaperone), NSP4 (a structural protein), and BLG (a globular protein) have dramatically different primary sequences. A higher affinity of intracellular housekeeping proteases for these particular sequences cannot be hypothesized since the fusion of a SP leads to the stabilization of the protein. Change of conformation is therefore the predominant criterion involved in the stabilization of the precursors and the higher yields observed. On the other hand, these proteins might undergo rapid folding right after their synthesis, which interferes with (or hampers) the secretion process. Such interferences between protein conformation and SE were previously shown in E. coli and B. subtilis [ 32 , 33 ]. Altogether, these results suggest that protein conformation rather than protein size is a major problem for heterologous protein secretion in L. lactis as well. A labile protein can be stabilized by fusion to a stable protein It was clearly demonstrated that the secreted form of E7, a reportedly labile protein, can be stabilized by fusion to Nuc [ 20 , 34 ]. Nuc is reportedly a stable protein and its use, as a fusion partner, does not affect its enzymatic activity. The production of the resulting chimerical protein is thus easy to follow. The cytoplasmic form of E7 was stabilized by the fusion to Nuc even when the production was induced in stationary phase (Fig. 2A ), whereas cytoplasmic E7 alone was degraded (see below; Fig. 3 ). Thus, fusion to the stable Nuc could rescue E7 production in L. lactis and allowed higher protein yields compared to E7 alone [ 20 ]. Stabilization by fusion to Nuc was observed for several secreted proteins as well. First, a Nuc-E7 fusion on a pSEC backbone resulted in higher production yield although the SE was altered (Fig. 2B ). Fusion to the synthetic propeptide LEISSTCDA in a pSEC:LEISS:Nuc:E7 construction restored an efficient secretion yield [ 34 ]. Second, in an attempt to increase the protein yield of the secreted L7/L12, a fusion to Nuc (pSEC:Nuc:L7/L12) resulted in a 2.5-fold increase in production yield (Fig. 2B ) [ 19 ]. Recent results concerning the production of BLG provide a third example of yield enhancement by fusion to Nuc. A pSEC:Nuc:BLG construction allowed a 2-fold increase in BLG yields compared to pSEC:BLG [ 31 ]. These results show that Nuc is a stable carrier protein and has a protective effect on labile heterologous chimerical proteins by reducing its sensitivity to intracellular proteolysis. To our knowledge, Nuc is the fusion partner most commonly tested so far for stabilization in L. lactis . Bernasconi et al (2002) fused the Lactobacillus bulgaricus proteinase PrtB to BLG, which was subsequently stabilized by the PrtB carrier [ 13 ]. It is thus difficult to postulate any rule concerning the stabilization effect. Different results (i.e. no stabilization) could perhaps be observed with a different partner and thus could help to determine the mechanism of the stabilization effect. In biotechnological use of recombinant L. lactis strains for protein production, fusions can also facilitate purification (e.g. His-tag strategy). Protein fusion has also been successfully used to optimize the production of the two subunits of heterodimeric complexes as demonstrated with murine interleukin-12 in L. lactis [ 22 ] or with heterodimeric enzymes in E. coli [ 35 ]. In both cases, the resulting fusion had the expected properties. In other cases however, such fusions might dramatically interfere with the conformation of one or both of the proteins, which might be deleterious for the expected activity. Nevertheless, when L. lactis is used as an antigen delivery vector, fusions can be envisioned since it was demonstrated that both moieties of the chimerical protein are still recognized by the corresponding antiserum [ 10 , 20 , 34 ] and are immunogenic [ 36 ]. Figure 2 Fusion to Nuc rescue E7 in intracellular production and increase protein yields for the secreted forms of E7 and L7/L12. A. A DNA fragment encoding the mature moiety of Nuc was fused to the fragment encoding E7 (pCYT:Nuc:E7). Production of Nuc-E7 analyzed by Western blot using anti-E7 antibodies on protein samples prepared from induced cultures harvested either at exponential (exp) or stationary (stat) phase. Positions and sizes of molecular weight marker (M) are indicated at left. B. The mature Nuc fragment was inserted between SP Usp45 and the fragment encoding E7 (pSEC:Nuc:E7) or L7/L12 (pSEC:Nuc:L7/L12). Secretion of the fusion proteins was analyzed by Western blot using either anti-E7 or anti-L7/L12 antibodies. C, cell lysates; S, supernatant fraction. Positions of precursor (prec) or mature forms of E7, Nuc-E7, L7/L12, NucB-L7/L12, and NucA-L7/L12 are indicated by arrows. Figure 3 Native E7 production in wt L. lactis depends on growth phase. E7 production and secretion were analyzed by Western blot from cultures induced at different times so that, 1 hour after nisin induction, the samples are harvested at exponential (OD 600 = 0.5–0.6, upper panels) or stationary phase (OD 600 = 1.5, lower panels). wt/pCYT-E7, NZ(pCYT-E7) strain (encoding native E7, cytoplasmic form). wt/pSEC-E7 NZ(pSEC-E7) strain (encoding the precursor preE7). Positions of E7 mature and precursor forms are given by arrows. C, cell lysates; S, supernatant fraction. ClpP is not involved in the intracellular degradation of E7 in L. lactis . Analysis by western blot shows that a strain of L. lactis deficient in the intracellular protease ClpP cannot rescue cytoplasmic E7 production. Induced cultures samples of wt L. lactis or L. lactis clpP mutant strain containing pCYT-E7 ( clpP /pCYT-E7) or pSEC-E7 ( clpP /pSEC-E7) taken at exponential- (upper panel) or stationary- (lower panel) phase. Secretion avoids proteolysis? Several of the results mentioned above suggest that secretion could be an efficient way to escape intracellular proteolysis. This hypothesis was particularly tested in E7 production [ 20 ]. E7 was indeed degraded when intracellular production was induced in late exponential or early stationary growth phase (Fig. 3 ). E7 production was then tested in a clpP deficient strain (ClpP is reportedly the major house keeping protease in L. lactis ; [ 37 ]) and in a dnaK deficient strain (DnaK is an intracellular chaperone that may promote proteolysis by maintaining the protein in an unfolded state; [ 38 ]). In exponential or stationary phase cultures, no significant difference in E7 patterns was observed between wild type and clpP - (Fig. 3 ) or dnaK - (not shown) strains: E7 was equally degraded in the cytoplasm and remained unchanged in supernatants samples. Altogether, these results indicate that E7 intracellular proteolysis is ClpP- and DnaK- independent. Until recently, only two cytoplasmic proteases, ClpP and FtsH [ 39 ], have been identified in L. lactis . The existence of a third, as yet unidentified protease was postulated by studies of a clpP mutant suppressor [ 40 ]. E7 may thus be a useful screening target to identify a putative L. lactis protease that, as suggested by our data, is activated in stationary phase. Besides the features of the precursor itself, these results also rise that host factors are involved in protein stability and SE (Fig. 4 ). Research efforts are now focusing on the analysis of host factors involved in protein production and secretion by either directed or random mutagenesis in L. lactis [ 41 ]. Figure 4 Schematic presentation of the molecular tools and the cellular events that can affect the production yields of heterologous protein in L. lactis . Thicknesses of the arrows are proportional to the final production yields. All the host factors involved in the cellular events are not identified and or characterized yet. SP, signal peptide (encoded in pSEC constructions), +Nuc, fusion between the protein of interest and the stable Nuc protein. Although L. lactis possesses a wide range of enzymes (peptidases, housekeeping proteases) dedicated to intracellular proteolysis, it possesses only one extracellular housekeeping protease (HtrA) [ 9 ] and its major extracellular scavenger protease, PrtP, is plasmid encoded [ 42 ]. Thus, a plasmidless strain does not present any protease activity in the medium. Better production yields could then be expected when secretion is used versus cytoplasmic production. These results give clues and provide the research workers with target proteins to study intracellular proteolysis and protein stability inside and outside the host strain. Such studies already led to the development of htrA deficient L. lactis strains. Heterologous protein secretion and anchoring in a htrA deficient strain allowed higher protein stability at the cell surface for several heterologous proteins [ 10 ]. Perspectives Current research works are now focusing on other host factors that affect protein production and secretion in L. lactis . L. lactis complete genome sequence analysis revealed indeed that the Sec machinery comprises fewer components than the well-characterized B. subtilis Sec machinery. Notably, L. lactis does not possess any SecDF equivalent and complementation of the lactococcal Sec machinery with B. subtilis SecDF results in better secretion yields as determined for Nuc reporter protein (Nouaille et al., submitted). Random mutagenesis approaches also revealed that features of some cell compartment, such as the cell wall, play an important role in the secretion process [ 41 ]. Similar approaches allowed the identification and characterization of genes of unknown functions specifically involved in production yields of the secreted proteins in L. lactis (Nouaille et al., in preparation). Many molecular tools are now available to direct heterologous protein secretion in L. lactis and the list of heterologous proteins produced in this bacterium is regularly increased. The reports where cytoplasmic and secretion production can be compared mostly show that secretion allows better protein yields compared to intracellular production; and allow a better understanding of the protein production and secretion process in L. lactis . Future works should investigate the L. lactis capacities for protein modifications. For example, we showed that proteins that require a disulfide bond (DSB) to acquire their native conformation can be efficiently produced and secreted in L. lactis [ 5 , 22 , 27 ]. However, no equivalent of E. coli dsb or B. subtilis bdb , the genes involved in DSB formation, was found by sequence comparison in L. lactis . Similarly, other folding elements (i.e. PPIases, so-called maturases...) are still to be identified and the L. lactis capacities for post-translational modifications are still to be investigated. Altogether, these works will contribute to the development and the improvement of new food-grade systems for L. lactis [ 43 ] and should lead, in a near future, to the construction of lactococcal strains dedicated to high-level production of proteins of interest. The GRAS status of L. lactis and LAB in general, is a clear advantage for their use in production and secretion of therapeutic or vaccinal proteins. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC545053.xml |
514546 | Nitric oxide-an endogenous inhibitor of gastric acid secretion in isolated human gastric glands | Background Endothelial nitric oxide synthase (eNOS) has previously been detected in the glandular part of the human gastric mucosa. Furthermore, nitric oxide (NO) has been shown to influence gastric secretion in various animal models. The present study was conducted to investigate the influence of exogenously and endogenously derived NO on histamine- and cAMP-stimulated gastric acid secretion in isolated human oxyntic glands. Methods Oxyntic glands were isolated from human gastric biopsies and were subsequently pre-treated with NO donors and nitric oxide synthase inhibitors and then exposed to histamine or dibutyryl-cAMP (db-cAMP). The secretory response of the glands was determined as accumulation of [ 14 C]aminopyrine. Results The histamine- or db-cAMP-induced acid secretion was attenuated by L-arginine, a known source of endogenous NO, and also by the NO-donors sodium nitroprusside (SNP) and S-nitroso-N-acetyl-penicillamine (SNAP). Pre-treatment with either of the NOS inhibitors N G -nitro-L-arginine methyl ester (L-NAME) or N G -nitro-L-arginine (L-NNA) enhanced the secretory response. Conclusion Our results show that NO inhibits gastric acid secretion in isolated human gastric glands, and that there is endogenous formation of NO within the glandular epithelium in the vicinity of the parietal cells. | Background Nitric oxide (NO) is produced from L-arginine in a reaction catalyzed by the enzyme nitric oxide synthase (NOS)[ 1 , 2 ]. NO is an important biological signalling molecule that influences circulation by regulating vascular smooth muscle tone and modulating systemic blood pressure. Furthermore, NO is involved in neurotransmission; it is a critical factor in the inflammatory response and immunity [ 3 - 5 ]; and it has been shown to exert positive effects on mucosal defence in the gastrointestinal system. In several studies (for review, see [ 6 ]), chemically induced mucosal damage seemed to be reduced by simultaneous addition of NO and impaired by removal of NO from the gastric mucosa. An explanation for those findings might be that NO increases mucosal blood flow[ 7 ], and it has been suggested that NO augments the release of mucus[ 8 ]. It is likely that NO is also involved in the regulation of other secretory processes in the gastrointestinal system. Takeuchi and co-workers [ 9 ] have reported that NO inhibits the secretion of duodenal bicarbonate, whereas other investigators have proposed that bicarbonate secretion is stimulated by NO [ 10 , 11 ]. In addition, several studies have indicated that NO affects the secretion of gastric acid [ 12 - 16 ]. Animal experiments have provided conflicting information about the interaction between NO and gastric acid secretion. For instance, studies in vitro have shown that NO stimulates secretion of gastric acid in the mouse[ 17 , 18 ] and bullfrog[ 19 ]. In addition, similar results have been obtained in dogs [ 12 ]. However, other investigations have shown that NO inhibits gastric acid secretion in the rat [ 13 , 14 ], in gastric glands isolated from rabbits [ 15 ], and in mucosa from toads [ 16 ]. Studies of humans have provided data indicating that NO can both inhibit and augment intragastric pH [ 20 , 21 ], but it is not yet known how this compound participates in gastric acid secretion in humans. In an earlier study, we found morphological support that endogenous NO plays a role in regulation of parietal cell function [ 22 ]. Also, the immunohistochemical data from that investigation revealed the presence of endogenous NOS in epithelial cells of the normal human oxyntic mucosa, more precisely, in both surface mucous cells and endocrine cells. In addition, we observed that there were close contacts between eNOS-positive cells and parietal cells either because the eNOS-positive cells contacted parietal cells via cytoplasmic processes or were invaginated by a parietal cell. Based on these findings, together with the chemical properties of NO, we concluded that NO derived from the endocrine-like cells might be a paracrine regulator of gastric acid secretion. In the present study, our aim was to verify the effect of exogenous NO on histamine- and cAMP-stimulated gastric acid secretion in humans, and also to determine whether endogenously derived NO has a functional effect on human parietal cells. Methods Subjects and ethical approval Twenty-four healthy men ranging in age from 22 to 31 years were recruited as paid volunteers. The selection criteria stipulated that the subjects had to be free from disease and should not have taken any medications or imbibed alcohol for at least one week prior to examination. The men fasted for at least six hours before examination. Pharyngeal anaesthesia was induced with lidocaine spray (Xylocain ® , AstraZeneca, Södertälje, Sweden), after which routine gastroscopy was performed using an Olympus GIF-100 endoscope. Pinch biopsy forceps (Olympus FB 24K-1) were used to take tissue specimens from the greater curvature, immediately distal to the fundus. In all subjects, the gastric mucosa appeared to be normal, both macroscopically and histologically. All subjects tested negative for Helicobacter pylori infection in the urease breath test (Diabact ® UBT 50 mg 13 C-urea, Diabact AB, Uppsala, Sweden). The experimental procedures were approved by the Regional Ethics Committee for Human Research at University Hospital, Linköping, Sweden (File no. 02-039), and all subjects gave informed consent. Secretory study Isolation and incubation of gastric glands The current experiments were based on a technique that was first described in 1976 for use in rabbits in vitro [ 23 ] and is now well established for indirect determination of gastric acid secretion induced by various stimuli. The method of isolating gastric glands was initially developed for animal tissue, but it was later refined so that it could also be applied to small amounts of human tissue [ 24 ]. The human oxyntic mucosal biopsies used in our study were washed and stored no longer than 15 minutes in ice-cold oxygenated phosphate-buffered saline (PBS). The tissue specimens were cut into smaller pieces with a pair of scissors and transferred to oxygenated (100% O 2 ) collagenase enzyme solution (130.0 mM NaCl, 12.0 mM NaHCO 3 , 3.0 mM Na 2 HPO 4 , 3.0 mM K 2 HPO 4 , 2.0 mM MgSO 4 , 1.0 mM CaCl 2 , 0.1 mM N (alfa) -tosyl-L-lysine chloromethyl ketone [TLCK], 10 μM indomethacin, 10 mM glucose, 2 mg/ml human serum albumin [HSA; Sigma], and 1 mg/ml collagenase type IA [Sigma]). The mixture was placed in a 37°C water bath and was gently stirred for 120 minutes, after which most of the treated specimen had disintegrated, leaving mainly isolated gastric glands. The mixture was subsequently filtered through a 200 μm mesh. The isolated glands were washed and re-suspended in pre-warmed (37°C) respiratory medium (132.4 mM NaCl, 1.0 mM NaH 2 PO 4 , 1.2 mM MgSO 4 , 5.4 mM KCl, 5.0 mM Na 2 HPO 4 , 1.0 mM CaCl 2 , 10 μM indomethacin, 10 mM glucose, and 2 mg/ml HSA). The glands were then transferred to vials containing fresh respiratory medium to which we added one of the following: the NOS inhibitor N G -nitro-L-arginine methyl ester (L-NAME; 1 mmol/L) or equivalent amounts of its biologically inactive enantiomer N G -nitro-D-arginine methyl ester (D-NAME); the NOS inhibitor N G -nitro-L-arginine (L-NNA; 0.1 mmol/L); either of the two NO donors sodium nitroprusside (SNP; 1 mmol/l) and S-nitroso-N-acetyl-penicillamine (SNAP; 0.1 mmol/L); the substrate for endogenous NO production, L-arginine (0.1 mmol/L) [ 15 ]. All gland suspensions, including those that were not stimulated, were incubated in a shaking water bath at 37°C for 30 minutes, after which we added histamine to a final concentration of 50 μmol/L or dibutyryl-cAMP (db-cAMP) to a final concentration of 1 mmol/L. To prevent degradation of cyclic nucleotides, we added 0.1 mmol/L 3-isobutyl-1-methylxantine (IBMX) to all stimulations. Determination of the [ 14 C]aminopyrine accumulation ratio A well-established method used to indirectly measure acid secretion by isolated gastric glands is to determine accumulation of 14 C-labeled aminopyrine (AP) in the glands themselves and in the supernatant after centrifugation and then calculate the ratio between those two values (called the AP ratio) [ 23 ]. In short, acid secretion was stimulated at 37°C for 40 minutes, and after that 0.5 μCi [ 14 C]labeled aminopyrine was added to the vials, which were then further incubated at 37°C for 90 minutes. Thereafter, the gland suspension was transferred to previously dried and weighed tubes, which were centrifuged at 4,000 rpm for two minutes. The supernatant was removed and transferred to scintillation vials. The pellets (glands) were dried at 100°C, and the dry weight was determined, and the glands were subsequently re-suspended in 0.5 mol/L NaOH at 60°C and transferred to scintillation vials. The radioactivity of the glands and the supernatant was determined in a liquid scintillation counter (1214 Rackbeta, LKB), and the AP ratio was calculated using the following formula[ 24 ]: where IGW is intraglandular water volume (= 2 × the dry weight of glands in mg). Background accumulation of AP is included in the values representing the secretory response. The AP ratios for background and histamine-and db-cAMP-stimulated conditions differed between the individuals. Therefore, for each subject, we determined the AP ratio for stimulated glands and considered that value to be 100% and used it as an individual reference value. All values are based on single analyses. Statistics Data were analysed by one-sample sign tests comparing median values using MINITAB™ Statistical Software. P values less than 0.05 were considered significant. Immunohistochemistry Isolated gastric glands from five test subjects were placed on charged Super Frost*/Plus glass slides (Menzel-Gläser, Germany) and then washed with PBS and permeabilized with 100% ethanol at -70°C for 5 min. Thereafter, the slides were incubated at room temperature overnight with rabbit anti-NOS3 antibody (1:1000; Santa Cruz Biochemicals) and then washed thoroughly in PBS and incubated for 1 h with biotinylated goat anti-rabbit secondary antibody. Slides where primary antibody had been left out served as negative controls. The slides were subsequently washed again, and biotinylated antibody was detected by exposure to 20 μg/ml Texas Red ® Avidin (Vector Laboratories) for 1 h. Following that treatment, the slides were washed and coverslipped using Vectashield ® mounting medium. A Nikon Eclipse ® E800 fluorescence microscope with a VFM EPI-fluorescence attachment was used to examine and evaluate the slides. A band-pass filter with a wavelength range of 520–560 nm and a long-pass filter with cut-on wavelength at 590 nm (for emitted light) were employed to visualize the Texas Red ® molecules. Hematoxylin and eosin staining For morphological evaluation, glands were fixed on glass slides and stained with Harris hematoxylin for five minutes and 0.5% eosin Y for two minutes. Each step was followed by a rinse in tap water. Results We studied the effects of NO on acid secretion induced by various stimulants in gastric glands isolated from stomach biopsies from human. Morphological examination of the hematoxylin-eosin-stained slides revealed that the isolation procedure had successfully yielded whole-gland preparations and that parietal cells were present in the gastric glands. Immunohistochemical analysis showed that the isolated glands contained eNOS-immunoreactive cells (Fig. 1 ), which agrees with results obtained using other types of mucosal preparations [ 22 ]. Control experiments were primary antibody was excluded showed no immunoreactivity. Figure 1 Immunofluorescence of an isolated gastric gland. Immunolocalization of eNOS (arrowheads) in a gastric gland isolated from human oxyntic mucosa was achieved using a rabbit anti-eNOS polyclonal antibody. The results were visualized with Texas Red ® -conjugated goat anti-rabbit IgG. Bar = 30 μm. Background AP-accumulation Background AP accumulation was observed in the isolated glands, with a median AP ratio of 8.6 (range 2.5–22.1; n = 19). After administration of 50 μmol/L of histamine or 1 mmol/L of db-cAMP, the median AP ratios were 24.7 (5.8–64.5; n = 16) and 38.2 (range 7.6–47.8; n = 11) respectively. The response to both histamine and db-cAMP exceeded the background by a factor of about 2–4 in all preparations (Figs. 2 and 3 ). Figure 2 Accumulation of 14 C-labeled aminopyrine in histamine-stimulated gastric glands. All values are expressed as percent of the gastric acid secretion induced by histamine (considered to be 100%), which was calculated separately for gastric glands isolated from each of the healthy volunteers. Each symbol represents the results for one individual. a) Accumulation of 14 C-aminopyrine in glands pretreated with the NO donor sodium nitroprusside (SNP, 1 mmol/L) or with L-arginine (0.1 mmol/L), the substrate for endogenous NO production. It can be seen that SNP markedly reduced AP accumulation (median = 48%; p < 0.05), which indicates that NO inhibits acid secretion from the isolated glands. Background 14 C-aminopyrine accumulation (bg) is also shown. b) Accumulation of 14 C-aminopyrine in gastric glands pretreated with the NOS inhibitors L-NNA (0.1 mmol/L) and L-NAME (1 mmol/L), respectively. L-NAME caused increased accumulation (median = 147%; p < 0.05), which suggests that acid secretion is elevated when endogenous NO production is prevented, indicating an inhibitory role for endogenous NO in human gastric glands. D-NAME, which is the biologically inactive stereo isomer of L-NAME, did not have an effect on acid secretion, and it was therefore used as a control substance. Figure 3 Accumulation of 14 C-labeled aminopyrine in db-cAMP-stimulated gastric glands. All values are expressed as percent of a value representing the gastric acid secretion induced by db-cAMP (considered to be 100%), which was calculated separately for each of the studied subjects. Each symbol represents the data for one individual. a) Pretreatment with SNP (median = 63%; p < 0.05) or SNAP (median = 81%; p < 0.05) to release exogenous NO before adding db-cAMP to stimulate acid secretion reduced the accumulation of 14 C-aminopyrine in gastric glands, as compared to levels of secretion seen in untreated glands. This indicates that NO can inhibit acid secretion in gastric glands isolated from humans. b) Treatment with L-NAME to inhibit NOS in the gastric glands increased the accumulation of 14 C-aminopyrine after stimulation with db-cAMP (median = 152%; p < 0.05). Those results indicate that NO inhibits db-cAMP-induced acid secretion. The NO substrate L-arginine reduced the accumulation of 14 C-aminopyrine in db-cAMP-stimulated glands (median = 77%; p < 0.05). Background accumulation (bg) is also shown. Effect of NO donors and NOS inhibitors on histamine-stimulated gastric acid secretion Pre-treatment of isolated glands with the exogenous NO donor SNP (1 mmol/L) reduced the histamine response to a median of 48% (n = 7) of the response seen in non-pre-treated glands (100%). In four out of five gland preparations, the substrate for endogenous NO formation, L-arginine (0.1 mmol/L), decreased the AP ratio. This effect however was not statistically significant (Fig. 2a ). When isolated glands were pre-treated with NOS inhibitor L-NAME (1 mmol/L), and then exposed to histamine, the AP ratio was markedly elevated to a median value of 147% (n = 13). Although a small number of individuals were tested, L-NNA (0.1 mmol/L) yielded a similar result; 172% (n = 2). By comparison, in control experiments, the L-NAME analogue D-NAME (1 mmol/L) had no effect at all on histamine-stimulated acid secretion (Fig. 2b ). Effect of NO donors and NOS inhibitors on db-cAMP-stimulated gastric acid secretion Exposing the isolated glands to db-cAMP increased the secretion of gastric acid compared to the background level. Compared to untreated glands, those that were pre-treated with SNP (1 mmol/L) or SNAP (0.1 mmol/L) accumulated less AP after stimulation with db-cAMP; 63%(n = 9) and 81%(n = 8) respectively (Fig. 3a ). Moreover, similar to histamine-stimulated secretion, the db-cAMP-induced secretion was increased to a median of 152% (n = 9) in glands that had been pre-treated with L-NAME (1 mmol/L). Although no effect on L-arginine on histamine-stimulated acid secretion could be seen, there was a significant effect of L-arginine on db-cAMP-induced secretion. Acid output was inhibited to a median of 77% (n = 10) in those pre-treated with L-arginine (0.1 mmol/L)(Fig. 3b ). Discussion The method of using isolated gastric glands in vitro is well suited for studying the interaction between gastric acid secretion and various endocrine signals. This technique has been thoroughly evaluated, chiefly in experiments on animals, and it has been reported to offer good reproducibility [ 23 ]. Furthermore, in a study of gastric glands isolated from stomach biopsies taken from humans [ 24 ], it was found that both histamine and db-cAMP induced secretory responses that were reproducible when repeated using gland preparations from the same subject, although there was considerable interindividual variation. Fellenius et al. [ 24 ] and Haglund et al. [ 25 ] have reported that both histamine and db-cAMP stimulated gastric acid secretion from isolated human gastric glands, and this was observed as a two- to threefold increase in AP accumulation compared to the background level. Those results agree with our data obtained using histamine and db-cAMP. It is known that SNP releases NO [ 26 ], and in our experiments SNP reduced secretion of gastric acid from isolated glands. Hence, NO inhibits acid secretion in isolated human gastric glands. Some of the effects of SNP may be due to cytotoxic interactions, although no such impact was found in a study of isolated rabbit gastric glands [ 15 ]. To rule out the possibility of a cytotoxic influence, we performed complementary experiments using the NO donor SNAP, which has chemical properties that differ from those of SNP. In those experiments, we observed the same reduction in AP accumulation after stimulation with db-cAMP, which further favours the conclusion that NO is in fact responsible for observed results. In db-cAMP-stimulated glands, the induced secretory response was reduced by L-arginine, a compound that depends on an endogenous factor (i.e., eNOS) to generate NO, although that reduction was not as pronounced as the decrease induced by SNP and SNAP. There are a number of possible explanations for that observation. If there was already enough L-arginine in the glands to sustain NO production at the time of the experiment, addition of L-arginine was therefore without effect. Furthermore, L-arginine may have had a weak impact because the effect of NO occurred through up- or down regulation of the enzyme NOS and was not influenced by access to substrate. Notwithstanding, L-arginine did decrease the accumulation of AP, albeit not as much as the exogenous NO donors did at the present doses. This indicates that some specific process is responsible for generating NO from L-arginine in isolated gastric glands. These results are consistent with studies showing that SNP, SNAP, and L-arginine inhibited histamine-stimulated acid secretion from gastric glands isolated from animals [ 13 , 15 ]. L-arginine has also been observed to reduce carbachol-stimulated acid secretion in toads [ 16 ]. In a previous study conducted by our research group [ 22 ], examination of the glandular epithelium of specimens of human oxyntic mucosa revealed that one particular type of cells contained NOS. These eNOS-immunoreactive cells, defined as endocrine cells, were in close contact with parietal cells. These two characteristics suggest that cells of this type release NO, which thus might be a paracrine regulator that directly affects the function of parietal cells. That assumption may be supported by a number of other conditions. For example, NO can easily penetrate cell membranes, which may indicate an intracellular site of action. Also, NO has a rather short life span, which implies that sources needed to generate this oxide must be available close to the NO target cell. In this study, the occurrence of eNOS in the glands is shown, but earlier extensive investigations using antibodies against both nNOS and iNOS have not revealed presence of any of the two isoforms in the glandular epithelium of normal human subjects (unpublished observation). Similar to results obtained in a study of isolated rabbit gastric glands[ 15 ], we found that the NOS inhibitors L-NAME and L-NNA, but not D-NAME, amplified the secretion-stimulating effect of histamine, which further indicates that the isolated human glands we used contained the enzyme NOS. Both the increase in the AP ratio that we observed following inhibition of NOS and the decrease in secretory responses that we noted in glands treated with L-arginine strengthen the hypothesis that NO is produced by cells in the glandular epithelium and, when released, it interferes with stimulated acid secretion. Interestingly, the mentioned observations suggest that the release of NO is sustained, regardless of whether acid secretion is stimulated, which implies that NO functions as an endogenous inhibitor of gastric acid secretion. The intensity of this inhibition probably depends on the number of eNOS-containing endocrine-like cells that are present in the vicinity of the parietal cells. The exact mechanisms behind this paracrine regulation of gastric acid secretion is yet to be elucidated. There are several different pathways within the parietal cell that might be affected by NO. It can induce ADP ribosylation of G-actin [ 27 ], thereby influencing the cytoskeleton. This could be essential for the morphological changes that parietal cells exhibit during acid secretion. Accordingly, if NO does have a persistent impact on an element such as the cytoskeleton, it might play a role in the membrane recycling hypothesis proposed by Forte et al. [ 28 ]. Briefly, that theory suggests that parietal cells undergo the following morphological alterations: they have a large active secretory surface during the stimulatory phase, and they display a minimal active secretory surface during the resting phase. Since it is known that guanylate cyclase is a general target of NO in many cell systems, some investigators have suggested that NO exerts its effects via cyclic guanosine 3',5'-monophosphate (cGMP) in both rat and rabbit parietal cells [ 13 , 15 ]. An ongoing study in our laboratory will show whether this is the case in human parietal cells. Downstream effects of cGMP may include activation of a number of effectors, such as ion channels, protein kinases, and phosphodiesterases [ 29 ]. It is also plausible that NO can exert its effect alone, without acting through other signalling molecules. Under experimental conditions, NO can induce nitrosylation and nitration of cellular proteins, although that is probably not the case in vivo, since those two processes often result permanent damage to vital functions [ 30 ]. There is a possibility that the suppression of acid secretion occurs not only at parietal cell level, but via other cell types. ECL-cells are probably present in the glandular preparation and in the rat, these cells have the ability to release histamine in response to increased intracellular levels of cAMP [ 31 ]. NO can inhibit this histamine-release [ 14 ] and thereby further contribute to the inhibition of acid secretion. Although there is little known about human ECL-cells and the effects of NO on histamine-release there are studies that indicate species differences in other histamine-secreting cells. For example, rat mast cells have been shown to produce an "NO-like factor" which inhibits histamine-release [ 32 ] while there are investigations that indicate that NO does not affect histamine-secretion in human basophils [ 33 ]. At present we can only establish differences in inhibitory response to l-arginine for histamine and db-cAMP stimulation. Further investigations are needed to clarify the role of NO in parietal cell function. Conclusions The findings of the present study suggest that NO produced endogenously in the human oxyntic mucosa can reduce the stimulatory effects of histamine or db-cAMP on gastric acid secretion. We obtained uniform results for gastric glands isolated from different healthy human subjects, which implies that NO released from specific cells within the secretory mucosa plays an important physiological role in the regulation of gastric acid secretion. Competing interests None declared. Authors' contributions AB participated in the design and coordination of the study, performed the secretory studies, carried out the immunohistochemical procedures, and drafted the manuscript. SR was the surgeon in charge and carried out all gastroscopic procedures. ACE and SES were involved in the design of the study and in drafting of the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514546.xml |
524485 | Evaluation of sense-strand mRNA amplification by comparative quantitative PCR | Background RNA amplification is required for incorporating laser-capture microdissection techniques into microarray assays. However, standard oligonucleotide microarrays contain sense-strand probes, so traditional T7 amplification schemes producing anti-sense RNA are not appropriate for hybridization when combined with conventional reverse transcription labeling methods. We wished to assess the accuracy of a new sense-strand RNA amplification method by comparing ratios between two samples using quantitative real-time PCR (qPCR), mimicking a two-color microarray assay. Results We performed our validation using qPCR. Three samples of rat brain RNA and three samples of rat liver RNA were amplified using several kits (Ambion messageAmp, NuGen Ovation, and several versions of Genisphere SenseAmp). Results were assessed by comparing the liver/brain ratio for 192 mRNAs before and after amplification. In general, all kits produced strong correlations with unamplified RNAs. The SenseAmp kit produced the highest correlation, and was also able to amplify a partially degraded sample accurately. Conclusion We have validated an optimized sense-strand RNA amplification method for use in comparative studies such as two-color microarrays. | Background One of the principal complications in microarray analysis of gene expression is the relatively large amount of input RNA required for each assay. On average, 1–20 μg of total RNA are required per study using glass microarrays [ 1 - 4 ]. This is easily obtained from standard tissue samples, but is more difficult to obtain from smaller samples, such as laser capture microdissections [ 5 , 6 ]. The primary impediment to the use of laser capture microscopy (LCM) in gene expression analysis is that microdissections yield insufficient mRNA due to low total RNA recovered from small sample sizes. With samples such as these, the ability to conduct a linear amplification of the target mRNA becomes imperative, to ensure that enough material is available for gene expression analysis. There are several methods for amplifying RNA including the arithmetic transcription methods [ 7 , 8 ], PCR based exponential amplification, or a combination of both arithmetic and exponential amplification [ 9 ]. Each method has proven effective in generating large amounts of amplified RNA from small starting samples. Each method is not without its drawbacks however. PCR based amplification has been shown to amplify sequence-dependent biases geometrically, and hybridization kinetics during the thermal cycles can create sequence-dependent and abundance-dependant biases [ 10 ]. New methods must be carefully validated with large numbers of mRNAs before they may be accepted for general use. Most RNA amplification methods are based on the T7-based antisense RNA amplification technique first described by Van Gelder and Eberwine in 1990 [ 7 ]. In this technique poly(A) + mRNA is reverse-transcribed and converted into double stranded cDNA using an oligo(dT) primer containing a promoter for T7 RNA polymerase. The second strand cDNA serves as a transcription template for amplified antisense RNA (aRNA) production. cDNA microarray studies using T7 amplified RNA have shown that the technique yields reproducible results that correlate with the results obtained from using total RNA [ 2 , 9 , 11 ]. This method is incompatible, however, with standard spotted oligonucleotide microarrays when combined with conventional reverse transcription based labeling methods. Spotted oligo microarrays consist of 'long' 50–80 mer sense-strand oligonucleotide probes arrayed onto a suitable substrate. Each probe sequence is designed to hybridize to a specific antisense cDNA reverse transcribed from a given mRNA species. The advantage of spotted oligo microarrays over cDNA microarrays is that the oligos can be designed to be more specific, with similar hybridization kinetics, lower homology among related transcript probes, and selection among different splice variants of the same gene. However, aRNA prepared from Eberwine-amplified mRNA would produce a sense-strand cDNA target that would not hybridize with sense-strand oligo probes on the microarray. The Genisphere SenseAmp linear mRNA amplification method produces sense-strand amplified mRNA by incorporating a double stranded T7 promoter into the 3' end of the first strand cDNA, driving transcription of an amplified RNA with the same strandedness as mRNA. SenseAmp linear amplification also allows for the use of dT and random primers in the synthesis of cDNA. This variation on the amplification protocol may be as effective on partially degraded mRNA or, using random primers in a first-strand reaction, on RNAs lacking a poly(A) tail. Further, the use of random primers combined with dT priming may help to reduce the 3' bias associated with Eberwine-based amplification methods [ 12 , 13 ] by improving the access of reverse transcription to the 5' end of mRNA. Most studies evaluating amplification validity compare unamplified to amplified material [ 3 , 14 - 17 ]. However, this is not a good model of experiments normally performed with spotted oligo microarrays. In most two-color microarray experiments, an experimental sample is compared with a reference sample on the same microarray, so it is the ratio between two samples that becomes the most important parameter. RNA amplification may have some sequence bias, but as long as the bias is consistent between reactions, the effect of the bias may be canceled. We chose, therefore, to evaluate amplification strategies by comparing two RNA samples both before and after amplification, and correlating the ratios obtained before and after amplification. This key difference allows us to identify the best amplification method for use with two-color microarrays. Throughout the course of this study, several pre-production versions of SenseAmp were evaluated with the aim of judging the optimal method. Total RNA from replicate rat brain and liver samples was amplified using one of several different techniques including three versions of the SenseAmp method, MessageAmp from Ambion, Nugen's Ovation RNA-based single primer isothermal amplification (Ribo-SPIA) method, and as an additional study, SenseAmp amplification of partially degraded RNA samples. The ratio of amplified RNAs obtained from each method was compared via relative qPCR to that of unamplified mRNAs from the same pool to determine how accurately the relative abundances were preserved. The use of qPCR provides a much broader range of results than possible with microarrays [ 18 ]. Relative qPCR analysis also allowed for the quantification of amplified RNA regardless of which strand was amplified, thus a direct comparison could be made between the various amplification techniques. The fidelity of the amplification methods was determined using the ΔΔC t relative quantification method for qPCR. This method is used to compare the expression of a given gene in one sample relative to a second, and is based on the amplification efficiency of the PCR primer pairs used [ 19 ]. Quantitative PCR was selected because of its universal use as a microarray validation method [ 10 , 11 , 18 - 21 ], enhanced dynamic range [ 18 - 20 ], and ease of use with limited sample sizes for evaluating expression changes for several hundred genes. The basis of this method is the assumption that the exponential amplification of the starting product, and therefore the amount of PCR products produced with each round of amplification, is dependent upon the efficiency of each PCR primer pair. This efficiency is determined either experimentally or is calculated from the raw fluorescence data obtained during the qPCR amplification [ 22 ]. Equation (1) was used to compare the expression of 192 different genes in rat liver and rat brain samples. Triplicate total RNA samples from rat brain and liver were analyzed for each pair of primers targeting the mRNA concentrations of a given gene. Ratio of gene expression = E -ΔΔ Ct (1) Through comparison of the relative gene expression across the various different amplification techniques, we were able to determine that each amplification method produces amplified RNA in quantities that accurately reflect the original mRNA proportions. The SenseAmp kit exhibited the best correlation to the unamplified control, and was effective in amplifying degraded RNA samples as well. In addition, we inadvertently identified a potential bias that can arise with the use of the oligo dT in reverse transcription priming. Results We compared liver/brain expression ratios for a broad collection (n = 192) of mRNAs before and after amplification. Rat brain and liver RNAs were chosen since we needed to begin with large quantities of unamplified materials in order to test several amplification reactions on the same starting material, and to reliably assay the unamplified RNA. Several variations on the amplification method were tested to determine which method best replicated the distribution of liver/brain ratios found in unamplified RNAs. As anticipated, each of the amplification techniques produced amplified RNA that reproduced the full range of relative quantities (RQ) between liver and brain RNAs (Figure 1 ) and correlated well with the initial mRNA pool (Table 1 , Figure 2 ). The SenseAmp version 1–2, which was designed to incorporate aspects of both version 1 and version 2, was shown to be most similar to the unamplified control results with a correlation coefficient of 0.90. As indicated by the lack of overlap in the 95% confidence intervals, SenseAmp version 1–2 produced amplified RNA with greater fidelity than either the MessageAmp or Ovation methods. Furthermore, each successive version of the SenseAmp protocol appeared to enhance the fidelity of the result. A series of two rounds of amplification with SenseAmp version 1–2 was indistinguishable in correlation to the unamplified control from a single round. These results suggest that each amplification technique is capable of producing linearly-amplified RNA that represents the relationships of the two original tissues. The SenseAmp kit (version 1–2) produced the most accurate reproduction of the original liver/brain ratios while also providing a sense-strand amplified RNA appropriate for use with oligonucleotide microarrays. Figure 1 Distributions of liver/brain RQ ratios for all amplification methods. Box and whiskers plot showing the distribution of log 2 RQ ratios for each amplification method. The blue diamond is centered on the mean and shows the 95% CI of the mean. The blue lines depict the percentile range. The center of the notched box is the median, with the notches showing the 95% CI of the median. The boxes show the inter-quartile range (IQR). Dashed lines are 1.5 times the IQR. Outliers are shown as red crosses (1.5–3.0 times the IQR) or red circles (>3.0 times the IQR). Table 1 Correlations between liver/brain RQ ratios of amplified vs. unamplified RNAs. For each correlation, n is the number of PCR results retained after filtering the amplification efficiency [22]. The correlation coefficient (r) is shown along with its 95% confidence interval (CI). Each correlation was significant at p < 0.0001. A cross-correlation matrix showing all relationships between samples is available at n * r ‡ 95% CI p MessageAmp™ 121 0.80 0.74 To 0.85 <0.0001 Ovation™ 112 0.82 0.76 To 0.86 <0.0001 SenseAmp™ Version 1 118 0.87 0.83 To 0.90 <0.0001 SenseAmp™ Version 2 121 0.88 0.85 To 0.91 <0.0001 SenseAmp™ Version 1–2 121 0.90 0.87 To 0.93 <0.0001 2 Rounds Version 1–2 121 0.89 0.85 To 0.92 <0.0001 SenseAmp™ on degraded RNA 121 0.94 0.92 To 0.96 <0.0001 * number of valid samples shared with unamplified control ‡ Pearson correlation coefficient Figure 2 Scatterplots comparing liver/brain log 2 RQ ratios of amplified RNAs with unamplified RNA. For each amplification method, a scatter plot shows the correlation of the liver/brain ratio to that of unamplified RNA. A linear regression fit is plotted as a line with the equation shown. The coefficient of determination (R 2 ) corresponds to the square of the correlation coefficient (r) in Table 1. Amplification of partially-degraded RNA samples using the SenseAmp version 1–2 method also produced a high correlation of liver/brain ratios to those from unamplified RNAs (r = 0.94). This high correlation using degraded RNA appeared to be due to the presence of random primer in the amplification reaction. Comparing the rank order of mRNA abundances in liver (Table 2 ), we found that reactions using oligo dT primers generally produced higher correlations between amplified RNAs indicating that a similar offset to the rank order was occurring for all dT based methods. However comparing the dT primer rank order to that of random primed samples demonstrates greater dissimilarity, although this effect was variable. We interpret these results as supporting the hypothesis that the addition of a random primer to the amplification assay inadvertently enhances the correlation to random-primed, unamplified RNA, partially offsetting the negative effect of RNA degradation. Table 2 Rank correlations of liver C t values identifies effects of oligo d(T) primers vs. random hexamer primers. Unamplified MessageAmp NuGen Version 1 Version 2 Version 1–2 2 Rounds V 1–2 MessageAmp 0.75 1 NuGen 0.65 0.83 1 Version 1 0.61 0.68 0.61 1 Version 2 0.84 0.92 0.78 0.71 1 Version 1–2 0.84 0.90 0.84 0.67 0.95 1 2 Rounds V1–2 0.79 0.89 0.81 0.67 0.93 0.92 1 Degraded V1–2 0.85 0.85 0.77 0.71 0.89 0.91 0.85 Rank cross-correlation matrix for liver C t values. The mean cycle threshold (C t ) values obtained with liver RNA samples were rank-ordered and correlated. Results indicate the faithful reproduction of an ordered list of mRNA concentrations in liver RNA before and after amplification. Results were filtered for acceptable PCR efficiencies (see Methods), producing 138 primer pairs for this analysis. Methods using random primer (including unamplified RNA) are bold, those using oligo d(T) are italicized. Scatter plots of each rank C t correlation are available at: Discussion Most studies of the fidelity of amplified RNA have compared the amplified sample to the original total RNA sample exclusively [ 2 - 4 , 10 , 14 ]. While this is valid, the approach described here more accurately reproduces the standard experimental conditions for two-color microarray expression analysis by comparing the ratio of gene expression between two different samples. The ratios obtained for amplified brain RNA vs. amplified liver RNA are then compared to the ratios from the unamplified control comparison (Table 1 , Figure 2 ). Any reproducible biases within the techniques are represented in both the brain and liver samples and therefore cancelled out in the comparison. This approach models a two-color gene expression comparison experiment and demonstrates the differences in expression profiles obtained from different amplification techniques. Using this approach, all three amplification kits tested had correlation coefficients of 0.80 or greater, indicating a great deal of fidelity in amplifying paired samples of RNA. The SenseAmp kit performed relatively better among the three, with a correlation coefficient of 0.90, with the 95% confidence interval lying above the means and intervals produced with MessageAmp or Ovation methods. Other researchers have shown that additional rounds of amplification yield reproducible results for a single RNA sample with only modest biases [ 6 , 10 ]. The fidelity of amplification was maintained in the course of our experiments with the SenseAmp production kit, through a second round of amplification. The similar correlations between the SenseAmp version 1–2 and the two rounds of version 1–2 amplification indicate that a second round of amplification does not significantly affect the relative abundance of mRNA. Of the three SenseAmp versions tested, version 1–2 had the highest correlation to unamplified RNA using this approach. In order to confirm that qPCR was an appropriate choice for validating RNA amplification procedures, we compared the brain vs. liver expression ratios on oligonucleotide arrays of SenseAmp version 1–2 amplified to unamplified RNA (not shown). As we observed with qPCR, a high correlation of about 0.93 was observed after comparing about 2700 differentially expressed genes, indicating that our qPCR experimental design was appropriate. Variations in correlation among the versions of the SenseAmp method may be due to modifications to the structure of the T7 promoter/cDNA template. The version 1 template consisted of a completely double stranded linear DNA molecule, with one strand of the promoter synthesized enzymatically. For version 2, the T7 promoter was composed of two prehybridized, synthetic DNA strands ligated to a single stranded cDNA template. For version 1–2, a double stranded T7 promoter was synthesized onto the end of a single stranded cDNA template from a T7 template oligo by a 3' recessed end "fill-in" reaction using the Klenow fragment of DNA polymerase I. Like version 1, the promoter contains one enzymatically-synthesized strand and like version 2 the cDNA portion is single stranded. The incorporation of an enzymatically-synthesized strand appears be a more effective initiation site for the T7 polymerase (unpublished results). Furthermore, single stranded DNA templates downstream of the ds T7 promoter have been shown to be very efficient T7 polymerase templates [ 23 , 24 ] demonstrating a 2 fold improvement in kinetics [ 24 ]. The combined increase in T7 amplification efficiency in version 1–2 may preserve the distribution of mRNA concentrations in the amplified product. Previous studies have cautioned against comparing samples using different reverse transcription primers [ 2 ]. Priming with oligo dT reduced PCR yields and created 3' and sequence-specific biases compared with the use of random primer [ 13 , 14 , 25 ]. These biases arise from the specificity shown by oligo dT primer for the 3' poly(A) tail and low processivity of T7 polymerase, as well as the presence of internal poly(A) sequences which may act as additional priming sites for the oligo dT. Random primer has also been shown to create a better 3'/5' ratio than the oligo dT primer [ 14 ]. Our experimental design called for the use of oligo dT primer in most of the RNA amplification reactions but random primer in the cDNA synthesis phase of qPCR. This design was used for each of the comparison experiments and therefore any bias introduced by the oligo dT primed reaction would be repeated for each of the amplification techniques. The effect of the oligo dT priming in the RNA amplification was identified when the degraded RNA sample was amplified using a mixture of oligo dT primer and random primer. The result showed that the degraded sample amplification resulted in a higher correlation to the unamplified control than any of the amplification techniques including the SenseAmp amplification of intact RNA. It is our interpretation that this high correlation of the amplified, degraded samples to the unamplified qPCR samples may be due to the common use of random primers for both data sets. Conclusions Overcoming the problem of tissue heterogeneity with LCM and other, similar techniques will allow the research community to focus its efforts on the biologically relevant cell types. The use of RNA amplification with these small, cell-type specific techniques provides reliable and reproducible quantities of mRNA suitable for high-throughput gene expression profiling. Amplification from small amounts of LCM-selected samples provides stronger hybridization signal and reduced biological noise attributed to the presence of other cell types. RNA amplification has been shown here, and elsewhere, to be both a useful and consistent technique for production of practical amounts of RNA when limited starting material is available. While there are several reliable amplification methods available, most amplify an antisense RNA which is suitable for cDNA microarray analysis. The most apparent benefit of the SenseAmp method is the amplification of the sense mRNA strand. This allows for the direct use of cDNA reverse-transcribed from amplified RNA as a hybridization target for oligo microarrays, and any other analysis that requires a sense-strand orientation. In addition, we observed similar liver/brain ratios between amplified RNAs and unamplified RNAs. This comparison models the relative expression ratios observed with two-color microarrays. While each of the methods tested produced acceptable results, the SenseAmp methods provided optimal correlation between unamplified samples and sense-strand amplified RNA. Methods Primer design A subset of 192 sequence targets was chosen from the Compugen/Sigma-Genosys Rat 8 K oligo library for qPCR analysis. Using previously-analyzed microarray results as a guide (not shown), we selected targets with a broad range of expression ratios from brain-specific, through common, to liver-specific mRNAs. GAPDH mRNA was also selected for normalization. Primers were designed for all 193 sequences using Applied Biosystems Primer Express software v2.0 (Applied Biosystems, Foster City, CA). Primers were designed to have a T m between 58°C and 60°C and with an optimal length of 20 nt. The %GC content was held between 20% and 80% with no 3' GC clamp. The target amplicon for each sequence was designed to be between 50 and 150 nt with an optimal T m of 85°C. The target mRNAs represented a broad range of sizes (as measured by cDNA lengths; range 110–8074; mean 1876 nt; 190 nt 95% CI) and base composition (range 38–68% GC; mean 52% GC; 0.85% 95% CI). Amplicons were distributed between 5'UTR (8.7%), coding sequence (82.0%), and 3'UTR (9.2%). Primers were purchased from Sigma-Genosys (The Woodlands, TX). The final working concentration for each of the primer pairs was 50 nM. A table of target sequences and primers is available in the supplemental materials . Preparation of total RNA Samples of rat brain (n = 3) and rat liver (n = 3) were frozen in liquid nitrogen and ground to a coarse powder. RNA was isolated from each sample using TRIzol (Invitrogen, Carlsbad CA). After isolation, samples of the prepared RNA were further purified using a Qiagen RNeasy column (Qiagen, Valencia CA). Total RNA was quantified by UV spectrophotometry and the integrity was assessed using a Bioanalyzer model 2100 (Agilent, Palo Alto CA). Identical total RNA samples were divided among the 8 different experiments (including unamplified control). Degraded RNA was prepared by treatment at 65°C for 15 minutes in fragmentation buffer (40 mM Tris acetate, pH 8.1, 100 mM potassium acetate, 30 mM magnesium acetate). Samples of RNA degraded under these conditions were analyzed on an Agilent Bioanalyzer using RNA Nano chips and 2100 Expert software. Degraded samples typically had little or no 28S rRNA peak remaining and a broad smear below a weaker 18S rRNA peak, corresponding to an RNA Integrity Number (RIN) of 4.9 (using baseline correction) out of a score of 10 for RNA of ideal quality. RNA amplification Each of the three replicates for each tissue was amplified using the Ambion messageAmp (Ambion, Austin TX), NuGen Ovation AminoAllyl amplification (NuGen Technologies, San Carlos CA), or SenseAmp version 1, version2, or version 1–2 kits. SenseAmp, version 1–2, is the commercial version of the Genisphere SenseAmp kit. Amplification with each method was done according to the protocol outlined for each method. For each of the MessageAmp and SenseAmp amplifications, 0.75 μg of input total RNA was used. For SenseAmp with random priming, 250 ng of input total RNA was used. The final yield of amplified RNA for each method was ~36 μg. For the NuGen Ovation amplification, 70 ng of input total RNA was used to yield ~10 μg of amplified cDNA. For all versions of SenseAmp, total RNA was reverse transcribed using 100 ng of an anchored dT primer [d(T) 24 V] as described in the SenseAmp manual . For the degraded RNA samples, random 9 mers were added to the reverse transcription reaction at twice the mass of the input total RNA (e.g. 500 ng random primers per 250 ng of total RNA). Superscript II (Invitrogen) was used for all reverse transcriptions. The cDNA was purified using a MinElute PCR Purification Kit (Qiagen). SenseAmp version 1 The purified cDNA was 3' tailed with dATP. A T7-promoter/oligo d(T) primer was used to initiate second strand cDNA synthesis using E. coli DNA polymerase I (Invitrogen) at 16°C for 2 hours as described by the manufacturer. Double-stranded cDNA was purified using the MinElute PCR Purification Kit and used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen) and the manufacturer's recommendation for RNA clean up. SenseAmp version 2 The purified cDNA was poly d(T) tailed as described in the SenseAmp (Genisphere) product manual. Excess double-stranded T7-promoter was ligated to the 3' poly d(T) tail on the cDNA in 1X ligation buffer (Roche) at room temperature for 30 minutes. The double stranded (ds)T7 promoter consisted of equal molar amounts of a T7 promoter oligo hybridized to a complementary oligo have a 10 base d(A) 10 overhang on the 3' end prehybridized in 6X ligation buffer (Roche Applied Science, Indianapolis IN). Excess unligated ds T7 promoter was removed using the MinElute PCR Purification Kit. The purified cDNA, which contained a double-stranded T7 promoter linked to a single stranded cDNA template [ 23 , 24 ], was used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen). SenseAmp version 1–2 The complete process is described in the Gensiphere SenseAmp product manual. Briefly, the purified cDNA was poly d(T) tailed. A T7-promoter/oligo dA template strand with a 3' blocking group was hybridized to the poly d(T) tail of the purified cDNA. Double-stranded T7-promoter was synthesized at room temperature for 30 minutes using Klenow fragment of DNA Polymerase I (Invitrogen). The 3' blocker was used to prevent the synthesis of complete second strand cDNA during the T7 promoter "fill-in" reaction. Excess T7 promoter template was removed using the MinElute PCR Purification Kit. The purified cDNA, which contained a double-stranded T7 promoter linked to a single stranded cDNA template, was used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen) and the manufacturer's recommendation for RNA clean up. cDNA synthesis Five μg of each amplified RNA sample and unamplified control (with the exception of the NuGen Ovation amplification which yielded cDNA directly) was reverse transcribed into cDNA. RNA was added to 1 μl of 50 ng/μl random hexamer primer, 1 μl 10 mM dNTP mix (Sigma, St. Louis MO), and RNase-free water to make 12 μl. The mixture was denatured at 65°C for 5 min and immediately chilled. Reaction buffer and SuperScript II (Invitrogen) was then added and the volume was adjusted to 20 μl. The mixture was then incubated at 25°C for 10 minutes, 42°C for 50 minutes, and finally 70°C for 15 minutes to stop the reaction. Quantitative real-time PCR (qPCR) Each treatment assay was conducted across a total of four 384-well plates per assay. Each plate targeted 48 different genes for PCR amplification, each with 3 brain and 3 liver samples as well as 6 GAPDH wells for normalization across plates. A calibrator plate was used for each treatment to determine the concentration of cDNA required from each amplification technique to produce a GAPDH C t comparable to that derived from the 1:10 dilution in the unamplified control. cDNAs for the NuGen, 2 rounds of SenseAmp version 1–2, and SenseAmp version 1–2 on degraded RNA were all diluted 100X. cDNAs from SenseAmp version 1 were diluted 120X. The remaining version 2, version 1–2, and messageAmp cDNA samples were diluted 200X. 2 μl of diluted cDNA was added to the primer pair mix and SYBR Green Master Mix (Applied Biosystems) in each well. qPCR was conducted on the Prism 7900HT Sequence Detection System (Applied Biosystems). Plates were run for 40 cycles and fluorescence intensity measured after every cycle. For each target sequence the average cycle number at which fluorescence was detected above background in the exponential phase of amplification was obtained for the brain and liver samples. This value, C t , or cycle number at threshold, was used for calculations of relative abundance of mRNA molecules in the liver samples compared to the brain samples for each of the amplification methods. PCR primer efficiency The efficiency of each of the 192 target gene PCR primer pairs was calculated using the LinRegPCR software [ 22 ]. Normalized fluorescence values for each well were recorded for each cycle of RT-PCR. LinRegPCR used the log of these data to calculate the linear regression of a "window of linearity" in the exponential phase of amplification. The efficiency of the primer pairs corresponds to 10 slope of the linear regression of the normalized log fluorescence values within the "window of linearity" for each well. As per the recommendations for this calculation, PCR primer pairs with strongly deviating PCR efficiencies or correlation coefficients below 0.999 were discarded [ 22 ] Average efficiency values for each primer pair were determined and used in equation (1) to reveal the relative abundance of mRNA in each sample. Data analysis The following algorithm was applied to the results from each amplification method as well as the unamplified control. As per the ΔΔC t qPCR analysis method, an average cycle number was determined at which fluorescence crossed a threshold above background. The resulting C t value was recorded for each tissue type and target gene. This C t value was normalized across plates by subtraction of the C t value from the housekeeping gene GAPDH. This value represents the ΔC t . The ΔC t from the reference brain samples was subtracted from the ΔC t obtained from the liver samples. This gave the change in ΔC t between the two tissues or ΔΔC t . With the addition of calculated primer pair efficiencies, the ratio of gene expression for each target mRNA sequence between the two tissues was determined using equation (1). Ratios of expression values for liver tissues relative to brain (RQ) for each amplification technique were plotted in Excel (Microsoft, Redmond WA) and Pearson correlations to the unamplified control were determined using Analyze-It (Analyse-It Software, ), an Excel Statistics Add-on. Authors' contributions LAG performed all qPCR assays, selected and designed primer pairs, developed databases holding all data, and prepared the first draft of the manuscript. JB, JS, KH and RCG participated in the design of the study, developed the SenseAmp reactions, and modified the reactions in response to qPCR validation results. RCG supervised SenseAmp development. RPH conceived the study, supervised the qPCR assays, and coordinated work. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524485.xml |
524491 | Mechanisms underlying fatigue: a voxel-based morphometric study of chronic fatigue syndrome | Background Fatigue is a crucial sensation that triggers rest, yet its underlying neuronal mechanisms remain unclear. Intense long-term fatigue is a symptom of chronic fatigue syndrome, which is used as a model to study the mechanisms underlying fatigue. Methods Using magnetic resonance imaging, we conducted voxel-based morphometry of 16 patients and 49 age-matched healthy control subjects. Results We found that patients with chronic fatigue syndrome had reduced gray-matter volume in the bilateral prefrontal cortex. Within these areas, the volume reduction in the right prefrontal cortex paralleled the severity of the fatigue of the subjects. Conclusion These results are consistent with previous reports of an abnormal distribution of acetyl-L-carnitine uptake, which is one of the biochemical markers of chronic fatigue syndrome, in the prefrontal cortex. Thus, the prefrontal cortex might be an important element of the neural system that regulates sensations of fatigue. | Background Chronic fatigue is common and is reported in more than 20% of people seen in primary care [ 1 ]. However, the neural substrates of chronic fatigue are not well understood. For clinical use, central fatigue is defined as difficulty in the initiation of, or the ability to sustain, voluntary activities [ 2 ]. Central fatigue, in contrast with neuromuscular or peripheral fatigue, represents a failure to complete physical and mental tasks that require self-motivation and internal cues, in the absence of demonstrable cognitive failure or motor weakness [ 3 ]. Based on this definition, Chaudhuri and Behan [ 2 ] proposed a conceptual model for central fatigue. The work output of voluntary activity depends on the applied voluntary effort, which is controlled by motivational input and perceived effort via feedback from motor, sensory and cognitive systems. Hence, any dissociation between the level of internal input (motivational and limbic) and that of the perceived effort from applied voluntary effort results in the sense of fatigue. Assuming that pathological fatigue is an amplified sense of the normal (physiological) fatigue induced by changes in the variables regulating work output, clinical studies of fatigue disorders can provide clues regarding the neural substrates of fatigue. Symptoms of lesions in the pathways of arousal and attention, such as the reticular and limbic systems, and the basal ganglia, generally include pathological fatigue [ 2 ]. Fatigue can also be the primary symptom of a disease itself – this is the case in chronic fatigue syndrome (CFS), which might therefore prove to be a good model for studying the mechanisms underlying fatigue sensation. CFS is a clinically defined condition characterized by severe disabling fatigue and a combination of symptoms, the prominent features being self-reported impairments in concentration and short-term memory, sleep disturbances and musculoskeletal pain [ 4 ]. The diagnosis of CFS can be made only after alternative medical and psychiatric causes of chronic fatigue have been excluded [ 4 ]. Recent studies found biochemical and genetic characteristics in CFS patients, such as a decreased concentration of serum acetyl-L-carnitine [ 5 ], a serotonin-transporter gene-promoter polymorphism [ 6 ], and autoantibodies against the muscarinic cholinergic receptor [ 7 ]. Among these, administration of L-carnitine, which is the precursor of acetyl-L-carnitine, is known to improve the clinical status of CFS patients [ 8 ]. In the brain, the acetyl moiety of acetyl-L-carnitine is utilized mainly for the biosynthesis of L-glutamate [ 9 ]. In CSF patients, a significant decrease in the uptake of acetyl-L-carnitine was found in several regions of the brain, including the prefrontal (Brodmann's area (BA) 9/46d), temporal (BA21 and 41), and anterior cingulate (BA24 and 33) cortices and cerebellum [ 9 ]. However, whether such focal cortical hypofunction is due to an anatomical abnormality has not yet been investigated. We hypothesize that there might be regions with explicit anatomical abnormalities that correlate with the severity of fatigue. To measure the reduction in gray-matter volume, we conducted voxel-based morphometry with high-resolution magnetic resonance imaging (MRI) [ 10 , 11 ]. Methods Sixteen CFS patients (aged 24–46 years; average age 34.0 years; 10 men and 6 women) and 49 age-matched healthy control subjects (aged 21–47 years; average age 34.4 years; 27 men and 22 women) were enrolled in the study. They were recruited from the outpatient fatigue clinic in Osaka University Hospital (HK's special clinic) where more than 430 CFS patients, who met the diagnostic criteria of CFS [ 4 ], are being followed. The protocol was approved by the ethical committee of the National Institute for Physiological Sciences, Japan, and all subjects gave their written informed consent for the study. The periods of CFS lasted between 10 and 244 months, and the mean duration was 69.8 months (Table 1 ). All CFS patients were unable to carry out normal activities or actively work for several days a week because of severe general fatigue at the time of diagnosis. The severity of fatigue was measured using self-reported ratings based on daily activities (performance status; Table 2 ). A detailed neurological examination, the time course of the patients' signs and symptoms, and additional MRI (for 7 out of 16 patients) made the diagnosis of multiple sclerosis (MS) unlikely. The characteristics of the patients are shown in Table 1 . To compare brain volumes, high-resolution anatomical images were acquired using a 3 Tesla MR scanner (Allegra, Siemens, Erlangen, Germany). A three-dimensional structural MRI was acquired for each subject using a T1-weighted magnetization-prepared rapid-gradient echo sequence (repetition time, 1970 ms; echo time, 4.3 ms; inversion time, 990 ms; number of excitation, 1; flip angle, 8°; matrix size, 256 × 256; field of view, 210 × 210 mm) yielding 160 sagittal slices with a slice thickness of 1.2 mm and an in-plane resolution of 0.82 mm. Table 1 Patient Characteristics Patient number Age (years) Duration (months) PS Difficulty in thinking Inability to concentrate 1 39 132 8 2 2 2 33 56 8 2 1 3 26 10 4 2 2 4 31 37 2 1 1 5 30 36 8 2 2 6 27 42 5 1 2 7 27 100 7 1 1–2 8 27 153 8 2 2 9 37 17 4 1 1 10 46 244 2 2 2 11 24 10 4 1 1 12 34 10 7 2 2 13 36 131 7 2 2 14 35 14 6 1 1 15 46 56 8 2 2 16 45 69 7 2 2 Level of fatigue, difficulty in thinking, inability to concentrate and depression are rated as follows: 2, severe; 1, mild; 0, none. PS, performance status at MRI examination. Table 2 Performance-status scores for evaluating the severity of fatigue in CFS patients. Scores Condition 0 No complaints; able to carry on normal activity without fatigue. 1 Able to carry on normal activity, but sometimes feels fatigue. 2 Able to carry on normal activity or to do active work with effort; requires occasional rest. 3 Several days a month, unable to carry on normal activity or to do active work; requires rest at home without work. 4 Several days a week, unable to carry on normal activity or to do active work; requires rest at home without work. 5 Unable to carry on normal activity or to do active work at all, although able to perform light tasks; requires rest at home without work for several days a week. 6 Requires rest without work at home for over one-half of a week; able to do light tasks in good health. 7 Unable to carry on normal activity or to do light tasks at all; able to care for self without assistance. 8 Remains in bed for more than one-half of each day; able to care for self to some extent, but requires frequent assistance. 9 Unable to care for self; must remain in bed with day-long assistance. Voxel-based morphometry (VBM) [ 12 ] was performed using SPM2 for image processing and was analyzed with SnPM99 [ 13 ] implemented in MATLAB 6.1 (MathWorks, Natick, MA, USA). VBM is a fully-automated whole-brain morphometric technique that detects regional structural differences between groups on a voxel-by-voxel basis. Briefly, images were segmented into gray matter, white matter, cerebrospinal fluid and skull/scalp compartments, then normalized to standard space and re-segmented. Any volume changes induced by normalization were adjusted [ 10 , 11 ]. The spatially normalized segments of gray and white matter were smoothed using a 12-mm full-width half-maximum isotropic Gaussian kernel. Statistical analysis of regional differences between groups was performed using a permutation test for decreased probability of a particular voxel containing gray or white matter. Potential confounding effects of age, sex and whole segment (gray or white matter) volume differences were modeled, and the variances attributable to them were excluded from the analysis [ 11 , 14 , 15 ]. The significance levels for statistics estimated by 500 nonparametric randomization and permutation tests were set at P = 0.05, corrected for multiple comparisons. Within the areas showing a significant volume reduction in patients, linear correlates between volume reduction and the degree of fatigue were examined under the threshold of P < 0.005. Results We observed a significant reduction in gray-matter volume in the bilateral prefrontal areas of CSF patients (Figure 1 ). The affected areas extended from BA8 to 9 in the right cerebral hemisphere, and from BA9 to 11 in the left. In comparison with healthy controls, there was an average of 11.8% volume reduction in CSF patients. Within these areas, there was a significant negative correlation between the gray-matter volume of the right prefrontal cortex and the performance status of the CFS group (r 2 = 0.46, P = 0.004; Figure 2 ). This relationship was confirmed using Spearman's rank-correlation coefficient (P = 0.004). In this area, the gray-matter volume was reduced by 16.9% for patients compared with controls. No significant atrophy was observed in the white matter of CFS patients. Figure 1 Regional differences between CFS patients and controls. Areas with significantly reduced gray-matter densities in the CFS patients were located at bilateral prefrontal areas, which were surface rendered onto the high-resolution MRI. The colored bar indicates the t-values. Figure 2 (Left) Correlations between volume and the performance status of CFS patients in the right prefrontal cortex (BA9; Talairach's coordinates: x = 48, y = 32 and z = 41). The colored bar indicates the t-values. (Right) Gray-matter volumes of CFS patients at the voxels of maximum correlation (r = 0.71) plotted against the performance status. The linear-regression line is plotted in blue. a.u., arbitrary units; Rt PFC, right prefrontal cortex. Discussion The present study provides the first report of focal gray-matter atrophy in the prefrontal cortex of CFS patients. Previous MRI studies of CFS revealed non-specific abnormalities: hyperintense small punctuated subcortical white-matter foci were observed predominantly in the frontal lobes [ 16 ] and their prevalence did not differ from an age-matched control group [ 17 , 18 ]. Ventricular enlargement was also reported [ 19 ]. Usually, MRI abnormalities in CSF patients cause the physician to conclude that the symptoms might be secondary to another medical condition [ 20 ]. Prefrontal pathology has been reported in MS with pathological fatigue [ 21 ]. Roelcke and colleagues [ 21 ] reported that MS patients with fatigue had a reduction of the cerebral metabolic rate of glucose (CMRGlu) in the bilateral prefrontal areas compared with MS patients without fatigue. Moreover, scores on the fatigue-severity scale were inversely related to CMRGlu levels in the right prefrontal cortex, suggesting that fatigue in MS is associated with prefrontal dysfunction due to the demyelination of frontal white matter [ 21 ]. Although the Talairach's coordinates reported by Roelcke and colleagues (x = 18, y = 42 and z = 20) were more medial and ventral than those observed here (x = 48, y = 32 and z = 41), both results suggest that prefrontal hypofunction might underlie pathological fatigue. Although MS should be excluded in the diagnosis of CFS, as in the present study, the similar clinical manifestations of the illnesses suggest that a common pathogenesis underlies the symptoms of fatigue in both disorders. This speculation is supported by the fact that the administration of L-carnitine, which improves fatigue in CFS patients, was effective for treating fatigue in MS patients [ 22 ]. In the present study, right dorsolateral prefrontal-cortex atrophy was significantly correlated with the severity of fatigue, as measured by the performance-status scores. As the performance status rates the daily activities that trigger or aggravate fatigue, this correlated volume reduction might reflect a functional deficiency that makes patients susceptible to fatigue. A single site in the dorsolateral prefrontal cortex revealed the parallel between volume reduction and fatigue severity. This does not necessarily mean that it is fatigue-specific; instead, this area might be the part of the network that, when functioning sub-normally, results in pathological fatigue. Fatigue is also a symptom of diseases that affect the basal ganglia, and that interrupt the connection between the prefrontal cortex and thalamus [ 3 ]. Hence, frontal-subcortical circuits might be important contributors to the sense of fatigue. The dorsolateral prefrontal cortex has dense widespread subcortical and cortical connections [ 23 ]. A series of parallel frontal-subcortical circuits have been described that link specific regions of the frontal cortex to the striatum, globus pallidus and thalamus [ 24 ]. These originate in the prefrontal cortex, project into the striatum (caudate, putamen and ventral striatum), connect to the globus pallidus and substantia nigra, and from there connect to the thalamus. There is then a final link back to the frontal cortex in each circuit, forming a closed loop [ 25 ]. Corticostriatal and thalamocortical connections use excitatory glutamatergic projections [ 25 ]. Frontal-subcortical circuits serve as organizational axes, integrating related information from widespread areas of the brain and mediating diverse behaviors. The three principal behaviorally-relevant circuits originate in the dorsolateral prefrontal, orbitofrontal and anterior cingulate cortices [ 26 ]. The marker behaviors specific to each circuit are executive dysfunction (dorsolateral prefrontal-subcortical circuit), disinhibition (orbitofrontal-subcortical circuit) and apathy (medial frontal-subcortical circuit), respectively [ 26 ]. Hence, these circuits are capable of concurrent participation in separate functions, including motor, cognitive and limbic processing [ 3 ]. The dorsolateral prefrontal cortex also has widespread reciprocal corticocortical connections with posterior temporal, parietal and occipital association areas [ 23 ]. Furthermore, at the level of the frontal lobes, the orbitofrontal, anterior cingulate and dorsolateral prefrontal cortices are linked to each other without cross connections at subcortical levels [ 26 ]. Therefore, the dorsolateral prefrontal cortex is poised to serve as a principal site for the integration of information. These anatomical and functional characteristics of the frontal-subcortical circuits suggest that the large decrease in acetyl-L-carnitine uptake in the dorsolateral prefrontal, anterior cingulate and temporal cortices [ 9 ] represents hypofunction of the frontal-subcortical circuits. Furthermore, this decrease might be due to the remote effects of the pathology in the dorsolateral prefrontal cortex [ 27 ]. Recently, Fillippi et al. [ 28 ] underwent fMRI with MS patients with fatigue using simple motor task. They found inverse correlation between fatigue severity score and the task-related activity of the thalamus, concluding that fatigue could be secondary to dysfunction of corticosubcortical circuits. Thus, according to the model by Chaudhuri and Behan [ 3 ], hypofunction of the dorsolateral prefrontal cortex might interrupt the associated striato-thalamo-cortical loop, resulting in enhanced fatigability. Conclusions The results of the present study suggest that the dorsolateral prefrontal cortex might be an important component of the neural substrates that regulate the sensation of fatigue. List of abbreviations BA, Brodmann's area; CMRGlu, cerebral metabolic rate of glucose; CFS, chronic fatigue syndrome; MRI, magnetic resonance imaging; VBM, voxel-based morphometry Competing interests The author(s) declare that they have no competing interests. Authors' contributions TO carried out the MRI scanning, data analysis and drafted the manuscript. MT conducted MRI scanning and participants' coordination. HK conducted the medical evaluation of the participants. YW and NS participated in the study design. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC524491.xml |
528724 | Chemical and Genetic Screens Hit the Target in Cytokinesis | null | Cytokinesis, in which newly formed daughter cells separate, is the culmination of the cell cycle. It is necessary for normal growth and development, and it is also a sine qua non in the pathogenesis of cancers—cells that can't divide can't form tumors, can't metastasize, and can't kill. Therefore, understanding the full range of proteins involved in cytokinesis has both deep theoretical and immediate practical applications. In this issue, Ulrike Eggert and colleagues report results from two complementary screening approaches to identify those proteins and to discover molecules that inhibit them. A cell cannot divide if it lacks a protein vital for cytokinesis or if that protein is inhibited. When that occurs, the cell retains both nuclei, and can be quickly identified by an automated process. Working with Drosophila cells, the first screen used almost 20,000 double-stranded RNAs, representing virtually the entire Drosophila genome. A double-stranded RNA pairs with, and causes the destruction of, a matching messenger RNA, thus preventing the encoded protein from being formed, a process called RNA interference (RNAi). The authors identified 214 proteins whose absence prevented cytokinesis. While some of these, including actin and Myosin, were already known to be essential for the process, others were not. The latter included a new discovery, CG4454 (named Borealin-related or Borr), which was found to be one of the handful of proteins deemed most critical to cytokinesis. Drosophila cells that have failed to divide The second screen also treated Drosophila cells, but this time used over 50,000 “small molecules,” a catchall term for molecules small enough to pass easily into cells. The vast majority of drugs currently in clinical use are small molecules. This screen revealed 50 cytokinesis inhibitors, of which 25, dubbed binucleines, were selected for further characterization. Not surprisingly, several inhibited actin, whose role in cytokinesis is key in contraction of the cytokinesis furrow. For the purposes of this study, however, binucleines affecting other proteins were even more interesting. By comparing the appearances of binucleate cells from the small-molecule screen with those from the RNAi screen, Eggert et al. identified one molecule and three proteins that caused a similar phenotype, suggesting that the three proteins acted within a single pathway, which the molecule could disrupt. One of the three proteins was CG4454/Borr, and the researchers' results indicated it interacts with Aurora B, an essential but still poorly understood protein that is needed for proper division of the chromosomes. The identified binucleine will be a valuable reagent for exploring the details of the Aurora B pathway. While these results are from Drosophila , the insights they provide into the cell cycle are likely to be applicable to humans as well. Equally importantly, they provide the proof of principle for a new drug discovery method. A major bottleneck in drug development is target identification—determining which of the cell's thousands of proteins is the right one to inhibit with a drug. The unique aspect of this study is the parallel use of the two approaches—small molecules and RNAi—to provide a “stereoscopic” view of cytokinesis and its inhibition. Working together, they provide a set of proteins and a matched set of inhibitors, the target and the bullet at the same time. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC528724.xml |
517729 | Disability weights for the burden of oral disease in South Australia | Background Australian burden of disease estimates appeared inconsistent with the reported repetitive and ubiquitous nature of dental problems. The aims of the study were to measure the nature, severity and duration of symptoms for specific oral conditions, and calculate disability weights from these measures. Methods Data were collected in 2001–02 from a random sample of South Australian dentists using mailed self-complete questionnaires. Dentists recorded the diagnosis of dental problems and provided patients with self-complete questionnaires to record the nature, severity and duration of symptoms using the EuroQol instrument. Data were available from 378 dentists (response rate = 60%). Results Disability weights were highest for pulpal infection (0.069), caries (0.044) and dentinal sensitivity (0.040), followed by denture problems (0.026), periodontal disease (0.023), failed restorations (0.019), tooth fractures (0.014) and tooth wear (0.011). Aesthetic problems had a low disability weight (0.002), and both recall/maintenance care and oral hygiene had adjusted weights of zero. Conclusions Disability weights for caries (0.044), periodontal disease (0.023) and denture problems (0.026) in this study were higher than comparable oral health conditions in the Australian Burden of Disease and Injury Study (0.005 for caries involving a filling and 0.014 for caries involving an extraction, 0.007 for periodontal disease, and 0.004 for edentulism). A range of common problems such as pulpal infection, failed restorations and tooth fracture that were not included in the Australian Burden of Disease and Injury Study had relatively high disability weights. The inclusion of a fuller range of oral health problems along with revised disability weights would result in oral health accounting for a larger amount of disability than originally estimated. | Background Although dental problems are widespread in number and impose a large burden on society in terms of lost production, pain and suffering, and health expenditure there is a tendency to underestimate their importance due to the generally non-fatal nature of most oral diseases and complacency arising from acknowledged improvements in oral health, such as trends toward lower caries levels among children and decreased edentulism in adults. Australians spend $2.6 billion on dental services, some 5.4% of recurrent health expenditure for 1998–99 [ 1 ]. While dental diseases are not usually life-threatening, the importance of delivering services needs to be considered in view of the repetitive and ubiquitous nature of dental problems which combine to create a large burden. For example, dental problems were ranked as the fourth most frequent illness condition, behind headache, hypertension and colds in a two week survey period [ 2 ], dental caries (decay) has been ranked as the highest diet-related disease in Australia in terms of both total costs and health care costs [ 3 ], and periodontal (gum) disease has been reported to be the fifth most prevalent health condition in Australia [ 4 ]. The disability-adjusted life year or DALY [ 5 , 6 ] provides a summary measure of population health that combines information on the impact of premature death and of disability and other non-fatal health outcomes. The Australian Burden of Disease and Injury Study used the DALY approach to assess the magnitude and impact of health problems in Australia [ 7 ]. This burden of disease methodology is designed to inform health policy in relation to the prevention and treatment of health problems. This provides a different picture to traditional approaches that take into account deaths, but not disability. However, the authors acknowledge that further work is required to refine and develop the data and methods. Estimates of DALYs are limited by inadequate information on the distribution of severity of disease and the course of a disease. Due to limitations in the data many of the disease models are necessarily simple and approximate, with their precision reflecting the source and nature of the data underlying the model. Also, the lack of Australian disease weights may mean that they are not completely representative of Australian societal preferences [ 7 ]. Hence the estimates of YLD (Years Lost due to Disability) and DALYs (Disability-Adjusted Life Years) should be regarded as provisional and developmental. The DALY estimates for oral health in the Australian Burden of Disease and Injury Study seemed inconsistently low with other reports of the high prevalence and incidence of oral health conditions such as dental caries and periodontal disease [ 4 ]. There are a number of specific problems associated with estimating oral health DALYs. There is a lack of recent national data on oral health. Just one national oral health survey (NOHSA) has been performed in Australia, which was conducted in 1987–88 [ 8 ] and hence is now out of date. Data from other sources [ 9 ] indicates that oral health status in Australia is changing, which makes it difficult to estimate disease models for caries and periodontal disease based on data from NOHSA. Sequelae need to be included in disease models, for example disease models should account for sequelae of caries such as pulpal/periapical infection. Oral health estimates need to include a fuller range of oral conditions such as cuspal fractures. Edentulism estimates were based on self-reported data, and may be under-estimates if edentulous persons are less likely to participate in population surveys of oral health. The disease models were based on assumptions regarding severity and duration of symptoms that may require quantitative confirmation and revision. The broad aims of the project were to evaluate methods used to measure the burden of disease associated with oral conditions in Australia. The specific aims were to obtain measures of burden of disease related to specific oral conditions, measure these in terms of the nature, severity and duration of symptoms, and calculate disability weights from these measures. Methods Design The study was conducted using a 2-stage sampling design whereby dentists were randomly sampled from the South Australian Dental Register, randomised into one of seven equal-sized study groups and sent a mailed self-complete dentist questionnaire along with up to five self-complete patient questionnaires depending on the study group. Dentists were provided with a practitioner logbook in which to record for the first 1 to 5 adult patients (depending on study group assignment of dentist) of a random clinical day the treatment they performed and diagnosis of the oral disease or condition treated. At the conclusion of treatment the practitioner passed on a survey kit to their sampled patient(s) containing a patient questionnaire, cover letter and explanation sheet. Sampled patients completing the patient questionnaire recording basic socio-demographic characteristics and data concerning the nature, severity and duration of their symptoms. The patient questionnaires were identified using the practitioner identification number allowing linkage between the practitioner logbook data and patient questionnaire data, but maintaining the anonymity of each patient to the investigators. Sampling and data collection The emphasis of the project was to obtain precise estimates of the component measures of the burden of oral disease. These are typically expressed as percentages, such as the percentage of persons or percentage of time experiencing symptoms of a given degree of severity. Taking a parameter size of 10% as a reference estimate for any given measure, in order to achieve a level of precision of 20% or less relative standard error, a minimum target sample of 225 patients was required. This would provide an acceptable minimum level of precision for estimates as low as 10% in size, and better precision for any estimates larger than 10% in size. Data were collected during 2001–2 with a primary approach letter sent initially to each dentist, followed a week later by the survey materials, with a reminder card two weeks later, and up to four follow-up mailings of survey materials to dentists who had not yet responded in order to ensure higher response rates [ 10 ]. Data items Dentists recorded the details of the dental conditions that patients had, and patients recorded their experience of those dental conditions. Diagnosis of dental conditions was collected from dentists using an open-ended question in the dentist questionnaire and coded using the coding scheme adopted in the Longitudinal Study of Dentists' Practice Activity [ 11 ]. Data on dental conditions in both the practitioner logbook and patient questionnaire were collected for the main dental condition that was currently being treated, another dental condition being treated besides the main condition, and for dental conditions that were not currently treated. In the patient questionnaire, patients were asked if the dental conditions had caused problems in each of six health state dimensions, the severity of the problem (prevalence and percent of time that problems were experienced in relation to each health state dimension) and duration of problems in each dimension. The six health state dimensions were: mobility (e.g, walking about), self-care (e.g, washing, dressing), usual activities (e.g., work, study, housework, family or leisure), pain/discomfort, anxiety/depression and cognition (e.g, memory, concentration, coherence, IQ). They were measured using the European Quality of Life indicator or EuroQol (EQ-5D+) instrument [ 12 ]. The EuroQol measures each of these six dimensions according to a 3-level response grading from 1 = no problems, 2 = some / moderate problems and 3 = extreme problems. Data analysis Following descriptive analysis of response rates and characteristics of respondents, the distribution of dental conditions was examined for the 11 most common dental conditions. These dental conditions were then examined in terms of the nature, severity and duration of each condition. Disability weights were then calculated for each dental condition by using a health state valuation algorithm based on UK population data [ 13 ]. A patient could have more than one dental condition and hence have more than one disability weight. This initial disability weight was then adjusted by multiplying the coefficients from the health state valuation by the percentage of time affected by the problem. A final adjustment to the disability weights was performed by subtracting the intercept term from the health state valuation equation from the disability weight that had been adjusted by the percentage of time affected by the problem (see appendix 1: additional file 1 for details), as there was some conjecture as to how such an intercept term should be interpreted [ 13 ]. For each type of disability weight (i.e., unadjusted and adjusted) a dental condition-specific weight was calculated as the average of the weights for each patient that had reported having that specific dental condition. Results are reported adjusted for the survey design effect of clustering of patient observations within the primary sampling unit of dentists [ 14 ]. Disability weights were also calculated using the multiplicative EQ-5D+ regression model from the Australian Burden of Disease and Injury Study [ 7 ] as a form of cross-validation of the approach (see appendix 2: additional file 1 for details). Results Response A total of 378 dentists responded to the survey (response rate = 60%). Response rates between study groups ranged from 49% to 70% and tended to be higher in study groups that required dentists to sample less patients, but the effect was not monotonic (Table 1 ). Data were available for 375 patients from the patient questionnaire, comprising a response rate of 72% of patients sampled, with response rates between study groups ranging from 69% to 92%. Table 1 Response to the practitioner logbook and patient questionnaires. Practitioner logbook Patient questionnaire Patients recorded Patients recorded Patients sampled per dentist Number of dentists responding Response rate (%) Number Percent Number Percent Response rate (%) Pilot study 5 60 (65) 135 (17.9) 93 (24.8) (69) Main study (a) 0 61 (70) 237 (31.4) - (-) (-) Main study (b) 1 56 (62) 37 (4.9) 29 (7.7) (78) Main study (c) 2 54 (60) 49 (6.5) 45 (12.0) (92) Main study (d) 3 43 (49) 61 (8.1) 41 (10.9) (67) Main study (e) 4 50 (58) 118 (15.6) 84 (22.4) (71) Main study (f) 5 54 (57) 119 (15.7) 83 (22.1) (70) Total 378 (60) 756 (100.0) 375 (100.0) (72) Characteristics of patients The characteristics of patients are presented in Table 2 where data from private general practice [ 11 ] and Australian population estimates [ 15 , 16 ] are presented for comparison. The majority of patients were female (59.5%), born in Australia (75.5%), had dental insurance (64.8%) and had visited a dentist in the last 12 months (65.3%). The main reason for dental visiting was for other dental problems not involving relief of pain (46.7%), followed by check-ups (35.2%) and emergency visits involving relief of pain (18.1%). Table 2 Characteristics of patients in the Burden of Oral Disease Study compared with private general practice and Australian population estimates. Burden of Oral Disease Study Private General Practice (a) Australian Population % % % Sex % Female 59.5 54.9 (b) 50.4 Place of birth % Australian 75.5 n.a. (b) 76.4 Dental insurance status % Insured 64.8 47.8 (c) 34.8 Reason for dental visit Check-up 35.2 41.1 (c) 45.1 Emergency 18.1 28.6 n.a. Other dental problem 46.7 30.8 n.a. Time since last dental visit % visited in last 12 months 65.3 n.a. (c) 61.3 (a): Longitudinal Study of Dentists' Practice Activity 1998–99 (b): Australian Bureau of Statistics 2002 (c): National Dental Telephone Interview Survey 1999 n.a. : denotes data not available Dental condition The distribution of dental conditions is presented in Fig 1 for the 11 most common conditions. Recall/maintenance (26.7%) and caries (23.7%) were the most common conditions followed by tooth fracture (18.4%), failed restorations (14.9%), pulpal infection and denture problems (both 12.3%), and periodontal disease (11.2%). Further analysis assumes zero disability weights for the conditions of recall/maintenance care and oral hygiene conditions due to the lack of symptoms associated with them, and therefore excludes each of these conditions from further consideration. Figure 1 Distribution of dental conditions (% of patients ± SE). Dental conditions by health state dimensions and duration Dental conditions are presented in Table 3 by health state dimensions and duration. A high percentage of patients reported problems (defined as level 2 = some/moderate or level 3 = extreme) with the dimension of pain or discomfort for problems such as pulpal infection (63%), dentinal sensitivity (55%), tooth wear (40%), caries and denture problems (both 38%) and tooth fracture and periodontal disease (both 35%). A high percentage of patients also reported problems with the dimension of anxiety or depression for problems such as periodontal disease (32%), tooth wear (30%) and dentinal sensitivity (27%). The percentage of time affected by dental conditions was generally high for most dimensions for dental conditions such as caries, tooth fracture, and denture problems, and for the dimensions of pain or discomfort and anxiety or depression for dental problems such as failed restoration, periodontal disease and pulpal infection. Aesthetics had the longest duration among dental conditions, however aesthetic problems comprised relatively low percentages of total conditions (as shown in Fig 1 ). Among the more common conditions caries and denture problems had long durations (ranging between 66 and 81 weeks). Table 3 Distribution of health state dimensions (± SE) by dental conditions. Duration (weeks) Health state dimensions Mean Mobility Self-care Usual activities Pain / discomfort Anxiety / depression Cognition Caries 81 ± 18 Prevalence (a) (3) 4 ± 2 (3) 3 ± 2 14 ± 4 38 ± 6 19 ± 5 (1) 10 ± 3 Time (b) (3) 25 ± 14 33 ± 8 26 ± 6 42 ± 7 34 ± 9 29 ± 8 Fracture (1) 27 ± 9 Prevalence (a) (3) 3 ± 2 (3) 3 ± 3 (3) 3 ± 2 35 ± 6 18 ± 5 (2) 10 ± 4 Time (b) †10 - †50 28 ± 7 (3) 20 ± 14 (3) 55 ± 45 Denture problem (1) 66 ± 24 Prevalence (a) (2) 13 ± 6 (3) 3 ± 3 (2) 16 ± 7 38 ± 10 (1) 22 ± 7 (1) 19 ± 7 Time (b) (3) 28 ± 24 †100 (3) 40 ± 23 33 ± 6 (1) 34 ± 10 (3) 25 ± 14 Failed restoration 15 ± 4 Prevalence (a) 0 0 (3) 2 ± 2 27 ± 6 (2) 10 ± 4 (3) 4 ± 3 Time (b) - - - 29 ± 8 (2) 23 ± 11 (3) 10 ± 10 Periodontal disease (1) 49 ± 19 Prevalence (a) (3) 3 ± 3 0 (3) 3 ± 3 35 ± 8 32 ± 9 (3) 3 ± 3 Time (b) - - - 32 ± 7 28 ± 7 - Pulpal infection 31 ± 8 Prevalence (a) (3) 2 ± 2 0 (3) 12 ± 6 63 ± 8 (1) 22 ± 7 (1) 10 ± 5 Time (b) †10 - 32 ± 9 46 ± 6 41 ± 6 (1) 30 ± 12 Wear (1) 69 ± 23 Prevalence (a) 0 0 0 (2) 40 ± 16 (3) 30 ± 15 (3) 10 ± 10 Time (b) - - - (2) 9 ± 4 (3) 33 ± 17 †50 Sensitivity (2) 21 ± 9 Prevalence (a) 0 0 0 55 ± 16 (3) 27 ± 14 0 Time (b) - - - (3) 21 ± 12 (3) 28 ± 23 - Aesthetics (2) 118 ± 51 Prevalence (a) 0 0 0 (3) 27 ± 19 (3) 9 ± 9 (3) 9 ± 9 Time (b) - - - (3) 5 ± 3 †5 †25 (a) Percentage of patients reporting problems (at level 2 = some/moderate or level 3 = extreme) with a health state dimension related to the dental condition (b) Percentage of time during the period that the patient had experienced reported symptoms or problems related to the dental problem -: denotes no observations †: denotes one observation only (1): Relative standard error = 30–39% (2): Relative standard error = 40–49% (3): Relative standard error = 50–59% Dental conditions by disability weights Unadjusted disability weights derived from the additive model (DW a ) were highest for pulpal infection, dentinal sensitivity and caries, followed by denture problems, periodontal disease, tooth wear and tooth fractures (Table 4 ). When adjusted by the percentage of time that dental conditions were experienced all disability weights (DW b ) were reduced. Pulpal infection remained the highest adjusted disability weight, followed by caries and dentinal sensitivity, followed by denture problems, periodontal disease and failed restorations. Subtracting the intercept from the unadjusted disability weight reduced all weights (DW c ) by a constant amount. Table 4 Disability weights (95% CI) by dental problem – derived from additive model. Unadjusted Disability Weight (DW a ) Disability Weight (DW b ) adjusted by % time experienced problems Disability Weight (DW c ) adjusted by % time experienced problems minus intercept‡ Caries 0.185 (0.143–0.226) 0.125 (0.094–0.157) 0.044 (0.013–0.076) Fracture 0.150 (0.123–0.178) 0.095 (0.085–0.105) 0.014 (0.004–0.024) Denture problem 0.163 (0.124–0.200) 0.107 (0.084–0.130) 0.026 (0.003–0.049) Failed restoration 0.136 (0.105–0.166) 0.100 (0.081–0.118) 0.019 (0.0001–0.037) Periodontal disease 0.158 (0.123–0.194) 0.104 (0.090–0.119) 0.023 (0.009–0.038) Pulpal infection 0.210 (0.162–0.258) 0.150 (0.110–0.191) 0.069 (0.029–0.110) Wear 0.152 (0.093–0.210) 0.092 (0.078–0.107) †0.011 (0.000–0.026) Sensitivity 0.191 (0.102–0.281) 0.121 (0.045–0.198) †0.040 (0.000–0.118) Aesthetics 0.121 (0.067–0.175) 0.083 (0.080–0.086) †0.002 (0.000–0.005) † confidence interval truncated at zero ‡ standard error for DW c is the same as DW b due to transformation by a constant The disability weights derived from the multiplicative model are presented in Table 5 . The unadjusted disability weights derived from the multiplicative model (DW d ) followed a similar rank order as for the unadjusted disability weights derived from the additive model (DW a ), being highest for pulpal infection with caries ranked second-highest, but with some re-ordering of the next highest conditions (i.e., denture problems were ranked second rather than fourth, while dentinal sensitivity was ranked fourth rather than second, then followed in the same order by periodontal disease and tooth wear). When adjusted by the percent of time that dental conditions were experienced all disability weights derived from the multiplicative model (DW e ) were reduced, with pulpal infection ranked highest, followed by caries, dentinal sensitivity, denture problems, tooth wear and periodontal disease. Table 5 Disability weights (95% CI) by dental problem – derived from multiplicative model. Unadjusted Disability Weight (DW d ) Disability Weight (DW e ) adjusted by % time experienced problems Caries 0.121 (0.073–0.170) 0.059 (0.022–0.095) Fracture 0.091 (0.050–0.132) 0.021 (0.006–0.035) Denture problem 0.124 (0.070–0.179) 0.041 (0.007–0.075) Failed restoration 0.065 (0.028–0.102) 0.030 (0.005–0.054) Periodontal disease 0.106 (0.056–0.156) 0.034 (0.017–0.052) Pulpal infection 0.128 (0.067–0.191) 0.076 (0.028–0.123) Wear 0.099 (0.005–0.193) †0.036 (0.000–0.083) Sensitivity 0.112 (0.007–0.218) †0.048 (0.000–0.138) Aesthetics †0.050 (0.000–0.110) †0.002 (0.000–0.005) † confidence interval truncated at zero The final adjusted disability weights derived from the additive (DW c ) and multiplicative (DW e ) models were similar in rank ordering, with pulpal infection, caries, dentinal sensitivity and denture problems ranked highest. While the adjusted disability weights derived from both models were also similar in magnitude those derived from the additive model were lower for all oral conditions except aesthetics, which was identical for both models. In the remainder of the paper the final adjusted disability weights derived from the additive model (DW c ) will be presented, as this provided the most conservative estimate. Comparison of disability weights The disability weights for oral conditions are presented in Table 6 along with the weights for oral conditions from the Australian Burden of Disease and Injury Study [ 7 ]. Comparing edentulism with denture problems shows a higher disability weight in the Burden of Oral Disease Study estimate. For periodontal disease the disability weight estimate from the Burden of Oral Disease Study was higher. For caries, the disability weight was higher for the Burden of Oral Disease Study estimate than either of the two estimates for caries from the Australian Burden of Disease and Injury Study. Table 6 Comparison of oral health disability weights by source. Australian Burden of Disease and Injury Study Burden of Oral Disease Study Edentulism Denture problems Edentulism 0.004 Denture problem 0.026 Periodontal disease Periodontal disease Periodontal disease 0.007 Periodontal disease 0.023 Caries Caries Caries (filling) 0.005 Caries (all cases) 0.044 Caries (extraction) 0.014 The disparity in disability weights for oral health conditions between the Australian Burden of Disease and Injury Study and the Burden of Oral Disease Study is examined further in Table 7 , which compares the assumptions for oral health disability weights by source. Comparing edentulism estimates with those for denture problems shows a slightly higher estimate for percentage of time affected and a more marked difference in percentage of cases affected in the Burden of Oral Disease Study estimates. For periodontal disease the estimates from the Burden of Oral Disease Study are higher for both percentage of time and percentage of cases. For caries, estimates of percentage of time and duration for moderate pain and moderate anxiety were both higher for the Burden of Oral Disease Study, as was the estimate for extreme pain. Table 7 Comparison of assumptions for oral health disability weights by source. Australian Burden of Disease and Injury Study Burden of Oral Disease Study (a) Edentulism % of time % of cases Denture problems %(± se) of time %(± se) of cases Moderate pain 25% of time 10% of cases Moderate pain 33 ± 6% of time 38 ± 10% of cases Moderate anxiety 25% of time 10% of cases Moderate anxiety (1) 34 ± 10% of time (1) 22 ± 7% of cases Periodontal disease % of time % of cases Periodontal disease %(± se) of time %(± se) of cases Moderate pain 10% of time 10% of cases Moderate pain 30 ± 8% of time 32 ± 8% of cases Caries % of time Duration Caries %(± se) of time Duration (± se) (a) filling (a) all caries Moderate pain 20% of time 2 months Moderate pain 34 ± 5% of time (1) 29 ± 9 months Moderate anxiety 20% of time 2 months Moderate anxiety 34 ± 10% of time (1) 13 ± 5 months (b) extraction (b) all caries Extreme pain 20% of time 2 weeks Extreme pain 59 ± 14% of time (2) 50 ± 23 weeks Moderate anxiety 20% of time 2 weeks Moderate anxiety 34 ± 10% of time (1) 51 ± 18 weeks (a): Estimates are reported specific to level of problem (eg, moderate), dimension (eg, pain) and condition (eg, caries) (1): Relative standard error = 30–39% (2): Relative standard error = 40–49% For comparison purposes the disability weights for oral conditions are presented in Table 8 along with a range of weights for other health conditions from the Australian Burden of Disease and Injury Study [ 7 ] classified into disability classes [ 17 ]. Some oral conditions such as dental aesthetics have very low weights, (e.g., 0.002). Conditions such as tooth wear and tooth fracture had weights comparable with moderate anaemia. Denture problems, failed restorations and periodontal disease were lower but comparable with the weight for mild asthma. Dentinal sensitivity and caries were comparable with the weight for an episode of influenza. Pulpal infection, which had the highest weight of all oral conditions, had a weight comparable with acute sinusitis and lower than other conditions such as severe anaemia and gastroenteritis. Table 8 Comparison of disability weights for a range of health conditions by source. Disability class Disability weights Health condition Disability Weight Source Oral/dental conditions 1 0.00–0.01 Aesthetics (dental) 0.002 Current study Yes Anaemia (mild) 0.005 ABDS 2 0.01–0.05 Wear (tooth) 0.011 Current study Yes Anaemia (moderate) 0.011 ABDS Fracture (tooth) 0.014 Current study Yes Failed restoration 0.019 Current study Yes Periodontal disease 0.023 Current study Yes Denture problem 0.026 Current study Yes Asthma (mild) 0.030 ABDS Sensitivity (dentinal) 0.040 Current study Yes Caries 0.044 Current study Yes Influenza (episode) 0.047 ABDS 3 0.05–0.10 Chronic back pain (episode) 0.060 ABDS Sinusitis (acute) 0.061 ABDS Pulpal infection 0.069 Current study Yes Anaemia (severe) 0.090 ABDS Gastroenteritis 0.093 ABDS 4 0.10–0.15 Mild depression (episode) 0.140 ABDS 5 0.15–0.20 Measles 0.152 ABDS Trachoma (moderate) 0.170 ABDS Conjunctivitis 0.180 ABDS 6 0.20–0.30 Asthma (severe) 0.230 ABDS Tuberculosis 0.295 ABDS 7 0.30–0.40 Moderate depression (episode) 0.350 ABDS 8 0.40–0.50 Trachoma (severe) 0.430 ABDS 9 0.50–0.65 Tetanus 0.612 ABDS 10 0.65–0.80 Severe depression (episode) 0.760 ABDS 11 0.80–1.00 Cancer (terminal stage) 0.930 ABDS ABDS: Australian Burden of Disease and Injury Study Discussion Response Response rates to the survey were adequate for both the dentist and patient questionnaires [ 18 ]. Comparison of respondents against estimates for private general practice and the Australian population indicated a slightly higher percentage of female patients compared to the population consistent with higher reported visiting rates by females [ 16 ], but both place of birth and time since last visit was similar. While dental insurance was higher, the percentage of check-up visits was lower among patients indicating a higher percentage of dental problems for patients compared to the population. The method of sampling patients showed that response rates tended to be higher among dentists who had to sample fewer patients consistent with a lower response burden, but selection of an optimal collection methodology requires consideration of efficiency of collection as well as response rates. Burden of disease approach The burden of disease approach is grounded on the use of the DALY to quantify the burden of disease that treats 'like as like' within an information set of health conditions of individuals [ 19 ]. While use of DALYs has been criticised on the basis of its assumptions and value judgements [ 20 ], Murray & Acharya [ 19 ] argue that the widespread use of DALYs makes them a convenient tool for comparative burden of disease and cost-effectiveness analyses. The EuroQol was developed as a standardised non-disease-specific instrument for describing and valuing health-related quality of life [ 12 ] and hence represents the best method to quantify DALYs. The EuroQol is intended to complement other forms of quality of life measures and it was purposefully developed to generate a generic index of health. Any classified health state can be valued using preferences elicited from a general population [ 12 ], and values can be modelled from such data sets [ 13 , 21 ]. The EuroQol is widely used internationally and reported to have adequate construct and convergent validity, but is highly skewed and has relatively poor sensitivity especially in relation to disease-based outcomes research [ 22 ]. The six dimensions of the EuroQol were used as a standardized description of health status in the development of disability weights for the Dutch Disability Weights Study [ 17 ]. The Australian Burden of Disease and Injury Study adopted the Dutch weights where possible. While both DALYs and the EuroQol instrument have their critics, if these approaches continue to influence policy decisions as to the scope and importance of oral disease then there will be an increasing need to assess the validity of the estimates and to address any shortcomings that are identified. Assumptions of disability weights Differences in disability weights between the Australian Burden of Disease and Injury Study and this paper probably reflect a lack of quantitative data in the Dutch study related to the nature of symptoms experienced by persons with dental conditions. The data from this paper shows that many common dental conditions are associated with symptoms that on average were more severe and of longer duration than previously assumed by Stouthard et al. [ 17 ]. The calculation of disability weights in this paper was based on the use of EuroQol health state descriptions as in the Dutch study, but instead of using a panel approach to elicit valuations we adopted a model-based approach to estimate health state valuations for each individual response and then derive a disability weight as the average of those individual estimates. Such a model-based approach was also used as a source of validation in the original Dutch study but was not developed in detail due to the lack of an adequate statistical model at the time of development [ 23 ]. Two strategies are recognised as ways of arriving at a link between epidemiological data and disability weights [ 24 ]. The first one is derivation of disease-specific disability weights using health state descriptions with a disease label. The second approach, adopted in this study, is derivation of disability weights using generic descriptions of health states associated with specific diseases. In this study disability associated with oral disease was described using a generic measure (the EuroQol) valued by applying an existing formula [ 13 ]. The advantage of this approach is the transparency of the valuation task and the use of the formula provides the facility to cover generic health states without additional valuation studies [ 24 ]. Disability weights reflect health state valuations whereby weights are assigned to health states that are worse than ideal health. A range of methods can be used to elicit health state valuations including visual analogue scale, time trade-off and person trade-off. The visual analogue scale method uses a scale anchored by the best imaginable health state at 100 and death at 0, with respondents asked to indicate the exact point on the scale they would place a particular health state relative to the best imaginable health, death and all other health states. Time trade-off methods ask respondents to imagine choosing between the two options of remaining in a particular health state for 10 remaining years of life or be restored to perfect health but live for a shorter time. Person trade-off methods ask respondents to choose between two different programmes, one that would prevent the deaths of 100 perfectly healthy individuals and one that would prevent the onset of a particular health problem in a certain number of healthy people. While there is little agreement as to which method is most appropriate [ 25 ], it has been shown that visual analogue scale methods tend to give lower values for particular health states, than time trade-off methods, which give lower health state values than person trade-off methods. The additive model weights in this study were derived from a U.K. study based on valuations produced from visual analogue scale and time trade-off methods [ 13 ] whereas the multiplicative model weights were derived from a Dutch study based on visual analogue scale and person trade-off methods [ 23 ]. It could be argued that since the Australian Burden of Disease and Injury Study used disability weights based on person trade-off methods and this study used disability weights based on time trade-off methods that any differences between the disability weights from this study with the Australian Burden of Disease and Injury Study could reflect differences in methodology. Also, the Australian Burden of Disease and Injury Study used a multiplicative model fitted to the Dutch weights for 153 disease sequelae or stages as multiplicative multi-attribute functions were preferred for providing better fit to observed preference data than additive models [ 7 ]. However, the final adjusted disability weights derived from the additive model produced results that were consistent with, but slightly lower than, the multiplicative model. Therefore methodological issues stemming from valuation and modelling strategies do not seem to explain the differences that were observed. One consideration arising from the disability weights derived in the present study was the reliance on the use of data from patients seeking care. The experience of dental problems from the perspective of a patient may be different than that from the population as a whole. If the symptoms experienced by patients were more severe compared to the general population then some further adjustment may be required to reduce the disability weights appropriately. However, it would not be right to assume that most patients attending for dental care would be symptomatic as patient-based data have shown that the majority of patients reported no problems on the six EuroQol dimensions (ranging from 69.7% for pain/discomfort to 98.6% for self-care), with 39.6% of patients reporting symptoms on one or more of the six dimensions [ 26 ]. Conversely, patients who are unable or unwilling to seek care can be expected to have a longer duration, and perhaps severity of dental symptoms and associated health problems than subjects in this study. There is some evidence of a symptom iceberg with respect to oral and facial pain, with Canadian population data showing that less than one in two who experience such pain consult a dentist or physician [ 27 ]. Since there are plausible arguments as to why patient-based estimates might reflect either more severe or less severe conditions the question of possible bias in a patient population remains open and perhaps could be settled by further research. An important design feature of this study was the use of dentists to diagnose the oral health conditions that were subsequently reported on by the patients. Further refinement of these disability weights could be achieved through the use of an oral health survey based on a population sample that also uses a linked questionnaire to survey the experience of oral health problems. It may also be the case that further refinements to the algorithm for estimating disability weights that incorporates the cognitive dimension may also increase the size of weights although oral health conditions related to this dimension were not as prevalent as other dimensions that were included such as pain/discomfort and anxiety/depression. The weights derived from the multiplicative model included the cognitive dimension and this may help explain why they were observed to be slightly larger than the weights derived from the additive model. Detailed prospective data would be required to evaluate whether persons report the experience of their symptoms accurately or are more influenced by the end-stage of their disease experience than by the average experience over the period of their symptoms. Generic measures such as SF-36 have been found to be less sensitive to changes in oral health and to exhibit limited construct validity in comparison to specific measures of oral health [ 28 ]. Despite being a generic measure the EuroQol has shown discriminant validity in relation to a range of dental patient, visit and oral health measures [ 29 ]. However, in general there can be problems assigning disability weights to diseases with high prevalence and low severity, relating to the lack of differentiation at this low end of the scale [ 24 ]. Implications of oral health disability weights The findings from this study indicate that oral health conditions may account for a considerably higher level of DALYs than previously thought, due to the lack of quantitative data on the nature of dental conditions. While Australia has not had another national oral health survey since the initial survey of 1987–88, there have been other studies that suggest that dental problems are common [ 2 , 4 ], and account for large amounts of health care costs [ 3 ]. Further work could be done to incorporate the revised disability weights for oral health into new estimates of the burden of disease in order to estimate the impact that such revisions to the disability weights have on the number of DALYs, and how this affects the ranking of oral health problems in relation to other health conditions. Conclusions Compared to the Australian Burden of Disease and Injury Study the adjusted disability weights for oral health conditions in this study were higher for comparable oral conditions of caries (0.044 versus 0.005 for caries involving a filling and 0.014 for caries involving an extraction), periodontal disease (0.023 versus 0.007) and denture problems (0.026 versus 0.004 for edentulism). In addition there were a range of common oral health problems such as pulpal infection, failed restorations and tooth fracture that were not included in the Australian Burden of Disease and Injury Study which had relatively high disability weights. The inclusion of a fuller range of oral health conditions along with revised disability weights would result in oral health accounting for a much larger amount of disability than originally estimated. Competing interests None declared. Authors' contributions DSB and AJS were chief investigators on the grants obtained to fund the study. DSB performed data collection, analysis and drafting of the manuscript. AJS participated in the design and coordination of the study, and completion of the manuscript. All authors read and approved the manuscript. Supplementary Material Additional File 1 Appendix 1: algorithm used to calculate disability weights from the additive model. Appendix 2: algorithm used to calculate disability weights from the multiplicative model Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517729.xml |
528730 | Enhancing the African bioethics initiative | Background Medical ethics has existed since the time of Hippocrates. However, formal training in bioethics did not become established until a few decades ago. Bioethics has gained a strong foothold in health sciences in the developed world, especially in Europe and North America. The situation is quite different in many developing countries. In most African countries, bioethics – as established and practiced today in the west- is either non-existent or is rudimentary. Discussion Though bioethics has come of age in the developed and some developing countries, it is still largely "foreign" to most African countries. In some parts of Africa, some bioethics conferences have been held in the past decade to create research ethics awareness and ensure conformity to international guidelines for research with human participants. This idea has arisen in recognition of the genuine need to develop capacity for reviewing the ethics of research in Africa. It is also a condition required by external sponsors of collaborative research in Africa. The awareness and interest that these conferences have aroused need to be further strengthened and extended beyond research ethics to clinical practice. By and large, bioethics education in schools that train doctors and other health care providers is the hook that anchors both research ethics and clinical ethics. Summary This communication reviews the current situation of bioethics in Africa as it applies to research ethics workshops and proposes that in spite of the present efforts to integrate ethics into biomedical research in Africa, much still needs to be done to accomplish this. A more comprehensive approach to bioethics with an all-inclusive benefit is to incorporate formal ethics education into health training institutions in Africa. | Background Before the modern discipline of bioethics evolved, ethics had been on the centre stage of medical practice for more than two millennia, since the time of Hippocrates. In 1803, Thomas Percival published his book on Medical Ethics , which became the template on which the code of ethics of the American Medical Association was based in 1847 [ 1 ]. Medical ethics then existed as a code of conduct for medical practitioners and was aimed at the physician putting the interests of his patients uppermost at heart. However, the origin of bioethics, as it is known and practiced today, can be traced back to three different but interrelated events: a set of scandals in biomedical research, advancement in medical technology and the civil rights movement [ 2 ]. Of the scandals, the most well-known is the infamous Nazi experimentation on war prisoners and the subsequent Nuremberg trials of the 1940s. As a result of this and other scandals that trailed the medical profession subsequent to Nuremberg, various codes, declarations, guidelines, policies and documents came into existence and became widely applied to research with human subjects and to health care practice as a whole. The scandals and the events thereafter led to three developments. First, physicians became more sensitive to the ethics of the profession. Medicine is a moral discipline but the indirect method of achieving moral acculturation would no longer be sufficient to equip the physician to meet the ethical challenges of modern day biomedical practice. The need for formal education in medical ethics was thus acknowledged. Second, society became sensitized to the necessity of becoming involved in the decisions which ultimately affect their health and liberty. This signaled the decline of paternalism and the rise of liberalism, individual rights and autonomy in medical practice. Third, the coming of other professionals from different disciplines like social sciences, humanities and the law into what had hitherto been the exclusive domain of medical professionals led to the "socialization" of biomedical science, which further spurred on the bioethics movement. The scope of bioethics has continued to expand in response to changes in societal dynamics, medical technology and health care practices. Perhaps more because of its antecedents than for want of content, most of the discourse and writings in the early days of bioethics centred on issues of patient-physician relationship, respect for person, best interest of the patient, and justice in health care delivery. Today, traditional bioethics discussions and literature are changing as new ethical concerns evolve around dilemmas posed by new technology on the subjects of end of life issues, organ donation, human reproduction and human genomics. Moreover, the bioethics agenda has expanded to include the subjects of resource allocation, organizational ethics and public health ethics, among others. Bioethics in its present form is rooted in and largely dominated by western culture. The tempo and content of bioethics discourse are largely influenced by the technological creations of the developed world. However, ethics is not exclusively the domain of the west. Core ethical values are essentially the same for all human communities leaving aside each community's customs, culture and preferences [ 3 ]. According to Potter, bioethics is "the application of ethics to all of life" [ 4 ]. In the globalization of bioethics, different cultural, ethnic and religious perspectives are given a voice. Though bioethics has come of age in the developed and some developing countries, it is still largely "foreign" to most African countries. It is time Africa joined the bioethics bandwagon. Its relevance and applications to science and research are vital and should not be overlooked. The call of this paper therefore, is for bioethics to be integrated as a required component of medical education curriculum in Africa. Discussion Research ethics In the bioethics literature, bioethical discourse and arguments have been most prominent and intense concerning research involving human participants. One major achievement in this regard is the creation of an oversight body that sees to the proper design and conduct of research that conforms to generally acceptable and established ethical guidelines. There resides in this body the duty of ensuring that research sponsors and investigators abide by established conventions for carrying out clinical research. They also perform the role of assuring the safety of research participants and ensuring that participants (and/or society) benefit from the outcome of research. The relevance of this body to modern day health care and research is partly exemplified in the absence of any major scandals in the form and magnitude of those already recorded in history. The establishment of research ethics boards has not solved all the ethical problems of biomedical research though. There is still a lot to do to re-structure, re-empower and re-position the board to match the complexities of the present-day technology-driven medical research and practice. Current efforts in Africa Various bodies within and outside Africa have pioneered the movement towards ensuring that medical research in Africa conforms to international ethical guidelines. This is the aspect of bioethics that is most visible in Africa and has been anchored partly by the Pan African Bioethics Initiative (PABIN), a pan-African organization that was established in 2001 to foster the development of bioethics in Africa with a particular focus on research ethics (5). This idea has arisen in recognition of the genuine need to develop capacity for reviewing the ethics of research in Africa. It is also a condition required by external sponsors of collaborative research in Africa. Ethics workshops and conferences have been held in different parts of Africa, including Tanzania [ 6 ], Zambia [ 7 ], South Africa [ 8 ], Ethiopia [ 9 ], Cameroon [ 10 ] and Nigeria [ 11 , 12 ]. Moreover, some institutions and research centres have established research ethics review committees and some members of these committees have attended training workshops on research ethics. While the present efforts and achievements are commendable, much still needs to be done for the effects to filter through to the grassroots, which is the main arena of research activities and where the burdens of research are most felt. I say this for the following reasons. First, the present efforts are still limited in extent and effect. Hitherto, most of the conferences have taken place in two or three geographical zones of the continent and have been limited to a few days of activities. Of course, the interests and motives of the sponsoring agencies together with the presence on the ground of those who are available to organize the conference locally determine where, when, for how long and the number of participants in the workshop. There is thus restriction on the number of researchers who can attend the conferences from all over Africa and on the amount of knowledge that can be imbibed in those few days. The consequence is that the same few people attend the conferences most of the time. These attendees from a few centres might not be able to change unethical research practices in their countries. Attempts by these few to train their colleagues locally are often constrained by lack of funds. Second, absence of national directories of research activities in most African countries makes the magnitude of biomedical and social sciences research in Africa to be underestimated. For example in Nigeria, five categories of research and researchers are easily identifiable. Individual or institution-supported research is done by students, clinicians (including resident doctors) and other scientists. This category constitutes a significant proportion of research in tertiary academic and health institutions. Industry-sponsored research is undertaken by researchers for pharmaceutical companies to promote new or old drugs. Such research protocol may be indigenously developed or be a part of multicentre trials. In most instances, these companies do not go through the institutions where the researchers are based, but deal directly with individual researchers, who may or may not subject the research protocol to an ethics board review. Collaborative research with colleagues from the developed countries is often externally funded. It includes hospital and community-based trials and mostly involves experimenting with drugs or vaccines. Of particular ethical concern in collaborative research is the fact that external sponsors may differ in their motives for conducting research and there may be limited applicability of research benefits to the country or local community [ 13 ]. Moreover, the clinician/researcher and/or institutions are themselves vulnerable to funding pressures. Another category of research is that which occurs through indigenous government-funded agencies. An example of such an agency is the National Institute for Medical Research, which has been carrying out research in Nigeria for more than thirty years on parasitic, infective and non-infective diseases. Non-Governmental Organizations (NGOs) are also involved to variable extents in both clinic and community-based research. Third, a majority of Africa's research participants are highly vulnerable given their low level of formal education and the political, social and economic milieu in which they live. The fourth reason is that Africa is a pluralistic society with diverse peoples and cultures. While general guidelines may apply in most cases, in some the peculiarities of each ethnic and cultural group will significantly affect what research is done and how it is done in those communities. Lastly, not every research centre has established an ethics review process. Where already established, most of the ethics review committees are grossly underfunded and unequipped for their duties. Clinical ethics This is the branch of bioethics that addresses ethical conflicts that arise in daily clinical practice in health care institutions, through the establishment of hospital ethics committees and ethics consultation services. Fletcher and Siegler define ethics consultation "as a service provided by an individual consultant, team or committee to address the ethical issues involved in a specific clinical case. Its central purpose is to improve the process and outcomes of patents' care by helping to identify, analyze, and resolve ethical problems" [ 14 ]. An ethics consultation service also responds to conflicts that arise from technological improvements in medical care and the increasing pressure to meet a perceived standard of care [ 15 ]. Clinical ethics is also concerned with organizational ethics and networks and the implications of health care policy at the bedside. Although there are contrasting views about the presence of ethics consultants at the bedside, hospital ethics committees are now available in most hospitals in North America and Europe, providing services to patients, families, staff and the entire hospital organization. Do we need the services of hospital ethics committees or consultants in African hospitals or at the bedside? That may not be the point presently. However, clinical ethics is neither about committees and consultations, nor about technology and end-of-life issues alone. Common sense and intuition are insufficient to address all ethical issues that arise in patients' care. The well-intentioned clinical decisions and judgments of yesterday may turn out to be unsound in the searchlight of today's ethical scrutiny. Although core moral virtues have generally guided medical practice in Africa as elsewhere, there is the increasing need to apply both cognitive and behavioural ethical values to everyday decision making at the bedside by the physician as well as other health-care professionals [ 16 ]. Perhaps ethical concerns have unwittingly been unrecognized, downplayed or overlooked by health care professionals. The management of chronic diseases like HIV/AIDS and cancer, the incidences of which are on the increase, has attendant ethical implications about care, cost and consequences on patients' personality, values and families. Besides, Africa will someday cross the technological divide that will make resolution of ensuing ethical issues urgent, which health care providers will no longer be able to ignore. The societies are becoming more enlightened and it may be sooner than anticipated when physicians and other health care workers begin to grapple with some ethical challenges for which they are ill-prepared. It is not here suggested that next on the agenda of health care in Africa is to devote attention and resources to training bioethics consultants for the bedside. Most people in Africa still do not have access to qualified health personnel and reasonable health care. The point is that deliberate efforts should be made to train present and future health care providers to be aware of the core moral virtues required of them in their duties to patients; and be sensitive to the ethical values of their patients, their families and the society. Ethics education In the developed world education in ethics is no longer a "hidden curriculum" [ 17 ] that is passively passed to medical students during their training. It has become an "open" subject that is actively taught, not only in medical schools, but also in institutions that train other categories of health care workers. It has also become a required module in the training of resident doctors in most countries where bioethics is well grounded. Ethics education is aimed at teaching the cognitive and behavioural aspects of ethics for the purpose of improving the quality of care in terms of both the process and outcome of care. It enhances the student's ability to integrate the technical and moral components of the decision making process in clinical practice [ 16 ]. It also prepares the recipients to meet with ethical challenges of clinical practice and biomedical research. The pedagogic formats used include didactic teaching, clinical case studies, small-group discussion of ethical issues, and ethics rounds or grand rounds. A survey of medical graduates in the United States who had received ethics teaching while at medical school revealed that they were better suited to confront ethical issues in their practice and favoured continuation and expansion of ethics teaching in medical schools [ 18 ]. Other reports from both developed and developing countries that evaluated medical ethics programmes among medical students attest to the positive impact it has on their appreciation of ethical issues in clinical practice and the way they resolve them [ 19 - 22 ]. It is now time for Africa to join the rest of the world by introducing ethics education into the curricula of all medical schools where it is not presently taught. This is where the future of bioethics and health care delivery and research in Africa lies. Apart from some countries in the southern and eastern part of Africa and a handful of universities in other parts of Africa, there is no formal ethics education in most of Africa's medical schools. Ethics education to medical students is a necessary and required commitment to accomplishing an all-round training of the doctor whose decisions are both technical and moral. Much attention has wholly focused on the technical aspect of medical education, leaving the student to develop his or her moral attitudes passively through observation and intuition. Formal ethics teaching aims at equipping students with a common framework on which to reconcile patients' medical needs with their values, perceptions, situations and beliefs [ 16 ]; and may be a process towards achieving the hitherto elusive regulation of medical practice in most of these developing countries. Pertinent to any discussion about teaching bioethics in Africa is the issue of shortage of trained bioethicists to fill the vacancies that would be created in academic institutions in many African countries. Apart from South Africa and a few others, most countries in Africa lack the requisite bioethics manpower that would be needed in the medical schools. Even in institutions where bioethics is already part of the medical curriculum, it is unlikely that there are enough bioethics teachers. It is in this regard that the efforts of international agencies that fund training of developing world bioethicists are noteworthy. Those Africans who have undergone bioethics training in the developed world and have become pioneers in their institutions have an awesome responsibility of establishing credible training agenda for their countries. They are also well positioned to directly seek funding for such home-based programmes from international sponsors. At the beginning, such scholars may encounter some crisis of identity and acceptance within the established academic system. However, such difficulties would fizzle out as they persist in highlighting and proffering solutions to the myriad of contemporary ethical problems within the system and the society. The initial difficulty of publishing their works in established western bioethics literature can be overcome by patronizing local or regional journals that target the primary audience for which their work is meant and open access journals that reach far and wide. Moreover, most bioethics literature consists of commentaries, observations, personal opinions and philosophical reasonings. As African boethicists embark on qualitative research to highlight ethical issues in Africa and provide quantitative data to fill the gap and provide information which are frequently lacking in most western bioethics journals, access to western dominated journals would be enhanced. In an editorial published in a recent issue of Bioethics , Chadwick and Schuklenk question the altruism behind training developing world bioethicists in the west and warn against bioethics colonialism. They opine that graduates of such programmes are subjected to western ethical views and ideologies and that the developing world is not funded to develop bioethics capacity based on its own thinking [ 23 ]. While I agree with and advocate the principle that more funding should be channeled into establishing bioethics training programmes for Africa, in Africa and by Africans, as is being presently done in South Africa, I do not support the notion that those who have received bioethics training abroad are necessarily placed at the mercy of their trainers to the point of becoming their stooges and hangers-on. Though schooled in the western bioethics tradition I am of the opinion that such trainees have been given the necessary training to critically analyze ethical issues and formulate bioethical frameworks from an African perspective. Their immediate post-training thinking which appears to be shaped by western sentiments would become more and more Afro-centric as they begin to identify, appreciate and explore the hitherto unexplored and emerging ethical issues in their jurisdiction. Rather than retreiting and reinforcing western notions, there are enough ethical issues in the developing world to which such trainees could direct their searchlight and scholarship. Summary In the light of the foregoing, it is imperative that African bioethics must evolve which should take cognizance of its unique needs and circumstances and which, though amenable to improvement as a result of continuing interactions with other cultures and values, yet is not overshadowed by those influences. The need for the individual clinician/researcher to be committed to upholding high ethical standards and principles that respect the social, cultural, economic, educational and religious values of the people can not be over-emphasized. More efforts are required towards increasing continent-wide awareness about ethical issues in biomedical practice and research through ethics conferences, workshops, national bioethics conferences, the public media and Non-Governmental Organisations (NGOs). Countries where bioethics presence is fairly strong should assist neighboring countries to establish a presence, especially in organizing ethics review committees at research centres and institutions. Within countries, the possibility of joint or regional ethics review committees should be explored. Continuing and expanded support from the international bioethics community is required now more than before, to develop capacity for training of academic faculty, clinicians, researchers, government health ministry officials, NGOs, and the media in bioethics. The initiatives of the National Institute of Health of the United States to provide training grants for bioethics programmes within and outside Africa and the support of other institutions and bodies like the Wellcome Trust, African Malaria Network Trust (AMANET) and European Forum for Good Clinical Practice (EFGCP) among others, to the course of bioethics in Africa are noteworthy. Their support for bioethics capacity building programmes should not be limited to one or two sub-regions but to the whole continent. Further sponsorship should be provided for academic institutions within Africa to establish more short- and long-term training programmes at sub-regional levels. More importantly, these institutions should support the movement towards formal incorporation of bioethics into the curricula of medical schools and other health training institutions in Africa. The present and future needs for this in Africa are most apparent now. According to an African adage, the best time to plant a tree is twenty years ago, the next best time is now. Competing Interests The author was a Fogarty Fellow (2003/2004) at the Joint Centre for Bioethics, University of Toronto 88, College Street, Toronto, Ontario, Canada M5G 1L4. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC528730.xml |
548952 | Ancient DNA Comes of Age | Ancient DNA enables researchers to study the genetics of populations in the past; despite difficulties in its extraction, aDNA reveals that evolution is even more complex than we had imagined | The study of genetic material from ancient specimens was, in its early years, dominated by a race to sequence DNA from extinct species like the dodo and the woolly mammoth. Now that the supply of these crowd-pleasing curiosities has run dry, scientists are starting to ask new questions of ancient DNA (aDNA) that are revealing how the genetic make-up of prehistoric populations changed through time. These findings look set to trounce assumptions about how evolution really unfolded. However, there is still concern that many studies are not paying enough attention to the exacting protocols needed to overcome the technical challenges of the discipline and to defend it from the ridicule that has plagued it in the past. In 1994, while Jurassic Park was still taking in millions of dollars at the box office, scientists claimed to have extracted and sequenced DNA from an 80-million-year-old dinosaur [ 1 ]. When sceptical researchers took a look at the sequence, it turned out to be of human rather than dinosaur origin. “To make that mistake, you'd have to try really, really hard,” says Alan Cooper, head of the Henry Wellcome Ancient Biomolecules Centre at Oxford University in the United Kingdom. If you think you've sequenced some dinosaur DNA, the first thing you'd do is run a phylogenetic analysis on it, he says. “Had they done that properly, with any mammal at all involved in the tree,…they would have found that their sequence was grouping with the mammals and not with the reptiles or the birds,” says Cooper. Perhaps they'd watched Michael Crichton's inventive fiction one too many times, he suggests. Setting the Standards It was this kind of bungling study that highlighted the need for an exacting protocol that would steer researchers around the significant pitfalls posed by DNA decay and contamination. A list of “authenticity criteria” emerged during the 1990s, aimed at preventing similarly bogus claims from entering the literature [ 2 ]. This list includes stringent laboratory controls; cloning of products amplified by polymerase chain reaction (PCR); replication of results from a second, independent extract; and, for really new or unexpected results, replication of results by an independent research group. Such requirements have allowed work on aDNA to move on and mature. Now, it's possible to focus on the really interesting questions that aDNA can answer. “What we're able to do with ancient DNA is really look at evolution,” says Cooper. The fossil record can only hint at how evolution unfolded. “It just shows you there's a bear and then there's not a bear,” he says. “It doesn't show you where it came from or what the relationship between the groups is.” By contrast, aDNA can do just that, giving researchers a window onto the population genetics of the past and revealing how evolution really played out. And the signs are that descriptions of the evolutionary process based on the fossil record and modernday gene pools are far too simple. “The modern data is clearly misleading us,” says Cooper. “Evolution is much, much more complex and dynamic than we would hope.” Thinking Big Because of the decay that occurs with time, there is a limit to how far back aDNA can gaze (Box 1) . “Your ideal preservation conditions are something that falls under ice, freezes instantly, and stays frozen until you get it,” says Cooper. “As soon as we get up to 2 million [years ago] we can't get anything to work, and that's even under deep-frozen conditions.” But within the past 60,000 years, there are several major evolutionary events that are worth studying—including a glacial maximum around 18,000 years ago, the invasion of the New World by humans about 12,000 years ago, and a global mass extinction about 11,000 years ago. These relatively recent events should be a good model for working out how similar events affected genetic diversity throughout evolutionary history. Box 1. Decay As soon as an organism dies, nucleases get the better of repair enzymes and rapidly digest strands of DNA. Under certain conditions, such as rapid desiccation, freezing, or high salt concentrations, the nucleases are inactivated before the damage is done. Even if some DNA is left intact, however, radiation, oxidation, and hydrolysis can still cause damage. These processes mean that ancient DNA specimens are like a four-letter alphabet soup, says Cooper. Very little of the original DNA remains, which is why most aDNA studies focus on mitochondrial rather than nuclear DNA: there are simply more copies of mitochondria, so the chances of getting an aDNA sequence are that much higher. Furthermore, chemical changes to the DNA fragments that remain cause additional problems: the PCR is often fooled into inserting inappropriate bases when it is copying an ancient template strand. “Amplification of DNA molecules older than one million years of age is overly optimistic,” note Pääbo and his colleagues [ 11 ]. In spite of these difficulties, several groups are hoping to work out ways to spot aDNA damage and set about repairing it. Since the 1980s, Svante Pääbo and Tomas Lindahl have made several stabs at removing glitches in aDNA using purified repair enzymes, filling in the gaps between sequences and then joining them together to resurrect something like an original sequence. “Sometimes it has seemed to help, but nothing really reproducible has come out of it,” admits Pääbo. One approach has, however, been successful at repairing DNA damage that occurs with time. Cross-links can form between reducing sugars and amino groups, he says ( Figure 4 ). Such cross-links can sometimes be broken using the chemical N-phenacylthiazolium bromide, releasing PCR fragments that would otherwise be tied up. The amount of repair that's possible will never be able to restore the DNA sequence of an extinct species Jurassic Park –style, but it should allow researchers to ask even more profound questions of aDNA. “In five years, I think we'll see some repair methods really get going,” says Cooper. Cooper's latest work has analysed DNA from over 400 bison fossils from Beringia—the frozen wastes between eastern Siberia and the Canadian Northwest Territories [ 3 ]. “What we've done is carbon-date a shitload of bison and get DNA out of them.” It's the largest aDNA study to date, he says ( Figure 1 ). The icy conditions mean that good quality mitochondrial DNA could be extracted from most of the specimens. The bison could also be dated accurately. This allowed Cooper and his colleagues to trace the changes in the bison genetic diversity from 150,000 years ago to the present. It was even possible to predict the effective population size throughout this period of bison evolution. “Our analyses depict a large diverse population living throughout Beringia until around 37,000 years before the present, when the population's genetic diversity began to decline dramatically,” they note. Figure 1 How Did Bison Really Evolve? (A) A modern bison ( Bison bison ), (B) the skull of an extinct bison ancestor, and (C) extraction of aDNA from a bison bone. (Images: [A] Steve Malowski, United States Fish and Wildlife Service, [B and C] Henry Wellcome Ancient Biomolecules Centre, Oxford University) This finding challenges some common assumptions. It has been argued that modern bison are descended from Beringian bison, but Cooper's data suggest otherwise. “All modern bison belong to a clade distinct from Beringian bison,” he and his colleagues report. Furthermore, the dramatic decline in the numbers of bison occurs long before humans arrive on the scene, scuppering the idea that hunting pressure was primarily responsible for the demise of the bison. As the glacial maximum approached 18,000 years ago, the cooler, dryer conditions were probably responsible for the downturn in the bison population, argues Cooper. “Climate change is giving the animals an absolute whacking,” he concludes. A similar analysis of brown bear DNA excavated from permafrost and cave deposits in the Arctic is also challenging conventional evolutionary wisdom [ 4 ]. Being able to get both a radiocarbon date and some DNA from a specimen pins a particular genetic sequence to a particular moment in time. These data suggest that genetically and geographically distinct groups of bear have replaced each other relatively often during the last 60,000 years. Regional extinctions and replacements seem to be tied to climate change and competition with the much larger short-faced bears, the authors argue ( Figure 2 ). Figure 2 What Are the Real Evolutionary Origins of the Brown Bear ( Ursus arctos )? (Image: John Nickles, United States Fish and Wildlife Service) Recent analysis of aDNA from Haast's eagle has also thrown up a surprising result. This New Zealand giant had a wingspan of up to three metres and a weight of around 14 kilograms, says Michael Bunce, an anthropologist at MacMaster University in Ontario, Canada. Analysis of aDNA from 2,000-year-old specimens indicates that this extinct creature is closely related to the little eagle from Australia and New Guinea, which typically weighs less than one kilogram. The common ancestor of these two eagles lived as recently as 1 million years ago, he and his colleagues estimate [ 5 ]. “It means an eagle arrived in New Zealand and increased in weight by 10–15 times over this period,” says Bunce. “Such rapid size change is unprecedented in terrestrial vertebrates.” In addition to illuminating these natural events, the study of aDNA can also show changes in the frequency of key genes that occurred during the domestication of crops and animals. For example, aDNA from samples of early maize reveals when certain desirable traits appeared [ 6 ]. “It's the first study of ancient DNA that looks at phenotype,” says Svante Pääbo, an evolutionary anthropologist at the Max Planck Institute in Leipzig, Germany. “One can actually look at specific genes that early humans selected during domestication of an important crop.” Pääbo's analysis suggests that the alleles typical of contemporary maize were already present in Mexican maize 4,400 years ago, so just a couple of thousand years after its initial domestication from the wild grass teosinte ( Figure 3 ). “Quite early on, properties were selected that were not only the structure of the plant but also the biochemistry,” he says. Figure 3 Domesticating Maize (A) Maize cob from the Ocampo Caves in Mexico dated to 3,890 years before the present. aDNA can reveal the selection of traits during early maize domestication that cannot be observed in the fossil record. (B) Examples of modern maize. (Images: [A] Svante Pääbo, Max Planck Institute, [B] Keith Weller, USDA Agriculture Research Service) aDNA is also being used to decipher human origins. Mitochondrial DNA from Neanderthals looks quite different from the mitochondrial DNA of early modern humans [ 7 ]. This lends support to the hypothesis that modern humans have a “single African origin” rather than the alternative hypothesis of “multiregional evolution”, where the ancestors of modern humans bred with Neanderthals. aDNA could also, in principle, be used to shed light on the evolutionary position of the 18,000-year-old “hobbit” recently unearthed on the Indonesian island of Flores [ 8 ]. Both Cooper and Pääbo have offered to have a go at isolating DNA from the “hominid” skeleton, but the early signs are that DNA has not survived. “The somewhat moist and tropical preservation conditions make the recovery of DNA improbable,” says Peter Brown, the paleoanthropologist at the University of New England in Armidale, Australia, who led the hobbit study. Efforts to extract DNA from other bones collected at the same site as this tiny hominid have not produced results. “We have made attempts with Stegodon molars,” he says, “but so far without success.” Ongoing Controversy However, in spite of the authenticity criteria and this transition towards testing the big questions in evolutionary biology, aDNA research continues to invite controversy. In 2000, a team of United States researchers claimed to have cultured a bacterium sealed inside a 250-million-year-old salt crystal [ 9 ]. For Cooper, this is the sort of study that should require replication by an independent laboratory before publication. “When we repeated that work with the same primers, we were pulling up halobacteria from everywhere,” he says. “We took some dust from the top of the natural history museum in Oxford, extracted [DNA], used their supposedly halospecific primers and extracted a whole bunch of sequences, including some that fell within their diversity.” This strongly suggests, says Cooper, that the bacterium that was cultured was a modern bacterium, rather than an ancient specimen. “I can't see any logic for having 250 million years without any evolution.” But Russell Vreeland, a microbiologist at West Chester University in Pennsylvania and first author of the salt-crystal study, is adamant that his methods were exacting. “The probability of having a contaminant in our sample was one chance in a billion,” he calculates. “If you use a Band-Aid today on your skin or your children, you are 1,000 times more likely to have an infection from that Band-Aid than I am to have a contaminant.” It's completely unscientific to argue that the cultured bacterium was a result of contamination simply because it resembles modern bacteria, says Vreeland. “That's throwing out the baby with the bathwater. If you can show that nothing has penetrated your sample and the DNA is inside, then the age of the DNA has to be equal to the age of that rock,” he says. “I think you can make your criteria so stringent that you miss reality.” Others are alert to this danger. Sticking rigidly to the authenticity criteria can be a problem, argues Tom Gilbert of the Department of Ecology and Evolutionary Biology at the University of Arizona. “[The criteria] can both hinder the publication of good studies that do not adhere to all the criteria, and also enable the publication of erroneous results that adhere strictly to them,” he says. Part of the problem is that many referees of aDNA papers do not have a background working with aDNA, so are inclined to use the authenticity criteria as a checklist rather than critically evaluating each bit of research on a case-by-case basis. For example, he says, a recent high-profile study that followed all the criteria found that aDNA from two Cro-Magnon-type humans was very similar to DNA from modern humans [ 10 ]. But this could just mean that the specimens were contaminated by modern humans. “As no information was provided on the sample's handling history,” says Gilbert, “it becomes impossible for a reader to decide whether the sequences are authentic or contaminant” (Box 2) . Such papers will continue to appear as long as the authenticity criteria are used by authors and referees as a checklist, he says. This does not mean the criteria should be relaxed, he adds, but they should be used in a more intelligent way. Box 2. Contamination Most tissues under the scrutiny of the aDNA researcher will contain not only DNA from the organism of interest, but also DNA from bacteria, fungi, and all sorts of other organisms. Of course, most of this confusion can be cleared up using a speciesspecific primer in the PCR to amplify DNA from just one genome. “You're after a needle in a haystack,” says Alan Cooper, “but fortunately that's what the PCR technique is so good at doing— sorting through that haystack for you.” A lot of focus has been placed on contamination in the laboratory. This “external contamination” is a particular problem because low levels of aDNA can easily be outnumbered by just a tiny amount of high-quality modern DNA floating around the lab. One of the criteria of authenticity—separating the site of DNA extraction from the site of PCR amplification—is designed to minimise this. In addition, there is “innate contamination” that has occurred to the sample before it even reaches the laboratory. This is much harder to control and is a real problem for those working on human origins because it's difficult to tell what is ancient human DNA and what is a modern contaminant. Bone is like sponge. “In life, bone is about 8% air. In death,…40% or 50% of it is air,” says Gilbert. So if an archaeologist digs up and washes a bone from some human ancestor, it's almost certain that modern DNA will find its way into the centre of the bone [ 12 ]. Some archaeologists have even been known to lick bones to determine their porosity, he says. “If they're licking bones, God knows what else they're doing to things.” This variable and unrecorded handling history of many museum specimens, means that contamination is difficult to rule out. This explains why many aDNA researchers focus on unusual species like the bison or the cave bear: these animals are extinct, so the chances of contamination are nil. It's easier to come up with real results that the scientific community will accept, says Gilbert. There will always be a temptation to work on humans, however, because it's these studies that grab the headlines, he says. But allowing authors the freedom to use the criteria as they see fit could come at a cost, says Cooper. “The trouble with a case-by-case basis is that it basically equates to no standards, because then people will do what they feel like doing and we're back to the 1990s again,” he says. Agreement This ongoing disagreement over how aDNA studies should be judged does, however, stem from a common concern. As more and more biologists come to appreciate the unique ability of aDNA to probe the evolutionary process, it is more important than ever to stress the immense challenges of working with just a few fragments of degraded DNA that might have come from several different sources. It is obvious why an archaeology lab might want to set up its own aDNA facility. But this is like creating molecular biologists without a license, says Pääbo. “You wouldn't buy an accelerator and say 'I will now start doing my own carbon dating,'” he says. “You have to really have experience working with low copy number.” However, in spite of the continual problem of eager but inexperienced biologists trying to extract DNA from specimens in the university museum, there is a sense that aDNA is starting to fill in the gaps in our understanding of key moments in evolutionary history. So at the start of 2005, as aDNA research enters its 21st year, the discipline is, perhaps, coming of age. Figure 4 Cross-Linked DNA Extracted from 4,000-Year-Old Liver of an Ancient Egyptian Priest Called Nekht-Ankh (Image: Svante Pääbo, Max Planck Institute) | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC548952.xml |
368167 | NCEAS: Promoting Creative Collaborations | NCEAS -- an ecological synthesis center -- is changing the way ecological research is conducted by fostering new forms of collaboration and interdisciplinary research | A substantial portion of research occurs in places where scholars congregate—in campus laboratories, in libraries, or in large specialized facilities, such as oceanographic ships, astronomical observatories, or accelerators. Under any of these circumstances, researchers can interact easily, exchanging ideas and information. Ecological research, especially the large component occurring in the field, takes place in disparate locations all over the world—in the air, on the surface, and below the oceans, lakes, and crust of the planet. Although there are many biological field stations where scientists and students gather, much of the research in ecology takes place in isolation. In addition to being highly dispersed geographically, ecology encompasses a disparate range of disciplines at scales from molecules to the globe, making the exchange of ideas and information even more difficult. Recognizing the benefits of interaction and collaboration, the ecological community began considering a synthesis center where researchers from many fields could meet to address important ecological questions. Several organizations held discussions about the nature of such a center, which culminated in two workshops hosted by the National Science Foundation (NSF) in the early 1990s, to set the scope. In 1994, NSF conducted an open competition for a synthesis center, eventually granting the University of California, Santa Barbara, the award for the National Center for Ecological Analysis and Synthesis (NCEAS). In addition to funding from NSF, the center is supported by the University of California system and its Santa Barbara campus and by several foundations. The center employs various types of research approaches. A primary approach is through Working Groups ( Figure 1 ) where scientists come to NCEAS to concentrate on specific issues requiring synthesis of ideas, in-depth analysis of data, development of models, and preparation of results. The groups generally visit NCEAS two to four times over two years and stay for three to ten days at a time. Working Group topics range from microbial diversity to global change and have included projects in sociology, economics, and computer science. The Center hosts about 100 meetings a year, involving hundreds of participants. Figure 1 A Working Group at NCEAS on Diseases in Natural Populations (Photo used by permission from NCEAS.) NCEAS also supports up to six visiting Center Fellows (sabbatical visitors) each year. These scientists often integrate their own research into a broader context or synthesize what is known about certain areas in ecology. Concurrently, the Center houses 15–18 Postdoctoral Associates for one to three years each. These postdoctoral positions are distinctive in that there are no permanent mentors for the larval scientists—rather, they interact with the other Associates, the resident Fellows, and the hundreds of individuals who annually visit the Center as part of Working Groups. The Center also conducts training activities, including a distributed graduate seminar program. In this approach, graduate students around the world become involved in seminars on specific topics using data from their region (e.g., the relationship between productivity and diversity) and then representatives from each of the seminars are brought to NCEAS for a grand synthesis. As would be expected for a discipline as broad as ecology, the participants at NCEAS are extremely diverse. Over 3,000 individuals have visited NCEAS in just over eight years, representing 43 countries and 49 states in the United States. They come from over 800 institutions, many non-biology departments, and 397 non-academic organizations (e.g., agencies and companies). An interesting measure of their breadth is that participants belong to more than 180 professional societies. Proposals are solicited twice a year and reviewed by a Science Advisory Board. The Board looks for topics that would benefit from synthesis and analysis and that would make significant contributions to our understanding of ecological relationships. While many proposals pertain to core ecological questions, others deal with economics or sociology (e.g., how metaphors affect the way we conduct research). Approximately 40% of the projects have some applied component, many influencing resource management practices and conservation policies. Because the Center is based on the use of existing data, access to highly dispersed and profoundly heterogeneous ecological information is essential, but also very difficult. Recognizing the need for open access to a wide variety of data—versus project-specific data solutions—NCEAS and several collaborators (see http://www.ecoinformatics.org ) have embarked on a major research program in developing tools to characterize data and make them available in standardized formats. The initial research effort, called the Knowledge Network for BioComplexity (KNB) is yielding tools to generate metadata (precise information about the data) and to make all the data available. The current research thrust, called Science Environment for Ecological Knowledge, will expand the capabilities of KNB by employing grid technology (in particular, EcoGrid, a network of networks), semantic mediation, knowledge representation, and workflow models for analysis and synthesis. The Center has supported almost 200 projects, the results of which are published in top scientific journals (see project results at http://www.nceas.ucsb.edu ). Furthermore, some of the projects have had direct influence on conservation and resource management. For example, scientists at NCEAS developed theories for the design of marine reserves that were soon thereafter applied to the placement of reserves directly off the coast of Santa Barbara. In addition to scientific results, NCEAS is changing the way we conduct ecological research through novel means of encouraging productive collaborations. Sociologists studying the NCEAS model of collaboration have identified several important factors in its success. These include a distant, neutral location facilitating periodic, highly focused opportunities to concentrate on the issues under consideration; logistic support that lowers the activation energy required to develop collaborations; and the proximity of scientists from many disciplines having the opportunity to interact in ways otherwise not possible. Many significant contributions to our understanding of the patterns and processes of the natural world have emerged from NCEAS research activities. In addition, the Center is fostering new forms of collaboration and interdisciplinary research by providing a place where scientists from many disciplines can productively interact and by working to make eclectic ecological data available to many users. This is an extremely simple model for the scientific enterprise—but one not captured in most existing institutional and organizational structures. As recognition of the success of NCEAS spreads, other institutions are attempting to incorporate some of the traits of the Center into their operations, and new centers are being proposed. For example, the NSF is in the midst of a review of proposals for an evolution synthesis center. It is clear that the complexity of ecological systems, as well as the importance of understanding and maintaining them, requires information and knowledge from many disciplines. This is true even at a time when disciplines are becoming more specialized and scientists have less time to concentrate on broader issues. By facilitating interactions among many scholars and practitioners, NCEAS provides both time when and a place where far-reaching topics can be addressed. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368167.xml |
546214 | In vitro digestion and lactase treatment influence uptake of quercetin and quercetin glucoside by the Caco-2 cell monolayer | Background Quercetin and quercetin glycosides are widely consumed flavonoids found in many fruits and vegetables. These compounds have a wide range of potential health benefits, and understanding the bioavailability of flavonoids from foods is becoming increasingly important. Methods This study combined an in vitro digestion, a lactase treatment and the Caco-2 cell model to examine quercetin and quercetin glucoside uptake from shallot and apple homogenates. Results The in vitro digestion alone significantly decreased quercetin aglycone recovery from the shallot digestate ( p < 0.05), but had no significant effect on quercetin-3-glucoside recovery ( p > 0.05). Digestion increased the Caco-2 cell uptake of shallot quercetin-4'-glucoside by 2-fold when compared to the non-digested shallot. Despite the loss of quercetin from the digested shallot, the bioavailability of quercetin aglycone to the Caco-2 cells was the same in both the digested and non-digested shallot. Treatment with lactase increased quercetin recovery from the shallot digestate nearly 10-fold and decreased quercetin-4'-glucoside recovery by more than 100-fold ( p < 0.05), but had no effect on quercetin recovery from apple digestates. Lactase treatment also increased shallot quercetin bioavailability to the Caco-2 cells approximately 14-fold, and decreased shallot quercetin-4'-glucoside bioavailability 23-fold ( p < 0.05). These Caco-2 cells had lactase activity similar to that expressed by a lactose intolerant human. Conclusions The increase in quercetin uptake following treatment with lactase suggests that dietary supplementation with lactase may increase quercetin bioavailability in lactose intolerant humans. Combining the digestion, the lactase treatment and the Caco-2 cell culture model may provide a reliable in vitro model for examining flavonoid glucoside bioavailability from foods. | Background Cardiovascular disease and cancer are the two most common causes of death in the United States and most industrialized nations. A diet high in fruits and vegetables has been correlated with a reduced risk for both cancer and heart disease [ 1 , 2 ]. It is thought that the phytochemicals found in fruits and vegetables may be responsible in part for these health benefits [ 3 ]. Phytochemicals from fruits and vegetables may inhibit cell proliferation, protect against oxidative stress, influence cell-signaling pathways, and reduce inflammation. Because these compounds appear to have such beneficial effects, interest has been raised in examining the bioavailability of these compounds. A phytochemical of particular interest is quercetin, a strong antioxidant that is widely consumed in many fruits and vegetables. Quercetin has potential protective effects against both cancer and heart disease. Briefly, quercetin has been found to down regulate expression of mutant p53 in breast cancer cells, arrest human leukemic T-cells in G1, inhibit tyrosine kinase, and inhibit heat shock proteins [ 4 ]. Quercetin has been shown to decrease lipid peroxidation, inhibit cell proliferation, induce apoptosis, and inhibit platelet aggregation [ 5 - 8 ]. Because quercetin exhibits such a wide array of positive health effects, it is especially important to understand quercetin bioavailability from whole foods. Two widely consumed, good food sources of quercetin are apples and onions [ 9 - 13 ]. In most foods, quercetin does not exist in the aglycone form, but is, instead, conjugated. The type of sugar moiety to which quercetin is bound affects quercetin bioavailability. For example, quercetin in the apple is bound mainly to galactosides, rhamnosides, and arabinosides, and these quercetin conjugates are not well absorbed by the small intestine. The onion contains mainly quercetin glucosides, which are well absorbed by the small intestine [ 14 ]. More work is needed to understand the bioavailability of quercetin and other flavonoids from foods. The Caco-2 cell culture model is a well-established in vitro technique, extensively used to study intestinal cell absorption of compounds such as pharmaceuticals and nutrients; it is an excellent in vitro tool to study bioavailability of specific compounds. We have previously used the Caco-2 cell culture model to examine the uptake of quercetin from apple and onion extracts [ 15 ]. Using this model, we found that absorbed quercetin from onion extracts was significantly greater than from apple extracts, as expected [ 15 ]. Others have used the Caco-2 cell culture model to evaluate cell transport and/or accumulation of pure phytochemicals such as quercetin, quercetin glucosides, chrysin, flavone, epicatechin, proanthocyanidin, and carotenoids [ 16 - 23 ]. To further understand quercetin bioavailability, it is important to examine the effects of digestion on foods prior to intestinal uptake. An in vitro digestion has been paired successfully with the Caco-2 cell culture model to study iron and carotenoid bioavailability [ 23 , 24 ]. Use of the in vitro digestion with the Caco-2 cell culture model could be quite useful in more specifically analyzing quercetin bioavailability from foods. At this time there is little information available describing the effects of digestion on flavonoids from foods. Vallejo et al. [ 25 ] found that over 80% of total flavonoids were lost during an in vitro digestion of broccoli. In a study of ileostomy patients, Walle et al. estimated that the intestine might absorb 65–81% of major forms of dietary flavonoids after enzymatic hydrolysis [ 26 ]. A good in vitro model would aid in evaluating bioavailability of phytochemicals from foods by offering a simple method to screen for factors that may affect intestinal absorption of quercetin and quercetin glucosides, such as the food matrix, food processing, digestion, and interactions with other foods. Human and animal models can be expensive and time consuming, while a cell culture model allows for rapid, inexpensive screenings. The Caco-2 model has the potential to be a good model to measure quercetin absorption, however there are some drawbacks. Caco-2 cells have been shown to express significantly less lactase phlorizin hydrolase (LPH) than the average human small intestine [ 27 ]. Since this enzyme is most likely responsible for the first step in the metabolism of quercetin glucosides [ 28 ], this deficiency would clearly limit the ability of the Caco-2 cells to metabolize and absorb quercetin from quercetin glucosides. Caco-2 cells used in our lab have expressed greater LPH activity (3 mU/mg protein) than other Caco-2 cells (0.3 mU/mg protein) [ 15 ], resulting in lactase activity similar to that expressed by enterocytes from a lactose intolerant human (2–10 mU/mg protein)[ 27 ]. The compound forskolin induced lactase phlorizin hydrolase activity four-fold in Caco-2 cells [ 29 ]. In weanling rats, lactose consumption increased lactase activity in the jejunum by three-fold [ 30 ]. Thus, we hypothesized that treating Caco-2 cells with either forskolin or lactase may raise lactase expression to rates comparable to humans, making the Caco-2 cell model a more valid model for screening quercetin glucoside bioavailability from food. If lactase activity cannot be induced in Caco-2 cells, treating food samples with lactase following the digestion procedure and prior to cell bioavailability assays may give more comparable results to humans. The objectives of this study were (1) to develop an optimized in vitro digestion method for examining quercetin and quercetin glucoside recovery from digestates using onions and apples; (2) to examine the effect of lactase on shallot digestates; and (3) to examine Caco-2 cellular uptake of quercetin and quercetin glucosides from digested and lactase treated shallot. Methods Chemicals and materials Shallots and onions (Northern Yellow) were obtained from a local grocery store. Apples (Red Delicious and Cortland varieties) were obtained from the Cornell Orchards (Cornell University, Ithaca, NY). Porcine pepsin, bile extract, pancreatin, lactase (beta-galactosidase, from Kluyveromyces lactis , activity of 3000 units/mL), quercetin, and quercetin-4'-glucoside were purchased from Sigma Chemical Company (St. Louis, MO). Quercetin-3-glucoside was purchased from Indofine Chemical Company, Inc (Hillsborough, NJ). Caco-2 cells were obtained from the American Type Culture Collection (Rockville, MD) and were cultured in Dulbecco's Modified Eagle Medium (DMEM; Gibco Life Technologies, Grand Island, NY) supplemented with 5% fetal bovine serum (Gibco Life Technologies, NY), 10 mM HEPES, 50 units/mL penicillin, 50 μg/mL streptomycin, and 100 μg/mL gentamicin, and were maintained at 37°C in 5% CO 2 . In vitro digestion Two hundred grams of each food sample were chopped, blended for 5 min with 200 mL saline (140 mM NaCl, 5 mM KCl) using a Waring blender, and then homogenized using a Virtis 45 homogenizer. The total homogenates were aliquotted in 15 mL centrifuge tubes and stored at -20°C until use. For the digestion treatment, 2 g aliquots of the food sample were placed in a centrifuge tube with an equal amount of saline. The pH was decreased to 2.0 by drop-wise addition of 1M HCl, and porcine pepsin was added to a final concentration of 1.3 mg/mL. The digestate was incubated in a shaking water bath at 37°C for 30 minutes. The pH of the digestate was then increased to 5.8 with the drop-wise addition of 1M NaHCO 3 . Porcine bile extract and pancreatin were added to a final concentration of 1.1 and 0.175 mg/mL, respectively. The pH was increased to 6.5 by drop-wise addition of 1M NaHCO 3 , and the samples were incubated for 1 hour in a water bath at 37°C. Following digestion the pH was decreased to 2 by addition of HCl and the digestates were stored at -80°C for further analysis. To examine and optimize the effects of digestion time and pH on the recovery of compounds from the digestate, the above parameters were varied. To examine the effects of pepsin digestion time, the pepsin digestates were incubated for 0, 30, 60 or 90 minutes and then incubated with the intestinal digestion enzymes for 60 minutes. To examine the effects of intestinal digestion, the samples were incubated with pepsin for 30 minutes, then incubated with pancreatin and bile for 0, 30, 60, or 90 minutes. The effects of 100 μM ascorbic acid and a nitrogen environment on quercetin and quercetin glucoside recovery from onion and apple digestates were examined. Following homogenization and prior to digestion, the food samples were mixed 1:1 with saline containing 200 μM ascorbic acid, leaving a final sample concentration of 100 μM ascorbic acid. During the digestion procedure described above, the samples were flushed constantly with nitrogen. The effect of pH of either 6.5 or 7.0 during intestinal digestion on quercetin and quercetin-3-glucoside recovery was compared. The effect of the storage pH was examined by comparing digested samples having either a final pH of 2.0 or 6.5. The effect of storage pH on 20 μM pure quercetin and 20 μM quercetin-3-glucoside was examined by comparing recoveries from samples stored at pH = 2.0, 3.5, 5.0 or 7.0. All samples were stored overnight at -80°C. Prior to HPLC analysis samples were thawed and extracted 4 times with acidified ethyl acetate (pH 2.0), evaporated to dryness and reconstituted in 2 mL acidified methanol (pH 2.0). Lactase digestion Doses of lactase (0.5 units to 3000 units per gram sample) were applied to 1 gram shallot extract and incubated for 15 minutes at 37°C. The final pH was brought to 2.0 and the samples were stored at -80°C. The time kinetics were examined by incubating 1 gram shallot extract with 100 units of lactase for 0, 15, 30, 60, 90, 120, 240, and 720 minutes. The effect of both lactase and digestion were examined by digesting the samples with pepsin and pancreatin as described above, then incubating the samples with 100 units of lactase for 30 minutes at 37°C. Samples were stored overnight at -80°C. Prior to HPLC analysis, all digestate samples were thawed and extracted 4 times with acidified ethyl acetate (pH 2.0), evaporated to dryness and reconstituted in 2 mL methanol. Uptake of quercetin-4'-glucoside and quercetin from shallot digestates by Caco-2 cells Caco-2 cells were seeded at a density of 5 × 10 5 cells per well in a collagen coated 6-well, flat bottom plate and incubated at 37°C in a 5% CO 2 environment. Caco-2 cells were used between passages #10–25, and the cells reached confluence approximately 5 days post seeding. Culture media was changed three times a week. On day 14 post seeding, the DMEM was removed and the cells were rinsed three times with phosphate buffered saline (PBS). Shallot homogenates were digested as previously described and were placed directly on the 14 day old Caco-2 cells, or the samples were diluted 1:2 or 1:4 in HBSS (Hank's Balanced Salt Solution). Cells were also incubated with non-digested shallot homogenates for comparison. For each treatment, two wells of cells were used for each sample, and each treatment was repeated in triplicate. To examine the effect of lactase on quercetin uptake from shallots, shallots were digested then incubated with lactase (50, 100, 300, and 1000 units/g shallot) for 20 minutes at 37°C. The digested shallot homogenates and the digested plus lactase treated shallot homogenates were diluted 1:2 in HBSS and placed on the cells. In all experiments, Caco-2 cells were incubated with treatment for 30 minutes at 37°C in 5% CO 2 . The shallot treatment and HBSS was removed and the cells were rinsed three times with 20% methanol in PBS. Cells were scraped in acidified methanol (pH = 2.0) and the wells were rinsed three times with methanol. The scraped cells were sonicated for 15 minutes, centrifuged at 1600 g for 5 minutes, and the methanol supernatant was collected. The cells were rinsed three more times with methanol, the supernatants were collected and the methanol extracts were evaporated to dryness under nitrogen and reconstituted in 400 μl acidified methanol for HPLC analysis. Induction of lactase activity in Caco-2 cells Caco-2 cells were seeded at a density of 5 × 10 5 cells per well in a 6-well flat bottom plate. The cells were cultured in DMEM spiked with different doses of either lactose (10, 50, 100, 500, and 1000 μM), or forskolin (1, 10, 50, 100, and 200 μM). Media was changed every two days, and cells were harvested and lactase activity was measured at 14 days post-seeding. Lactase activity of Caco-2 cells was measured using a method adapted from Dahlqvist [ 31 ]. Cells were trypsinized, collected, centrifuged and resuspended in homogenization buffer (50 mM sodium phosphate; 1 mM EDTA; 10 mM dithiothreitol; protease inhibitor cocktail, Sigma Chemical Co., St. Louis, MO). Cells were homogenized 5 times for 30 seconds with 1 minute of cooling between bursts using a benchtop homogenizer. Homogenates were treated with 56 mM lactose and incubated at 37°C for 60 minutes. Glucose oxidase, peroxidase, and o-dianisidine were applied to the cell homogenates and the final colored products were measured at 420 nm using a spectrophotometer [ 31 ]. The results were compared to a glucose standard curve to determine the amount of glucose released by lactase in the Caco-2 cell monolayer. Protein was determined from crude cell homogenates colorimetrically using the Lowry method with comparisons to a bovine serum albumin standard curve. Results are expressed as milliunits/mg of protein, and one unit is defined as the lactase activity that hydrolyzes 1 μmole of lactose per minute at 37°C. HPLC analysis Quercetin and quercetin-3-glucoside content of untreated homogenates, digestates, and Caco-2 cell extracts were determined using an RP-HPLC procedure with a Supelcosil LC-18-DB column (150 mm × 4.6 mm, and 3 μm pore size). Waters 515 HPLC pumps (Waters Corp., Milford, MA) and a Waters 2487 dual wavelength absorbance detector (Waters Corp., Milford, MA) set at 370 nm were used for all HPLC analysis. Quercetin, quercetin-3-glucoside, and quercetin-4'-glucoside were used as standards. For the analysis of quercetin, quercetin-3-glucoside, and quercetin-4'-glucoside in the apple peel extracts, shallot extracts, and digestate extracts, the solvent system used was (A) acidified water (pH 2.0; triflouroacetic acid) and (B) acetonitrile. The gradient method was the following: 0.0 min, flow rate = 1.4, (A) 90% and (B) 10%; 53 min, flow rate = 1.5, (A) 80% and (B) 20%; 58 min, flow rate = 1.7, (A) 65% and (B) 35%; 64 min, flow rate = 1.4, (A) 90% and (B) 10%. Twenty μL injections were made for each sample. Quercetin, quercetin-3-glucoside, and quercetin-4'-glucoside concentrations in the apple peel extracts, shallot extracts, and in the digestates were extrapolated from the pure quercetin and quercetin-3-glucoside standard curves. Statistical analysis All data were reported as means ± SD for three replicates of each treatment. An analysis of variance (ANOVA) was used to compare results between treatment groups, and pairwise multiple comparisons were performed using Fisher's LSD with an individual error rate of 0.05. The statistical analysis was completed using Minitab Release 12 software (State College, PA). Results In vitro gastrointestinal digestion The total pepsin digestion time and pancreatin/bile digestion time had little to no effect on recovery of both quercetin and quercetin-3-glucoside from apple and onion homogenates when treated for up to 60 minutes (data not shown). After 90 minutes of pepsin digestion and 90 minutes of pancreatic digestion, quercetin and quercetin 3-glucoside in both the apple and the onion decreased slightly. Based on these results we chose to use a 30-minute pepsin digestion and a 60-minute pancreatin/bile digestion. In past studies, quercetin from onion and quercetin from quercetin-4-glucoside supplements reached the plasma in less than an hour following consumption by human volunteers [ 32 ]. Therefore, long in vitro digestion times were not necessary to mimic human digestion of quercetin compounds from apples and onions. The presence of ascorbic acid and nitrogen had no effect on quercetin or quercetin-3-glucoside recoveries from the digestates (data not shown). Quercetin and quercetin-3-glucoside recoveries from digested samples treated with ascorbic acid, nitrogen or both ascorbic acid and nitrogen were not different from the recoveries from the untreated digested samples. The factor that had the greatest effect on recovery was pH (Figure 1A ). Quercetin is less stable at higher pH, therefore the effect of pH during intestinal digestion was examined. Recoveries of quercetin and quercetin-3-glucoside after intestinal digestion at pH 7.0, when compared to pH 6.5, were not significantly different ( p > 0.05). However, following overnight storage at -80°C, the samples stored at pH 2.0 had significantly greater quercetin and quercetin-3-glucoside recoveries than samples stored at pH 6.5 and 7.0 ( p < 0.05). Pure quercetin and quercetin-3-glucoside were also more stable at lower storage pH following digestion (Figure 1B ). At pH 2.0, the recoveries for pure quercetin and quercetin-3-glucoside were 74.8% and 86.2% when compared to the control. At the highest pH (7.0), recoveries for quercetin and quercetin-3-glucoside were 46.5% and 13.9%, respectively. Figure 1 The effects of intestinal digestion pH and acidic storage on quercetin and quercetin-3-glucoside recovered from digested onions (A) and the effects of storage pH on digested pure quercetin and quercetin-3-glucoside (B). Samples were digested for 30 minutes with pepsin, 60 minutes with pancreatin and bile, and then stored at -80°C. Each point represents the mean ± standard deviation of triplicate observations within the same experiment. Different letters indicate significantly different observations within each compound ( p < 0.05). Based on these results, optimal digestion conditions were decided to be: pepsin digestion at pH 2.0 for 30 minutes, pancreatin/bile digestion at pH 6.5 for 60 minutes, and a final storage at pH 2.0. Ascorbic acid and nitrogen treatments were not continued. Using these conditions, the effect of digestion on quercetin and quercetin-3-glucoside recoveries from apples, onions, and pure quercetin and quercetin-3-glucoside was examined (Figure 2 ). Following digestion, recoveries of pure quercetin-3-glucoside, apple quercetin-3-glucoside, and onion quercetin-3-glucoside were similar to recoveries from non-digested samples ( p > 0.05). Quercetin-3-glucoside recoveries from the digested apple, onion, and pure compound were 87.7, 89.5, and 86.4%, respectively. Quercetin recovery was significantly reduced in digested pure quercetin and digested onion samples, when compared to non-digested samples ( p < 0.05). Quercetin recovery was lower than quercetin-3-glucoside recovery and tended to vary more, depending on the food matrix: 52.5% and 74.3%, from the onion and pure compound, respectively. There was no significant difference in quercetin recovery between to the non-digested and digested apple homogenates. There was only trace or no quercetin in non-digested apple homogenates, so the appearance of any quercetin following digestion resulted in a net increase. Figure 2 The effects of digestion on pure quercetin and quercetin-3-glucoside and quercetin and quercetin-3-glucoside from apple and onion. Each point represents the mean ± standard deviation of triplicate observations within the same experiment. An asterisk indicates a significant difference between the control and the digestate ( p < 0.05). Uptake of quercetin-4'-glucoside and quercetin from shallot digestates by Caco-2 cells Quercetin-4'-glucoside and quercetin were absorbed by Caco-2 cells following treatment with both digested shallot and non-digested shallot homogenates (Figure 3 ). Quercetin-3-glucoside was not detected in any sample. Quercetin-4'-glucoside uptake by the Caco-2 cells increased by approximately 2-fold following digestion ( p < 0.05). Caco-2 cells treated with shallot homogenate absorbed approximately 2.9 ± 0.65 nmol of quercetin-4-glucoside, and Caco-2 cells treated with digested shallot absorbed 5.4 ± 0.04 nmol. Quercetin aglycone recovery from the digested shallot extract was only 47% that of the non-digested homogenate (Figure 3B insert), however quercetin uptake from the digested samples was similar to the non-digested samples ( p > 0.05). Caco-2 cells absorbed 2.8 ± 0.4 nmol and 2.7 ± 0.2 nmol quercetin from the non-digested and digested shallot homogenates, respectively. Absorption of both quercetin-4-glucoside and quercetin from digested shallot followed a dose response. The Caco-2 cells absorbed quercetin 4'-glucoside and quercetin incrementally less from the digested samples that were diluted 1:2 or 1:4 in HBSS. Figure 3 Caco-2 uptake of quercetin-4-glucoside (A) and quercetin (B) from digested and non-digested shallot homogenates. Shallot homogenates were digested for 30 minutes with pepsin at pH 2.0 and for 60 minutes with pancreatin/bile at pH 6.5. Digestates were directly placed on cells or diluted 1:2 or 1:4 in HBSS and then placed on cells. Cells were incubated with digestates for 30 minutes at 37°C. The imbedded graph in (B) shows quercetin recovery from shallots following the digestion procedure only. Each bar represents the mean ± standard deviation of triplicate observations within the same experiment. Different letters indicate significantly different observations within each compound ( p < 0.05). Induction of lactase activity in Caco-2 cells Addition of lactose and forskolin, a specific inducer of lactase [ 29 ], to Caco-2 cells did not significantly increase lactase activity of Caco-2 cells. The lactase activity of all cells ranged from 2–4 mU/mg protein in all treatments. Lactase Digestion Treatment with 100 units lactase/g sample had a significant effect on both quercetin and quercetin-3-glucoside recoveries from the shallot ( p < 0.05; Figure 4 ). Quercetin recovery from shallot digestates increased 5.5 fold, from 47.5 ± 7.6 μg/g sample in the untreated digestate to 262.2 ± 17.6 μg/g sample in the lactase treated sample. The lactase plus digestion treatment resulted in a non-significant decrease in quercetin recovery compared to the lactase only treated samples. Quercetin-3-glucoside from shallot digestates also increased approximately 5 fold, from 17.3 ± 1.7 μg/g sample to 80.0 ± 10.3 μg/g sample following the lactase treatment. The effect of lactase on the apple samples was not as great. Quercetin-3-glucoside recovery decreased slightly, while changes in quercetin levels were not significant ( p > 0.05). Figure 4 The effects of lactase and a combined lactase and digestion treatment on quercetin and quercetin-3-glucoside recovery from shallot (A) and apple (B) homogenates. Each point represents the mean ± standard deviation of triplicate observations within the same experiment. Different letters indicate significantly different observations within each compound ( p < 0.05). Because treating shallots with lactase increased quercetin recovery so greatly without significantly decreasing quercetin-3-glucoside recovery, the effect of lactase on quercetin-4'-glucoside recovery was also examined. More quercetin-4'-glucoside is found in shallots when compared to quercetin-3-glucoside. As the dose of lactase increased, quercetin-3-glucoside recovery increased from 18.2 ± 3.7 up to 175.5 ± 48.1 μg/g shallot at the 1000 unit dose and then decreased to 60.2 ± 2.0 μg/g at the 3000 unit dose (Figure 5A ). As the dose of lactase increased, quercetin recovery increased and quercetin-4'-glucoside decreased (Figure 5A ). The increase in quercetin was quite dramatic. Recovery of quercetin from untreated shallot samples was 93.7 ± 2.2 μg quercetin per gram sample, and at the highest lactase dose, recovery of quercetin from shallot samples was 958.8 ± 76.1 μg quercetin per gram shallot. Quercetin-4'-glucoside recovery decreased from 518.2 ± 10.7 μg/g shallot from the untreated sample to 3.2 ± 0.8 μg/g shallot at the highest treatment dose. A similar trend was seen for all compounds in the kinetic experiment. As the incubation time increased, recoveries of quercetin increased and quercetin-4'-glucoside decreased (Figure 5B ). Quercetin-3-glucoside increased through two hours, and then decreased following four and eight hours of incubation with lactase. In both the dose response and kinetic experiments, increases in quercetin recoveries were greater than decreases in quercetin-3-glucoside or quercetin-4'-glucoside recoveries. Figure 5 Dose response (A) and kinetics (B) of lactase on quercetin and quercetin glucoside recovery from shallots. Homogenized shallots were incubated 60 for minutes with 10, 50, 100, 300, 500, 1000, or 3000 units of lactase/mL sample. Homogenized shallots were incubated with 100 units lactase/mL sample for 15, 30, 60, 90, 120, 240, and 720 minutes. Each point represents the mean ± standard deviation of triplicate observations within the same experiment. Caco-2 cell uptake of quercetin and quercetin glucosides following lactase treatment The addition of lactase following the pepsin and pancreatin/bile digestion significantly increased the amount of quercetin absorbed by the Caco-2 cells with a significant decrease in the amount of quercetin-4'-glucoside absorbed by the Caco-2 cells ( p < 0.05, Figure 6 ). Quercetin uptake increased from 0.98 ± 0.67 nmol from the digested sample up to 14.1 ± 1.6 nmol from the digested plus 1000 units lactase treated sample. Quercetin-4'-glucoside uptake by Caco-2 cells decreased as the dose of lactase increased, however the increase in quercetin was more dramatic than the decrease in quercetin-4'-glucoside. Quercetin-3-glucoside uptake was not detected. Figure 6 Caco-2 uptake of quercetin-4-glucoside and quercetin from digested shallot and digested plus lactase treated shallot. Shallot homogenates were digested for 30 minutes with pepsin at pH = 2.0 and for 60 minutes with pancreatin/bile at pH = 6.5. Digested shallots were then treated with either 50, 100, 300, or 1000 units lactase/mL sample for 20 minutes. Samples were diluted 1:2 and then placed on the cells for 30 minutes. Each point represents the mean ± standard deviation of triplicate observations within the same experiment. Discussion In vitro digestion Previously, our laboratory determined that our Caco-2 cells had the potential to be used as a model to study quercetin bioavailability from onions and apples [ 15 ]. In the present study, we modified an in vitro digestion procedure and combined it with the Caco-2 cell model to give a more comprehensive examination of quercetin and quercetin glucoside bioavailability in Caco-2 cells. The digestion procedure modified in these experiments resulted in quercetin-3-glucoside recoveries that ranged from 78.9 to 89.5% and quercetin recoveries that ranged from 47.3 to 74.3%. In both cases, the lowest digestate recoveries were from the shallot. Interestingly, quercetin recovery from both the onion and shallot was considerably lower than from the pure compound. This difference is not yet explained, but could potentially be due to interactions with other compounds found in the onion and shallot. In all cases, quercetin recovery from digestates was lower than quercetin-3-glucoside. The glucoside moiety may lend stability to quercetin-3-glucoside during digestion, and could contribute to its greater bioavailability in vivo as well. Quercetin aglycone may be more susceptible to oxidation or other degradation during exposure to both the digestive enzymes and the variations in pH in the stomach and intestine. Ascorbic acid and nitrogen, both added to help decrease oxidation, had no effect on quercetin or quercetin-3-glucoside recoveries from digested onions. The factor that had the greatest effect on both quercetin and quercetin-3-glucoside stability in the digestate was pH. Recoveries of digested pure compounds and digested compounds from the onion homogenates were significantly less if stored at a pH of 6.5 or 7.0 than if stored at pH 2.0 at -80°C (Figure 1 ). Vallejo et. al [ 25 ] used an in vitro digestion method to measure the effect of digestion on a variety of compounds from broccoli. Following the pepsin and pancreatic digestion, they recovered only 16% of total flavonoids, and the main flavonoids found in the broccoli were quercetin and kaempferol glycosides. The recovery of quercetin and quercetin-3-glucosides, flavonoids common to the foods in our study, was much higher than 16% from the digested shallot, onion and apple. It has been estimated that quercetin glucoside bioavailability may be as high as 80% in humans and quercetin bioavailability may range from 35–53% [ 26 , 33 ]. Our results would appear to be more reasonable estimates, if indeed, quercetin and quercetin glucoside bioavailability lies within the approximated ranges found by Walle et. al [ 26 , 33 ]. Effect of digestion on quercetin and quercetin glucoside uptake by Caco-2 cells Digestion of the shallot resulted in decreased recoveries of both quercetin and quercetin-3-glucoside, therefore it was expected that digestion might decrease the bioavailability of these compounds as well. Following digestion, quercetin aglycone in the shallot was decreased by approximately 50%; however, quercetin bioavailability was unchanged following digestion compared to the non-digested samples. This means that the digestion procedure must degrade quercetin, and simultaneously enhances the bioavailability of quercetin, bringing the cellular uptake back to comparable levels with the non-digested samples. Quercetin-4'-glucoside uptake by the Caco-2 cells from the shallot increased by approximately 2-fold following the in vitro digestion. We hypothesize that the digestion procedure may have released more compounds from the food matrix leaving them more available for uptake by the Caco-2 cells. The digestion procedure may also have improved solubility of the compounds, increasing their absorption by the Caco-2 cells. Quercetin-3-glucoside was not detected in the Caco-2 cells following treatment with shallot. Quercetin-3-glucoside is a minor compound in the shallot, and it is believed that the levels were below our detection limit. In the past, we found that Caco-2 cells did absorb trace amounts of quercetin-3-glucoside from shallot extracts [ 15 ]. In the previous experiments, shallots were first extracted with ethanol and ethyl acetate, and finally reconstituted and concentrated in methanol. This procedure produced more concentrated shallot extracts for cell treatment than with our current procedure. In the current study, shallot homogenates and digestates were too dilute to detect small changes in initial concentrations or in cellular uptake of quercetin-3-glucoside, which was below the detection limit. Strong evidence suggests that quercetin glucosides are more bioavailable in humans than the quercetin aglycone, however it has not yet been determined why this is the case. Based on the digestion data, quercetin glucoside is more stable following the in vitro digestion conditions than quercetin and is therefore more likely to reach the intestine intact. Quercetin-4'-glucoside bioavailability in Caco-2 cells was increased nearly 2-fold following digestion and quercetin absorption was not changed (Figure 3 ). It has been hypothesized that absorbed intact quercetin glucosides are then quickly hydrolyzed by cytosolic β-glucosidase to quercetin aglycone [ 34 ]. It has also been hypothesized that the major pathway for quercetin glucoside absorption begins with hydrolysis by LPH. Deglycosylation of quercetin glucosides at the brush border membrane positions the resulting aglycone in a prime position for diffusion across the brush border. The deglycosylation of the quercetin glucoside would result in a higher concentration of aglycone at the apical enterocyte membrane and potentially increase the rate of absorption [ 35 ]. Effect of lactase on quercetin and quercetin-4'-glucoside uptake by Caco-2 cells The potential pathways for quercetin glucoside and quercetin metabolism and absorption can be seen in Figure 7 . Quercetin aglycone passively diffuses across the apical membrane and is then glucuronidated. Evidence strongly suggests that quercetin glucosides are first hydrolyzed by the lactase site of lactase phlorizin hydrolase prior to diffusion across the apical membrane [ 36 ]. Quercetin glucosides may also be transported into the cell by the sodium-dependent glucose transporter1 (SGLT1) and then hydrolyzed by the cytosolic beta-glucosidase. Quercetin-3-glucoside is not a good substrate for cytosolic beta-glucosidase [ 37 ]. Since research has shown that both quercetin-3-glucoside and quercetin-4'-glucoside are similarly bioavailable in humans [ 14 , 38 ], this could be an indication that hydrolysis by LPH and the subsequent passive diffusion of quercetin into the cell is the main pathway for quercetin glucoside absorption across the brush border. Following hydrolysis and incorporation into the cells, quercetin aglycone is then glucuronidated. Quercetin glucosides and possibly quercetin glucuronides are then transported back into the lumen by multidrug resistance protein 2 (MRP2). Conjugated quercetin metabolites also eventually reach circulation, but the transporter involved in transporting them across the basolateral side is still unknown. Figure 7 Potential mechanism of quercetin and quercetin glucosides uptake by enterocytes. LPH, lactase phlorizin hydrolase; SGLT1, sodium-dependent glucose transporter 1; CBG, cytosolic B-glucosidase; MRP2, multi-drug resitance protein 2; UDP-GT, UDP glucuronosyl transferase; QUE, quercetin. Since lactase is an important enzyme in the metabolism and subsequent absorption of quercetin glucosides, lactose intolerant individuals may have a reduced capability to hydrolyze quercetin glucoside for further absorption across the small intestinal wall. Many lactose intolerant people use commercial lactase to break down lactose. Not only might this enzyme help improve digestibility of lactose, but it may also increase bioavailability of quercetin from foods. Initial lactase treatments were applied both to shallot and apple homogenates and digestates. Lactase had little to no effect on apple samples. Apples contain quercetin bound mainly to galactosides, rhamnosides, and xylosides, conjugates that would not be readily hydrolyzed by lactase. However, lactase treatment had great effects on shallot and onion digestates. The shallot and onion are high in quercetin glucosides, mainly quercetin-4'-glucoside, quercetin-3-glucoside, and quercetin-3,4'-diglucoside, compounds readily hydrolyzed by lactase. Treatment with lactase in the range of 15 units/mg sample up to 1000 units/mg sample, significantly increased both quercetin and quercetin-3-glucoside recovery in shallot homogenates and digestates. The increase in quercetin-3-glucoside is most likely a result of deglycosylation of quercetin-3,4'-diglucoside. Rhodes et al. [ 39 ] found that over time quercetin-3,4'-diglucoside in chopped onion will autolyze to monoglucosides, and within 24 hours the diglucoside will completely disappear. This may also explain the increase in quercetin-3-glucoside over time. Quercetin-4'-glucoside decreased following treatment with lactase as expected. Results from this work suggest that quercetin-4'-glucoside is utilized by lactase prior to quercetin-3-glucoside. Interestingly, the increase in total quercetin was greater than the decrease in quercetin-4'-glucoside. Digestion with lactase may release quercetin from the food matrix as well, making it more available for absorption. Following hydrolysis of quercetin glycosides, it has been hypothesized that quercetin is quickly glucuronidated, and quercetin glucuronides are then found circulating in the plasma [ 40 ]. In the current studies, these Caco-2 cells showed no signs of glucuronidating quercetin following quercetin absorption, but do express some LPH activity as was evident by the increased quercetin uptake from shallots and from the lactase activity assays [ 15 ]. Thus, these Caco-2 cells have the potential to be a good model of quercetin absorption, but not of further metabolism. A good model of quercetin glucoside bioavailability should incorporate lactase activity. The Caco-2 cells used for these experiments expressed lactase activity similar to that of a lactose intolerant human (2–10 mU/mg protein). These cells had approximate lactase activity of between 2–4 mU/mg protein, consistent with what we previously reported [ 15 ]. Lactose tolerant humans tend to have intestinal lactase activity that ranges from 20–80 mU/mg protein [ 41 ]. Forskolin and lactose did not induce lactase activity in our Caco-2 cells. The lactase activity of our cells was nearly 10 times higher than previously reported values for Caco-2 cells of 0.3 mU/mg protein of lactase activity [ 27 ], and it is quite possible that the lactase enzyme in our Caco-2 cells is already expressed to the fullest extent. Since lactase activity could not be increased in the Caco-2 cells, we combined a lactase treatment with digestion to provide an intestinal uptake model that is more comparable to a lactose tolerant human, or a lactose intolerant human ingesting a lactase digestive aid to help improve lactose digestion. Not only did lactase increase the amount of quercetin in digested shallot homogenates, but it also increased the amount of quercetin taken up by the Caco-2 cells from the digested shallot extracts. This suggests that a lactase containing digestive aid may increase absorption of quercetin from onions in lactose intolerant humans. Combining the Caco-2 cell model with an in vitro digestion, simulating stomach and small intestinal digestion, and a lactase digestion may provide a more useful model to examine and screen for bioavailability of flavonoid glucosides from common foods (Figure 8 ). Figure 8 Caco-2 cell culture model for examining quercetin bioavailability from foods. Conclusions Following an in vitro stomach and small intestinal digestion, the recovery of quercetin and quercetin-3-glucoside is optimized at a storage pH at or below 3.5. Storage at pH above 3.5 results in loss of most of the compounds. The in vitro digestion increased the uptake of shallot quercetin-4'-glucoside by the Caco-2 cells. Quercetin uptake by the Caco-2 cells was similar between digested and non-digested samples, despite the fact that approximately 50% of shallot quercetin is lost during digestion. Treating shallot digestates with lactase increased the recovery of quercetin aglycone 10-fold and decreased the recovery of quercetin-4'-glucoside. Lactase treatment increased the bioavailability of quercetin aglycone 14-fold and decreased the bioavailability of quercetin-4'-glucoside to the Caco-2 cells. Combining pepsin, pancreatin/bile, and lactase digestions with the Caco-2 cell culture monolayer may results in a useful model for studying flavonoid bioavailability from foods. Many advances have been made in understanding flavonoid bioavailability, however many questions still remain unanswered. Food processing, interactions with other compounds as well as with other foods are all factors that may affect bioavailability of flavonoids. A simple and inexpensive screening model would be beneficial as a first step in examining many of these factors. The Caco-2 cell model has the potential to be a good model for analyzing intestinal uptake of quercetin, quercetin glucoside and other flavonoids. While the Caco-2 cell model will never be an exact replica of a human small intestine, it could provide a valuable tool for initial screenings of large quantities of samples relatively quickly and inexpensively. In this study, it was found that a simple digestive aid such as lactase might increase quercetin bioavailability. This may be of importance to lactose intolerant people. Such significant trends may be examined in more detail using human or animal models. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC546214.xml |
514552 | Drop-out and mood improvement: a randomised controlled trial with light exposure and physical exercise [ISRCTN36478292] | Background Combining bright light exposure and physical exercise may be an effective way of relieving depressive symptoms. However, relatively little is known about individual factors predicting either a good response or treatment failure. We explored background variables possibly explaining the individual variation in treatment response or failure in a randomised trial. Methods Participants were volunteers of working-age, free from prior mental disorders and recruited via occupational health centres. The intervention was a randomised 8-week trial with three groups: aerobics in bright light, aerobics in normal room lighting, and relaxation/stretching in bright light. Good response was defined as a 50% decrease in the symptom score on either the Hamilton Depression Rating Scale (HDRS) or 8-item scale of atypical symptoms. Background variables for the analysis included sex, age, body-mass index, general health habits, seasonal pattern, and sleep disturbances. Results Complete data were received from 98 subjects (11 men, 87 women). Of them, 42 (5 men, 37 women) were classified as responders on the HDRS. Overall, light had a significant effect on the number of responders, as assessed with the HDRS (X 2 = .02). The number needed to treat (NNT) for light was 3.8. Conclusions We investigated the effect of bright light and exercise on depressive symptoms. Problems with sleep, especially initial insomnia, may predict a good response to treatment using combined light and exercise. Bright light exposure and physical exercise, even in combination, seem to be well tolerated and effective on depressive symptoms. | Background At northern latitudes reduced vitality, increased appetite and sleep complaints are common symptoms during wintertime, even among people considered healthy [ 1 ]. Atypical depressive symptoms, which are often seen in seasonal depression, appear to correlate with decreased illumination [ 2 ]. Exposure to natural light also appears to have a substantial effect on well-being in twins with bipolar disorder [ 3 ]. Disorganised circadian clockwork, related to the shortening photoperiod and changes in this most important external time-giver, is thought to play a role in the pathophysiology of seasonal mood changes. Bright (>2500 lx) light therapy has proven effective for season-related major depressive episodes, and also for milder, subsyndromal symptoms [ 4 ]. An interesting alternative to bright light is dawn simulation (short, timed pulses of light during the natural awakening), which may be helpful in seasonal affective disorder [ 5 ] and sleeping problems, even in the general population [ 6 ]. Exercise would seem to be the ideal treatment for depression: available, affordable, with minimal side effects. Unfortunately, many exercise treatment studies suffer from methodological weaknesses and lack of adequate follow-up to determine long-term efficacy. In their systematic review, Lawlor and Hopker even concluded that the effectiveness of exercise in reducing depressive symptoms cannot be determined because of a lack of good quality research, though exercise was found to be more effective than no treatment, and as effective as cognitive therapy [ 7 ]. Fortunately, absence of evidence does not necessarily indicate evidence of absence. A recent 16-week study with rigorous methodology indicates that exercise is as effective as standard medication (sertraline) for treatment of depression [ 8 ]. A 6-month follow-up of the study subjects showed that remitted subjects in the exercise group had significantly lower relapse rates than remitted subjects in the medication group, and that continued exercise was associated with lower rates of depression [ 9 ]. Other studies on the efficacy of exercise treatment for depression are also conducted, to address e.g. the question of a dose-response relationship [ 10 ]. Several mechanisms may explain the mood-lifting effects of exercise: psychological (increased sense of self worth, positive feedback), social (an increase in social contacts), and physiological (changes in central endorphin and monoamine concentrations). Exercise may induce phase-shifts in the human circadian rhythms [ 11 ], so it is possible that exercise also may exert part of its action on mood by influencing the circadian clock. Adding light exposure to exercise for the treatment of depression and depressive symptoms seems a promising intervention. Combinations of bright light exposure and physical exercise have achieved beneficial effects on mood in trials on healthy adult populations [ 12 , 13 ]. Natural light exposure (one hour walk outdoors) may also be effective in treating seasonal affective disorder [ 14 ]. It remains to be determined, however, whether it is possible to define a subgroup of people who are especially likely to benefit from this kind of intervention, and what, if any, are the individual factors predicting a good response to light or exercise, or their combination? And on the contrary, another important subgroup to identify, in determining the efficacy of any intervention, is the subjects who drop out of the study prematurely. Several predictors of response to light treatment in winter depressives have been identified: the ratio of atypical to classical symptoms of depression [ 15 ] and hypersomnia, increased eating and younger age [ 16 ]. Meesters et al. found that a large diurnal variation had a negative predictive value on response to light treatment [ 17 ]. Temperament dimensions have also been investigated. Although higher harm avoidance scores have been linked to non-response to light therapy in one study [ 18 ], another study found no predictive value of avoidance scores [ 19 ]. With regard to exercise treatment of depression, baseline levels of self-reported anxiety and life satisfaction were found to be best predictors of both dropout and treatment success, when exercise alone was compared to antidepressive medication or exercise with medication [ 20 ]. In the present study we tried to address this question: who will benefit from light, exercise or their combination? A variety of background variables were investigated: age, seasonality, depressive and atypical symptoms, treatment adherence, fitness, body mass index, self-perceived quality of sleep, and alcohol consumption. We did not measure diurnal variation or personality dimensions. Methods Adult volunteers of working age were invited to participate in a study of light and exercise via occupational health centres. The enrolled subjects were randomly allocated to three intervention groups: aerobics training in bright light (>2500 lx, measured at eye-level), similar training in the normal lighting of the gym (400–600 lx), and relaxation and stretching sessions in bright light. The training or relaxation sessions (45 minutes each, starting at 7:30 a.m. or 8:30 a.m. Monday through Friday, and at 10:00 a.m. or 11:00 a.m. on Saturdays) were scheduled two times a week over eight weeks. Study was conducted between November 25, 1997, and January 25, 1998. The length of daylight on these dates was 6 h 48 min and 7 h 23 min, respectively. Intervention Both the aerobics training and relaxation groups were led by 3 physiotherapists, each of whom supervised one third of each group's training or relaxation sessions. The training and relaxation sessions were structured to maintain treatment consistency. In the aerobics groups, the intensity of the training was checked with a heart rate monitor, the target rate being 120 to 150 beats per minute. Stretching/relaxation training was designed to avoid raising the pulse. All training sessions were in the same gym, the ceiling of which was equipped with 30 extra light fixtures with cool-white (6000 K) fluorescent lamps (F58W/186, Sylvania, Germany), which were turned on for the bright light groups. Assessment Mood during the study period was recorded using the Structured Interview Guide for the Hamilton Depression Rating Scale – Seasonal Affective Disorders Version Self-Rating Format (SIGH-SAD-SR) [ 21 ], which includes the 21-item Hamilton Depression Rating Scale (HDRS) plus an eight-item addendum for atypical symptoms (ATYP). The SIGH-SAD-SR was filled in at baseline, after week 4 and at the end of the 8-week study period. At the start of the study and at weeks 4 and 8, all subjects were weighed to assess body-mass index (BMI). Before and after the study period all subjects in the Aerobics training groups participated in a 2-km walking test, which predicts maximal oxygen uptake using a model with age, sex, walking time, BMI, and heart rate at the end of the test as variables [ 22 ]. At baseline, sleep quality was assessed with the Basic Nordic Sleep Questionnaire (BNSQ) [ 23 ], and the subjects also completed an abbreviated, 26-item FINRISK questionnaire [ 24 ] concerning smoking, alcohol consumption, dietary fat intake, and habitual exercise. The Seasonal Pattern Assessment Questionnaire (SPAQ) [ 25 ] measures seasonal changes in mood and behaviour. The SPAQ includes a 6-item scale yielding the Global Seasonality Score (GSS). Based on the GSS the subjects were thereby divided into seasonals and non-seasonals, according to the criteria for subsyndromal seasonal affective disorder presented by Bartko and Kasper [ 26 ]. Baseline demographic data on all participants included sex, age, and educational level. Ethics All subjects returned a written informed consent prior to participation. The ethics committee of the National Public Health Institution approved the study protocol. Statistics All analyses were done on SPSS for Windows (Release 11.5.1)-statistical package (SPSS Inc., Chicago, Illinois). Dropouts Participants were classified as dropouts if they, for any reason, did not finish the eight-week study protocol. Analysis of variance (ANOVA)-models were used to compare the baseline characteristics of dropouts with those who completed the study. In the models, the baseline characteristic was the dependent variable, and the outcome (dropouts vs. completers) and treatment group (Light & Exercise, Exercise, Light) were factors. The Outcome × Treatment group interaction was also tested in each model. Background characteristics examined were age, GSS, BMI, fitness, and alcohol consumption, all as continuous variables. Baseline HDRS and ATYP were included, as well as percentage of sessions attended. From the BNSQ, following variables were chosen: initial, middle, and late insomnia, and quality of sleep. Treatment benefit was defined separately as response and, with stricter criteria, as remission. Treatment response The main outcome measures were changes in the HDRS, ATYP and the SIGH-SAD-SR over the 8-week study period. A 50 % decrease on the HDRS, ATYP or the SIGH-SAD-SR total score was used to divide subjects into responders and non-responders. To assess the effect of baseline characteristics, logistic regression models were formulated, with the defined clinical response as the dependent variable. Light therapy, physical exercise, and sex were constant in the models. Other independent baseline variables in the analysis were age (over/under 40 years), seasonality (from the SPAQ), initial, middle and late insomnia, quality of sleep, feeling tired after waking (from the BNSQ), serum total cholesterol levels, current smoking, physical training, and consumption of alcoholic beverages (from the FINRISK questionnaire). All categorical variables were dichotomised for the analysis. The best-predicting co-variates were found by backward step-wise selection. Analysis of variance (ANOVA) was applied to compare means between groups, and associations were analysed by calculating partial correlation coefficients, after controlling for age and sex. Pearson chi-square (two-sided) was used when applicable. Remission Stricter criteria were applied for the definition of remission. To increase clinical meaningfulness and to avoid 'flooring effect', subjects with low symptom scores were excluded from these analyses. HDRS Only subjects with a baseline HDRS of eight or higher were included. Remission was defined as at least a 50% reduction on the HDRS during the trial, and a score of less than eight at the end of the study period. SIGH-SAD Subjects with a baseline SIGH-SAD-total score of fourteen or more were included. Remission was defined as at least a 50% reduction on the score during the eight-week study, and a final SIGH-SAD-score of eight or less. All analyses were done 'intention-to-treat', i.e. dropouts were classified as treatment failures. With remitted subjects, we desisted from using logistic regression because of lower number of subjects, which would limit the number of variables. Instead, the background variables were examined one-by-one with ANOVA-models (see Dropouts for description). Results Complete data were received from 98 subjects (11 men, 87 women, see Figure 1 ) with a mean (s.d.) age of 43.4 (9.5), ranging from 26 to 63 years. Sixty-nine subjects were assigned to the light therapy groups, and 61 subjects to the aerobic exercise treatment groups. There were 37 of these subjects in the combined group, and their mean (s.d.) score on the HDRS was 10.5 (6.3), on the ATYP 5.9 (4.2), and on the SIGH-SAD-SR 16.4 (9.4). On average (s.d.), the GSS was 10.5 (4.9), and the BMI 24.2 (3.7). At baseline, the GSS was negatively associated with habitual training (r = -.26, p = .01), and correlated with initial insomnia (r = .20, p = .05), low quality of sleep (r = .30, p = .003), and feeling tired after waking (r = .35, p = .001). Subjects reporting initial insomnia on the BNSQ (n = 28) had, as expected, a higher score on the HDRS at baseline than other subjects (F = 11.2, p = 0.001), and they also had a higher ATYP score (F = 6.70, p = 0.01) and a trend towards higher GSS (F = 3.92, p = 0.05). Twenty-three of these subjects received light therapy, and 13 (57%) of them were classified as responders based on the changes in HDRS scores (X 2 = .04). Figure 1 Study protocol There was a negative correlation between response on the HDRS and alcohol consumption (more than 7 drinks a week) (r = -.23, p = .03), and high levels of serum total cholesterol (r = -.21, p = .04). Treatment response Based on the HDRS, 42 subjects (5 men, 37 women, X 2 = .9) were classified as responders. Their mean age (s.d.) was 41.3 (9.5) years, ranging from 26 to 58. Thirty-five (83%) had had light therapy, 24 (57%) had been in the aerobic exercise groups, and 17 subjects (40%) in the combined group. Overall, light had a significant effect on the number of responders, as assessed with the HDRS (X 2 = .02). The number needed to treat (NNT) for light was 3.8. On the basis of the ATYP scores, 51 subjects (8 men, 43 women) were classified as responders. Their mean age (s.d.) was 41.9 (9.8) years, ranging from 26 to 63. Thirty-seven (73%) had received light therapy, 30 (59%) had been in the exercise groups, and 16 (31%) in the combined group. Response on the SIGH-SAD-SR was negatively associated with baseline self-reported alcohol consumption (r = -.26, p = .01). There were 45 responders (5 men, 40 women) on the SIGH-SAD-SR, with a mean age (s.d.) of 41.5 (9.5) years, ranging from 26 to 58. Thirty-seven (82%) had received light therapy, 26 (58%) had done aerobic exercise, and 18 (40%) had been in the combined group. The effect of light therapy was significant (X 2 = .03). Based on these figures, the NNT for light was 3.8. The logistic regression models for the HDRS, ATYP, and SIGH-SAD-SR total scores are presented in Table 1 . Table 1 Key results from logistic regression models. Variable coefficient s.e. p value HDRS Age group* -.8 .50 .09 Total cholesterol** -1.6 .66 .01 Alcohol consumption† -1.6 .62 .008 ATYP score Age group* -1.0 .52 .05 Initial insomnia‡ 1.8 .72 .01 Quality of sleep ± -2.1 .69 .002 Alcohol consumption† -1.2 .60 .04 SIGH-SAD-SR total score Age group* -1.1 .53 .04 Initial insomnia‡ 1.5 .70 .03 Quality of sleep ± -1.6 .66 .02 Alcohol consumption† -1.8 .62 .005 *Age group: over 40 years vs. under 40 years **Total cholesterol: previous high total serum cholesterol, yes vs. no †Alcohol consumption: over 7 drinks per week vs. 7 drinks or less per week ‡Initial insomnia: trouble falling asleep once a week to daily vs. less than once week ± Quality of sleep: bad or rather bad vs. normal to good Dropouts There were 26 (21%) subjects classified as dropouts (4 male, 22 female, X 2 = .6), 8 (20%) in the light & exercise group, 13 (31%) in the exercise group, and 5 (12%) in the light group (X 2 = .1). Thirteen subjects (50%) had received light therapy (X 2 = .05). Table 2 presents the background variables investigated from all subjects and by treatment group. Dropout-status was significantly influenced by the GSS (F = 5.40, p = .02) and treatment sessions attended (F = 143.0, p = .000). There was a trend towards baseline HDRS having an effect on dropout-status (F = 4.00, p = .05), but baseline HDRS was also influenced by treatment group (F = 4.38, p = .02), despite random assignment to groups. The pre-intervention fitness test result (in the exercise groups) was predictive of dropout status (F = 11.1, p = .001), and there was also a significant Treatment group × Dropout interaction (F = 7.82, p = .007). Initial insomnia, derived from the BNSQ, was also a significant factor (F = 6.00, p = .02, Treatment group × Dropout interaction F = 5.43, p = .006). Table 2 Comparison of baseline variables (S.D) of drop-outs vs. completers Analysis of variance Variable Treatment group Dropout group Interaction All Exercise&Light Exercise Light F p F p F p Age .50 .61 2.33 .13 2.20 .12 Drop-outs 39.5 (8.2) 41.3 (7.2) 35.4 (7.2) 43.4 (9.6) Completers 43.4 (9.6) 41.8 (9.2) 45.5 (10.2) 43.2 (9.3) GSS 1.35 .26 5.40 .02 .98 .38 Drop-outs 13.1 (4.5) 13.0 (5.0) 11.1 (3.3) 15.8 (4.5) Completers 10.5 (4.9) 10.1 (5.2) 10.5 (4.6) 10.9 (5.1) HDRS 4.38 .02 4.00 .05 1.55 .22 Drop-outs 13.6 (8.4) 16.3 (10.9) 8.29 (3.9) 16.6 (5.6) Completers 10.5 (6.4) 10.8 (7.0) 9.00 (5.2) 11.4 (6.6) ATYP * 1.18 .31 2.42 .12 .23 .79 Drop-outs 7.45 (5.3) 7.50 (5.4) 6.14 (5.0) 9.20 (6.0) Completers 5.92 (4.3) 6.22 (4.9) 5.07 (3.7) 6.32 (4.2) BMI ** .30 .74 1.88 .17 1.33 .27 Drop-outs 25.5 (4.9) 27.0 (6.2) 24.9 (4.5) 24.4 (3.8) Completers 24.2 (3.7) 23.6 (3.1) 24.1 (3.6) 24.7 (4.3) Sessions attended (%) 2.70 .07 143 .000 2.29 .11 Drop-outs 32.5 (24.4) 25.8 (20.6) 30.6 (24.9) 48.0(27.2) Completers 82.1 (14.4) 82.7 (14.4) 80.5 (15.2) 82.9(14.1) Fitness 2.61 .11 11.1 .001 7.82 .007 Drop-outs 93.3 (14.3) 83.7 (11.3) 99.1 (13.0) ---- Completers 103.2 (12.1) 105.1 (13.6) 101.0 (10.2) --- BNSQ Initial insomnia 3.00 .06 6.00 .02 5.43 .006 Drop-outs 2.61 (1.2) 3.50 (.84) 2.14 (1.1) 2.20 (1.3) Completers 2.06 (.93) 1.84 (.81) 1.83 (.93) 2.43 (.93) Middle insomnia 1.91 .15 .23 .64 1.34 .27 Drop-outs 3.21 (1.4) 3.57 (1.4) 2.43 (1.1) 3.80 (1.6) Completers 3.11 (1.3) 3.10 (1.3) 3.03 (1.3) 3.19 (1.4) Late insomnia 2.97 .06 .55 .46 1.15 .32 Drop-outs 1.68 (.95) 1.86 (1.1) 1.14 (.38) 2.20 (1.1) Completers 1.92 (.92) 1.78 (.83) 1.79 (.90) 2.14 (.98) Quality of sleep 1.615 .20 .10 .753 .70 .50 Drop-outs 2.47 (1.1) 2.86 (1.2) 2.00 (0.0) 2.60 (1.3) Completers 2.42 (1.1) 2.34 (1.0) 2.21 (1.0) 2.65 (1.2) Alcohol consumption † .079 .92 .31 .58 .098 .91 Drop-outs 6.05 (5.6) 5.63 (6.3) 6.57 (6.7) 6.00 (3.4) Completers 5.34 (5.5) 5.00 (4.4) 4.97 (5.9) 5.92 (6.0) *ATYP – atypical symptom score ** BMI – Body Mass Index † Alcohol consumption – drinks per week Remitted subjects HDRS (see Table 3 ) Table 3 Comparison of baseline variables (S.D) of subjects in remission (HDRS) with those who did not remit during the study Analysis of variance Variable Treatment group Remitted group Interaction All Exercise&Light Exercise Light F p F p F p Age .11 .90 1.56 .22 .11 .89 Remitted 40.5 (10.5) 39.4 (11.6) 39.6 (11.2) 41.7(10.2) Not remitted 43.4 (9.0) 43.8 (8.0) 42.9 (9.6) 43.4 (9.7) GSS 1.59 .21 1.86 .18 .24 .79 Remitted 11.2 (4.7) 10.2 (5.2) 9.60 (5.0) 12.8 (3.9) Not remitted 12.6 (5.0) 12.8 (5.5) 11.4 (4.3) 13.5 (5.1) HDRS 3.09 .05 .76 .38 .11 .90 Remitted 14.2 (4.9) 16.3 (5.7) 11.0 (3.5) 14.0 (4.3) Not remitted 15.1 (6.4) 16.7 (8.1) 12.6 (3.7) 15.9 (6.2) ATYP 1.51 .23 .26 .61 .17 .84 Remitted 7.56 (5.0) 8.22 (4.7) 5.00 (3.5) 8.18 (5.6) Not remitted 7.76 (4.5) 8.27 (5.7) 6.69 (4.1) 8.28 (3.9) BMI .63 .54 .088 .77 .51 .60 Remitted 24.5 (3.9) 24.8 (2.6) 22.4 (1.8) 25.3 (5.2) Not remitted 24.5 (4.4) 24.3 (5.4) 24.4 (3.8) 24.7 (4.4) Sessions attended (%) .58 .56 8.66 .004 1.35 .27 Remitted 80.3 (15.8) 82.2 (10.0) 81.3 (27.2) 78.2(14.6) Not remitted 61.6 (30.1) 52.0 (33.6) 59.2 (31.1) 71.9(24.2) Fitness .34 .57 .003 .96 .30 .59 Remitted 100.1 (13.7) 98.3 (16.5) 103.4 (6.8) --- Not remitted 100.6 (12.8) 100.5 (16.0) 100.7 (10.2) --- BNSQ Initial insomnia 3.83 .03 1.19 .28 1.87 .16 Remitted 2.32 (1.0) 2.22 (.97) 1.40 (.55) 2.82 (.98) Not remitted 2.42 (1.1) 2.71 (.99) 2.13 (1.2) 2.44 (.98) Middle insomnia .43 .65 .00 .99 .47 .63 Remitted 3.36 (1.3) 3.22 (1.3) 3.20 (1.5) 3.55 (1.2) Not remitted 3.31 (1.2) 3.64 (.93) 3.00 (1.2) 3.33 (1.4) Late insomnia 1.37 .26 .69 .41 .90 .41 Remitted 2.04 (.94) 2.00 (1.0) 2.00 (1.0) 2.09 (.94) Not remitted 1.85 (.90) 1.93 (.83) 1.38 (.50) 2.22 (1.1) Quality of sleep 2.72 .07 .00 .99 .52 .60 Remitted 2.84 (1.2) 2.78 (1.1) 2.20 (1.1) 3.18 (1.3) Not remitted 2.71 (.99) 3.00 (.96) 2.31 (.70) 2.83 (1.2) Alcohol consumption .17 .85 1.08 .30 1.29 .28 Remitted 5.08 (3.9) 6.78 (5.4) 3.80 (2.2) 4.27 (2.5) Not remitted 6.63 (6.8) 5.20 (5.4) 6.38 (7.5) 8.06 (7.2) Abbreviations as in Table 2 A total of 74 subjects (10 male, 64 female) were included in the analyses. Twenty-five subjects (3 male, 22 female, X 2 = .8) were considered remitted on the HDRS after the study period. Nine had been in the light & exercise group, 5 in the exercise group, and 11 in the light group (X 2 = .5). Thus, 20 of the subjects had received bright light therapy (X 2 = .3) and 14 had been in the exercise groups (X 2 = .5). Proportion of sessions attended had a significant impact on remission status (F = 8.66, p = .004). The BNSQ initial insomnia-variable was influenced by treatment group assignment (F = 3.83, p = .03). SIGH-SAD (see Table 4 ) Table 4 Comparison of baseline variables (S.D) of subjects in remission (SIGH-SAD total score) with those who did not remit during the study Analysis of variance Variable Treatment group Remitted group Interaction All Exercise&Light Exercise Light F p F p F p Age .26 .77 .068 .80 .54 .58 Remitted 42.0 (10.5) 43.6 (11.4) 37.5 (6.4) 41.8 (11.2) Not remitted 42.0 (9.5) 40.1 (8.6) 41.7 (10.2) 43.6 (9.7) GSS 1.60 .21 5.23 .03 .17 .85 Remitted 10.62 (4.9) 10.3 (4.8) 7.00 (1.4) 11.8 (5.4) Not remitted 13.2 (4.7) 13.3 (5.7) 11.9 (4.3) 14.4 (4.1) HDRS 1.71 .19 1.07 .31 .093 .91 Remitted 14.5 (5.3) 15.3 (6.7) 11.5 (2.1) 14.5 (4.6) Not remitted 15.6 (6.2) 18.3 (7.9) 12.7 (3.8) 16.2 (5.7) ATYP 1.89 .16 2.68 .11 .52 .60 Remitted 7.71 (4.7) 8.29 (4.2) 3.50 (.71) 8.25 (5.4) Not remitted 8.88 (4.2) 10.3 (4.8) 7.76 (3.8) 8.84 (4.1) BMI .63 .54 .57 .45 1.79 .18 Remitted 24.3 (2.9) 25.7 (2.5) 21.0 (1.4) 23.9 (2.8) Not remitted 24.7 (4.5) 23.4 (4.2) 24.6 (3.8) 25.6 (5.3) Sessions attended (%) .64 .53 2.66 .11 .60 .55 Remitted 82.4 (14.9) 84.8 (6.34) 66.7 (47.1) 84.2 (8.68) Not remitted 65.3 (28.3) 59.0 (31.6) 64.3 (30.5) 70.9 (24.0) Fitness 1.06 .31 .12 .73 2.01 .17 Remitted 99.7 (16.5) 96.6 (17.7) 110.5 (2.1) --- Not remitted 101.4 (11.6) 102.7 (13.8) 100.5 (10.1) --- BNSQ Initial insomnia 2.46 .09 .69 .41 1.26 .29 Remitted 2.35 (.93) 2.00 (1.0) 1.50 (.71) 2.88 (.64) Not remitted 2.39 (1.0) 2.54 (.78) 2.12 (1.2) 2.53 (1.1) Middle insomnia .19 .83 .88 .35 .707 .50 Remitted 3.18 (1.4) 3.00 (1.4) 3.00 (.00) 3.37 (1.6) Not remitted 3.47 (1.2) 3.92 (.95) 3.24 (1.2) 3.37 (1.3) Late insomnia 1.48 .24 .003 .96 .068 .94 Remitted 2.06 (.90) 2.00 (1.0) 1.50 (.71) 2.25 (.89) Not remitted 1.92 (.95) 1.85 (.99) 1.65 (.70) 2.21 (1.1) Quality of sleep 1.87 .16 .21 .65 1.35 .27 Remitted 2.82 (1.1) 2.43 (.98) 2.00 (.00) 3.38 (1.1) Not remitted 2.76 (1.1) 2.92 (1.2) 2.53 (.87) 2.84 (1.3) Alcohol consumption .059 .94 1.49 .23 .26 .77 Remitted 4.06 (2.8) 4.43 (3.3) 4.50 (3.5) 3.63 (2.4) Not remitted 6.50 (6.1) 5.36 (5.7) 6.76 (7.0) 7.11 (5.8) Abbreviations as in Table 2 Sixty-seven subjects (8 male, 59 female) were included in the analyses. After the trial, sixteen of them (1 male, 15 female, X 2 = .4) were considered to be in remission on the SIGH-SAD-scale. Seven subjects had been in the light & exercise group, 1 in the exercise group, and 8 in the light group (X 2 = .08). Fifteen subjects (94%) had been in groups with bright light exposure (X 2 = .03), and eight (50%) in the exercise groups (X 2 = .4). In the ANOVA-models, remission was significantly influenced only by the GSS (F = 5.23, p = .03). Discussion Treatment response The results of this study confirm earlier findings from light and exercise trials that these interventions are well tolerated and effective. Considering the study population was not a clinical one, but consisted of volunteers not suffering from any major mental or physical disorder, the NNT for light therapy was high: 4 subjects need to be treated for one subject to respond, as assessed with both the HDRS and the SIGH-SAD-SR. The overall response rate, on all the scales, was about 50 %. Initial insomnia at the start of the study was an independent variable predicting good response, both on the ATYP and the SIGH-SAD-SR. Disorders of sleep are common in depressive states, and also in the general population [ 27 ]. The mean GSS of our study subjects was relatively high, suggesting that they had a marked degree of seasonal variation in mood and behaviour and might be predisposed to desynchrony between the sleep-wake cycle and circadian rhythms in winter. It is probable that entrainment of internal clocks by environmental stimuli is impaired in depression. Light and exercise are both capable of entraining the circadian rhythms, which could be one, but not the only mechanism of action reflected externally as improved sleep and mood [ 28 ]. However, a limitation of our study was that we did not measure circadian rhythms. Ageing changes sleep-wake habits. This may be due to a deteriorating impact of light with age on the flexibility of the internal clock [ 29 ]. No studies comparing the young and the old on the benefits of bright light therapy have been published to our knowledge. Age has not been a significant factor in trials of bright light therapy. Baehr et al. have examined the circadian phase-shifting effects of exercise in two age groups (20–32 and 55–73 years), and no significant differences were found [ 30 ]. However, our hypothesis that the older age group would benefit from this kind of intervention was not supported; in fact, the opposite occurred. One explanation for this is the frequency of the intervention: two times a week may be a signal powerful enough to entrain circadian rhythms for younger subjects, but not for older subjects, even when light and exercise interventions are combined. We found that even moderate consumption of alcohol (>7 drinks per week) predicted a poorer response on all the assessed scales. One explanation to this might be the negative effect of alcohol on circadian rhythms and especially on sleep [ 31 , 32 ]. Dropout from the study The dropout rate was relatively low (combined 21%), and did not differ significantly between the treatment conditions. There seemed to be a trend towards subjects in groups receiving bright light therapy adhering to the study more closely than subjects in the exercise group. Subjects might have felt bright light therapy is a novel, more attractive treatment option than plain, 'old-fashioned' exercise. We tried to minimise this problem by emphasising 'exercise trial' in leaflets provided to possible volunteers. It was not possible to avoid this problem altogether, as reflected by those four subjects who dropped out of the study after hearing they had been randomised into the exercise group. When these four subjects, now counted as dropouts, are excluded, the dropout rates of the light & exercise and exercise groups are virtually identical, and similar to the rates reported previously [ 20 ]. The dropout rate in the light group was considerably lower than in the exercise groups, but the difference failed to reach statistical significance. Subjects possibly experienced bright light exposure without the strenuous exercise very comfortable, which is understandable. An interesting finding is that completers were in a better physical condition in the pre-intervention fitness test than were dropouts. Regular exercising may be a representation of self-motivation trait, which would increase adherence to a therapeutic exercise program [ 33 ]. A major limitation is of course that the subjects in the bright light group did not perform the fitness test. This had to be omitted from the study protocol for economical reasons. Remitted subjects Using the strict remission criteria yielded few results. Attendance to treatment sessions did predict remission on the Hamilton scale (but not the SIGH-SAD total score), but post-hoc analyses showed that this was caused by dropouts, which were automatically labeled as treatment failures. A lower GSS was predictive of remission on the SIGH-SAD total score. Again, post-hoc analyses showed this effect was caused by dropouts with higher than average scores. In previous research on the use of light therapy, atypical depressive symptoms have been predictive of treatment response and remission. This effect was not seen in the present study. We did separate analyses for hypersomnia, hyperphagia, increased appetite / carbohydrate craving, and reduced vitality, but none of these individual atypical symptoms predicted remission either. Assessment The study subjects were not patients with clinically diagnosed depression, but volunteers with varying degrees of depressive symptoms. This poses a major question of definition of treatment response and remission, and also measurement of depressive symptoms, e.g. using scales originally designed for the follow-up of depressed in-patients [ 34 ]. Our primary focus in planning this study was practical: to find an intervention that would benefit the public at large. Study subjects were not a random sample of population, but volunteers invited through occupational health centres, and free of pre-existing, diagnosed or medicated mental illness. However, we decided to use established methods for the assessment of depressive symptoms. In their systematic review on exercise studies, Lawlor and Hopker demand the use of dichotomous outcomes, arguing them to be more understandable and more important outcomes in clinical terms [ 7 ]. We agree, and use the concepts of response and remission in this study. The cut-offs selected were based on previous studies [ 35 ], done on depressed patients. The application of these criteria to a trial with healthy subjects may seem artificial, but we feel this increases the clinical meaningfulness of the results. Future research More studies, with expanded methodology, are clearly needed to shed light on the individual factors separating responders and non-responders in exercise trials, with or without bright light. Interesting research subjects would be circadian phenotyping (with Morning-Eveningness Questionnaire; [ 36 ]), and motor activity measurement. Pre-treatment expectations should be assessed, to estimate the possible placebo-effect. Conclusions We investigated the effect of bright light and exercise on depressive symptoms in working-age men and women, free from mental disorder and/or psychotropic medication. We found that problems with sleep, especially initial insomnia, may predict a good response to treatment using combined light and exercise. Regular intake of alcoholic beverages (over 7 drinks per week) seems to have an opposite effect. Bright light exposure and physical exercise, even in combination, seem to be well tolerated and effective on depressive symptoms, but more research is needed to confirm these findings. Competing interests None declared. Authors' contributions SL, TP, and JL planned the study protocol and supervised the study. JH planned the statistical analyses. SL, TP, and JH analysed the data. SL and TP wrote the manuscript, which was commented by JH and JL. All authors have read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC514552.xml |
555532 | Ca2+ regulation in the absence of the iplA gene product in Dictyostelium discoideum | Background Stimulation of Dictyostelium discoideum with cAMP evokes an elevation of the cytosolic free Ca 2+ concentration ([Ca 2+ ] i ). The [Ca 2+ ] i -change is composed of liberation of stored Ca 2+ and extracellular Ca 2+ -entry. The significance of the [Ca 2+ ] i -transient for chemotaxis is under debate. Abolition of chemotactic orientation and migration by Ca 2+ -buffers in the cytosol indicates that a [Ca 2+ ] i -increase is required for chemotaxis. Yet, the iplA - mutant disrupted in a gene bearing similarity to IP 3 -receptors of higher eukaryotes aggregates despite the absence of a cAMP-induced [Ca 2+ ] i -transient which favours the view that [Ca 2+ ] i -changes are insignificant for chemotaxis. Results We investigated Ca 2+ -fluxes and the effect of their disturbance on chemotaxis and development of iplA - cells. Differentiation was altered as compared to wild type amoebae and sensitive towards manipulation of the level of stored Ca 2+ . Chemotaxis was impaired when [Ca 2+ ] i -transients were suppressed by the presence of a Ca 2+ -chelator in the cytosol of the cells. Analysis of ion fluxes revealed that capacitative Ca 2+ -entry was fully operative in the mutant. In suspensions of intact and permeabilized cells cAMP elicited extracellular Ca 2+ -influx and liberation of stored Ca 2+ , respectively, yet to a lesser extent than in wild type. In suspensions of partially purified storage vesicles ATP-induced Ca 2+ -uptake and Ca 2+ -release activated by fatty acids or Ca 2+ -ATPase inhibitors were similar to wild type. Mn 2+ -quenching of fura2 fluorescence allows to study Ca 2+ -influx indirectly and revealed that the responsiveness of mutant cells was shifted to higher concentrations: roughly 100 times more Mn 2+ was necessary to observe agonist-induced Mn 2+ -influx. cAMP evoked a [Ca 2+ ] i -elevation when stores were strongly loaded with Ca 2+ , again with a similar shift in sensitivity in the mutant. In addition, basal [Ca 2+ ] i was significantly lower in iplA - than in wild type amoebae. Conclusion These results support the view that [Ca 2+ ] i -transients are essential for chemotaxis and differentiation. Moreover, capacitative and agonist-activated ion fluxes are regulated by separate pathways that are mediated either by two types of channels in the plasma membrane or by distinct mechanisms coupling Ca 2+ -release from stores to Ca 2+ -entry in Dictyostelium . The iplA - strain retains the capacitative Ca 2+ -entry pathway and an impaired agonist-activated pathway that operates with reduced efficiency or at higher ionic pressure. | Background Aggregation of Dictyostelium discoideum proceeds by an oriented migration of the amoebae towards a source of the attractant cAMP which is synthesized and released periodically by cells in the center of the aggregate. Stimulation with cAMP activates liberation of stored Ca 2+ and extracellular Ca 2+ -entry [ 1 ] leading to a [Ca 2+ ] i -transient [ 2 - 4 ]. Chemotaxis proceeds in the presence of extracellular EGTA but not in the presence of intracellular Ca 2+ buffers, so a [Ca 2+ ] i -elevation is necessary and release of stored Ca 2+ is sufficient for oriented migration [ 5 ]. On the other hand, the view that a [Ca 2+ ] i -increase is essential for chemotaxis was called into question by analysis of a cell line where the iplA gene was disrupted by homologous recombination [ 6 ]. The iplA gene is the only gene known in the Dicyostelium genome so far that shares homology with IP 3 -receptors of higher eukaryotes. However, whether its protein product indeed constitutes a functional IP 3 -receptor and its cellular localization are not known. The iplA - mutant was found to aggregate and to form fruiting bodies although neither cAMP-activated 45 Ca 2+ -entry nor a [Ca 2+ ] i -elevation were detected [ 6 ]. From these results the authors concluded that the iplA gene product is central to the regulation of [Ca 2+ ] i and that its presence and thus the presence of an agonist-activated [Ca 2+ ] i -increase is not necessary for proper chemotaxis and development. However, agents that interfere with IP 3 -receptor mediated signaling such as XestosponginC [ 7 ] were found to influence not only cAMP-induced Ca 2+ -fluxes but also the chemotactic response and aggregation of Dictyostelium [ 8 ]. In this study we aimed to clarify these conflicting findings and analyzed both, capacitative and chemoattractant-induced Ca 2+ -fluxes and the effect of their disturbance on chemotaxis and differentiation of the iplA - mutant. Mn 2+ -influx was used to determine the rates of ion fluxes into cells with filled and emptied stores and related to Ca 2+ -electrode recordings in cell suspensions. We found that ion fluxes, chemotaxis and differentiation were sensitive towards alteration of the Ca 2+ -homeostasis. Capacitative Ca 2+ -entry was normal in the mutant and upon stimulation with agonist Ca 2+ - and Mn 2+ -fluxes occurred, yet to a considerably reduced extent. Spontaneous motility and chemotactic performance of mutant amoebae was strongly impaired by the intracellular presence of a Ca 2+ -chelator. Results Extracellular [Ca 2+ ] affects development and chemotaxis of wild type and iplA - As iplA - cells formed fruiting bodies, albeit somewhat smaller in size, it was concluded that chemotactic aggregation and differentiation was normal [ 6 ]. We analyzed development of the mutant in parallel with wild type at various conditions. When cells differentiated on H5-agar plates (control situation) we consistently found a delay in the onset of aggregation by 1–2 h in the mutant; the smaller size of fruiting bodies was due to breaking of aggregation strands yielding smaller mounds (Fig. 1 ). Next we asked whether the absence or presence of Ca 2+ affects development. Differentiation on EGTA-containing agar plates and thus the steady reduction of internal Ca 2+ -levels dose dependently resulted in a delay of aggregation and a decrease in the size of aggregates and fruiting bodies in both strains. Doses of 5–10 mM EGTA in the agar did not significantly alter the time point of aggregation which is in accordance with previous data [ 9 ] showing requirement of additional multiple washing of amoebae with EGTA in order to affect aggregation. At concentrations of 15–20 mM EGTA however, aggregation occurred at later time points (Fig. 2 ), on average at 13 ± 3 h in wild type and at 19 ± 2 h in iplA - cells (mean ± s.e.m. from 5 experiments); despite the daily variations in aggregation timing the mutant strain was delayed as compared to the wild type in each of the experiments performed. On the other hand, the presence of Ca 2+ in the agar and therefore the continuous loading of cells with Ca 2+ [ 10 ] resulted in stronger impairment of aggregation in the wild type. The delayed aggregation of wild type cells in the presence of Ca 2+ was not due to inhibition of chemotaxis (see below). Now the formation of aggregates was observed consistently at earlier time points in the iplA - strain than in wild type (Fig. 3 ; on average 7 ± 0.5 h vs. 15 ± 5 h until aggregate formation in iplA - and wild type amoebae, respectively, at 20 mM CaCl 2 in 6 independent experiments); indeed, under this condition differentiation of iplA - cells resembled that of wild type observed in the control situation. Figure 1 iplA - cells have an altered pattern of development. Differentiation of the mutant and the wild type strain was assayed in parallel on agar plates. Cells at different time points of development on H5-agar are shown. Wild type amoebae aggregated at t 7 , whereas aggregation of the mutant strain was delayed and aggregation strands broke (t 10 ); therefore, smaller fruiting bodies were formed as compared to the wild type. The full width of the image corresponds to 12.5 mm. Figure 2 Development of iplA - cells is impaired by depletion of internal Ca 2+ -stores due to EGTA-treatment. Differentiation of the wild type and the mutant on plates containing 20 mM EGTA is shown. Aggregation was delayed in both strains till t 15 and t 18 in wild type and iplA - cells, respectively. The size of the aggregates and the fruiting bodies were much smaller than under control conditions. The full width of the image corresponds to 12.5 mm. Figure 3 In the presence of external Ca 2 aggregation is accelerated in iplA - cells. Differentiation of the mutant and the wild type strain was assayed in parallel on agar plates supplemented with 20 mM CaCl 2 . Aggregate formation occurred earlier in iplA - cells (at t 7 ) than in wild type (starting at t 19 ) in the presence of Ca 2+ . The full width of the image corresponds to 12.5 mm. Then we analyzed the effect of treatment with either EGTA or Ca 2+ on basal cell motility. We found that under control conditions the general morphology of the cells as well as extension of pseudopods was practically identical in both strains (Fig. 4 A, B , [see Additional file 1 ]). Preincubation with 10 mM EGTA for 60 min led to strong rounding of wild type and mutant amoebae (Fig. 4 C, D ) with reduced extension of small pseudopods [see Additional file 2 ]. By contrast, pretreatment with 10 mM CaCl 2 did not affect the morphology (Fig. 4 E, F ) or the extension of pseudopods [see Additional file 3 ] in both strains. Next we tested chemotaxis of amoebae towards a cAMP-filled glass capillary. Under control conditions cells of both strains oriented and migrated towards the tip of the capillary (Fig. 5 A, B ); the average chemotactic speed was not different between wild type and the mutant strain (10.7 ± 2.1 vs. 11.0 ± 0.7 μm/min; mean ± s.e.m. of 20 wild type and 43 mutant amoebae analyzed in 3 and 4 independent experiments, respectively). Incubation in 10 mM EGTA for 60 min abolished chemotaxis in most of the wild type and the iplA - amoebae: small pseudopods were extended randomly and the cells did not approach the capillary tip (Fig. 5 C, D ). Only rarely, cells of both strains exhibited an oriented but highly reduced migration towards the cAMP source (3% and 5% of 33 wild type and 19 mutant cells analyzed in 3 independent experiments, respectively). Thus the loss of Ca 2+ from stores impairs both, orientation and migration also in the absence of the iplA gene product. By contrast, when amoebae were incubated in 10 mM CaCl 2 for 60 min to load stores, they oriented and migrated towards the cAMP capillary (Fig. 5 E, F ). The chemotactic speed of wild type cells (9.9 ± 1.2 μm/min; mean ± s.e.m. of 17 cells tested in 3 independent experiments) was comparable to that under control conditions whereas mutant amoebae chemotaxed significantly faster (13.6 ± 1.7 μm/min; mean ± s.e.m. of 15 mutant amoebae analyzed in 3 independent experiments) than wild type cells in the presence of 10 mM CaCl 2 (Mann-Whitney rank sum test, p = 0.041). Figure 4 General morphology of wild type and iplA - cells under control conditions (A, B), in the presence of 10 mM EGTA for 60 min (C, D) or in the presence of 10 mM CaCl 2 for 80 min (E, F). In H5-buffer or in the presence of 10 mM CaCl 2 the morphology was not significantly different between wild type and mutant amoebae. However, in the presence of EGTA the cells of both strains were rounded. Photographs were taken at t 5 . Basal motility under these conditions can be viewed in the accompanying movies. Figure 5 Chemotaxis of wild type and mutant amoebae at different experimental conditions. The tracks of individual cells (in red) migrating during chemotactic stimulation (position of the tip of the cAMP-filled capillary: green star) are shown. In H5-buffer (A, B) both cell types migrated in an oriented manner towards the capillary tip, albeit not always in a straight line. After preincubation with 10 mM EGTA for 60 min and in its continued presence during the chemotaxis assay (C, D) the cells remained stationary with random pseudopod extension. Preincubation of amoebae with 10 mM CaCl 2 (E, F) did not impair chemotaxis; rather, the cells of both strains migrated towards the capillary tip. Chemotaxis experiments were done at t 6 . Buffering of intracellular [Ca 2+ ] impairs chemotaxis The observation that aggregation occurred in the mutant cell line although a cAMP-activated increase in [Ca 2+ ] i was not detectable resulted in the conclusion that [Ca 2+ ] i -changes were not necessary to accomplish chemotaxis [ 6 ]. We used the mobile buffer approach originally described by Speksnijder et al. [ 11 ] which allows to analyze the requirement of a [Ca 2+ ] i -gradient for a given response. If in Dictyostelium a [Ca 2+ ] i -increase was necessary for chemotaxis, the presence of a Ca 2+ -chelator in the cytosol should impair orientation and/or migration. In a previous study, we had introduced the Ca 2+ -chelator BAPTA and its derivatives into the cytosol of wild type amoebae which indeed had inhibited chemotactic migration and reduced chemotactic orientation [ 5 ]. Here we used the Ca 2+ -indicator Fura2-dextran to clamp [Ca 2+ ] i and loaded the indicator into wild type and mutant cells in the absence of external CaCl 2 . The treatment affected chemotactic performance of wild type as well as iplA - amoebae. Lack of extracellular CaCl 2 during the loading process induced strong rounding of the amoebae and loss of migration. Figure 6 shows that the capacity to orient chemotactically and to extend pseudopods towards the capillary tip was reduced by 58% in wild type (93 cells tested in 4 independent experiments). Inhibition was also evident in iplA - cells (Fig. 6 ) showing sensitivity of the mutant towards buffering of intracellular Ca 2+ -levels and eradication of [Ca 2+ ] i -changes: the fraction of pseudopods extended in direction of the cAMP-source was reduced by 75% (74 cells tested in 3 independent experiments). These results show that not only in wild type but also in the iplA - cell line the ability to orient and to migrate in fact depends on an agonist-activated [Ca 2+ ] i -elevation. Figure 6 Chemotaxis of iplA - cells is impaired in the intracellular presence of a Ca 2+ -buffer. Wild type and mutant amoebae were loaded with Fura2-dextran and their ability to protrude pseudopods towards a cAMP-filled glass capillary was compared to that of untreated cells. In both strains the presence of the chelator in the cytosol led to a decrease in the fraction of cells extending pseudopods and migrating towards the cAMP source. Analysis of Ca 2+ -fluxes Our findings that differentiation was sensitive towards depletion of Ca 2+ or loading of the cells with Ca 2+ and that chemotaxis was blocked by intracellular Ca 2+ -buffers led us to investigate Ca 2+ -fluxes in the mutant cell line. We used a Ca 2+ -sensitive electrode in cell suspensions to measure Ca 2+ -fluxes, an approach different from that of Traynor et al. [ 6 ] who had studied ion fluxes by 45 Ca 2+ -measurements. First we tested whether the coupling of stores to the plasma membrane, i.e. capacitative Ca 2+ -fluxes without prior stimulation with agonists were altered. In Dictyostelium induction of capacitative Ca 2+ -influx requires active intracellular Ca 2+ -pumps. Their inhibition by either thapsigargin or 2,5-di-(t-butyl)-1,4-hydroquinone (BHQ) does not evoke influx; rather, stores have to be emptied by treatment with EGTA [ 12 ]. Capacitative Ca 2+ -fluxes were studied early during differentiation (t 2 –t 4 ). At this time Ca 2+ -influx and Ca 2+ -efflux are at an equilibrium which held true for both, wild type and mutant cells (not shown); in suspensions of cells at later stages of development influx strongly exceeds efflux [ 1 ]. In iplA - and in wild type cells emptying of storage compartments via preincubation of amoebae with EGTA induced capacitative Ca 2+ -entry (Fig. 7 A ) which was blocked by addition of 1 mM NaN 3 (Fig. 7 B ). The characteristics of influx were comparable in wild type and mutant cells. These data show that capacitative Ca 2+ -influx does not depend on the product of the iplA gene. Figure 7 Recordings of Ca 2+ -fluxes in iplA - and wild type amoebae. [Ca 2+ ] e was measured in cell suspensions with a Ca 2+ -sensitive electrode. (A) Treatment of amoebae with 5 mM EGTA for 30 min activated capacitative Ca 2+ -influx (one out of 12/6 determinations in 4/3 independent experiments is shown for iplA - and wild type, respectively). (B) Capacitative influx was blocked by the addition of 1 mM NaN 3 (one out of 5/4 determinations in 3/3 independent experiments). Measurements were done at t 3 . On the other hand, agonist-activated 45 Ca 2+ -entry had been reported to be absent in the mutant strain; in their study, Traynor et al. had stimulated cells with cAMP in the presence of 0.1 mM CaCl 2 [ 6 ]. The use of a Ca 2+ -sensitive electrode allows to measure much lower levels of extracellular Ca 2+ to analyze Ca 2+ -fluxes, in the range of approximately 1 μM Ca 2+ . Indeed, we found that under this condition reversible Ca 2+ -entry occurred after addition of 1 μM cAMP (Fig. 8 A ) that amounted to 10.2 ± 4.3 pmol Ca 2+ /10 7 cells (mean ± s.d. from 9 experiments). The level of influx represented roughly 5% of wild type influx (Fig. 8 B and [ 13 , 14 ]). Ca 2+ -influx was delayed in the mutant and the time to reach the maximum was longer than in wild type cells [ 13 , 14 ]. In addition, challenge with arachidonic acid (AA) induced influx (Fig. 9 A ). Again, the mutant was less sensitive and higher concentrations were required than those reported to evoke Ca 2+ -entry in wild type cells (Fig. 8 B , 9 C and [ 13 ]). Neither 10 nor 20 μM AA were effective; in the wild type 10 μM AA activates influx of 190 ± 58 pmol Ca 2+ /10 7 cells [ 14 ]. At 60 μM AA entry occurred in the mutant strain which amounted to an average of 107 ± 21 pmol Ca 2+ /10 7 cells (mean ± s.d. from 7 experiments). Preincubation of cells with the SERCA-type Ca 2+ -ATPase inhibitor BHQ reduced AA-induced influx by 82 % (Fig. 9 B ) to an average of 21 ± 18 pmol Ca 2+ /10 7 cells (mean ± s.d. from 3 experiments). These data show that Ca 2+ -fluxes across the plasma membrane do occur in iplA - cells as well but at a reduced level. Figure 8 Agonist-activated Ca 2+ -fluxes in suspensions of iplA - and wild type amoebae. cAMP elicited reversible Ca 2+ -influx in the mutant (A) and in wild type ((B) and see [14]); measurements were done at t 7 –t 7.5 . Note the different doses of CaCl 2 added for calibration. The time points of cAMP-addition (1 μM) and of AA-addition (6 μM) in the wild type are indicated by arrows. Figure 9 Fatty acids activate Ca 2+ -fluxes in iplA - amoebae. (A) 60 μM AA evoked a transient decrease in [Ca 2+ ] e representing Ca 2+ -influx; measurement was done at t 6 (B) After preincubating amoebae with the SERCA-type Ca 2+ -ATPase blocker BHQ (100 μM) for 20 min to inhibit uptake of Ca 2+ into internal storage compartments, the AA-activated response was absent; measurement was done at t 7.5 . Results of measurements with wild type (C, D) stimulated with 6 μM AA are shown for comparison. Next we tested whether the mutant strain was able to release stored Ca 2+ when stimulated with cAMP or AA. Fluxes were measured in suspensions of cells with permeabilized plasma membranes; any change in [Ca 2+ ] e thus reflects efflux of Ca 2+ from storage compartments. Both, cAMP and arachidonic acid activated release of stored Ca 2+ (Fig. 10 A ). On average, addition of 1 μM cAMP released 7.3 ± 3.4 pmol Ca 2+ /10 7 cells and 16.3 ± 7.2 pmol Ca 2+ /10 7 cells were liberated after stimulation with 3 μM AA (mean ± s.d. from 10 and 3 experiments, respectively). The amount of Ca 2+ -efflux from stores after cAMP stimulation was 61% of that found in wild type cells (Fig. 10 B and [ 15 ]) whereas release upon AA-challenge was in the range of 5–10% of wild type (see Fig. 2 in [ 14 ]). In addition to the Ca 2+ -electrode recordings, we studied Ca 2+ -fluxes in suspensions of partially purified storage compartments fluorimetrically. ATP induced Ca 2+ -sequestration (Table 1 ) was of similar magnitude and rate as in wild type stores. This result indicates that the decreased release of Ca 2+ from the stores measured with the Ca 2+ -electrode is not due to a lack of storage capacity. Moreover, the addition of AA evoked release of Ca 2+ from stores as did inhibition of Ca 2+ -pump(s) by thapsigargin. XestosponginC that inhibits Ca 2+ -uptake and activates Ca 2+ -release in wild type [ 8 ] and the ionophore ionomycin also resulted in substantial Ca 2+ release in the mutant cell line (Table 1 ). All values were in the same range as those for wild type. Table 1 Determination of Ca 2+ -fluxes in partially purified storage compartments of the iplA - mutant and of wild type. Ca 2+ -sequestering vesicles were prepared as outlined in Methods. Measurements were performed with the pellet and supernatant fraction. ATP-induced uptake and release activated by different agents is given as nmol Ca 2+ -uptake/min and mg of protein and pmol Ca 2+ -release/tube, respectively (mean ± s.d.). In release experiments 60–75 μl of pellet and 120–140 μl of supernatant fraction were used per tube. Numbers in brackets give number of experiments; n.d.: not determined. iplA - Wt Stimulation Fraction Fraction Pellet Supernatant Pellet Supernatant Uptake (nmol/min*mg) 1 mM ATP 1.96 ± 0.55 (4) 0.28 ± 0.15 (4) 1.87 ± 0.74 (3) 0.38 ± 0.16 (3) Release (pmol/tube) 10 μM AA 360 ± 227 (8) 761 ± 218 (6) 396 ± 122 (6) 961 ± 374 (2) 40 μM Thapsigargin 570 ± 250 (6) 170 ± 73 (6) 582 ± 123 (5) 265 ± 135 (2) 6 μM XestosponginC 201 ± 55 (4) n.d. 276 ± 46 (3) n.d. 2 μM Ionomycin 447 ± 147 (5) 147 ± 41 (4) 580± 173 (3) 193 ± 76 (2) Figure 10 cAMP and arachidonic acid elicit Ca 2+ -release from internal stores. (A) [Ca 2+ ] e was recorded at t 7 in iplA - cells with permeabilized plasma membranes. Amoebae were challenged with 1 μM cAMP and 3 μM AA, respectively. (B) The response of permeabilized wild type stimulated with 1 μM cAMP at t 6 is shown for comparison. Mn 2+ -quenching experiments The [Ca 2+ ] e -recordings in suspensions of cells as described above detect the sum of Ca 2+ -influx and efflux. Therefore, a complementary approach which monitors influx only was pursued, by using the Mn 2+ -quenching technique in single intact amoebae. This method is based on the fact that many Ca 2+ -channels are permeable to Mn 2+ [ 16 ] and that the Ca 2+ -indicator Fura2 binds Mn 2+ with high affinity. Fluorescence of the indicator is quenched upon binding [ 17 ]. We compared quenching of Fura2-dextran fluorescence activated by addition of Mn 2+ alone or in combination with 1 μM cAMP in wild type and mutant cells. Higher concentrations of MnCl 2 were required to quench Fura2-dextran fluorescence in iplA - amoebae (Fig. 11 , Table 2 ). Reduction of fluorescence occurred at 1 μM Mn 2+ and 1 μM Mn 2+ /cAMP in wild type (Fig. 11 A, B ; see also [ 12 ]) but not in the mutant (Fig. 11 C, D ) where addition of 100 μM Mn 2+ /cAMP was necessary; 100 μM Mn 2+ alone was not effective (Fig. 11 C, D ) but started at 200 μM Mn 2+ (not shown). These data show that the reduction in ion fluxes in the mutant were indeed due to an alteration in entry mechanisms. Table 2 Rate of basal and cAMP-induced Mn 2+ -influx. Amoebae were challenged with 1 or 100 μM Mn 2+ either with or without 1 μM cAMP. Cells were preincubated with 0.1 mM EGTA as outlined in Methods. Mn 2+ quenching of fura-2-dextran fluorescence was tested in H5-buffer and is expressed as decrease in fluorescence units/sec (mean ± s.e.m.). Numbers in brackets give number of cells tested and number of experiments. Stimulation Preincubation none EGTA (0.1 mM) 1 μM Mn 2+ 0 (121/5) 0.37 ± 0.2 (142/3) 1 μM Mn 2+ /1 μM cAMP 0 (135/5) 1.4 ± 0.1 (207/4) 100 μM Mn 2+ 0 (109/3) 100 μM Mn 2+ /1 μM cAMP 1.0 ± 0.2 (292/9) Figure 11 Basal and cAMP-induced Mn 2+ -influx. Influx was assayed by quenching of Fura2-dextran fluorescence. (A, B) The response of wild type amoebae is shown for comparison; 1 μM Mn 2+ ± 1 μM cAMP was added. iplA - cells in nominally Ca 2+ -free buffer were challenged with 100 μM Mn 2+ ± 1 μM cAMP at t 7 (closed symbols); when 1 μM Mn 2+ was added (open symbols) no influx was detected (C, D). After preincubation with EGTA influx was observed at 1–2 μM Mn 2+ ± 1 μM cAMP (E, F). Fluorescence intensity at 360 nm excitation is shown as mean ± s.e.m In principle, the iplA gene product could form a channel in the plasma membrane or in membranes of internal stores. The lack of the iplA gene product in the stores might impair their coupling to the plasma membrane. As we had observed capacitative Ca 2+ -entry in the mutant we asked whether manipulation of the filling state of the stores altered ion fluxes. First we tested the effect of emptying of stores on Mn 2+ -influx. When cells were preincubated with EGTA, the requirement for high doses of Mn 2+ to quench fluorescence was abrogated. Now capacitative and also agonist-activated Mn 2+ -influx occurred at concentrations of MnCl 2 comparable to those used under control conditions in wild type, in the range of 1–2 μM (Fig. 11 E, F ). This result renders the possibility that the plasma membrane is altered in the mutant unlikely. Yet, the rate of Mn 2+ -influx observed in EGTA-treated mutant amoebae was still less than in wild type cells with respect to both basal and cAMP-activated fluxes (53 and 58% of wild type [ 12 ], respectively). [Ca 2+ ] i -determination In wild type cells treatment with EGTA augments responsiveness and cAMP-elicited [Ca 2+ ] i -transients are detected at low extracellular [Ca 2+ ] [ 12 ]. However, an agonist-induced [Ca 2+ ] i elevation was not observed in iplA - cells under these conditions. On the other hand, when stores were loaded in the continued presence of CaCl 2 , we observed that differentiation of the mutant resembled the wild type as described above. This led us to compare the [Ca 2+ ] i -response of wild type and mutant amoebae after pretreatment with CaCl 2 . In wild type cells preincubation with 1 mM CaCl 2 for 10–15 min and its continued presence during the [Ca 2+ ] i -imaging experiment is required to activate a [Ca 2+ ] i -transient after challenge with cAMP (Fig. 12 A and see [ 12 ]); in nominally Ca 2+ -free medium or at very low extracellular [Ca 2+ ] a cAMP-activated [Ca 2+ ] i -elevation is not observed [ 12 ]. In accordance with the data of Traynor et al. [ 6 ] this condition (Fig. 12 B ) and even increasing the concentration of CaCl 2 to 20 mM resulted in no detectable [Ca 2+ ] i -increase in the mutant strain (not shown). However, we found that the basal [Ca 2+ ] i level in iplA - amoebae was significantly lower than in wild type and amounted to an average of 36 ± 3 nM (mean ± s.e.m. of 8 determinations in 3 independent experiments) as compared to 50 ± 2 nM in wild type (mean ± s.e.m. of 29 determinations in 9 independent experiments; Mann-Whitney rank sum test, p = 0.002). Figure 12 [Ca 2+ ] i -recordings in cells preincubated with CaCl 2 in order to load stores. (A) The response of wild type upon stimulation with 1 μM cAMP (arrow) at standard conditions, i.e. after preincubation with 1 mM CaCl 2 for 10–15 min and stimulated in the presence of 1 mM CaCl 2 is shown. Values give mean ± s.e.m. of 7 cells. (B) When iplA - cells were stimulated with 1 μM cAMP at standard conditions (as outlined in (A)), no response was observed. Mean ± s.e.m. of 6 cells is shown. (C) Wild type was preincubated with 1 mM CaCl 2 for 4–5 h; after washing cells were incubated in H5-buffer supplemented with 1 μM CaCl 2 and challenged with 1 μM cAMP (arrow). Values give mean ± s.e.m. of 16 cells. (D) iplA - incubated for 3 h with 20 mM CaCl 2 were washed and subsequently [Ca 2+ ] i -imaging was done in buffer containing 1 mM CaCl 2 . Arrow indicates the time point when 1 μM cAMP was added. Mean ± s.e.m. of 10 cells is shown. For stronger loading of Ca 2+ -stores, we preincubated cells with 1 mM CaCl 2 for 4 h. After this treatment a [Ca 2+ ] i -elevation upon addition of cAMP was detected in 60% of wild type amoebae even at low extracellular [Ca 2+ ] levels, i.e. when the buffer used to wash the cells had been supplemented with only 1 μM CaCl 2 (Fig. 12 C ). Starting from a basal level of 48 ± 4 nM, the height of the [Ca 2+ ] i -transient amounted to 23 ± 2 nM (mean ± s.e.m. of 12 determinations in 8 independent experiments). Again, these conditions were not effective in iplA - cells; rather, the sensitivity of the mutant was shifted to higher Ca 2+ concentrations as had been found with Mn 2+ -quenching experiments. We preincubated iplA - amoebae with 20 mM CaCl 2 for 3 h; after washing thoroughly, a cAMP-induced [Ca 2+ ] i -elevation in the presence of 1 mM CaCl 2 was observed (Fig. 12 D ) in 28% of the cells; its average height amounted to 67 ± 11 nM (mean ± s.e.m. of 15 determinations in 4 independent experiments) starting from a basal level of 39 ± 2 nM. In the course of these experiments we once observed a response also under standard conditions, i.e. at 1 mM [Ca 2+ ] e without prior incubation in 20 mM CaCl 2 ; the height of the increase amounted to 54 ± 6 nM (mean ± s.e.m.). Yet, this was a rare event (once in 31 determinations). Discussion The role of cAMP-activated [Ca 2+ ] i -changes for chemotaxis has been questioned by Traynor et al. [ 6 ] who reported results obtained with the iplA - mutant cell line favouring insignificance of [Ca 2+ ] i for the chemotactic response. The authors had observed formation of fruiting bodies even though neither 45 Ca 2+ -fluxes nor an agonist induced [Ca 2+ ] i -elevation were detectable. The discrepancy between our view that a [Ca 2+ ] i -elevation is necessary for a proper chemotactic response [ 5 ] and the conclusion of Traynor et al. prompted us to analyze chemotaxis, differentiation and the [Ca 2+ ]-regulation of the iplA - mutant in detail. In particular, we tested not only basal and cAMP-activated ion fluxes but also capacitative Ca 2+ -entry which is induced by emptying internal Ca 2+ -stores via preincubation of amoebae with EGTA [ 12 ]. Aggregation and development of wild type and mutant cells on agar plates was sensitive towards continuous emptying or loading of Ca 2+ -stores. These effects are not necessarily caused by altering chemotactic migration. It is conceivable that other Ca 2+ -dependent processes were affected, e.g. that the timing or pattern of gene expression or the establishment of cell contacts was altered. Although incubation of mutant amoebae for 2 h with 20 mM CaCl 2 or of wild type with 1 mM CaCl 2 for 4–5 h or with 1 mM EGTA for 1 h [ 12 ] did not significantly increase or lower basal [Ca 2+ ] i it is possible that the continued presence of 10 mM EGTA or CaCl 2 for many hours affects basal levels of [Ca 2+ ] i which in turn might mediate effects on gene expression as was shown for prolonged incubation of cells with BHQ [ 18 ]. During development Dictyostelium cells form Ca 2+ -dependent and EDTA/EGTA-sensitive cell-cell contacts that are mediated by gp24 and DdCAD-1 ([ 19 , 20 ]; for review see [ 21 ]). Therefore, chelation of extracellular Ca 2+ might also inhibit cell adhesion. However, mutant cells whose gene encoding DdCAD-1 had been disrupted show normal chemotaxis and cell streams. Furthermore, mound formation was accelerated and only culmination was delayed by about 6 hours [ 20 ]. If only Ca 2+ -dependent cell adhesion was affected in our development assay in the presence of EGTA we would expect a similar phenotype. However, aggregation was clearly delayed. This argues for additional Ca 2+ -dependent processes during aggregation. When we tested the influence of the presence of EGTA or CaCl 2 on spontaneous motility and chemotaxis we found that in both strains motility in general was strongly impaired and that chemotaxis of the amoebae towards the cAMP-filled glass capillary was virtually abolished upon depletion of internal stores by the extracellular presence of EGTA. This effect is time dependent; after 30 min of incubation with 10 mM EGTA the behaviour of wild type amoebae was found to be unaltered and only after treatment for 0.5–1 h rounding and reduction of pseudopod elongation towards the capillary tip occurred [ 5 ]. Prolonged incubation for more than 1 h as carried out in this study completely inhibited the chemotactic response. These results strengthen the view that Ca 2+ has a necessary role in chemotaxis in wild type and in the mutant as well. When the cellular Ca 2+ content falls below a critical value Ca 2+ -dependent cytoskeletal rearrangements [ 22 , 23 ] that are necessary for both, random pseudopod extension during spontaneous motility and oriented pseudopod formation after chemotactic stimulation no longer take place correctly. On the other hand, the presence of 10 mM CaCl 2 induced no alteration of basal cell motility in wild type or mutant amoebae. Yet, during chemotactic stimulation the average speed of migration towards the capillary tip was higher in mutant than in wild type cells. In this respect it is of importance that the basal level of [Ca 2+ ] i was significantly lower in the former. At standard conditions the reduced basal [Ca 2+ ] i does not impair the capacity of the mutant to chemotax. Therefore, this particular mutant strain represents the "minimal solution" with respect to the concentration of cytosolic Ca 2+ necessary to accomplish cytoskeletal rearrangements and extrusion of a pseudopod correctly. However, in the presence of 10 mM extracellular Ca 2+ during cAMP-stimulation Ca 2+ -fluxes are enhanced allowing more efficient formation of pseudopods. We had shown previously that a small global elevation of [Ca 2+ ] i activates the extension of pseudopods all over the cell's circumference whereas a larger increase induces contraction of the amoebae [ 24 ]. In our view, the strongest evidence that a [Ca 2+ ] i -transient is necessary for the extension of pseudopods rests upon the experiment where a Ca 2+ -chelator was introduced into the cytosol of the amoebae. This treatment led to rounding of the amoebae and a general reduction of pseudopod formation (see also [ 5 ]). Upon stimulation with a cAMP-filled capillary, the extension of oriented pseudopods was greatly reduced and migration towards the capillary tip was abolished. As Speksnijder et al. [ 11 ] had pointed out the fact that the presence of a chelator has an effect shows that a [Ca 2+ ] i -gradient is essential for a given response. In summary, these data support the notion that an elevation of [Ca 2+ ] i is required to extend pseudopods; suppression of the [Ca 2+ ] i -elevation inhibits motility in general. Upon chemotactic challenge with cAMP this [Ca 2+ ] i -gradient has to be established in a locally restricted fashion in order to allow local, oriented pseudopod formation (see [ 2 , 25 , 26 ]); otherwise pseudopods would be extended in all directions (see above, [ 24 ]). Our results imply that in iplA - cells such a [Ca 2+ ] i -gradient occurs as well, either nonrestricted allowing extension of pseudopods at random sites during spontaneous motility or restricted locally after chemotactic stimulation leading to oriented pseudopod formation. The fact that in the mutant cell line cAMP-activated [Ca 2+ ] i -changes were practically undetectable under our standard condition argue for a [Ca 2+ ] i -increase that is either smaller and/or more restricted to distinct domains within the cell than in wild type amoebae. Indeed, in only one out of roughly 30 determinations did we observe a cAMP-activated [Ca 2+ ] i -transient under standard conditions. These results imply a crucial role but not an absolute necessity of the iplA gene product for the regulation of cAMP-induced [Ca 2+ ] i -changes. By using a Ca 2+ -sensitive electrode in cell suspensions, we analyzed which aspects of [Ca 2+ ] i are controlled by the iplA gene product. Besides studying agonist-induced Ca 2+ -fluxes we also investigated capacitative Ca 2+ -entry and found that this type of influx was similar in mutant and wild type cell suspensions. We obtained equivalent results by testing Mn 2+ -quenching of Fura2-dextran fluorescence which showed that capacitative entry is independent of the iplA gene product. On the other hand, using the Ca 2+ -sensitive electrode, we found that in the iplA - mutant the agonist cAMP and also AA did activate Ca 2+ -entry into intact cells. The difference between the data published by Traynor et al. [ 6 ] and our results is most likely due to the experimental conditions: the magnitude of the Ca 2+ -fluxes that we observed was considerably lower than in wild type cells and detectable at low extracellular [Ca 2+ ] only. The 45 Ca 2+ -flux studies had been performed at 100 μM external CaCl 2 ; so the fraction of 45 Ca 2+ entering the cells was presumably too low to be detected reliably. Moreover, we found cAMP- and AA-induced Ca 2+ -release from stores in cells with permeabilized plasma membranes. These data show that cAMP-induced Ca 2+ -release from stores in iplA - cells is functional. However, much like the Ca 2+ -influx, agonist-activated liberation from stores was smaller than in wild type amoebae. In line with these results are the findings using Mn 2+ -quenching to assay ion fluxes in intact single cells: higher doses of Mn 2+ were necessary to detect influx. There are several interpretations for the results above. (i) There are two types of channels responsible for Ca 2+ -influx: one type being activated by emptying of the stores and sustaining capacitative Ca 2+ -entry which is unaffected in iplA - cells and the other one mediating agonist-induced Ca 2+ -fluxes, the latter being under the control of the iplA gene product. The view that there are two strictly separated ion channels seems unlikely as under conditions of emptied stores cAMP-activated Mn 2+ -quenching occurred in the mutant as well. (ii) The same channel(s) mediate capacitative and agonist-activated fluxes but upon stimulation with agonists it cannot be addressed properly when iplA is disrupted. This implies a role of the protein in the liberation of Ca 2+ from the stores which is a prerequisite for the triggering of Ca 2+ -entry [ 12 ]. In the mutant this cannot proceed normally so subsequent activation of Ca 2+ -influx and the generation of a full [Ca 2+ ] i -increase is impaired. The results of the experiments where stores were strongly loaded with Ca 2+ prior to stimulation support this notion. In this situation release from stores should be augmented. Indeed, in both, wild type and mutant cells, cAMP-activated [Ca 2+ ] i -elevations occurred at an extracellular [Ca 2+ ] (see Fig. 12 ) where without pretreatment no increase was observed. Presumably, release of Ca 2+ from the filled stores contributed to the observed [Ca 2+ ] i -increase to a greater extent than under standard conditions. The requirement for 20 fold higher concentrations of CaCl 2 during preincubation to elicit an agonist-induced [Ca 2+ ] i -elevation in iplA - cells are most likely due to the reduction in Ca 2+ -entry which necessitates a higher concentration gradient across the plasma membrane to fill the stores efficiently. An as yet unresolved issue is the mechanism that induces Ca 2+ -entry upon liberation of Ca 2+ from the stores. From our data we conclude that in Dictyostelium these signals are different when the stores are emptied by EGTA or by agonist-activated signaling cascades. Otherwise one cannot explain normal capacitative Ca 2+ - and Mn 2+ -influx induced by EGTA-treatment and a requirement for 100 fold higher ion concentrations to induce Mn 2+ -entry by cAMP. If indeed the iplA gene product constitutes an IP 3 -receptor like channel that is located on membranes of stores the physical coupling of the receptor to channels in the plasma membrane as a mechanism to activate extracellular Ca 2+ -entry [ 27 ] should be missing in the mutant. On the other hand, emptying of stores by EGTA-treatment influences not only the IP 3 -sensitive store but also other stores and thus exerts a much more general effect on the cells. Studies using microarrays should reveal whether the expression of other genes is affected by the absence of iplA and thus might give a clue how [Ca 2+ ] i is regulated in the mutant although one type of Ca 2+ -store is malfunctional. Conclusion Our results show that Ca 2+ fluxes and regulation of Ca 2+ homeostasis take place in the iplA - mutant and that chemotaxis and development of the mutant are sensitive to disturbance of the Ca 2+ homeostasis. In wild type cells and in cells lacking the iplA gene changes in [Ca 2+ ] i are necessary to orient and to migrate chemotactically; their abolition causes loss of chemotaxis towards a cAMP source. The iplA gene product exerts a crucial role in the control of basal [Ca 2+ ] i and of agonist induced Ca 2+ -fluxes. It is not required to activate capacitative Ca 2+ -influx. Thus the mechanisms responsible for capacitative and agonist-activated Ca 2+ -fluxes are different. Methods Materials Fura2-dextran and Fura2 were purchased from MobiTec; cAMP was from Boehringer. Cell culture D. discoideum wild type strain Ax2 and the iplA - cell lines HM1049 and HM1038 (kindly provided by Dr. D. Traynor) were cultured as described [ 14 ] in the absence or presence of 10 μg/ml Blasticidin S, respectively. There was no difference between the two mutant strains with respect to the assays performed; therefore, results of measurements with either HM1038 or HM1049 are shown. Cells were washed by repeated centrifugation and resuspension in cold Sørensen phosphate buffer (17 mM Na + /K + -phosphate, pH 6.0). Amoebae were shaken at 2 × 10 7 cells/ml, 150 rpm and 23°C until use. The time, in hours, after induction of development is designated t x . [Ca 2+ ] e -electrode recordings [Ca 2+ ] e in cell suspensions was recorded as described elsewhere [ 14 ]. Cells at t 5 –t 8 were washed by repeated centrifugation and resupended at 5 × 10 7 cells/ml in 5 mM Tricine, 5 mM KCl, pH 7.0. Permeabilization was done by addition of filipin (15 μg/ml) to cell suspensions exactly as outlined in [ 15 ]. Capacitative Ca 2+ -influx was analyzed in cells with emptied storage compartments [ 12 ]: amoebae at t 2 –t 4 were incubated with 5 mM EGTA for 30 min before washing in the above buffer. [Ca 2+ ] i -determination and Mn 2+ -quenching experiments Cells were loaded with Fura2-dextran (5 mg/ml + 1 mM CaCl 2 ) at t 4 –t 5 as described [ 12 ]. Aliquots (2–5 μl) of washed cells in H5-buffer (5 mM Hepes, 5 mM KCl, pH 7.0) were placed on glass coverslips and incubated in a humid chamber. 10–15 min prior to the experiment, 85–88 μl of H5-buffer + 1 mM CaCl 2 were added. In a series of experiments to load stores, wild type and iplA - cells were incubated with 1 mM CaCl 2 for 4–5 h and with 20 mM CaCl 2 for 2–3 h, respectively. Then they were thoroughly washed exactly as described previously [ 12 ] and incubated either in H5-buffer supplemented with 1 μM CaCl 2 (wild type; free [Ca 2+ ] in the solution was measured to be 2–2.5 μM, see also [ 12 ]) or in H5-buffer +1 mM CaCl 2 ( iplA - ); final volume was 90 μl. Single cell [Ca 2+ ] i -imaging was performed at t 7 –t 8 as described [ 14 ]; stimulation was done by adding 10 μl of cAMP (10 μM). For Mn 2+ -quenching assays, washed cells were incubated in H5-buffer and challenged with Mn 2+ or Mn 2+ /cAMP. In order to study fluxes in cells with partially emptied internal storage compartments cells were preincubated with EGTA (10 μl of H5-buffer plus 0.1 mM EGTA for 1–2 h). 10–15 min prior to the experiment this solution was carefully removed and 100 μl of H5-buffer was added. This was repeated three times; final volume was 90 μl. Fluorescence quenching was measured at 360 nm excitation; influx rates are given as decrease of fluorescence units/sec. Measurement of Ca 2+ -fluxes in partially purified storage compartments Analysis of vesicular Ca 2+ -fluxes was done as described [ 8 ]. In brief, 3 ml of cells at t 1 –t 6 (2 × 10 8 cells/ml) in 20 mM Hepes, pH 7.2, were lysed by passage through Nuclepore filters. A final concentration of 3 % sucrose, 50 mM KCl, 1 mM MgCl 2 , 20 μg/ml leupeptin, 1 μg/μl aprotinin, 2.5 mM dithiothreitol and 1 μM microcystin were added; unbroken cells were removed by centrifugation at 3000 g for 5 min. The supernatant was centrifuged again at 12000 g for 20 min. The sediment (P) was resuspended in 1 ml of the above buffer. The rate of uptake and release was determined in the pellet and supernatant fraction by measuring the extravesicular [Ca 2+ ] with Fura2. Chemotaxis assays Cells were analyzed for chemotaxis towards a capillary filled with 0.1 mM cAMP [ 28 ]. 250 μl of 1 × 10 5 cells/ml in H5-buffer were pipetted onto a glass coverslip and allowed to settle for 60 min. Chemotaxis was recorded on a video recorder for 30–45 min. Chemotaxis was also assayed in the presence of EGTA or CaCl 2 ; then amoebae were incubated in the respective agents for 60 min before they were challenged with cAMP. Images were digitized and the behaviour of the cells was analyzed using a computer program written for this purpose. For determination of cell velocity, a square area of interest (AI) of variable size (usually roughly 1/3 of the area of the cell) was placed at the perimeter of the cell in the first image digitized at the beginning of the assay. In the next image (images were digitized at a 2–4 sec time interval) the program analyzed an area larger than the AI (this area was defined by adding a given number of pixels on each side of the AI) for a pattern that resembled that of the AI; when such a pattern was found then the AI was placed on this new spot. The difference between the position of the AI in the first image to that in the second image was expressed as a vector of a given length. The changes in cell shape during migration were compensated by updating the pattern within the AI for every consecutive image analyzed. Calibration of the system allowed to convert the sum of the vector lengths to the distance in μm that the cells had migrated at the end of the experiment and to calculate the velocity of the amoebae. To test the effect of the intracellular presence of a Ca 2+ -buffer on chemotaxis, cells were loaded with Fura2-dextran (5 mg/ml in the loading solution) by electroporation in the absence of added external Ca 2+ . The amount of indicator present in the cytosol is in the range of 2–5% of the concentration present during electroporation [ 29 ]. 20 min after loading, cells were stimulated for 3–4 min by placing the cAMP-filled glass capillary at a distance of 10–20 μm of the cells and the number of cells that extended oriented pseudopods and thus elongated towards the capillary tip within this time period was counted. We had shown previously that loading of amoebae with FITC-dextran as a control does not alter chemotaxis as compared to untreated cells [ 5 ]. Analysis of differentiation Time lapse recordings of the development of Ax2 and iplA - cells on 1.5 % agar in H5-buffer (H5-agar) were done by placing 4 × 10 6 cells each on one half of a petri dish (∅ 35 mm) at t 1 . The two populations were separated from each other by a thin plastic disc that had been inserted in the melted agar during cooling. Only after removal of fluid and slight drying of the plate the disc was removed which resulted in a thin rim separating the strains. Differentiation was recorded by capturing an image of the plate every 30 min using a stereo microscope (Stemi 2000, Zeiss) equipped with a CCD camera (AVT Horn) under the control of the AxioVision software package (Zeiss). In addition, development was assessed at various levels of extracellular CaCl 2 . Then H5-agar contained either 5–20 mM EGTA or 5–20 mM CaCl 2 . List of abbreviations Cytosolic free Ca 2+ concentration: [Ca 2+ ] i 2,5-di-(t-butyl)-1,4-hydroquinone: BHQ Arachidonic acid: AA Area of interest: AI Authors' contributions RS recorded extracellular [Ca 2+ ] in cell suspensions and participated in the design of the study. DFL participated in the recordings of extracellular [Ca 2+ ] and the design of the study. KBR analyzed chemotaxis and differentiation of wild type and mutant cells. KH performed [Ca 2+ ] i measurements. DM analyzed fluxes in partially purified storage compartments and was involved in the design of the study. CS participated in [Ca 2+ ] i measurements, did Mn 2+ -flux studies, participated in the design of the study and wrote the manuscript. Supplementary Material Additional File 1 Spontaneous cell motility of wild type and iplA - cells in H5-buffer. Images of cells at t 5 were captured every 15 sec for 20 min. Click here for file Additional File 2 Basal cell motility after preincubation of wild type and mutant amoebae with 10 mM EGTA for 60 min (t 4 –t 5 ). Images of cells at t 5 were captured every 15 sec for 20 min in the continued presence of EGTA. Cells were rounded and extended smaller pseudopods than under control conditions. Click here for file Additional File 3 Cell motility of wild type and mutant cells after preincubation with 10 mM CaCl 2 for 80 min (t 4 –t 5.3 ) is shown. Images of cells at t 5.3 were captured every 15 sec for 20 min in the continued presence of CaCl 2 . The behaviour of treated cells was not different from control amoebae. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC555532.xml |
551595 | Melanoma Inhibitory Activity (MIA) increases the invasiveness of pancreatic cancer cells | Background Melanoma inhibitory activity (MIA) is a small secreted protein that interacts with extracellular matrix proteins. Its over-expression promotes the metastatic behavior of malignant melanoma, thus making it a potential prognostic marker in this disease. In the present study, the expression and functional role of MIA was analyzed in pancreatic cancer by quantitative real-time PCR (QRT-PCR), immunohistochemistry, immunoblot analysis and ELISA. To determine the effects of MIA on tumor cell growth and invasion, MTT cell growth assays and modified Boyden chamber invasion assays were used. Results The mRNA expression of MIA was 42-fold increased in pancreatic cancers in comparison to normal pancreatic tissues (p < 0.01). In contrast, MIA serum levels were not significantly different between healthy donors and pancreatic cancer patients. In pancreatic tissues, MIA was predominantly localized in malignant cells and in tubular complexes of cancer specimens, whereas normal ductal cells, acinar cells and islets were devoid of MIA immunoreactivity. MIA significantly promoted the invasiveness of cultured pancreatic cancer cells without influencing cell proliferation. Conclusion MIA is over-expressed in pancreatic cancer and has the potential of promoting the invasiveness of pancreatic cancer cells. | Background Despite improvements in diagnosis and treatment, pancreatic cancer remains one of the most common causes of cancer-related deaths in the world [ 1 ]. One of the reasons for the dismal prognosis is the propensity of pancreatic cancer cells to invade surrounding tissues and to metastasize. Melanoma inhibitory activity (MIA) is a small secreted protein normally expressed in cartilage and also produced by malignant melanoma cells and to a lesser degree by breast, colon cancer, and glioblastoma cells [ 2 - 4 ]. The exact biological functions of MIA are still unclear, but recent evidence indicates an important role of MIA in tumor progression and metastasis. MIA has been shown to interact with the components of the extracellular matrix, such as fibronectin and laminin, possibly via the binding motif for integrins. For example, MIA inhibits the attachment of suspended melanoma cells to surfaces coated with laminin or fibronectin [ 5 ]. In addition, overexpression of MIA in melanoma cells induces an aggressive tumor type by enhancing the metastatic potential. It has been shown that there is a correlation between increased plasma levels of MIA and a more advanced metastatic disease state in malignant melanoma patients [ 6 ]. Previously, using DNA array technology, we have demonstrated an increase of MIA mRNA expression in pancreatic cancer in comparison with the normal pancreas [ 7 ]. In the present study, we have further investigated the expression and localization of MIA, and its functional role in pancreatic cancer. Results To quantify the mRNA expression of MIA in pancreatic tissues, QRT-PCR was performed using RNA from pancreatic cancer tissues (n = 23) and normal pancreatic tissue samples (n = 17). The analysis revealed a 42 ± 28-fold increase (p = 0.0013) of MIA mRNA levels in pancreatic cancer tissues compared to the normal pancreas (Fig. 1A ). To determine the exact localization of MIA in pancreatic tissues, immunostaining was carried out in 32 primary pancreatic cancers and in 17 normal pancreatic tissue samples. In the normal pancreas, MIA immunoreactivity was absent in ductal, acinar and islets cells, but was observed in the muscular layer of vessels (Fig. 2A–C ). In contrast, in pancreatic cancer tissues, MIA immunoreactivity was moderate in the cancer cells and in tubular complexes in CP-like lesions adjacent to the tumor mass (Fig. 2D–F ), and in blood vessels and nerve ganglia (Fig. 2G,H ). Further analysis to correlate different tumor stages and grades with MIA immunoreactivity in pancreatic cancer tissues was performed. No difference between tumor stages, grades and MIA immunostaining was observed. To ensure the specificity of the antibody used, a malignant melanoma metastasis to the peritoneum was also analyzed. Strong cytoplasmic MIA staining of the malignant melanoma cells but not the surrounding tissues could be detected (Fig. 2I ). Since a correlation between increased serum levels of MIA in malignant melanoma and more advanced metastatic disease has been reported previously, we next investigated MIA serum levels in pancreatic cancer patients and healthy donors. The mean values of MIA serum levels were 8.3 ± 3.56 ng/ml in pancreatic cancer patients (n = 50) and 8.82 ± 2.01 ng/ml in control subjects (n = 14) (n.s.) (Fig. 1B ). Further analysis revealed that there was also no significant difference between patient groups with different tumor stages or grades. Figure 1 MIA mRNA expression and serum levels. A: MIA mRNA values in normal pancreatic tissues and pancreatic ductal adenocarcinoma (cancer) tissues by real-time quantitative polymerase chain reaction, as described in the Methods section. Values were normalized to housekeeping genes (cyclophilin B and hypoxanthine guanine phosphoribosyltransferase). B: ELISA was carried out as described in the Methods section. Fifty pancreatic cancer sera samples and 14 healthy donor sera samples were analyzed. The horizontal lines represent the mean expression levels. Figure 2 Localization of MIA in pancreatic tissues. MIA localization in pancreatic tissues: immunohistochemistry using a MIA specific antibody was carried out as described in the Methods section. A-C: normal pancreatic tissues; D-H: pancreatic cancers; I: malignant melanoma metastasis to the peritoneum. Note that in melanoma metastasis the signal is red (using HistoMark Red phosphatase system) to differentiate the staining from the brown pigment in melanoma cells. To determine the functional role of MIA in pancreatic cancer, we first investigated MIA expression in pancreatic cell lines. QRT-PCR analysis revealed relatively high MIA mRNA levels in Mia PaCa-2, Panc-1, and SU8686 pancreatic cancer cells compared to the other cell lines (Fig. 3A ). Immunoblot analysis was employed to evaluate MIA protein levels in pancreatic cancer cell lines. This analysis revealed a band of 15 kDa corresponding to the known size of MIA in the control melanoma cell line B16 (B78/H1), whereas it was only weakly present in Mia Paca-2, Panc-1, and SU8686 pancreatic cancer cell lines, and below the level of detection in the other tested cell lines (Fig 3B ). To confirm the specificity of the signal, immunoprecipitation was performed. This demonstrated an immunospecific band at 15 kDa in B78/H1, Mia PaCa-2, and SU8686 cell lines (Fig. 3C ). Figure 3 Expression and effects of MIA in cultured pancreatic cancer cells. A: MIA mRNA levels in indicated pancreatic cancer cell lines were determined by real-time quantitative polymerase chain reaction, as described in the Methods section. Data are presented as median + SD of MIA mRNA copies per μl of input cDNA normalized to housekeeping genes CPB and HPRT. B: 30 μg protein lysates of the indicated cell lines were subjected to immunoblotting analysis using a specific MIA antibody, as described in the Methods section. C: Immunoprecipitation analysis was carried out as described in the Methods section. D: An in vitro cell invasion assay was performed using 8 μM filters coated with Matrigel, as described in the Methods section. 4 × 10 5 of the indicated pancreatic cancer cells were seeded onto the filters in 10% serum overnight, and then treated as indicated for 24 h. Invaded cells were stained and counted. The values shown are the mean ± SEM obtained from three independent experiments. In order to determine the effects of MIA on the proliferation of pancreatic cancer cells, MTT cell growth assays were performed next. This analysis revealed no significant effects of MIA on the proliferation of pancreatic cancer cells (data not shown). To analyze whether MIA may promote invasiveness of pancreatic cancer cells, Matrigel-based invasion assays using a modified Boyden chamber were carried out in T3M4 and Aspc-1 pancreatic cancer cell lines that exhibited relatively low MIA expression levels according to QRT-PCR and Western blot data. Added to the top chamber as described in Methods section, MIA significantly increased the invasion of Aspc-1 by 2.4-fold (p < 0.001) and the invasion of T3M4 by 3.1-fold (p < 0.0001) (Fig. 3D ). To investigate possible mechanisms of MIA overexpression in pancreatic cancer cells, we analyzed whether micro-environmental changes may modulate MIA expression. Neither TGF-β1 nor hypoxia was able to alter MIA mRNA expression, according to the QRT-PCR analysis of correspondingly treated pancreatic cancer cell lines (data not shown). Discussion One of the most devastating aspects of malignant growth is the emergence of cancer foci in organs distant from the primary tumor, with most cancer mortality being related to metastases. Thus, understanding the molecular mechanisms underlying the metastatic process is one of the most important issues in cancer research. Pancreatic cancer is characterized by aggressive local tumor growth and early systemic tumor spread [ 8 - 10 ]. Many factors are involved in transforming pancreatic cancer into a highly aggressive and metastatic disease, such as alterations in cell-cell interaction [ 11 ], deregulated expression of extracellular proteases [ 12 ], and metastasis-associated genes such as KAI-1, heparanase [ 13 , 14 ] and a number of other molecules. Another important aspect of the metastasis process is neo-angiogenesis. Angiogenesis itself encompasses a cascade of sequential processes emanating from microvascular endothelial cells, which are stimulated to proliferate, degrade the endothelial basement membranes of parental vessels, migrate, penetrate host stroma, and initiate a capillary sprout [ 15 ]. Numerous angiogenic factors are overexpressed in pancreatic cancer, including vascular endothelial growth factor (VEGF), bFGF, and angiogenin, as well as members of the TGF-β, and FGF gene families [ 16 - 20 ]. In order to migrate and metastasize, cancer cells have to overcome and move through natural barriers created by cell-cell and cell-extracellular matrix (ECM) adhesion structures. Any destruction in cell-cell and ECM networks will facilitate motility and allow the cancer cells to migrate and metastasize. The invasion and metastatic potential of cancer cells depends on their intrinsic properties and the host microenvironment [ 21 ]. Melanoma inhibitory activity (MIA) increases cell motility by decreasing the attachment of the cells to the extracellular matrix (ECM). Overexpression of MIA leads to increased metastasis of malignant melanoma cells by enhancing invasion and extravasation [ 22 , 23 ]. In the present study we show by QRT-PCR and immunohistochemistry that MIA is significantly over-expressed in pancreatic cancer in comparison with normal pancreatic tissues. These data are in agreement with findings in malignant melanoma and breast cancer, in which MIA is also highly expressed [ 6 , 24 , 25 ]. In contrast to observations in malignant melanoma, where MIA has been established as a reliable marker for prognosis [ 6 , 24 ], we could not detect either a significant difference of MIA serum levels between pancreatic cancer patients and donors or a significant difference between patients at different stages of pancreatic cancer. Therefore, MIA cannot serve as a diagnostic or prognostic marker in pancreatic cancer. The reason why high MIA mRNA levels lead to high serum levels in malignant melanoma, but not in pancreatic cancer, is currently not known. As to the possible role of MIA in pancreatic cancer pathogenesis, MIA had no effect on the proliferation of pancreatic cancer cells, similar to previous experiments employing fibroblasts, keratinocytes, endothelial cells and lymphocytes. The only cellular system in which MIA has been found to influence cell growth is melanoma cells; in these cells, MIA exerts anti-proliferative effects [ 26 ]. Although MIA did not affect the growth of pancreatic cancer cells in vitro, its impact on the invasion was striking. Interestingly, promotion of invasiveness of pancreatic cancer contrasts the previously demonstrated decrease in the invasion of MIA-treated malignant melanoma cells [ 26 ]. A possible explanation for this dissimilarity might be that MIA has no effect in detachment of pancreatic cancer cells from the ECM, like in malignant melanoma [ 26 ]. Alternatively, the status of MIA-interacting partners or downstream targets in the MIA signaling pathway may differ between pancreatic and melanoma cancer cells. So far, a possible correlation between MIA and other proteins known to be involved in pancreatic cancer metastasis – such as extracellular proteases, MMP, VEGF and bFGF – has not been studied. Therefore, the mechanism responsible for the invasion-promoting action of MIA requires further evaluation. Conclusion In conclusion, our study shows a striking overexpression of MIA in cancerous pancreatic tissues without consequent elevation of MIA in the circulation. Involvement of MIA in regulation of invasiveness of pancreatic cancer cells indicates that this protein may serve as a novel therapeutic target in the search for anti-metastatic drugs. Methods Patients and tissues Pancreatic cancer tissue samples were collected from 55 patients who underwent pancreatic cancer resection in the Department of General Surgery at the University of Heidelberg, Germany, and in the Department of Visceral and Transplantation Surgery at the University of Bern, Switzerland. Twelve cases were stage I, 13 cases stage II, 23 cases stage III, and 7 cases stage IV pancreatic adenocarcinomas, according to the Union International Contre Le Cancer (UICC) system. According to routine pathological grading, 16 cases were well-differentiated, 22 moderately differentiated, and 17 poorly differentiated. Normal pancreatic tissues were collected from 34 healthy organ donors. Pancreatic tissues were either frozen in liquid nitrogen and stored at -80°C (for RNA and protein extraction) or immediately fixed in 4% paraformaldehyde solution and subsequently embedded in paraffin. In order to determine MIA serum concentrations, sera from 50 pancreatic cancer patients (35 male, 15 female; median age 59 years; range 29–80 years) and healthy volunteers (14 male; median age 27 years; range 25–35 years) were collected at the Department of General Surgery, University of Heidelberg, Germany. Written informed consent was obtained from all patients. The study was approved by the Ethics Committees of the Universities of Bern, Switzerland, and Heidelberg, Germany. Cell lines and culture conditions Mia PaCa-2, T3M4, Aspc-1, Bxpc-3, Capan-1, Colo-357, SU8686 and Panc-1 pancreatic cancer cells and B16 (cloneB78/H1) mouse melanoma cells were grown in RPMI 1640 medium containing 10% FBS (fetal bovine serum), 100 U/ml penicillin and 100 μg/ml streptomycin (Invitrogen, Karlsruhe, Germany). Cells were maintained in a 37°C humidified atmosphere saturated with 5% CO 2 . For TGF-β1 induction experiments, pancreatic cancer cells were seeded in 10 cm dishes in 10% FBS growth medium and allowed to attach for 12 hrs. Growth medium was replaced by serum-reduced medium (0.5% FBS), supplemented with 200 pM TGF-β1 for the indicated time periods. For experimental hypoxia, cells were subjected to a hypoxic microenvironment by one hour-long flushing in a special incubator chamber with an anoxic gas mixture (89.25% N 2 , 10% CO 2, 0.75%O 2 ) and sealing of the unit. Real-time quantitative polymerase chain reaction (QRT-PCR) All reagents and equipment for mRNA/cDNA preparation were purchased from Roche Applied Science (Mannheim, Germany). mRNA was prepared by automated isolation using MagNA Pure LC instrument and isolation kits I (for cells) and II (for tissue). cDNA was prepared using a 1st strand cDNA synthesis kit for RT-PCR according to the manufacturer's instructions. Real-time PCR was performed with the Light Cycler Fast Start DNA SYBR Green kit [ 27 ]. The number of specific transcripts was normalized to housekeeping genes (cyclophilin B and hypoxanthine guanine phosphoribosyltransferase, HPRT). All primers were obtained from Search-LC (Heidelberg, Germany). Immunohistochemistry Briefly, consecutive paraffin-embedded tissue sections (5 μm thick) were deparaffinized and rehydrated. Antigen retrieval was performed by pretreatment of the slides in citrate buffer (pH 6.0) in a microwave oven for 10 min. Thereafter, slides were cooled to room temperature in deionized water for 5 min. After blocking of endogenous peroxidase activity with 0.3% hydrogen peroxide and washing in deionized water 3 times for 10 min, the sections were blocked for 1 h at room temperature with normal rabbit serum (DAKO, Hamburg, Germany), then incubated with primary goat polyclonal anti-MIA antibody (A-20, Santa Cruz Biotechnology, Santa Cruz, CA; dilution 1:35 in normal rabbit serum) overnight at 4°C. The slides were rinsed with washing buffer (Tris-buffered saline with 0.1% BSA) and incubated with secondary rabbit anti-goat HRPO-labeled IgG (Sigma-Aldrich, Taufkirchen, Germany), diluted 1:200 for 45 min at room temperature. After color reaction, tissues were counterstained with Mayer's hematoxylin. For negative control, appropriately diluted goat IgG was used instead of the primary antibody. Enzyme-linked immunosorbent assay (ELISA) The amount of secreted MIA protein in cell culture supernatants and serum samples was determined using a one-step MIA ELISA (Roche Diagnostic GmbH, Mannheim, Germany) according to the manufacturer's instructions. Immunoblot Cells were washed with ice-cold PBS and collected in lysis buffer (50 mM Tris-HCl, 100 mM NaCl, 2 mM EDTA, 1% SDS) containing the Complete mini-EDTA-free protease inhibitor cocktail tablets from Roche (Roche Applied Science, Mannheim, Germany). Lysates were centrifuged at 13,000 rpm at 4°C for 30 min, the supernatants were collected, and protein concentrations were measured with the BCA protein assay (Pierce Chemical Co., Rockford, IL, USA) using BSA as protein standard. 20 μg of protein were mixed with loading buffer, heated at 95°C for 5 min, separated on 12% SDS polyacrylamide gels, and transferred onto nitrocellulose membrane at 100 V for 90 min. Membranes were blocked in 5% non-fat milk in TBS-T (20 mM Tris-HCl, 150 mM NaCl, 0.1% Tween-20) for 1 h, incubated overnight at 4°C with anti-MIA antibody (A-20, Santa Cruz) and exposed to secondary HRPO-labeled donkey anti-goat antibody (Santa Cruz) for 1 h at room temperature. The signal detection was performed using the ECL system (Amersham Life Science, Amersham, UK). Immunoprecipitation For immunoprecipitation, pancreatic cell lines (Mia PaCa-2 and SU8686) were suspended in lysis buffer (50 mM Tris, 150 mM NaCl, 1% Triton X-100, 25 mM NaF, 10% glycerol, 1 mM PMSF) supplemented with the Complete-TM mixture of proteinase inhibitors (Roche Diagnostic, Mannheim, Germany) and incubated for 30 min on ice. After centrifugation, the supernatant was transferred into a fresh vial, pre-cleared with protein A-Sepharose beads (Santa Cruz) and incubated with 50 μl anti-MIA antibody (A-20, Santa Cruz) overnight at 4°C. Following addition of 30 μl of protein A-Sepharose for 1 h at 4°C, the mixture was pelleted, washed three times with lysis buffer, and resuspended in Laemmli sample buffer. MTT cell growth assays Cell growth experiments were performed using the 3-(4, 5-methylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. Pancreatic cancer cells were seeded at a density of 5000 cells/well in 96-well plates, grown overnight, and then exposed to different concentrations of recombinant MIA protein as indicated. After 24 h, MTT was added (50 μg/well) for 4 hours. Formazan products were solubilized with acidic isopropanol, and the optical density was measured at 570 nm. Invasion assays Invasion assays were performed in a BD Biocoat Matrigel Invasion Chamber with 8-μm pore size (BD Biosciences, Heidelberg, Germany) according to the manufacturer's instructions. The Matrigel was rehydrated with 500 μl DMEM (serum-free) and incubated in a 37°C, 5% CO2 atmosphere for 2 h. 5 × 10 4 cells were incubated for 24 h and subsequently treated with MIA (100 ng/ml) [ 26 ], which was added to the top chamber and incubated for 24 h. The non-invading cells were removed from the upper surface of the membrane with cotton-tipped swabs. Cells adhering to the lower surface were fixed with 75% methanol mixed with 25% acetone and stained with 1% toluidine blue (Sigma-Aldrich, Taufkirchen, Germany). The whole membrane was scanned using the software of the Zeiss KS300 and Zeiss AxioCam HR system (Jena, Germany). To calculate the total number of all invading cells, the cells were counted in every cut-out of the mosaic image of the whole membrane using the same software. The assays were performed in duplicate and repeated three times. Competing interests The author(s) declare that they have no competing interests. Authors' contribution JEF, NG, and AG carried out all the experiments, and participated in data analysis and interpretation. JK, MWB, and HF conceived of the study, and participated in its design and coordination. JK, NG, and AKB analyzed and interpreted the data and drafted the manuscript. All authors read and approved the final version. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC551595.xml |
538251 | The use of microbubbles to target drug delivery | Ultrasound-mediated microbubbles destruction has been proposed as an innovative method for noninvasive delivering of drugs and genes to different tissues. Microbubbles are used to carry a drug or gene until a specific area of interest is reached, and then ultrasound is used to burst the microbubbles, causing site-specific delivery of the bioactive materials. Furthermore, the ability of albumin-coated microbubbles to adhere to vascular regions with glycocalix damage or endothelial dysfunction is another possible mechanism to deliver drugs even in the absence of ultrasound. This review focuses on the characteristics of microbubbles that give them therapeutic properties and some important aspects of ultrasound parameters that are known to influence microbubble-mediated drug delivery. In addition, current studies involving this novel therapeutical application of microbubbles will be discussed. | Introduction The recent advances in gene therapy and molecular biology have improved the interest in methods of noninvasive delivery of therapeutic agents. Besides the well known application of microbubbles as contrast agents for diagnostic ultrasound, microbubbles have also been demonstrated an effective technique for targeted delivery of drugs and genes [ 1 - 6 ]. Drugs can be incorporated into the microbubbles in a number of different ways, including binding of the drug to the microbubble shell and attachment of site-specific ligands. As perfluorocarbon-filled microbubbles are sufficiently stable for circulating in the vasculature as blood pool agents, they act as carriers of these agents until the site of interest is reached. Ultrasound applied over the skin surface can then be used to burst the microbubbles at this site, causing localized release of the drug [ 7 - 10 ]. This technique then permits using lower concentrations of drugs systemically, and concentration of the drug only where it is needed. This improved therapeutic index may be extremely advantageous in cases of drugs with hazardous systemic side effects, like cytotoxic agents. Albumin-encapsulated microbubbles have also demonstrated to adhere to the vessel walls in the setting of endothelial dysfunction [ 11 ]. This also may be a method of targeting delivery with microbubbles but without the application of ultrasound. Mechanisms for Target Drug Delivery Using Microbubbles Two possible strategies for delivering drugs and genes with microbubbles are emerging. The first consists on the ultrasound-mediated microbubble destruction, which is based on the cavitation of microbubbles induced by ultrasound application, and the second is the direct delivery of substances bound to microbubbles in the absence of ultrasound. Different drugs and genes can be incorporated into the ultrasound contrast agents. It has already been demonstrated that perfluorocarbon-filled albumin microbubbles avidly bind proteins and synthetic oligonucleotides [ 12 ]. In a similar way, microbubbles can directly take up genetic material, such as plasmids and adenovirus [ 12 , 13 ], and phospholipid-coated microbubbles have a high affinity for chemotherapeutic drugs [ 14 ]. Furthermore, specific ligands for endothelial cell adhesion molecules, such as P-selectin and leukocyte intercellular adhesion molecule 1 (ICAM-1), can be attached to both lipid- and albumin-encapsulated microbubbles, which increases their deposition to activated endothelium [ 15 , 16 ]. The mechanisms by which ultrasound facilitates the delivery of drugs and genes result from a complex interplay among the therapeutic agent, the microbubble characteristics, the target tissue, and the nature of ultrasound energy. The presence of microbubbles in the insonified field reduces the peak negative pressure needed to enhance drug delivery with ultrasound. This occurs because the microbubbles act as nuclei for cavitation, decreasing the threshold of ultrasound energy necessary to cause this phenomenon. The results of optical and acoustical studies have suggested the following mechanisms for microbubble destruction by ultrasound: 1- gradual diffusion of gas at low acoustic power, 2- formation of a shell defect with diffusion of gas, 3- immediate expulsion of the microbubble shell at high acoustic power, and 4- dispersion of the microbubble into several smaller bubbles. Cavitation of the bubbles is characterized by rapid destruction of contrast agents due to a hydrodynamic instability excited during large amplitude oscillations, and is directly dependent on the transmission pressure [ 17 , 18 ]. It has been reported that the application of ultrasound to contrast agents creates extravasation points in skeletal muscle capillaries [ 2 , 19 ], and this phenomenon is dependent on the applied ultrasound power. High intensity ultrasound (referred to as a high mechanical index) can rupture capillary vessels, resulting in deposit of protein and genetic material into the tissues. Skyba et al [ 1 ] demonstrated in an exteriorized spinotrapezius preparation that ultrasonic destruction of gas-filled microbubbles caused rupture of microvessels with diameter ≤ 7 μm (capillaries), with local extravasation of red blood cells. Price et al [ 2 ] have shown that polymer microspheres could be driven as much as 200 μm into the parenchyma with this method. The authors calculated that only a small number of capillary ruptures were required to deliver large quantities of the colloidal particles to the muscle. Using the same model of polymer microspheres bound to microbubbles and ultrasound, it has also been demonstrated that the ultrasound pulse interval and microvascular pressure influence the creation of extravasation points and the transport of microspheres to the tissue. Both were greatest when the pulse interval was around 5 seconds, which allows maximal microbubble replenishment within the microcirculation after destruction by the ultrasound pulse [ 19 ]. The formation of pores in the membranes of cells as a result of ultrasound-induced microbubble cavitation has been proposed as a mechanism for facilitating the drug deposition. Taniyama et al [ 7 ] demonstrated the presence of small holes in the surface of endothelial and vascular smooth muscle cells immediately after transfection of a plasmid DNA by ultrasound-mediated microbubble destruction, using electron microscopic scanning. It was then postulated that these transient holes in the cell surface caused by microbubbles and ultrasound resulted in a rapid translocation of plasmid DNA from outside to cytoplasm. Mukherjee et al [ 10 ] demonstrated by electron microscopy of a rat heart performed during application of ultrasound, that disruption or pore formation of the membrane of the endothelial cells occurred with acoustic power of 0.8 to 1.0 W/cm 2 . However, it was a lower intensity of ultrasound (0.6 W/cm 2 ) that caused more drug delivery with microbubbles. More recently, voltage clamp techniques were used to obtain real-time measurements of membrane sonoporation in the presence of albumin-coated microbubbles (Optison). Ultrasound increased the transmembrane current as a direct result of membrane resistance due to pore formation [ 20 ]. Another important therapeutic property of microbubbles is their increased adherence to damaged vascular endothelium. Albumin-coated microbubbles do not adhere to normally functioning endothelium, but their adherence does occur to activated endothelial cells or to extra-cellular matrix of the disrupted vascular wall, and this interaction could be a marker of endothelial integrity [ 11 ]. Because of this characteristic, the delivery of drugs or genes bound to albumin-coated microbubbles could be selectively concentrated at the site of vascular injury in the presence [ 21 ] or absence of ultrasound application [ 22 ]. Microbubbles Use for Gene Therapy The clinical use of viral vectors for gene therapy is limited because viral proteins elicit an immune response within the target tissue [ 23 ], and have been shown to cause an intense inflammatory activation of endothelial cells [ 24 ]. On the other hand, the nonviral delivery of vehicles, such as plasmids and antisense oligonucleotides, has been associated with a lower transfection efficiency and transient expression of the gene product [ 25 ]. The first published report of targeted DNA delivery was performed in 1996, using surface ultrasound and intravenously delivered microbubbles carrying antisense oligonucleotides [ 3 ]. In 1997, Bao et al [ 26 ] described the use of ultrasound and albumin-coated microbubbles to enhance the transfection of luciferase reporter plasmid in cultured hamster cells. Since then, many studies have confirmed the efficacy of ultrasound-mediated microbubble destruction for drug and gene delivery, both in vitro and in vivo [ 3 , 7 - 9 ]. Shohet et al [ 9 ] demonstrated for the first time with an adenovirus vector that the ultrasound-mediated disruption of gas-filled microbubbles could be used to direct transgene expression to the heart in vivo. They showed that intravenously injected recombinant adenovirus vectors encoding a beta-galactosidase reporter gene were successfully delivered to normal rat myocardium using microbubbles and transthoracic 1.3 MHz diagnostic ultrasound, at a mechanical index of 1.5, delivered at a burst of 3 frames of ultrasound every 4 to 6 cardiac cycles. Of note, transfection was not observed if the adenovirus was administered in the same dose without microbubbles, or if the adenovirus was administered with microbubbles but in the absence of ultrasound. Importantly, using the same model the authors confirmed that plasmid transgene expression can be directed to the heart, with an even higher specificity than viral vectors, and that this expression can be regulated by repeated treatments [ 27 ]. Taniyama et al [ 7 ] have also shown effective transfection of a plasmid DNA to endothelial and vascular smooth muscle cells with albumin-coated microbubbles (Optison) and ultrasound. In vivo studies demonstrated that transfection of wild-type p53 plasmid DNA into balloon-injured blood vessels was effective and resulted in significant inhibition of the ratio of neointimal-to-medial area, as compared with transfection of control vector. In contrast, transfection of p53 plasmid DNA by means of ultrasound without microbubbles failed to inhibit neointimal formation in the rat carotid [ 7 ]. In a recent study, Teupe et al [ 28 ] have documented efficient transfer of plasmids encoding either beta-galactosidase or endothelial nitric oxide synthase to the endothelial cells of conductance arteries with preservation of the functional integrity of the transfected endothelial cell layer after ultrasound treatment. Other Potential Therapeutic Applications of Microbubble Target Drug Delivery Restenosis after vascular balloon injury or stent deployment has been shown to result from neointimal hyperplasia due to smooth muscle cell migration and proliferation. The c- myc protooncogene is responsible for the regulation of gene expression involved in the process of intimal hyperplasia that leads to restenosis. Synthetic antisense oligonucleotides, such as those to the c- myc protooncogene, can bind to the messenger ribonucleic acid and inhibit the synthesis of the protooncogenes. Therefore, antisense to c- myc protooncogene can prevent its translation into proteins that may be mediators of the pathologic process of restenosis. These synthetic agents, when administered directly into the vessel, have successfully inhibited restenosis after coronary or carotid injury [ 29 ]. In 1996 Porter et al [ 3 ] demonstrated that perfluorocarbon-exposed sonicated dextrose albumin (PESDA) microbubbles, unlike room air-containing sonicated dextrose albumin microbubbles, have bioactive albumin on their surface that can avidly bind synthetic antisense oligonucleotides, and then release them in the presence of ultrasound. In the initial study that examined the effectiveness of PESDA and ultrasound in enhancing the delivery of the antisense to c- myc , 21 pigs had carotid balloon injury performed with an oversized balloon catheter and were randomized to receive intravenous antisense to c- myc bound to PESDA, intravenous antisense alone, or no treatment. The pigs that received antisense bound to PESDA also had transcutaneous 20 kHz ultrasound applied over the carotid wall following injections. The ultrasound targeted group showed a significantly lower percent area stenosis (8 ± 2%) than the two control groups (19 ± 8% and 28 ± 3%; p < 0.01) [ 21 ]. Since PESDA microbubbles adhere to sites of endothelial injury even in the absence of ultrasound, the efficacy of this therapy in inhibiting coronary restenosis has been evaluated in animals. Porter et al [ 22 ] measured the uptake of antisense to c- myc into coronary arteries using high phase liquid chromatography in pigs. Intravenous PESDA containing anti c- myc was given in the presence or absence of transthoracic 1 MHz ultrasound (0.6 W/cm 2 ). In this study, the authors demonstrated that anti c-myc can be selectively concentrated within a stretch-injured coronary artery segment when given intravenously bound to PESDA. The decrease in neointimal formation following intravenous injection of anti c-myc with PESDA without ultrasound was similar to that observed with higher doses of the same antisense given directly into the coronary artery using an infiltrator delivery system [ 30 ]. The basis for this hypothesis stems from previous observations that albumin-coated microbubbles adhere to activated endothelial cells [ 11 , 21 , 31 ]. Albumin-coated microbubbles have been observed binding to activated leukocytes and monocytes which slowly roll along injured venular endothelial cells [ 11 ]. Since leukocyte and monocyte accumulation has also been observed early following arterial balloon injury [ 32 ], it is possible that PESDA microbubbles were concentrated at the injured coronary artery surface by adherence to these activated cells. Other potential mechanisms could be related to complement activation, since both albumin- and lipid-encapsulated microbubbles take up complement proteins [ 33 ], and thus may bind to upregulated complement receptors at the injured surface. It was recently demonstrated that albumin-coated microbubbles adhere to sites of arterial endothelial dysfunction induced by balloon-injury of carotid arteries [ 34 ]. Figure 2 illustrates an example of microbubble binding to the endothelium of an injured carotid artery, which was confirmed by scanning electron microscopy. Lu et al [ 35 ] have also shown that albumin-coated microbubbles significantly improved transgene expression in skeletal muscle of mice, even in the absence of ultrasound. However, in this study, the delivery was an intramuscular injection of microbubbles and plasmid into otherwise normal tissue, and not in the setting of endothelial injury [ 35 ]. Figure 2 Ultrasound images with low mechanical index pulse sequence scheme showing the presence of microbubbles binding to the arterial endothelium in a balloon-injured carotid artery (Panel A , right) and the absence of microbubbles in the control noninjured carotid artery (Panel B , right). Scanning electron microscopy (Bar = 10 μm; magnification 1420 ×) revealed sites of injury with endothelial denudation and attachment of microbubbles (black arrows) to the denuded endothelium only in the injured vessel (A) and normal appearing endothelium in the control vessel (B) . (Reprinted with permission from Tsutsui JM, Xie F, Radio SJ, Phillips P, Chomas J, Lof J et al. Non-invasive detection of carotid artery endothelial dysfunction due to hypertriglyceridemia and balloon injury with high frequency real time low mechanical index imaging of retained microbubbles . J Am Coll Cardiol 2004; 44 :1036-46). Another innovative application of microbubbles and ultrasound is in the delivery of proteins that induce growth of endothelial cells, such as vascular endothelial growth factor (VEGF). Mukherjee et al [ 10 ] demonstrated a marked increase in endothelial VEGF uptake using ultrasound alone (eight-fold increase) and using ultrasound and PESDA (ten- to thirteen-fold increase, as compared to control) in the myocardium of rats. In a canine model of chronic myocardial ischemia, intravenous infusion of VEGF combined with ultrasound and an albumin-based contrast agent significantly reduced the infarct area/risk area ratio, and increased myocardial blood flow in the ischemic territory, suggesting a new potential therapeutic approach for angiogenesis [ 36 ]. Optimization of Ultrasound Parameters for Cardiac Drug and Gene Delivery The effect of several ultrasound parameters, including transducer frequency and acoustic power, are known to influence microbubble destruction and, thus, the transfection of genes and drugs. Although the optimal ultrasound parameters for maximizing this process are not known, we will briefly discuss some important aspects. Unger et al [ 6 ] have shown that the type of ultrasound used to destroy phospholipid-coated microbubbles may regulate how much drug is released in vitro. When analyzing the number of acoustically active particles that persist after exposure to different types of ultrasound in a flow chamber, they demonstrated that a 2.5 MHz transducer resulted in some destruction, but the addition of a lower-frequency transducer (100 kHz) significantly increased the destruction. When the 100 kHz energy was given in a pulsed-wave mode as opposed to a continuous wave, the destruction of microbubbles was even faster. In a similar way, Porter et al [ 21 ] have demonstrated that a continuous wave diagnostic ultrasound frequency of 2 MHz was not able to enhance the carotid uptake of antisense to c- myc protooncogene (0.19 ± 0.04 μg/mg), but low-frequency 20 kHz ultrasound significantly increased vascular uptake (0.28 ± 0.04 μg/mg; p = 0.008 vs other groups) when compared to antisense bound to PESDA alone (0.21 ± 0.06 μg/mg). The results of this study suggested that a lower frequency could be better suited to target antisense deposition into major vessels. Because there were minimal differences in peak negative pressure generated by 2 MHz and 20 kHz in this study (46 kPa and 13 kPa, respectively), the enhanced uptake was attributed to a lower threshold for cavitation with 20 kHz ultrasound frequency. In another study, the efficacy of ultrasound-mediated delivery of VEGF bound to PESDA into the myocardium of rats was evaluated with an ultrasound frequency of 1.0 MHz at various acoustical outputs (0.2, 0.4, 0.6, 0.8 and 1.0 W/cm 2 ). The authors found a significant increase in VEGF uptake with the combination of ultrasound and PESDA at all power outputs when compared with controls, but there was a dose-dependent increase in the amount of VEGF uptake with increasing power until 0.6 W/cm 2 and a subsequent plateau. Table 1 illustrates some parameters used in previous studies for drug and gene delivery. It seems that at higher frequencies, higher peak negative pressures are necessary to induce cavitation-mediated drug and gene delivery using microbubbles and ultrasound. In a recent study of Chen et al [ 8 ] it was shown that, when using ultrasound at diagnostic frequencies, optimal ultrasound parameters for gene expression by ultrasound-targeted microbubble destruction to the myocardial microcirculation included a low-transmission frequency (1.3 MHz), high mechanical index, and electrocardiogram triggering to allow complete filling of the myocardial capillary bed by microbubbles. The authors found that maximal acoustic pressure resulted in higher myocardial gene expression, providing indirect evidence that high peak negative pressures increase the amount of gene delivery from microbubbles. Furthermore, the optimal ultrasound parameters for targeted delivery may be dependent on the desired site for delivery. While a triggered mechanism of once every four to five seconds may work for delivering drugs by ultrasound-mediated destruction of microbubbles in the myocardial microcirculation, a more frequent pulsed delivery may be required for vascular delivery. Table 1 Ultrasound parameters and microbubbles used for delivering genes and drugs. Author Transfection Transducer frequency Delivery mode Delivery site Output Peak negative pressure Microbubble Efficacy Porter TR, et al 1 Antisense c- myc protooncogene 1 MHz PW Coronary arteries 0.6 W/cm 2 PESDA + Zhou Z, et al 2 VEGF 1 MHz CW Myocardium 1.2 W/cm 2 Sonazoid + Taniyama Y, et al 3 Luciferase Carotid artery 2.5 W/cm 2 Optison + Teupe C, et al 4 β-galactosidase/ eNOS 2.2–4.4 MHz CW Coronary arteries Gas-filled albumin microbubble + Porter TR, et al 5 Antisense c- myc protooncogene 2 MHz CW Carotid artery 13 kPa PESDA - 20 kHz CW Carotid artery 46 kPa PESDA + Mukherjee D, et al 6 VEGF 1.0 MHz CW Myocardium 0.2 W/cm 2 0.164 MPa PESDA 9.37 ± 1.98* 1.0 MHz CW Myocardium 0.4 W/cm 2 0.194 MPa PESDA 18.58 ± 2.46* 1.0 MHz CW Myocardium 0.6 W/cm 2 0.328 MPa PESDA 23.12 ± 3.95* 1.0 MHz CW Myocardium 0.8 W/cm 2 0.394 MPa PESDA 25.46 ± 2.78* 1.0 MHz CW Myocardium 1.0 W/cm 2 0.419 MPa PESDA 26.48 ± 3.98* Shohet RV, et al 7 β-galactosidase 1.3 MHz ECG-triggered Myocardium Perfluorocarbon-filled microbubbles + Bao S, et al 8 Luciferase 2.25 MHz Cultured cells 0.2–0.4 MPa Albunex + * Efficacy is demonstrated as mean ± SD endothelial vascular growth factor uptake by enzyme-linked immunosorbent assay. CW = continuous wave; ECG = electrocardiogram; eNOS = endothelial nitric oxide synthase; PESDA = perfluorocarbon-exposed sonicated dextrose and albumin; PW = pulsed wave; VEGF = vascular endothelial growth factor. However, a high peak negative pressure may have detrimental bioeffects. Several investigators have reported on the occurrence of tissue hemorrhage and endothelial cell damage after ultrasound exposure of cultured cells and organs containing air, such as the lungs or the intestine [ 37 - 39 ]. Ay et al [ 38 ] examined the functional and morphological effects of ultrasound and contrast in an isolated rabbit heart preparation, using increasing levels of acoustic energy. Simultaneous exposure to contrast and high-energy ultrasound resulted in a reversible and transient decrease in left ventricular contractile performance, increase in the coronary perfusion pressure, increase in the myocardial lactate release, and presence intramural hemorrhage in the plane of ultrasound transmission. Additionally, light microscopy revealed the presence of capillary ruptures, erythrocyte extravasation and endothelial cell damage. These effects were directly related to the mechanical index. These studies indicate that although high-energy ultrasound seems to be necessary to induce tissue permeability facilitating local drug delivery, it may also have significant bioeffects in the myocardium. Therefore, the optimal ultrasound parameters to enhance drug delivery with microbubbles remain to be determined. Competing interests Dr. Jeane M. Tsutsui – declares no competing interests. Dr. Feng Xie – declares no competing interests. Dr. Thomas R. Porter – declares ImaRx Therapeutics, Inc.: Grant support and Consultant; Bristol Myers Squibb Medical Imaging: Grant support; AVI BioPharma, Inc.: Grant support Figure 1 Intravascular ultrasound examples of the proximal reference site and balloon injury site 30 days after the angioplasty. Note that there was both greater intimal thickening (arrows) in the vessel treated with intravenous antisense alone, and a reduction in lumen size when compared to the proximal reference segment. The balloon injury site of the vessel treated with intravenous antisense plus PESDA and 20 kHz transcutaneous ultrasound did not exhibit any reduction in lumen area or visually evident plaque. (Reprinted with permission from Porter TR, Hiser WL, Kricsfeld D, Deligonul U, Xie F, Iversen P et al: Inhibition of carotid artery neointimal formation with intravenous microbubbles . Ultrasound Med Biol 2001, 27 :259-265). | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538251.xml |
521072 | Heme oxygenase-2 gene deletion attenuates oxidative stress in neurons exposed to extracellular hemin | Background Hemin, the oxidized form of heme, accumulates in intracranial hematomas and is a potent oxidant. Growing evidence suggests that it contributes to delayed injury to surrounding tissue, and that this process is affected by the heme oxygenase enzymes. In a prior study, heme oxygenase-2 gene deletion increased the vulnerability of cultured cortical astrocytes to hemin. The present study tested the effect of HO-2 gene deletion on protein oxidation, reactive oxygen species formation, and cell viability after mixed cortical neuron/astrocyte cultures were incubated with neurotoxic concentrations of hemin. Results Continuous exposure of wild-type cultures to 1–10 μM hemin for 14 h produced concentration-dependent neuronal death, as detected by both LDH release and fluorescence intensity after propidium iodide staining, with an EC 50 of 1–2 μM; astrocytes were not injured by these low hemin concentrations. Cell death was consistently reduced by at least 60% in knockout cultures. Exposure to hemin for 4 hours, a time point that preceded cell lysis, increased protein oxidation in wild-type cultures, as detected by staining of immunoblots for protein carbonyl groups. At 10 μM hemin, carbonylation was increased 2.3-fold compared with control sister cultures subjected to medium exchanges only; this effect was reduced by about two-thirds in knockout cultures. Cellular reactive oxygen species, detected by fluorescence intensity after dihydrorhodamine 123 (DHR) staining, was markedly increased by hemin in wild-type cultures and was localized to neuronal cell bodies and processes. In contrast, DHR fluorescence intensity in knockout cultures did not differ from that of sham-washed controls. Neuronal death in wild-type cultures was almost completely prevented by the lipid-soluble iron chelator phenanthroline; deferoxamine had a weaker but significant effect. Conclusions These results suggest that HO-2 gene deletion protects neurons in mixed neuron-astrocyte cultures from heme-mediated oxidative injury. Selective inhibition of neuronal HO-2 may have a beneficial effect after CNS hemorrhage. | Background Hemin is a potent oxidant that accumulates in intracranial hematomas and may contribute to neural cell injury [ 1 , 2 ]. It is also the preferred substrate for heme oxygenase-2, the constitutively-expressed isoform that accounts for most CNS heme oxygenase (HO) under normal conditions [ 3 ]. In pathologic states, HO frequently has an antioxidant effect, putatively due to the protection provided by increased cellular bilirubin, decreased heme, and up-regulation of other antioxidants [ 4 - 7 ]. However, in models that are relevant to CNS hemorrhage, HO inhibitors have surprisingly been found to be protective [ 8 - 10 ]. All HO inhibitors that are currently available have numerous non-specific actions that may complicate the interpretation of experimental results, including inhibition of nitric oxide synthase and guanyl cyclase, and modification of voltage-gated calcium currents [ 11 - 14 ]. Some may also have a direct antioxidant effect that is unrelated to HO inhibition [ 15 ]. In order to investigate HO-2 in heme-mediated injury more specifically, we have cultured neurons and astrocytes derived from HO-2 knockout mice and genetically-similar wild type controls. In recent studies, we observed that astrocytes derived from mutant mice were more vulnerable to hemin [ 16 ]. Conversely, HO-2 gene deletion decreased the vulnerability of neurons to hemoglobin [ 17 ]. Neither wild type nor knockout astrocytes were injured by hemoglobin at the micromolar concentrations that are feasible in vitro. HO-2 gene deletion per se did not result in a compensatory increase in HO-1 in these cultures, and produced minimal or no change in other cellular antioxidants [ 16 , 17 ]. The disparate effects of HO-2 gene deletion on hemin toxicity to astrocytes and hemoglobin toxicity to neurons may reflect the inability of neurons to tolerate the products of heme metabolism, i.e. iron, carbon monoxide, and bilirubin. Alternatively, it may reflect the different oxidant properties of hemin and hemoglobin. Although the oxidant effect of hemoglobin may be due in part to hemin release to membrane lipids [ 18 ], other mechanisms may also contribute. Extracellular hemoglobin undergoes autoxidation, which produces superoxide [ 19 ]. In addition to being an oxidant, superoxide reacts with globin amino acids in a complex fashion to generate a variety of reactive species, including thiyl radicals, hydroxyl radicals, and hydrogen peroxide [ 20 , 21 ]. It is also noteworthy that hemoglobin is highly water soluble while hemin is quite lipophilic; their accumulation in separate cellular compartments may lead to a different pattern of site-specific oxidative damage [ 22 , 23 ]. The present study was designed to test the effect of HO-2 gene deletion on the oxidative neuronal injury produced by extracellular hemin. We specifically tested the hypothesis that targeted deletion of the HO-2 gene attenuated oxidative cell injury in a primary cell culture model of hemin toxicity. Results Effect of HO-2 gene deletion on hemin neurotoxicity In preliminary experiments, we observed that overnight (14 h) exposure to low micromolar concentrations of hemin consistently produced morphologic evidence of neuronal injury in wild-type cultures (Fig. 1 ). This time interval was therefore used for cytotoxicity studies. Consistent with prior observations in pure astrocyte cultures [ 24 ], no morphologic evidence of injury was observed in the astrocyte monolayer at hemin concentrations up to 10 μM. In order to specifically assess neuronal injury in this study, the concentrations used were limited to this range. In wild-type cultures, cell injury as quantified by LDH release was observed at 1 μM hemin and then increased exponentially, to release of 69.7 ± 8.6% of neuronal LDH at 3 μM (Fig 2A ). The calculated EC 50 was 1.85 μM. LDH release was significantly reduced in knockout cultures subjected to the same treatment. At 3 μM hemin, only 12.6 ± 4.1% of LDH had been released at this time point. Control experiments demonstrated that these low hemin concentrations do not interfere with the LDH assay. Cell death was also quantified by analysis of fluorescence intensity after staining cultures with propidium iodide. Using this method, widespread neuronal death was also observed at 3–10 μM hemin in wild type cultures, and the calculated EC 50 was 1.05 μM. Propidium staining of nuclei was significantly reduced in cultures prepared from HO-2 knockout mice (Fig. 2B ). The maximal fluorescence was produced by exposure to 10 μM hemin, which was 37.0 ± 3.2% of that observed in control sister cultures treated with NMDA to kill all neurons. Effect of HO-2 gene deletion on markers of cell oxidation In order to assess reactive oxygen species formation after hemin exposure, cultures were stained with 20 μM dihydrorhodamine 123 after 4 hour hemin exposure. This time interval was used because it preceded cell lysis, and therefore allowed cell retention of the reduced fluorophore. A marked increase in fluorescence was observed in cultures prepared from wild type mice (Fig. 3 ). This signal was concentrated in neuronal cell bodies and processes. In contrast, fluorescence in cultures prepared from HO-2 knockout mice was minimal, and did not exceed that observed in cultures subjected to medium exchanges only. In order to further investigate the effect of HO-2 gene deletion on oxidative stress produced by hemin, cells were harvested after 4 hour hemin exposure. Protein carbonyl groups (i.e. aldehydes and ketones), which are markers of oxidation, were then derivatized and detected with a dinitrophenylhydrazone antibody. Increased immunoreactivity was apparent in lysates of wild type cultures treated with hemin (Figure 4 ). A prominent band was present at approximately 44 kDa, along with a higher molecular weight smear. At 10 μM hemin, the carbonyl signal intensity in wild type cultures was 2.3-fold higher than in cultures exposed to culture medium only, compared with only 1.3-fold higher in knockout cultures. Hemin neurotoxicity is attenuated by iron chelators Based on our prior observations in astrocytes and neuroblastoma cells [ 24 , 25 ], we hypothesized that the toxic product produced by hemin breakdown in primary murine neurons was iron. In order to test this hypothesis, the effect of iron chelators on hemin neurotoxicity in wild type cultures was assessed. Most cell death, as detected by both LDH release and PI staining, was prevented by concomitant treatment with phenanthroline, a lipid-soluble iron chelator (Fig. 5 ). Deferoxamine, which is water soluble, was less potent; its effect when applied at a concentration tenfold greater than that of hemin reached statistical significance only when injury was assessed by PI staining. Discussion In prior experiments, we demonstrated that targeted deletion of the HO-2 gene in primary neuron/astrocyte cultures did not alter expression of HO-1, and had little or no effect on other cellular antioxidants [ 17 ]. This simplified system therefore permits investigation of HO-2 without the confounding compensatory effects that have been observed in whole animal models [ 26 , 27 ]. We have previously reported that HO-2 gene deletion increased the vulnerability of astrocytes to hemin, the preferred substrate of HO, in cultures containing only astrocytes. The present study targeted neurons in mixed neuron/astrocyte cultures by using hemin concentrations that did not injure astrocytes [ 24 ]. In this model, the opposite was observed. HO-2 deletion attenuated hemin-induced ROS formation and reduced levels of oxidized proteins. Consistent with the oxidative nature of hemin toxicity, neuronal death was reduced in knockout cultures. Although hemin is a highly reactive pro-oxidant, its breakdown as catalyzed by the heme oxygenases generates biologically active and potentially toxic products. Prior in vitro studies suggest that neurons are particularly vulnerable to these, i.e. iron, carbon monoxide, and bilirubin [ 28 - 30 ]. The present results suggest that when neurons are provided with an excess of HO substrate, the toxicity of breakdown products outweighs any benefit provided by hemin removal. The protective effect of iron chelators suggests that this phenomenon is at least partly due to iron neurotoxicity. Inorganic iron is toxic to cultured cortical neurons, with an EC 50 of approximately 10 μM [ 17 ]. The lower EC 50 for hemin is not surprising, given its lipophilicity and accumulation in cell membranes [ 31 ]. The latter phenomenon likely accounts for the greater efficacy of phenanthroline, which unlike deferoxamine is lipophilic. Deferoxamine is quite effective against hemoglobin neurotoxicity in this culture system [ 32 ], suggesting that hemoglobin releases its iron either in the medium or in an aqueous cellular compartment. The present results are consistent with observations that heme oxygenase inhibitors are protective in models of CNS hemorrhage [ 2 , 8 , 9 ], in contrast to the beneficial effect of HO in ischemia [ 33 ]. In a recent study, Koeppen et al. [ 2 ] observed that repeated administration of tin mesoporphyrin protected thalamic neurons from the delayed degeneration that occurred in tissue adjacent to injected autologous blood. Similarly, Huang et al. [ 9 ] observed that tin protoporphyrin attenuated edema formation after stereotactic hemoglobin injection into the rat striatum. It is noteworthy that the number of astrocytes per neuron is significantly higher in the human brain than in rodents [ 34 ]. The deleterious effect of HO inhibition on heme mediated injury to astrocytes may therefore be less prominent in animal models than in clinical intracerebral hemorrhage [ 35 ]. The disparate effect of HO on neurons and astrocytes exposed to extracellular hemin suggests that it may be somewhat difficult to target it effectively after CNS hemorrhage. All currently available HO inhibitors inhibit both HO-2, which is predominantly neuronal in vivo [ 36 ], and HO-1, which is induced mainly in glial cells [ 37 ]. The protection that these non-selective agents provide to neurons may be negated by their deleterious effect on astrocytes. Further investigation is needed for the development of strategies that would permit the selective inhibition or down-regulation of HO-2 in neurons. Conclusions Targeted deletion of the heme oxygenase-2 gene mitigates oxidative stress in cultured neurons exposed to hemin, and is cytoprotective. Selective inhibition of neuronal heme oxygenase may have a beneficial effect after CNS hemorrhage. Methods Cell cultures The HO-2 knockout mice which were used in this study are descended from mutants produced by Poss et al. [ 38 ], and have a C57BL/6 X 129/Sv genetic background. All mice were obtained from our local breeding colony, and were provided with food and water ad libitum and a 12 hour light/dark cycle. All breeding mice were the offspring of heterozygotes. Genotype was determined by polymerase chain reaction (PCR) using genomic DNA isolated from tail clippings; primers were previously published [ 17 ]. Cortical cell cultures were prepared from fetal mice at gestational age 15–17 d as previously described [ 39 ]. Under a dissecting microscope, cortices were dissected free from other brain tissue, minced with forceps, and incubated in medium containing 0.075%-acetylated trypsin at 37°C for one hour. Tissue was then collected by low speed centrifugation, and was dissociated by trituration through a flamed Pasteur pipette in plating medium containing Eagle's minimal essential medium (MEM), 5% fetal bovine serum (Hyclone, Logan, UT), 5% heat inactivated equine serum (Hyclone), glutamine (2 mM), and glucose (23 mM). The cell suspension was diluted with additional plating medium, and cells were plated on confluent astrocyte cultures in 24-well plates (Primaria, Falcon) at a density of 3 hemispheres/plate. Cultures were incubated at 37°C in a humidified atmosphere containing 5% CO2/95% air. Two-thirds of the culture medium was replaced at days 4 and 8 in vitro with MEM containing 10% equine serum, 2 mM glutamine, and 23 mM glucose. After ten days in vitro this feeding procedure was performed daily. Hemin exposure Hemin was freshly prepared as a 1 mM stock solution and was diluted to the desired concentration with minimal essential medium containing 10 mM glucose (MEM10). Experiments were conducted at 12–16 days in vitro. Serum was washed out of cultures with MEM10 (> 1000X dilution) prior to addition of hemin. Cultures were incubated at 37°C in a 5% CO2 atmosphere for the entire exposure interval. Detection of reactive oxygen species ROS formation was quantified by staining with dihydrorhodamine 123 (DHR, Molecular Probes, Eugene, OR), which is a cell-permeable, non-fluorescent compound that is oxidized by cellular peroxides to fluorescent rhodamine [ 40 ]. Fluorescence intensity is directly proportional to cellular oxidative stress. In order to prevent oxidation of DHR by hemin in the medium, cultures were washed free of hemin prior to DHR addition. After incubation with 20 μM DHR in MEM10 for 15 min, the medium was replaced, and cultures were imaged using a Nikon inverted microscope with epifluorescence attachment. Images were captured immediately after illumination (25 msec exposure). Photomicrographs of random 100X fields were analyzed with IPLab image analysis software (Scanalytics, Inc., Fairfax, VA). The low fluorescence in control cultures exposed to experimental medium only was subtracted from mean values to define the signal associated with hemin exposure. Detection of protein oxidation Protein oxidation was assessed using the Oxyblot™ kit (Chemicon, Inc., Temecula, CA). At the end of the hemin exposure interval, culture medium was aspirated, and cells were washed and then harvested in 100 μl of lysis buffer containing 210 mM mannitol, 70 mM sucrose, 5 mM HEPES, 1 mM EDTA, and 0.1% sodium dodecyl sulfate. Carbonyl groups were derivatized to 2, 4-dintrophenylhydrazone (DNP-hydrazone) by reaction with 2, 4-dinitrophenylhydrazine, following the manufacturer's instructions. Proteins were then separated on a 12% polyacrylamide gel and were transferred onto a polyvinylidene difluoride Imobilon-P transfer membrane filter (Millipore, Billerica, MA) using a semidry transfer apparatus (Bio-Rad, Hercules, CA). Carbonylated proteins were detected with rabbit anti-DNP (1:150) followed by goat anti-rabbit IgG (1:300). Immunoreactive proteins were visualized using Super Signal West Femto Reagent (Pierce Biotechnology, Rockford, IL) and Kodak ImageStation 400. Quantification of cell death After examination of cultures using phase contrast microscopy, cell death was quantified by measurement of LDH activity in the culture medium, as previously described [ 41 ]. To facilitate comparisons, values were scaled to the mean value in sister cultures exposed to NMDA 300 μM for 40 h. This treatment releases essentially all neuronal LDH in this system without injuring astrocytes [ 42 ]. Since the low micromolar concentrations of hemin that were used in this study do not injure cultured cortical astrocytes [ 24 ], the contribution of astrocyte LDH to the total signal is negligible. Cell death was also quantified by staining with propidium iodide (13 μg/ml for 15 min). When viewed with a rhodamine filter, the nuclei of cells with disrupted membranes stain red, while cells with intact membranes exclude propidium. Random 100X fields were captured with a Nikon Diaphot epifluorescence microscope and were analyzed with IPLab image analysis software. As with LDH data, fluorescence intensity was scaled to that in sister cultures treated with NMDA 300 μM for 40 h, which kills all neurons. Propidium iodide fluorescence was not observed in cells that had an astrocyte phenotype after treatment with NMDA or hemin at the concentrations used in this study. Abbreviations DHR: dihydrorhodamine; DNP: dinitrophenylhydrazone; HO: heme oxygenase; LDH: lactate dehydrogenase; MEM10: minimal essential medium containing 10 mM glucose; NMDA: N-methyl-D-aspartate; PI: propidium iodide; ROS: reactive oxygen species. Authors' contributions RFR designed the study, collected and analyzed data, and wrote the manuscript. JC also participated in data collection and analysis, and edited the manuscript. LBZ participated in genotyping and edited the manuscript. All authors reviewed and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521072.xml |
521728 | Nature's Nanotechnologists: Unveiling the Secrets of Diatoms | Diatoms are unicellular algae with ornate silica shells. Their dazzling ability to build tiny structures could inspire applications in the semiconductor industry, drug delivery, and engineering | Diatoms, unicellular algae with ornate silica shells, have fascinated amateur and professional biologists ever since the invention of the microscope. But these days, diatoms and their exquisite shells are also attracting the attention of nanotechnologists who hope that diatoms will teach them how to make minute structures currently beyond the capabilities of materials scientists. And now these nanotechnologists, together with ecologists interested in the global carbon cycle—in which diatoms play a central role—have a genomic blueprint to help them in their studies: the annotated genome sequence of Thalassiosira pseudonana ( http://genome.jgi-psf.org/diatom/ ). What Are Diatoms? Diatoms, microalgae that are found in all aquatic and moist environments, first appeared more than 180 million years ago. Since then, diatom diversity has literally exploded; no one is sure how many living species there are—probably about 100,000—or why there are so many different types. Plant molecular biologist Chris Bowler (Ecole Normale Supérieure, Paris, France and Stazione Zoologica, Napoli, Italy) explains that molecular phylogeny and morphological studies suggest that diatoms originated ‘probably as the result of a eukaryote being invaded or engulfed by a photosynthetic eukaryote, most probably a red alga’. The basic structure of all diatoms is similar: a single cell, often with a large vacuole, contained within a silica shell or frustule made of two overlapping halves or valves joined by girdle bands, which are also made of silica. The girdle bands form the rims of the two valves and allow unidirectional growth of the diatom during vegetative division. ‘The shell is rather like a Camembert cheese box or a petri dish’, explains marine ecologist Christian Hamm (Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany). There are only two main types of diatom: centric diatoms, which often have a circular symmetry, and pennate diatoms, which are usually bilaterally symmetrical. Nevertheless, diatom shells come in a dazzling array of forms and sizes ( Figure 1 ; Box 1 ). ‘They can be circular, oval, stick-shaped, you name it, and range from several micrometres large to about a millimetre’, says ecologist Mary Ann Tiffany (San Diego State University, California, United States), who is using scanning electron microscopy to examine diatom valve formation as part of her graduate studies. ‘When a diatom divides, each daughter cell makes a new half shell’, explains Tiffany. The first stage of construction is the generation and deposition of silica nanospheres; the more ornate structures are built up from there. Both the finished shells, with their precise and reproducible nanometre-scale features, and the intermediate structures that lead up to the finished product, could be of interest to nanotechnologists, suggests Tiffany. Figure 1 Scanning Electron Micrographs of Diatoms (A) Biddulphia reticulata . The whole shell or frustule of a centric diatom showing valves and girdle bands (size bar = 10 micrometres). (B) Diploneis sp. This picture shows two whole pennate diatom frustules in which raphes or slits, valves, and girdle bands can be seen (size bar = 10 micrometres). (C) Eupodiscus radiatus . View of a single valve of a centric diatom (size bar = 20 micrometres) (D) Melosira varians . The frustule of a centric diatom, showing both valves and some girdle bands (size bar = 10 micrometres). (Images courtesy of Mary Ann Tiffany, San Diego State University.) Turning to Nature for Engineering Solutions Richard Gordon, Professor of Radiology at the University of Manitoba in Winnipeg, Canada, somewhat accidentally laid the foundations of ‘diatom nanotechnology’ in 1988 when he was invited to give a lecture at an engineering conference. ‘I'm not an engineer’, explains Gordon, ‘but I knew engineers were interested in what was then called microfabrication so I told them about diatoms because they are so good at making small things’. Gordon, a keen diatom hobbyist, explained to his audience how diatoms could make a three-dimensional micro- or nanoscale structure for them without them lifting a finger. By contrast, says Gordon, ‘nanotechnology techniques then and now are tedious, involving painstakingly building three-dimensional structures up layer by layer’. Such tedious techniques are currently used in the semiconductor industry. At present, explains Michael Sussman, Director of the Biotechnology Center at the University of Wisconsin-Madison (Madison, Wisconsin, United States), ‘features are etched onto circuit boards using light. However, the wavelength of light limits the smallest size that can be achieved, and for the next generation of faster computers, engineers need to get denser features onto computer chips than is possible with light etching’. Diatoms, says Sussman, ‘are natural-born lithographers in the nanometre range. If we could work out how diatoms lay down micro lines of silica, then we may be able to simulate it’. The proteins that diatoms use to direct silica deposition could be very useful to the semiconductor industry, says Sussman. There are other ways in which diatoms could help us clumsy humans build nanoscale ‘widgets’. Molecular biologist Mark Hildebrand (Scripps Institution of Oceanography, San Diego, California, United States) is a member of a collaborative project trying to develop genetically engineered micro/nanodevices (also called GEMs). Already, engineers are using diatoms to help them build extremely sensitive sensors based on microfluidic devices, he explains. Hildebrand is also interested in the optical properties of diatoms. ‘Information processing technology is moving from electronically to optically based hardware, which allows more information to be carried and stored. Optical systems need materials with regularly repeating structures with features below the micrometre size range. These are very difficult to make by standard manufacturing techniques, but diatoms make structures like this all the time’. It might also be possible to use diatom shells as delivery vehicles for drugs, suggests chemical engineer Tony Rogers, an assistant professor at Michigan Technological University (Houghton, Michigan, United States). ‘They have a uniform nanoscale pore structure and are chemically inert and biocompatible’. Rogers envisages loading diatoms with a drug that would then leach out into the blood stream at a rate dependent on the diatom species used. By incorporating ferromagnetic particles within the diatom structure, it might be possible to use a magnet to guide the drug to the right organ, he suggests. Diatom structures are not just of interest to people interested in tiny objects. As Hamm comments, ‘in diatoms, Nature has solved many of the problems that engineers want to solve. For example, diatoms are particularly good at making lightweight but strong structures. Because it is possible to scale static structures like shells, diatoms can teach us how to make lightweight constructions for the aerospace and car industry’. Some of the potential applications of diatoms can be investigated right now, using naturally occurring diatoms. In addition, subtle but important changes can be induced in diatoms by varying the amount of silica in their environment or changing the water flow. Gordon also envisages a device he calls a compustat, which would be used to select diatoms for a specific purpose. Diatoms taken from the sea, for example, would be individually examined using a computer-controlled microscope. ‘We would tell the computer what characteristics we were looking for, and it would go through the culture, zapping those diatoms furthest from the ideal with a laser beam. The culture would then be allowed to grow up again and the process repeated until we got the sort of diatoms we wanted’, says Gordon. Gordon has not built a compustat yet—it may not work, he says, because we don't know how far we can push diatoms by forced evolution. And even if the compustat does work, to make the most of the nanotechnological potential of diatoms, we need to know exactly how diatoms make their shells. At present, all we know is that silicon transporters and a group of long-chain, polyamine-containing proteins called silaffins, which act as nucleation points for silica deposition, are involved. This is where the diatom sequencing project at the United States Department of the Environment's Joint Genome Initiative (JGI) at Walnut Creek, California, comes in. The First Diatom Is Sequenced Daniel Rokhsar, Department Head for Computational Genomics at JGI, explains why his institute undertook the sequencing and computer annotation of the genome of T. pseudonana , a marine centric diatom ‘We believe that knowing this genome will help us to figure out how to mimic the processes that diatoms use to construct their very precise structures, and that we can then learn how to create similarly precise structures ourselves’. Also, he adds, diatoms are extremely important on an ecological level. Oceanographer Ginger Armbrust (University of Washington, Seattle, Washington, United States), Principal Investigator on the sequencing project for T. pseudonana , explains further. Diatoms are responsible for between 25% and 40% of all the primary productivity of the oceans, she says. ‘They also keep the biological pump going. By fixing carbon dioxide and then sinking, diatoms draw carbon dioxide out of the atmosphere and take it into the deeper waters of the ocean, where it is retained for longer than it would be if the diatoms stayed near the surface’. T. pseudonana , she continues, was chosen as the first diatom to sequence in part because it has a small genome, but mainly because it represents a cosmopolitan genus of diatoms and its physiology has been well studied. Once the primary sequence of the genome had been determined, molecular biologists, oceanographers, and ecologists from around the world gathered at JGI for a ‘genome jamboree’. ‘The first of these was in October 2002, a massive brainstorming session at which we all dug around in the genome for our favourite genes and tried to get a feel for what was there’, explains Bowler. ‘It was really refreshing to get the insights of oceanographers and ecologists into what this genome was telling us’. Among other things, Armbrust and her collaborators are interested in finding out what the T. pseudonana genome can tell them about the difference between photosynthesis on land and in the sea. They also want to investigate how these organisms adapt to their environment. ‘Now that we have the genome’, says Armbrust, ‘we can investigate how gene expression varies at different places in the water column, for example. This will be the first time a eukaryotic genome has been interpreted in this ecological sort of way’. What About Silicon Metabolism and the Nanotechnology Dream? ‘One of the striking things about the T. pseudonana genome is that we can figure out quite a bit from it about how this diatom deals with organic materials, but it is hard to figure out what it is doing with silicon’, admits Rokhsar. ‘The only way we can really figure out what a gene is doing is by comparing it with known genes in other organisms, but because diatoms are so unique in their use of silicon, we don't have that option. We literally just have the parts list’. To get a hook on which of the 10,000 or so T. pseudonana genes is important in silicon metabolism, Sussman is using microarrays to investigate how silicon concentrations affect gene expression patterns in the diatom. ‘There may be a few hundred genes whose expression changes in response to silicon stress’, he predicts, ‘and we can then focus on the role that these genes play in silicon metabolism’. In another approach, Hildebrand is purifying the proteins present in diatom shells. ‘Once we have isolated these proteins, we can get a little bit of protein sequence, and from there go back to the genome to pull the gene out’, he explains. In an ideal world, the next step would be to see what effect genetically altering the expression of the proteins identified by Sussman and Hildebrand has on the silica shell of T. pseudonana . Unfortunately, this can't currently be done. ‘The only diatom we can genetically manipulate is Phaeodactylum tricornutum , a pennate diatom’, explains Bowler. P. tricornutum , he says, is the ‘lab rat’ of the diatom world but is much less important ecologically than T. pseudonana ( Figure 3 ). Bowler has previously determined the size of P. tricornutum 's genome and is now leading a JGI project that is 75% of the way through sequencing the P. tricornutum genome. ‘It will be critical to have this second genome’, notes Rokhsar, ‘because it will highlight what is unique to this group of organisms, and provide additional help in pulling out silicon metabolism genes’. Figure 3 Light Micrograph of Phaeodactylum tricornutum This pennate diatom is the ‘lab rat’ of diatoms, and its genome sequence is currently being determined. (Image courtesy of Alessandra de Martino and Chris Bowler, Stazione Zoologica and Ecole Normale Supérieure.) Once the details of silicon metabolism have been revealed, the stage should be set for nanotechnologists to harness diatom proteins for the manufacture of nanodevices. ‘Whether we use those proteins inside the diatom or in test tubes remains to be seen, but one way or another, diatoms are harbouring a secret that engineers need to learn about’, says Sussman. Hildebrand agrees, noting how ‘important it is that materials scientists recognise the incredible ability of biology to make structures that could perhaps be incorporated in the design of nanotechnological widgets’. For Armbrust, it is the ecological insights are coming out of the T. pseudonana genome sequencing project—which is part of a bigger JGI program on algal genomics—that are most exciting. ‘Already, multiple little insights are encouraging us to think differently about how diatoms perceive their environment and survive in it. We have also seen many things we can't figure out at all right now. My heart lies in the ecology of these organisms, but if we can generate information that leads to spinoffs for nanotechnology, that will be fantastic’, she concludes. Figure 2 Diatoms in Art (Image courtesy of David Roberts, University of Wales, Bangor, UK.) Box 1. Diatoms in Art Diatoms don't inspire only biologists and engineers—artists, too, are fascinated by their intricate structures. Exquisite line drawings produced by zoologist Ernst Haeckel influenced the Art Nouveau movement, and more recently, wood-worker Louise Hibbert and jeweller Sarah Parker-Eaton have collaborated to produce three-dimensional objects based on diatoms and other plankton. ‘We both independently used marine biology as a source of inspiration for our art’, explains Parker-Eaton. ‘As a student, I often visited the Natural History Museum in London, where there were drawers of fascinating marine organisms that I could sketch’. In January 2002, Hibbert and Parker-Eaton were invited to the marine laboratories at the University of Wales at Bangor (United Kingdom) by oceanographer David Thomas. ‘What we saw down the microscopes just blew our socks off’, says Parker-Eaton. ‘We could see how the plankton moved, the forms, the incredible different layers within the diatoms. What we particularly liked about diatoms was their complexity—they are totally unlike any other life form’. Parker-Eaton and Hibbert translate what they see down the microscope into objects made of wood and silver, usually small enough to hold in the hand. Figure 2 shows a representation of Navicula sp. The main body is sycamore, the ‘blobs’ are resin, and the object is coloured with inks. The piece is held together by magnets but splits in half to reveal two silver inserts at its centre. More examples of these artists' work can be seen at http://www.louiseandsarah.com . | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC521728.xml |
538292 | The impact of antidepressant treatment on population health: synthesis of data from two national data sources in Canada | Background In randomized, controlled trials, antidepressant medications have been shown to reduce the duration of major depressive episodes and to reduce the frequency of relapse during long-term treatment. The epidemiological impact of antidepressant use on episode duration and relapse frequency, however, has not been described. Methods Data from two Canadian general health surveys were used in this analysis: the National Population Health Survey (NPHS) and the Canadian Community Health Survey (CCHS). The NPHS is a longitudinal study that collected data between 1994 and 2000. These longitudinal data allowed an approximation of episode incidence to be calculated. The cross-sectional CCHS allowed estimation of episode duration. The surveys used the same sampling frame and both incorporated a Short Form version of the Composite International Diagnostic Interview. Results Episodes occurring in antidepressant users lasted longer than those in non-users. The apparent incidence of major depressive episodes among those taking antidepressants was higher than that among respondents not taking antidepressants. Changes in duration and incidence over the data collection interval were not observed. Conclusions The most probable explanation for these results is confounding by indication and/or severity: members of the general population who are taking antidepressants probably have more highly recurrent and more severe mood disorders. In part, this may have been due to the use of a brief predictive diagnostic interview, which may be prone to detection of sub-clinical cases. Whereas antidepressant use increased considerably over the data-collection period, differences in episode incidence and duration over time were not observed. This suggests that the impact of antidepressant medications on population health may have been less than expected. | Background Depressive disorders are among the most important contributors to disease burden at the population level . While primary prevention for this condition has remained an elusive goal, provision of treatment has been viewed as having the capacity to reduce its impact on population health. Randomized, controlled clinical trials confirm that treatment with antidepressant medications can favorably impact the course of major depressive disorder. Clinical practice guidelines recommend acute treatment to reduce episode duration, continuation treatment to prevent relapse and maintenance treatment for those at high risk of recurrence [ 1 ]. Direct generalization of clinical trial data to the general population results in an expectation that depressive episode frequency and episode duration should be reduced in those receiving antidepressant treatment. However, outcomes reported in clinical trials are not necessarily reflected in "real world" outcome data. Since treatments are not assigned randomly in clinical settings, those treated are likely to have more severe illness (both in terms of episode duration and recurrence risk) than those who do not seek or receive treatment. In such circumstances, the effect of treatment may become confounded with the effect of the underlying disorder itself, and/or its severity [ 2 ]. Despite the plausible occurrence of confounding by indication and confounding by severity, population-based studies examining outcomes in relation to treatment status in the general population have not been reported. The objective of the current study was to estimate the incidence and duration of major depressive episodes in members of the general population who are receiving or not receiving antidepressant treatment. Methods The National Population Health Survey (NPHS) is a longitudinal general health survey conducted by the Canadian government's statistical agency, Statistics Canada The NPHS sample consists of 17,262 subjects selected in 1994 and 1995 (hereafter denoted 1994/95) who have been followed prospectively with interviews every two years since. Data has been released for the first four cycles (1994/95 to 2000/01). The Canadian Community Health Survey (CCHS) is another general health survey conducted by Statistics Canada. The CCHS has a very large sample size (n = 130,880) and employed a cross-sectional study design. Data collection for the CCHS occurred in 2000. Both the NPHS and the CCHS utilized probability samples, based on the same sampling frame, from the Canadian general population. The sampling procedures incorporated both clustering and unequal selection probabilities. Valid inference therefore requires the use of sampling weights and statistical procedures accounting for non-independence within clusters. In order to deal with these methodological issues, a bootstrap procedure for variance estimation developed by Statistics Canada was employed in this analysis. This procedure accounts for the design effects. Both the NPHS and the CCHS recorded medication use with a series of self-report items. The item relevant to this analysis asked whether the respondent had taken antidepressant medications during the month preceding the interview. Each interview also included the Composite International Diagnostic Interview Short Form for Major Depression (CIDI-SFMD), which was developed and validated by Kessler et al. [ 3 ]. This is a brief, fully structured instrument derived from a set of modified CIDI items. The CIDI-SFMD was designed to provide an operationalization of the DSM-IV [ 4 ] diagnostic criteria for major depression and is sufficiently brief that it can be included in general health surveys. The instrument detects symptoms indicative of major depression, and identification of five such symptoms (one of which must be depressed mood or loss of interest) indicates a high probability that the subject fulfilled DSM-IV criteria for major depression in the 12-months preceding the interview. It should be noted, however, that the Short Form does not contain all of the clinical significance probes and organic exclusion items that are included in the full CIDI, and may therefore detect some subclinical episodes [ 5 ]. A component of the CIDI-SFMD is an item that asks (of subjects reporting a probable episode of major depression) the number of weeks in the preceding year that were characterized by depressive symptoms. In calculating incidence, pairs of observations across NPHS longitudinal data collection cycles were used. There were three suitable intervals covered by the four data collection rounds: 1994/95 to 1996/97, 1996/97 to 1998/99 and 1998/99 to 2000/01. Attrition rates have generally been modest in the NPHS, with 76.6% of subjects having been successfully followed over the first four cycles [ 6 ]. In each instance, the subjects with major depression at the baseline interview were excluded and the remaining subjects were regarded as the population at risk of having a new or recurrent episode. It was not possible to differentiate between new and recurrent episodes, as lifetime history was not available. The proportion of subjects not reporting an episode in the 12-months preceding an interview who subsequently reported an episode in the 12-months preceding their interview 2 years later was used as an approximation of episode incidence. With the four available NPHS cycles, incidence could be estimated in this way across the three intervals. Results Estimates of the number of weeks depressed in the past year derived from the CCHS were computed from 126,715 subjects who provided valid responses both to the CIDI-SFMD (including the duration item) and the antidepressant use survey item. There were 9729 subjects with an episode of major depression in the year preceding the interview and 9508 (97.7%) of these provided valid duration data. Figure 1 shows the number of weeks depressed in the past year as reported by subjects with major depression in the CCHS, depending on whether or not they were taking antidepressants. Weeks depressed in the past year is presented in Figure 1 as a cumulative frequency; the Figure depicts the proportion (on the 'y' axis) of subjects reporting a duration less than or equal to the number of weeks specified (on the 'x' axis). Figure 1 shows that subjects reporting antidepressant use had a greater number of weeks depressed in the year preceding the interview. Analogous plots were generated for the each of the NPHS cycles, and each presented a similar pattern. Figure 2 presents weeks depressed in the past year from the 1994/95 NPHS. In the CCHS, the mean reported number of weeks depressed in the past year was 10.8 weeks among those not taking antidepressants and 18.7 weeks among subjects who reported taking antidepressants. Figure 1 Cumulative proportion reporting ≤ specified number of weeks depressed in the past year for CIDI-SFMD positive subjects (n = 9508) in the Canadian Community Health Survey, by antidepressant use. Figure 2 Cumulative proportion reporting ≤ specified number of weeks depressed in the past year for CIDI-SFMD positive subjects (n = 1030) in the 1994/95 National Population Health Survey, by antidepressant use. Figure 3 presents the weeks depressed in the past year data from the NPHS and CCHS, without reference to antidepressant use. The reported weeks depressed in the past year is virtually identical in each of the four NPHS data collection cycles and the CCHS. Figure 3 Proportion with ≤ specified weeks depressed in past year, by year of data collection. Table 1 presents approximate episode incidence, as calculated for the three intervals between the four NPHS data collection interviews. The point estimate for the 1996/97 to 1998/99 interval was slightly lower than the other two, but the confidence intervals associated with these estimates suggest that this difference could be due to chance. The incidence of new episodes in subjects reporting the use of antidepressant medication was approximately three times that of subjects not using antidepressants. Table 1 Approximate incidence* in subjects taking or not taking antidepressants in the baseline year Baseline year Follow-up interview Taking antidepressants Not taking antidepressants Approximate incidence* (unweighted proportion) 95% confidence interval Approximate incidence* (unweighted proportion) 95% confidence interval 1994 1996 12.7% (20/172) 6.0 – 19.4 3.4% (277/9055) 2.9 – 4.0 1996 1998 7.8% (21/234) 3.5 – 12.0 3.5% (375/9127) 3.0 – 4.1 1998 2000 12.7% (47/352) 8.6 – 16.8 3.5% (317/8994) 2.9 – 4.0 Average 11.1% 3.5% *Proportion of subjects free from a major depressive episode in the year preceding the baseline interview who developed major depression in the year preceding the follow-up interview. These estimates are weighted to account for design effects. The unweighted raw proportions have been placed beside the weighted estimates. Discussion Direct generalization of clinical trial data to the general population would lead to an expectation that subjects in the general population who report antidepressant treatment should have briefer episodes of major depression than those who do not receive such treatment. Similarly, one might hypothesize that subjects reporting antidepressant treatment should have a reduced incidence of episodes. In the current analysis of national survey data, neither expectation was found to hold true. Subjects reporting an episode of major depression and reporting receipt of antidepressant treatment reported more, rather than fewer, weeks depressed in the preceding year. Similarly, subjects who did not have an episode of major depression in the year preceding an interview but who nevertheless reported using antidepressant medications had a higher risk of having an incident episode than similar subjects who did not report taking antidepressants. The most obvious explanation for these findings is that of confounding by indication or severity. Some of these results may have been due to inadequacies involving the data sources. One of these is the brief, and therefore somewhat crude [ 5 ] nature of the CIDI-SFMD as a measure of major depression. As this instrument does not contain detailed clinical significance probes, some sub-clinical episodes may have been detected. As the CIDI-SFMD does not contain organic exclusions, the instrument may have detected some episodes characterized by organic symptoms. The 12-month prevalence of major depression in the CCHS was 7.4% which is higher than most recently published estimates of major depression prevalence, consistent with the possibility of non-specificity. This draws into question whether these results would be replicated with the use of a more detailed diagnostic instrument. However, this concern should not be overstated. Some studies using the full CIDI have reported higher estimated 12-month prevalence [ 7 , 8 ]. Severe depressive disorders that are treated with antidepressants may have longer episode durations and higher relapse rates than less severe and untreated disorders. Items evaluating antidepressant use in each survey referred to use of the medications during the past month, whereas probable major depressive episodes occurring during the past year are detected by the CIDI-SFMD. Therefore, even though subjects who reported taking antidepressants were found to be more likely to have a subsequent episode of major depression, the data did not allow a determination of whether some of these subjects may have stopped or started antidepressants at some time during the follow-up interval. Another limitation of the data sources used in this project was the lack of comorbidity data. Many of the subjects taking antidepressants may have been doing so for indications such as the prophylaxis of migraine headaches or for treatment of anxiety disorders. Both migraine headaches [ 9 , 10 ] and anxiety disorders [ 11 ] are frequently associated with major depression. To the extent that these disorders impact upon the risk and prognosis of major depressive episodes, they could also confound associations between antidepressant use, major depression episode incidence and episode duration. While confounding by indication and severity offer, perhaps, the most appealing explanation for these results it is important to emphasize that the attractiveness of these explanations is based on a set of assumptions: that antidepressants are efficacious in reducing episode duration and the risk of relapse and recurrence. An altered set of initial assumptions leads to other possible interpretations. For example, some authors have hypothesized that antidepressant treatment may lead to a deterioration in the long-term course of mood disorders [ 12 ]. This hypothesis, although not widely accepted, predicts that episode duration and incidence would be higher in those reporting antidepressant use than in those not using these medications. A finding consistent with this idea was a meta-analysis by Baldessarini et al., which found that subjects taking antidepressant medications for longer periods were more likely to relapse upon discontinuation [ 13 ]. Generally, the public health challenges associated with major depression have been conceptualized in "common sense" terms, and in a way that does not depend on underlying etiological features of the disorder. For example, the idea that preventing relapse (episode incidence) should translate into reduced prevalence and reduced disease burden seems on the surface to be a common-sense belief. However, it has been hypothesized that depression can assume an adaptive role [ 14 ]. If an adaptive role for depression involves, for example, limiting an individual's interaction with a stressful environment (e.g. if depressive symptoms serve the adaptive purpose of discouraging interaction with elements of the environment that trigger them), then treatment of depression may indirectly lead to increased stress exposure. If this is true, then antidepressant treatment may increase people's comfort and capacity to function in a stressful environment, but may also increase the intensity of stress in the environment that surrounds them. Such complex dynamics could obscure an expected decline in prevalence due to increased treatment. Conclusions Most of the literature concerned with major depression and public health has emphasized that the disorder is under-treated, although more recent studies have begun to move beyond the frequency of treatment to address the issue of treatment adequacy [ 15 ]. There is an emerging need to address the lack of epidemiological evidence confirming the population-health benefits of increased antidepressant treatment. Specifically, it will be necessary to determine the extent to which negative outcomes in association with antidepressant treatment in observational data sources represent a methodological artifact. List of Abbreviations CIDI-SFMD Composite International Diagnostic Interview Short Form for Major Depression DSM-IV Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. MDE Major Depressive Episode NPHS National Population Health Survey CCHS Canadian Community Health Survey (iteration 1.1) Competing Interests The author(s) declare that they have no competing interests. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538292.xml |
517503 | Graft calcifications and dysfunction following liver transplantation | Background The molecular events, following ischemia and reperfusion (I/R) of the liver during transplantation are largely unknown. There is evidence that apoptotic and necrotic events may take place, and occasionally result in primary graft dysfunction. We herein report two cases, where significant I/R injury correlated with the development of liver calcification and primary liver dysfunction. Case Presentation Both patients with clinical and biochemical evidence of primary graft dysfunction demonstrated calcification at light and electron microscopy levels. In addition, one patient had macroscopic evidence of calcification on cross-sectional imaging. Both patients died secondary to the sequelae of the graft dysfunction. Conclusions Severe I/R-induced injury to the liver, clinically leads to graft dysfunction. This is due to advanced apoptotic and/or necrotic events at the hepatocyte level that may, on the most severe form, lead to calcification. The study of microcalcification at the early posttransplant period could provide insight in the events taking place following significant ischemia/reperfusion-induced injury to the graft. | Background Liver transplantation (LT) remains the only treatment for end-stage liver disease. However the transplant procedure mandates cold perfusion, hypothermic storage, warm ischemia and warm reperfusion of the graft, resulting in Ischemia/Reperfusion (I/R)-induced injury to the transplanted graft. Although the introduction of the University of Wisconsin solution (UW) has improved clinical outcomes, I/R injury remains one of the major clinical problems following LT leading, in cases of marginal donor quality or prolonged cold or warm ischemic time, to the development of graft dysfunction or non function. Recently the cellular events following liver I/R during LT have been brought to sharp focus. Nevertheless, it is still controversial if the major mode of cell death during I/R is apoptosis and/or necrosis [ 1 ]. It has been shown in an animal model of viral-induced hemorrhagic liver necrosis, that the liver undergoes several morphologic changes including mineralization [ 2 ]. Furthermore, previous clinical reports have documented the development of calcifications in liver upon extensive ischemia [ 3 , 4 ]. The above observations may reflect a high degree of cell damage leading to an enhanced apoptotic cell engulfment by non-professional phagocytes of the liver [ 5 ] with subsequent necrosis and biomineralization. In this report, using a combination of cross-sectional imaging, histochemistry, and light (LM) as well as transmission electron microscopy (TEM) we identified liver calcification, in two grafts with severe I/R injury following LT. Case Presentations Case 1 A 65-year-old man of Asian origin underwent LT at our institution on June 2002, for decompensated Hepatitis B related cirrhosis. The patient did not have a history of abnormal calcium metabolism, or hyperparathyroidism. Upon listing his serum ionized calcium was 1.07 mmol/L. The donor was a previously healthy, 42-year-old male, who suffered intracranial bleeding following a motor vehicle crash. He did not suffer any period of hypoxia but he was hypotensive (SBP = 90 mm Hg) prior to procurement. His serum liver function tests were normal prior to harvesting (AST 32 U/L, ALT 40 U/L). The organ was procured by our institution's transplant team. During procurement the liver was found to be well perfused with no focal injuries and no macroscopic evidence of steatosis. The recipient underwent an uncomplicated conventional LT without the use of a veno-venous bypass. There were no periods of hypoxia or severe hypotension during transplantation. The cold ischemic time of the graft was 8 hours while the warm ischemic time was 45 minutes. The graft reperfused well and no biopsies were taken. Intravenous methylprednisolone (500 mg) was administered intraoperatively, and postoperatively the patient received induction with Antithymocyte Globulin, which is the protocol followed at our institution. During transplantation the patient received a total of 4 units of packed red blood cells (PRBCs) and 6 units of fresh frozen plasma (FFP). At the time of LT, the international normalization ratio (INR) was 1.53, while serum total bilirubin was 103 μmol/L (Figure 1A,1B ). On postoperative day 2 the patient had a peak of his serum AST (3469 U/L) and at this point he had further biochemical evidence of primary graft dysfunction, with inability to normalize his INR (Figure 1B ), and with progressive elevation of his total serum bilirubin (Figure 1A ). Repeated ultrasonographic examination revealed a patent hepatic artery and portal vein, as well as patent hepatic veins. At this point, a liver biopsy demonstrated severe reperfusion injury with several apoptotic bodies, several dystrophic calcifications (Figure 1E ), and no evidence of acute cellular rejection. His clinical status deteriorated, he developed multiorgan system failure and died 12 days after his transplantation. No septic focus was identified. Both kidneys harvested from the same donor did not present any signs of delayed graft function after transplantation. Figure 1 A: Serum Bilirubin levels (μmol/L) for patient 1 (solid line) and for patient 2 (dashed line). The arrowheads indicate the time points where calcifications were detected. B: International Normalization Ratio (INR) for patient 1 (solid line) and for patient 2 (dashed line). Arrowheads indicate the time points where calcifications were detected. C: Computed Tomography of patient 2. The arrow points an area in the right liver with the same density as the spinal column (arrowhead). D: Picture of the explant liver during retransplantation of the same patient (case 2). The arrow shows the abnormal area of the right liver correlating with the computed tomography findings. E: Light microscopy of epoxy embedded semi-section obtained from the liver biopsy from patient 1. The image shows moderate calcification (microcalcification) throughout the section. The arrow indicates a representative pattern of calcification. F: Light microscopy of epoxy embedded semi-section obtained from the tissues of the explant, following liver retransplantation of patient 2. The image shows the interface between calcified region (upper right) and non-calcified adjacent hepatic cells (lower left region). G: Light microscopy image showing a higher magnification of calcified region as shown in F. The bright and high contrast regions represent massive mineralization of hepatic cells of the explant, following retransplantation. H: Transmission electron microscopy images of ultrathin section obtained from the transitional zone between calcified and non-calcified tissue. Showing the mode of calcification and textural organization of hydroxyapatite crystal aggregates (dark contrast) within cytoplasmic region of the cell. Note alteration of the nucleus in the center. Case 2 A 55-year-old man of Greek origin underwent LT at our institution for ethanol and hepatitis B related cirrhosis, as well as a large hepatocellular carcinoma. The patient did not have a history suggestive of hyperparathyroidism or abnormal calcium metabolism, and upon listing his serum ionized calcium was 0.94 mmol/L. The donor was a previously healthy, 52 year-old male who suffered a closed head injury during a motor vehicle crash. The organ was procured by our transplant team. Prior to procurement the donor did not suffer any periods of hypoxia or hypotension. His liver function tests were normal prior to harvesting (AST 36 U/L, ALT 45 U/L). During procurement the liver was found to be well perfused, with no evidence of aberrant vascular anatomy and no evidence of trauma. Macroscopic examination of the liver did not show any evidence of steatosis. The recipient underwent a conventional LT without venovenous bypass and without intraoperative hypotension. The cold ischemic time was 10 hours while the warm ischemic time was 40 minutes. Following reperfusion, the graft appeared well perfused and again no biopsies were taken. Intraoperatively the patient received 500 mg of methylprednisolone, and postoperatively he was induced with Antithymocyte Globulin. During transplantation the recipient received 3 units of PRBCs and 6 units of FFP. In the early postoperative period the patient had to be explored once for retroperitoneal bleeding associated with hypotension (SBP< 90 mm Hg). At the time of LT, the patient had an INR of 2.7 and a serum total bilirubin of 104 μmol/L. Following LT, the patient developed severe primary graft dysfunction with rising serum bilirubin and INR (Figure 1A,1B ), while his serum ALT and AST peaked during the 2 nd and 3 rd postoperative day (4700 U/L and 6598 U/L respectively). At that time, ultrasonography demonstrated uniformly patent vessels (hepatic artery, portal and hepatic veins), while Computed Tomography (CT) showed areas in the right lobe of the liver isodense with the spinal column (Figure 1C ). The patient was listed for retransplantation. During the retransplant procedure the explant liver graft had a "bony" consistency in the involved right lobe. Cross-sections of the right lobe showed a "clay-like" parenchyma with clear evidence of calcification (Figure 1D ). Light (LM) and transmission electron microscopy (TEM) investigation of ultrathin sections obtained from specimens selected from biopsies at the interface of calcified and non-calcified tissues showed extensive intracellular calcification within the hepatic cells (Figure 1F ). High-resolution TEM (HRTEM) images and selected-area electron diffraction (SAED) combined with energy dispersive spectroscopy (EDS) analysis demonstrated the presence of hydroxyapatite (HA) as a solid phase in the calcified region. The adjacent non- or partially calcified hepatic cells displayed extensive nuclear condensation suggestive of significant apoptosis as well as severe vacuolization, suggestive of an extensive apoptotic and necrotic process (Figure 1G,1H ). The patient had a complicated postoperative course and finally died from ventricular fibrillation unresponsive to electrical cardioversion. Both kidneys harvested from the initial donor were transplanted without any evidence of delayed or primary graft dysfunction/non-function. Conclusions Currently, more than 16,000 candidates are listed with the United Network for Organ Sharing awaiting liver transplantation. Nevertheless, only 4800 cadaveric liver transplants are performed annually in the United States. Due to this discordance between organ demand and supply, it is estimated that approximately 10% of patients in the waiting list will die before obtaining an organ. As a result, novel strategies to expand the donor pool have been explored. With the exception of live donor liver transplantation, the remaining strategies involve the use of older cadaveric grafts, allografts with mild steatosis or even donors with evidence of past hepatitis B or C infection [ 6 ]. This is why, one of the major obstacles to be tackled, is the development of clinically significant ischemia and reperfusion injury, which is even more important for "marginal" grafts. Every progress towards understanding the molecular events following not only cold storage but also cold and warm reperfusion of the graft could have a significant impact on the current transplantation practices. Indeed, recent data suggest that following I/R there is a balanced apoptosis and occasionally necrosis of hepatocytes translating into cell swelling, distension of various cellular organelles, clumping and random degradation of nuclear DNA, extensive plasma membrane endocytosis and autophagy [ 7 ]. Furthermore, when these events become predominant, they can lead, at least in animal models, to the development of calcifications as observed in livers of rabbits infected with rabbit haemorrhagic virus [ 2 ]. In the present case report, we have shown that these events can take place in human subjects following liver transplantation. To our knowledge these are the first reported cases in the literature of liver calcification following liver transplantation, presumably secondary to I/R injury. Not only did both patients have biochemical evidence of severe graft I/R injury, they also had biopsy proven I/R induced injury associated with the development of calcifications. Furthermore, both succumbed to the sequelae of this injury. Both recipients received grafts from donors with normal serum biochemistries and no evidence of hepatic trauma or steatosis. Both donors had no evidence of crystal deposition or storage disease, and although we did not perform any donor liver biopsies, the grafts appeared macroscopically normal and perfused well with UW solution. Corroborating to this remains the fact that all four kidneys (from both donors) were transplanted without any problems. Neither recipient had any evidence of calcium metabolism problems, since both had normal serum calcium upon listing. Both recipients had an anticipated intraoperative course without periods of hypotension and without massive transfusion requirements. Finally, both grafts did not demonstrate any vascular problems in the postoperative period by Ultrasonography or CT scan examination or any evidence of intrahepatic thrombosis in postmortem or explant examination. Ischemic stress has been previously reported to induce calcium accumulation at the cell level, either by impaired energy metabolism and/or plasmalemmal alterations. This elevated intracellular calcium concentration is responsible for cytoskeletal modifications, which alter cell shape, and for the activation of phospholipases, which results in perpetuation of membrane damage and finally, mitochondrial calcification [ 8 ]. Although, the crystal shape, composition and organization of HA in our samples are similar to those observed in bone and cartilage [ 9 ], as well as synthetic HA formed in serum [10], the intracellular precipitation of HA within hepatic cells is unique and has not been reported from other physiological and pathological tissues. The observation of calcified, vacuole-like structures in hepatic cells from these two livers could be suggestive of mitochondrial calcification. In addition, the extensive presence of phagocytic structures in the pre-calcified regions of these livers suggests an intense apoptotic/necrotic process undergone after I/R injury in these regions. Further investigation, however, is required to understand the mechanism(s) and the mode of calcification in the liver. In conclusion, we believe that the described phenomenon is underreported at least in the liver transplant literature. Furthermore, it appears that there is a correlation between the development of severe I/R injury leading to apoptosis and/or necrosis and calcifications detectable even by light microscopy. We think that the development of microcalcifications should be studied more extensively in the context of I/R injury following liver transplantation. Although, such a phenomenon appears to correlate with significant I/R injury, evident by biochemical data, it has the potential to be provide further information on the pathways of severe I/R injury post transplant. Competing Interests None declared. Authors Contributions GNT: conceived the study and wrote the manuscript MA: carried out the electron microscopy studies EC: participated in the design and analyzed the light microscopy results, critical review of the manuscript AE: analyzed light microscopy results AV: carried out electron microscopy studies PM: participated in the design of the study All authors read and approved the final manuscript. Abbreviations I/R: Ischemia and Reperfusion LM: Light Microscopy TEM: Transmission Electron Microscopy HRTEM: High-resolution Transmission Electron Microscopy EDS: Energy Dispersive Spectroscopy HA: Hydroxyapatite Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC517503.xml |
406397 | Many Ribosomal Protein Genes Are Cancer Genes in Zebrafish | We have generated several hundred lines of zebrafish (Danio rerio), each heterozygous for a recessive embryonic lethal mutation. Since many tumor suppressor genes are recessive lethals, we screened our colony for lines that display early mortality and/or gross evidence of tumors. We identified 12 lines with elevated cancer incidence. Fish from these lines develop malignant peripheral nerve sheath tumors, and in some cases also other tumor types, with moderate to very high frequencies. Surprisingly, 11 of the 12 lines were each heterozygous for a mutation in a different ribosomal protein (RP) gene, while one line was heterozygous for a mutation in a zebrafish paralog of the human and mouse tumor suppressor gene, neurofibromatosis type 2. Our findings suggest that many RP genes may act as haploinsufficient tumor suppressors in fish. Many RP genes might also be cancer genes in humans, where their role in tumorigenesis could easily have escaped detection up to now. | Introduction The zebrafish (Danio rerio) has long been used as a model organism for the identification of genes required for early vertebrate development ( Kimmel 1989 ). There is reason to believe that the zebrafish can also be used in genetic screens to identify cancer genes. Zebrafish can live for 4–5 y ( Gerhard et al. 2002 ), and like other fish species ( Schmale et al. 1986 ; Wittbrodt et al. 1989 ), they develop tumors in a variety of tissues ( Amatruda and Zon 2002 ; Smolowitz et al. 2002 ). They are also susceptible to chemical carcinogens and to well-known oncogenes, in a manner similar to the conventional mouse models ( Beckwith et al. 2000 ; Spitsbergen et al. 2000a , 2000b ; Langenau et al. 2003 ). Many of the spontaneous and chemically- or oncogene-induced tumor types are histologically similar to their mammalian counterparts ( Amatruda and Zon 2002 ; Langenau et al. 2003 ). The normal functions of many mammalian tumor suppressor genes are required for normal development ( Jacks 1996 ). In fact, nonessential tumor suppressors, such as p53 ( Donehower et al. 1992 ), appear to be the exception rather than the rule. These findings raised the possibility that one could discover genes with a role in tumorigenesis among zebrafish genes identified initially for having essential roles during embryonic development. We have used retroviral vectors as a mutagen in a large-scale insertional mutagenesis screen and have isolated many zebrafish mutants with lesions in genes essential for embryogenesis ( Amsterdam et al. 1999 ; Golling et al. 2002 ). We are maintaining approximately 500 lines, in most of which an embryonic lethal mutation is linked to a single proviral insert. We have identified the mutated genes in over 400 of the lines, and these include mutations in 300 distinct zebrafish genes. To maintain the lines, we identify approximately 15 heterozygous carriers and outcross these at 15–20 mo of age to produce the subsequent generation. The maintenance of these mutations in adults provides a unique opportunity to ask whether heterozygosity in genes required for embryonic development predisposes the animals to cancer. Here we describe how such an analysis has identified genes that encode ribosomal proteins (RPs) as cancer genes in zebrafish. Results Mutations in Many RP Genes Predispose Zebrafish to Malignant Peripheral Nerve Sheath Tumors and Other Cancers In the course of establishing and maintaining heterozygous mutant lines of fish, we noticed several lines that displayed early mortality by 2 y of age, and this phenotype was seen in successive generations. Typically, only about 10% to 15% of the fish in a tank are lost by 2 y of age, but in these apparently high-mortality lines losses sometimes exceeded 50%. Furthermore, fish from these lines were often found to have gross lumps ( Figure 1 A and 1 B). Histological analysis of step sections showed that the growths were predominantly large, malignant spindle cell tumors that were highly invasive, had a high mitotic index, and often exhibited focal necrosis ( Figure 1 C– 1 H). The tumor cells were aligned into stacks and fascicles to form a whirling, storiform pattern ( Figure 1 E– 1 H) that resembled malignant peripheral nerve sheath tumors (MPNSTs) seen in other species of fish ( Schmale et al. 1983 ; Roberts 2001 ) and in mammals ( Cichowski et al. 1999 ; Jimenez-Heffernan et al. 1999 ; Woodruff 1999 ). In keeping with the published work on fish tumors, while adhering to the caution suggested by the National Neurofibromatosis Foundation regarding animal models of MPNST (M. McLaughlin, personal communication), we have designated these tumors zMPNSTs (zebrafish MPNSTs). Figure 1 Spindle Cell Tumors Resembling MPNSTs in Zebrafish Heterozygous for Mutations in RP Genes (A and B) Fish with apparent masses, as indicated by the arrows, or other evident pathology were selected for histological analysis: (A) a hi2582 fish, (B) a hi1034B fish. (C–H) Histopathology of representative tumors stained with hematoxylin and eosin reveals patterns consistent with the diagnosis of MPNST in hi10 fish (C and D), hi1974 fish (E–G), and hi1807 fish (H). (C) Tumors typically filled the entire abdomen (sb, swim bladder; br, brain) (80×). (D) A large tumor with central necrosis is seen emanating from the optic nerve (n) (e, eye) (20×). (E) Tumors consist of spindle cells that stack into short fascicles, typically organizing into whorls (400×). (F) Tumor is aggressively invading muscle (m) and gill (g) (br, brain) (100×). (G) Mitotic figures (arrows) are evident (1000×). (H) Areas of focal necrosis (arrows) are frequently seen (200×). Although we had occasionally observed individual fish with lumps in our colony, it was unusual to find so many within a single line. Thus, we reasoned that the lines with early mortality that also frequently displayed gross lumps by 2 y of age might be lines with elevated rates of lethal cancer. Surprisingly, we found that the several potentially high-tumor lines were all heterozygous for mutations in genes that encode different RPs. This unexpected observation, combined with the knowledge that many tumor suppressors are recessive embryonic lethal genes, prompted us to survey our colony systematically to determine the incidence and spectrum of tumors arising in the colony as a whole, and to ask specifically whether genes that encode many different RPs predispose to cancer. To determine cancer incidence in the colony as a whole, we sectioned 152 “control” fish that were 20–26 mo of age. Forty-nine of the control fish were nontransgenic, while 103 were selected at random from 54 lines heterozygous for mutations in genes other than RP genes. The latter fish had been generated and maintained in a comparable manner to our RP mutant lines and thus were appropriate controls. The incidence of tumors detected by step sectioning in this control population was 11% ( Table 1 D). Although we observed a variety of different tumor types (most frequently seminomas and pancreatic islet cell adenomas), most of the tumors (15/17) were benign neoplasias and none were zMPNSTs. There was neither a significant difference in spectrum nor an increase in incidence of tumors in the non-RP heterozygous mutant fish relative to the wild-type fish, indicating that the presence of viral insertions, per se, does not have an obvious effect on tumorigenicity. Table 1 Tumor Incidence in Zebrafish RP-Heterozygous Lines and in the Colony a One individual had two tumors, each of which was malignant. RP animals were collected as tumors became apparent, or as healthy animals at the maximum age specified (age range). Number lost indicates those that either died before the appearance of external symptoms or were lost from their tanks. Control animals from the colony were selected without regard to gross appearance. Incidence rates are based on the number of fish examined histologically (that is, excluding lost fish) To compare the frequency and types of tumors arising in RP mutant lines with those of the control population, we established the fate of all heterozygotes in a single generation of each of 16 RP mutant lines. In each family, some fish were lost prior to any observation of external symptoms, precluding determination of the cause of death. The rest were sacrificed either when they developed visible masses or when they reached 18 or 22 mo of age, and step sections were examined ( Table 1 ). The 16 RP families fell into three groups with respect to tumor incidence. Six lines had high mortality (including both lost fish and those with external growths) and a high tumor incidence (60% or more, including both fish with gross tumors and tumors detected only upon sectioning). Nearly all of the tumors observed by 22 mo in these lines were zMPNSTs ( Table 1 A). These lines included those with mutations in RP genes S8, S15a, L7, L35, L36, and L36a. Five RP mutant lines made up a second group. These lines had either a moderate incidence of cancer, or had a low incidence but were unusual in having an apparently elevated incidence of zMPNSTs. This group included lines with mutations in L13, L23a, S7, S18, and S29. As in the high-cancer lines, in most lines with moderate cancer incidence, most tumors observed in fish by 22–24 mo of age were zMPNSTs ( Table 1 B). In one line (hi1026, with a mutation in S18 ), however, other tumor types predominated, suggesting that RP mutations can increase the frequency of tumor types besides zMPNSTs. The third group of RP mutant lines included five lines that were not tumor prone. These lines, with mutations in L3, L24, LP1, S12, and S15, were indistinguishable from controls in tumor incidence and spectrum ( Table 1 C versus 1 D). In summary, 11 of 16 RP mutant lines had an elevated incidence of cancer, and most of these 11 lines are predisposed to develop zMPNSTs. Together these findings suggest that zMPNSTs are rare in our colony except in RP mutant lines. However, because the cancer incidence was low in the control fish, we observed only 17 tumors in this group of fish in the experiment described above. Furthermore, only four of these 17 tumors were grossly visible, with 13 being detected only after sectioning. To obtain more data on tumor spectrum in our colony, including the types of tumors that present as externally visible growths in non-RP mutant lines and wild type, we sought out fish with externally visible tumors from throughout our colony, coded them to avoid bias, and identified the tumor types by histological analysis of step sections. In total, we analyzed gross tumors from 41 control fish (wild type or non-RP mutant lines, including the four tumors found above). We also analyzed a total of 65 RP heterozygotes with grossly visible tumors (including the fish represented in Table 1 A– 1 C). Figure 2 shows a comparison of the types of tumors in control versus RP mutant lines that presented as externally visible growths. In the control fish, seminomas accounted for 57% of these tumors, while a wide variety of other tumor types, including ultimobranchial gland tumors, neuroblastomas, islet cell adenomas, and lymphomas, each arose at low frequency. Overall, 69% of the grossly visible tumors observed in non-RP fish were benign. Only 10% of these externally visible tumors were zMPNSTs (see below). In contrast to the control fish, and as is apparent from the data in Table 1 , the majority of grossly visible tumors in the RP mutants were zMPNSTs (81%), greatly exceeding the number of seminomas (4%) or other (15%) tumor types ( Figure 2 ). Since fish with external growths were found far more often within RP families than in the colony at large, the dramatic shift in the spectrum of tumors in RP relative to non-RP mutant lines reflects the profound increase in incidence of zMPNSTs rather than any obvious reduction in the incidence of seminomas and other tumor types. Figure 2 The Tumor Spectrum in Fish Heterozygous for Mutations in RP Genes Shows an Increased Proportion of zMPNSTs Fish with apparent masses were selected and processed for histological analysis. Numbers are shown as percent of the total number of diagnosed tumors from either population. The control group includes 42 tumors from 41 fish, including both wild-type and non-RP family transgenics. The RP group includes 68 tumors from 65 RP heterozygotes from 18 different lines representing mutations in 16 different genes. The “other” tumor category includes pancreatic islet adenomas, ultimobranchial gland tumors, neuroblastomas, retinoblastomas, lymphomas, ganglioneuromas, ductal carcinomas, gastrointestinal adenocarcinomas, hepatocellular carcinomas, leukemias, meningiomas, and histiocytic sarcomas. As noted above, we detected zMPNSTs in only four of 41 control fish with grossly visible tumors. Two of these fish, aged 15 and 24.5 mo, were from the hi3332 line, the only non-RP line in which more than a single zMPNST has been observed to date. Significantly, the viral insertion that is linked to the embryonic lethal phenotype of this line lies within one (NF2a) of two distinct zebrafish genes that are highly homologous to the mammalian neurofibromatosis type 2 gene (NF2). The insertion abrogates expression of this gene in homozygous mutant embryos ( Figure S1 and data not shown). NF2 was originally identified as a tumor suppressor gene that predisposes individuals to develop tumors of the nervous system ( Trofatter et al. 1993 ; Ruttledge et al. 1994 ). Given this finding, we screened the remaining 53 fish in this family for tumors between 17.5 and 23 mo of age by sectioning. Seven of these 53 fish had small spindle cell tumors. These tumors were not identical to typical zMPNSTs found in RP families, but shared some key characteristics (data not shown). Given the elevated incidence of rare tumor types including zMPNSTs, we conclude that NF2a acts as a tumor suppressor gene in fish, as it does in mammals. Early Mortality in an RP Mutant Line Results from Multiple Types of Cancer The experiment described above identified six RP mutant lines with high mortality. While some of the mortality could be accounted for by fish that displayed gross tumors and therefore were removed from the tanks before they died, many fish simply disappeared or were found dead and were too deteriorated to be analyzed histologically. To determine whether early mortality in these lines was entirely due to lethal cancers, and if so, whether it was due to zMPNSTs or to other tumor types, we performed two experiments using fish from the early-mortality, high-tumor hi10 line. In one experiment we screened hi10 heterozygotes and their wild-type siblings weekly for evidence of ill health or externally visible growths in an effort to catch all sick fish before they died or were lost. Sickly fish were sacrificed and subjected to histological examination, as were all of the fish that still appeared healthy at 22 mo of age. The results are shown in Figure 3 . Only the RP heterozygous carrier fish displayed early mortality, and, as anticipated, this was due to cancers. Strikingly, among tumors found by 15 mo of age, while two were zMPNSTs, one was a retinoblastoma and three were lymphomas, tumor types that, like zMPNSTs, arise infrequently in our control populations. The tumors detected in the older fish were predominantly zMPNSTs. By the endpoint of the experiment (22 mo) all of the noncarrier sibling controls appeared healthy, and step sectioning detected only one tumor-bearing fish among 13, a frequency comparable to the control population. These results support the conclusion that the early mortality observed in the hi10 line is the result of lethal tumors, and reveal that these include zMPNSTs but also other tumor types. Figure 3 Rate of Tumor Appearance in hi10 Heterozygotes A cohort of 28 hi10 fish and 13 of their noncarrier siblings were observed over 22 mo for the appearance of ill health or externally visible tumors. Symptomatic individuals were sacrificed, fixed, and sectioned for histological analysis. The graph represents the percentage of fish remaining over time, with the diagnosis of each removed fish. Three fish labeled “dead” died before fixation and had too much tissue damage to establish a diagnosis. Also, seven of the carrier fish (though none of the noncarriers) were lost to unknown causes over the course of the experiment; while they most likely died, to be conservative these were removed from the total number of fish charted. At 22 mo, the remaining externally healthy fish (4/21 carriers, 13/13 noncarriers) were also histologically examined, and the status of these fish is indicated. Further evidence that fish from the hi10 line are predisposed to multiple tumor types was obtained in the second experiment, in which we sectioned hi10 heterozygotes and their noncarrier sibling controls (specifically including any sick or growth-bearing fish along with apparently healthy fish) at approximately six-week intervals between eight and 14 mo of age. As shown in Table 2 , we found both grossly visible and occult zMPNSTs and other tumor types in the hi10 carrier fish. Thus, the hi10 line (and presumably other high-mortality RP lines) is predisposed to multiple tumor types, though particularly strongly predisposed to develop zMPNSTs, especially at later time points. Table 2 Onset of Tumor Development in hi10 Fish and Noncarrier Siblings a One fish at each of these time points had two tumors Carriers: starting population was 70 fish; seven fish were lost over the course of the experiment. Noncarriers: starting population was 92 fish; three fish were lost over the course of the experiment; 32 externally healthy fish at the end of the study (14 mo) were not histologically examined RP Genes May Be Haploinsufficient Tumor Suppressors Dominant mutations that predispose vertebrates to cancer can be activated oncogenes, recessive tumor suppressors, or haploinsufficient tumor suppressors ( Largaespada 2001 ). Several lines of evidence suggest that RP mutant genes may be acting as haploinsufficient tumor suppressors in zebrafish. The mutagenic inserts in all of our RP mutant lines reduced or eliminated expression of the RP gene, as determined by RT-PCR and, in some cases, Northern blotting ( Figure 4 A and data not shown). Thus, most if not all of these viral insertions appear to be loss-of-function mutations. This suggests that the RP genes are not mutated to form activated oncogenes, but rather may act as tumor suppressors. In mammals, the most frequent mechanism of inactivation of recessive tumor suppressor genes is the acquisition of a mutation (either germline or somatic) in one allele and subsequent loss of the wild-type allele through loss of heterozygosity (LOH) ( Haber and Harlow 1997 ). Thus, we investigated whether the wild-type RP gene had been lost in the zebrafish tumors. We isolated both normal and tumor tissue from three RP heterozygous mutant lines, hi10, hi258, and hi1974, each of which showed a reduction in expression of its respective RP mutant gene of 10-fold or more ( Figure 4 A) and examined DNA from these samples for the presence of the mutant and wild-type RP alleles by PCR ( Figure 4 B). In every case, we detected the wild-type allele, arguing against LOH in these tumors. A concern is that tissue contamination can yield misleading LOH results, particularly because the red blood cells of fish are nucleated. Thus control PCR experiments were performed in which DNA samples from heterozygous and homozygous embryos were mixed at different ratios. The results show that our assay was sensitive to a decrease as small as 3-fold in the relative amount of the wild-type allele (data not shown). Thus, unless the tumor samples contained more than 33% nontumor cells, we can conclude that the wild-type RP alleles were not lost in these tumors and thus the RP genes are probably not recessive tumor suppressors. In one of the tumor samples shown in Figure 4 , tumor hi10–1, the wild-type allele appears not only to be present but possibly at higher concentration than the mutant allele, and Southern analysis of this same DNA sample supported this observation (data not shown). Thus, in this particular tumor the mutant allele may have been lost and only the wild-type allele retained. Figure 4 RP Genes Appear to Be Haploinsufficient Tumor Suppressors (A) RP mutations decrease the amount of RP gene expression. RNA was prepared from 3-d-old homozygous mutant embryos and their wild-type siblings, and serial dilutions of first strand cDNA were used as templates for PCR. The decrease in expression in the mutants can be determined by the difference in the dilution between wild type and mutant where the PCR product amount diminishes. The actin control shows that the total amount of mRNA was the same between samples. (B) LOH is not observed in RP mutant tumors. DNA was prepared from tumors (T) and normal tissue (N) from the same fish, and PCR was conducted with three primers that show the presence or absence of both the insert-bearing (mutant) and wild-type chromosomes. In each case, the upper band is the wild-type chromosome and the lower band is the insert-bearing one. hi10 fish #1 normal (lane 1), tumor (lane 2); hi10 fish #2 normal (lane 3), tumor (lane 4); hi258 fish normal (lane 5), tumor (lane 6); hi1974 fish normal (lane 7), tumor (lane 8). In mice, a tumor cell line has been described in which one copy of an RP gene is deleted and the other copy has suffered a mutation that may contribute to tumorigenesis ( Beck-Engeser et al. 2001 ). To rule out the acquisition of a point mutation in the wild-type allele in RP mutant tumors, all of the coding exons of the appropriate RP gene and at least 50 bp of intronic sequence flanking them were sequenced from each normal and tumor DNA sample. There was no indication of any point mutations in any of the tumors. The apparent retention of the wild-type allele in the tumor cells in these samples, and the fact that no point mutations were observed in the wild-type RP genes in the tumor cell DNA, suggests that it is not a second hit in these loci that leads to tumorigenesis. Rather, the data obtained suggest that these genes function as haploinsufficient tumor suppressors in zebrafish. RP Mutations Alter the Relative Amounts of 18S and 28S rRNAs In yeast, a decrease in the amount of at least some RP genes results in a reduction in the amount of the corresponding ribosomal subunit and a reduction in the number of assembled ribosomes ( Moritz et al. 1990 ). To determine if this is also true in fish, we examined the relative amounts of 18S and 28S rRNA in homozygous mutant embryos compared to sibling controls. Embryos from heterozygote crosses of lines hi10, hi1974, and hi2649 were sorted by phenotype at 3 d post-fertilization, and total RNA was prepared from pools of mutant or phenotypically wild-type sibling embryos. Electrophoresis and ethidium bromide staining were used to determine the amounts of 18S and 28S RNA, which we assume reflect the amounts of 40S and 60S ribosomal subunits, respectively ( Figure 5 ). As a loading control, the same RNA samples were subjected to Northern analysis and probed for beta actin ( Figure 5 ). In each case we observed a decrease in the overall amount of rRNA, and, significantly, a preferential loss of the rRNA found in the ribosomal subunit with which the mutated RP was associated. Thus in hi10, in which a component of the large ribosomal subunit was mutated, while both 18S and 28S RNA levels were decreased, the level of 28S RNA was affected more than that of 18S. Conversely, in hi1974 and hi2649, in which components of the small ribosomal subunit were mutated, the 28S RNA levels were mildly reduced, but 18S RNA was sharply decreased. In none of these cases was the actin level reduced, so the effect was not simply a result of a reduction of cell number, RNA degradation, or cell death. Thus, as in yeast, RP mutations in fish that result in reduced gene expression lead to a relative decrease in the amount of the subunit to which they belong as measured by a decrease in rRNA. Figure 5 Ribosomal RNA Levels Are Reduced in RP Mutants RNA was prepared from 3-d-old homozygous mutant embryos or their wild-type siblings from lines hi10 (L36a), hi1974 (S8), and hi2649 (S15a), and RNA content was visualized by electrophoresis and ethidium bromide staining. The ratio of 28S/18S as determined by densitometry is shown below each lane. Note that L36a mutants show a preferential loss of the 28S band by 1.5-fold, while S8 and S15a mutants show a preferential loss of the 18S band by 1.9- and 1.8-fold, respectively. These RNAs were also northern blotted and probed for beta actin as an mRNA content control. Discussion In this study, we have found that heterozygous mutations in 11 different ribosomal protein genes predispose zebrafish to cancer, predominantly to zMPNSTs, but also to other rare tumor types. All of these mutations reduce RP gene expression, indicating that these 11 genes are not oncogenes. Moreover, in the tumors we examined, the wild-type allele appeared to be present and did not contain point mutations; thus these genes are not recessive tumor suppressors. Rather, our findings suggest that these 11 genes are haploinsufficient tumor suppressor genes; that is, reducing their activities by about a factor of two increases the likelihood of cancer. These findings raise two important, unanswered questions: first, how do these mutations lead to cancer, and second, do similar mutations cause cancer in humans? How Do These Mutations Cause Cancer? The finding that mutations in so many different RP genes, including S7, S8, S15a, S18, S29, L7, L13, L23a, L35, L36, and L36a, predispose to cancer suggests that a function shared by RPs underlies their role in this phenotype. However, not all RP genes were cancer genes: S12, S15, L3, L24, and LP1 heterozygotes appeared normal. This raises the possibility that the oncogenic RP genes could conceivably share some novel biological function independent of their role in the ribosome and that inhibition of this function leads to tumor formation. Individual RPs have been implicated in a wide variety of biological functions, including cell cycle progression, apoptosis, and DNA damage responses ( Ben-Ishai et al. 1990 ; Sonenberg 1993 ; Chen et al. 1998 ; Chen and Ioannou 1999 ; Hershey and Miyamoto 2000 ; Volarevic et al. 2000 ; Volarevic and Thomas 2001 ; Lohrum et al. 2003 ), and it has been suggested that their role in these processes may arise independently of their role in the ribosome itself ( Wool 1996 ; Wool et al. 1996 ; Soulet et al. 2001 ). However, it seems somewhat unlikely to us that there could be such an important, yet still undetected function involving so many different RPs. Thus, we favor the possibility that it is a shared, ribosome-associated function that allows them to be tumor suppressors. If so, then why were not all RP genes cancer genes in this study? At present we can only speculate. We have not found any correlation that distinguishes the RP genes that predispose to cancer from those that do not. Both can belong to either the large or the small ribosomal subunit, and all the mutants show reduced gene expression. Possibly some RP genes are normally expressed at higher levels than others, so that a 50% reduction in their expression does not reduce their protein level below some critical, hypothetical threshold required for tumor suppression. The best-known function shared by RPs is their role in the assembly of ribosomal subunits, and as a result, their role in translation. In homozygous mutant fish embryos, the RP mutations reduce the amount of the rRNA of the subunit to which they belong, and hence almost certainly reduce the amount of the corresponding ribosomal subunit relative to the remaining subunit. In yeast this is known to reduce the number of ribosomes, and thus also to reduce the amount of protein synthesis. How might this predispose to cancer? In truth, we do not know, and suspect that understanding the mechanism that explains these findings will lead to new insights into growth control. At present we can only list our speculations and several relevant observations. Reduced protein synthesis could lead to a reduction in the level of a critical tumor suppressor protein, or of a positive regulator of apoptosis or differentiation, either of which could favor growth. A reduction in ribosome number might signal the cell to try to overcome the deficit by making more of the components required for ribosome biogenesis, and this in turn might promote cell growth. Alternatively, a reduction in the number of ribosomes might alter the identity of the messages recruited to ribosomes—similar to the way that modulation of the translational capacity of mammalian cells by oncogenes such as Ras or Akt is known to alter the identity of mRNAs recruited to polysomes—changing the translation rate of growth-promoting genes ( Rajasekhar et al. 2003 ). Finally, and most speculative of these possibilities, reduced ability of a ribosomal subunit to assemble properly might generate a signal that cells interpret as growth-promoting. For example, degradation of excess rRNA, a molecule with many hairpins, might generate such a signal in the form of RNAi. Are RP Genes Cancer Genes in Other Vertebrates? Given that so many different RP genes can be cancer genes in fish, it seems surprising that they are not already a well-known class of cancer genes in vertebrates. Only two examples are known that suggest a role for RP mutations in mammalian tumor susceptibility, one in mice and one in humans. In the mouse study, two independent murine tumor cell lines were found to express tumor antigens that were mutated RPs ( Beck-Engeser et al. 2001 ). In both cases, the tumors were found to become more aggressive upon either loss or mutation of the wild-type allele of the RP gene. It was postulated that the mutant RPs might have an oncogenic activity that was suppressed by the wild-type protein. Such a mechanism does not seem to be involved in the tumors that develop in the RP mutant fish described here, since we failed to detect evidence of oncogenic activation of RP genes. In humans, there is a possible association of mutations in one particular RP gene with cancer: approximately 25% of both sporadic and familial cases of Diamond-Blackfan anemia (DBA) are associated with a mutation of rpS19 ( Draptchinskaia et al. 1999 ), and this syndrome includes an increased risk of developing leukemia ( Wasser et al. 1978 ). It has been demonstrated that the anemia is likely due to a block in erythroid differentiation ( Hamaguchi et al. 2002 ), but it is currently unclear whether the leukemia is an indirect result of the anemia, caused by a stimulation in the production of hematopoietic precursors, or whether the rpS19 gene dosage plays a direct role in tumorigenesis. It is important to note that DBA is a multigenic disease with very heterogeneous clinical presentation. While DBA patients in general have an increased predisposition to certain cancers, it is not yet clear whether this is true of the subset whose DBA is caused by rpS19 mutation. While these examples from mouse and human are consistent with the idea that mutations in individual RP genes might contribute to tumorigenesis in mammals, they have seemed to be unusual examples, rather than suggesting that RP genes in general might be potential cancer genes. Our study suggests for the first time, we believe, that this is a general property of many RP genes. The possibility that a reduction in ribosome levels might be oncogenic in mammals is further supported by the fact that mutations in DKC1, a pseudouridine synthase that is required for rRNA processing and for properly functioning ribosomes, cause dyskeratosis congenita, a disease characterized by both premature aging and increased tumor susceptibility ( Ruggero et al 2003 ). If RP genes frequently cause human cancers, it is not at all certain that their role would have been detected. Even a deliberate search for their involvement in human cancers would be difficult because there are so many (80) RP genes. This plethora of genes, the fact that it is hard to know which tumor type(s) to examine for RP mutations, and the fact that the mutations might lie in regulatory elements rather than protein-coding regions of the genes would make such a search difficult. Nonetheless, given the high degree of conservation of biological mechanisms among vertebrates, it seems likely that rp mutations will prove to increase the incidence of tumors in humans as they do in zebrafish. If so, it may be advantageous to devise diagnostic strategies based on ribosomal protein levels or on a function that these proteins share, for example, in translation, rather than on the analysis of such a large number of individual genes. In summary, by examining aging populations of mutant lines of fish with defects in embryonic essential genes, we identified a novel group of cancer genes. The ability to identify cancer genes by screening populations of fish heterozyogous for recessive embryonic mutations and the reassuring finding that NF2a is a tumor suppressor gene in this system demonstrate the power of large-scale, forward-genetic screens in the zebrafish to identify new disease susceptibility genes. Materials and Methods Mutagenesis and maintenance of mutant lines The insertional mutagenesis screen was carried out as previously described ( Amsterdam et al. 1999 ). Stocks of all lines were maintained by outcrossing heterozygotes to nontransgenic fish, preparing DNA from tail fin biopsies of 8- to 18-wk-old fish, and performing PCR with insert-specific primers for each line to identify heterozygotes. Fixation and histology Adult fish were euthanized in ice water and fixed within 30 min in Bouin's solution, embedded in paraffin, and sectioned as previously described ( Moore et al. 2002 ). LOH analysis DNA was prepared from tumor tissue or tail tissue isolated from fish prior to fixation for histology. PCR was conducted with one primer complementary to proviral sequence and two primers complementary to sequences on either side of the insertion for the appropriate mutation. Primer sequences were as follows: hi10: 10gen5 (5′-CAGCACAGATTCTTGAAAGCGCC-3′), 10gen3 (5′- GCATATGTAGCATCTCGAAGGTCC-3′), and NU3X (5′- TGATCTCGAGCCAAACCTACAGGTGGGGTC-3′); hi258: 258A5a (5′-GGTACGTCTGTGCTTATGTTTGTGTC-3′), 258A3a (5′-TCTCAAGACTTCATCCATTCATAATTCTGC-3′), and NU3X; hi1974: 1974c1 (5′-CTACACCACAGGTATCTCAAGGG-3′), 1974c1est3 (5′-CCACCACGGACTCTTATTGTGTG-3′), and IPL3 (5′-TGATCTCGAGTTCCTTGGGAGGGTCTCCTC-3′). RNA analysis RNA was prepared from mutant and wild-type embryos using Trizol reagent (Invitrogen, Carlsbad, California, United States). For RT-PCR, serial dilutions of first strand cDNA were amplified for 30 (hi1974) or 35 (hi10 and hi258) cycles using the following primers for the genes indicated: rpL36a: 10rt5 (5′-CAACCATGGTAAACGTACCGAAG-3′) and 10RTR (5′-CACAAAAGAAGCACTTGGCCCAGC-3′); rpL35: 258RTF2 (5′-GCTGCTTCCAAGCTCTCAAAAATCC-3′) and 258RTR (5′-TGCCTTGACGGCGAACTTGCGAATG-3′); rpS8: 1974RTF1 (5′-TCTCAAGGGATAACTGGCACA-3′) and 1974RTR1 (5′-GAACTCCAGTTCTTTGCCCTC-3′); actin: actinF (5′-CATCAGCATGGCTTCTGCTCTGTATGG-3′) and actinR (5′-GACTTGTCAGTGTACAGAGACACCCT-3′). For visualization of 18S and 28S RNA, two embryo equivalents of RNA were electrophoresed through a nondenaturing agarose gel containing 0.5 μg/ml ethidium bromide. For detection of beta actin RNA, four embryo equivalents of RNA were electrophoresed through a 7.5% formaldehyde/MOPS-buffered agarose gel, blotted to Hybond N+ (Amersham Biosciences, Little Chalfont, United Kingdom), and hybridized with a random primed beta actin probe. Supporting Information Figure S1 Position of Mutagenic Insertions The genomic sequence of part of each of these genes is represented as exonic (boxed) and promoter or intronic (line). White boxes represent 5′ UTR while shaded boxes represent coding exons. Where no white boxes are shown, the location of the 5′ UTR and beginning of the coding region has not been determined relative to the part of the locus shown here. In all cases, at least one coding exon (and all of the 3′ UTR) is downstream of the region of the gene represented here. The position and orientation of the proviruses are shown above each genomic sequence. All drawings are to the scale of the top scale bar, except the rpl36 locus, which has its own scale bar. (62 KB PDF). Click here for additional data file. Accession Numbers The GenBank ( http://www.ncbi.nlm.nih.gov/Genbank/) accession numbers for the genes discussed in this paper are L13 (AY561516), L23a (AY561517), L24 (AY099532), L3 (AY561514), L35 (AF506205), L36 (AY561518), L36a (AY099511), L7 (AY561515), LP1 (AY561519), NF2a (AY561520), S12 (AY561510), S15 (AY561511), S15a (AY561512), S18 (AY099517), S29 (AY561513), S7 (AY561508), and S8 (AY561509) . | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC406397.xml |
544832 | Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics | Background Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. Results Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. Conclusion The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings. | Background Traditional immunoassay platforms have very limited multiplexing capability and high sample volume requirement. The development and application of high throughput, multiplex immunoassays that measure hundreds of known proteins in complex biological matrices, is becoming a significant tool for quantitative proteomics studies, diagnostic discovery and biomarker-assisted drug development [reviewed in [ 1 - 4 ]]. Two broad categories of antibody microarray experimental formats have been described: [ 1 ] direct labelling, single antibody experiments, and [ 2 ] dual antibody, sandwich immunoassays [ 4 ]. In the direct labelling method, all proteins in a complex mixture are tagged, providing a means for detecting bound proteins following incubation on an antibody microarray. In the sandwich immunoassay format, proteins captured on an antibody microarray are detected by a cocktail of detection antibodies, each antibody matched to one of the spotted antibodies. In addition, a variety of microarray substrates have been described, including nylon membranes, plastic microwells, planar glass slides, gel-based arrays and beads in suspension arrays. Much effort has been expended in optimizing antibody attachment to the microarray substrate. Finally, various signal generation and signal enhancement strategies have been employed in antibody arrays, including colorimetry, radioactivity, fluorescence, chemiluminescence, quantum dots and other nanoparticles, enzyme-linked assays, resonance light scattering, tyramide signal amplification and rolling circle amplification. Each of these formats and procedures has distinct advantages and disadvantages, relating broadly to sensitivity, specificity, dynamic range, multiplexing capability, precision, throughput, and ease of use [ 1 - 4 ]. In general, multiplexed microarray immunoassays are ambient analyte assays [ 5 ]. Given the heterogeneity of antibody array formats and procedures currently in use in proteomics studies, and the absence of a "gold standard", there exists an urgent need for development and adoption of standards that permit platform comparisons and benchmarking. Unique, general considerations in assembling multiplexed immunoassays include: Requirements for elimination of assay cross-reactivity; configuration of multi-analyte sensitivities; achievement of dynamic ranges appropriate for biological relevance when performed in diverse matrices and biological states; and optimization of reagent manufacturing and chip production to achieve acceptable reproducibility. In contrast to traditional monoplex enzyme-linked immunoassays, generally agreed specifications and standards for antibody microarrays have not yet been formulated. A number of recent articles have started to examine certain of these issues [ 3 , 6 , 7 ]. Microarray immunoassays performed on planar glass slides and employing signal enhancement with rolling circle amplification (RCA), have been developed by several groups and have demonstrated usefulness in measurements of temporal and dose-dependent changes in a variety of immunological model systems and human diseases [[ 1 , 2 , 8 - 16 ]; Patel, D.D. et al. Submitted]. In general, these RCA microarray immunoassays have utilized indirect sandwich immunoassays featuring five steps (Figure 1 ): Figure 1 Schematic layout of antibody microarray slide and RCA immunoassay. At the far left is an illustration of the 1" × 3" slide platform containing sixteen individual sample wells with an etched barcode. Within each of the wells, a 16 × 16 configuration of printed capture antibodies is arrayed. Each of the capture antibodies is capable of binding analytes from applied samples and undergoing RCA signal amplification. Finally, the fluorescently labeled signal, detected through conventional laser scanning, is quantified. I. Analytes in an applied sample bind to capture antibodies immobilized on a silanized glass surface. II. Applied secondary biotinylated detector antibodies bind to captured analytes, creating a highly specific immune complex. III. Biotinylated detector antibodies bound to the immune complex are detected with a universal anti-biotin antibody. The latter is conjugated to primer oligonucleotides that are pre-annealed to a complementary circular oligonucleotide. IV. DNA polymerase extends the 3' ends of primers around the circles, resulting in long, single stranded RCA products that remain attached to the complex. The RCA product, composed of tandem DNA repeats complementary to the circle sequence, is detected by hybridization with cyanine 5 (Cy5)-labeled complementary oligonucleotides. The present report describes initial development of standardized operating procedures, quality controls and standards for microarray immunoassays performed on planar glass slides using signal enhancement with RCA. These metrics have been tested for use in generation of data with adequate sensitivity, reproducibility and assay performance for biomarker discovery [[ 12 - 14 , 16 ], Patel D.D et al., submitted]. Initial specifications and standards are also described for the addition of new analytes to antibody microarrays, which are needed to ensure that a high level of performance is maintained. While certain of these recommendations and standards are specific to RCA immunoassays, others represent generally applicable first generation standards for benchmarking antibody array platforms that enable interoperability of data generated in proteomics studies. Results Data Quality To demonstrate the feasibility of using a multiplex immunoassay system to measure protein levels in complex biological matrices, the performance of dual-antibody, sandwich immunoassay arrays performed on planar glass slides with RCA signal enhancement was evaluated for specificity, sensitivity, reproducibility and accuracy using standardized titrations, spiked biological matrices and clinical samples. Array performance was evaluated based on ability to: measure analytes across a broad dynamic range at sufficiently low coefficients of variation (CVs); detect proteins at levels requisite to capture biologically relevant expression differences; confirm reliability of methods to normalize data to minimize platform imprecision and demonstrate the utility of generating standard curves to convert analyte MFI (mean fluorescence intensity) data into mass unit information. Data Redaction An advantage of arrays is the ability to measure each analyte multiple times, enhancing precision. Capture antibody spots were printed in quadruplicate on planar glass slides providing redundancy of individual analyte measurements. Data redaction was applied to raw immunoassay data to improve data quality by eliminating outlier data points. Outliers were identified by employing two subsequent statistical approaches in a step-wise manner. First, the Bland-Altman plot was used. Bland-Altman plots are often used in DNA microarray analysis to identify differences and/or replicate outliers. This involves plotting the difference between the logarithm of intensities of two replicates (M) versus the average of logarithm of intensities (A) for each analyte within an individual array (see Material and Methods). Thus, there will be 6 MvA plots for each data set to reflect the 170 analytes positioned across 6 arrays. Each MvA plot will contain 3*Ns*Na points, where 3 reflects the number of possible unique pair wise combinations of the three replicates, Ns represents the number of samples and Na defines the number of analytes measured on a given array. An example of an MvA plot produced in a project comprising 150 clinical serum samples for Array 4 with 37 analytes is shown in Figure 2 (panel a). This plot contains 3*150*37 = 16650 data points. The quadruplicate measurements within an arrayfor each anlayte are represented as a mean replicate value.. Lines represent 99% confidence intervals for individual data points. Data points outside of 99% confidence intervals are considered outliers. The quality and /or intensity of individual spots are manually investigated for each outlier by using proprietary visualization software, which allows examination of individual spot image/quality at every data processing step. Outliers are redacted by removing aberrant spots from the data set. The resulted MvA plot is shown on Figure 2 (panel b). Figure 2 An example of raw data quality and outlier removal. (panel a, top) Raw data (37 analytes) from array 4 containing all sample replicates shown on an MvA plot (a typical microarray data plot of the log ratio vs. the log difference for each pair of intensities. See: Dudoit, S., Yang, Y. H, Callow, M. J., and Speed, T. P. (2002) Statistica Sinica 12 , 111–140). The dashed lines indicate a 99% confidence interval around the data and outliers of this interval are shown in red, black or magenta. (panel b, bottom) Redacted data with 1% of outlier data removed (all points outside of the displayed confidence interval). The second step of data reduction involves a linear correlation analysis. Pair-wise correlation analysis is done between all replicates of individual sample. Figure 3 shows the three scatter plots generated for the three replicates of a representative sample. The correlation coefficient (R 2 ) is examined for each plot. Each plot contains Na data points, where Na reflects the number of analytes. Plots with R 2 values <0.95 are examined to identify the cause of the poor correlation. We have identified two major sources of poor correlation: incorrect positioning of the capture grid during image quantitation and general aberrations in image spot quality. Assigning the specific source of low correlation is accomplished by tracing back to the image data. In the case of grid misplacement, suspect data images are re-quantified. Poor correlations due to aberrant spot morphology/intensity are manually examined and removed from data set. If the R 2 value does not improve as a result of outlier removal, the replicate is redacted from the data set. The sample is considered passed if there are two replicates with R 2 >= 0.95. The pass rate is defined as the number of passed samples divided by the total number of samples. A run of an array is considered to be passed if 85% of the samples have two or more passed replicates. Figure 3 Pair wise scatter plots between three replicates of a sample. Each replicate was assayed on a different slide. Solid lines represent linear regression fits. Regression equation is indicated within legend box along with the individual slide barcodes for this particular assay. R 2 value of the fit is indicated in the title. Both X and Y-axes indicate mean fluorescence signal Log 2 (MFI). In our experience, applying the MvA statistical approach first, followed by the linear correlation analysis is an efficient process to identify outliers without compromising data throughput. Since, MvA plots can be generated quickly, it allows for relatively fast redaction of significant outliers using an objective semi-automated approach. In contrast, the sample correlation analysis is considerably more labor intensive and currently requires manual investigation of each scatter plot with R 2 values < 0.95. This process reduces throughput of data redaction, particularly on large data sets. Table 1 shows the impact of using MvA plot analysis as a first step approach for outlier removal in a clinical project containing 106 samples. Each assay in Table 1 represents a single sample replicate, with a total possible number of assay points equal to 418 (106*3 = 418). The table reflects an assay count of 417 due to one sample having only two replicates due to a shortfall in sample volume. The correlation analysis performed on all sample replicates increased the pass rate by 8% following outlier removal. This improvement was due to the elimination of individual analyte replicates having a negative impact on total sample correlation derived from all analyte replicates within an array (Table 1 ). Table 1 Improved sample pass rates achieved through individual analyte data reduction Before After Total Assays (#) 357 393 417 Assays (%) 86 94 100 In general, for data sets with more than 40 samples, outlier removal only demonstrated small improvements in reducing average CVs across all samples. The most significant impact of outlier removal is on improving reproducibility across the three replicates of the individual samples. In our experience, outlier removal has been shown to reduce individual sample replicate CVs by 2–3 fold. This effect is directly related to improving sample correlation pass rates by by 10–20%. Normalization Many systematic factors can modify spot intensity during the process of measurement. Normalization is the process of reducing the effects of systematic variation on spot intensity. Normalization in DNA microarrays typically involves adjusting distributional summaries of data (mean, median) from each chip to common reference values. For example, one assumption could be that the average signal from each protein chip should be the same, as with DNA microarrays and the difference between replicate values is due to systematic variability in the measurement process. Unfortunately, the nature of protein antibody microarrays, configured with a multiplex of individual capture and detector antibodies, is more specialized and differentiated than that of a DNA microarray. Use of a single reference factor derived from a global value is not sufficiently refined to take into account the difference in platform configuration. In the current report, the organization of protein microarrays allows the measurement of up to 16 samples per slide (chip). This is very different from DNA microarrays where one chip represents the total collection of measured values for an individual sample. To accommodate the differences inherent to the platform, we have applied a normalization strategy based on the three major sources of technical variability observed in our system. The first type of variability relates to spot-to-spot differences observed between quadruplicate spots of the individual analytes printed within a sample well. The second level of variability can be described as the difference in measurements between wells within the same slide. The third element of variability represents the variability observed between sample wells compared across different slides. We found that slide-to-slide variability is the largest source of variation accounting for more than 70% of the total measurement imprecision (data not shown). Thus the goal of normalization is to reduce the imprecision of slide-to-slide measurement error since this represents the major source of platform variability. Normalization is performed using a system of standard controls to reduce the effect of slide-to-slide variability. A series of four standard control samples (see "Anchor Point Calibrators" in Methods and Materials) are run in 4 wells of each slide. Each control sample represents a cocktail of the full repertoire of analytes for the given array tittered at 4 specific concentrations. The standards have been optimized at concentrations (12 pg/ml, 111 pg/ml, 333 pg/ml and 1000 pg/ml) to capture measurements across the linear range of detection for each analyte. The global average of total analyte signal for the four prepared controls is calculated across all slides run in a batch. An adjustment factor is created for each slide that reflects the difference between global intensity average for all slides and the individual intensity average based on the controls from the individual slide. The averaged pixel intensity of each spot on the slide is scaled by the adjustment factor. As an example, the average value of the adjustment factor was evaluated across a batch of 33 slides and found to have a value of 1.33+/- 0.47. The primary benefit of normalization was in reducing the replicate sample CVs. Figure 4 contains two panels revealing the impact of normalization on individual analyte CVs across a series of samples for a given analyte. The upper panel shows the variation in raw MFI signal intensities on a logarithm scale observed between the 3 replicate measurements for each of the 11 samples. The lower panel reveals the impact of normalization on reducing variability. Normalization typically reduced sample replicate CVs an average of 5% without producing rank order changes in analyte MFI. Figure 4 Effect of Normalization. The top panel reveals the raw data, shown as the Log 2 (MFI), for the analyte Monokine induced by interferon gamma (MIG) across three replicates with 11 patient samples (numbered on the X-axis). The bottom panel reflects the impact of normalization in reducing variation in intensity within each sample and hence the replicate MFI CV. Assessment of Platform Precision A 15-point series of standardized titrations containing recombinant proteins diluted in buffer were used to evaluate platform precision. This assessment was used in the quality control of each slide lot prior to release, as well as within each client project to verify run-time analyte performance. Six replicates for each point were run in the quality control testing of each slide lot and six replicates of each point were run within each client study to generate standard curves. CVs were evaluated for each concentration of analyte across six slides. Average CVs were calculated for each analyte. Statistical summaries of CV distribution across all array 2 analytes using the standardized 15-point standard titration series are shown in Table 2 . The mean CVs of the control titration replicates were typically in the 10–15% range following normalization. Collectively evaluating mean, median and interquantile range CVs served to identify measurements significantly influenced by outlier values producing a skewed distribution. In general, CVs obtained for the quadruplicate within-well analyte measurements were 5–9% for the prepared controls. Replicate sample CVs obtained from biological samples tended to be somewhat higher than prepared controls with quadruplicate within well measurements at 10–15% post normalization and 20–25% average CVs for replicates samples positioned in wells across different slides. Table 3 reveals CVs obtained in a project containing 110 clinical serum samples run across the 6 arrays. Each sample was tested in triplicate generating 3 replicates measurements obtained from 3 different slides. The average CVs were 18%, 20%, 17%, 20%, 16% and 17 % for Arrays 1, 2, 3, 4, 5 and 6 respectively. The data reduction rate was less than 5% of all data points. This reduction rate is typical of what we have observed across more than 30 clinical projects. Table 2 Mean and standard deviation of analyte MFI CVs from titration standards for a given array %CV Conc. (pg/ml) N* Maximum Mean Minimum Std. Dev. 12 26 19.4 14.0 9.4 2.4 111 26 15.8 9.4 6.1 2.9 333 26 15.3 9.4 4.5 2.5 1,000 26 29.1 12.0 2.6 5.8 3,000 26 26.4 9.7 2.5 6.2 9,000 26 22.2 7.8 2.8 4.3 27,000 26 16.3 8.2 2.5 4.0 81,000 26 19.7 7.8 2.6 4.1 * N reflects 26 analytes measured on array 2. Table 3 Mean and standard deviation of MFI CVs from clinical samples Array N* <CV> Std Dev 1 3856 18.1 11.2 2 3752 19.7 12.3 3 3891 16.9 10.6 4 5211 20.4 15.4 5 3750 16.2 11.2 6 4274 17.4 10.9 * N reflects all analyte measurements for all QC passed sample replicates (project contained 110 samples tested in triplicate). Variance Decomposition A variance decomposition analysis was performed to reveal the extent to which platform error influenced the ability to identify biomarkers. The variance component assigned to platform error was typically found to be an order of magnitude lower than the average inter-individual variation. Figure 5 reveals the contribution of platform error on the total variance observed in a given project for each analyte across array 1. These results indicated the system variability was sufficiently low to capture moderate expression level differences that were reflective of biological change. Figure 5 Variance Decomposition . Example of a variance decomposition analysis performed on the analytes for array 1 in a client study. The X-axis corresponds to analyte name and y-axis corresponds variance. Red blocks reflect platform variation, while green and blue blocks represent inter-patient and inter-treatment variance respectively. Average lower limit of quantitation (LLQ)/ upper limit of quantitation (ULQ) values and analyte dynamic range The left panel of Figure 6 shows a typical dose response curve of MFI (mean fluorescence intensity) versus analyte concentration, generated for a single analyte based on the 3 replicate measurements from the 15-point titration series containing a multiplex of recombinant analytes spiked into buffer at fixed concentrations. Each titration point was replicated across 3 control slides generating 3 replicate measurements. The vertical lines defined the LLQ and ULQ as well as the dynamic range of the individual analyte within a 30% CV of analyte concentration. The right panel of Figure 6 shows the corresponding clinical sample values obtained in the same run revealing the sample values that fell within, above and below the linear range of detection as defined by the standard titrations. Table 4 contains a summary of the average dynamic range obtained for the 170 analytes surveyed over 8 independent runs. Figure 6 LLQ/ULQ . ( Left ) Plot of 3 replicate points from a 15-point titration series of IL-8. The LLQ is indicated by the green vertical line and the ULQ indicated by the rightmost black vertical line. The zero point was removed from the curve fitting procedure since the data undergoes a log transformation. The right panel reveals sample values that fell within and above dynamic range of assay. Here, the majority of tested points for IL-8 fell within the LLQ/ULQ dynamic range. Table 4 Average dynamic range achieved across each of the production arrays Detectable 1 ((W+A)>50%) > 1 log > 1.5 log > 2 log > 2.5 log > 3 log Array 1 59% 96% 78% 41% 0% 0% Array 2 65% 100% 92% 77% 12% 0% Array 3 67% 100% 70% 33% 7% 0% Array 4 92% 97% 92% 54% 16% 3% Array 5 100% 92% 80% 48% 20% 0% Array 6 85% 100% 74% 41% 7% 0% Average 78% 98% 81% 49% 10% 1% Data shown is based on a summary of 8 independent project runs. 98% of the analytes demonstrated at least 1 log dynamic range, 49% of the analytes demonstrated at least a 2 log dynamic range, 10% at least a 2.5 log dynamic range and 1% with at least a 3 log dynamic range. 1 See legend table 5–10 for explanation. Performance assessment A performance assessment of individual analytes was conducted to determine the utility of each analyte across multiple projects covering diverse disease areas. Each analyte was evaluated according to the percentage of clinical samples that fell within (W), below (B) or above (A) the linear range of detection. (Tables 5 , 6 , 7 , 8 , 9 , 10 ) Analytes were considered to be detectable if the percentage of samples that fell in the W+A categories was greater than 50%. The projects surveyed across 8 independent studies containing over 1,000 clinical samples. The disease areas included rheumatoid arthritis, osteoarthritis, systemic lupus erythematosus (SLE), chronic obstructive pulmonary disease (COPD), asthma, diabetes and ovarian cancer. The average percentage of detectable analytes was 56% for array 1, 62% for array 2, 67% for array 3, 73% for array 4, 81% for array 5 and 85% for array 6 across the 8-project survey group. A limited number of analytes (<5%) revealed high endogenous concentrations, producing assay saturation where >90% of the measured samples fell above the linear range of detection. In most cases, this could be resolved by re-running a sample dilution or scanning at a lower gain. Although there were analytes that had detectable percentages below 50%, in many cases these reflected analytes that were only detected under up-regulated conditions associated with specific disease states or conditions of drug induction, revealing value within specific disease or therapeutic areas. Tables 5 , 6 , 7 , 8 , 9 , 10 also reveal the average LLQ/ULQ values of the 170 analytes within a 30% CV of concentration obtained from the control titrations run in parallel with the clinical samples. Table 5 Array 1: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) ANG 1 6 93 99 7 1262 BLC 7 93 0 93 62 4614 EGF 32 65 3 68 347 1184 ENA-78 8 81 12 92 161 9225 Eot 19 81 0 81 186 4454 Eot2 2 83 15 98 23 2313 FGF-7 28 72 0 72 218 19367 FGF-9 67 33 0 33 463 21049 Fas 16 84 0 84 290 39248 GDNF 66 34 0 34 48 7715 GM-CSF 67 33 0 33 67 3626 IL-13 29 71 0 71 29 4458 IL-15 73 27 0 27 4682 52224 IL-1ra 45 54 0 55 71 8960 IL-2sRa 3 94 3 97 20 3975 IL-3 58 42 0 42 852 19428 IL-4 81 19 0 19 43 3548 IL-5 67 33 0 33 13 2438 IL-6 59 34 7 41 14 2291 IL-7 73 27 0 27 32 2396 IL-8 21 65 13 79 6 916 MCP-2 13 84 4 87 42 2144 MCP-3 45 54 1 55 58 3205 MIP-1a 51 46 3 49 464 10315 MPIF-1 9 91 0 91 293 7410 OSM 73 27 0 27 78 8511 PlGF 46 54 0 54 61 3080 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Table 6 Array 2: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) AR 73 27 0 27 48 5599 BDNF 8 87 5 92 26 3956 Flt3Lig 2 98 0 98 17 9835 GCP-2 26 74 0 74 132 13153 HCC4 8 46 46 92 112 7907 I-309 30 70 0 70 20 5142 IL-17 95 5 0 5 330 7921 IL-1a 69 31 0 31 10 2943 IL-1b 46 54 0 54 4 2932 IL-2 89 7 4 11 31 3671 M-CSF 55 45 0 45 86 6761 MCP-1 17 69 14 83 82 2065 MIG 8 87 5 92 13 5030 MIP-1b 29 56 16 71 16 2399 MIP-1d 10 72 18 90 192 6969 NT-3 75 25 0 25 160 22314 NT-4 60 40 0 40 128 19170 PARC 4 25 70 96 12 1870 Rantes 0 13 87 100 5 1302 SCF 29 71 0 71 69 20306 TARC 15 85 0 85 21 3134 TNF-R1 2 97 1 98 108 16285 TNF-a 71 29 0 29 56 6901 TNF-b 88 12 1 12 221 7617 VEGF 86 14 0 14 702 79564 sgp130 0 63 37 100 334 38573 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Table 7 Array 3: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) BTC 84 16 0 16 980 25361 DR6 7 93 0 93 1200 86864 FGF1 60 40 0 40 162 53854 FasL 79 21 0 21 4300 82436 Fractalkine 78 22 0 22 662 12170 GROb 6 91 3 94 66 2505 HCC1 3 28 70 97 164 3610 HGF 70 30 0 30 1039 80079 HVEM 6 94 0 94 636 105560 ICAM-3 0 100 0 100 477 126635 IGFBP2 0 40 60 100 1523 46325 IL2Rg 71 29 0 29 429 41325 IL5Ra 63 37 0 37 1945 57281 IL-9 36 64 0 64 4506 156041 L-Selectin 0 47 53 100 161 28007 Leptin 5 69 26 95 1322 58408 MCP4 21 74 6 79 93 2508 MIP3b 18 82 0 82 40 9211 MMP7 0 99 1 100 70 21138 MMP9 0 51 49 100 3043 163481 PECAM1 6 93 1 94 1033 52935 RANK 17 83 0 83 223 87693 SCF R 3 97 0 97 445 38465 ST2 51 49 0 49 558 66234 TIMP1 0 77 23 100 2010 90647 TRAIL R4 87 13 0 13 4945 122116 VEGF R2 17 83 0 83 1254 138750 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Table 8 Array 4: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) ALCAM 0 100 0 100 991 145528 CD27 10 90 0 90 508 148468 CD30 53 47 0 47 2460 128280 CTACK 0 100 0 100 43 10691 Eot-3 37 63 0 63 130 28149 FGF-2 31 67 2 69 102 5814 FGF-4 57 43 0 43 260 14563 Follistatin 8 92 0 92 138 57120 GRO-g 12 75 13 88 59 4344 I-TAC 11 89 0 89 16 6191 ICAM-1 1 76 23 99 289 29018 IFN-g 39 60 1 61 14 7365 IFN-w 37 58 5 63 1177 42508 IGF-II 0 85 15 100 46 13538 IGF-1R 33 67 0 67 330 91601 IGFBP-1 2 72 26 98 272 85578 IGFBP-3 0 7 93 100 5530 30760 IGFBP-4 0 80 20 100 410 22880 IL-1 sR1 30 70 0 70 534 54857 IL-10rb 12 88 0 88 28 11331 IL-16 28 72 0 72 724 86874 IL-1 srII 19 81 0 81 509 76440 IL-2rb 71 29 0 29 10277 107828 LT bR 14 86 0 86 34 37957 Lymphotactin 28 72 0 72 166 9216 M-CSF R 0 91 9 100 1951 121318 MIP-3a 16 84 0 84 13 3389 MMP-10 10 90 0 90 158 42033 PDGF-Ra 30 66 5 70 8112 151722 PF4 0 23 77 100 67 5458 TGF-a 33 67 0 67 35 2678 TIMP-2 0 12 88 100 130 25224 TRAIL R1 33 67 0 67 21 10956 VAP-1 1 23 76 99 4624 150226 VE-cadherin 1 94 5 99 2652 146826 VEGF-D 34 66 0 66 1370 100539 b-NGF 27 73 0 73 141 12400 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Table 9 Array 5: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) 4-1BB 46 54 0 54 334 92233 ACE-2 37 63 0 63 1138 128330 AFP 4 96 0 96 17 11483 AgRP 18 82 0 82 72 13198 CD141 0 62 38 100 780 14852 CD40 30 70 0 70 101 19145 CNTF Ra 18 82 0 82 46 21212 CRP 4 28 68 96 201 12376 D-Dimer DD5 0 4 96 100 12070 65452 E-Selectin 0 85 15 100 89 21531 HCG 40 59 0 60 345 18736 IGFBP-6 0 2 98 100 855 38589 IL-12p40 44 56 0 56 2505 159213 IL-18 0 100 0 100 5 3743 LIF Ra 45 54 1 55 5350 117637 MIF 3 84 13 97 9753 132966 MMP-8 0 82 18 100 111 48374 NAP-2 0 19 81 100 103 9114 Neut Elast 0 66 34 100 376 24009 P-Selectin 0 82 18 100 2128 93967 PAI-II 28 72 0 72 251 115374 Prolactin 0 96 4 100 1133 77120 Protein C 0 83 17 100 1266 154054 Protein S 0 1 99 100 10808 64646 TSH 43 57 0 57 81 15614 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Table 10 Array 6: Averaged LLQs/ULQs in pg/mL obtained from 15 point standard titrations Feature B W A W+A LLQ (pg/mL) ULQ (pg/mL) 6Ckine 0 100 0 100 152 27541 ACE 0 60 40 100 3283 93777 CA125 19 81 1 81 273 120834 CNTF 67 33 0 33 2562 109254 ET-3 9 83 8 91 881 25735 Endostatin 0 17 83 100 432 9966 ErbB1 1 95 4 99 3864 86553 ErbB2 12 88 0 88 2293 118586 FGF R3 (IIIb) 47 53 0 53 455 89028 FGF R3 (IIIc) 53 47 0 47 214 51823 FGF-6 42 58 0 58 220 18535 G-CSF 69 31 0 31 1487 49342 HB-EGF 41 59 0 59 47 3143 IFN-a 41 59 0 59 20 5021 LIF 52 48 0 48 655 52660 MMP-1 3 97 0 97 537 103951 MMP-2 0 99 1 100 1446 154542 OPN 0 97 3 100 496 60615 PAI-1 0 10 90 100 22 8289 PDGF Rb 14 86 0 86 645 59309 PEDF 0 19 81 100 2599 63199 TGF-b RIII 10 50 40 90 595 13518 Tie-2 43 57 0 57 6005 147662 VEGF R3 10 90 0 90 466 37150 uPA 12 88 0 88 89 16374 uPAR 11 89 0 89 1259 125972 VCAM-1 0 49 51 100 1577 150401 Data shown is from titrations run in 8 client projects (1000 clinical samples surveyed) covering 8 diverse disease areas. The percentage of samples falling below (B), within (W) or above (A) the linear range of detection are presented. The analyte was considered to be detectable if the W+A percentage was above 50%. Validation of Array Performance The development of an antibody array featuring 25–40 novel immunoassays requires extensive validation related to the comprehensive assessment of antibody cross reactivity, definition of analyte minimal detection limits (MDL) and establishing robust assay performance. Each antibody array must be validated for use with several matrices, since the latter may have different ambient analyte levels (and therefore, different ideal MDL) or cross-reactivity profiles. Analyte sensitivity Analyte sensitivity was assessed to identify analytes lacking adequate performance for retention on an array. Additional experiments were performed to determine the endogenous levels of each analyte. For analytes without previously reported biological values, the "0 × n" assays indicated the approximate ambient analyte level. Testing across multiple biological matrices was required, since different matrices affected the detection of analyte specific signals. The "0 × n" experiments also revealed the level of non-specific background which was influenced by the total concentration of antibody load in the detector mix. In our experience, certain plasma matrices were also more likely to generate high background when compared to matched serum samples. The impact of high generalized background is a reduced sample pass rate. When background was observed, the total detector antibody concentration could often be reduced to minimize background noise. Ultimately, a balance between reduction in background and enhancement of sensitivity was required to achieve maximal analyte performance in a mutiplex configuration. Analyte cross reaction The results of the 1 × (n-1) assays identified analytes that demonstrated cross-reaction between the captured analyte and the complex detector mix prepared without the cognate detector antibody. Binding between the spiked analyte and the cognate capture that generated signal, indicated a cross-reaction to one or more non-cognate detector antibodies contained within the complex mix. In cases where non-cognate detector signal was observed, an additional series of experiments were run with the corresponding analyte tested against each of the individual detectors to identify the cross-reacting detector antibody. Since cross reaction is an additive process, the outcome of the cross reaction assessment allowed for adjustments to be made to achieve a balance between maximizing content with multiplexed array specificity. The 0 × (n-1) assays were run to provide a baseline of MFI values to compare to the results obtained in the 1 × (n-1). In addition, the 0 × (n-1) experiments also served to screen the various biological matrices for cross-reactivity with endogenous proteins. Analyte performance under multiplexed conditions Serum MDLs were typically found to be higher than buffer MDLs due to the presence of endogenous analyte, potential analyte-binding proteins present in the biological matrix and other possible matrix-related interferences. The assay conditions used to stress test the system under conditions of high analyte load were designed to identify cross-reaction thresholds for each of the individual analytes. MFI cut off values were used to identify significant increases in non-cognate signal that warranted removal of a feature from the array. The results provide a certain utility in predicting array performance under conditions where sample analyte concentrations exceed reported biological levels. Examples might include patient samples tested under diseased states, elevated analytes produced in stimulated cell culture supernatants or in samples exhibiting a strong drug response. The final validation involved measuring the accuracy of the multiplex assay when challenged with a high concentration of analyte. Figure 7 shows the correlations of signal intensities obtained between (1 × n) compared to (n × n) experiments at 50x MDL levels. High R 2 values obtained between the two conditions provided a measurement of the accuracy of the multiplexed system. Figure 7 New array validation . Stress testing at 50X MDL analyte concentration. The pink line reveals the specific MFI signal for each analyte at 50X MDL in the presence of all detectors (n × n). The blue line shows the signal for each analyte under conditions where all analytes are added at 50X MDL along with all detector antibodies minus the cognate detector antibody (n × (n-1)) to reveal non-specific signal contributed by non-cognate detectors. Discussion Thirty years of widespread use of conventional, monoplex immunoassays has established firm benchmarks for performance in protein measurement. In the present paper, we have examined several, unique but general considerations in assembling multiplexed immunoassays with performance similar to conventional monoplex immunoassays. These include development of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; application of standardized statistical approaches for data handling for highly replicated assays; inclusion of standardized samples in each run to normalize sample replicate measurements; quality control of reagents and antibody microarrays; implementation of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and initial procedures for identification of specific, significant immunoassay results in biomarker discovery projects involving clinical samples. Each of these will be discussed briefly. Requirement for a comprehensive array validation program An array validation program represents the foundation of tests required to establish robust assay performance in a multiplexed environment. The most significant component in array validation is the comprehensive evaluation of cross reactivity. The vast majority of the ~5000 commonly available antibody pairs available today have not previously been evaluated for cross reactivity in a multiplexed environment. Therefore, the recommended program should include procedures that identify analytes demonstrating cross reactivity with immobilized capture antibodies as well as cross reaction that might manifest between the secondary detector antibody with a non-cognate analyte or non-specific binding to an immobilized capture agent. The performance of analytes in a multiplexed configuration should be benchmarked against the baseline, monoplex performance. This multiplexed immunoassay comparison with baseline performance, together with minimal standards for multiplexed cross-reactivity, permits determination of the practical, optimal number of array elements that can be successfully combined. In our experience, using dual-antibody, sandwich immunoassays, planar glass slides and RCA signal amplification, protein micorarrays can generally accommodate multiplexing of 25–35 analytes without an appreciable drop in individual analyte sensitivity or performance. Specifically, we have described development of six different dual-antibody sandwich immunoassay arrays, each containing 25–37 sandwich immunoassays. Since cross reactivity is an additive process, the ultimate goal is to achieve a balance between maximal multiplexing and monoplex-like performance. With exhaustive selection for antibodies without cross-reactivity in multiplexed format, it is possible to multiplex 50 sandwich immunoassays. However, this exercise is very expensive. In our experience, suspension arrays, alternative microarray surface substrates and attachment chemistries do not offer significant advantages in multiplexing while maintaining performance. We have not evaluated the impact of novel, affinity ligands on multiplexing. Additional array validation for cross-reactivity should include "stress-testing" under high analyte load to reflect conditions where analytes may be significantly over-expressed. In our experience, levels of induction of proteins in common biological matrices can be very large following drug administration or in disease states, and may induce cross-reactivity that is not observed in testing within normal biological analyte levels. Finally, array validation should be performed across all common sample matrices to examine effects on assay performance associated with endogenous analyte, matrix specific analyte binding proteins or other matrix-specific inhibitors. Absence of cross-reactivity for an immunoassay in one matrix does not always imply absence of cross-reactivity in others. The matrices for which the antibody microarrays described herein have been validated include isotonic buffers, serum, citrate plasma, heparin plasma, EDTA plasma, cell culture supernatants, amniotic fluid, sputum, and exhaled breath condensates. Several of the arrays have also been validated for use with ex vivo treated whole blood. EDTA plasma and ex vivo treated whole blood had higher levels of background signal and lower sample pass rates than other matrices. Applying Standardized Approaches to Data Redaction A significant advantage of array-based immunoassays is the ability to measure each analyte in a sample many times. Removal of outlier replicates is obligatory for microarray assays due to signal-related and morphology-based artefacts typically associated with dispersing small volumes of material on a solid substrate in a microarray format. Application of standardized statistical approaches for data redaction is superior to manual inspection and removal of outliers since operator-dependent subjectivity is minimized and throughput is greatly increased. The data redaction procedures described herein employed two, separate steps: Bland-Altman plots and linear correlation analysis. Bland-Altman plots were employed first and identified 99% confidence intervals for all collected data points. This enabled rapid identification and elimination of the outlying 1% of the data with minimal human intervention. This was determined to be an objective, reproducible redaction procedure that greatly reduced time and effort associated with the subsequent, second data redaction step of linear correlation analysis. Linear correlation analysis required performance of 3 replicate assays on each sample, and manual inspection of the series of 3 scatter plots generated from pair-wise correlations of these 3 sample replicates. Individual replicate points for each specific analyte that fell outside the R 2 > 0.95 range were eliminated. In order for data from sample replicates to pass and be admitted into the final data set, the overall sample replicate-to-replicate correlation for the 25–37 analytes of the array was required to have an R 2 > 0.95. Experience in multiplexed immunoassay measurements in samples across more than 30 research projects indicated the R 2 value >0.95 to be routinely achievable and associated with high quality replicate data. In each project, the data lost through these two sequential redaction procedures was typically less than 5% of the total original data. An additional quality metric to assess the overall run performance was that at least two of the three replicates must have passed for 85% of the total samples. Runs falling short of this metric were failed and subject to repeat. The typical run fail rate was less than 3%. Within-Run Controls to Normalize Data Within-run controls were employed to account for the effects of systematic variation in replicate measurements. Variation was identified at three levels based on the unique configuration of the 16 sample well microarray chip. The lowest level of variability was observed between the quadruplicate spots of an individual analyte measured within a single sample well. The next level of variation was described as the difference between replicate analyte values measured in different wells located within the same slide. The highest level of variation was associated with measurements taken from a single sample applied to multiple wells positioned across different slides within a run. Since slide-to-slide variation demonstrated the highest system variation, a series of four controls were designed to minimize the impact on sample replicate measurements. The four controls contained all analytes for that array at four concentrations spread across the dynamic range. The four controls were run on every slide within a project and used to generate a global average of total analyte signal. Based on the global average, each individual slide was assigned an adjustment factor to compensate for the slide specific intensity bias. The analyte signal from each individual slide could then be scaled by the adjustment factor to normalize the intensity values between the sample replicates positioned across different slides. In addition, it is possible to use a blocking experimental design, intentionally positioning sample replicates across different slides and different slide locations to eliminate the potential for a slide-specific or location-specific intensity bias. An example of the latter might have been the well at the corner of a slide. Replicate measurements in conjunction with a mechanism to normalize systemic variation results in the production of high quality data required for maximal sensitivity in the identification of significant differences between samples in multiplexed immunoassays. An additional benefit of inclusion of standardized controls run across all slides of every project is the ability to standardize data, for example in mass units, and enable data comparisons between runs, between days and between projects. Such comparisons are necessary when projects constitute large numbers of samples or when it is desired to create a relational database of assay results. Our platform described herein, for example, can perform triplicate measurements on up to 200 samples in a single run. Stringent Quality Control of Reagents and Arrays Quality control of approximately 1200 individual reagents is necessary in order to provide consistent performance of 170 immunoassays on the array platform described herein. These reagents, unfortunately, have widely different shelf life and storage conditions. Stringent quality control procedures specifying performance metrics associated with these reagents were required to achieve reproducible array performance across hundreds of slide lots and reagent sets. Each new lot of a given component was benchmarked to an earlier lot to verify performance. Analyte intensity, dose-response curve, LLD/ULD absolute values, dynamic range and background signal were evaluated in fuctional tests performed on all assay components. Historical performance was monitored by comparing running averages obtained from earlier lots to prevent performance change over time. These procedures were made practical by assembling cocktails of reagents for each step in an assay, dispensing these in single-use aliquots, establishing optimal storage conditions and shelf life, and performing regular (typically weekly) quality checks on aliquots. Implementation of such procedures required use of a laboratory information management system. Real-Time Monitors of Platform Performance The utility of integrating real-time platform performance monitors cannot be understated. Given the complex nature and potential instability of biological reagents associated with a multiplex antibody array, it is critical have a program in place to evaluate performance beyond the quality control release. Real time monitors measure performance of controls under conditions identical to the test samples and reflect a second level verification of assay performance. Our test system employed a series of monitors to capture precision metrics that would create a flag to review the data if the specifications were not met. The requirements included mean coefficients of variation of assay values for controls be less than 15% and for sample replicates be less than 25% for project samples run within a batch. Failure to achieve these metrics indicated a problem related to the performance of the manufactured slides and/or reagents or a technical failure associated with sample handling or assay execution. 15-point standardized titrations were also performed on 6 slides in every run in order to captured detail related to analyte dynamic range, LLQ/ULQ values, dose response behaviour, and background signal that provided a comprehensive assessment of real time platform performance. The detail of the performance assessment was included in final reports for each project to verify data quality and generate confidence in the data generated from a highly complex assay. Evaluating the Utility of Multiplexed Immunoassays in Quantitative Proteomics Evaluating data generated from multiplexed immunoassays for utility in systematic identification of significant differences between samples, or "biomarker discovery", is an important step in understanding the true platform performance. One of the procedures that revealed the sensitivity of the platform for biomarker discovery was variance decomposition analysis for each project. Variance decomposition analysis examines the magnitude of individual components of platform variation and how they compare to analyte variation between samples or individuals. In our experience the platform error of the system described herein was generally an order of magnitude lower than the heterogeneity observed between samples or individuals of the same test group. The utility of this test is in revealing the extent to which platform error impacts the ability to discover moderate expression level differences between samples that are reflective of biological change. Platforms with lower precision will have less sensitivity for detection of relevant differences between samples and will discovery only a subset of the markers that would have been identified with a more precise system. Finally, a global performance assessment should be performed across multiple projects covering diverse disease areas to gain a solid understanding of the platform utility. An evaluation of this type can be used to identify assays that will not identify differences in expression between samples because they are not sufficiently sensitive, unable to generate sufficient dynamic range given the window of expression, or reveal high endogenous abundance producing assay saturation artefacts. In addition, specific assays that have appropriate sensitivity and dynamic range may be constitutively expressed and therefore poor biomarker candidate analytes for certain disease or treatment effect studies. This analysis may be used to direct efforts to continue to optimize the survey platform in order to generate the highest value in identifying biomarkers using a quantitative proteomic approach. Conclusions Protein microarrays offer the ability to simultaneously survey multiple protein markers in an effort to develop expression profile changes across multiple protein analytes for potential use in diagnosis, prognosis, and measurement of therapeutic efficacy. The current report details certain minimal standards, use of which was found to be necessary to generate the requisite specificity, sensitivity and reproducibility to discover biomarkers. Results revealed that a multiplex system could be operated with high analyte specificity, adequate detection sensitivity and sufficiently broad dynamic range to capture expression differences across diverse disease and therapeutic areas. Methods Slide Manufacture Glass inspection Raw soda-lime glass slides (1" × 3") prepared with a Teflon mask configured to provide 16 individual sample wells and an etched barcode for traceability were subjected to visual inspection to identify imperfections that might translate into printing and/or scanning artifacts. Slides with scratches, surface contamination or defects in the applied Teflon mask were identified through a visual examination using a long wavelength inspection lamp equipped with a 532 nm filter. The inspection also failed slides that did not meet stringent dimensional specifications, required for downstream printing and automated assay conditions. Surface activation Slides passing the visual inspection were silanized with 3-cyanopropyltriethoxysilane according to procedures previously described [ 17 ]. Measurements of water contact angle were taken at six discrete locations across the slide surface over a 2% batch sampling to evaluate the uniformity of the applied surface. Since the mean value of contact angle measurements can be influenced by external factors, the deviation in measurements within a batch was also evaluated as an indicator of surface uniformity. Slide batches achieving a mean contact angle value of 52 ± 5 degrees and an average standard deviation of less than 3 degrees were considered suitable for printing. Printing arrays Capture antibodies prepared as previously described [ 11 ] were printed onto coated slides using a PerkinElmer SpotArray Enterprise piezoelectric, non-contact arrayer housed in a class 10,000 controlled access cleanroom. Quadruplicate spots of ~350pL of each capture antibody were applied to each of the 16 wells within a slide generating 256 printed elements per well, 4096 spots per slide and 108 slides per print batch. Controls Printed features Each printed array contained 256 spots representing 64 individual elements printed in quadruplicate. Each array contained 25–40 capture antibodies spread across production chips 1–6, generating a panel of 170 survey analytes. The balance of the elements was reserved for internal assay controls. Each printed array contained multiple copies of an element called BLANK, containing the components used in capture antibody preparation. Blanks were used to survey non-specific sample background within each well. Other printed controls included a series of biotinylated mouse IgG calibration standards to monitor RCA signal amplification and a third control that acted as a monitor for spot contamination resulting from carry-over between sequentially printed features. 15-point standard titration calibrators Preparations of standardized multiplex analyte titration series were manufactured using recombinant analytes diluted in buffer that covered the range from 12 pg/mL up to 81 ng/mL at 14 discrete points along with two zero analyte buffer blanks. These titration points were distributed among the sixteen available wells on a slide (Figure 1 ). The standard titrations, designed to overlap the linear range of detection for each individual analyte, were used to generate standard curves from which sample analyte concentrations were determined. The standardized titrations were utilized in both the quality control testing performed on each print lot prior to release, as well as within each client project to verify real-time analyte performance. Six replicates for each point were run in the quality control testing of each slide lot and three replicates of each point were run within each client study to generate standard curves. Anchor point calibrators The three replicates tested for each study sample were positioned across different slides to avoid slide specific signal bias. Four of the fifteen standard titration points identified as "anchor" points were run across four wells of each sample slide to allow for data normalization of the replicates. The four specific points selected for each array were intended to capture the linear range of detection across the dose response curves for the individual panels of analytes. The remaining 12 wells of the slide were reserved for study samples. Slide Qualification Microscopic Examination Microscopic inspection of printed spots was performed on a 10% sampling of slides within each print batch. Slide selection was biased to interrogate slides located at critical positions on the arrayer deck, reflecting the beginning, middle and end of the print run. Printed slides were examined under a light microscope to evaluate spot positioning, morphology and print grid alignment within each well. Print lots demonstrating features with poor spot morphology, missing spots or misaligned features were not released for use. Positional confirmation Slides were subject to a full assay function test to confirm the proper location of the printed capture antibodies. Each printed slide lot was tested to confirm the position of the individual feature by spiking in purified analytes in groups of 1–3 per well at a fixed analyte concentration, and performing the full RCA assay to confirm signal at the appropriate printed location. Slide lots revealing signals in inappropriate locations, printing defects or missing signals failed the positional QC test and were not released for use. Performance assessment Functional testing was performed on a 10% sampling of each slide lot to evaluate the performance of each analyte. Replicates of the 15-point standardized cytokine titration series, were run to evaluate analyte dose-response, average fluorescent signal intensity, replicate spot variability, replicate sample correlations and LLQ/ULQ values to establish functionality of individual features as well as overall array performance for each slide lot produced. Values obtained for the various metrics were compared to historical averages to identify deviations in performance for the individual analytes. Slide lots were failed if analyte dose-response curves produced sample correlations with R 2 values less than 0.90, if average replicate spot-to-spot CVs were >15%, or if RCA signal amplification as measured by the biotinylated mouse IgG calibration standards fell below predefined MFI cutoffs. Assay Assay Automation The manual RCA microarray immunoassay reported previously was modified to optimize performance on an automated platform (Protedyne BioCube). Manual immersion washes were substituted with pipette delivered solutions finely tuned to control pipette tip aspiration and delivery position above printed slide wells and to carefully control liquid application and aspiration speeds to minimize disruption to the assembled immunosandwich complex. Incubation times were increased from 30 to 45 minutes for two of the assay steps (RCA signal amplification and detector incubation) and the number and volume of washes between steps increased from 2 to 4–5 and from 20 uL to 30 uL respectively. A Tecan LS200 unit was used to scan the slides. Microarray images were quantified using image capture software (ImageGrabber) developed in-house. Clinical Samples Sample procurement/processing Frozen serum samples from over 800 clinical patients were thawed, centrifuged to remove particulate matter and mixed with 0.25 mg/ml Heteroblock (Omega), 0.25 mg/ml IIR (Bioreclamation) and 0.1% Tween-20 prior to the assay. Twenty microliters of serum was applied to each well. Data processing Outlier removal Data points producing outlier events as a result of missing spots, spots with poor morphology, or printed features demonstrating high pixel outliers were removed using a combination of automated and manual methods. MvA plots, were generated by plotting the difference of the log intensities (M=log 2 (Rep1/Rep2) versus the average of the log intensities (A=log 2 ((Rep1*Rep2))/2) for each of the replicates across all analytes. Patterns were visualized using fitted curves from robust local regression with applied visual cues to identify a 99% confidence interval. All outliers in the MvA plot outside of the interval (having a p-value < 0.01) were automatically removed from analysis. The MvA scatter plots also allowed the user to highlight subsets of points on the plot and investigate patterns of intensity differences observed between replicate values. In cases where redaction of an entire replicate (comprised of 4 individual spots) was too stringent, individual spots could be removed using an in-house developed software tool (Terminator) to visually inspect aberrant data points. Data redaction using this method was performed on a limited basis to remove individual spot outliers with poor circularity, non-uniform pixel intensity or missing spots. Sample replicate correlation QC As a quantitative QC measure, data review included a sample replicate correlation assessment with a predefined correlation coefficient (R 2 ) value cutoff. An ideal microarray, when compared to its identical replicate, would have a R 2 value of 1. Any comparison producing values lower than the cutoff would result in at least one failed replicate. Individual sample correlations were generated by plotting analyte MFI values (on a Log 2 scale) from each replicate against the other replicates individually covering all combinations of replicates over the 25–37 analytes within the array. The R 2 values obtained for the three plots were manually reviewed to identify failed sample replicates. Only sample replicates with R 2 values >0.95 for replicates run within a day or R 2 values >0.90 for replicates run across multiple days passed the correlation QC. A summary of the overall sample replicate pass rate monitored the number of failed replicates observed across each of the individual arrays. Project performance specifications required that >85% of all study samples had at least 2 reported replicates. Data Normalization Individual sample values were normalized using linear regression of the anchor points run across 4 wells of each sample slide to reduce assay imprecision observed among replicates. A four-point standard titration was run on every slide for normalization and quality control purposes. Fluorescence intensities of the four spot replicates for each analyte within a well were averaged on a logarithmic (base two) scale to generate within-slide titration curves. Linear regression coefficients (slope and intercept) were calculated between individual titration curves from each slide to generate an "average" titration curve. Calculated slope and intercept were used to transform averaged analyte values for each sample well. Data normalization was performed on the data set after outlier removal. Precision assessment A standardized precision assessment was performed on each run to monitor assay performance with respect to; within well variation (based on mean coefficient of variation (CV) observed between quadruplicate printed spots for all features across all sample wells of a project) and between-slide variation (reflecting the average CV observed between all sample replicates across all samples in a study). The mean and median CVs with standard deviations were also metrics included in the precision assessment. The precision assessment was performed as a quality control using the 15-point titration calibrators to qualify new slide lots and generate quality metrics for each client project. LLQ/ULQ determinations Mean fluorescent intensity (MFI) values, on a logarithmic scale, from the 3 replicate measurements of the 15 point standard titration series were used to generate precision profiles to define the upper and lower limit of quantitation (ULQ, LLQ) within a predefined concentration CV [ 18 ]. To do this, a dose-response curve was fitted to the 15-point calibrators using 4-paramter logistic curve fitting procedures. The MFI standard deviation (SD) of the triplicate measurements was converted to concentration SD for the 15 concentration units by dividing by the slope of the dose-response at each concentration point. The conversion provides the relative SD or %CV as a function of analyte concentration to define the precision of the assay for each analyte throughout the working range. Variance decomposition analysis The VARCOMP procedure of SAS (SAS Institute), was used to obtain estimates of the variance components in a mixed model. The fixed effect variable represents variance observed in different groups in the study, for example groups of healthy versus diseased individuals. Random effects were represented by unique sample identifiers nested within levels of a fixed variable. This component of variance represented within-group differences associated with patient-to-patient variability or disease heterogeneity. The residual variance represented the platform error. New Array Validation Establishing analyte sensitivity Assay sensitivity was determined in two series of experiments. Initial testing to identify analyte cross-reactivity was performed in a configuration where all printed capture antibodies are surveyed in a "1 × n" format, representing a single recombinant analyte tested against all (n) detectors across multiple matrices (serum, heparin plasma, citrate plasma, EDTA plasma and buffer). Capture antibodies that revealed binding to non-cognate antigens were removed or replaced with suitable alternatives. Analytes that demonstrated low signal across all matrices were removed. If signals were low in buffer, a comparison was made with signals obtained in serum or plasma to determine if the endogenous analyte level was detectable and determine if depressed signals were due to analyte instability in a non-biological matrix. Assessment of analyte endogenous level was performed using a "0 × n" format where unadulterated serum and plasma (heparin, citrate, EDTA) are assayed with the full complement of detector antibodies for a given array. Evaluating cross reaction Two conditions were examined to study potential cross-reactivity between the complex detector antibody mixture and the immobilized capture analyte. The first condition included a 1 × (n-1) format in which 1 analyte was tested in the presence of all detectors minus the detector antibody specific to the added analyte (n-1). In the case of an array containing 40 printed features, 40 unique detector antibody cocktails are prepared containing 39 of the detector antibodies found in the complex mix, with each mix containing all but one of the 40 corresponding detectors. The 40 individual reaction mixes are added to specific arrays after the arrays were incubated with the antigen corresponding to the missing detector. The second condition represented the 0 × (n-1) format where no analyte was added in the presence of all detectors minus the detector specific to the analyte under examination. In each case the analytes were spiked in buffer, serum, and plasma (heparin, citrate, EDTA) at a fixed analyte concentration of 50 ng/ml. Stress testing Single analyte titrations were prepared in buffer, serum and plasma (heparin, citrate, EDTA) to assign a minimum detection limit (MDL) for each analyte based on a 95% confidence interval above background. The format of the experiments included an n × n design, where all analytes were run in the presence of all detectors. Then, using a 1 × n format, where only one antigen was added to an assay containing all detectors (n), each analyte was tested at 0X, 10X, 50X, and 100X MDL across the same test matrices to identify non-cognate cross-reaction under high analyte load. Additional antigen titration experiments were run to compare the performance achieved in the presence of a single antigen (1 × n) to one in which all analytes were present (n × n). List of Abbreviations MFI: Mean Fluorescence Intensity. RCA: Rolling Circle Amplification. CV: Coefficient of Variation R 2 : correlation coefficient LLQ: lower limit of quantitation ULQ: upper limit of quantitation MDL: minimal detection limits SD: standard deviation Competing interests L.T. Perlee, J. Christiansen, B. Grimwade, S. Lejnine, V. Tchernev and M. Sorette were employees of Molecular Staging, Inc. and D.D. Patel and S.F. Kingsmore have received consulting fees. Authors' contributions RD oversaw the manufacturing of reagents, JC established standardized quality control testing procedures, MS implemented assay automation and oversaw all clinical testing. BG was responsible for data curation, SL performed statistical analysis. MM and WS contributed to array develoment. SFK, VTT and DDP were involved in study design, LTP in project execution and LTP, SL, JC and SFK in manuscript preparation. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544832.xml |
550660 | PSSM-based prediction of DNA binding sites in proteins | Background Detection of DNA-binding sites in proteins is of enormous interest for technologies targeting gene regulation and manipulation. We have previously shown that a residue and its sequence neighbor information can be used to predict DNA-binding candidates in a protein sequence. This sequence-based prediction method is applicable even if no sequence homology with a previously known DNA-binding protein is observed. Here we implement a neural network based algorithm to utilize evolutionary information of amino acid sequences in terms of their position specific scoring matrices (PSSMs) for a better prediction of DNA-binding sites. Results An average of sensitivity and specificity using PSSMs is up to 8.7% better than the prediction with sequence information only. Much smaller data sets could be used to generate PSSM with minimal loss of prediction accuracy. Conclusion One problem in using PSSM-derived prediction is obtaining lengthy and time-consuming alignments against large sequence databases. In order to speed up the process of generating PSSMs, we tried to use different reference data sets (sequence space) against which a target protein is scanned for PSI-BLAST iterations. We find that a very small set of proteins can actually be used as such a reference data without losing much of the prediction value. This makes the process of generating PSSMs very rapid and even amenable to be used at a genome level. A web server has been developed to provide these predictions of DNA-binding sites for any new protein from its amino acid sequence. Availability Online predictions based on this method are available at | Background There has been a growing interest in the prediction of DNA-binding sites in proteins which play crucial roles in gene regulation [ 1 - 4 ]. We have previously developed a method of predicting DNA-binding sites of proteins from the sequence information [ 5 ]. We reported development of a neural network and corresponding web server to predict amino acid residues which are likely to bind DNA. The only input to the neural network in this algorithm was the identity of the amino acid residue and its two sequence neighbors on C- and N- terminals. We also developed a method to identify DNA-binding proteins using electrical moments from structural information of proteins [ 6 ]. On the other hand, several investigators have reported that the use of evolutionary information in sequence-based predictions of secondary structure and solvent accessibility can improve the prediction capacity of a neural network [ 7 - 10 ]. Here we report the use of such evolutionary information in improving the prediction of DNA-binding sites of proteins. We note that one of the major problems in applying evolutionary information by way of position specific scoring matrices (PSSMs) for sequence based prediction is that such matrices are generated over large data sets and take a long time to complete. Thus large scale predictions remain inaccessible to moderately capable computers. This is a serious limitation in the portability of neural network based predictions using PSSMs [ 8 ]. In this work, we report that evolutionary profiles or PSSMs against much smaller representative reference data sets may be utilized to achieve almost the same levels of prediction as would be obtained from alignments with large sequence data sets representing entire available sequence space. We have used four different reference data sets of PSSMs for 62 representative protein sequences. These are (1) PDNA-RDN: a data set of protein sequences from all Protein-DNA complexes from the PDB, (2) PDNA-NR90: a non-redundant data set compiled from PDNA-RDN, (3) PDB-ALL: a data set of all amino acid sequences from PDB and (4) NCBI-NR: a non-redundant data set of all protein sequences taken from sequence and structure databases and compiled by NCBI (see Methods). We find that the net prediction (an average of sensitivity and specificity) of the best of these systems (using PIR sequence data as reference) improves to 67.1% from the value of 58.4% reported earlier for a sequence-only prediction. We also report that a small reference data set of 375 sequences (PDNA-NR90) can give a 64.6% net prediction – just 2.5% poorer than the best- while reducing the PSSM calculation time from more than two hours (against NCBI-NR) to just about one minute. A better compromise could be the use of PDNA-RDN data for which 65.2% net prediction #150; 1.9% less than the best- was obtained, while about 2 and a half minutes are taken to generate their PSSMs. It is also reported that the presence of redundancy is helpful in improving the prediction whereas presence of data not relevant for DNA-binding may in some cases reduce predictive performance. Results and discussion Position Specific Iterative BLAST (PSI BLAST) is a strong measure of residue conservation in a given location. In the absence of any alignments, PSI BLAST simply returns a 20-dimensional vector representing probabilities of conservation against mutations to 20 different amino acids including itself. A matrix consisting of such vector representations for all residues in a given sequence is called Position Specific Scoring Matrix or PSSM. When a residue is conserved through cycles of PSI BLAST, it is likely to be due to a purpose i.e. biological function. It has been established by several authors cited in the introduction that the prediction of structural properties is significantly enhanced by the use of PSSMs compared to predictions based on unique representations of amino acid sequence and its environment. Protein structure universe is vast and a prediction of structural properties should span the entire range of this diversity. However, the question of predicting DNA-binding sites is much narrower and hence the significance of conservation of residues at specific locations may be limited to a subset of this protein space. Such reduction in the protein search space or the reference data sets against which PSSM-based predictions should be attempted is desired for a rapid prediction of binding sites as well as portability of prediction methods. Compact reference data size can not only answer these questions of speed and portability but also try to minimize noise in information contents and improve prediction quality. Table 1 shows the results of DNA-binding site prediction using different sets of PSSMs as the neural network inputs. The best net prediction results were 67.1% which is 8.7% better than the predictions with sequence information only. These results were obtained for PSSMs against PIR sequence data. An even larger NCBI-NR data set showed a slightly smaller (66.7%) net prediction. The fact that NCBI-NR reference data sets produce somewhat worse results than PIR sequence suggests that the redundancy present in the PIR sequence data could be the factor responsible for giving better PSSMs than those of a non-redundant NCBI sequence data. Thus an overall redundancy in the data turns out to be helpful in improving the prediction of binding sites. The question is how rapidly the prediction ability will fall if we reduce the redundancy even further, replacing the larger data sets with smaller ones until a small representative data set is left. This question is partly answered by first using a sequence database of the entire protein data bank (PDB-ALL), which gives an accuracy of 64.7% (about 2.4% poorer than the best). Further reducing the data set to protein sequences from only the Protein-DNA complexes surprisingly increases the net prediction to 65.2%. We suggest that the increase in net prediction on the PDNA-RDN over the entire PDB is caused by the fact that PDNA-RDN contains all the data from PDB which is relevant for the DNA-binding. However, an additional data in the PDB-ALL represents conservation scores in regions not involved in DNA-binding and hence lead to a somewhat lower net prediction. Going further down from a redundant (PDNA-RDN) to a non-redundant (PDNA-NR90) sequence data of Protein-DNA complexes, we observe a 0.6% fall in net prediction- just about the same we observed from PIR to NCBI-NR. We attribute this fall in net prediction to the reduction in the redundancy in the sequence data sets, which is concluded to be useful in better prediction of DNA-binding sites. In terms of CPU time, it may be noted that the time taken by 62 protein sequences used here is about one hour for the best (PIR) data sets. These times are prohibitively large for making predictions at a genomic scale or for providing rapid web services. A compromise could be obtained by using PDNA-RDN instead, which reduces the CPU time by a factor more than 8. The loss of net prediction for this compromise is about 1.9%, which is still 6.8% better than the predictions obtained from sequence information only. PSSMs against this data set for a typical protein of 500 residues can be generated in about 1 s, making it possible to run large scale predictions. A smaller size of reference data and high speed of PSSMs also make this method portable and light weight with a strong predictive ability. Binary decision function of the neural network (see Methods) assigns a value of zero (not binding) or 1 (binding) based on a threshold on the real value output received at the output node. Most of the accuracy scores presented here have been obtained by using 0.5 as the cutoff (mid point of the transfer function range). By changing this threshold from 0.5 to higher and lower values, the balance between sensitivity and specificity can be adjusted. In our online prediction we also present the scores obtained for a ROC analysis of such adjustments (Figure 2 ). ROC for only one reference data set has been shown here as most other graphs show a similar behavior. Online predictions We have provided online predictions based on the above method at our web site [ 16 ]. The raw probability scores, their annotations at different sensitivity thresholds, and a reference scale for expected sensitivity and specificity have been provided. In addition, results of sequence alignments obtained after PSI BLAST iterations against a reference data (PDNA-RDN) are also provided. This allows us to have a complete picture of similarity of a given sequence with known DNA-binding proteins and predictions based on neural network using alignment profiles in the form of PSSM. The only input to this neural network is the amino acid sequence of the protein. The web server will automatically generate PSSMs of the given sequence against a reference data and use them as the input to a neural network, trained for predictions of 62 DNA-binding proteins. Conclusion A PSSM-based neural network method for predicting DNA-binding sites in proteins has been developed. PSSMs were developed against different data sets and it was observed that significant computer time can be saved by replacing the reference data sets with much smaller reference data sets without loss of much prediction ability. Redundant reference data sets show a better prediction than the non-redundant data sets. A web server was developed to provide prediction of DNA-binding sites based on this method. In addition, the web server provides BLAST alignments against a reference data set of known DNA-binding proteins. Methods Data sets PDNA-62 This is the (non redundant) target data set of 62 DNA-binding proteins from Protein Data Bank (PDB) [ 11 ]. The same data set has been used in our related studies [ 5 , 12 ]. PDNA-RDN This is a new data set, developed for this work. We have selected all Protein-DNA complexes from PDB and separated their chains. 1386 protein chains were obtained in this way. FASTA formatted sequences were subsequently formatted using formatdb program of the BLAST package [ 13 ]. PDNA-NR90 The data set ( PDNA-RDN ), obtained from the procedure mentioned above was filtered to remove redundancy at 90% sequence identity level by using sequence clustering program BLASTCLUST [ 13 ]. Resulting data set now contains 375 sequences which are formatted for use as a reference data set using formatdb . This data set is called PDNA-NR90 . Other data sets PDB-ALL (47,189 sequences) is a data set of all protein sequences obtained from NCBI. PIR is the sequence data set (283,177 sequences) of Protein Information Resource at Georgetown University [ 14 ]. NCBI-NR is a non-redundant data set of all protein sequences compiled from GeneBank, PIR, SwissProt, PDB and other resources by NCBI [ 17 ]. Generation of PSSMs Target sequences are scanned against the reference data sets to compile a set of alignment profiles or position specific scoring matrices (PSSMs) using Position Specific Iterative BLAST (PSI BLAST) program [ 15 ]. Three cycles of PSI-BLAST were run for each protein and the scores were saved as profile matrices (PSSMs). Neural network Neural network inputs Conservation scores in 20 amino acid positions for every residues form 20 columns (column 3 onwards) of corresponding row in a PSI-BLAST PSSM. For every residue, we make a binary or real-value (interpreted as probability) prediction of that residue being a binding site or not. Input for every prediction is the PSSM score on the row corresponding to this target residue and two more rows on either side, totaling 20 × 5 = 100 inputs (Figure 1 ). Network architecture and transfer function We use a neural network with one hidden layer (two nodes) in addition to the input layer described above and a single node output layer. Large number of units in the hidden layer and additional layers were not tried because the data size does not justify an unreasonably large neural network. Network signal is transferred to subsequent layers by an algebraic summation of inputs from the previous layer. Total signal in the last unit is transformed to a real output by a binary decision function much in the same way as in our previous work except that the input to the network is now replaced by PSSM scores rather than 20 bit binary coding [ 5 ]. Training and validation A six-fold cross-validation has been used in this work. Out of 62 proteins, 10 were removed at one time and the remaining 52 were trained until the accuracy on the left-out 10 also improved. Six random sets are created in this way and the figures in Table 1 report the averages on all six runs of each set of 10 proteins. Training error function and measure of prediction quality Data imbalance in the two binary categories for this neural network makes the choice of error function particularly important. We have used an accuracy score called Net Prediction, which is the average of sensitivity and specificity values defined below. Neural network learns to maximize this accuracy score rather than minimizing an error function. Sensitivity is defined as the number of correct prediction in the binding category relative to total number of such items in the original data and specificity is the number of correctly rejected residues in this category relative to the total number of non-binding residues in the original data. Sensitivity (S1) = 100 * TP/(TP+FN) (1) Specificity (S2) = 100 * TN/(TN+FP) (2) where TP: True Positive; TN: True Negative; FP: False Positive; FN: False Negative Relative number of true positive (TP) values in the prediction was termed as accuracy in our previous work. We have avoided using that term here, as we prefer a more operational definition of accuracy measures here. The imbalance of sensitivity (S1) and specificity (S2) is taken care of by comparing the Net Prediction of the models which gives a better comparison when S1 and S2 vary from one sample to the other. Thus, Net Prediction (NP) = (S1+S2)/2 (3) List of abbreviations PSSM: Position Specific Substitution Matrix PSI BLAST: Position Specific Iterative Basic Local Alignment Search Tool Authors' contributions SA conceived and implemented this project. AS contributed in manuscript preparation, results analysis and discussions. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550660.xml |
538286 | Effect of straining on diaphragmatic crura with identification of the straining-crural reflex. The "reflex theory" in gastroesophageal competence | Background The role of the crural diaphragm during increased intra-abdominal pressure is not exactly known. We investigated the hypothesis that the crural diaphragm undergoes reflex phasic contraction on elevation of the intra-abdominal pressure with a resulting increase of the lower esophageal pressure and prevention of gastro-esophageal reflux. Methods The esophageal pressure and crural diaphragm electromyographic responses to straining were recorded in 16 subjects (10 men, 6 women, age 36.6 ± 11.2 SD years) during abdominal hernia repair. The electromyogram of crural diaphragm was recorded by needle electrode inserted into the crural diaphragm, and the lower esophageal pressure by a saline-perfused catheter. The study was repeated after crural anesthetization and after crural infiltration with saline. Results The crural diaphragm exhibited resting electromyographic activity which showed a significant increase on sudden (coughing, p < 0.001) or slow sustained (p < 0.01) straining with a mean latency of 29.6 ± 4.7 and 31.4 ± 4.5 ms, respectively. Straining led to elevation of the lower esophageal pressure which was coupled with the increased electromyographic activity of the crural diaphragm. The crural response to straining did not occur during crural diaphragm anesthetization, while was not affected by saline infiltration. The lower esophageal pressure declined on crural diaphragm anesthetization. Conclusions Straining effected an increase of the electromyographic activity of the crural diaphragm and of the lower esophageal pressure. This effect is suggested to be reflex in nature and to be mediated through the "straining-crural reflex". The crural diaphragm seems to play a role in the lower esophageal competence mechanism. Further studies are required to assess the clinical significance of the current results in gastro-esophageal reflux disease and hiatus hernia. | Background Swallowing is a physiologic process by which the food bolus is transmitted from the pharynx to the stomach without esophagopharyngeal or gastro-esophageal reflux [ 1 ]. A sphincteric action exists within the lower 4 cm of the esophagus which prevents reflux of gastric contents into the esophagus [ 2 , 3 ]. The mechanism of gastro-esophageal competence is complex and incompletely understood [ 4 - 7 ]. A true anatomical sphincter could not be demonstrated at the lower end of the esophagus, and the sphincter is considered a physiological one [ 8 - 11 ]. The resting pressure within the lower esophageal sphincter (LES) normally exceeds the intragastric pressure by 15–25 cm H 2 O due to tonic contraction of the esophageal musculature [ 10 ]. The LES squeeze increases by gastrin and decreases by cholecystokinin, secretin, and glucagons [ 5 , 6 ]. Cholinergic and ∝ – adrenergic stimuli enhance while β – adrenergic stimuli inhibit sphincter contraction 11 . The LES contributes to the prevention of gastric reflux into the esophagus [ 2 , 3 ]; however, the mechanism of action is not exactly known [ 2 - 6 ]. The diaphragm is believed to play a contributory role in the barrier function of the lower esophagus. This auxiliary function seems to be carried out by the crural and not the costal diaphragm. The latter contracts and relaxes with respiration. Crural diaphragm (CD) contraction effects LES pressure increase which is directly proportional to the depth of inspiration at the force of diaphragmatic contraction [ 12 ]. Pressure gradients across the esophagogastric junction during expiration is counteracted by the smooth muscle relaxation of the LES, and increases in the gastrocrural pressure gradient caused by the skeletal muscle activity of the diaphragm and abdominal wall are counteracted by the CD [ 13 ]. Crural diaphragm has been demonstrated to contribute actively in the process of deglutition [ 14 ]. Thus, on crucial balloon distension the CD relaxed, while gastric distension effected CD contraction [ 14 ]; this sphincter-like CD action was found to be mediated through the esophago-crural inhibitory and the gastro-esophageal excitatory reflexes, respectively [ 14 ]. The role of the CD during increased intra-abdominal pressure is not completely understood. We hypothesized that the CD, upon increase in intra-abdominal pressure by coughing, sneezing or straining, undergoes reflex phasic contraction with a resulting augmentation of the lower esophageal pressure and inhibition of stress reflux of the gastric contents into the esophagus. This hypothesis was investigated in the current communication. Methods Subjects Sixteen subjects were enrolled in the study. Ten were men and six women with a mean age of 36.6 ± 11.2 SD years, (range 27–43). The tests were performed during operative repair of an upper abdominal ventral hernia in 9 patients and of incisional hernia after cholecystectomy for calculous cholecystitis in 7 patients. The patients did not complain of swallowing problems in the past or at the time of enrollment. They gave an informed consent after having been fully informed about the nature of the tests to be done and their role in the study. Physical examination results, including neurologic assessment, were normal. Also barium swallow studies and upper gut endoscopy yielded normal findings. The results of laboratory work including blood count, renal and hepatic function tests as well as electrocardiography were unremarkable. The study was approved by the Review Board and Ethics Committee of the Cairo University Faculty of Medicine. Methods The EMG activity of the CD was recorded during coughing and during straining. The subjects had received general anesthesia using 5% halothane/ 95% oxygen for their above mentioned hernia operations. EMG activity of the CD A concentric electromyographic needle electrode of 40 mm in length and 0.65 mm in diameter (Type 13 L 49 Disa, Copenhagen) was introduced into the CD as it encircled the lower end of the esophagus. A ground electrode was applied to the thigh. A standard electromyographic (EMG) apparatus (Type MES, Medelic, Woking, UK) was used to amplify and display the potentials recorded. Films of the potentials were taken on light-sensitive paper (Linagraph type 1895, Kodak, London, UK) from which measurements of the motor unit action potentials' duration were obtained. The electromyopraphic signals were also stored on an FM tape recorder (type 7758 A, Hewlett-Packard, Waltham, MA) for further analysis as required. Before performing the experiment, the normality of the EMG activity of the CD was tested by stimulating it with a needle electrode introduced into the CD and registering the motor unit action potentials from the already inserted needle electrode. The CD had normal EMG activity in all examined subjects. Manometric studies A manometric 6-F catheter was introduced into the esophagus to lie in the high pressure zone at its lower end. The catheter with 2 side ports and a metallic clip applied to its distal closed end for fluoroscopic control was connected to a pneumohydraulic capillary infusion system (Arndorfer Medical Specialities, Greendale, Wis). The pump delivered saline solution continuously via the capillary tube at a rate of 0.6 ml / min. The transducer outputs were registered on a rectilinear recorder (model RS-3400, Gould Inc). Occlusion of the recording orifice produced a pressure elevation rate that was greater than 250 cm H 2 O/s. During pressure measurements, the catheter was rotated so as to record anteroposterior and lateral pressures. Induction of cough and straining Near the end of the operation when the effect of muscle relaxant had waned, the anesthetist was asked to induce coughing and straining via laryngeal and tracheal stimulation by moving the endotracheal tube while lying in the trachea. The EMG response of the CD to increased intra-abdominal pressure was registered. Readings were recorded during two types of straining: the sudden forcible straining as that induced by coughing, and the slow sustained straining which simulates that occurring during defecation or micturition. The latency of the crural response was measured from the stimulus (straining) to the first deflection of the muscle action potential complex. The millisecond latencies were calculated when the movement artifact associated with straining appeared on the crural EMG and then the time to the first muscle action potential was measured as an index of latency. Crural anesthetization To define whether the effect of coughing or straining on the crural diaphragm was direct or reflex action, the following lest was done. In 8 subjects (5 men and 3 women), the CD was infiltrated with 5 ml of 2% lidocaine to anesthetize the crura around the needle electrode. The crural response to sudden and slow sustained straining was recorded after 10 minutes and after 2 hours when the anesthetic effect had waned. Similarly, normal saline was injected and the crural response to straining was registered. The results were analyzed statistically using the Student's t test and values were given as the mean ± standard deviation. Differences assumed significance at p < 0.05. Results The CD in all of the subjects showed a basal activity with a mean of 112.3 ± 16.3 μV (range 86–123, fig 1 ). Upon sudden straining (coughing), the CD exhibited an increase in the EMG activity to a mean of 553.6 ± 54.2 μV (range 480–675 μV, p < 0.001, fig 1 ). The basal activity was resumed after cessation of straining. Slow sustained straining induced increase of the crural EMG activity to a mean of 482.7 ± 42.5 μV (range 366–610, p < 0.01, fig 2 ). Figure 1 Electromyographic activity of the crural diaphragm a) at rest and b) on sudden straining (coughing). ↑ = coughing Figure 2 Electromyographic activity of the crural diaphragm a) at rest and b) on slow sustained straining. ↑ = straining The crural response to straining (sudden or slow sustained) was reproducible in all studied subjects. It was weaker in women than men, and in the elderly than in the young subjects, though the difference was insignificant (p > 0.05). The CD response disappeared when straining was sustained for more than 15–18 seconds (mean 16.8 ± 1.2) and was not evoked after frequent successive straining. The latency of the response recorded a mean of 29.6 ± 4.7 ms (range 21–33, fig 1 ) for the sudden straining (fig 1 ) and 31.4 ± 4.5 ms (range 22–36) for the slow sustained straining (fig 2 ) with no significant difference between the 2 latencies. In the 8 subjects in whom the CD was anesthetized, the crural response to straining did not occur, except after 2 hours when the effect of lidocaine had waned; the response after 2 hours was similar to that before anesthetization with no significant difference (p > 0.05). Saline injection of the crura did not affect the crural response to straining. Lower esophageal pressure response to straining The pressure at rest in the LES recorded a mean of 25.4 ± 6.3 cm H 2 O (table 1 ). On sudden straining (coughing), we registered a mean of 96.6 ± 10.8 cm H 2 O (table 1 ), while with slow sustained straining a mean of 82.6 ± 8.3 cm H 2 O (table 1 ). The elevated esophageal pressure was coupled with the increased EMG activity of the CD and was sustained along with the increased motor unit action potentials. Table 1 The pressure in the lower esophageal sphincter at rest and on straining + . Pressure (cm H 2 O) Mean Range Basal 25.4 ± 6.3 17 – 32 Sudden straining 96.6 ± 10.8 * 72 – 124 Sustained straining 82.6 ± 8.3 * 58 – 97 + values were given as the mean ± standard deviation * p < 0.01 P values were compared to the basal value. On CD anesthetization, the lower esophageal pressure dropped to a mean of 14.2 ± 2.4 cm H 2 O (table 1 ). It rose significantly (p > 0.01) to a mean of 63.7 ± 10.4 cm H 2 O on sudden straining and to a mean of 56.2 ± 7.5 cm H 2 O (p < 0.01, table 2 ) on slow sustained straining. The pressure returned to the pre-anesthetic level after 2 hours when the anesthetic effect had worn off. Table 2 The pressure in the lower esophagus upon crural anesthetization at rest and on straining + . Pressure (cm H 2 O) Mean Range Basal 14.2 ± 2.4 9 – 18 Sudden straining 63.7 ± 10.4 * 49 – 84 Sustained straining 56.2 ± 7.5 * 43 – 73 + values were given as the mean ± standard deviation * p < 0.01 P values were compared to the basal values. Discussion The current study seems to shed some light on the effect of coughing-or-straining-induced intra-abdominal pressure increase on the CD and the lower esophagus. The CD has a respiratory rhythm but is not a respiratory muscle. It surrounds the lower end of the esophagus, which is an intra-abdominal structure and is continuously exposed to variations in the intra-abdominal pressure. The lower esophagus contains a physiologic sphincter, which is the LES. In contrast to the CD which consists of striated muscle fibers, the LES is composed of smooth fibers. The resting electric activity exhibited by the CD most likely denotes that the CD possesses a resting tone which presumably shares in inducing the high pressure within the LES. The high pressure zone in the lower esophagus appears to be created not only by the effect of the LES but also by the muscle tone of the CD. This is evidenced by the reduced lower esophageal pressure on the CD anesthetization. The increased crural electric activity and the elevated esophageal pressure upon straining presumably denote crural contraction. The CD tone at rest and crural contraction on straining probably share in preventing gastro-esophageal reflux under resting and stress conditions. The disappearance of the crural response on prolonged straining and the non-response after frequent successive straining appear to be due to the fact that the CD consists of striated muscle fibers which are easily fatigable and cannot remain contracted for long periods. On CD anesthetization, the lower esophageal pressure dropped from the mean basal pressure of 25.4 ± 6.3 cm H 2 O to 14.2 ± 2.4 cm H 2 O. This denotes that the CD has a share of approximately 44% in the basal lower esophageal pressure against 54 % of the lower esophageal sphincter. On straining while the CD was anesthetized, the lower esophageal pressure recorded values significantly below those before anesthetization. These findings would indicate that the CD shares the formation of the lower esophageal high pressure zone with the LES. The question that needs to be discussed is whether the crural response to straining is the result of a direct action or reflex in nature. The straining-crural reflex The current study have demonstrated that the CD contracts on straining as evidenced by increase of both the crural EMG activity and the lower esophageal pressure. The crural contraction on straining could be a direct or reflex action; it seems to be reflex in nature as became evident from its absence when the CD, a suggested arm of the reflex arc was anesthetized. This reflex relationship was reproducible and we call it the "straining – crural reflex". Lidocaine blocks the sensory fibers (C and A delta – fibers) which are responsible for pain and reflex activity [ 15 , 16 ]. The straining-crural reflex appears to be evoked in conditions of increased intra-abdominal pressure as occurs during coughing, squeezing and during straining at defecation or micturition. Role of the straining-crural reflex in lower esophageal competence: The "reflex theory", a new concept The mechanism of gastroesopageal competence is vague and incompletely understood [ 2 - 7 ]. There are several factors claimed to maintain the lower esophageal competence. These include the "diaphragmatic pinchcock", a circular anatomic sphincter and a flap valve [ 17 , 18 ]. However, in spite of the general acceptance that the circular fibers at the lower esophagus acts as a sphincter, there is so far no anatomical evidence to support the presence of a true sphincter [ 17 - 21 ]. Meanwhile, it is highly probable in the light of the findings of our study that the prevention of gastro-esophageal reflux is a "reflex process" rather than an anatomical entity. We have previously demonstrated that gastric distension by food or an increase in the intra-abdominal pressure would evoke the "gastroesophageal reflex" which acts to tighten the LES [ 22 ]. The more voluminous the gastric distension or the higher the intra-abdominal pressure, the tighter the LES. The current study presumably denotes that the CD shares reflexly in the competence mechanism of the gastroesophageal junction. Thus, upon increase of the intra-abdominal pressure, the straining-crural reflex seems to be evoked effecting crural contraction and increase of the lower esophageal pressure. In view of the aforementioned results and discussion, we believe that the "reflex theory" plays a more important role in gastroesophageal competence than the diaphragm pinchock, the flap valve mechanism or other possible anatomical factors. Conclusion The CD appears to play a role in the lower esophageal competent mechanism. Straining effected an increase in the EMG activity of the CD and in the lower esophageal pressure. This effect is suggested to be reflex in nature and to be mediated through the "straining-crural reflex". Further studies are needed to evaluate the clinical significance of the current results in the pathogenesis and treatment of gastresophageal disease and hiatus hernia. List of abbreviations lower esophageal sphincter (LES) crural diaphragm (CD) electromyographic (EMG) Competing interests The author(s) declare that they have no competing interests. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538286.xml |
515300 | Antibiotic susceptibility patterns among respiratory isolates of Gram-negative bacilli in a Turkish university hospital | Background Gram-negative bacteria cause most nosocomial respiratory infections. At the University of Cumhuriyet, we examined 328 respiratory isolates of Enterobacteriaceae and Acinetobacter baumanii organisms in Sivas, Turkey over 3 years. We used disk diffusion or standardized microdilution to test the isolates against 18 antibiotics. Results We cultured organisms from sputum (54%), tracheal aspirate (25%), and bronchial lavage fluid (21%). The most common organisms were Klebsiella spp (35%), A. baumanii (27%), and Escherichia coli (15%). Imipenem was the most active agent, inhibiting 90% of Enterobacteriaceae and A. baumanii organisms. We considered approximately 12% of Klebsiella pneumoniae and 21% of E. coli isolates to be possible producers of extended-spectrum beta-lactamase. K. pneumoniae isolates of the extended-spectrum beta-lactamase phenotype were more resistant to imipenem, ciprofloxacin, and tetracycline in our study than they are in other regions of the world. Conclusions Our results suggest that imipenem resistance in our region is growing. | Background Nosocomial bacterial pneumonia is frequently polymicrobial, with gram-negative bacilli predominating [ 1 ]. Because delays in antimicrobial treatment can lead to adverse outcomes, the choice of empirical therapy is vital. Many effective antimicrobial agents are available, but the treatment of nosocomial pneumonia remains challenging. We recently reported the antibiotic-resistance patterns of respiratory isolates of Pseudomonas aeruginosa in our region [ 2 ]. The current study investigates the distribution and drug resistance of other gram-negative bacteria in the respiratory secretions of hospitalized patients. Results Table I and Table II present the antibiotic susceptibility patterns of our isolates. The most common organisms were Klebsiella spp (35%), A. baumanii (27%), and E. coli (15%). We also isolated rare organisms such as Stenotrophomonas maltophilia, Burkholderia spp, and Hafnia alvei . All studied Enterobacteriaceae (except Enterobacter spp) were far more susceptible to ticarcillin-clavulanate than to ticarcillin alone, which suggests that the primary mechanism of resistance in these organisms is β-lactamase production. K. pneumoniae accounted for 79% of Klebsiella isolates. Klebsiella spp were generally more susceptible to the tested antimicrobials than were Enterobacter spp, Serratia spp , or E. coli . The overall resistance rates to the third-generation cephalosporins (cefotaxime, ceftazidime, and ceftriaxone) were as follows: Klebsiella spp, 10%–19%; Serratia spp, 16%–33%; and Enterobacter spp, 22%–45%. Serratia spp were less resistant to third-generation cephalosporins than Enterobacter spp. E. coli isolates resistant to piperacillin, gentamicin, and the fluoroquinolones accounted for only 4% of all E. coli isolates. Imipenem was the most active agent against our isolates. After imipenem, ciprofloxacin, and the aminoglycosides, tetracycline was the most active agent against A. baumanii . Tobramycin was more effective against A. baumanii than against Enterobacteriaceae. Tobramycin and imipenem were the most active agents against both gentamicin- and ciprofloxacin-resistant A. baumanii (Table III ). We observed the ESBL phenotype in 10 E. coli isolates (20.8%) and 11 K. pneumoniae isolates (12.2%). All K. pneumoniae and E. coli isolates with the ESBL phenotype were resistant to tetracycline. Regarding K. pneumoniae isolates, 2 were susceptible to tobramycin, 3 to gentamicin, and 4 to ciprofloxacin, but 8 were susceptible to amikacin and imipenem. Regarding E. coli isolates, 4 were susceptible to tobramycin, 7 to gentamicin, 5 to ciprofloxacin, and 8 to amikacin, but all were susceptible to imipenem. Discussion Contrary to the findings of the Turkish antimicrobial resistance study group [ 3 ], our Klebsiella isolates were more susceptible to third-generation cephalosporins (42.6% vs. 81.6% for ceftazidime; 65.8% vs. 85.7% for cefotaxime), aztreonam (44.0% vs. 65.6%), and ticarcillin-clavulanate (37.0% vs. 60.3%). Klebsiella spp were 81.6% susceptible to ceftazidime in our study; these rates are 96.6% in North America [ 4 ], 86.7% in China [ 5 ], 80.5% in Korea [ 6 ], 69.4% in Latin America [ 7 ], and 51.9% in India [ 8 ]. Although the isolation of Acinetobacter spp in respiratory specimens may reflect colonization and not necessarily infection [ 9 ], the most common site of nosocomial Acinetobacter infection is the lower respiratory tract, especially in mechanically ventilated patients [ 10 ]. Acinetobacter spp were the second most frequent gram-negative bacilli isolated from patients with pneumonia in Latin America [ 7 ]. In our survey, all compounds tested showed decreased activity among the A. baumanii isolates. Susceptibility to imipenem was >95% in Canada [ 11 ], India [ 8 ], and China [ 5 ]; susceptibility was 80.5% in our study and 55.5% in another study from Turkey [ 12 ]. The high prevalence of respiratory tract infections due to multiresistant A. baumanii will stimulate the use of carbapenems and possibly increase carbapenem resistance in our region. Only 75% of our E. coli isolates were susceptible to ciprofloxacin. However, this rate was greater in Europe (95.2%) [ 13 ], North America (93.3%) [ 4 ], and Latin America (93.9%) [ 7 ]. E. coli's susceptibility to ceftazidime was >95% in Europe [ 13 ], North America [ 4 ], China [ 5 ], and Korea [ 6 ] but only 84.8% in Latin America [ 7 ], 69.6% in our study, and 42.1% in India [ 8 ]. Imipenem, the most active compound, inhibited 97.8% of our E. coli isolates. Conversely, E. coli strains were not resistant to imipenem in Europe [ 13 ], Latin America [ 7 ], India [ 8 ], China [ 5 ], or Korea [ 6 ]. Enterobacter spp showed high rates of resistance to broad-spectrum penicillins with or without β-lactamase inhibitors (41.7% resistance to ticarcillin-clavulanate) and third-generation cephalosporins (45.2% resistance to ceftazidime). The high rates of ceftazidime resistance among Enterobacter spp suggests a high prevalence of stably derepressed AmpC cephalosporinase-producing strains. Interestingly, resistance to third-generation cephalosporins, aztreonam, and ticarcillin-clavulanate was higher in our study (28.1%–48.0%) than with the Turkish antimicrobial resistance study group (13.3%–38.3%) [ 3 ]. In their study, no Enterobacter or Serratia isolates were resistant to imipenem. In our study, however, the rates of susceptibility to imipenem were 86.2% for Enterobacter spp and 76.5% for Serratia spp. Imipenem susceptibility for these two species was >95% in other parts of the world [ 7 - 10 , 13 ]. Moreover, Serratia spp were at least 95% susceptible to ceftazidime in the United States [ 14 ], Canada [ 11 ], India [ 8 ], China [ 5 ], and Korea [ 6 ]. From 1997 to 1999, ESBL detection rates in K. pneumoniae isolates were 45.4% in Latin America, 24.6% in the Western Pacific, 22.6% in Europe, 7.6% in the United States, and 4.9% in Canada [ 15 ]; this rate was 12.2% in our survey, but the other study from Turkey reported a rate of 60.5% [ 3 ]. During this same period, ESBL detection rates in E. coli isolates were 8.5% in Latin America, 7.9% in the Western Pacific, 5.3% in Europe, 4.2% in Canada, and 3.3% in the United States [ 15 ]; this rate was 20.8% in our study. The presence of the ESBL phenotype in E. coli isolates decreased susceptibility to the aminoglycosides, tetracycline, and ciprofloxacin but not imipenem, suggesting the presence of other resistance genes in ESBL-encoding plasmids. Despite the high percentage of ESBL production in E. coli isolates, antibiotics remained reasonably effective with these isolates. Imipenem was active against all ESBL-producing E. coli isolates. E. coli remained 30.0% resistant to gentamicin; this resistance rate was 75.9% in the Western Pacific, 57.8% in Latin America, 25.7% in Europe, and 21.1% in the United States [ 15 ]. Only 0.5%–0.7% of ESBL-producing K. pneumoniae isolates were resistant to imipenem in the United States, Latin America, the Western Pacific region, and Canada [ 15 ]. Our rate (27.2%) was very high in comparison. This finding may be due to our low number of isolates or our lack of a confirmation test for the ESBL phenotype. Resistance to tetracycline among ESBL-producing K. pneumoniae strains was 61.1% in Canada, 55.1% in the Western Pacific, 52.0% in Latin America, 49.5% in Europe, and 44.4% in the United States [ 15 ], but this rate was 100% in our study. Resistance to ciprofloxacin among ESBL-producing K. pneumoniae strains was 44.2% in the Western Pacific, 34.6% in the United States, 24.3% in Europe, 23.1% in Latin America, 22.2% in Canada, and 63.6% in our study. We found only one imipenem-resistant E. coli isolate. It was resistant to ampicillin, ticarcillin, and piperacillin but susceptible to ceftazidime, ceftriaxone, and aztreonam. This profile suggests an oxacillinase with carbapenemase properties. This finding is interesting because class D enzymes have been found only in Acinetobacter spp [ 16 ]. Two imipenem-resistant Klebsiella spp were resistant to all β-lactams, including aztreonam. These species were probably expressed a metallo-β-lactamase with additional mechanisms (efflux, cephalosporinase hyperproduction) [ 16 ]. The absence of a confirmation test for the ESBL phenotype limits the impact of our results. On the other hand, it is known that supplemented media (blood) can alter the zone diameters for several agents and bacterial species. Despite these limitations, our data can be used for local therapeutic choices. Conclusions We previously presented the antibiotic susceptibility patterns of 249 respiratory isolates of P. aeruginosa during the same period [ 2 ]. When combined with our current data, these results show that, in our region, ceftazidime can still be used for managing respiratory infections due to gram-negative aerobic bacteria in combination with aminoglycosides. It appears that increasing imipenem resistance may cause serious therapeutic problems in future. Methods We collected our data from 01/01/1999 to 01/01/2002 at the microbiology laboratory of the University of Cumhuriyet. We processed the data to eliminate duplicate registrations. We excluded any isolates collected within 7 days when they came from the same specimen source of the same patient. We initially identified the isolates using such routine methods as colonial/microscopic morphology and enzymatic characteristics. We confirmed species identification with API-bioMerieux products. We retrospectively analyzed antibiotic susceptibility patterns in 238 respiratory isolates of Enterobacteriaceae members and 90 respiratory isolates of A. baumanii . We accepted all consecutive isolates because we did not attempt to distinguish actual pathogens from colonizing strains. Specimen types consisted of sputum (54.2%), transtracheal/endotracheal aspirates (24.6%), and bronchial lavage fluid (21.2%). We cultured sputum samples that showed no oral contamination in the presence of sputum purulence or a suspected lower respiratory infection. We confirmed susceptibility to 18 antimicrobial agents using disk diffusion according to the National Committee for Clinical Laboratory Standards (NCCLS) guidelines [ 17 ], except insofar as we supplemented Mueller-Hinton agar with 5% defibrinated blood. We aerobically incubated the inoculated plates at 35°C and evaluated them after 24 h. For quality control of the disk diffusion tests, we used E. coli ATCC 25922 and Staphylococcus aureus ATCC 25923 strains. The disks (Oxoid) contained the following antimicrobials: ampicillin (10 μg), ampicillin/sulbactam (20 μg), piperacillin (100 μg), aztreonam (30 μg), cefazolin (30 μg), cefuroxime (30 μg), cefotaxime (30 μg), ceftriaxone (30 μg), ceftazidime (30 μg), amikacin (30 μg), gentamicin (10 μg), tobramycin (10 μg), ciprofloxacin (5 μg), imipenem (10 μg), tetracycline (30 μg), and cotrimoxazole (25 μg). Until November 1999, our microbiology laboratory based susceptibility rates on disk zone sizes; thereafter, we used a coordinating laboratory to determine the minimal inhibitory concentrations (MICs) of these 18 antimicrobial agents, accomplished with a standardized microdilution technique (Sceptor System, Becton Dickinson Microbiology System). We used this system to determine MICs for all strains. We used the NCCLS criteria to identify possible extended-spectrum β-lactamase (ESBL)-producing strains of Klebsiella spp and E. coli when MICs were increased (2 mg/mL) with ceftazidime and/or ceftriaxone and/or aztreonam [ 18 ], but we lacked a test to confirm the ESBL phenotype. We classified our results into two categories. We labeled strains deemed susceptible by the disk diffusion method or microdilution technique as susceptible . We labeled all resistant and intermediate isolates as resistant . We divided the number of resistant isolates by the total number of isolates that had undergone susceptibility testing. Authors' contributions UG had primary responsibility for study design, collection of data, and writing the manuscript. IA, MZB, TE had intellectual contribution as well as the writing of manuscript. All authors read and approved the final manuscript. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC515300.xml |
523842 | Getting the Fluid Balance Right in Malaria | null | Acidosis is a major cause of death in patients with malaria, although what causes acidosis is still unclear. One possibility is that hypovolemia contributes to the problem, and that rehydration therapy could be of benefit. Now, Sanjeev Krishna and colleagues have shown that in children with severe malaria dehydration is not severe and is not correlated with other measures of disease severity. “The optimum resuscitation approach in severe childhood malaria remains to be defined,” says Nick White (Mahidol University, Thailand), the academic editor of the paper. “The relative advantages of blood, colloids, and crystalloids need to be characterized.” Anopheles gambiae, the principal vector of malaria (Photo: Jim Gathany) Every year around 200 million people worldwide contract malaria, of whom over a million die. The vast majority of those who die are children under five years, mostly in Africa, since young children have had little chance to acquire any immunity. Fluid resuscitation is generally considered to be a cornerstone of treatment—but how much fluid should be given? Some researchers believe that surrogate signs of fluid depletion—such as tachycardia, reduced capillary refill time, and reduced urine excretion—suggest that there is substantial volume depletion. The reason that the amount of fluid given matters so much is that giving too much, especially of hypotonic solutions, can lead to electrolyte imbalance, especially hyponatremia and hypokalemia. Research efforts have been hampered by not having an easy way to assess in patients the fluid depletion in different compartments of the body, i.e., total body water and extracellular and intracellular water volume. Krishna and colleagues used heavy-water distribution to calculate the total body water and bromide distribution to determine the extracellular volume in 19 children with moderately severe malaria and 16 with severe malaria in Gabon. By subtracting extracellular volume from total body water, they were able to calculate intracellular volume for each child. They also used a less invasive and more rapid method of determining water volumes based on using bioelectrical impedance to calculate the volume. None of the children were severely dehydrated (defined as more than 100 ml/kg depletion), and only three of the children with severe anemia had fluid depletion, which was moderate (60–90 ml/kg depletion). “This challenges the view that dehydration is a major contributor to the pathology of this frequently lethal disease,” says White. So based on these data, obtained from a carefully studied, albeit small group of children, what should people who treat children with malaria do? The authors' first recommendation is that clinicians should think again about how vigorously they rehydrate children, and if they have access to ways of assessing fluid volume more precisely, they should do so (not a trivial undertaking in many hospitals where these children are treated). And certainly the methods used by Krishna and colleagues should undergo wider testing in larger groups of children to confirm their usefulness. Until the worldwide efforts to prevent malaria come to fruition, refining the management of infected children will remain a cornerstone of the efforts against this devastating disease. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC523842.xml |
538279 | Comparison of energy-restricted very low-carbohydrate and low-fat diets on weight loss and body composition in overweight men and women | Objective To compare the effects of isocaloric, energy-restricted very low-carbohydrate ketogenic (VLCK) and low-fat (LF) diets on weight loss, body composition, trunk fat mass, and resting energy expenditure (REE) in overweight/obese men and women. Design Randomized, balanced, two diet period clinical intervention study. Subjects were prescribed two energy-restricted (-500 kcal/day) diets: a VLCK diet with a goal to decrease carbohydrate levels below 10% of energy and induce ketosis and a LF diet with a goal similar to national recommendations (%carbohydrate:fat:protein = ~60:25:15%). Subjects 15 healthy, overweight/obese men (mean ± s.e.m.: age 33.2 ± 2.9 y, body mass 109.1 ± 4.6 kg, body mass index 34.1 ± 1.1 kg/m 2 ) and 13 premenopausal women (age 34.0 ± 2.4 y, body mass 76.3 ± 3.6 kg, body mass index 29.6 ± 1.1 kg/m 2 ). Measurements Weight loss, body composition, trunk fat (by dual-energy X-ray absorptiometry), and resting energy expenditure (REE) were determined at baseline and after each diet intervention. Data were analyzed for between group differences considering the first diet phase only and within group differences considering the response to both diets within each person. Results Actual nutrient intakes from food records during the VLCK (%carbohydrate:fat:protein = ~9:63:28%) and the LF (~58:22:20%) were significantly different. Dietary energy was restricted, but was slightly higher during the VLCK (1855 kcal/day) compared to the LF (1562 kcal/day) diet for men. Both between and within group comparisons revealed a distinct advantage of a VLCK over a LF diet for weight loss, total fat loss, and trunk fat loss for men (despite significantly greater energy intake). The majority of women also responded more favorably to the VLCK diet, especially in terms of trunk fat loss. The greater reduction in trunk fat was not merely due to the greater total fat loss, because the ratio of trunk fat/total fat was also significantly reduced during the VLCK diet in men and women. Absolute REE (kcal/day) was decreased with both diets as expected, but REE expressed relative to body mass (kcal/kg), was better maintained on the VLCK diet for men only. Individual responses clearly show the majority of men and women experience greater weight and fat loss on a VLCK than a LF diet. Conclusion This study shows a clear benefit of a VLCK over LF diet for short-term body weight and fat loss, especially in men. A preferential loss of fat in the trunk region with a VLCK diet is novel and potentially clinically significant but requires further validation. These data provide additional support for the concept of metabolic advantage with diets representing extremes in macronutrient distribution. | Introduction Recent reports showing a greater weight loss with a free-living very low-carbohydrate ketogenic (VLCK) than a low-fat diet after 3 and 6 months [ 1 - 5 ] has generated interest in mechanisms that may account for these responses. Earlier work that involved comparison of isocaloric formula VLCK and low-fat (LF) diets [ 6 ], indicated that weight loss was greater with a VLCK, suggesting a metabolic advantage (i.e., a greater weight loss with one diet over another with different macronutrient distribution but the same energy content) [ 7 , 8 ]. Although several studies have shown that VLCK diets result in greater reductions in body mass, it remains unclear how these diets affect the composition of weight loss and the distribution of fat loss. Some early reports show that VLCK diets result in preferential loss of fat and preservation of lean body mass [ 9 - 12 ], suggestive of a nutrient partitioning effect. In accordance with this notion, we recently reported that a free-living 6-week VLCK diet prescribed to be isoenergetic resulted in significant decreases in fat mass and increases in lean body mass in normal-weight men [ 13 ]. However, other studies have not shown a preferential loss of fat on a VLCK diet [ 14 ]. No studies have examined the effects of a VLCK diet on the distribution of fat loss. Since accumulation of fat in the abdominal area is associated with insulin resistance, diabetes, dyslipidemias and atherosclerosis [ 15 ], demonstration of the effects of a VLCK diet on regional fat distribution is important. Volek and Westman [ 16 ] have reviewed the potential favorable effects of VLCK diets while other reviews that have focused on the potential adverse effects of VLCK diets caution to avoid or limit their use [ 17 - 19 ]. Given the varying opinions in respect to VLCK diets, we thought it was important to provide additional information related to the effects of a VLCK diet on weight loss, body composition, and regional fat distribution. We previously reported that a VLCK diet has favorable effects on biomarkers for cardiovascular disease [ 20 - 22 ]. The primary purpose of this investigation was to compare the effects of isocaloric, energy-restricted (-500 kcal/day from estimated needs to maintain weight) VLCK and LF diets on weight loss, body composition, trunk fat, and REE in overweight men and women. Methods Subjects A total of twenty-eight healthy volunteers (15 men and 13 women) were recruited by flyers and word-of-mouth. Subjects were between 20 and 55 y, nonsmokers, and greater than 25 percent body fat determined via dual-energy X-ray absorptiometry (DEXA). Subjects went through a thorough screening procedure to ensure they would be committed to completing the study. Exclusion criteria included a body mass >145 kg (because of technical difficulties in performing DEXA), post-menopausal women, overt diabetes, cardiovascular, respiratory, gastrointestinal, thyroid or any other metabolic disease, weight change ± 2 kg over the last month, adherence to special diets, use of nutritional supplements (except a daily multi-vitamin/mineral), and use of medications to control blood lipids or glucose. The majority of subjects were sedentary and were instructed not to start an exercise program during the study. Those who were active were instructed to maintain the same level of physical activity throughout the study. Baseline characteristics of men and women stratified by diet order are shown in Table 1 (see additional file 1 ). The study was conducted in accordance with the guidelines of the Institutional Review Board at the University of Connecticut. Experimental Approach Our primary research question was to compare VLCK and LF diets on weight loss, fat loss, and trunk fat loss. We addressed this in several ways. First, subjects were initially randomly assigned to either a LF or VLCK weight loss diet. Weight loss, body composition (fat mass and lean body mass), trunk fat, and resting energy expenditure (REE) were assessed before and after each diet (Phase I). Because there is often a great deal of variation in response to diet, we decided that a direct comparison of responses to a VLCK and LF diet should be made in the same person. To achieve this aim, we asked subjects to switch to the opposite diet after completion of the first diet period (Phase II), after which the same measurements were assessed (i.e., each subject consumed a VLCK and LF diet). This experimental approach allowed us to compare these two diets in two ways: a between group comparison of subjects who either consumed a VLCK or LF diet during Phase I, and a within group comparison of subjects who consumed both a VLCK and LF diet. The within group comparison was further analyzed to determine if the order of diets had any effect on the responses. Subjects kept detailed food diaries during three 1 wk periods (21 days total) of each diet. Men consumed each diet for 50 days whereas women consumed the diets for approximately 30 days in order to control for possible effects of menstrual phase on some of the dependent variables measured in this study [ 23 , 24 ]. All testing for women was performed between days 2–4 of the follicular phase as self-reported by the women. Diet Interventions Both experimental diets were designed to be hypoenergetic (-500 kcal/day). Energy levels were assigned to the nearest 200 kcal increment based on REE obtained using indirect calorimetry at the start of the study and appropriate activity factors. Standard diabetic exchange lists were used to ensure a constant energy and macronutrient balance of protein (~20% energy), fat (~25% energy), and carbohydrate (~55% of energy) during the LF diet. The LF diet was also designed to contain <10% saturated fat and <300 mg cholesterol (i.e., a Step-I diet). Foods encouraged during the LF diet included whole grains (breads, cereals, and pastas), fruit/fruit juices, vegetables, vegetable oils, and low-fat dairy and meat products. We developed customized diabetic exchange lists for the VLCK diet period in order to ensure a constant energy and balance of protein (~30% energy), fat (~60% energy), and carbohydrate (~10% of energy) throughout the day. There were no restrictions on the type of fat from saturated and unsaturated sources or cholesterol levels. Foods commonly consumed on the VLCK diet were beef (e.g., hamburger, steak), poultry (e.g., chicken, turkey), fish, oils, various nuts/seeds and peanut butter, moderate amounts of vegetables, salads with low-carbohydrate dressing, moderate amounts of cheese, eggs, protein powder, and water or low-carbohydrate diet drinks. Low-carbohydrate bars and shakes (Atkins Nutritionals, Inc., Hauppauge, NY) were provided to subjects during the VLC diet. A daily multi-vitamin/mineral complex that provided micronutrients at levels ≤ 100% of the RDA was given to subjects during both experimental diets. All subjects received extensive initial instruction and follow-up by registered dietitians on how to translate foods/meals into diabetic exchanges. Subjects were also provided with a packet outlining specific lists of appropriate foods, recipes, and sample meal plans that were compatible with their individual preferences for both experimental diets. Subjects received thorough instructions for completing detailed weighed food records during three 7-day periods (21 days total) for each diet. Food measuring utensils and scales were provided to subjects to ensure accurate reporting of food/beverage amounts consumed. Food diaries were analyzed for energy and macro/micronutrient content (NUTRITIONIST PRO™, Version 1.3, First Databank Inc, The Hearst Corporation, San Bruno, CA). The program had no missing values for the nutrients reported. The database was extensively modified by our group to include new foods and recipes. To ensure that carbohydrates were restricted throughout the VLCK diet, subjects tested their urine daily using reagent strips (Bayer Corporation, Elkhart, IN) at the same time of day and recorded the result on log sheets. The test is specific for acetoacetic acid, which produces a relative color change when it reacts with nitroprusside. We have found this to be a very sensitive indicator of carbohydrate restriction and compliance to a VLCK diet in our prior studies [ 13 , 21 , 22 , 25 ]. Subjects were required to report to the laboratory each week to monitor weight, dietary compliance, and check the level of ketones (during the VLCK diet only). Subjects received follow-up counseling and dietetic education in necessary. Body Mass and Body Composition Body mass and body composition were measured in the morning after a 12 h overnight fast. Body mass was recorded to the nearest 100 g on a digital scale (OHAUS Corp., Florham Park, NJ) with subjects either nude or wearing only underwear. Whole body and regional body composition were assessed using a fan-beam DEXA (Prodigy™, Lunar Corporation, Madison, WI). Regional analysis of the trunk was assessed according to anatomical landmarks by the same technician using computer algorithms (enCORE version 6.00.270). Coefficients of variation for lean body mass, fat mass, and bone mineral content on repeat scans with repositioning on a group of men and women in our laboratory were 0.4, 1.4, and 0.6%, respectively. Resting Energy Expenditure Resting energy expenditure measurements were made by indirect calorimetry (MedGraphics CPX/D, Medical Graphics Corporation, St. Paul, MN) after an overnight fast (>12 h) with subjects resting supine in comfortable thermoneutral conditions. The metabolic cart was calibrated with a standard gas mixture each morning. Subjects were instructed to relax quietly in a dimly lit room without sleeping for 30 min and oxygen consumption (VO 2 ) and VCO 2 were averaged during the last 20 min for determination of REE [ 26 ]. We assessed reliability on two subjects who were tested two times per day for six consecutive days. The coefficient of variation for REE (kJ/day) was 2.95% for duplicate measures on the same day and 6.20% between days. Statistical Analysis Changes in body weight, body composition, and REE between diets were assessed using independent t-tests for between group comparisons (i.e., Phase I responses) and dependent t-tests were used to assess within group comparisons. All statistical analyses were performed with Statistica 5.5 for windows (StatSoft Inc, Tulsa, OK). Significance was set at P ≤ 0.05. Results Dietary nutrient intakes (Table 2) There were no differences in dietary nutrient intakes between groups at baseline. Subjects complied very well with the given instructions for both diet interventions according to analysis of diets records. During the diet interventions, all dietary nutrients were significantly different between the VLCK and LF diets with the exception of total dietary energy (women only) and alcohol (see additional file 1 Table 2). Dietary energy was higher during the VLCK than the LF diet in men. We achieved our goals for each diet with <25% of total energy coming from fat on the LF diet and <10% of total energy coming from carbohydrate on the VLCK diet. All subjects were in ketosis throughout the VLCK diet as indicated by color changes on the urinary reagent strips (data not shown), indicating compliance in terms of carbohydrate restriction. Between group comparison of subjects who either consumed a VLCK or LF diet The reductions in body mass, total fat mass, and trunk fat mass were significantly greater after the VLCK than the LF diet for men, but not for women (Fig 1 ). The greater reduction in trunk fat was not merely due to the greater total fat loss in men, because the ratio of trunk fat/total fat was also significantly reduced during the VLCK diet in men (VLCK 57.9 ± 1.8 to 57.1 ± 1.7%; LF 60.2 ± 1.3 to 61.4 ± 1.1%). Although the ratio of trunk fat/total fat in women was reduced more on the VLCK diet (51.9 ± 2.4 to 51.2 ± 2.3%) compared to the LF diet (44.2 ± 2.2 to 44.5 ± 2.3%), this was not significant. There were no significant differences in REE expressed in absolute terms between the VLCK diet (men 2005 ± 283 to 1865 ± 96; women 1177 ± 43 to 1161 ± 101 kcal/day) and the LF diet (men 2352 ± 316 to 2119 to 137; women 1319 ± 92 to 1224 ± 100 kcal/day). Expressed relative to body mass, REE was maintained in men consuming the VLCK diet (19.6 ± 0.7 to 19.8 ± 0.7 kcal/kg) but decreased on the LF diet (20.4 ± 1.0 to 19.0 ± 0.8 kcal/kg). As expected, the respiratory exchange ratio decreased on the VLCK compared to the LF diet further indicating compliance to the VLCK diet. Figure 1 Mean decreases in body mass, total fat mass, trunk fat mass, and lean body mass in men who consumed a very low-carbohydrate ketogenic (VLCK) diet ( n = 8) or a low-fat (LF) diet and in women who consumed a VLCK ( n = 7) and LF ( n = 6) diet. * P < 0.05 from LF change in men (independent t-test). Within group comparison of subjects who consumed both a VLCK and LF diet Dependent t-tests were used to assess the difference between changes on the VLCK and LF diets. Again, the VLCK diet resulted in significantly greater reductions in body mass, total fat mass, and trunk fat mass for men. For these variables, the reductions were also significantly greater in women, in contrast to the results from between group comparisons (Fig 2 ). Individual data showing the comparison between diets for each person is shown for body mass (Fig 3 ), total fat mass (Fig 4 ), and trunk fat mass (Fig 5 ). In men, a majority benefited more from the VLCKD in terms of weight loss (11/15 subjects), total fat loss (11/15 subjects), and trunk fat loss (12/15 subjects). In women, a majority also benefited more from the VLCK diet in terms of weight loss (8/13 subjects), total fat loss (10/13 subjects), and trunk fat loss (12/13 subjects). It is noteworthy that 5 men showed more than a 10 pound difference in weight loss when the diets were compared. There was a preferential loss of fat in the trunk region as evidenced by significantly greater reduction in the ratio of trunk fat to total body fat after the VLCKD in both men and women. There were no significant differences in REE responses between diets. Figure 2 Mean decreases in body mass, total fat mass, trunk fat mass, and lean body mass in men ( n = 15) and women ( n = 13) who consumed both a very low-carbohydrate ketogenic (VLCK) and a low-fat (LF) diet in a randomized and balanced fashion. * P < 0.05 from LF change (dependent t-test). Figure 3 Individual differences between weight loss on a very low-carbohydrate ketogenic (VLCK) diet minus weight loss on a low-fat (LF) diet for each person. Positive numbers reflect greater weight loss on the VLCK, whereas negative numbers indicate greater weight loss on the LF diet. Red circles = order of diets VLCK then LF. Blue diamonds = order of diets LF then VLCK. Figure 4 Individual differences between total fat loss on a very low-carbohydrate ketogenic (VLCK) diet minus total fat loss on a low-fat (LF) diet for each person. Positive numbers reflect greater weight loss on the VLCK, whereas negative numbers indicate greater weight loss on the LF diet. Red circles = order of diets VLCK then LF. Blue diamonds = order of diets LF then VLCK. Figure 5 Individual differences between trunk fat loss on a very low-carbohydrate ketogenic (VLCK) diet minus trunk fat loss on a low-fat (LF) diet for each person. Positive numbers reflect greater weight loss on the VLCK, whereas negative numbers indicate greater weight loss on the LF diet. Red circles = order of diets VLCK then LF. Blue diamonds = order of diets LF then VLCK. The results presented thus far indicate that VLCK diets result in superior weight loss and fat loss in men, and to a lesser extent in women, compared to a low-fat diet. To determine if this finding was influenced by the order the diets were implemented, we compared the responses to both diets between those who consumed the VLCK diet first to those who consumed the LF diet first. The individual responses to both diets over time are shown for body mass (Fig 6 ), total fat mass (Fig 7 ), and trunk fat mass (Fig 8 ). Statistically comparing the responses to a VLCK and LF diet within subjects, the only variable that was significantly affected by the order of the diet was body mass. In other words, the advantage of the VLCK over the LF diet was more dramatic for those who started the VLCK first. The individual responses reveal that three men and four women who did VLCK first, actually regained body mass and fat mass after the switch to the LF diet, whereas no subjects regained weight or fat mass after switching to the VLCK diet. Figure 6 Individual changes in body mass in men (upper panels) and women (lower panels) who started on a very low-carbohydrate ketogenic (VLCK) and switched to a low-fat (LF) diet (left panels) and vice versa (right panels). Mean response is shown in red. Figure 7 Individual changes in total fat mass in men (upper panels) and women (lower panels) who started on a very low-carbohydrate ketogenic (VLCK) and switched to a low-fat (LF) diet (left panels) and vice versa (right panels). Mean response is shown in red. Figure 8 Individual changes in trunk fat mass in men (upper panels) and women (lower panels) who started on a very low-carbohydrate ketogenic (VLCK) and switched to a low-fat (LF) diet (left panels) and vice versa (right panels). Mean response is shown in red. Discussion We previously reported superior responses with a VLCK over a LF diet in a number of cardiovascular risk factors in these subjects [ 25 , 27 ]. The results of this study demonstrate that short-term VLCK diets also outperform LF diets in terms of weight loss and fat loss. These effects occurred despite apparently similar energy deficits between diets and in the case of men, significantly greater energy intake. Greater weight loss with a VLCK over a LF diet is consistent with the findings from other studies, and provides further support for the concept of metabolic advantage [ 7 , 8 ]. Since food was not provided this conclusion cannot be made with certainty, but we find it highly unlikely that any potential error in quantifying energy intake would account for the dramatic differences in weight and fat loss between diets. We can say with confidence that we studied subjects that were restricting carbohydrates to very low levels as verified by dietary food records, urine ketones, and low resting respiratory exchange ratios obtained with indirect calorimetry. The basic principle on which weight loss diets are based is to reduce dietary energy intake below energy expenditure. Whether the relative composition of macronutrients can influence the magnitude or composition of weight loss achieved on an energy-restricted diet has been a point of contention. Several comparisons of isocaloric VLCK and LF diets, like the current report, show greater weight loss on a VLCK diet [ 6 , 16 ] supporting the long held notion of a metabolic advantage [ 28 ]. Given such evidence, it is difficult to understand the alternate position claiming a calorie must be a calorie in order to satisfy the first law of thermodynamics [ 29 ]. Although the origin of the difference in weight loss between VLCK and LF diets remains controversial, such a response clearly does not violate any thermodynamic laws [ 7 ]. Not all studies have shown greater weight loss with a VLCK diet [ 30 ] and the specific conditions that are required to elicit a metabolic advantage remain unknown. One argument is that the greater weight loss on ad libitum VLCK diets is a result of spontaneously reducing energy intake [ 31 ], and this has been reported previously [ 32 ]. A reduction in energy intake on a VLCK diet has a logical physiologic basis and could account for a portion of the greater weight observed in studies that involved free-living ab libitum VLCK diets. Ketone levels increase several-fold on a VLCK diet, and β-hydroxybutyrate (the major circulating ketone body) has been shown to directly inhibit appetite [ 33 ]. Also, the low glycemic nature of a VLCKD may prevent transient dips in blood glucose, which can occur with higher carbohydrate diets. Thus, avoidance of hypoglycemic episodes may reduce appetite [ 34 ]. In this study we did not report a significantly lower energy intake on the VLCK compared to the LF diet. In fact, a higher energy intake was observed on the VLCK diet in men. In this case, it is often claimed that inaccurate reporting of dietary intake or errors in nutrient databases (e.g., overestimation of calories from certain cuts of meats) account for the greater weight reducing effects of VLCK diets. On the other hand, LF diets are frequently encouraged because of their high bulk and over-reporting seems as likely on a LF as a VLCK diet. In the absence of a clear reason why error in these studies should always go in one direction – LF rarely do better than VLCK – one has to take the data at face value. Also, the large difference in weight loss between men on the VLCK and LF diets in the present study suggests that at least some impact of macronutrient composition is being seen. Metabolic advantage may occur on a VLCK diet due to the demand on protein turnover for gluconeogenesis [ 35 ], greater thermogenic effect of protein and loss of energy as heat [ 36 , 37 ], and/or excretion of energy in the form of ketones via urine, feces, and/or sweat. Although we did not see a difference in REE, the metabolic advantage on a VLCK diet may be below the sensitivity of our measurements. Further, since REE was obtained in a postabsorptive state, this does not rule out a potential benefit derived from the acute postprandial thermic effect of protein ingestion. In terms of REE, there was a slight advantage for men on the VLCK diet when expressed relative to body mass, which could benefit long-term weight maintenance but this needs to be validated in studies of longer duration. Although the issue of whether VLCK diets result in greater weight loss compared to LF diets has obvious significance, a primary purpose of this study and an equally important question relates to the composition of weight loss. In a meta-analysis, Garrow and Summerbell [ 38 ] predict from regression analysis that for a weight loss of 10 kg by dieting alone, the expected loss from fat mass is 71%. The few studies that have assessed body composition suggest that VLCK diets may result in preferential loss of fat mass. Benoit et al. [ 10 ] showed that a 10 day VLCK diet (4.2 MJ/day) resulted in a weight loss of -6.6 kg in obese men, 97% of which was fat mass. Young et al. [ 9 ] compared the effects of three isoenergetic (7.5 MJ/day), isoprotein (115 g/day) diets containing varying carbohydrate contents (30, 60, and 104 g/day) on weight loss and body composition in obese men. After 9 weeks, weight loss was 16.2, 12.8, and 11.9 kg and fat accounted for 95%, 84%, and 75% of the weight lost, respectively. Willi et al. [ 11 ] showed that an 8 week VLCK diet (2.7–3.0 MJ/day) resulted in a weight loss of -15.4 kg and an increase in lean body mass of +1.4 kg in obese adolescents. An 8-week VLCK diet in overweight women resulted in a decrease in body mass of -5 kg, 80% of which was fat mass [ 12 ]. Our laboratory recently reported that a 6 week VLCK diet resulted in significant decrease in body mass (-2.2 kg), entirely accounted for by a decrease in fat mass (-3.3 kg) and concomitant increases in lean body mass (+1.1 kg) in normal-weight men [ 13 ]. The body composition results from the present study are in closer agreement with predictions from the meta-analysis [ 38 ]. A novel and potentially clinically significant finding was a preferential loss of fat in the trunk region with a VLCK diet, which was approximately three-fold greater during the VLCK than the LF diet. Upper body fat carries a greater health risk than fat stored in other regions of the body and thus an effective weight loss approach should consider the regional distribution of fat loss. Proportionally, trunk fat mass comprised less of the total fat mass after the VLCK but not the LF diet. The mechanisms regulating composition of weight loss and distribution of fat loss during VLCK diets remain unclear, but could be mediated in part by changes in hormones such as insulin, leptin, or cortisol that could differentially impact nutrient partitioning. In summary, this study showed greater weight loss and fat loss preferentially from the trunk region in subjects on a closely monitored free-living VLCK diet compared to a LF diet. These diets were prescribed to be energy restricted and isocaloric. The superiority of the VLCK diet over the LF diet was most dramatic for men, but when individual responses were examined, a group of women clearly showed metabolic advantage as well. Indeed, 12/13 women experienced greater fat loss in the trunk region during the VLCK diet compared to the low-fat diet. Such a response is consistent with a metabolic advantage of VLCK diets. The ultimate proof for such a theory will depend on the findings from carefully controlled feeding and metabolic studies that encompass physiological measurements to isolate plausible mechanisms. Supplementary Material Additional File 1 Table 1. Baseline characteristics of men and women based on their starting diet. Table 2. Daily intakes of dietary energy and nutrients at baseline and during both diets. Click here for file | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC538279.xml |
314480 | Brain Activity during Slow-Wave Sleep Points to Mechanism for Memory | null | How does your brain pass the time while you're sleeping? If you've ever wrestled the demons of insomnia, you know what sleepless nights can do to your mental agility. Sleep cycles in mammals are characterized by two distinct, successive sleep stages: slow wave and rapid eye movement (REM). Both stages of sleep have uniquely associated electrical activity in the brain, which neuroscientists can measure by placing elec-trodes on the brain during sleeping and waking states. What neuroscientists can't easily measure is the purpose of these two sequential sleep stages. The notion that sleep helps to improve memory was introduced over 80 years ago. Since then, several studies have demonstrated that sleep deprivation following the acqui-sition of a new memory strongly impairs its consolidation. Insight into the mechanisms underlying this effect came from the observation that neuronal activity patterns detected during waking reappear during ensuing sleep, suggesting that newly acquired “memory traces” may be replayed in the brain to solidify neural connections and thus “consolidate” memory. These reverberating patterns of activity have been observed in both mammals and birds, pointing to a very general biological phenomenon. Still, the relationship between brain reverberation and memory consolidation remains unclear for a number of reasons. First, studies to date have observed only subtle, short-lived reverberations lasting less than an hour and can't explain the memory-disrupting effects of sleep deprivation applied several hours and even days after initial memory encoding. And since brain reverberation in mammals has only been investigated in the hippocampus and cerebral cortex, it is unclear whether the phenomenon is specific to this neural circuit or is a more general property of the brain. Furthermore, reverberation studies have so far relied on neural activity measured in animals that were highly trained on specific laboratory tasks and therefore may simply not be representative of the acquisition of new memories. Finally, experience-dependent neural reverberation has been detected in both phases of sleep as well as waking, but no quantitative comparison of the different contributions of each state has been established. In a study designed to address these concerns, Sidarta Ribeiro and his colleagues at Duke University in Durham, North Carolina, recorded over a hundred neurons continuously over the course of the normal sleep--wake cycle in rats, focusing on four major forebrain areas that are essential for rodent-specific behaviors. Halfway through the recording time, animals were transiently allowed to explore four strictly novel objects, each of them designed to provide different spatial and sensory cues. The researchers found that in all the forebrain areas examined the neuronal firing patterns recorded when the rats initially explored the new objects reverberated for up to 48 hours after these objects were removed. The reverberation of neuronal activity sampled when rats explored familiar environs was insignificant. Reverberation was most significant during slow-wave sleep (a state that accounts for nearly 40% of a rat's life), decreased during waking periods, and was highly variable during REM sleep. In this study, Ribeiro et al. demonstrate that long-lasting neuronal reverberation following novel waking experiences can occur in several forebrain sites and is strongly enhanced during slow-wave sleep. Because neuronal reverberations are sustained for long periods, this may provide a mechanism to recall and amplify memories until they are effectively stored. On the basis of differences observed between REM and slow-wave sleep in this and previous studies, the authors propose that the two phases of sleep play separate and complementary roles in memory consolidation. Thus, the two stages of sleep give the brain a chance to process the novel events of the day in peace. Sleeping rats | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC314480.xml |
550648 | Leisure-time versus full-day energy expenditure: a cross-sectional study of sedentarism in a Portuguese urban population | Background Low physical activity is known to be a potential risk factor for cardiovascular disease. With high prevalence of cardiovascular diseases in the Portuguese urban population, little is known about how sedentary this population is and what factors are associated to sedentary lifestyles. This study's objective was to examine sedentary lifestyles and their determinants through a cross-sectional study. Methods 2134 adults (18 years and older) were interviewed using a standard questionnaire, comprising of social, behavioural and clinical information. Time spent in a variety of activities per day, including: work, household chores, sports, sedentary leisure time and sleep, were self-reported. Energy expenditure was estimated based on the related metabolic equivalent (MET) and time spent in each activity (min/day). Those with less than 10% of energy expenditure at a moderate intensity of 4 METs or higher were categorised as sedentary. The proportion of sedentary people and 95% Confidence Intervals (CI) were calculated, and the magnitude of associations, between sedentary lifestyles and the population characteristics, were computed as age-adjusted odds ratios using logistic regression. Results Sedentarism in both genders during leisure time is high at 84%, however in full day energy expenditure, which includes physical activity at work, sleeping hours and household chores, 79% of males and 86% of females are found to be sedentary. In leisure-time only, increased age is associated with higher odds of being sedentary in both genders, as well as in women with increased BMI. In comparison, in full-day energy expenditure, sedentarism is more likely to occur in those with higher levels of education and in white-collar workers. Conclusions A high prevalence of sedentarism is found in the study participants when measuring leisure-time and full-day energy expenditure. The Portuguese population may therefore benefit from additional promotion of physical activity. | Background Physical activity has been defined by World Health Organization [ 1 ] as comprising of all movements in everyday life, including work, recreation, and sports activities and has been categorised in levels of intensity from light to moderate to vigorous. Health benefits, including decreasing risk of coronary heart disease [ 2 - 5 ] have mostly been associated with moderate to vigorous activities [ 6 ]. Practicing 30 minutes of moderate physical activity at least five days a week is widely promoted to achieve health benefits and is also felt to be an achievable lifestyle change for sedentary adults [ 1 ]. Physical activity tends to be associated with lower cardiovascular morbidity and mortality and an overall improved quality of life. Some studies [ 6 - 9 ] have defined or examined sedentary lifestyles and associated factors at the population level, however few have approached the subject in the context of Southern Europe. This may be due in part to the fact that it is difficult to classify a person as sedentary since no universally accepted classification is currently available. Previous studies have used a simple question or an evaluation of whether adults perform at least 30 minutes of moderate activity five times a week [ 10 ], or did not take part in leisure time physical activity at all [ 4 , 11 ], to classify participants as inactive or sendentary. Portugal has the highest stroke mortality rates in Western Europe and cardiovascular diseases cause approximately 40% of deaths [ 12 , 13 ]. The current study's objective was to examine sedentarism in leisure time and throughout a full day in a Portuguese urban population and to cross-sectionally assess the associations between sedentarism and demographic, social, behavioural, clinical and anthropometric factors. Methods Data was obtained as part of an ongoing cross-sectional health survey of adults living in the city of Porto, Portugal. Random digit dialling was used to select a single person over 17 years old from each household, without allowing for substitution of refusals. A participation rate of 70% was achieved [ 14 ]. Using a structured questionnaire, trained interviewers collected data from 2134 adults on demographic, personal and family medical history, and behavioural characteristics (physical activity, smoking, alcohol intake and diet) [ 15 ]. Sixty-seven participants who scored less than 24 on the Folstein mini-mental state examination [ 16 ] were considered probably unable to provide reliable information due to cognitive impairment and were excluded from the analysis. An additional 16 participants who did not fit the survey criteria (did not live in Porto or had severe disabilities and diseases) were also excluded. As well, participants missing relevant data were not included in the study analyses, leaving 2004 participants (1226 women; 778 men) in the analysis. As reported in an earlier publication [ 17 ], education was recorded as completed years of schooling and divided into three broad categories: less than 5, 5–11, and more than 11 years. Body weight was measured to the nearest 0.1 kg using a digital scale, and height was measured to the nearest centimetre in the standing position using a wall standiometer. Body mass index (BMI) was calculated as weight in kilograms divided by square height in meters. The distribution of BMI is reported by standard WHO categories and nomenclature [ 18 ]: underweight to normal (<25.0 kg/m2), overweight (25.0–29.9 kg/m2), and obese (> = 30 kg/m2). The number of self-reported medical visits occurring in the last 12 months was grouped based on tertiles (0–1, 2–3, >3). Current occupation was self-reported and divided into the three usual categories of white collar, blue-collar and retired or unemployed. White collar work included all non-manual and superior professionals such as teachers, health professionals, secretaries etc. Blue-collar work included all manual professionals including agriculturers, taxi drivers, cooks, factory workers and sewers. Women who stated that they performed domestic work in their own home and had no other employment were classified as unemployed. Each participant was also asked about chronic diseases requiring continued medical care. Energy intake was estimated based on a semi-quantitative food frequency questionnaire validated for the Portuguese population and results were presented in tertiles, separately for each gender. Alcohol intake was self-reported and classified into three categories: current drinkers (daily alcohol intake), ex-drinkers (no alcohol for more than 6 months), and never or occasional drinkers. Smoking was self-reported and classified based on the WHO categories [ 19 ]: current smoker included both daily and occasional smokers, ex-smokers were those who had not smoked a cigarette in the last 6 months, and non-smokers were those who never smoked at all. Participants completed a physical activity questionnaire designed to estimate usual individual daily energy expenditure, focused on the activity in the past year. Time spent in a variety of activities per day, including: work, transport to or from work, household chores, sports, sedentary leisure time and sleep, was self-reported and activity intensity categorised as very light, light, moderate and heavy with a corresponding average of 1.5, 2.5, 5.0 and 7.0 METs respectively, where one MET is equal to the energy expended at the basal metabolic rate or at rest [ 20 ]. Due to the manner in which these questions were presented during the face-to-face interviews, a large variation resulted in the number of hours reported per day (Average = 19 hours/day (minimum = 6.5 to maximum = 32.5 hours) with 46 (2.3%) participants reporting activity resulting in more than 24 hours per day). Energy expenditure was estimated by multiplying the related metabolic equivalent (MET) to the self-reported time spent in each activity (min/day). Participants with less than 10% of daily energy expenditure at a moderate or high intensity level (>4 METs) during leisure-time or throughout the day were categorised as sedentary, the remaining being considered active [ 21 ]. Proportions of sedentary individuals and 95% CI were calculated for both leisure-time and full-day energy expenditure, the latter including energy expended at work, during sleep and in household chores. The magnitude of associations, between sedentary lifestyles and the factors studied, were computed as age-adjusted odds ratios using logistic regression. In the analyses of the percentages of sedentarism and its associations with leisure-time energy expenditure, 15 people were excluded since they did not report any leisure-time activities. Analyses were conducted using Stata 7.0. Results In the exploration of the population studied it was found that a significant difference between men and women was noted in most baseline characteristics other than in the age distribution and the hours of sleep (mean hours of sleep per night equalled 8; 95%CI 7.9–8.1). A higher proportion of household work was undertaken by women (95.5% versus 55.5% of men), a higher proportion of men were married (84.3% versus 61.3% of women), 68.3% of women and 55.7% of men reported no chronic disease. 31% of all participants worked between 20 and 40 hours a week, with a higher percentage of men working greater than 40 hours (31.1% versus 15.2% of women). It is also worthy to note that a high percentage of both genders reported not undertaking regular leisure-time sports and exercise (69.3% of women and 58.9% of men). All subsequent analyses were performed separately for males and females. Overall sedentary lifestyle percentages (Table 1 and 2 ) are high, 83.7% (95%CI: 80.9–86.2) for males and 84.4% (95%CI: 82.2–86.3) for females during leisure time. A lower percentage was found for males with 78.8% (95%CI: 75.7–81.6) when the full day energy expenditure is calculated including physical activity at work, hours of sleep and household chores. The full-day sedentary lifestyle percentage for women, however, increased slightly to 86.1% (95%CI: 84.0–88.0). Table 1 Sedentarism in the Female Population Characteristics Leisure-time Energy Expenditure * Full-day Energy Expenditure ** N (%) % (95% CI) OR † (95% CI) % (95% CI) OR † (95% CI) 1226 (61.2) 84.4 (82.2–86.3) 86.1 (84.0–88.0) Age (years) 18–29 88 (7.2) 68.2 (57.4–77.7) 75.0 (64.6–83.6) 30–39 125 (10.2) 71.4 (62.4–79.3) 1.2 (0.6–2.1) 77.6 (69.3–84.6) 1.2 (0.6–2.2) 40–49 294 (24.0) 84.6 (80.0–88.6) 2.6 (1.5–4.5) 83.3 (78.6–87.4) 1.7 (0.9–3.0) 50–59 311 (25.4) 85.1 (80.5–88.8) 2.7 (1.5–4.6) 85.2 (80.7–88.9) 1.9 (1.1–3.4) 60–69 238 (19.4) 91.5 (87.2–94.7) 5.0 (2.7–9.6) 90.8 (86.3–94.1) 3.3 (1.7–6.3) 70+ 170 (13.9) 90.0 (84.5–94.1) 4.2 (2.1–8.2) 98.2 (94.9–99.6) 18.6 (5.4–64.1) Marital Status Married 751 (61.3) 85.3 (82.5–87.7) 86.4 (83.7–88.7) Not married 475 (38.7) 82.9 (79.1–86.1) 0.8 (0.6–1.2) 85.7 (82.1–88.6) 0.8 (0.6–1.2) Education (years) <5 years 530 (43.2) 93.7 (91.2–95.6) 87.0 (83.7–89.7) 5–11 years 330 (26.9) 84.5 (80.0–88.1) 0.4 (0.2–0.6) 83.9 (79.4–87.6) 1.2 (0.8–1.8) >11 years 366 (29.9) 70.6 (65.6–75.2) 0.2 (0.1–0.3) 86.9 (82.9–90.1) 2.2 (1.4–3.6) BMI (kg/m2) <25 455 (37.1) 77.5 (73.2–81.2) 85.3 (81.6–88.3) 25–30 452 (36.9) 85.1 (81.4–88.2) 1.3 (0.9–1.9) 85.2 (81.5–88.3) 0.7 (0.5–1.0) >30 319 (26.0) 93.1 (89.6–95.5) 2.9 (1.8–4.9) 88.7 (84.6–91.9) 0.9 (0.6–1.4) Physician visits in last year (n) 0–1 422 (34.4) 84.4 (80.5–87.7) 84.4 (80.5–87.6) 2–3 visits 381 (31.1) 79.1 (74.6–83.0) 0.6 (0.4–0.8) 84.8 (80.7–88.2) 0.8 (0.6–1.2) >3 423 (34.5) 89.0 (85.6–91.8) 1.2 (0.8–1.8) 89.1 (85.7–91.9) 1.1 (0.7–1.7) Occupation White collar worker 425 (34.7) 77.1 (72.7–81.0) 88.2 (84.7–91.1) Blue collar worker 193 (15.7) 92.1 (87.3–95.5) 3.0 (1.7–5.4) 61.7 (54.4–68.5) 0.2 (0.1–0.3) Unemployed or retired 608 (49.6) 87.0 (84.0–89.5) 1.4 (0.9–2.1) 92.4 (90.0–94.4) 1.0 (0.6–1.6) Energy Intake (kcal/day) <1800 400 (32.7) 83.3 (79.3–86.9) 1.0 (0.7–1.5) 86.8 (83.0–89.9) 1.0 (0.7–1.5) 1800–2300 461 (37.7) 82.7 (78.8–86.0) 85.7 (82.1–88.7) >2300 362 (29.6) 87.5 (83.6–90.7) 1.8 (1.2–2.7) 85.9 (81.9–89.3) 1.3 (0.9–1.9) Alcohol Use Non/Occasional-drinkers 576 (47.0) 80.7 (77.2–83.8) 83.7 (80.3–86.6) Ex-drinkers 103 (8.4) 94.2 (87.8–97.8) 2.6 (1.1–6.2) 93.2 (86.5–97.2) 1.7 (0.8–4.0) Drinkers 547 (44.6) 86.3 (83.1–89.0) 1.3 (0.9–1.3) 87.4 (84.2–90.0) 1.2 (0.9–1.8) Tobacco Use Non-smokers 893 (72.8) 84.9 (82.3–87.2) 86.6 (84.1–88.7) Ex-smokers 119 (9.7) 81.7 (73.5–88.3) 0.9 (0.6–1.6) 89.1 (82.0–94.1) 1.6 (0.9–3.0) Smokers 214 (17.5) 83.6 (77.9–88.3) 1.5 (0.9–2.3) 82.7 (77.0–87.5) 1.2 (0.8–1.8) * Leisure time energy expenditure encompasses the energy expended in all leisure activities (not including sleep, work and household chores) where being sedentary is defined as spending less than 10% of their time in activities requiring ≥ 4 metabolic equivalents (MET). ** Full-day energy expenditure encompasses the energy expended in all activities in a day where being sedentary is defined as above. † Age-adjusted Odds ratios Table 2 Sedentarism in the Male Population Characteristics Leisure-time Energy Expenditure * Full-day Energy Expenditure ** N (%) % (95% CI) OR † (95% CI) % (95% CI) OR † (95% CI) 778 (38.8) 83.7 (80.9–86.2) 78.8 (75.7–81.6) Age (years) 18–29 49 (6.3) 57.1 (42.2–71.2) 69.4 (54.6–81.7) 30–39 68 (8.7) 74.6 (62.5–84.5) 2.2 (1.0–4.9) 73.5 (61.4–83.5) 1.2 (0.5–2.8) 40–49 173 (22.2) 79.2 (72.4–85.0) 2.9 (1.5–5.6) 78.0 (71.1–84.0) 1.6 (0.8–3.2) 50–59 180 (23.1) 85.6 (79.6–90.3) 4.4 (2.2–9.0) 76.7 (69.8–82.6) 1.4 (0.7–2.9) 60–69 174 (22.4) 89.5 (84.0–93.7) 6.4 (3.0–13.5) 80.5 (73.8–86.1) 1.8 (0.9–3.7) 70+ 134 (17.2) 94.0 (88.5–97.4) 11.7 (4.7–29.2) 86.6 (79.6–91.8) 2.8 (1.3–6.2) Marital Status Married 656 (84.3) 85.1 (82.1–87.7) 78.7 (75.3–81.7) Not married 122 (15.7) 76.2 (67.7–83.5) 1.1 (0.6–2.0) 79.5 (71.3–86.3) 1.4 (0.8–2.5) Education (years) <5 years 262 (33.7) 93.4 (89.7–96.1) 74.8 (69.1–79.9) 5–11 years 282 (36.2) 84.0 (79.2–88.1) 0.5 (0.3–0.9) 78.7 (73.5–83.4) 1.6 (1.0–2.4) >11 years 234 (30.1) 72.5 (66.3–78.2) 0.3 (0.2–0.5) 83.3 (77.9–87.9) 2.5 (1.5–4.2) BMI (kg/m2) <25 279 (35.9) 79.9 (74.7–84.4) 77.4 (72.1–82.2) 25–30 375 (48.2) 84.9 (80.8–88.3) 1.2 (0.8–1.9) 78.7 (74.1–82.6) 1.1 (0.7–1.6) >30 124 (15.9) 88.7 (81.8–93.7) 1.8 (0.9–3.4) 82.3 (74.4–88.5) 1.3 (0.8–2.3) Physician visits in last year (n) 0–1 354 (45.5) 80.9 (76.3–84.8) 76.0 (71.1–80.3) 2–3 visits 236 (30.3) 84.7 (79.4–89.0) 1.1 (0.7–1.7) 79.2 (73.5–84.2) 1.1 (0.7–1.7) >3 188 (24.2) 87.8 (82.2–92.1) 1.1 (0.6–1.9) 83.5 (77.4–88.5) 1.4 (0.9–2.3) Occupation White collar worker 336 (43.2) 83.1 (79.5–86.2) 85.4 (82.0–88.3) Blue collar worker 133 (17.1) 86.6 (81.8–90.6) 1.6 (0.9–2.9) 65.6 (59.4–71.5) 0.2 (0.1–0.3) Unemployed or retired 309 (39.7) 53.8 (25.1–80.8) 0.8 (0.5–1.4) 69.2 (38.6–90.9) 0.6 (0.4–1.0) Energy Intake (kcal/day) <2300 261 (33.7) 88.1 (83.6–91.8) 1.1 (0.7–1.8) 86.6 (81.8–90.5) 1.6 (1.0–2.5) 2300–2900 283 (36.5) 84.3 (79.6–88.4) 79.5 (74.3–84.1) >2900 231 (29.8) 77.7 (71.8–82.9) 0.8 (0.5–1.3) 68.8 (62.4–74.7) 0.6 (0.4–0.9) Alcohol Use Non/Occasional drinkers 87 (11.2) 80.2 (70.2–88.0) 82.8 (73.2–90.0) Ex-drinkers 48 (6.2) 83.3 (69.8–92.5) 0.7 (0.2–1.8) 79.2 (65.0–89.5) 0.6 (0.2–1.5) Drinkers 643 (82.7) 84.2 (81.1–86.9) 1.0 (0.5–1.8) 78.2 (74.8–81.3) 0.7 (0.4–1.2) Tobacco Use Non-smokers 218 (28.0) 82.6 (76.9–87.4) 78.9 (72.9–84.1) Ex-smokers 296 (38.1) 86.1 (81.6–89.8) 1.0 (0.6–1.6) 77.0 (71.8–81.7) 0.8 (0.5–1.3) Smokers 264 (33.9) 82.1 (76.9–86.5) 1.2 (0.7–1.9) 80.7 (75.4–85.3) 1.3 (0.8–2.0) * Leisure time energy expenditure encompasses the energy expended in all leisure activities (not including sleep, work and household chores) where being sedentary is defined as spending less than 10% of their time in activities requiring ≥ 4 metabolic equivalents (MET). ** Full-day energy expenditure encompasses the energy expended in all activities in a day where being sedentary is defined as above. † Age-adjusted Odds ratios Few differences were found in the level of sedentarism in adults when considering differences in population characteristics. Younger participants tend to have lower percentages of sedentarism compared to older participants. In the leisure-time only estimation unmarried men (76.2%; 95%CI: 67.7–83.5) and female white-collar workers (77.1%; 95%CI: 72.7–81.0) tend to be more active. Women and men tend to be more active in leisure-time with increasing years of education, changing from 94% sedentarism in those with less than five years of education to 84% for those with five to eleven years of education and 72.5% for men and 70.6% for women with greater than 11 years of schooling. However, when the full-day energy expenditure is used as the estimate, these differences are no longer found and the trends with education and occupation are reversed. The lowest levels of sedentarism are found in males (74.8%; 95%CI: 69.1–79.9) with less education, and men who have a high energy intake (68%; 62.4–74.7) as well as, both male (65.6%; 95%CI: 59.4–71.5) and female (61.7%; 95%CI: 54.4–68.5) blue-collar workers. When further examining the results of the age-adjusted associations between the population characteristics and sedentarism it is found that few factors were associated with an increased proportion of sedentarism. Marital status, physician visits in the last year and tobacco consumption, once adjusted for age, were not associated with differences in energy expenditure and sedentarism. In the leisure-time only estimation, increased age was associated with higher odds of being sedentary in both males and females. Sedentarism increased with increased BMI in women (BMI 25–30 = OR 1.3 95% CI: 0.9–1.9 ; BMI >30 = OR 2.9 95%CI:1.8–4.9), as well as in women with a high energy intake (>2300 Kcal/day = OR 1.8 95%CI:1.2–2.7). Sedentarism also increased in males who were ex-drinkers when compared to non or occasional drinkers (OR 2.6 95%CI: 1.1–6.2). Following what was noted earlier, higher levels of education were associated with higher levels of activity in leisure-time in both males (5–11 years education = OR 0.5 95%CI: 0.3–0.9; >11 years education = OR 0.3 95%CI:0.2–0.5) and females (OR 0.4 95%CI: 0.2–0.6 and OR 0.2 95%CI: 0.1–0.3, respectively) and blue-collar workers were more likely to be sedentary (males: OR 1.6 95%CI: 0.9–2.9; females: OR 3.0 95%CI: 1.7–5.4). In comparison, in the full-day energy expenditure estimation, increased odds in age were not as strong for men and evidence of an association was not apparent with increased BMI or calorie intake for women. However, the reverse association was identified where those with higher amounts of education tended to be more sedentary in both males (5–11 years education = OR 1.6 95%CI: 1.0–2.4; >11 years education = OR 2.5 95%CI:1.5–4.2) and females (OR 1.2 95%CI: 0.8–1.8 and OR 2.2 95%CI: 1.4–3.6, respectively) and blue-collar workers were found to be significantly less sedentary (OR 0.2 95%CI:0.1–0.3). Relationships with energy intake also were identified in men with those consuming less than 2300 Kcal/day on average having a higher odds of being sedentary (OR 1.6 95%CI: 1.0–2.5) and those consuming greater than 2900 Kcal/day having a lower odds of being sedentary (OR 0.6 95%CI:0.4–0.9). Discussion Our results highlight the primarily sedentary nature of this adult urban population, with 70% of women and 60% of men not undertaking any regular physical activity or sports during leisure time. Similar studies, which have only evaluated leisure time physical activity, have identified comparable levels of sedentarism, as well as associations between sedentarism and certain population factors. In a European Union study [ 22 ] conducted in 1997, it was reported that the Portuguese population was one of the most sedentary among the 15 countries studied, with 85.2% of men and 90.0% of women being classified as sedentary compared to 83.7% of men and 84.4% of women in this study. It would be expected that, since the sampling in the study was meant to be representative of the whole country, a greater difference in the overall levels of sedentarism would be found mainly due to the differences in the levels and types of activities undertaken by rural and city dwellers. The small sample number in the European study (1007 participants) may also not capture the full extent of activities undertaken by the population in general. Similar associations were also noted for leisure-time energy expenditure, where the prevalence of sedentarism was higher with age and higher in the less educated in the European and in a Swiss [ 23 ] study. Other associations found in the European study, that obese individuals had higher prevalence of sedentarism was only found to be true in women in our study and no association was found between sedentarism and current smoking as identified in the European study. Lower levels of physical activity have also been associated with those who were female, older and with lower socio-economic status in a New Zealand study [ 10 ]. The differences between other studies results and ours may be due to true differences between the study sample baseline characteristics, or possible due to the study methods utilised. The questionnaire, which was used to collect data on physical activity, was developed according to the European Prospective Investigation into Cancer and Nutrition study questionnaire, which showed acceptable repeatability and validity [ 24 ]. Formal validation of the questionnaire was undertaken using four seven days records (data not published). Participant recall may limit accurate capturing, through the questionnaire, of time and intensity spent undertaking various activities [ 25 ] during an average day or week in the last year. Although a variation in the hours of activities reported in a day was found, the percentage of participants reporting over 24 hours of activity was small (2.2%) and would not substantially affect the results of the study. As well, the description of types of activities provided in the questionnaire allow for METs to be estimated based on the Compendium of physical activity[ 20 ]. Variation is also present between studies in the categorisation of metabolic equivalents for activities with moderate intensity, with the US Surgeon General reporting moderate intensity exercise as being equal to 3–5 times the basal metabolic rate [ 26 ], while other studies use a cut off for moderate activity being more than 4, [ 2 , 21 , 22 ] or even greater than 5 METs [ 8 ]. Thirty minutes of activity at 4 METs, in an adult with 75 kg, will lead to an approximate energy expenditure of 150 Kcal per day or 1050 Kcal per week, which is a minimum level of moderate intensity daily activity recommended in the US Surgeon General report [ 26 ]. As energy expenditure varies from person to person, previous studies [ 21 , 22 ] have measured energy expenditure and have defined someone as being sedentary if they expend less than 10% of their daily energy in the performance of moderate-intensity activities (at least 4 times the basal metabolism rate) and therefore, on average, expend less than the recommended150 Kcal per day. The above mentioned studies only recorded and based results on leisure-time energy expenditure, excluding the potential input of physical activity that is undertaken at work or on household tasks. As presented in the results of this study, the inclusion of work-time energy expenditure shows that those less educated and those with manual occupations are less sedentary, which reverses the association seen in the leisure-time only estimation. The differences between the associations of the two separate measurements, leisure-time energy expenditure versus full-day energy expenditure, therefore demonstrate the potential for work-related and household-related physical activity to significantly affect the proportion of sedentarism, and the associations between sedentarism and the factors studied. Efforts, therefore, need to be made to include all components of daily physical activity and energy expenditure and to study the effects of this energy expenditure as a whole, on cardiovascular disease and other health benefits of moderate and high-intensity energy expenditure, which has also been highlighted by Salmon et al [ 27 ]. However, the different psychosocial aspects expectedly associated with the decision of engaging in leisure time physical activity or related to hard work as part of occupational tasks might result in different effects on health for the same amount of energy expenditure. The European Society of Cardiology has outlined, in a recent position paper, the need for physical activity to be prescribed in primary and secondary prevention and to implement successful strategies to reduce cardiovascular risks [ 28 ]. It has been observed for centuries that physical activity maintains and improves health and well-being, however health-systems have done little to promote and support appropriate levels of physical activity, especially in groups with elevated cardiovascular risk [ 29 ]. The lack of knowledge of the determinants of, and health problems related to, sedentarism and of the best interventions for behavioural change and long-term adherence to physical activity may play a part in low prescription of physical activity. Interventions to decrease sedentarism through primary health care [ 11 ] and in workplace settings [ 30 ] have had positive results, however all interventions may not affect change, such as was found with a population-wide print-media intervention [ 31 ]. Lessons can be learned from these interventions, and appropriate public health interventions prepared, in order to reduce the high levels of sedentarism, which acts as a main factor in high cardiovascular risk. Conclusions The urban Portuguese population has a very high prevalence of reported sedentarism potentially contributing to the high levels of cardiovascular disease in the country. Caution, however needs to be taken in the classification of individuals as sedentary when considering leisure-time versus full-day energy expenditure, as work and household-related activities can account for a large portion of the energy spent. Including these measures may also affect the overall associations found between sedentarism and the population characteristics. Abbreviations BMI Body Mass Index MET Metabolic Equivalent RMR Resting Metabolic Rate WHO World Health Organisation Competing interests The author(s) declare that they have no competing interests. Authors' contributions DG designed the study, performed the statistical analysis and drafted the manuscript. ACS participated in the design of the study and in the interpretation of the results. HB conceived the study, and participated in its design and coordination. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC550648.xml |
544952 | Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus | Background Previous results with the planar robot MIT-MANUS demonstrated positive benefits in trials with over 250 stroke patients. Consistent with motor learning, the positive effects did not generalize to other muscle groups or limb segments. Therefore we are designing a new class of robots to exercise other muscle groups or limb segments. This paper presents basic engineering aspects of a novel robotic module that extends our approach to anti-gravity movements out of the horizontal plane and a pilot study with 10 outpatients. Patients were trained during the initial six-weeks with the planar module (i.e., performance-based training limited to horizontal movements with gravity compensation). This training was followed by six-weeks of robotic therapy that focused on performing vertical arm movements against gravity. The 12-week protocol includes three one-hour robot therapy sessions per week (total 36 robot treatment sessions). Results Pilot study demonstrated that the protocol was safe and well tolerated with no patient presenting any adverse effect. Consistent with our past experience with persons with chronic strokes, there was a statistically significant reduction in tone measurement from admission to discharge of performance-based planar robot therapy and we have not observed increases in muscle tone or spasticity during the anti-gravity training protocol. Pilot results showed also a reduction in shoulder-elbow impairment following planar horizontal training. Furthermore, it suggested an additional reduction in shoulder-elbow impairment following the anti-gravity training. Conclusion Our clinical experiments have focused on a fundamental question of whether task specific robotic training influences brain recovery. To date several studies demonstrate that in mature and damaged nervous systems, nurture indeed has an effect on nature. The improved recovery is most pronounced in the trained limb segments. We have now embarked on experiments that test whether we can continue to influence recovery, long after the acute insult, with a novel class of spatial robotic devices. This pilot results support the pursuit of further clinical trials to test efficacy and the pursuit of optimal therapy following brain injury. | Background Rather than using robotics as an assistive technology for a disabled individual, our research focus is on the development and application of robotics as a therapy aid, and in particular a tool for therapists. We foresee robots and computers as supporting and enhancing the productivity of clinicians in their efforts to facilitate a disabled individual's functional motor recovery. To that end, we deployed our first robot, MIT-MANUS (see figure 1 ), at the Burke Rehabilitation Hospital, White Plains, NY in 1994 [ 1 ]. In the last ten years, MIT-MANUS class robots have been in daily operation delivering therapy to over 250 stroke patients. Hospitals presently operating one or more MIT-MANUS class robots include Burke (NY), Spaulding (MA), Rhode Island (RI), Osaka Prefectural (Japan) and Helen Hayes (NY) Rehabilitation Hospitals, and the Baltimore (MD) and Cleveland (OH) Veterans Administration Medical Centers. Figure 1 Stroke Inpatient during Therapy at the Burke Rehabilitation Hospital (White Plains, NY). Therapy is being conducted with a commercial version of MIT-MANUS (Interactive Motion Technologies, Inc., Cambridge, MA). Most of the work to date has focused on the fundamental question of whether task specific training affects motor outcome and positively influences brain recovery. These efforts directly confront the overwhelming task of reversing the effects of natural injury where lesion size, type and location profoundly determine outcome, and applying controlled conditions in environment and training – nurture – to exploit the ability of the mature nervous system to learn, adapt and change. Through our work with MIT-MANUS, providing task specific training for patients' with moderate to severe hemiparesis, we have gathered convincing evidence (summarized below) that nurture has a significant impact in speeding motor recovery of the paretic shoulder and elbow, and that robot therapy is effective in delivering the necessary exercise. This recovery is most pronounced in the trained muscle groups and limb segments. Encouraged by these positive results, we have expanded our project to develop a family of novel, modular robots, designed to be used independently or together to rehabilitate other muscle groups and limb segments. This paper describes two different implementations of a new module developed at MIT that expands the capabilities of MIT-MANUS to include motion in a three-dimensional workspace. We will present both implementations, the basic engineering differences between these modules, and pilot clinical results from their use with stroke patients. Proof-of-Concept Volpe [ 2 ] reported the composite results of robotic training with 96 consecutive stroke inpatients admitted to Burke who met inclusion criteria and consented to participate [ 3 - 7 , 2 ]. Patients were randomly assigned to either an experimental or control group and although the patient groups were comparable on all initial clinical evaluation measures, the robot-trained group demonstrated significantly greater motor improvement (higher mean interval change ± standard error measurement) than the control group on the Motor Status and Motor Power scores for shoulder and elbow (see Table 1 ). In fact, the robot-trained group improved twice as much as the control group in these measures. These gains were specific to motions of the shoulder and elbow, the focus of the robot training. There were no significant between-group differences in the mean change scores for wrist and hand function. Similar results were gathered in patients who have had a paralyzed upper extremity after stroke for at least one year [ 8 - 10 ] (See Table 1 ). Table 1 Mean interval change in impairment and disability (significance p < 0.05). Between Group Comparisons: Final Evaluation Minus Initial Evaluation Robot Trained (N = 55) Control (N = 41) P-Value Impairment Measures (±sem) Motor Power (MP) 4.1 ± 0.4 2.2 ± 0.3 <0.01 Motor Status shoulder/elbow (MS-se) 8.6 ± 0.8 3.8 ± 0.5 <0.01 Motor Status Wrist/Hand (MS/wh) 4.1 ± 1.1 2.6 ± 0.8 NS Description of Robots Modularity and Integration Potential MIT's experience with well over 250 stroke patients has reinforced the importance of one of our core design specifications: Modularity . From the outset we believed that modularity is essential to success in robotic therapy, particularly in extending the approach to patients suffering from distinct afflictions. Consider, for example, patients undergoing surgery at the wrist (e.g., Colles Fracture) who might not require a device that manipulates the payload of all the degrees-of-freedom (DOF) of the arm. Therapy for these patients requires only the wrist robot [ 11 - 13 ]. Conversely there will be patients for whom different modules must be coupled to deliver therapy and carry the payload of the human arm. Presently MIT has deployed four modules into the clinic (Burke Rehabilitation): a planar 2-dof active module; vertical 1-dof active module; wrist 3-dof active module; and 1-dof passive grasp module. Features common to all modules All of our robot modules are specifically designed and built for clinical rehabilitation applications. Unlike most industrial robots, they are configured for safe, stable, and compliant operation in close physical contact with humans. This is achieved using backdrivable hardware and impedance control, a key feature of the robot control system. Each active module can move, guide or perturb movements of a patient's limb and can record motions and mechanical quantities such as the position, velocity, and forces applied. The most profound engineering challenge specific to this family of robots is achieving the dual goals of high force production capability and backdrivability. Each module must be capable of generating sufficient force to move a patient's limb, but it must also itself be easily movable by an elderly or frail patient. Backdrivability is essential in keeping the patient engaged in the task and in allowing him to observe his successful and unsuccessful attempts at motion. Backdrivable hardware also improves the performance of systems controlled by impedance controllers. Achieving backdrivability and high force production, together in a single machine, is often difficult and becomes more so when the robot geometry is more complex. The robot control system is an impedance controller that modulates the way the robot reacts to mechanical perturbation from a patient or clinician and ensures a gentle compliant behavior. Impedance control refers to using a control system (actuators, sensors and computer) to impose a desired behavior at a specified port of interaction with a robot, in this case the attachment of the robot to the patient's hand. Conceived in the early 1980's by one of the co-authors [ 14 ], it has been applied successfully in numerous robot applications that involve human-motor interaction. Impedance control has been extensively adopted by other robotics researchers concerned with human-machine interaction. In rehabilitation robotics impedance control has been successfully implemented in MIT-MANUS since its clinical debut in 1994. For robots interacting with the human, the most important feature of the controller is that its stability is extremely robust to the uncertainties due to physical contact [ 14 , 15 ]. The stability of most robot controllers is vulnerable when contacting objects with unknown dynamics. In contrast, dynamic interaction with highly variable and poorly characterized objects (to wit, neurologically impaired patients) will not de-stabilize the impedance controller above; even inadvertent contact with points other than the robot end-effector will not de-stabilize the controller. This is essential for safe operation in a clinical context. Planar 2-dof robot MIT-MANUS The MIT-MANUS project was initiated in 1989 with support from the National Science Foundation. MIT-MANUS has been in daily operation since 1994 delivering therapy to stroke patients at the Burke Rehabilitation Hospital. This robot has been extensively described in the literature [ 4 ] (See Figure 1 ). MIT-MANUS is a planar module which provides two translational degrees-of-freedom for elbow and forearm motion. The 2-dof module is portable (390 N) and consists of a direct-drive five bar-linkage SCARA (Selective Compliance Assembly Robot Arm). This configuration was selected because of its unique characteristics of low impedance on the horizontal plane and almost infinite impedance on the vertical axis. These allow a direct-drive backdrivable robot to easily carry the weight of the patient's arm. The mechanism is driven by brushless motors rated to 9.65 Nm of continuous stall torque with 16-bit virtual absolute encoders for position and velocity measurements (higher torques can be produced for limited periods of time). Redundant velocity sensing may be provided by DC-tachometers with a sensitivity of 1.8 V/rad/sec. A six degrees-of-freedom force sensor is mounted on the robot end-effector. The robot control architecture is implemented in a standard personal computer with 16-bit A/D and D/A I/O cards, as well as a DIO card with 32 digital lines. Besides its primary control function, this computer displays the task to both the operator and the subject or patient via dedicated monitors. Custom-made hand holders connect a patient's upper limb to the robot end-effector. The selected design created a highly backdrivable robot capable of delivering therapy in a workspace of 15" by 18" with an end-point anisotropy of 2:1 ratio (2/3 < I < 4/3 Kg; 56.7 < static friction < 113.4 grams) and achievable impedances between 0 and 8 N/mm. Note that the static friction is significantly below the just noticeable difference (JNF) for force, which is 7% of the reference force. The robot maximum achievable impedance is above the human perception of 4.2 N/mm for a "virtual wall." The robot is capable of delivering forces up to 45 N although the robot target design aimed at a force of 28 N, which corresponds to the arm strength during elbow extension for a weak woman in seated position [ 16 ]. Vertical 1-dof Novel Robot Following the successful clinical trials of MIT-MANUS, a 1-dof module to provide vertical motion and force was conceived and built. The primary goal of this module is to bring the benefits of planar therapy on MIT-MANUS to spatial arm movements, including movement against gravity. The module can be used independently or mounted to MIT-MANUS for movement in a limited spatial workspace. The module can permit free motion of the patient's arm, or can provide partial or full assistance or resistance as the patient moves against gravity. Because the vertical module moves with the endpoint of the planar module when the two are integrated, overall module mass is an important design concern in addition to on-axis mass and friction. Two embodiments are described below. Screw-driven module One prototype of the 1-dof module was completed at MIT late 2000 and is shown alongside a test stand in Figure 2 . A second clone was completed at MIT and deployed in the clinic (Burke Rehabilitation Hospital), where it is presently collecting pilot data with stroke patients. The module incorporates a custom-made "rollnut" and a custom-made screw with a linear guide system. Significant effort was engaged in the design of the screw transmission, which provides an efficient conversion of rotary to linear motion designed to eliminate nearly all-sliding friction in favor of rolling contact. Its low friction provides an intrinsically back-drivable design. The bracket mounted to the rollnut allows the attachment of different interfaces. Incorporated into the design are therapists' suggestions that functional reaching movements often occur in a range of motion close to shoulder scaption. Thus, the robotic therapy games that use the spatial robot focus on movements within the 45° to 65° range of shoulder abduction and from 30° to 90° of shoulder elevation or flexion. A Gripmate is used to hold the patient's hand in place. Figure 2 Constant-Velocity Friction Experiments (0.5 to 50 mm/sec). Photo shows alpha-prototype. The mean friction force was 20.075 ± 1.056 N. This prototype has been fully characterized at MIT [ 17 , 18 ] (Figures 4 and 5 ). In comparison to MIT-MANUS, the vertical module has a greater effective endpoint mass and friction, though the resulting system is still back-drivable. In order to partially compensate for this increased impedance, force-feedback is incorporated into the impedance controller, resulting in a substantial reduction in friction, down to approximately 3 N, and mass, to approximately 1 kg. This improvement is illustrated in Figure 3 . The module is capable of providing well over the force specification of 65 N in the upward direction (20 N estimate of patient's arm weigh) and 45 N in the downward direction, and can achieve stiffness in excess of 10 N/mm, far greater than the values generally used for therapy. Figure 4 Graduates from Planar Robot Protocol Receiving Additional Vertical Anti-Gravity Training at the Burke Rehabilitation Hospital (White Plains, NY). The robot is sufficiently backdrivable to be lifted with the tip of the little finger. Figure 5 Graduates from Planar Robot Protocol Receiving Additional Vertical Anti-Gravity Training at the Burke Rehabilitation Hospital (White Plains, NY). The robot is sufficiently backdrivable to be lifted with the tip of the little finger. Figure 3 The graph shows force versus position with spring behavior commanded (heavy dot). PD controller alone (solid), PD controller with force feedback, K f = 5 (dashed). Qualitatively, the roughly 3 N of friction force is almost imperceptible. Linear direct-drive module The screw-driven prototype has proven very successful both in standalone operation and mounted at the end of the planar module enabling spatial movement therapy in the clinic with compliant and stable behavior. However recent changes in linear motor technology have created the potential to achieve similar outcomes with effective vertical endpoint inertia comparable to the planar MIT-MANUS and much lower friction, without the need for force feedback control. The main change is complete enclosure of the magnets within the motor forcer. While this does not increase the magnetic field strength, it dramatically increases the line integral and concatenates magnetic lines. The practical advantages of converting the spatial system to direct-drive linear motors would be a significant reduction of friction and elimination of backlash. This simplification would also carry through to the control system and controller, as well as affording a reduction in the system's overall dimensions and weight. To determine if the expected friction levels are realistic, we tested Copley Control ThrustTube TB2504. Figures 6 , 7 , 8 shows our experimental results characterizing the static friction for the TB series and the force vs current relationship. Figures 9 and 10 shows the commercial implementation of the novel module (Interactive Motion Technologies, Inc., Cambridge, MA). The novel module allows 19.4" of linear range of motion and it is capable of moving the desired target maximum endpoint force of 65 N upward and 45 N downward. This new module achieves significant reductions in friction and inertia to 25% and 76% of the lead-screw prototype. Figure 6 Characterization of TB2504. Plot shows the force versus current curve. Figure 7 Characterization of TB2504. Plot shows the static friction and cogging. Figure 8 Characterization of TB2504. Figure 9 Vertical 1-dof Module Using Electrical Linear Technology. This commercial version of MIT's module can be operated in standalone fashion or integrated to the planar MIT-MANUS to allow spatial movements. Note that in the standalone fashion it can be operated at any angle to the horizontal and vertical planes with adjustable handle positions. Figure 10 Vertical 1-dof Module Using Electrical Linear Technology. This commercial version of MIT's module can be operated in standalone fashion or integrated to the planar MIT-MANUS to allow spatial movements. Note that in the standalone fashion it can be operated at any angle to the horizontal and vertical planes with adjustable handle positions. Pilot Clinical Trials with the Anti-gravity Module To test the novel vertical module we conducted a pilot study to analyze whether additional anti-gravity training further improves motor outcomes for "graduates" of the planar robot-assisted protocol. In-/Exclusion Criteria Outpatients were included in the study if they met the following criteria: a) first single focal unilateral lesion with diagnosis verified by brain imaging (MRI or CT scans) that occurred at least 6 months prior; b) cognitive function sufficient to understand the experiments and follow instructions (Mini-Mental Status Score of 22 and higher or interview for aphasic subjects); c) Motor Power score ≥1/5 or ≤3/5 (neither hemiplegic nor fully recovered motor function in the 14 muscles of the shoulder and elbow); d) informed written consent to participate in the study. Patients were excluded from the study if they have a fixed contracture deformity in the affected limb that limited pain-free range of motion. We have found severe tendon contractures around the rotator cuff particularly, in patients with complete hemiplegia for longer than 6 months after stroke. It is reasonable to expect that robotic training for the upper limb would not have an impact on a fixed contracture deformity. Trials commenced only after baseline assessment across three consecutive evaluations, 2 weeks apart, shows a stable condition in three motor impairment scales (F-M, MSS, MP). Our rationale for administering multiple baseline evaluations is based on an interesting "Hawthorne effect" that we observed in previous subjects [ 19 , 20 ]. Between first and second pre-treatment evaluations, some subjects have shown a remarkable improvement in clinical impairment scores. We speculate that the anticipated participation in a research study may contribute to a significant change in life routines. Demographics Ten (10) community dwelling volunteers who have suffered a single stroke at least 6 months prior to enrollment were enrolled in the pilot protocol. The mean group age was 62 ± 4.3 years old (mean ± sem) with the onset of the stroke occurring 50 ± 8.9 months (mean ± sem) prior to enrollment. Table 2 summarizes admission status of volunteers (See Table 2 ). Table 2 Data on the Ten (10) Community Dwelling Stroke Volunteers Age Handed Lesion foci Lesion side Months stroke Fugl-Meyer adm (/66) 59 Left AVM hem. Left 16.5 11 53 Ambi Intracerebral bleed Left 88.5 18 44 Right Carotid dissection Left 36 11 63 Right Cerebral embolism, subcortical Left 58 9 82 Right Cerebral embolism, subcortical Left 69 9 72 Right Carotid endarectomy Right 24 24 41 Right cortical/subcortical and basal ganglia stroke Right 96 17 72 Right cortical/subcortical stroke Right 47.5 9 57 Right Cerebral embolism, subcortical Right 48 30 77 Right cerebral embolism, mixed Right 16 34 Description of Protocol Patients were trained during the initial six-weeks with the planar module (i.e., training limited to horizontal movements with gravity compensation as in past studies). This training was followed by six-weeks of robotic therapy that focused on performing vertical arm movements against gravity. The 12-week protocol includes three one-hour robot therapy sessions per week (total 36 robot treatment sessions) (Figure 9 ). Figure 11 Movement Component Training. The circular display in front of the subject represents the workspace of the planar 6-weeks trial. The component training added 6 additional weeks training movements over two vertical lines. For shoulder-and-elbow planar therapy, the center of the workspace was located in front of the subject at the body midline with the shoulder elevation at 30° with the elbow slighted flexed. The point-to-point movements started at the workspace center and extended in eight different directions of the compass (Figure 11 ). A one-hour session included two batches of 20 repetitions of point-to-point movements. The protocol incorporated a novel performance-based adaptive algorithm [ 21 ], which encouraged subjects to initiate movement with their hemiparetic arm. Just as in the planar study [ 10 ], the anti-gravity robotic protocols consisted of visually evoked and visually guided point-to-point movements to different targets (along two vertical lines) with some robotic therapy games providing assistance and others visual feedback only. The protocol incorporated therapists' suggestions: a) robot therapy should focus on encouraging subjects to initiate movement against gravity with their hemiparetic arm beginning in a position of slight shoulder flexion (elevation) and scaption; b) functional reaching movements often occur in a range of motion close to shoulder scaption; c) no support should be provided at the elbow; and d) the visual display should be kept simple, since more complex displays proved to be difficult for our historical pool of stroke survivors to follow. Thus the robotic therapy protocols with the spatial robot focused on movements within the 45° to 65° range of shoulder abduction and between 30° to 90° of shoulder elevation or flexion. This sector is considered "safe" for the shoulder joint because it prevents gleno-humeral impingement that may occur when attempting to elevate the paretic limb to higher levels of shoulder elevation; The one-hour session included three batches of 20 repetitions of point-to-point movements. The first batch only provided visual feedback to a repetitive sequence of targets, while the second and third batches assisted the subject if needed to reach the target. Clinical Assessment Scales In this pilot, standard clinical evaluations included the upper extremity sub-test of the Fugl-Meyer Assessment (FM, maximum score = 66) from which we derived a Fugl-Meyer score for shoulder/elbow coordination (FM-SE, 42 out of 66); a more comprehensive evaluation of motor power or strength in 14 different muscle groups of the shoulder and elbow, using the MRC Motor Power score (MP, out of 70); and the Motor Status Score which is divided into two subscales, one for shoulder and elbow movements (MS-SE, maximum score = 40), and a second for wrist and hand abilities (MS-WH, maximum score = 42) [ 22 , 3 , 24 , 6 , 7 ]. The Modified Ashworth Scale (Bohannon, 1987) provides a measure of tone. The Fugl-Meyer test is a widely accepted measure of impairment in sensorimotor and functional grasp abilities [ 24 ]. To complement the Fugl-Meyer, we developed the Motor Status to further quantify discrete and functional movements in the upper limb. The MS-SE and MS-WH scales expand the F-M and have met the standards for inter rater reliability, significant intra-class correlation coefficients and internal item consistency [ 23 , 25 ]. Results We have completed the study with ten (10) outpatients. Nine (9) outpatients who completed the planar training protocol at the Burke Rehabilitation Hospital were enrolled for an additional six-weeks with training three sessions per week on the vertical module. One (1) naïve outpatient completed only the six-week training on the vertical module (no previous exposure to the planar training). Table 3 and 4 shows the results for the shoulder-and-elbow subcomponent of the upper extremity Fugl-Meyer scale, the Motor Status Score, Motor Power, and Modified Ashworth scale. Table 3 Anti-Gravity Vertical Module Pilot Study. Results from nine (9) outpatients that continued for an additional 6 weeks of training in the vertical module robotic unit. Statistical tests showed that outcomes at discharge from planar robot protocol were distinct from admission (B vs. A), and there was a trend favoring further improvement when comparing discharge from anti-gravity protocol with discharge from the planar protocol (C vs. B). Our protocol was safe and did not increase tone. Timeline N = 9 A – Admission B – Discharge from planar robot protocol C – Discharge from anti-gravity protocol F-M s/e (/42) 12.7 ± 1.6 14.8 ± 2.0 (p = 0.03, S) 17.0 ± 1.9 (p = 0.19, NS) MSS s/e (/40) 18.1 ± 1.9 19.9 ± 2.0 (p = 0.01, S) 21.5 ± 1.8 (p = 0.29, NS) MP 26.5 ± 3.5 33.3 ± 3.6 (p < 0.01, S) 38.8 ± 2.4 (p = 0.07, NS) Ashworth 8.0 ± 1.4 4.9 ± 0.99 (p < 0.03, S) 4.4 ± 1.01 (p = 0.67, NS) Table 4 Anti-Gravity Vertical Module Pilot Study. Results from one naive (1) outpatient that trained for 6 weeks in the vertical module robotic unit (no prior robot exposure). Timeline N = 1 B – Admission to anti-gravity protocol C – Discharge from anti-gravity protocol F-M s/e (/42) 24.0 27.0 MSS s/e (/40) 21.8 31.0 MP 35.0 43.0 Ashworth 4 1 Results of this pilot suggested that the vertical protocol was safe and well tolerated by the patients with no patient presenting any adverse effect (e.g., shoulder pain). Furthermore, pilot results suggested an additional reduction in shoulder-elbow impairment following the anti-gravity vertical training. In fact, for these 9 patients the reduction in impairment during the vertical training phase was comparable to the reduction during the planar phase (5.2% for the vertical training vs 5.0% for the planar training of the shoulder-elbow subcomponent of the Fugl-Meyer scale – albeit without achieving statistical significance). As mentioned earlier, we reliably incorporated therapists' feedback during the design phase of the protocol and have not observed increases in muscle tone or spasticity, as indicated by the Modified Ashworth scale, during the anti-gravity training protocol (actually the trend in 8 out of 9 patients is towards a decrease in tone). Note also that consistent with our past experience with the persons with chronic strokes, there was a statistically significant reduction in tone measurement from admission to discharge of performance-based planar robot therapy. While the benefits from the additional anti-gravity therapy did not achieve statistical significance, this is likely due to the small sample size (9 outpatients). We anticipate that a modest increase of sample size will demonstrate statistical improvement for the shoulder and elbow of the anti-gravity training across the three clinical scales and we plan to commence trials shortly (See Table 3 and Table 4 ). Conclusions Our clinical experiments have focused on a fundamental question of whether task specific robotic training influences brain recovery. To date several studies demonstrate that in mature and damaged nervous systems, nurture indeed has an effect on nature. The improved recovery is most pronounced in the trained limb segments (i.e. shoulder and elbow). We have now embarked on experiments that will test whether we can continue to influence recovery, long after the acute insult, with a novel class of robotic devices. It is broadly accepted that outcome measures do not significantly change in persons with chronic motor impairments more than six months from stroke onset. However, recent task specific training programs have resulted in improved motor performance in persons with chronic stroke. For example, our trials with persons with chronic stroke-related impairments showed that planar robotic training contributed to statistically significant improvements in motor abilities [ 8 - 10 ]. If so, further robot training of stroke survivors who were enrolled in the planar robot trials might result in additional performance improvements when a distinct training protocol is provided. Our pilot results and novel robotic modules provide a proof of concept that supports our engineering efforts, as well as further clinical trials to test efficacy. We found that the protocol was safe and well tolerated by the patients with no patient presenting any adverse effect (e.g., shoulder pain). Furthermore, the pilot results suggested an additional reduction in shoulder-elbow impairment following the anti-gravity vertical training without detrimental changes in muscle tone or spasticity. Therefore we plan to investigate in detail the effect of training each movement component in isolation versus integrated spatial movement, and study its impact on disability. We expect that this will bring us closer to our ultimate goal, efficient delivery of optimal therapy, personalized to serve the individual's needs. | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC544952.xml |
518977 | Survey of attitudes, materials and methods employed in endodontic treatment by general dental practitioners in North Jordan | Background General dental practitioners provide the majority of endodontic treatment in Jordan. The aim of this study was to gather information on the methods, materials and attitudes employed in root canal treatment by dentists in North Jordan, in order to evaluate and improve the quality of current practice. Methods A questionnaire was posted to all registered general dental practitioners working in private practice in Irbid Governate in North Jordan (n = 181). The questionnaire included information on methods, materials and techniques used in endodontic treatment. Results Reply rate was 72% (n = 131). The results demonstrated that only five dentists used rubber dam occasionally and not routinely. The majority used cotton rolls for isolation solely or in combination with a high volume saliva ejector (n = 116). The most widely used irrigants were sodium hypochlorite and hydrogen peroxide, which were used by 32.9% (n = 43) and 33.6% (n = 44) of the respondents, respectively. Forty eight percent of the respondents (n = 61) used the cold lateral condensation technique for canal obturation, 31.3% (n = 41) used single cone, 9.9% (n = 13) used vertical condensation and 12.2% (n = 16) used paste or cement only for the obturation. The majority used zinc oxide eugenol as a sealer (72.5%). All, but one, respondents used hand instruments for canal preparation and the technique of choice was step back (52.7%). More than 50% (n = 70) of the dentists took one radiograph for determining the working length, whilst 22.9% (n = 30) did not take any radiograph at all. Most practitioners performed treatment in three visits for teeth with two or more root canals, and in two visits for teeth with a single root canal. Conclusions This study indicates that dentists practicing in North Jordan do not comply with international quality standards and do not use recently introduced techniques. Many clinicians never take a radiograph for determining the working length and never used rubber dam or intra-canal medicaments. | Background Root canal treatment is considered an essential element in the dental services provided to the population in developed countries. Various investigations were, therefore, carried out to explore the standard of root canal treatment carried out by general dental practitioners in Europe [ 1 - 3 ]. It is the responsibility of the academics and dental schools to prepare their students to adopt the guidelines and recommended standards in root canal debridement, shaping and obturation [ 4 , 5 ]. Several studies have revealed that the majority of dentists do not comply with the formulated guidelines on the quality of root canal treatment [ 1 - 3 , 6 ]. These studies investigated the attitude of dentists in Western countries such as Germany [ 1 ], UK [ 2 ], Belgium [ 3 ] and the USA [ 6 ]. On the other hand, few studies have investigated the attitude of general dental practitioners toward various aspects of endodontic treatment in developing countries [ 7 - 9 ]. The majority of endodontic treatment in Jordan is provided by the general dental practitioners due to absence of specialists in endodontics and to the lack of postgraduate programs in Jordan. The purpose of the current study was, therefore, to investigate the attitude of dentists toward endodontic treatment and to explore the materials and methods employed by general dental practitioners in North Jordan and to compare these findings with well-acknowledged international academic standards. Methods A postal survey of general dental practitioners in Jordan was carried out to investigate common materials and methods employed in root canal treatment. A questionnaire was developed and piloted by sending it to 20 general dental practitioners. According to the replies, the questionnaire was modified. Few questions were added and others were reworded. Additionally, the questionnaire was provided in Arabic and English language. The finally modified questionnaire was posted to all registered general dental practitioners (n = 181) listed in the records of the Jordanian Dental Association and working in private practices in Irbid Governate in North Jordan, 'Questionnaire [see Additional file 1 ]'. The questionnaire consisted of 28 questions concerning different aspects of endodontic treatment including the provision of molar endodontics, root canal therapy stages, materials, the choice of instruments, the use of rubber dam and isolation methods, number of appointments, number of radiographs taken throughout the treatment, the use of canal irrigants, the use of intracanal medicaments, the choice of obturation technique, temporary and permanent coronal restoration, and case monitoring and follow-up. There was a space made available in the questionnaire for free comments of respondents. The questionnaire was accompanied by an explanatory covering letter. To investigate the influence of the years of practical experience on the materials and techniques employed, the sample was divided into groups based on the years of professional experience: group 1, up to 5 years; group 2, 6–10 years; group 3, 11–15 years; group 4, 16–20 years, and group 5, more than 20 years. The collected data were entered into a personal computer and analyzed using the statistical package SPSS. Simple descriptive statistics were used together with Chi-square (χ 2 ) test. The chosen level of significance was set at P < 0.05. Unanswered questions were treated as missing values. Results Of the 181 questionnaires distributed, 131 completed replies were received, which is a 72% response rate. The high response rate ensured that this study was representative for the general dental practitioners in North Jordan. All the respondents performed endodontic treatment including molar teeth. However, none of the dentists reported that they would refer patients for a specialised endodontist opinion except cases, which were difficult or did not respond to initial treatment provided. The distribution of the repondents according to the years of professional experience is shown in Table 1 . Years in practice were not evenly distributed amongst the total respondents. The number of the first two groups (0–5 and 6–10) consisted of more than half the total respondents due to the significant increase in the number of graduates in the last 10 years. Seventy four percent of the respondents were males, 26% were females. These findings are consistent with the statistics obtained from the Jordanian Dental Association. In the current study, no statistically significant differences were found between the different periods of professional experience and any of the materials, instruments or techniques employed ( P > 0.05). Table 1 Data related to professional experience of the respondents. Years of Professional experience Frequency Percentage % 0–5 43 32.8 6–10 28 21.4 11–15 26 19.8 16–20 20 15.3 >20 14 10.7 Table 2 shows the hand instruments used for preparation of the root canal. K-files were the most popular instruments. Root canal preparation was performed using K-files solely (30.5%) or in combination with other instruments (93.1%). Only one practitioner reported using engine-driven instruments (Profile, Dentsply Maillefer, ballaigues, Switzerland). Table 2 The choice of root-canal preparation techniques and instruments Root canal preparation techniques Root canal instrument Technique Frequency % Instrument Frequency % Filing (push-pull) 36 27.5 File 40 30.5 Step back 69 52.7 Reamer 3 0.2 Step down 26 19.8 Hedström file 6 4.6 File + hedström file 30 22.9 File + reamer 20 15.3 File, reamer + hedström file 32 24.4 The majority of dentists instrumented the canal using the step back technique. The next most popular preparation technique was the filing (push-pull) technique followed by the step down technique (Table 2 ). The vast majority used gutta-percha points as their priniciple root filling material (87.8%), whilst 12.2% reported using only paste or cement to obturate the canal. Cold lateral compaction was the most common obturation technique (Table 3 ). The majority of dentists reported the use of a zinc oxide based sealer with the gutta-percha points (72.5%) followed by a calcium hydroxide based sealer, Sealapex (13.7%) (Table 3 ). Few dentists (n = 8) used the sealer Endomethasone as a paste root canal filling. Table 3 The choice of obturation technique and type of sealer. Root canal obturation techniques Type of sealer Technique Frequency % Type of material Frequency % Single cone 41 31.3 Zinc oxide-eugenol 95 72.5 Lateral condensation 61 46.6 Sealapex 18 13.7 Vertical condensation 13 9.9 Endomethason 10 7.6 Cement only 16 12.2 Other 8 6.2 Intracanal medication was used by 63% of the respondents. The most common material used was tricresol formalin followed by calcium hydroxide. Other formulations were also used (Table 4 ). Table 4 The frequency and percentages of intracanal medications used. Type of product Frequency Percentage % Calcium hydroxide 15 11.5 Formaldehyde 6 4.6 Tricresol formaline 45 34.4 Dexamethasone 1 0.8 Iodophorm 5 3.8 CMCP * 2 1.5 Other 8 6.1 None 49 37 * Camphorated monochlorophenol Sodium hypochlorite and hydrogen peroxide solutions were used equally as an irrigating solutions. The most popular concentration of sodium hypochlorite was 3% which was used by 14.5% (n = 19) of the repondents, with only 2.3% (n = 3) using a 0.5% concentration. The most commonly used concentration of hydrogen peroxide was 3%, which was used by 21.4% (n = 28) of the respondents. The remainder used either normal saline or local anesthetic solutions (Table 5 ). Table 5 Data related to the choice of root-canal irrigants. Root-canal irrigants used Concentration of NaOCl used Concentration of H 2 O 2 used Type Frequency % Concentration (%) Frequency % Concentration (%) Frequency % Sodium hypochlorite 43 32.8 0.5 3 2.3 1 2 1.5 Normal saline 32 24.4 1 3 2.3 2 2 1.5 Hydrogen peroxide 44 33.6 2 8 6.1 3 28 21.4 Local anesthetic solution 2 1.5 3 19 14.5 4 2 1.5 None 10 7.6 5 3 2.3 6 10 7.6 6 5 3.8 Do not use H 2 O 2 87 66.4 Do not use NaOCl 88 67.2 None of the dentists reported using rubber dam routinely to isolate the field of operation during root canal therapy. However, only five dentists reported using rubber dam occasionally but not as a routine practice. The majority of the general dental practitioners used cotton rolls solely (n = 68) or cotton rolls in combination with a high volume saliva ejector (n = 116) to reduce contamination with saliva (Figure 1 ). Figure 1 The number of dentists using different isolation methods. The number of visits required to complete root canal treatment related to the number of root canals in a tooth is shown in Figure 2 . It demonstrates that general dental practitioners complete root canal treatment in more than two visits for teeth with two or more root canals. However, half the respondents (49.7%) reported completing root canal treatment for teeth with single root canal in two visits. Figure 2 The number of visits according to the number of root canals per tooth. Twenty seven percent of the practitioners took 3 radiographs for routine root canal treatment. 22.9% took only 2 radiographs. However, 23% reported taking only one preoperative radiograph with 4% taking only one radiograph for determining the working length. The remaining 22.9% of respondents undertook root canal treatment without taking any radiograph. Only 14.5% of the respondents reported monitoring the root treated tooth radiographically after a period of 6 months. However, many of them mentioned that they would take a follow-up radiograph only if patients could afford to pay for it. The remainder indicated that they do not monitor their patients mostly for financial reasons and that patients would not return for follow-up appointment unless they have postoperative symptoms. Zinc oxide eugenol cement was the most commonly placed temporary filling (92%). All dentists reported using amalgam for posterior teeth and composite for anterior teeth as a permanent coronal restorative material. All practitioners completed the restorations themselves. Sixty four percent of the respondents preferred to wait from 1 to 2 weeks after obturation before placing the permanent coronal filling, whilst the remainder placed the restoration immediately after completion of the treatment. Discussion The response rate was 72%. It was higher than in many previous surveys conducted in Western countries with better communication infrastructure [ 2 , 7 , 10 , 11 ]. The vast majority of the respondents did not practice single visit root canal treatment. This finding was in agreement with the results of a previous study undertaken in another developing country, Sudan [ 9 ]. However, a study from the US [ 12 ] demonstrated a clear inclination to single visit endodontics, especially in cases without apical periodontitis. Single visit treatment appears to have gained more popularity and an increased credibility in the pre-clinical endodontic teaching in America and Europe [ 4 ]. Another survey [ 3 ], showed that a high percentage of Flemish dentists performed single visit root canal treatment. Multiple visit endodontic treatment could be a direct result of lacking adequate clinical time to complete the treatment in a single visit. The dentists may prefer to wait till the complete subsidence of pain and other symptoms before obturating the canal system. Another possible explanation could be that the initial visit was spent for treating the pain and acute symptoms [ 3 ]. Although the application of rubber dam is always recommended as a standard during root canal treatment procedure to provide isolation, protection and improve visual access, only five dentists reported using rubber dam very occasionally and not as a routine practice. Similar findings were found in Sudan (2%) and among Flemish dentists (3.4%) [ 6 , 8 ]. However, 59% of American dentists [ 6 ], 60% of dentists in UK [ 13 ] and 57% of general dental practitioners in New Zealand [ 14 ] reported using rubber dam routinely in endodontic treatment. The reasons for not using rubber dam could be the extra cost, additional time, lack of adequate skills or training, absence of patient's acceptability or inadequate education in the undergraduate teaching curriculum. It was found that continuing education course attendees seem to be encouraged to use rubber dam [ 14 ]. In the current survey, most general dental practitioners used hydrogen peroxide and sodium hypochlorite solutions as canal irrigants. The same result was demonstrated amongst dentists in Switzerland [ 11 ]. Sodium hypochlorite is recommended as the material of choice for irrigating the root canal system because of its effective antimicrobial and tissue solving action [ 15 ]. The selection of irrigant could be associated with the use of rubber dam, as it was found that 70% of rubber dam users among British dentists irrigated with sodium hypochlorite, whilst non-users tended to use local anesthetic solution [ 13 ]. The current findings do not mirror these findings. The vast majority of our respondents were non-users of rubber dam and one third of them use sodium hypochlorite routinely. A similar trend toward using sodium hypochlorite as an irrigant despite not using rubber dam for isolation, was noticed amongst Flemish dentists [ 16 ]. In the UK, the majority of dentists used local anesthetic solution to irrigate the canal space [ 2 ]. The use of either sodium hypochlorite or hydrogen peroxide without isolating the field of operation tightly with a rubber dam presents an obviously hazardous practice in the use of potentially irritant irrigation solutions. Despite the fact that calcium hydroxide is recognized as the standard intracanal medicament for inter-appointment dressing [ 17 ], it was used by only 11.5% of the respondents. More than one third of the general practitioners reported using formaldehyde-containing materials. This finding is consistent with previous findings recorded for Sudanese dentists [ 9 ]. Although formaldehyde-containing products have been used for their antimicrobial and fixative properties, they are toxic to periradicular tissues [ 18 ] and may have mutagenic and carcinogenic potential [ 19 ]. The use of calcium hydroxide, as intracanal medication, should be encouraged among dentists in developing countries such as Jordan, as it is effective against most root canal pathogens and able to denature bacterial endotoxins [ 20 , 21 ]. It has, also, been reported to be the material of choice by dentists in the Western world [ 11 , 22 ]. The step back technique was the most popular canal preparation technique among North Jordanian general dental practitioners. The filing (push-pull) technique, on the other hand, was used by 27.5% of the respondents. In another study, 60.4% of Flemish dentists used the standard filing technique [ 16 ]. Generally, dentists in Jordan tended to use hand instruments and were not inclined to use more advanced engine driven techniques for shaping the root canal system. Almost half of the general dental practioners in North Jordan used cold lateral compaction of gutta-percha to obturate the root canal space. This technique is acknowledged universally and is the most common obturation technique [ 4 ]. However, 31.3% of the dentists in the current survey used a single cone technique, in common with 68% of Swiss dentists [ 11 ]. Additionally, 12.2% of respondents used only paste to obturate the root canal system. Seemingly, dentists in North Jordan are not strong advocates of the more recently introduced advanced obturation techniques. This may be attributed to additional cost involved or the lack of skill and training. Conclusions This study investigated the status of endodontic practice among general dental practitioners working in private offices in North Jordan. It demonstrated that dentists performed procedures which often deviated from well-acknowledged endodontic quality guidelines. Dentists did not use rubber dam for isolation and frequently use formaldehyde-containing materials for inter-appointments dressing. In addition, a significant proportion of dentists (n = 30) did not use radiographs at any stage of endodontic treatment. General practitioners did not seem to keep up with recently introduced techniques, but use more conventional methods. The North Jordanian general dental practitioners carried out endodontic treatment with few referals to specialists. However, the absence of postgraduate endodontic programs and continuing education courses in addition to economic restrictions could explain why dentists in Jordan do not carry out endodontic treatment in accordance with recognized international standards. Competing Interests None declared. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Endodontic Survey Questionnaire text of the file contains questions related to endodontic practice among general dental practitioners. 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368173 | Extensive Association of Functionally and Cytotopically Related mRNAs with Puf Family RNA-Binding Proteins in Yeast | Genes encoding RNA-binding proteins are diverse and abundant in eukaryotic genomes. Although some have been shown to have roles in post-transcriptional regulation of the expression of specific genes, few of these proteins have been studied systematically. We have used an affinity tag to isolate each of the five members of the Puf family of RNA-binding proteins in Saccharomyces cerevisiae and DNA microarrays to comprehensively identify the associated mRNAs. Distinct groups of 40–220 different mRNAs with striking common themes in the functions and subcellular localization of the proteins they encode are associated with each of the five Puf proteins: Puf3p binds nearly exclusively to cytoplasmic mRNAs that encode mitochondrial proteins; Puf1p and Puf2p interact preferentially with mRNAs encoding membrane-associated proteins; Puf4p preferentially binds mRNAs encoding nucleolar ribosomal RNA-processing factors; and Puf5p is associated with mRNAs encoding chromatin modifiers and components of the spindle pole body. We identified distinct sequence motifs in the 3′-untranslated regions of the mRNAs bound by Puf3p, Puf4p, and Puf5p. Three-hybrid assays confirmed the role of these motifs in specific RNA–protein interactions in vivo. The results suggest that combinatorial tagging of transcripts by specific RNA-binding proteins may be a general mechanism for coordinated control of the localization, translation, and decay of mRNAs and thus an integral part of the global gene expression program. | Introduction The dynamic structure and physiology of a cell depend on coordinated synthesis, assembly, and localization of its macromolecular components ( Orphanides and Reinberg 2002 ). The timing and level of expression of the genes that encode these components are controlled by transcription factors that regulate initiation of transcription in a gene-specific manner by binding to specific DNA sequences proximal to the genes they regulate. The combinatorial binding and activity of specific transcription factors confer a distinctive program of regulation on each individual gene while enabling coherent global responses of large sets of genes in physiological and developmental programs. Much less is known about either the system architecture or molecular mechanisms that underlie regulation of the post-transcriptional steps in the gene expression program. There are approximately 15,000 mRNA molecules in each Saccharomyces cerevisiae cell during exponential growth in rich medium ( Hereford and Rosbash 1977 ) and at least a 10-fold larger number in a typical mammalian cell ( Hastie and Bishop 1976 ). The extent to which the location, activity, and fates of these diverse populations of mRNAs are coordinated and the post-transcriptional mechanisms that might mediate their coordinated regulation remain largely unknown. RNA-binding proteins (RBPs) have been implicated in diverse aspects of post-transcriptional gene regulation, including RNA processing, export, localization, degradation, and translational control ( Dreyfuss et al. 2002 ; Maniatis and Reed 2002 ; Mazumder et al. 2003 ). Although there appear to be hundreds of RBPs encoded in eukaryotic genomes ( Costanzo et al. 2001 ; Issel-Tarver et al. 2002 ), for only a few of these proteins have the RNA targets been systematically identified ( Takizawa et al. 2000 ; Tenenbaum et al. 2000 ; Brown et al. 2001 ; Hieronymus and Silver 2003 ; Li et al. 2003 ; Shepard et al. 2003 ; Waggoner and Liebhaber 2003 ). For example, a recent study in S. cerevisiae found that two nuclear RNA export factors were each associated with large and distinct mRNA populations, and common functional themes were found among the 1,000 or so proteins encoded by each population ( Hieronymus and Silver 2003 ). These observations support a role for RBPs in the coordinated regulation of mRNA subpopulations ( Keene and Tenenbaum 2002 ; Keene 2003 ). Systematic identification of the mRNA targets of RBPs can be a powerful approach to understanding the cellular roles of RBPs and the mechanisms by which they might regulate the post-transcriptional lives of mRNAs. We have focused first on the Pumilio–Fem-3-binding factor (FBF) (Puf) proteins from S. cerevisiae , which belong to a structurally related family of cytoplasmic RBPs that are implicated in developmental processes in various eukaryotes ( Wickens et al. 2002 ). Puf proteins are defined by the presence of several (typically eight) consecutive repeats of the Pumilio homology domain (Pum-HD), which confers RNA binding activity ( Zamore et al. 1997 ; Wang et al. 2002a ). The Puf proteins characterized to date have been reported to bind to 3′-untranslated region (UTR) sequences encompassing a so-called UGUR tetranucleotide motif and thereby to repress gene expression by affecting mRNA translation or stability. Despite the widespread occurrence of Puf family members, only a few mRNA targets have been identified for these RBPs ( Wickens et al. 2002 ). For example, in Drosophila , the PUMILIO protein binds maternal hunchback mRNA and, in concert with NANOS protein, represses translation of the mRNA at the posterior pole during early embryogenesis. The Caenorhabditis elegans Puf homologs, called Fem-3-binding factors (FBFs), regulate the switch from spermatogenesis to oogenesis by repressing fem-3 translation, and they are implicated in the propagation of germline stem cells through binding and inhibition of gld-1 mRNA expression ( Zhang et al. 1997 ; Crittenden et al. 2002 ). Less is known about the human homologs: PUMILIO-2 protein interacts with DAZ (deleted in azoospermia) protein and is expressed in embryonic stem cells and germ cells, whereas PUMILIO-1 is almost ubiquitously expressed ( Moore et al. 2003 ). In S. cerevisiae , five proteins, termed Puf1p to Puf5p, bear six to eight Puf repeats ( Figure 1 ). Little is known about the physiological function of these proteins. Mutations in either PUF4 or PUF5 result in diminished longevity ( Kennedy et al. 1997 ). PUF1 was isolated as a multicopy suppressor of certain microtubule mutants ( Machin et al. 1995 ), and a PUF2 null mutant displayed increased resistance to cycloheximide and paromomycin ( Waskiewicz-Staniorowska et al. 1998 ). However, S. cerevisiae mutants lacking all five PUF genes are viable ( Olivas and Parker 2000 ). A genome-wide analysis of mRNA expression patterns in yeast mutants lacking all five PUF genes found differential expression of 7%–8% of all mRNAs under steady-state conditions, but no common theme was found among the affected genes ( Olivas and Parker 2000 ). Only two specific mRNA targets have been identified for yeast Puf proteins: Puf3p binds to the COX17 mRNA 3′-UTR in vitro and may regulate its turnover ( Olivas and Parker 2000 ), and Puf5p negatively regulates expression of reporter genes substituting for the HO endonuclease ( Tadauchi et al. 2001 ). Figure 1 Protein Domain Structure of Yeast Puf Proteins Pum-HD repeats ( Zamore et al. 1997 ) are shown as red ovals and classical RNA-binding domains (RBDs) are depicted as blue boxes. Regions of low complexity, such as proline-, serine-, threonine-, and/or methionine-rich domains, are shown in gray boxes; asparagine stretches are striped. The numbers correspond to the length of proteins in amino acids. Using DNA microarrays to identify the specific mRNAs that interact with the five S. cerevisiae Puf proteins, we have found that each Puf protein bound to a large set of distinct and functionally related mRNAs. We identified novel and conserved sequence elements in the mRNAs bound by Puf3p, Puf4p, and Puf5p. The results suggest a system for large-scale coordinated control of cytoplasmic mRNAs and provide insights into the physiological logic of the gene expression program. Results Systematic Identification of mRNAs Associated with Specific RBPs To identify RNAs associated with Puf proteins, tandem-affinity purification (TAP)-tagged proteins were purified from whole-cell extracts of S. cerevisiae ( Figure 2 ). The TAP tag ( Rigaut et al. 1999 ), a sequence encoding two IgG-binding units of protein A, a specific protease recognition site, and a calmodulin-binding domain, was fused in-frame at the C-terminus of the respective open reading frame (ORF) in its original chromosomal location ( Ghaemmaghami et al. 2003 ). This design was intended to preserve normal regulation of the expression of the fusion protein. Cells of the TAP-tagged strains showed growth rates and cell morphologies similar to wild-type cells. Cells were grown to mid-log phase in rich medium, extracts were prepared, and ribonucleoprotein complexes were recovered by affinity selection on IgG beads and subsequent cleavage with tobacco etch virus (TEV) protease (see Materials and Methods ). To control for nonspecifically enriched mRNAs, the same procedure was performed with wild-type cells lacking the TAP tag. TEV protease cleavage was superior to direct elution of proteins from beads, as it gave lower contamination from nonspecifically interacting RNAs in the resulting purified fractions (data not shown). RNA was isolated from the purified protein samples and from extracts. We obtained 0.8–2 μg of RNA from the Puf affinity-isolated samples gathered from 1-l cultures, but no detectable RNA (<0.1 μg) was recovered when the same procedure was applied to untagged control cells. The yield of RNA from the Puf affinity isolation procedure was sufficient to perform further labeling steps directly, without amplification of RNA by PCR, as had been required in previous studies ( Takizawa et al. 2000 ; Hieronymus and Silver 2003 ). Two samples from each cell population, total RNA, and RNA isolated by the Puf affinity procedure were used to prepare cDNA probes labeled with different fluorescent dyes, which were mixed and hybridized to S. cerevisiae DNA microarrays containing all known and putative ORFs, introns, and the mitochondrial genome (see Materials and Methods ). The ratio of the fluorescent hybridization signals from the two differentially labeled RNA samples, at the array element representing each specific gene, provided an assay for enrichment of the corresponding mRNA by the Puf-affinity procedure. Figure 2 Strategy for Analyzing Genome-Wide RNA–Protein Interactions Protein A-tagged Puf proteins were captured with IgG–Sepharose and released from the beads by cleavage with TEV protease. RNAs associated with the released proteins were isolated, and cDNA copies were fluorescently labeled and hybridized to yeast DNA microarrays. The Cy5/Cy3 fluorescence ratio for each locus reflects its enrichment by affinity for the cognate protein. Puf3p is the only one of the five S. cerevisiae Puf proteins for which direct in vitro interaction with an mRNA ( COX17 ) has previously been described, thereby providing an internal positive control ( Olivas and Parker 2000 ). COX17 mRNA was substantially and consistently enriched in four independent Puf3p affinity isolations (ratio = 10 ± 1.4; Figure 3 A), but not in mock isolations (ratio = 0.8 ± 1.2). In general, after filtering for spots with high background or irregular shapes, enrichment values for the entire set of arrayed sequences were reproducible (median of standard deviations in all arrayed spots = 0.35 on a log 2 scale) (see Materials and Methods ). To define targets specific to each Puf protein, we first selected all sequences for which enrichment factors in the corresponding affinity isolation procedures were at least two standard deviations above the mean for all arrayed sequences ( Figure S1 ; for samples isolated by the Puf3p-affinity procedure, this corresponded to an enrichment factor of greater than or equal to 2.5). Second, we eliminated from this selected group any sequences that were also consistently enriched in the mock procedure (see Materials and Methods ). Although no cutoff can perfectly distinguish the actual physiological targets from false positives, the high reproducibility of the results (see Figure 3 B), the occurrence of distinct mRNA populations associated with the different Puf proteins, and the characterization of these targets described in the subsequent sections, including the identification of distinct sequence motifs and in vivo confirmation of the role of these motifs in specific RNA–protein interactions, strongly support the validity of the majority of the targets. Finally, the list of target mRNAs did not change substantially by application of other statistical methods for selection (see Lieb et al. 2001 ). Figure 3 Defining Puf Target RNAs (A) Distribution of average Cy5/Cy3 fluorescence ratios from four independent microarray hybridizations analyzing Puf3p targets. The arrow depicts enrichment of COX17 mRNA, which is known to bind to Puf3p ( Olivas and Parker 2000 ). The red dashed line indicates the threshold applied for defining 220 target RNAs (a magnification is shown of the enriched region). (B) Cluster of RNA targets for Puf proteins. Rows represent genes (unique cDNA elements) and columns represent individual experimental samples. Each Puf protein and an untagged strain (mock control) were assayed in quadruplicate. The color code indicates enrichments (green–red color scale). The number of mRNAs interacting with each Puf protein is indicated in parentheses. mRNAs clustering with the mock controls were removed as false positives (see Materials and Methods ). A large number of arrayed sequences, 818, identified transcripts associated with at least one Puf protein (see Figure 3 B; Table S1 ), with 735 encoding distinct ORFs. This represents approximately 12% of the known and predicted protein-coding sequences in the S. cerevisiae genome. Of these, 90 transcripts interact with more than one Puf protein. The largest overlap was observed between the groups of transcripts associated with Puf1p and Puf2p—which also have the greatest overall similarity in amino acid sequence among the Puf proteins (45% identical); 36 of the 40 Puf1p targets were also associated with Puf2p. Twenty-eight mRNAs were bound by both Puf4p and Puf5p, and 16 were bound both by Puf2p and Puf5p. Seven transcripts were enriched with three different Puf proteins ( DHH1 and YOL109w mRNAs with Puf1p, Puf2p, and Puf5p; NOP1 mRNA with Puf1p, Puf4p, and Puf5p; SUR7 and SFL1 mRNAs with Puf2p, Puf4p, and Puf5p; and IFM1 mRNA with Puf3p, Puf4p, and Puf5p). The remaining 645 target mRNAs were each associated with only one of the Puf proteins. Thus, each Puf protein associates with a distinct and highly specific subset of mRNAs (see Tables S3–S7 ). We estimated the number of Puf proteins per cell by a filter affinity blot analysis using protein A as a standard for calibration ( Table S2 ). We found that Puf1p, Puf2p, Puf3p, and Puf5p were similar in abundance, with 350–400 molecules per cell. Puf4p was approximately twice as abundant (approximately 900 molecules per cell). The relatively low abundance of the Puf proteins is therefore comparable to that of transcription factors, protein kinases, and cell cycle proteins ( Futcher et al. 1999 ). Moreover, our measurements imply that the intracellular concentrations of the Puf proteins range between 20 and 50 nM, approximately one order of magnitude higher than the dissociation constants for binding of their metazoan homologs to the cognate target RNAs. The number of Puf proteins per cell approximates the estimated numbers of cognate Puf target mRNA molecules present in the cell ( Holstege et al. 1998 ; Wang et al. 2002b ) ( Table S2 ), consistent with a model in which each Puf protein molecule is associated with one mRNA molecule in the cell. Puf3p Specifically Binds mRNAs Encoding Mitochondrial Proteins As a first step toward identifying functional themes among the mRNAs associated with each Puf protein, we retrieved the Gene Ontology (GO) annotations for process, function, and compartment from the Saccharomyces Genome Database (SGD) ( Issel-Tarver et al. 2002 ). (The target mRNAs for each Puf protein are listed in Tables S3–S7 .) We then searched for significant shared GO terms in the lists of Puf mRNA targets ( Table S8 ). Puf3p associated almost exclusively with transcripts of nuclear genes that encode mitochondrial proteins ( p < 10 −88 ; see Table S5 ). In particular, of the 154 Puf3p-associated transcripts for which GO annotation of subcellular localization was available, 135 (87%) were assigned to mitochondria ( Figure 4 A). Of the Puf3p-associated mitochondrial gene products, 80 (59%) are involved in protein biosynthesis, including structural components of the ribosome (55 genes), tRNA ligases (12 genes), and translational regulators (nine genes). Twenty-two of the Puf3p-bound transcripts are involved in mitochondrial organization and biogenesis, 17 in aerobic respiration, and 12 in mitochondrial translocation. Based on this striking cytotopic (relating to location in the cell) concordance, we suggest that the remaining 66 Puf3p mRNA substrates (30%) for which no GO annotations were available are likely to encode mitochondrial proteins. (While this paper was under review, a genome-wide analysis of protein localization in S. cerevisiae [ Huh et al. 2003 ] reported a mitochondrial localization for 27 additional Puf3p targets, raising the total to 162 of the 220 putative Puf3p mRNA targets encoding mitochondrial proteins.) Figure 4 Classification of mRNAs Interacting with Puf Proteins (A) Column charts showing compartmentalization of characterized gene products encoded by the Puf targets. The same compartments are shown for the entire genome in the columns designed “All” (YPD, May 2003). The number of genes represented in the charts is indicated on the top of columns. An asterisk indicates classes with p values of less than 0.001. (B) Fraction of membrane-associated gene products among the Puf targets. We classified the targets by combining both GO and YPD annotations (May 2003). “Plasma membrane” (light blue) is a subpopulation of the total membrane-associated proteins (blue). Soluble cytoplasmic or nuclear proteins were classified as “non-membrane.” “All” refers to the genome-wide compartmentalization of characterized genes, and respective numbers were retrieved from YPD. “Puf2 Top 40” refers to the 40 highest enriched Puf2p targets and equals the total number of Puf1p targets. Puf1p- and Puf2p-Associated mRNAs Disproportionately Encode Membrane-Associated Proteins Of all the characterized S. cerevisiae genes for which any information about subcellular localization is available, 18% are currently classified as encoding membrane-associated proteins (Yeast Proteome Database [YPD], May 2003; see Costanzo et al. 2001 ). A much greater fraction of the mRNAs associated with Puf1p and Puf2p encode membrane-associated proteins: 16 of the 28 (57%) known proteins encoded by Puf1p-interacting mRNAs and 55 of 106 (52%) known proteins encoded by Puf2p-interacting mRNAs (see Figure 3 B; see Tables S3 and S4 ). Transcripts encoding proteins associated with the plasma membrane were particularly enriched among the Puf1p- and Puf2p-bound mRNAs. Most of the mRNAs bound by Puf1p were also associated with Puf2p. However, Puf2p bound uniquely to many additional mRNAs (146 Puf2p mRNA targets versus 40 for Puf1p). In terms of cellular processes, many Puf1p- and Puf2p-associated transcripts encode proteins with roles in transmembrane transport and vesicular trafficking of proteins: 9 out of 26 (34%; p < 0.0002) of annotated Puf1p targets and 24 out of 104 (23%; p < 10 −5 ) annotated Puf2p targets (compared to 9% of all characterized genes) (YPD, May 2003). This group includes transporters for spermine (Tpo1, Tpo2, Tpo3), proteins (Nce101, Nce102, Ast1, Vps72, Mas6, Sfk1, Mup3), vesicles (Sso2, Snc2, Yip1, Aps3, Ypr157w), and lipids (Pdr16, Ykl091c, Fps1 [glycerol]). (Tpo2 and Tpo3 may cross-hybridize on arrays because of their high sequence identity [89%], but Tpo1 does not [ Shepard et al. 2003 ]). Puf4p and Puf5p Interact Selectively with mRNAs Encoding Nuclear Components Among the Puf5p targets (see Table S6 ), we found two common themes. First, a remarkable fraction encodes nuclear proteins that participate in covalent modification of histones, chromatin-remodeling complexes, or transcriptional regulation (64 of the 113 annotated genes [57%; p < 3 × 10 −6 ]). Second, the Puf5p-associated transcripts included a substantial fraction of the mRNAs known to encode components or regulators of the mitotic spindle apparatus in yeast: 14 mRNAs that encode microtubule-based spindle components, including seven of the 25 (28%; p < 4 × 10 −5 ) structural components of the spindle pole body (Kar1, Ccd31, Spc19, Spc42, Bbp1, Cnm67, and Nuf2) ( Wigge et al. 1998 ). Messages encoding nuclear and cytoplasmic proteins that regulate polarized growth (Ame1, Boi2, Bsp1, Bub1, Bud9, Dad2, Elm1, Gic1, Kar9, Rax2, Ste7), some of them known to interact with spindle components, were also Puf5p targets. Transcripts encoding nucleolar proteins were highly enriched among the Puf4p-bound mRNAs: 36 of the 133 (27%) annotated genes in this group encode nucleolar proteins, as compared to 3% of all the annotated genes in the S. cerevisiae genome ( p < 10 −12 ). Of these 36, 29 are directly involved in ribosomal RNA (rRNA) synthesis, processing, and ribosome maturation ( p < 10 −15 ), major functions of the nucleolus ( Fatica and Tollervey 2002 ; Gerbi et al. 2003 ) (see Tables S5 and S8 ). Twenty-eight transcripts were enriched in both the Puf4p and Puf5p affinity isolations, including six transcripts encoding components of the nucleosome ( p < 10 −11 ), among them the four core histone proteins (histones 2A and 2B, histone 3, and histone 4; note that histones 2A and 2B are 98% identical and therefore cross-hybridize). Diverse Functional Links among Transcripts Associated with Each Puf Protein In addition to the cytotopic relationships within each group of Puf-associated mRNAs, we were struck by the frequency with which transcripts encoding different components of protein complexes or systems of interacting proteins were bound by the Puf proteins. For example, most of the nuclear transcripts encoding components of the mitochondrial ribosome (55 out of the 77 known genes; Gan et al. 2002 ) were Puf3p-associated. This observation prompted us to search for other protein complexes and functional systems that shared similarly Puf-associated mRNAs. Other examples of coordinate “tagging” of transcripts encoding subunits of multiprotein complexes include Puf4p association of mRNAs encoding three of the four protein components of the H/ACA core particle (Cbf5p, Gar1p, and Nhp2p), which synthesizes pseudouridine in rRNAs ( Henras et al. 1998 ) ( Figure S2 ; no data were obtained for the fourth component, Nop10p). Puf5p bound mRNAs encoding histone acetylases (Ada2p, Spt8p, and Hfi1p), which are components of the Spt–Ada–Gcn5–acetyltransferase (SAGA) complex, and transcripts encoding at least four of the six members of the RSC (remodels the structure of chromatin) family of DNA-stimulated ATPases with bromodomains (Bdf1p, Bdf2p, Rsc2p, and Rsc4p; no array data were obtained for the two other members, Rsc1p and Spt7p). As mentioned above, the mRNAs encoding at least three of the four core histones were enriched in both Puf4p and Puf5p affinity isolations. We also found numerous cases in which the transcripts encoding multiple members of a functional group of proteins were bound by the same Puf protein. For example, the transcripts encoding the Tpo1, Tpo2, and Tpo3 proteins, the three known spermine transporters in the plasma membrane ( Albertsen et al. 2003 ; see note above about cross-hybridization), and the two known genes implicated in the nonclassical protein export pathway ( NCE101 , NCE102 ) ( Cleves et al. 1996 ) were bound by Puf1p and Puf2p and by Puf2p, respectively. Puf5p was associated with all of the histone deacetylases (HDACs) that act on histones located around coding sequences—Sin3p (a class I HDAC), Hda1p (a class II HDAC), and both components of the Set3C complex (Hst1p and Snt1p) ( Kurdistani and Grunstein 2003 ). (Two other HDACs, Hos1p and Hos3p, which deacetylate histones around the ribosomal DNA locus, were not enriched in Puf5p affinity isolations.) Finally, we identified cases in which the mRNAs encoding multiple components of a specific regulatory system were bound by the same Puf protein. For example, Puf2p associates with mRNAs encoding diverse proteins regulating Pma1p, which is an ATP-dependent proton transporter located in the plasma membrane, and with PMA1 mRNA itself ( Figure S2 ). All of the mRNAs encoding nucleolar glycine/arginine-rich (GAR) domain-bearing proteins (Sbp1p, Nsr1p, Nop1p, Gar1p) as well as HMT1 mRNA, encoding a dimethylase that modifies the nucleolar GAR proteins ( Xu et al. 2003 ), were associated with Puf4p, while none of the mRNAs encoding the distinct group of nonnucleolar GAR proteins were bound by Puf4p ( Figure S2 ). Sequence Motifs in the 3′-UTR of mRNA Targets Direct Binding by Puf Proteins The Puf homologs in Drosophila and C. elegans bind to sequences in the 3′-UTR of mRNAs ( Wickens et al. 2002 ). We therefore examined the sets of mRNAs associated with each of the S. cerevisiae Puf proteins for the presence of common sequence motifs in 5′-UTRs and 3′-UTRs, using multiple expectation maximization for motif elicitation (MEME) as a motif discovery tool ( Bailey and Elkan 1994 ). We identified distinct 10- or 11-nucleotide sequence motifs in the 3′-UTR among the mRNAs interacting with Puf3p, Puf4p, and Puf5p ( Figure 5 A, Tables S9–S11 ). We have thus far been unable to identify conserved sequence elements among Puf1p and Puf2p targets; these proteins may recognize structural elements in the RNA rather than simple sequence strings, possibly via their classical RNA-binding domains instead of their six-repeat Pumillio domains. Figure 5 Sequence Motifs Interacting with Puf Proteins (A) Consensus motifs detected within 3′-UTR sequences of Puf3p, Puf4p, and Puf5p target mRNAs. Height of the letters specifies the probability of appearing at the position in the motif. Letters with less than 10% appearance were omitted. Fraction of genes bearing a motif in the 3′-UTR sequence is indicated to the right. Y-helicase proteins are nearly identical in sequence and were excluded from this analysis. (B) Scheme of three-hybrid assay for monitoring RNA–protein interactions in vivo ( Bernstein et al. 2002 ). (C) β-Galactosidase activity for three-hybrid assay. Proteins assayed are indicated on top, RNAs to the left. Abbreviations: pum, pum-HD; cons., consensus motif; UGU/AGA, UGU in consensus sequence mutated to AGA. (D) Activation of HIS3 reporter gene and resistance to 3-aminotriazole (3-AT), a competitive inhibitor of the HIS3 gene product, in a three-hybrid assay ( Bernstein et al. 2002 ). The conserved motifs we identified in the Puf3p, Puf4p, and Puf5p targets each include a UGUR tetranucleotide sequence, which is a feature of all previously reported RNA targets of Puf family proteins ( Wickens et al. 2002 ). Furthermore, in each case, the consensus sequence contains a conserved dinucleotide (UA), located two, three, or four nucleotides downstream of the UGUR motif, in the consensus sites for Puf3p, Puf4p, and Puf5p. Remarkably, the Puf3p consensus motif matches a sequence (CYUGUAAAUA) previously identified by computational tools in 3′-UTR sequences of nuclear genes coding for mitochondrial proteins ( Jacobs Anderson and Parker 2000 ). We examined the distribution of the consensus sequence motifs in the entire S. cerevisiae genome ( Table 1 ). Of the genes whose mRNAs were predicted by computational analysis to contain one of these three target sequences in their 3′-UTRs, 42% were identified experimentally as targets in the corresponding affinity isolation procedure ( Table 1 ). The consensus motifs were occasionally found in the coding sequence of an experimentally identified target gene, but were much rarer in the predicted 5′-UTR sequences ( Table 1 ). Moreover, only a few mRNAs had two copies of the motifs: five mRNAs among the Puf3p targets, six among the Puf4p targets, and one among the Puf5p targets (see Tables S5–S7 ). As our computational method did not detect the cognate consensus sequence elements in all the experimentally identified targets, alternative sequences or structural elements in RNAs might also allow specific interactions with Puf proteins, some mRNAs may be associated indirectly as part of larger complexes, and some of the putative mRNA targets identified by our affinity procedure are likely to be false positives. Table 1 Number of Consensus Motifs Found in the Genome and in Puf Targets a Known and putative ORFs (6,330 genes) from SGD b The probability that the motifs are enriched in Puf targets by chance c Average lengths of predicted UTR sequences (134 bp of 5′-UTR sequences, 237 bp of 3′-UTR sequences; Mignone et al. 2002 ). Syntax for multiple bases: H = A/C/T, W = A/T, Y = C/T To test the in vivo function of the putative recognition elements identified by the computational analysis, we assayed RNA–protein interactions in vivo using the yeast three-hybrid system ( Bernstein et al. 2002 ) (see Figure 5 B). Puf3p, Puf4p, and Puf5p bound specifically to a sequence matching to the cognate consensus sequence, as assayed by activation of the lacZ and HIS3 reporter genes (see Figure 5 C and 5 D). For Puf3p and Puf4p, the Pum-HD alone was sufficient to confer specific binding (see Figure 5 C and 5 D), but no interaction could be seen with the Puf5p Pum-HD alone (data not shown). These interactions were specific: mutations in the UGU of the Puf3p consensus sequence disrupted binding, and each Puf protein interacted with its cognate consensus sequence in preference to the closely related consensus sequences recognized by the other Puf proteins. We detected a weak interaction between Puf3p and the Puf4p target sequence, an interaction that was not seen with the Puf3p Pum-HD alone. These results suggest that binding of the Puf proteins to these specific cis -acting elements directs their functions to specific sets of mRNAs. Subcellular Distribution of Puf Proteins We investigated the localization of the TAP-tagged Puf proteins by immunofluorescence with antibodies against the TAP tag (see Materials and Methods ). All five Puf proteins were predominantly localized to multiple discrete foci in the cytoplasm ( Figure 6 ). The predominantly cytoplasmic localization is consistent with previous reports for S. cerevisiae Puf3p and Puf5p ( Tadauchi et al. 2001 ) and for the homologous proteins in higher eukaryotes ( Lehmann and Nüsslein-Volhard 1991 ; Zhang et al. 1997 ). The distribution of the foci of Puf proteins was not obviously related to distinct cellular organelles or structures, with the exception of Puf1p and Puf2p, which localized in foci enriched near the periphery of the cell. Because of the diffuse and pleiomorphic distribution of mitochondria in the cell, we cannot exclude the possibility that Puf3p, which specifically bound transcripts of proteins destined for the mitochondria, is associated with mitochondria. Figure 6 Localization of Puf Proteins TAP-tagged Puf proteins were visualized in fixed cells. DNA was costained with 4′,6-diamidino-2-phenylindole dimethylsulfoxide (DAPI). Altered Levels of Puf3p-Associated mRNAs in a puf3 Δ Mutant A previous study compared steady-state mRNAs levels of cells bearing deletions of all five Puf proteins and wild-type cells grown in rich media ( Olivas and Parker 2000 ). Only 12 of the 148 (8%) mRNAs whose abundance changed by more than 2-fold were selectively enriched in our affinity isolations with Puf proteins. The lack of a simple relationship between the mRNA binding specificity we observed and the reported effects of these multiple mutations on global gene expression prompted us to design a more specific experiment to search for a possible connection between specific mRNAs levels and binding to Puf proteins. We focused on Puf3p, as its strong association with mRNA-encoding mitochondrial proteins suggested that we should look for a regulatory function for this protein in mitochondrial physiology. Indeed, we found that puf3 Δ cells grew more slowly than isogenic puf3 + cells on minimal media plates with glycerol as the carbon source ( Figure S3 ). We therefore compared mRNA levels in the puf3 Δ and puf3 + cells grown under these conditions by DNA microarray hybridization. Although the magnitude of the change was small, the relative expression levels of the 220 Puf3p-associated mRNAs were selectively increased in puf3 Δ cells, compared to all other mRNAs analyzed ( p < 10 −34 ) ( Figure 7 ). Of the 16 mRNAs whose abundance was increased by more than 2-fold in the puf3 Δ mutant, 11 (70%) were among the transcripts identified as Puf3p targets by our co-purification experiments, and all encode mitochondrial proteins. This result could reflect a direct effect of Puf3p on its target mRNAs, for example, by promoting mRNA decay ( Olivas and Parker 2000 ). However, the levels of transcripts involved in respiration and mitochondrial function, including many that did not appear to be bound directly by Puf3p, were increased in the puf3 Δ mutant, suggesting the possibility that the elevated abundance of Puf3p target mRNAs could instead be an indirect response to impaired mitochondrial and respiratorial function in puf3 Δ cells. Figure 7 Gene Expression Profiling of puf3 Mutants Distribution of average Cy5/Cy3 fluorescence ratios from three independent microarray hybridizations comparing mRNA levels of puf3 Δ with wild-type cells grown in minimal media with glycerol. The left frequency axis refers to all genes (black line); the axis to the right refers to Puf3p and Puf4p (control) targets, shown as red and blue lines, respectively. Relative expression levels of the 220 Puf3p mRNA targets in puf3 Δ cells were selectively increased compared to all other mRNAs analyzed ( p < 10 −34 ), whereas Puf4p targets were not ( p > 0.05). Thirty-nine genes involved in aerobic respiration (according to GO annotation and SGD), but not bound by Puf3p, were similarly enriched ( p < 5 × 10 −5 ) in the puf3 mutant as random sets of 39 Puf3p targets ( p < 10 −6 ). Likewise, 220 randomly selected mRNAs coding for mitochondrial proteins that were not associated with Puf3p in the experiments herein were weakly enriched in the mutant ( p < 10 −8 ). Discussion In an analysis of just five of the hundreds of RBPs encoded by the S. cerevisiae genome, we found that more than 700 transcripts appeared to be specifically bound by one or more RBPs, with each of the five Puf family proteins “tagging” a distinct set of mRNAs. These sets encode functionally and cytotopically related proteins. For three of the Puf proteins, we identified distinct short sequences in the associated specific set of mRNAs, typically in the 3′-UTR, which were sufficient for specific binding to the cognate Puf protein in vivo. Many sets of mRNAs encoding proteins localized to the same subcellular compartment, protein complex, or functional system were bound by the same Puf protein. Puf3p, which specifically associated with cytoplasmic mRNAs encoding mitochondrial proteins, generally affected the steady-state levels of its mRNA targets as reflected by their increased abundance in puf3 mutant cells. The selective “tagging” by sequence-specific RBPs of mRNAs that share common physiological roles suggests a general and widespread mechanism for coordinated control of their expression. Previous reports have identified coordinated regulation of small sets of functionally related mRNAs by specific RBPs. For example, mammalian stem–loop binding protein (SLBP) associates with all five classes of histone mRNAs and guides proper 3′-end formation ( Dominski and Marzluff 1999 ). Iron regulatory proteins (IRPs) bind to and regulate translation of five different mRNAs encoding proteins involved in iron metabolism ( Eisenstein and Ross 2003 ), and a cytoplasmic poly(A) polymerase regulates multiple mRNAs in early development ( Mendez and Richter 2001 ). Based on these and other examples ( Tenenbaum et al. 2000 ), Keene and Tenenbaum (2002 ) have suggested that messenger RBPs could define “post-transcriptional operons.” Our results provide strong support for this general idea of coordination of gene expression via RBPs and suggest that the post-transcriptional control afforded by combinatorial binding of RBPs to mRNAs could allow greater regulatory flexibility than a simple operon (see also Keene and Tenenbaum 2002 ). Further, we suggest that RBPs may play important roles in subcellular localization and efficient assembly of protein complexes. The RBPs encoded in eukaryotic genomes rival specific transcription factors in their numbers and diversity, raising the intriguing possibility that specific regulation of the localization, translation, and survival of mRNAs might be comparable in their richness and complexity to regulation of transcription itself. Each of the five Puf proteins interacts with a distinct large set of mRNAs, comprising more than 700 different mRNAs in total. Five other RBPs in S. cerevisiae have been subjected to a similar genome-wide survey of their mRNA targets. She2p, which plays a critical role in selective targeting of specific mRNAs to the bud tip ( Shepard et al. 2003 ), Khd1p, which has also been implicated in localizing gene expression to the nascent bud (A. P. Gerber, unpublished data), and Scp160p, an RBP implicated in genome stability ( Li et al. 2003 ), were each found to bind from 20 to hundreds of distinct mRNAs, and two proteins implicated in RNA export from the nucleus, Yra1p and Mex67p, were each associated with more than 1,000 mRNAs ( Hieronymus and Silver 2003 ). Thus, just ten of the 567 S. cerevisiae proteins known or predicted from the genome sequence to have RNA binding activity ( Costanzo et al. 2001 ) have been found to bind, in a functionally specific pattern, a total of approximately 2,500 different transcripts (approximately 40% of the transcriptome). The extent and specificity of the RNA–protein interactions represented by the proteins studied to date, extrapolated to the hundreds of putative RBPs that remain to be investigated, suggest the existence of an extensive network of RNA–protein interactions that coordinate the post-transcriptional fate of large sets of cytotopically and functionally related RNAs through each stage of its “lifecycle.” It further suggests a potential regulatory repertoire comparable in its diversity and richness to that of the DNA-binding transcription factors ( Figure 8 ). Indeed, the combinatorial binding of mRNAs by multiple RBPs could, in principle, define a specific post-transcriptional fate for each individual mRNA (for an example, see Sonoda and Wharton 2001 ). Figure 8 Specific Proteins Bind Functional Groups of Genes for Regulation At the transcriptional level (top), transcription factors (TFs) regulate initiation of transcription (green arrow) in the nucleus by binding to sequence elements (yellow box) proximal to their target coding regions (boxes). At the post-transcriptional level (middle), RBPs regulate decay, translation, or localization of mRNAs in a coordinated fashion by interaction with sequence/structural elements in the RNA that are often found in 3′-UTR regions (red box). Functional relations at the protein level (bottom) can be reflected at both the transcriptional and post-transcriptional levels: sets of genes that encode functionally related proteins, such as subunits of stochiometric complexes (blue) or components of the same regulatory or metabolic pathway (gray and cross-hatched boxes), may be regulated by common transcription factors and their mRNAs post-transcriptionally coregulated by RBPs (dashed interactions). Many sets of mRNAs bound by the same Puf protein encode proteins that act in the same subcellular location, form stochiometric complexes, or are implicated in the same cellular pathway. This organization is most clearly exemplified by Puf3p, which selectively bound mRNAs encoding mitochondrial proteins, including at least 70% of all mitochondrial ribosomal proteins (see Figure 4 ). Combinations of RBPs could specify smaller sets of RNAs encoding more precisely defined functional groups of proteins. For example, the mRNAs encoding the core histone proteins were among the small set of mRNAs that were associated with both Puf4p and Puf5p. These results therefore hint that networks of functional and physical interactions among proteins could be reflected in a corresponding network of mRNA–protein interactions that coordinate post-transcriptional control of their expression and fate. For three of the Puf proteins, we found that RNA–protein interactions were directed by compact sequence elements, usually located in the 3′-UTR of the mRNA (see Figure 5 ). Interactions with 3′-UTR sequences have been described for many cytoplasmic RBPs involved in post-transcriptional regulation ( Mazumder et al. 2003 ). Our analysis has revealed that such recognition elements are probably much more widespread than previously recognized. Sequence and structural elements in mRNAs that are related to the function or cellular localization of the encoded proteins may be a general feature of eukaryotic genes, paralleling the role of the DNA sequences that direct specific transcription factors to promoters and enhancers ( Cliften et al. 2003 ). The multifocal cytoplasmic distribution of Puf proteins raises the possibility that the mRNAs associated with each Puf protein are colocalized (see Figure 6 ). In mammalian cells, specific mRNA molecules and specific messenger RBPs have also been found to be localized to specific “granular” subcytoplasmic loci, although the generality of this phenomenon has not been established ( Andersen and Kedersha 2002 ; Eystathioy et al. 2002 ; Farina et al. 2003 ). One function of the Puf proteins and related proteins that bind specific families of mRNAs could be to localize functionally related mRNAs to specific cytoplasmic loci. Physical clustering of functionally related groups of mRNAs could aid the assembly of complexes and the coordinated control of translation or RNA turnover. In support of this idea, it has recently been suggested that mRNA decay in the cytoplasm of S. cerevisiae occurs in distinct loci ( Sheth and Parker 2003 ) and, further, that mRNAs encoding different subunits of stoichiometric complexes do indeed have concordant decay rates ( Wang et al. 2002b ). We propose that the location in the cell at which any mRNA is translated or degraded is not left to chance. Instead, every mRNA that leaves the nucleus may be delivered, in a process directed by specific protein–RNA interactions, to one of a limited number of specific foci in the cytoplasm, designated as destinations for a specific functionally related family of mRNAs. These foci could serve to colocalize and coregulate synthesis of proteins that need to assemble or act together, thereby facilitating efficient and rapid assembly and localization of the proteins. The number of distinct families of functionally specialized foci may be quite large. The locations of these foci need not correspond to recognizable cellular features, but may simply be ad hoc sites for localized, coordinated translation of proteins that are to be assembled into a complex or a functional unit. Specific predictions of this hypothesis, such as colocalized translation of the subunits of stoichiometric complexes, should be amenable to direct experimental tests. Combinatorial binding of mRNAs by specific regulatory proteins, linking their post-transcriptional regulation to specific signal transduction pathways, could allow rapid and efficient reprogramming of gene expression during development or in response to changing physiological conditions. Indeed, regulation of specific genes by external signals via RPBs has been described in higher eukaryotes ( Lasko 2003 ). For example, the signal transduction and activation of RNA (STAR) proteins contain RNA-binding motifs combined with protein–protein interaction domains and phosphorylation sites, which could allow integration of stimuli conducted by signal transduction cascades ( Lasko 2003 ). Similarly, the Puf proteins contain numerous putative phosphorylation motifs, as well as domains with characteristics often implicated in protein–protein interactions, such as glutamine/arginine-rich regions ( Michelitsch and Weissman 2000 ) (see Figure 1 ). Coordination of cellular processes has long been thought to be mediated primarily at the transcriptional and post-translational level. Our results join a growing body of studies ( Tenenbaum et al. 2000 ; Eystathioy et al. 2002 ; Wang et al. 2002b ; Hieronymus and Silver 2003 ; Shepard et al. 2003 ; see also Keene and Tenenbaum 2002 ) that suggest that the localization, translation, and stability of mRNAs are subject to extensive and important regulation and coordination by interaction with a diverse set of RBPs. Systematic mapping of these interactions and deciphering their roles, molecular mechanisms, and coordination will undoubtedly yield important new insights into biological regulation and the gene expression program. Materials and Methods Oligonucleotide primers Restriction sites are in italics: Puf3-F1, 5′-cg ggatcc ATGGAAATGAACATGGATATGGATATGG-3′; Puf3-R1, 5′-g gaattc TCACACCTCCGCATTTTCAACCAATG-3′; Puf3-F6nco, 5′- cCATGg CACTAAAAGACATCTTTGG-3′; Puf4-F2nco, 5′- ccatgG CGGACGCAGTTTTAGACCAATA-3′; Puf4-R1eco, 5′- gaattc gTGAATCTAAATGTAACATTCCG-3′; Puf5-F2nco, 5′- ccATGG TCGAAATCAGCGCACTACC-3′; Puf5-R1xho, 5′- ctcgag cACTTGGAAGTAATTCTTTTGTA-3′; M16-1, 5′-GGG CTCGAG tagggaataccttgtaaatatcctatgaaaGCATG-3′; M16-2, 5′-Ctttcataggatatttacaaggtattcccta CTCGAG CCC-3′; M16-1mut, 5′-GGG CTCGAG tagggaatacctacaaaatatcctatgaaaGCATG-3′; M16-2mut, 5′-Ctttcataggatattttgtaggtattcccta CTCGAG CCC-3′; Caf-1, 5′-GGG CTCGAG tgggcacgattgtaataatacttcatgataaGCATG-3′; Caf-2, 5′-Cttatcatgaagtattattacaatcgtgccca CTCGAG CCC-3′; Yor-1, 5′-GGG CTCGAG gctttcatcatctgtataatatttatatgtcGCATG-3′; and Yor-2, 5′-Cgacatataaatattatacagatgatgaaagc CTCGAG CCC-3′. Strains and plasmid construction The TAP-tagged Puf3p strain (SC1249) was obtained from Cellzome (Heidelberg, Germany) ( Gavin et al. 2002 ). TAP-tagged Puf1p, Puf2p, Puf4p, and Puf5p strains were a gift from Dr. Erin O'Shea ( Ghaemmaghami et al. 2003 ). Correct genomic integration of each tag was verified by PCR and by immunoblot analysis of cell extracts (data not shown). Strain BY4741 was used for mock-control affinity isolations of RNA, and deletions of the PUF3 and PUF4 genes in this strain were obtained from Dr. Ron Davis ( Winzeler et al. 1999 ). The ORF of PUF3 was amplified by PCR with primers Puf3-F1 and Puf3-R1 from S. cerevisiae genomic DNA and cloned into pCR2.1 using the TOPO TA Cloning Kit (Invitrogen, San Diego, California, United States). The PUF3 ORF was sequenced and subcloned into pACTII via NcoI and EcoRI restriction sites, resulting in plasmid pACTII-Puf3. A full-length Puf5p construct pGAD- MPT5 was a gift from Dr. Kenji Irie ( Tadauchi et al. 2001 ). Sequences encoding the Pum-HD domains of Puf3p (amino acids 535–879), Puf4p (amino acids 557–888), and Puf5p (amino acids 202–578) were PCR-amplified from genomic DNA with oligo pairs Puf3-F6nco/Puf3-R1, Puf4-F2nco/Puf4-R1eco, and Puf5-F2nco/Puf5-R1xho, respectively. Products were ligated into pCR2.1-TOPO, sequenced, and further cloned into pACTII via restriction sites present in the oligonucleotides used for amplification. The RNA consensus sequences interacting with Puf proteins plus ten nucleotides of flanking sequences were cloned into the SmaI and SphI sites of the vector pIIIA/MS2-2 ( Bernstein et al. 2002 ) using annealed synthetic oligonucleotides. The PUF3 RNA consensus sequence spanning nucleotides 24–33 in the 3′-UTR of YBL038w/ MRPL16 was constructed with oligonucleotides M16-1 and M16-2. In M16mut the conserved UGU motif was changed to ACA. The PUF4 consensus (nucleotides 24–34 in the 3′-UTR of YOR145c) was constructed with oligonucleotides Yor-1 and Yor-2. The PUF5 consensus (nucleotides 105–114 in the 3′-UTR of YNL278w/ CAF120 ) was constructed with oligonucleotides Caf-1 and Caf-2. Isolating RNAs specifically associated with selected RBPs For a detailed protocol, see the Supporting Information on our Web site. In brief, 1 l of cells were cultured in YPAD medium (yeast–peptone–dextrose [YPD] supplemented with 20 mg/ml adenine–sulfate) at 30°C and collected during exponential growth by centrifugation. Cells were washed twice with ice-cold buffer A (20 mM Tris–HCl [pH 8.0], 140 mM KCl, 1.8 mM MgCl 2 , 0.1% Nonidet P-40 [NP-40], 0.02 mg/ml heparin) and resuspended in 5 ml of buffer B (buffer A plus 0.5 mM dithiothreitol [DTT], 1 mM phenylmethylsulfonylfluoride, 0.5 μg/ml leupeptin, 0.8 μg/ml pepstatin, 20 U/ml DNase I, 100 U/ml RNasin [Promega, Madison, Wisconsin, United States], and 0.2 mg/ml heparin). Cells were broken mechanically with glass beads, and extracts were incubated with 400-μl slurry (50% [v/v]) IgG–agarose beads (Sigma, St. Louis, Missouri, United States) for 2 h at 4°C. The beads were washed four times for 15 min at 4°C with buffer C (20 mM Tris–HCl [pH 8.0], 140 mM KCl, 1.8 mM MgCl 2 , 0.5 mM DTT, 0.01% NP-40, 10 U/ml RNasin). Puf proteins were released from the beads by incubation with 80 U of TEV protease (Invitrogen) for 2 h at 15°C. RNA was isolated from the TEV eluates, which corresponds to the purified fraction and from extracts (input) by extraction with phenol/chloroform and isopropanol precipitation. Microarray analysis and data selection Equal amounts of a pool of five synthetically prepared Bacillus subtilis RNAs were added to each RNA sample prior to labeling and served as a control for the labeling procedure ( Wang et al. 2002b ). Total RNA (3 μg) derived from the extract and 300 ng of affinity-isolated RNA (or up to 40% of isolated RNA) were labeled with Cy3 and Cy5 fluorescent dyes, respectively, following cDNA synthesis with amino-allyl dUTP in addition to the four natural dNTPs using a 1:1 mixture of oligo(dT) and random nonamer primers. The Cy3- and Cy5-labeled cDNA samples were mixed and competitively hybridized to DNA microarrays representing all S. cerevisiae ORFs, introns, and the mitochondrial genome (see http://brownlab.stanford.edu/protocols.html ). Microarrays were scanned with an Axon Instruments (Foster City, California, United States) Scanner 4000. Scanning parameters were adjusted to give similar fluorescent intensities for B. subtilis spots in both channels. Data were collected with the GENEPIX 3.0 Program (Axon Instruments), and spots with abnormal morphology were excluded from further analysis. Arrays were computer normalized by the Stanford Microarray Database (SMD) ( Gollub et al. 2003 ). Log 2 median ratios were retrieved from SMD and exported into Microsoft (Redmond, Washington, United States) Excel after filtering for regression correlation of greater than 0.6 (filters for large variations in the ratios of pixels within each spot), CH1I/CH1B of greater than 1.8 (signal over background in the channel measuring total RNA from extract), and CH2I/CH2B of greater than 1.0 (affinity-isolated RNA signal greater than background) and for data from at least two independent measurements. Average log 2 ratios were calculated for each gene across the four independent experiments performed for each Puf protein (microarrays and raw data can be downloaded from our supporting Web sites [ http://microarray-pubs.stanford.edu/yeast_puf/ and http://genome-www5.stanford.MicroArray/SMD/ ]). Genes for which the enrichment ratios were at least two standard deviations above the median across all genes were selected. A total of 923 genes were selected in this way. To eliminate nonspecifically enriched RNAs from this gene list, the results from the affinity enrichments for each of the Puf proteins and the data obtained from four independent mock affinity enrichments were clustered by the Pearson correlation algorithm ( Eisen et al. 1998 ). Transcripts of 84 genes were enriched beyond the two standard deviation threshold in all the Puf affinity isolations as well as in the mock procedure. These were presumed to represent RNAs whose enrichment was unrelated to specific interactions with Puf proteins and therefore were excluded from further analysis. Among the finally selected target mRNAs (see Tables S3–S7 ), most were represented in the four independent measurements: PUF1 , 98%; PUF2 , 97%; PUF3 , 82%; PUF4 , 93%; PUF5 , 97%. Gene expression profiling puf3 mutant and wild-type cells were cultured in minimal media supplemented with 3% glycerol and harvested during exponential growth (OD 600 = 0.5). Total RNA (8 μg) isolated from wild-type and mutant cells were used to prepare Cy3 and Cy5 fluorescently labeled cDNA as described above, except that only an oligo(dT) primer was used. The two differentially labeled cDNAs were mixed together and hybridized to yeast DNA microarrays. Arrays were scanned and the data were collected, entered into SMD, and computer normalized ( Gollub et al. 2003 ). Log 2 median ratios were retrieved from SMD after filtering for regression correlation of greater than 0.6 and signal over background of greater than 1.5. Results from three independent experiments were averaged for this analysis (raw data can be retrieved from our Web site). Motif searches As the exact 5′- and 3′-UTR lengths are unknown for most of the Puf target mRNAs, we used the estimated average lengths from yeast ( Mignone et al. 2002 ). Hence, the coding 237 nucleotides of predicted 3′-UTR and 134 nucleotides of predicted 5′-UTR sequences were retrieved from SGD for the Puf target genes. The sequences were searched for motifs in the sense strand with the program MEME under the proposed default settings ( http://meme.sdsc.edu/meme/website/intro.html ) ( Bailey and Elkan 1994 ) (see Tables S9–S11 ). The number and location of consensus motifs in the S. cerevisiae genome was obtained by searching “Pattern Match” in the SGD ( Issel-Tarver et al. 2002 ). Thereby, nucleotides that were at least 19% conserved among the MEME selected sequences were used to compile the Consensus Motif that was searched for. Three-hybrid assays Three-hybrid assays were performed as described elsewhere ( Bernstein et al. 2002 ). Immunofluorescence Immunofluorescence was performed as described at http://www.med.unc.edu/%7Ehdohlman/IF.html . Fixed and permeabilized cells were treated with 5 μg/ml purified rabbit immunoglobulin (Sigma) for 1 h at room temperature. After washing, cells were incubated with Cy3 goat anti-rabbit antibodies (1:400). Images were obtained on a Zeiss (Oberkochen, Germany) Axioplan-2 microscope using an Axiocam HRC camera. Supporting Information Full microarray results and other supporting information can be viewed at http://microarray-pubs.stanford.edu/yeast_puf/ and at http://genome-www5.stanford.MicroArray/SMD/ . Figure S1 Distribution of Average Cy5/Cy3 Fluorescence Ratios from Quadruplicate Microarray Hybridizations Analyzing mRNA Targets for Puf1p, Puf2p, Puf4p, and Puf5p See Figure 3 A for Puf3p. (167 KB EPS). Click here for additional data file. Figure S2 Examples of Groups of mRNAs Associated with the Same Puf Protein and Encoding Related Proteins (A) Puf2p-bound mRNAs encode diverse proteins involved in regulation of ATP-dependent proton transport. PMA1 and PMA2 encode plasma membrane proteins that comprise the major ATP-dependent proton transporters and regulate cellular pH levels. Pmp1p, Pmp2p, and Pmp3p are small isoproteolipids, which are present in a physical complex with Pma1p and act as regulators of its activity upon stress conditions ( Navarre et al. 1994 ). Hrk1p is a protein histidine kinase, which activates Pma1p in response to glucose ( Goossens et al. 2000 ). Ast1p is implicated in proper delivery of Pma1p to plasma membranes ( Bagnat et al. 2001 ). (B) Puf4p-bound mRNAs encode the nucleolar GAR proteins (blue), members of the H/ACA core complex (boxed), and Hmt1p, a dimethylase acting on GAR proteins. Nop1p performs 2′- O -ribose methylation of pre-rRNA, a process guided by small nucleolar RNAs (snoRNAs) of the box C/D family. Cbf5p catalyzes pseudouridine formation with box H/ACA snoRNAs, and three of the four components of the H/ACA core complex were Puf4p-associated (Cbf5, Gar1, and Nhp2 [ Henras et al. 1998 ]; no data were obtained for the fourth component, Nop10, shown in gray). All transcripts encoding nucleolar proteins of the GAR repeats family (Gar1p, Sbp1p, Nop1p, Nsr1p) were Puf4p-bound. The GAR domain is dimethylated at arginine residues. Remarkably, several mRNAs coding for S-adenosylmethionine-dependent methyltransferases were Puf4p-bound including Hmt1p, the major protein arginine-methyltransferase in yeast ( Gary et al. 1996 ). Hmt1p has recently been shown to dimethylate arginines of the proteins Gar1p, Nop1p, and Nsr1p ( Xu et al. 2003 ). (38 KB EPS). Click here for additional data file. Figure S3 Phenotypic Analysis of puf3 Δ Cells Serial dilutions (1:10) of cells were spotted on plates supplemented with the indicated media. Plates were incubated for 3 d at 30°C. Abbreviations: YPD, yeast–peptone–dextrose; YPGE, yeast–peptone–3% glycerol–2% ethanol; SC, synthetic complete. (264 KB PDF). Click here for additional data file. Table S1 Number of mRNA Targets Shared between Puf Proteins (15 KB XLS). Click here for additional data file. Table S2 Protein Copy Number Determination of Puf Proteins Cells were grown to mid-log phase in YPAD medium and the number of cells was counted. Whole-cell extracts were prepared as described previously (Hoffman et al. 2002). In brief, cells were resuspended in 1× SDS-PAGE sample buffer, incubated at 100°C for 10 min, and vortexed for 2 min with glass beads. After a short centrifugation, eight dilutions of cell extracts and protein A (Amersham, Little Chalfont, United Kingdom), which served as a reference standard, were spotted on a nitrocellulose filter. Expression of IgG-binding domains was monitored with rabbit peroxidase–anti-peroxidase soluble complex at 1:5,000 (Sigma). Chemiluminescence was measured with a Typhoon 8600 Imager (Molecular Dynamics, Sunnyvale, California, United States) and quantified with the ImageQuant 5.2 software. Averaged numbers from two independent measurements were used for calculations. The total number of mRNA copies in the pool associated with each Puf protein was estimated as follows: copy numbers for individual mRNAs were retrieved from two independent genome-wide measurements ( Holstege et al. 1998 ; Wang et al. 2002b ). For genes with no data, we added the median value for copy numbers of all mRNAs in the respective pool. (30 KB XLS). Click here for additional data file. Table S3 List of Puf1p Target mRNAs Columns indicate the following (from left to right): ORF; gene name; GO annotations; classification of gene products (soluble/membrane-associated); average log 2 ratios of enrichment across four independent Puf affinity isolations; standard deviations; association of mRNA with other Puf proteins; mRNA copy numbers. (28 KB XLS). Click here for additional data file. Table S4 List of Puf2p Target mRNAs Notations are as in Table S3 . (52 KB XLS). Click here for additional data file. Table S5 List of Puf3p Target RNAs Columns indicate the following (from left to right): ORF; gene name; GO annotations; classification of gene products (soluble/membrane-associated); average log 2 ratios of enrichment across four independent Puf affinity isolations; standard deviations; association of mRNA with other Puf proteins; location of consensus motif identified by MEME; mRNA copy numbers. (70 KB XLS). Click here for additional data file. Table S6 List of Puf4p Target mRNAs Notations are as in Table S5 . (61 KB XLS). Click here for additional data file. Table S7 List of Puf5p Target mRNAs Notations are as in Table S5 . (64 KB XLS). Click here for additional data file. Table S8 Significant Shared GO Annotations among Puf mRNA Targets Only annotations with p values of less than 0.001 are indicated. GO annotations were retrieved from the SGD with GO Finder ( http://db.yeastgenome.org/cgi-bin/SGD/GO/goTermFinder ) on May 21, 2003. Respective p values are indicated in a column next to the names of the GO term. (30 KB XLS). Click here for additional data file. Table S9 Results of MEME Motif Searches: Motifs among Puf3p mRNA Targets (63 KB XLS). Click here for additional data file. Table S10 Results of MEME Motif Searches: Motifs among Puf4p mRNA Targets (55 KB XLS). Click here for additional data file. Table S11 Results of MEME Motif Searches: Motifs among Puf5p mRNA Targets (34 KB XLS). Click here for additional data file. Accession Numbers All accession numbers for human, Drosophila , or C. elegans proteins are from the SwissProt database ( http://www.ebi.ac.uk/swissprot/ ): CPEB (Q18317), GLD1 (Q17339), DAZL (Q92904), FBF-1 (Q9N5M6), FEM3 (P34691), IRP (P21399), NANOS (P25724), Drosophila PUMILIO (P25822), human PUMILIO-1 (Q14671), human PUMILIO-2 (Q9HAN2), and SLBP (P97330). The accession numbers for S. cerevisiae genes are from SGD ( http://genome-www.stanford.edu/Saccharomyces/ ) (ORF/SGD identification number): ADA2 (YDR448W/S0002856), AME1 (YBR211C/S0000415), APS3 YJL024C/S0003561), AST1 (YBL069W/S0000165), BBP1 (YPL255W/S0006176), BDF1 (YLR399C/S0004391), BDF2 (YDL070W/S0002228), BOI2 (YER114C/S0000916), BSP1 (YPR171W/S0006375), BUB1 (YGR188C/S0003420), BUD9 (YGR041W/S0003273), CBF5 (YLR175W/S0004165), CDC31 (YOR257W/S0005783), CNM67 (YNL225C/S0005169), COX17 (YLL009C/S0003932), DAD2 (YKR083C/S0001791), DHH1 (YDL160C/S0002319), ELM1 (YKL048C/S0001531), FPS1 (YLL043W/S0003966), GAR1 (YHR089C/S0001131), GIC1 (YHR061C/S0001103), HDA1 (YNL021W/S0004966), HFI1 (YPL254W/S0006175), HMT1 (YBR034C/S0000238), HOS1 (YPR068C/S0006272), HOS3 (YPL116W/S0006037), HST1 (YOL068C/S0005429), HTA1 (YDR225W/S0002633), IFM1 (YOL023W/S0005383), KAR1 (YNL188W/S0005132), KAR9 (YPL269W/S0006190), KHD1 (YBL032W/S0000128), MAS6 (YNR017W/S0005300), MEX67 (YPL169C/S0006090), MUP3 (YHL036W/S0001028), NCE101 (YJL205C/S0003742), NCE102 (YPR149W/S0006353), NHP2 (YDL208W/S0002367), NOP1 (YDL014W/S0002172), NSR1 (YGR159C/S0003391), NUF2 (YOL069W/S0005430), PDR16 (YNL231C/S0005175), PMA1 (YGL008C/S0002976), PUF1 (YJR091C/S0003851), PUF2 (YPR042C/S0006246), PUF3 (YLL013C/S0003936), PUF4 (YGL014W/S0002982), PUF5 (YGL178W/S0003146), RAX2 (YLR084C/S0004074), RSC1 (YGR056W/S0003288), RSC2 (YLR357W/S0004349), RSC4 (YKR008W/S0001716), SBP1 (YHL034C/S0001026), SCP160 (YJL080C/S0003616), SFK1 (YKL051W/S0001534), SFL1 (YOR140W/S0005666), SHE2 (YKL130C/S0001613), SIN3 (YOL004W/S0005364), SNC2 (YOR327C/S0005854), SNT1 (YCR033W/S0000629), SPC19 (YDR201W/S0002609), SPC42 (YKL042W/S0001525), SPT7 (YBR081C/S0000285), SPT8 (YLR055C/S0004045), SSO2 (YMR183C/S0004795), STE7 (YDL159W/S0002318), SUR7 (YML052W/S0004516), TPO1 (YLL028W/S0003951), TPO2 (YGR138C/S0003370), TPO3 (YPR156C/S0006360), VPS72 (YDR485C/S0002893), YIP1 (YGR172C/S0003404), YKL091c (YKL091C/S0001574), YPR157w (YPR157W/S0006361), and YRA1 (YDR381W/S0002789). | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC368173.xml |
340953 | Mutation Rates and Gene Location: Some Like It Hot | xx | The growing library of sequenced genomes is challenging scientists to extract new biological meaning from DNA sequences. Comparative analysis of the mouse and human genome, for example, has already revealed that mutation rates in the 3 billion base pairs of the human genome vary considerably. What accounts for this regional disparity, however, is unclear. Mutations—substitutions in the nucleotide bases of DNA—produce variation in the genome. In classical evolutionary theory, natural selection drives evolutionary change by determining which of these mutations live on in the next generation or die with the organism. Mutations can be neutral, harmful, or beneficial, though the neutral theory of molecular evolution predicts that most mutations are “nearly” neutral or only slightly deleterious, while beneficial mutations—which confer a survival advantage on an organism and, if it reproduces, on its progeny—are quite rare. As a whole, mutations occur at the rate of approximately five substitutions per billion nucleotide sites per year. There are many types of neutral mutations—that is, mutations that have no effect on function. DNA base substitutions that lie outside of gene-coding regions or occur within introns (regions that are excised before being translated into a protein sequence) can fall into this category. Neutral mutations can also occur within gene-coding regions. For example, there are many instances where more than one codon—say, CUU, CUC, CUA, CUG—specify the same amino acid—in this case, leucine. Since these mutations can be used to gauge the neutral mutation rate of a region in the genome, they can be used to analyze the relationship between local mutation rates and gene location. Correlating gene mutation rates with their location in the genome, Jeffrey Chuang and Hao Li not only confirm that regional mutation rates indeed exist, but also calculate the size of these regions. Strikingly, certain classes of genes tend to congregate in mutational “hot spots”—regions with high mutation rates—while other types of genes gravitate toward “cold spots”—regions with relatively low mutation rates. Chuang and Li first determined whether mutation rates have regional biases—that is, whether the frequency and distribution of mutations follow a distinct pattern along the genome. The researchers calculated the substitution rates of neutral mutations in nearly 15,000 orthologous mouse and human genes—orthologous genes are genes that have evolved from a common ancestor without diverging in biological function—and found that mutation rates were in fact skewed toward either high or low rates. Mutation rate analysis of the orthologs' neighbors revealed rates similarly skewed toward high or low substitutions, indicating that the region itself, rather than a particular gene, is prone to these differential rates. These regions, Chuang and Li report, were either one megabase or ten megabases long, affecting up to roughly 100 genes. But the question remained: Does the organism take advantage of these mutational hot and cold spots? If there is an adaptive advantage, gene families should occur in an appropriate mutational zone. In mutational hot spots, for example, one would expect to find genes that would benefit from high rates of mutation, which would in turn facilitate flexible responses to constantly changing environmental stimuli. Likewise, one would expect genes in cold regions to need protection from potentially deleterious mutations. And that's just what Chuang and Li found. Overall, genes in hot regions code for proteins involved in cell signaling, such as olfactory receptors, G-protein coupled receptors, membrane proteins, and immune response proteins—being in an area subject to high mutation rates means these genes can evolve quickly enough to adapt to constantly changing stimuli. Cold-region genes code for “housekeeping” proteins involved in core cellular processes, like transcription regulation and protein modification—these genes tend to be highly conserved, changing very little since they first evolved. Thus, it appears that natural selection may also operate at the level of gene location, relegating genes to different mutational genomic niches according to their function. While Chuang and Li explore possible mechanisms to account for these genomic niches—such as gene duplication and gene transposition—they argue that the selective pressures that influence gene location are the same that influence mutations in genes. By calculating the sizes of these mutational hot and cold regions, the researchers lay the groundwork for investigating genetic mechanisms that operate on these scales. And by showing that location matters, they have revealed a new force in genome evolution. Olfactory genes lie in a mutational “hot spot” | /Users/keerthanasridhar/biomedlm/data/PMC000xxxxxx/PMC340953.xml |
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